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BY 4.0 license Open Access Published online by De Gruyter September 16, 2021

Putative neural consequences of captivity for elephants and cetaceans

Bob Jacobs ORCID logo, Heather Rally, Catherine Doyle, Lester O’Brien, Mackenzie Tennison and Lori Marino

Abstract

The present review assesses the potential neural impact of impoverished, captive environments on large-brained mammals, with a focus on elephants and cetaceans. These species share several characteristics, including being large, wide-ranging, long-lived, cognitively sophisticated, highly social, and large-brained mammals. Although the impact of the captive environment on physical and behavioral health has been well-documented, relatively little attention has been paid to the brain itself. Here, we explore the potential neural consequences of living in captive environments, with a focus on three levels: (1) The effects of environmental impoverishment/enrichment on the brain, emphasizing the negative neural consequences of the captive/impoverished environment; (2) the neural consequences of stress on the brain, with an emphasis on corticolimbic structures; and (3) the neural underpinnings of stereotypies, often observed in captive animals, underscoring dysregulation of the basal ganglia and associated circuitry. To this end, we provide a substantive hypothesis about the negative impact of captivity on the brains of large mammals (e.g., cetaceans and elephants) and how these neural consequences are related to documented evidence for compromised physical and psychological well-being.

Introduction

Although some large mammals fare relatively well in captive environments (i.e., zoos and marine parks), those with extensive home ranges do not (Clubb and Mason 2003, 2007; Mason 2010). Large-brained animals with complex cognitive capacities such as elephants and cetaceans seem particularly prone to poor welfare in captive environments insofar as they do not have an adequately stimulating, natural environment. Globally, more than 3000 cetaceans and 17,000 elephants are held in captivity (Jackson et al. 2019; Riddle and Stemme 2011). In the present review, we begin by summarizing the shortcomings of captive environments and the concomitant, often stress-related clinical issues for elephants and cetaceans. Although one can directly observe the physical and behavioral manifestations of welfare in captivity, we cannot do the same for potential neural consequences. Thus, we must infer the effects on the brain from the animal’s behavior, biomedical assays, and from inductive extrapolations of empirical neuroscience research. We propose several neural systems in elephants and cetaceans that are likely negatively affected by the chronic stress of captivity.

Elephants and ∼75% of cetacean species, along with humans and three pinniped species, belong to a small subset of species with brain masses >700 g (Manger et al. 2013). The adult African elephant brain mass is ∼5000 g (Manger et al. 2009; Figure 1). Across the ∼86 species of odontocete and mysticete cetaceans, brain mass ranges from 164 g (Indus River dolphin, Platanista minor) to 8030 g (sperm whale, Physeter macrocephalus) (Manger 2006; Marino 2009). The African elephant (Loxodonta africana) brain contains ∼257 billion neurons, three times as many as the ∼86 billion neurons in the adult human brain, with ∼251 billion (or 97.5%) of these neurons in the cerebellum (compared to ∼69 billion in the human) and only 5.6 billion in the neocortex (compared to 16.3 billion in the human; Herculano-Housel 2009; Herculano-Housel et al. 2014). Whole brain neuron counts in cetaceans are not available, but an unbiased stereological estimate suggests ∼13 billion neurons in the minke whale cerebral cortex (Eriksen and Pakkenberg 2007). Elephant and cetacean brains are not only large in absolute size but in relative size. The elephant brain is slightly larger than expected for its body size (Roth and Dicke 2005) and the brains of many odontocete cetacean species are significantly larger than predicted by their body size (Marino 2009). Size differences aside, all eutherian mammals share the same brain components (Finlay and Darlington 1995), with many parts of elephant and cetacean brains appearing to be highly conserved in terms of neuroanatomy and chemoarchitecture, including the limbic system (Butti et al. 2015; Denver 2009; Jacobs et al. 2011, 2015; Limacher-Burrell et al. 2018; Patzke et al. 2014). Phylogenetic variations in neuroanatomy for these species are primarily related to sensorimotor specializations.

Figure 1: Midsagittal sections of the African elephant (Loxodonta africana), bottlenose dolphin (Tursiops truncatus), human (Homo sapiens), and rat (Rattus norvegicus) brains.Included are tracings of superficial pyramidal neurons from the neocortex of each species. Note that the anterior portion of the frontal lobe has been removed from the dolphin brain. Traced neurons are reproduced from previous studies on quantitative neuromorphology: African elephant (Jacobs et al. 2011), bottlenose dolphin (Butti et al. 2015), human (Jacobs et al. 2018; Warling et al. 2020), and rat (Jacobs et al. 2018). Elephant brain image courtesy of Dr. Paul Manger, University of Witwatersrand, Johannesburg, South Africa. Dolphin brain image courtesy of Drs. Bruno Cozzi and Ksenia Orekhova, University of Padova, Padua, Italy. Abbreviations: Ca, caudate; Cb, cerebellum; CC, corpus callosum; Cereb, cerebral cortex; H, hypothalamus; M, medulla; Mid, midbrain; P, pons; Th, thalamus.

Figure 1:

Midsagittal sections of the African elephant (Loxodonta africana), bottlenose dolphin (Tursiops truncatus), human (Homo sapiens), and rat (Rattus norvegicus) brains.

Included are tracings of superficial pyramidal neurons from the neocortex of each species. Note that the anterior portion of the frontal lobe has been removed from the dolphin brain. Traced neurons are reproduced from previous studies on quantitative neuromorphology: African elephant (Jacobs et al. 2011), bottlenose dolphin (Butti et al. 2015), human (Jacobs et al. 2018; Warling et al. 2020), and rat (Jacobs et al. 2018). Elephant brain image courtesy of Dr. Paul Manger, University of Witwatersrand, Johannesburg, South Africa. Dolphin brain image courtesy of Drs. Bruno Cozzi and Ksenia Orekhova, University of Padova, Padua, Italy. Abbreviations: Ca, caudate; Cb, cerebellum; CC, corpus callosum; Cereb, cerebral cortex; H, hypothalamus; M, medulla; Mid, midbrain; P, pons; Th, thalamus.

For practical and ethical reasons, options for experimentally exploring the neural consequences of a captive/impoverished environment are severely limited for mammals such as elephants and cetaceans. To date, only three African elephant brains have been perfused to allow detailed histological investigations (Manger et al. 2009). In the current review, we therefore extrapolate from experimental findings in other well-studied species (e.g., murid rodents and primates). We also offer comparisons from nonexperimental in vivo findings in humans and other animals who have experienced deprived environments. Our inductive conclusions about the effects of captivity on elephant and cetacean brains are based on the fact that brain structures are highly conserved across vertebrates, especially across mammals (Finlay and Darlington 1995). Moreover, substantial evidence suggests that mammalian brains employ very similar mechanisms for interacting with their environment (Lupien et al. 2009).

The clinical profiles of captive elephants and cetaceans manifest in many of the same physical and psychological perturbations as do other mammals in impoverished environments. Such similar welfare outcomes are likely to be based on common neural disruptions, which is why we hypothesize that elephants and cetaceans in artificial environments suffer neural damage. In the present paper, we review the neural consequences of impoverished environments, the effects of short-term and chronic stress on mammalian brains (specifically, cortico-limbic structures), and the neural foundations of stereotypy, with a focus on basal ganglia circuitry. We argue that neural inferences from other mammals to elephant and cetacean brains are strongly supported using the logic of triangulation (Thurmond 2001), which is employed in other animal welfare assessments (Clegg and Delfour 2018). Thus, we connect the known effects of impoverished environments on brains from experimental studies in other species as well as the shared clinical profiles in impoverished environments across species to infer the effects of captivity on the brains of elephants and cetaceans.

The captive environment for elephants and cetaceans

In their natural habitat, elephants have expansive home ranges that extend from tens to 10,000 km2 (Bahar et al. 2018; Ngene et al. 2017), in which they typically travel ∼8–12 km/day, with much greater distances common (up to ∼50 km/day; Miller et al. 2016; Wall et al. 2013). Elephants engage in a variety of activities, such as socializing, caring for offspring, and foraging on a wide selection of food species (e.g., grasses, trees, bark, roots, and fruits; Dierenfeld 2006). In captivity, however, the actual size of most enclosures is in the range of only 0.017–6.937 km2 per animal (Taylor and Poole 1998). Small enclosure size prevents elephants from moving long distances and freely interacting with a large network of conspecifics; natural foraging is replaced with a limited zoo diet. Exercise is extremely constrained, even though elephants are physically and cognitively adapted for long-distance movement over diverse substrate while actively interacting with an ever-changing, challenging environment (Poole and Granli 2009). The static environments found in captive situations preclude natural behaviors. This is especially true if the animals are restrained with chains or ropes, which is common for circus and temple elephants, and is sometimes employed in zoos for management reasons (Bradshaw 2007; Lenhardt 2006). Moreover, free-living elephants live in matriarchal, multigenerational family groups of two to 10 adult females and their immature offspring (de Silva et al. 2011; Vance et al. 2009). Zoos, on the other hand, do not provide biologically appropriate social groups (Poole and Granli 2009) insofar as conspecific interactions are largely limited to small groups of mostly unrelated adult females and very few infants or juveniles (Clubb and Mason 2002), with some elephants even held in solitary confinement for decades (Lindsay 2017). Finally, most captive elephants are forced to interact directly in some capacity with humans, whether it is for entertainment, tourism, or religious purposes, potentially creating further stress.

Similar issues obtain for captive cetaceans who, despite routinely swimming tens of kilometers a day in the ocean (Matthews et al. 2011), are typically held in concrete tanks that are too small and too shallow to allow for any natural ranging or diving behaviors (McPhee and Carlstead 2010). Even in the largest facilities, cetaceans are kept in tanks that are ∼10,000 times smaller than their natural home range (https://www.cascadiaresearch.org/projects/killer-whales/using-dtags-study-acoustics-and-behavior-southern). Such tanks are characterized by reflective, barren, smooth surfaces as opposed to naturalistic textures and substrates (Rose and Parsons 2019), creating an environment with constant, unnaturally high levels of ultraviolet radiation. As with elephants, cetaceans naturally have long juvenile periods and depend heavily on cultural learning as well as life-long support from a complex social network (O’Corry-Crowe et al. 2020). In contrast, captive cetaceans have little choice in terms of social associations and partners. Most captive groupings are artificial and unstable because animals are moved among facilities for breeding purposes (Clegg and Butterworth 2017). As with elephants, natural feeding behavior is absent in captive cetaceans, who are fed a narrow selection of dead fish/invertebrates, which are delivered in an unnatural manner (i.e., above water, thrown directly into their mouths) that requires none of the cognitive or behavioral engagement necessary in the wild. Finally, as with elephants, many captive cetaceans are trained to perform artificial behaviors and are routinely forced to interact with humans (e.g., swim with the dolphin programs; Frohoff 2018).

The clinical profiles of captive elephants and cetaceans

Because elephants have complex physical and social needs that are difficult to meet even in professionally accredited zoological institutions (Kagan et al. 2018), they suffer from high rates of behavioral and physical pathology (Lahdenperä et al. 2018). In terms of behavior, a prevalent abnormality is stereotypic behavior (Mason and Rushen 2008), which consists of aberrant, repetitive movements (e.g., limb swaying, and rocking) induced by the frustration of natural impulses (Clegg et al. 2017). It is estimated that 47–85% of elephants in zoos and 100% of those in circuses exhibit stereotypies (Greco et al. 2016; Mason and Veasey 2010; Schmid 1995). Captive elephants also exhibit hyperaggression (Harvey et al. 2018), in part because there is no opportunity for physical distancing during heighted intragroup stress (Archie et al. 2006). Medically, captive elephants suffer from both gastrointestinal diseases (e.g., impaction and colic; Greene et al. 2019) and nutritional/metabolic disorders because of their captive diet and lack of exercise (Khadpekar et al. 2020), with obesity being a serious issue (Brown et al. 2020). Across North American zoos, 74% of elephants were found to be overweight with 34% believed to be clinically obese (Morfeld et al. 2016). Skin issues (e.g., inflammation, lesions, and pressure sores) are common (Brown et al. 2020; Fowler 2006a) as are foot-related disorders (e.g., hyperkeratosis, cracked nails, and abscesses; Fowler 2001). Osteoarthritis in the feet, exacerbated by locomotor stereotypies and obesity, occurs prematurely in captive elephants and can lead to euthanasia (Issa and Griffin 2012). Finally, captive elephants are particularly susceptible to several infectious diseases (e.g., Mycobacterium tuberculosis, TB, the endotheliotropic herpesvirus, EEHV), which are highly contagious (Fuery et al. 2018; Mikota and Maslow 2011). TB is deadly in elephants and treatment is often unsuccessful (Lyashchenko et al. 2006). EEHV is prevalent in captive environments, particularly in young, chronically stressed, immunocompromised Asian elephants (Elephas maximus; Schaftenaar et al. 2010), and is now the leading cause of death for captive elephant calves (Perrin et al. 2021). These factors appear to be associated with reproductive issues (Clubb and Mason 2002; Perrin et al. 2021) and a reduced lifespan for both Asian and African elephants in captivity (Clubb et al. 2008, 2009).

Captive cetaceans also exhibit a variety of stereotypies (e.g., repetitive swimming patterns; regurgitation/reingestion of food), with the most common being oral stereotypies that result in severely worn teeth from grating them on hard surfaces (Jett et al. 2017; Ugaz et al. 2013). Some cetaceans also exhibit symptoms characteristic of depression (e.g., logging on the surface, lying motionless on the bottom of the tank, and loss of appetite; Jett and Ventre 2012). As with elephants, hyperaggression is more common in captive cetaceans than in their free counterparts due to their severely confined living space (Lott and Williamson 2017; Marino 2020). In terms of medical issues, there are several parallels with elephants. Nutrition/metabolism disorders (e.g., insulin resistance, fatty liver disease, hemochromatosis, and hypocitraturia; Mazzaro et al. 2012; Venn-Watson et al. 2012, 2013; Zuckerman and Assimos 2009) are often linked to the captive diet (Rosen and Worthy 2018). Additionally, digestive and gastrointestinal disturbances (e.g., gastritis, ulcerations, and torsion) pose significant and sometimes fatal problems for captive cetaceans (Stoskopf 2015). Two common skin disorders in captive cetaceans are tattoo skin disease, which is caused by pox virus and is associated with immunocompromised individuals, and the potentially life-threatening diamond skin disease, caused by Erysipelothrix rhusiopathia (Van Bressem et al. 2018). When facilities fail to maintain levels of chlorine and ozone within strict parameters, elevated concentrations of these chemicals can cause eye damage, respiratory problems, and skin sloughing (Gage 2010). The main cause of fatality in captive cetaceans is (viral and bacterial) pneumonia (Jett and Ventre 2012). Moreover, the prevalence of infectious diseases in captive cetaceans is compounded by the routine use of antibiotics and antifungals, including frequent prophylactic administration, leading to an imbalance of microflora and an increased risk of medicinal resistance (Park et al. 2020; Reidarson et al. 2018). Such disruptions have broader health implications insofar as research in both humans and rats strongly suggests bidirectional communication (e.g., neural, hormonal, and immune) between gut microbiota and the brain, with alterations in the gut microbiome associated with chronic stress and depression (Kelly et al. 2016). Finally, as with elephants, reproductive issues (Robeck et al. 2018) and a reduced lifespan in some cetacean species have been documented (Rose and Parsons 2019).

In summary, the clinical profiles of captive elephants and cetaceans indicate that they experience a similar pattern of psychological, behavioral, and physical health issues. Many of these problems appear to be manifestations of the same kinds of neurobiological deficits demonstrated in other mammals in impoverished environments under controlled experimental conditions. Below, we examine the neural consequences of impoverished environments and the associated effects of chronic stress on the brain across several different species. In doing so, we provide support for the inference that captive elephants and cetaceans incur neurobiological damage that is similar to that documented in other animals.

The neural consequences of impoverished environments

The brain’s exquisite responsiveness to its environment is a hallmark of plasticity, for better or worse, and has been demonstrated across all species examined, from insects (e.g., honeybees; Groh and Rössler 2020), to invertebrates (e.g., aplysia; Antonov et al. 2001), to a variety of mammals (Holtmaat and Svoboda 2009). Following Hebb’s (1947) observation that free-roaming rats performed better on cognitive tasks than laboratory-housed rats, researchers at the University of California, Berkeley (Edward Bennett, Marian Diamond, David Krech, and Mark Rosenzweig) created a framework for exploring the neural effects of housing environments in what has come to be known as the environmental enrichment/complexity paradigm. In this basic framework, littermates are placed in one of three conditions: (1) A relatively large, enriched/complex condition together with several conspecifics and multiple objects/toys, which are changed frequently to provide novelty—in short, the enclosure is designed to enhance the animal’s sensory, motor, and social interactions; (2) a standard/control condition, where several animals are housed together without opportunities to interact with stimulatory objects; and (3) an impoverished condition, where animals are alone in smaller cages with no opportunity for social or object interaction. It should be noted that the standard/control condition is, relative to the enriched/complex condition, also a form of impoverishment as these housing conditions constitute a continuum of environmental stimulation. Moreover, active, direct contact with conspecifics and objects in the environment is crucial; merely observing an enriched environment is not enough to promote neural changes (Ferchmin et al. 1975).

Six decades of these studies have underscored the profound functional, anatomical, chemical, and molecular effects the environment has on the central nervous system (CNS) across a wide variety of species (Table 1A). The CNS appears particularly sensitive during early development (Bogart et al. 2013), but environmentally induced changes occur across the lifespan, including in very old animals (Diamond et al. 1985), and transgenerationally (Arai and Feig 2011). Although most research of this nature has emphasized the neural benefits of an enriched environment, the impoverished environment is likewise detrimental. Impoverished rats (Katz and Davies 1984), mice (Henderson 1970), and gerbils (Rosenzweig and Bennett 1969) tend to exhibit lower overall brain weight than enriched cohorts. As brain weight decreases with impoverishment, so does cortical volume (Altman and Das 1964) and section weight (Globus et al. 1973), even though impoverished rats tend to have greater body weight than enriched rats (Walsh 1981), a finding that parallels the obesity problem identified in many captive animals (Clubb et al. 2008).

Table 1:

Environment-brain interactions across species.

A. Epigenetic changes in response to environmental enrichment/impoverishment
SpeciesMajor findingSource
Atlantic cod fish (Gadus morhua)Enriched rearing promoted social learning.Strand et al. (2010)
Beagle dog (Canis lupus familiaris)Increased brain derived neurotrophic factor (BDNF) and cognitive improvement in response to environmental enrichment and antioxidant dietFahnestock et al. (2012)
Cat (Felis catus)Complexity of sensory environment altered morphology of synapses, resulting in enhanced responsiveness of neurons in visual cortex to stimuli.Beaulieu and Cynader (1990)
Crayfish (Procambarus clarkii, Procambarus acutus)Environmental enrichment enhanced rate of neurogenesis.Ayub et al. (2011)
Human (Homo sapiens)Increased dendritic complexity was associated with higher formal education levels in Wernicke’s area.Jacobs et al. (1993)
Human (Homo sapiens)Training induced transient structural changes in the midtemporal region and the posterior intraparietal sulcus.Draganski et al. (2004)
Marmoset monkey (Callithrix jacchus)Complex social housing increased dendritic complexity in hippocampus and prefrontal cortex.Kozorovitskiy et al. (2005)
Octopus (Octopus vulgaris)Enriched environment promoted neurogenesis in brain areas involved in learning, memory, and sensory integration.Bertapelle et al. (2017)
Pigeon (Columba livia)Neurogenesis in prosencephalon was observed in response to enriched housing.Melleu et al. (2016)
B. Stereotypies observed across species
SpeciesMajor finding (Type of stereotypy)Source
African (Loxodonta africana), Asian elephant (Elephas maximus)Locomotor (e.g., swinging limb or trunk), whole-body (e.g., pacing), oral (e.g., bar biting), and self-directed (e.g., trunk sucking)Greco et al. (2017)
Parrot (Amazona amazonica)Locomotor (e.g., pacing, perch circles) and oral (e.g., wire chewing)Meehan et al. (2004)
American black bear (Ursus americanus)PacingCarlstead and Seidensticker (1991)
Orca (Orcinus orca)Oral (e.g., biting and chewing hard tank surfaces)Jett et al. (2017)
Pacific walrus (Odobenus rosmarus divergens)Tusk rubbing on concrete structuresDittrich (1987)
Rhesus monkeys (Macaca mulatta)Pacing, stereotypy-related self injurious behaviorLutz et al. (2003)
Horse (Equus caballus)Crib-biting, weaving, and box-walkingMcBride and Hemmings (2009)
Giraffe (Giraffa camelopardalis tippelskirchi)Oral (e.g., tongue-playing, object licking, and vacuum chewing)Baxter and Plowman (2001)
C. Enrichment-induced reductions in stereotypies
SpeciesMajor findingSource
African lion (Panthera leo), Sumatran tiger (Panthera tigris sumatrae)Feeding enrichment reduced stereotypic behavior and increased nonstereotypic activity.Bashaw et al. (2003)
Australian sea lions (Neophoca cinerea)Enrichment objects reduced pattern swimming.Smith and Litchfield (2010)
Chimpanzee (Pan troglodytes)Enrichment devices (e.g., manipulable toys) reduced repetitive stereotypies.Brent et al. (1989)
Common seal (Phoca Vitulina)Enrichment devices focused on feeding/foraging significantly reduced stereotypical circling behavior.Grindrod and Cleaver (2001)
Cynomolgus monkey (Macaca fascicularis)Enriched playpen environment reduced stereotypy and autoaggression.Bryant et al. (1988)
Giant panda (Ailuropoda melanoleuca)Behavioral enrichment items significantly reduced rate and time engaged in stereotypic behaviors.Swaisgood et al. (2001)
Giraffe (Giraffa camelopardalis tippelskirchi)Feeding enrichment reduced oral stereotypies.Fernandez et al. (2008)
Horse (Equus caballus)Enriched foraging device reduced several types of stereotypic behavior (e.g., weaving).Henderson and Waran (2001)
Parrot (Amazona amazonica)Enriched cages significantly reduced locomotor and oral stereotypies.Meehan et al. (2004)
Sea turtles (Caretta caretta, Chelonia mydas)Enrichment devices decreased stereotypic resting and pattern swimming.Therrien et al. (2007)
Sloth (Melursus ursinus), American black (Ursus americanus), brown bear (Ursus arctos)Enriched feeding methods reduced stereotypic pacing.Carlstead et al. (1991)

Neocortical consequences of impoverishment

Consistent across environmental complexity studies is a significant decrease in cortical thickness with impoverishment (Diamond et al. 1967), especially in occipital cortex (Katz and Davies 1984; Møllgaard et al. 1971; Figure 2), reflecting several changes in underlying cortical neuropil. Within the cortex, capillary volume, and hence cortical blood supply, tends to be lower in impoverished rats than enriched rats (Diamond et al. 1964; Figure 2). Also, the impoverished rat brain possesses fewer glial cells, especially oligodendrocytes, than does the enriched rat brain (Altman and Das 1964; Katz and Davies 1984), which implies that cortical neurons in impoverished brains receive less metabolic and structural support than neurons in enriched brains. Both nuclear and perikaryon diameters in supragranular neurons are smaller in impoverished rats (Diamond et al. 1967). Impoverished animals exhibit dendritic systems for both pyramidal and stellate neurons that are less complex in terms of number and length, especially for more distal branches (Volkmar and Greenough 1972; Figure 2) in occipital (Sirevaag and Greenough 1985), parietal (Leggio et al. 2005), and temporal (Greenough et al. 1973) cortices for rats, and in motor cortex for deer mice (Turner et al. 2003). Marmoset monkeys (Callithrix jacchus) housed in standard cages for one month, compared to cohorts in complex environments, exhibited less basilar dendritic complexity in pyramidal neurons of the prefrontal cortex (Kozorovitskiy et al. 2005), which is involved in executive functions (e.g., cognitive flexibility and planning).

Figure 2: Different levels of the cerebral cortex affected by impoverished (captive) and enriched (natural) environments.In impoverished/captive environments, there are several cortical changes: (a) Decreases in cortical thickness, (b) smaller capillary diameter, (c) decreases in neuronal soma size and fewer glial cells per neuron, (d) less complex dendritic branching, (e) fewer dendritic spines, and (f) less efficient synapses. Image courtesy of Dr. Arnold B. Scheibel.

Figure 2:

Different levels of the cerebral cortex affected by impoverished (captive) and enriched (natural) environments.

In impoverished/captive environments, there are several cortical changes: (a) Decreases in cortical thickness, (b) smaller capillary diameter, (c) decreases in neuronal soma size and fewer glial cells per neuron, (d) less complex dendritic branching, (e) fewer dendritic spines, and (f) less efficient synapses. Image courtesy of Dr. Arnold B. Scheibel.

Several other neocortical deficits related to impoverishment have also been documented. Pyramidal neurons in both occipital (Globus et al. 1973) and parietal (Leggio et al. 2005) cortex exhibit reduced spine density in impoverished rats (Figure 2). Lower spine density along the basilar dendrites of pyramidal neurons has also been observed in the prefrontal cortex of marmoset monkeys (Kozorovitskiy et al. 2005). At the synaptic level, impoverished rats have been shown to have fewer synapses per cortical neuron than their enriched counterparts, suggesting less overall synaptic activity (Sirevaag and Greenough 1985). Moreover, impoverished rats tend to have smaller synapses than enriched cohorts (Møllgaard et al. 1971), with significantly shorter postsynaptic opaque regions in asymmetrical synapses (Sirevaag and Greenough 1985; Figure 2). Similar findings have been documented in cat visual cortex, where the number of round-asymmetrical synapses per neuron is lower and the number of flat-symmetrical contacts is higher in impoverished compared to enriched animals, functionally suggesting that impoverished cortex may be less responsive to visual stimuli because there are more inhibitory synapses per neuron (Beaulieu and Cynader 1990).

Although experiments of this nature are not possible in humans, there are documented effects of a stimulating environment on the human brain as well. For example, as with the environmental complexity studies (Kleim et al. 1998), specific training (e.g., formal music practice) causes structural changes (e.g., volumetric increases in somatosensory and motor cortices) in the human brain (Gaser and Schlaug 2003). At the morphological level, Scheibel et al. (1990) found a positive relationship between the basilar dendritic extent in cortical pyramidal neurons and the complexity of the computational task performed by that area, a finding confirmed in subsequent studies (monkey: Elston and Rosa 1997; human: Jacobs et al. 2001). In addition, they found preliminary evidence of a positive association between dendritic complexity in the hand-finger region of primary somatosensory cortex and the nature of an individual’s occupation, a relationship recently supported by neuroimaging (Lenhart et al. 2021). A subsequent study in Wernicke’s area found a positive correlation between education level (seen as a form of enrichment) and dendritic extent, with university educated individuals having more complex basilar dendritic systems than those who did not complete high school (Jacobs et al. 1993). Recently, more complex pyramidal dendritic arbors in human temporal and frontal cortices have also been positively associated with intelligence (Goriunova et al. 2018). Although one cannot determine causation in such correlational studies, the nonhuman animal research indicates that the brain of an enriched animal exhibits detrimental changes (e.g., decreases in dendritic length) when the animal is put in an impoverished environment, and vice-versa, underscoring the epigenetic sensitivity of neural tissue (Diamond 1988).

The neocortex in elephants and cetaceans—potential parallels with other mammals

The experimental evidence indicates that impoverished environments have wide-reaching and damaging effects on the cerebral cortex by contributing to thinner cortical laminae, a decreased blood supply, smaller neuronal cells bodies with fewer glial cells to provide metabolic and structural support, decreased dendritic branching for synthesizing information, fewer dendritic spines (indicating fewer connections with other neurons), and smaller, potentially less efficient synapses (Holler et al. 2021). Although the neocortex of elephants and cetaceans is largely agranular (Hof et al. 2005; Jacobs et al. 2011), it is logical to expect that an impoverished environment would affect their neocortex similarly to the way that it affects that of other mammals. An agranular cortex simply represents a variation of the six-layer cortex characteristic of euarchontoglires (e.g., murid rodents and primates). Generally, cetacean neocortical neurons are morphologically very similar to those observed in other cetartiodactyls (Butti et al. 2014, 2015; Jacobs et al. 2015). Elephant neocortical neurons are similar in in overall dendritic extent to humans but tend to have fewer branches and extend more laterally than in other mammals (Jacobs et al. 2011). As is the case with other mammals, the neocortex of elephants and cetaceans exhibits a variety of complex spiny neurons, with pyramidal neurons being dominant (Butti et al. 2015; Jacobs et al. 2011). In both elephant and cetacean neocortex, aspiny interneurons appear to be highly conserved morphologically and thus similar to those observed in other eutherian mammals (Jacobs et al. 2011, 2015).

Impoverishment across other brain regions

The effects of impoverishment also extend to other brain regions. In the cerebellum, for example, impoverished/inactive rats fail to show the same increases in synaptic number along parallel fibers as do their enriched/active cohorts (Kleim et al. 1998). Similarly, in monkeys (Macaca fasciularis), impoverished animals do not exhibit the same dendritic growth that characterizes the Purkinje neurons of their enriched counterparts (Floeter and Greenough 1979). Although the cerebellum in most cetaceans and in elephants is much larger in both relative and absolute size compared to other eutherians (Marino et al. 2000; Maseko et al. 2012), the neuronal morphology of the elephant and cetacean cerebellum is very consistent with what has been observed in other mammals (Jacobs et al. 2014), and likely responds to impoverishment in a similar manner. The disproportionate size of the cerebellum in elephants and cetaceans, particularly in the lateral hemispheres (Smaers et al. 2018), appears to be related to its sensory acquisition and processing role and the importance of infrasound in elephants and echolocation in cetaceans for exploring the environment (Hanson et al. 2013; Jacobs et al. 2014). It remains unclear to what extent the cerebellum also contributes to cognitive and emotional functions in elephants and cetaceans, although such functions have been demonstrated in other species (primates: Habas 2021; rats: Shipman and Green 2020).

Finally, two limbic structures are also negatively affected by impoverished environments. The hippocampal-dentate complex (or hippocampus), which is particularly sensitive to environmental influences, exhibits a lower volume in impoverished animals compared to enriched animals largely because of decreased neurogenesis (mice: Kemperman et al. 1977; pigeons: Melleu et al. 2016; rats: Veena et al. 2009). In the amygdala, impoverished rats show greater c-Fos (a gene involved in cell proliferation/differentiation following extracellular stimulation) expression in the medial nucleus following aversive training than enriched animals, suggesting they experience greater levels of stress (Nikolaev et al. 2002). Comparatively, the elephant possesses a typical mammalian hippocampus in terms of both size and architecture (Patzke et al. 2014). Although the hippocampus in cetaceans is smaller than one would expect (Oelschläger and Oelschläger 2009; Patzke et al. 2015), perhaps because of a greatly reduced olfactory system (Kishida et al. 2015), it exhibits typical mammalian subregions (e.g., dentate gyrus, hippocampus proper, and subiculum; Oelschläger et al. 2008). Moreover, despite the reduced hippocampal formation, the paralimbic region in cetacean brains is enormously elaborated (primarily by the well-developed entorhinal cortex and cortical limbic lobe) suggesting there may have been transfer and elaboration of non olfactory hippocampal functions (i.e., long-term memory and learning) to the paralimbic cortex (Marino 2015). Although this hypothesis has yet to be tested, it comports with the behavioral evidence for sophisticated cognitive functions in dolphins and many other cetaceans (Deecke 2018; Marino et al. 2008).

In terms of the amygdaloid complex, the African elephant has a well-developed amygdala similar to that observed in other mammals, although there are some specializations (e.g., enlarged anterior cortical nucleus) thought to be related to the animal’s heavy reliance on olfaction (Ngwenya et al. 2011) and its affect-laden and social-empathic behaviors (Limacher-Burrell et al. 2018). The cetacean amygdaloid complex resembles that of other mammals (Oelschläger et al. 2010) but is smaller in relative size (Patzke et al. 2015). Moreover, the cetacean limbic lobe, which includes cingulate, insular, and parahippocampal cortices, is extensive with deep folds (Oelschläger and Oelschläger 2009; Oelschläger et al. 2010). It remains unclear how the relatively smaller hippocampus and amygdala affect susceptibility or resiliency of cetaceans to environmental perturbations. Nevertheless, these relative size differences do not necessarily negate the argument that their psychological functions (and those of other well-developed adjacent brain areas) are impacted by impoverished environments, as the clinical profiles would suggest.

Impoverishment at the molecular level

At the molecular level, epigenetic-related deficiencies in impoverished brains are ubiquitous (Table 2). In this regard, the chemoarchitecture of elephant and cetacean brains underscores considerable similarities across mammals. For example, the primary antibodies used in African elephant research (Maseko et al. 2013; Ngwenya et al. 2011; Patzke et al. 2014) were developed in the rabbit and work in several species (e.g., bats, drosophila, felines, ferrets, humans, mice, mollusks, pigs, rats, and squid), suggesting synapomorphic cytochemistry across a wide array of taxa. For example, quantitative distribution of gamma aminobutyric acid (GABA)-immunoreactive neurons in the Black Sea porpoise (Phocoena phocoena) visual cortex is similar to that observed in euarchontoglires (Garey et al. 1989). In primary visual cortex, the general typology of GABA-ergic neurons immunoreactive to calretinin (CR) is similar for bottlenose dolphins (Tursiops truncatus) and humans (Glezer et al. 1992). As with neuroanatomy, differences in distribution, density, and typology in neurochemical systems typically reflect specialized sensorimotor and ecological adaptations (Glezer et al. 1998; Manger et al. 2021), but they do not diminish the fundamental similarities across all mammalian brains. Finally, many studies have examined the impact of differential environments on neurotrophins, nerve growth factors (NGF), and brain derived neurotrophic factor (BDNF), all positively associated with neurogenesis, neuroplasticity, emotional resilience, and improved cognitive performance (Table 2). Underlying these findings is the fundamental, lifelong effect that the environment, including training or even a single exposure to enrichment (Ali et al. 2009), has on the expression of a large number of genes linked to neuronal structure, synaptic plasticity, and neural transmission (Rampon et al. 2000) and, by extension, an animal’s emotional and cognitive functioning (Neidl et al. 2016).

Table 2:

Effects of impoverished environment at the molecular level.

Major FindingSource
AcetylcholineTotal acetylcholinesterase activity levels decreased in impoverished animals compared to enriched littermates.Rats: Rosenzweig and Bennett (1972)

Mice: La Torre (1968)
MonoaminesImpoverished rats exhibited higher densities of dopamine D1 receptors in the prefrontal cortex than animals housed in enriched environments, which correlated with higher levels of spontaneous, open field motor activity for the impoverished animal.del Arco et al. (2007)
Environmental enrichment appeared to increase coping behaviors because of a reduction in the release of dopamine (and acetylcholine) in the prefrontal cortex.Segovia et al. (2009)
NoradrenalineLower levels observed in control mice versus enriched cohorts in the parieto–temporal–occipital cortex, as well as in the cerebellum and lower brainstem.Naka et al. (2002)
SerotoninImpoverished rats exhibited significantly lower expression of the gene for serotonin 1A receptors in the dorsal hippocampus, suggesting potentially less neuronal plasticity than in the more environmentally stimulated cohorts.Rasmuson et al. (1998)
Amino acid transmittersReduced levels of metabotropic glutamate receptors observed in the prefrontal cortex of impoverished rats, potentially impairing cognitive functions.Melendez et al. (2004)
During early development in mice, an impoverished environment impeded the maturation of both gamma aminobutyric acid GABA-ergic and glutamatergic synapses in the forebrain and hippocampal regions.He et al. (2010)
Nerve growth factors (NGF) and brain derived neurotrophic factor (BDNF)Impoverished rats exhibited lower NGF and BDNF levels than enriched cohorts in cerebral cortex, hippocampus, basal forebrain, and hindbrain.Pham et al. (2002)
Levels of BDNF mRNA were lower in beagle dogs not receiving behavioral enrichment.Fahnestock et al. (2012)
Cell proliferation was reduced for unstimulated, control octopuses (Octopus vulgaris) in brain areas involved in learning, memory, and sensory integration.Bertapelle et al. (2017)

Impoverishment and lack of exercise in the captive environment

A crucial component to an enriched environment is exercise (Basso and Suzuki 2017), which is severely lacking for captive elephants and cetaceans (Clubb et al. 2008; Morfeld et al. 2016). Exercise not only increases the supply of oxygenated blood to a metabolically expensive brain, but also increases serum neurotrophic factors and BDNF (Heisz et al. 2017; Liang et al. 2021) which, in turn, contribute to potential neurogenesis and enhanced cognitive abilities through a series of complex biochemical cascades (Horowitz et al. 2020). Moreover, exercise generally has a positive influence on the immune system, leading to a reduction in inflammatory biomarkers, and increases in antioxidant defenses (Gomes and Florida-James 2016). Finally, as reviewed by van Praag et al. (2000), exercise appears to enhance the activity of several neurotransmitter systems in rats: (1) cholinergic functioning in the hippocampus, which improves spatial learning (Fordyce and Farrar 1991), (2) opioid activity, which modulates pain (Sforzo et al. 1986), and (3) monoamine functioning (noradrenaline and serotonin), which contributes to learning and synaptic plasticity (Chaouloff 1989). One can logically expect the same exercise-related neural changes in elephants and cetaceans.

Lack of exercise and other shortcomings of the captive environment are apparent to those in the captive industry. However, zoos and aquariums cannot practically make wholesale changes to an animal’s environment as can be done in laboratory settings, where general enrichment and exercise are known to reduce stress and anxiety (mice: Varman et al. 2012; rats: Veena et al. 2009), enhance memory (mice: van Praag et al. 2000), increase cognitive functions and neural plasticity (mice: Arai and Feig 2011; fish, Gadus morhua: Strand et al. 2010), protect against lead toxicity (mice: Schneider et al. 2001), treat developmental disorders (humans: Ball et al. 2019), and ameliorate several psychiatric and neurogenerative disorders in humans (Nithianantharajah and Hannan 2006). Instead, zoos and aquariums engage animals in limited types of directed enrichment (Law and Kitchener 2017; Markowitz 1982) in an attempt to alleviate the specific psychological/behavioral problems arising from an impoverished environment.

Current evidence suggests that targeted, ad hoc zoo/aquarium enrichment remains insufficient for the overall neural health of mammals such as elephants and cetaceans as long as they remain constrained by standard captive conditions. Here it is worth noting a couple of additional points: natural environments appear to be better for the emotional health of rats (as measured by c-Fos activation in the nucleus accumbens) than artificially enriched environments (Lambert et al. 2016), with similar findings in humans (Lambert et al. 2015). Thus, not all types of enrichment are equally effective (Lyn et al. 2020). Moreover, transient, inconsistent enrichment can create more stress and frustration for the animal than no enrichment at all (Latham and Mason 2010). Finally, insofar as the developing brain is particularly susceptible to impoverishment induced alterations (Narducci et al. 2018), the greatest challenge is for those animals born into a captive environment, which applies to most mammals in zoos (Hosey et al. 2020).

Corticolimbic structures and the neural consequences of stress

In response to environmental stressors, all animals attempt to maintain dynamic homeostasis (Schulkin 2011). The exquisitely sensitive stress response system promotes quick activation of the body in the face of acute stress and then a return to homeostasis once the threat has abated (Sapolsky et al. 2000). In captivity, however, stress can become chronic, leading to distress or “toxic stress”, which adversely affects physiological mechanisms (McEwen 2017). Three intricately interconnected systems are involved in the stress response: the nervous system, the endocrine system, and the immune system (Besedovsky and del Rey 1996). At the core of this tripartite schema is the hypothalamic–pituitary–adrenal (HPA) axis which, despite small heterospecific specializations (Atkinson et al. 2015), is highly conserved across mammals (Denver 2009; Nikolova et al. 2018). Here, we provide a simplified overview of the neural consequences when the HPA axis is chronically activated, resulting in an allostatic overload that is generally associated with poorer physical and mental health outcomes (Guidi et al. 2021).

Environmental stresses cause three, cascading linear events: (1) Corticotrophin releasing hormones are released from the paraventricular nucleus of the hypothalamus, (2) adrenocorticotrophic hormone is released from the anterior pituitary into the bloodstream, and (3) the adrenal glands release glucocorticoids such as cortisol (Lupien et al. 2009). In addition to stimulating the sympathetic nervous system to prepare the body for short-term action, glucocorticoids flow through the bloodstream into the brain where, when chronically elevated, they have complex, wide-ranging effects. These include excitotoxity mediated by excitatory amino acids (e.g., glutamate), mitochondrial dysfunction, modulation of extra- and intra-cellular mediators (e.g., BDNF), microglial activation, detrimental epigenetic changes, induction of neuroinflammatory processes, and apoptosis (McEwen et al. 2015; Tynan et al. 2010; Vyas et al. 2016). Three corticolimbic brain structures—the prefrontal cortex, the hippocampus, and the amygdala (Figure 3)—are particularly affected by these stress responses (Chattarji et al. 2015; McEwen et al. 2016; Vyas et al. 2016), in part because they express a high density of corticosteroid (e.g., mineralocorticoid and glucocorticoid) receptors.

Figure 3: Schematic of hypothalamic–pituitary–adrenal (HPA) axis activation.Coronal sections of the African elephant, bottlenose dolphin, human, and rat brains revealing major structures involved in the neural response to stress following hypothalamic–pituitary–adrenal (HPA) axis activation and the release of glucocorticoids (black arrows) from the adrenal cortex. A simplified schematic illustrates the basic structures and connections within this circuitry. Structures in the schematic are color coded to match brain cross sections—note that the medial prefrontal cortex (PFC) and the bed nucleus of the stria terminalis (BNST) are not visible in cross-sections. In addition, the entire hypothalamus is illustrated in the cross-sections rather than just the paraventricular nucleus (PVN). Major excitatory (red arrows) and inhibitory (blue arrows) projections are shown. In general, the amygdala and associated circuitry provide a positive feedback loop to activate the HPA axis whereas the hippocampus and associated circuitry contribute to a negative feedback loop to reduce HPA activity. Although not shown in the schematic, the anterior BNST tends to increase HPA axis activity whereas the posterior division tends to inhibit it (Ch’ng et al. 2018). Also represented are three types of neurons and their response to chronic stress: (1) Stellate neurons in the (basolateral) amygdala, which tend to increase dendritic extent; (2) cortical pyramidal neurons in the medial PFC, which show reductions in apical dendritic extent; and (3) CA3 pyramidal neurons in the hippocampus, which undergo degeneration of the apical dendrite.

Figure 3:

Schematic of hypothalamic–pituitary–adrenal (HPA) axis activation.

Coronal sections of the African elephant, bottlenose dolphin, human, and rat brains revealing major structures involved in the neural response to stress following hypothalamic–pituitary–adrenal (HPA) axis activation and the release of glucocorticoids (black arrows) from the adrenal cortex. A simplified schematic illustrates the basic structures and connections within this circuitry. Structures in the schematic are color coded to match brain cross sections—note that the medial prefrontal cortex (PFC) and the bed nucleus of the stria terminalis (BNST) are not visible in cross-sections. In addition, the entire hypothalamus is illustrated in the cross-sections rather than just the paraventricular nucleus (PVN). Major excitatory (red arrows) and inhibitory (blue arrows) projections are shown. In general, the amygdala and associated circuitry provide a positive feedback loop to activate the HPA axis whereas the hippocampus and associated circuitry contribute to a negative feedback loop to reduce HPA activity. Although not shown in the schematic, the anterior BNST tends to increase HPA axis activity whereas the posterior division tends to inhibit it (Ch’ng et al. 2018). Also represented are three types of neurons and their response to chronic stress: (1) Stellate neurons in the (basolateral) amygdala, which tend to increase dendritic extent; (2) cortical pyramidal neurons in the medial PFC, which show reductions in apical dendritic extent; and (3) CA3 pyramidal neurons in the hippocampus, which undergo degeneration of the apical dendrite.

Stress and the prefrontal cortex

The prefrontal cortex plays a major role in stress-related behaviors and fear extinction by exerting top-down modulatory regulation of both the amygdala and the hippocampus (Chattarji et al. 2015; Radley et al. 2015). In particular, the medial prefrontal cortex is part of a negative feedback system to regulate stress-induced HPA activation and amygdala-mediated arousal (Radley et al. 2015). During chronic stress, this negative feedback system is disrupted, resulting in downregulation of glucocorticoid receptors (Mizoguchi et al. 2003), which then results in decreased corticosteroid receptor density throughout the limbic forebrain (Radley et al. 2015). Such disruptions are associated with the pathogenesis of stress-induced neuropsychiatric disorders (e.g., depression, post traumatic stress disorder, and PTSD; Alt et al. 2010; Lecorps et al. 2021; Radley et al. 2015). Stress-induced gray matter reductions have also been documented (Nikolova et al. 2018) as well as N-methyl-D-aspartate (NMDA)-dependent decreases in apical dendritic complexity and spine density in the medial prefrontal cortex (McEwen 2016, 2017; Radley et al. 2015; Figure 3). In the orbitofrontal cortex, chronic stress has been associated with increased dendritic complexity, as would be expected in captivity due to increased vigilance (McEwen et al. 2015). Finally, prolonged stress also results in structural changes to cortico-striatal circuitry involved in decision making (Dias-Ferreira et al. 2009).

Stress and the hippocampus

The hippocampus is especially sensitive to sustained exposure to glucocorticoids and mineralocorticoids (McEwen 2016, 2017; McEwen et al. 2015). Because mineralocorticoid receptors are more highly expressed in the hippocampus than in the prefrontal cortex (Patel et al. 2000), their activation leads to excess release of glutamate (Olijslagers et al. 2008). In turn, it has been shown in both rodents and primates that stress-elevated levels of extracellular glutamate activate NMDA receptors, which mobilizes free cytosolic calcium to toxic levels, subsequently resulting in hypoxia-ischemia, excitotoxic seizures, soma shrinkage, nuclear pyknosis, and loss of dendritic spines along with apical dendritic atrophy (Figure 3), particularly in CA3 pyramidal neurons (McEwen 2001; McEwen et al. 2016). Similar structural-functional correlates (e.g., reduction of hippocampal volume) have been documented in humans and associated with clinical depression, bipolar disorders, PTSD, and other stress-related illnesses (McEwen 2016; McEwen et al. 2016). Such stress-related damage could be particularly detrimental in cetaceans insofar as their hippocampus appears not to exhibit neurogenesis under normal conditions (Parolisi et al. 2018).

Stress and the amygdala

The amygdala, in conjunction with interconnected structures involved in autonomic, neuroendocrine, and behavioral arousal, is crucially involved in emotional processing of sensory information and regulation of emotional responsiveness, especially as related to fear (LeDoux 1994). Structurally, chronic stress contributes to long-lasting morphological changes in the amygdala in both human and nonhuman animals. Specifically, both stellate and pyramidal neurons in the basolateral amygdala (a putative locus for the storage of fear memories) exhibit increased dendritic complexity and greater spine density in response to chronic stress (Mitra et al. 2005; rats: Vyas et al. 2002; Figure 3). In contrast, neurons in the medial amygdala show stress-induced decreases in dendritic extent and spine density, a change that appears associated with reduced social interaction (mice: McEwen 2017). Volumetric changes in several corticolimbic regions (e.g., the nucleus accumbens, Reynolds and Berridge 2008), including the amygdala, also appear to positively correlate with chronic stress (Nikolova et al. 2018).

Under stressful conditions, when glucocorticoid levels are high, the baseline GABA-ergic inhibitory control exerted by the medial prefrontal cortex over the central nucleus (the major output nucleus) of the amygdala is disrupted, resulting in amygdaloid hyperreactivity to perceived environmental stressors (Skórzewska et al. 2015) with functional and structural consequences (Christoffel et al. 2011). Functionally, there is an increased fear response, prolonged HPA and sympathetic activation, increased aggression and, because of the amygdala’s strong reciprocal connections with the bed nucleus of the stria terminalis (BNST), excessive anxiety (Avery et al. 2016). In humans, such dysfunctions have been associated with a variety of anxiety disorders, including PTSD, generalized anxiety disorder, phobias, panic disorders, and obsessive-compulsive disorders (Koenigs and Grafman 2009; Shin and Liberzon 2010). Amygdala hyperactivity may also increase the risk for developing the stress-related symptoms of depression (Nikolova et al. 2018). Moreover, under inescapably stressful conditions, the amygdala and the BNST, modulated by serotonergic input from the dorsal raphe nucleus, may mediate learned helplessness and conditioned defeat (Maier and Seligman 2016).

Stress for elephants and cetaceans

Because of the complex social world of elephants and many cetaceans, an issue of special relevance to the present review is the effect that social isolation has on corticolimbic structures (Mumtaz et al. 2018). In rats and nonhuman primates, chronic isolation appears to enhance HPA responsiveness to stressors (Serra et al. 2007) and increase basal cortisol levels (Hawkley et al. 2012). Stress from social isolation induces alterations in several neurochemical systems, including (1) decreases in BDNF in the hippocampus (rats: Scaccianoce et al. 2006), which is associated with increased anxiety-like symptoms in rats (Murínová et al. 2017) and several neuropsychiatric disorders in humans (Autry and Monteggia 2012); (2) reduced levels of serotonin in both hippocampus and frontal cortex, which is associated with increased aggression and depression-like symptoms (rats: Miura et al. 2002); and (3) overproduction of nitric oxide, a retrograde messenger, in the hippocampus, which is involved in excitotoxicity (mice: McLeod et al. 2001). Structural changes in response to social isolation have also been observed, including selective loss of prefrontal cortex volume (rats: Schubert et al. 2009). These findings are not limited to rodents and nonhuman primates. For example, decreased dendritic complexity has been documented in pallial brain regions important for the development of social/sexual preferences in socially isolated zebra finches (Taeniopygia guttata, Shukla and Sadananda 2021). Also, ants raised in isolation show impairment in the growth of the mushroom bodies, which are crucial for learning and memory in social insects (Seid and Junge 2016), as well as weakened immune systems (Scharf et al. 2021). Humans subjected to early socioemotional deprivation in Romanian orphanages exhibited several neural deficits, including glucose hypometabolism and white matter abnormalities in limbic and paralimbic structures (including prefrontal cortex, amygdala, and hippocampus; Chugani et al. 2001; Eluvathingal et al. 2006). Such changes may underlie some of the cognitive, behavioral, and socioemotional deficits observed in these children. Human findings of this nature underscore the importance of the early environment for shaping corticolimbic systems and the potential long-term consequences to chronic stress (Frodl and O’Keane 2013). Current human research, in fact, suggests that childhood trauma may subsequently make the adult brain more vulnerable to maladaptive stress responses (Banihashemi et al. 2020), an issue particularly relevant for long-lived, highly social animals such as elephants and cetaceans born into captivity.

Stress and neuroendocrine-immune system interactions

Neuroendocrine-immune interactions are dynamic (Wrona 2006). Acute stress tends to enhance immune functions whereas chronic stress tends to inhibit them (Schedlowski and Schmidt 1996), with negative health and neural consequences (McEwen et al. 2015). Under chronic psychological or physical stress, pro-inflammatory cytokines (e.g., interleukins and tumor necrosis factors) are released by activated immune cells and can interact with multiple corticolimbic brain structures, dysregulating different growth factors (e.g., BDNF) and neurogenesis (especially in the hippocampus), several neurotransmitter systems (e.g., glutamate, serotonin, and dopamine), and neuroendocrine communication (Capuron and Miller 2011). One neural consequence under such conditions is microglia activation and a sustained release of inflammatory mediators (Leszek et al. 2016). For example, chronic stress increases the number of activated microglia in several corticolimbic regions, which can lead to neurodegeneration (mice: Nair and Bonneau 2006; rats: Tynan et al. 2010) as well as neuroinflammation that contributes to physiological, behavioral, affective, and cognitive disorders (de Pablos et al. 2014; McLeod et al. 2001).

Although there has been no direct comparative research on the neural consequences of stress in captive versus free cetaceans or elephants, existing data suggest that the immune system is negatively affected. For example, candidiasis, which is often observed in immunocompromised individuals, is relatively common in captive cetaceans secondary to stress (Ohno et al. 2019). In elephants, clinical outbreaks of salmonellosis tend to follow stress-related depression of the immune system (Fowler 2006b). Direct comparisons between captive animals and their free counterparts have also suggested weakened immune systems for some captive animals (e.g., spotted hyenas: Flies et al. 2015; zebras: Seeber et al. 2020). Biomarkers such as cortisol have also been examined to a limited degree, with acute measures indicating expected elevations in cortisol levels associated with events such as beach strandings in dolphins (Kellar et al. 2015) or transportation/relocation in elephants (Laws et al. 2007) and cetaceans (Noda et al. 2007; Spoon and Romano 2012). Notably, captive bottlenose dolphins kept in sea pen facilities that allow for ocean water flow and entry of small fish had significantly lower salivary cortisol levels than their cohorts in tanks (Ugaz et al. 2013). Similarly, not only do Asian and African elephants in larger enclosures exhibit lower glucocorticoid metabolite concentrations than their cohorts in smaller enclosures, but they also exhibit lower cortisol levels when they can access diverse enrichment options and allowed to be in compatible social groups (Brown et al. 2019). In Asian elephants, cortisol levels negatively correlate with locomotion and positively correlate with stereotypies (Schmid et al. 2001). To the extent that captivity induces stress-related immunosuppression, captive animals would thus be more susceptible not only to neuroinflammation but also to opportunistic infections and possible disruptions of fertility (Edwards et al. 2019).

Stress summary

From the neural perspective, both the PFC and hippocampus attempt to inhibit HPA activity, thus enhancing cognitive functions. However, the amygdala tends to facilitate HPA activity, potentially overriding the inhibitory mechanisms of the PFC and hippocampus, resulting in excessive anxiety and fear reactivity and, when chronically activated, inhibition of the immune system (Chattarji et al. 2015). It has been suggested that these corticolimbic structures are not only evolutionarily conserved in terms of volumetric measures, but also in terms on their functional interconnectivity (Nikolova et al. 2018). As such, we expect that the large, complex brains of animals such as elephants and cetaceans would react to a chronically stressful environment in a similar manner as do the brains of other mammals (including humans) that have been investigated more thoroughly (Marino et al. 2020). Indeed, much of what we know about the neuropsychiatric consequences of chronic stress in humans derives from nonhuman animal models (Chattarji et al. 2015; Lecorps et al. 2021).

Stereotypies and neural dysregulation

Stereotypies are common human and nonhuman responses to chronic stress. In humans, although clinical definitions of stereotypy vary (Edwards et al. 2012), repetitive motor dysfunctions (e.g., hand flapping and head nodding) have been documented in several conditions: Autism spectrum disorder (Langen et al. 2014), primary complex motor stereotypies (Singer 2013), frontotemporal dementia (Mendez et al. 2005), neurodevelopmental disorders (Wilkes and Lewis 2018), Rett syndrome (Temudo et al. 2007), and schizophrenia (Morrens et al. 2006). Children with a history of early institutional care are more likely to exhibit stereotypies, underscoring the influential role of the environment during early development (Bos et al. 2010). In nonhuman animals, such behavioral stereotypies are seldom if ever observed in nature (Boorer 1972), but have been consistently documented in many captive animals beyond murid rodents (Table 1B).

Imaging studies in humans implicate nucleus size, connectivity, and structural variation with restricted repetitive behaviors (Wilkes and Lewis 2018), and have revealed positive correlations between enlargement of the caudate and putamen with the severity of stereotypic behaviors (Langen et al. 2014). However, the fundamental neural synapomorphy across eutherians allows for much more detailed (e.g., pharmacological, surgical, genetic) explorations in animal models (Langen et al. 2011b; Péter et al. 2017). The circuitry involved in motor control and stereotypies is complex. At the neural center of this circuitry is the basal ganglia (or corpus striatum), one of the largest subcortical structures in the cerebrum (Figure 4). Both elephants and cetaceans possess all components of the basal ganglia found in other vertebrates (i.e., caudate, putamen, and globus pallidus) as this is a highly conserved system crucial for integrative functions (Oelschläger et al. 2008). These structures also show the typical mammalian topographic relationships to each other and to adjacent structures (Cozzi et al. 2001; Oelschläger and Oelschläger 2009). In cetaceans, the corpus striatum, involved in motor and reward systems, is prominent in size (Oelschläger et al. 2008) with a histological organization similar to that observed in other mammals (Oelschläger and Oelschläger 2009). Through a series of reciprocal connections with the cerebral cortex, the basal ganglia select and orchestrate appropriate cortical activity for a given situation. To this end, three parallel corticostriatal loops appear to be involved in this process: (1) Sensorimotor (involved with motor output, including stereotypies), (2) associative (involved with cognitive processing and impulsivity/rigidity), and (3) limbic (involved with motivations and obsessions/compulsions; Langen et al. 2011a). A fourth, hyperdirect loop, has also been proposed which, in concert with the subthalamic nucleus, acts to shut down basal ganglia output (McBride and Parker 2015).

Figure 4: Schematic of brain structures involved in behavioral stereotypies.Horizontal sections of African elephant and bottlenose dolphin brains, and coronal sections of human and rat brains revealing major structures involved in behavioral stereotypies. Not all structures are visible in all cross sections except for the human brain. A simplified schematic illustrates basic GABAergic, glutamatergic, and dopaminergic connections within this circuitry. Structures in the schematic are color coded to match brain cross sections. The direct pathway includes the following structures/projections: motor cortical areas → striatum → globus pallidus (interna)/substantia nigra (pars reticulata) → ventral anterior and ventral lateral nuclei of the thalamus → motor cortical areas. The structures of the indirect pathway are similar to those in the direct pathway with the addition of the subthalamic nucleus: motor cortical areas → striatum → globus pallidus (externa) → subthalamic nucleus→ globus pallidus (interna)/substantia nigra (pars reticulata) → ventral anterior and ventral lateral nuclei of the thalamus → motor cortical areas (Calabresi et al. 2014; Langen et al. 2011b; Lewis et al. 2006). Abbreviations: D1 and D2, dopamine receptors; GPe, globus pallidus externa; GPi, globus pallidus interna; SNpc, substantia nigra pars compacta; SNpr, substantia nigra pars reticulata; STN, subthalamic nucleus. Schematic is adapted from Gao and Singer (2013).

Figure 4:

Schematic of brain structures involved in behavioral stereotypies.

Horizontal sections of African elephant and bottlenose dolphin brains, and coronal sections of human and rat brains revealing major structures involved in behavioral stereotypies. Not all structures are visible in all cross sections except for the human brain. A simplified schematic illustrates basic GABAergic, glutamatergic, and dopaminergic connections within this circuitry. Structures in the schematic are color coded to match brain cross sections. The direct pathway includes the following structures/projections: motor cortical areas → striatum → globus pallidus (interna)/substantia nigra (pars reticulata) → ventral anterior and ventral lateral nuclei of the thalamus → motor cortical areas. The structures of the indirect pathway are similar to those in the direct pathway with the addition of the subthalamic nucleus: motor cortical areas → striatum → globus pallidus (externa) → subthalamic nucleus→ globus pallidus (interna)/substantia nigra (pars reticulata) → ventral anterior and ventral lateral nuclei of the thalamus → motor cortical areas (Calabresi et al. 2014; Langen et al. 2011b; Lewis et al. 2006). Abbreviations: D1 and D2, dopamine receptors; GPe, globus pallidus externa; GPi, globus pallidus interna; SNpc, substantia nigra pars compacta; SNpr, substantia nigra pars reticulata; STN, subthalamic nucleus. Schematic is adapted from Gao and Singer (2013).

Direct and indirect motor control pathways

Within the sensorimotor loop, which is most closely linked to stereotypic behavior, there are two parallel pathways, both of which are modulated by dopaminergic input from the substantia nigra pars reticulata. The direct (striatonigral) pathway is a double inhibitory system (McBride and Parker 2015) that ultimately activates motor programs (Figure 4). Functionally, dopamine from the substantia nigra (pars compacta) acts on D1 receptors in the striatum to enhance excitatory input from the cortex. This increases GABAergic inhibition of both the globus pallidus (interna) and substantia nigra (pars reticulata) which, in turn, remove inhibition from the thalamocortical projections to motor cortices, thereby activating motor programs. In contrast, the indirect (striatopallidal) pathway is a triple inhibitory system that normally inhibits motor programs (Figure 4). However, when dopamine from the substantia nigra (pars compacta) acts on D2 (instead of D1) receptors in the striatum, it reduces (rather than enhances) excitatory input from the cortex. This decreases GABAergic inhibition of the globus pallidus (externa) which, in turn, increases the amount of inhibition on the subthalamic nucleus. Increased inhibition of the subthalamic nucleus reduces its ability to excite the globus pallidus (interna) and substantia nigra (pars reticulata). Less activity in these two structures translates into greater disinhibition (i.e., more excitation) of thalamocortical projections, and more subsequent activity of motor programs.

The striatum and associated circuitry are thus tasked with evaluating the processed information received from diverse cortical areas and determining the context appropriate motor output for the given situation (Balleine et al. 2007). Normal movement depends on a delicate balance between the direct and indirect pathways, which are interconnected with other neural systems (e.g., mesolimbic). Several neurotransmitter systems influence these pathways (Gao and Singer 2013; Lewis et al. 2006), with dopamine and serotonin appearing to be the most crucial. Overactivation of striatal D2 receptors, for example, tends to suppress the indirect pathway, allowing stereotypical behaviors to emerge (McBride and Hemmings 2005). Moreover, the dopaminergic system itself appears to be modulated by serotonin, especially when stereotypies are stress induced (Langen et al. 2011b). Chronic stress also creates heightened dopamine sensitivity in the nucleus accumbens, which is part of the mesolimbic pathway associated with motivation (Cabib 2006). Under such conditions, overactivation of the nucleus accumbens may enhance the selection of specific behavioral sequences, contributing to the emergence and maintenance of spontaneous stereotypies (Poirier and Bateson 2017).

Environmental deprivation and social isolation have repeatedly been shown to dysregulate these motor control pathways in several species, resulting in stereotypies (rats: Hall et al. 1998; primates: Martin et al. 1991; horses: McBride and Hemmings 2005; and pigs: Sharman et al. 1982). By extension, environmental enrichment appears to rebalance activity in these pathways, thus at least partially ameliorating or even preventing the emergence of stereotypies (Table 1C). These effects have been documented in both human and nonhuman animals, underscoring common neural mechanisms (Garner et al. 2003). At the neural level, enrichment has multiple effects on these motor control systems. In the subthalamic nucleus and globus pallidus, both part of the indirect pathway, significant enrichment-related increases in neuronal activity and dendritic spine densities appear to attenuate stereotypies (mice: Bechard et al. 2016). Environmental enrichment appears to prevent stereotyped behaviors by increasing metabolic activity (as measured by cytochrome oxidase) in the motor cortex, the striatum, and the nucleus accumbens (mice: Turner et al. 2002). The prevention of stereotypies has also been linked to increased BDNF in the striatum resulting from enrichment (mice: Turner and Lewis 2003).

Stereotypies summary

Although the underlying neural mechanisms are not immediately obvious, the presence of stereotypies in captive animals, including elephants and cetaceans, reflects the neural attempt to cope with an impoverished environment and the resulting detrimental effects of chronic psychosocial stress (Cabib 2006; Poirier and Bateson 2017). What remains unclear is whether the observed stereotypies are the result of temporary pharmacological dysregulation or permanent structural damage (Cabib 2006).

Conclusion

The evidence reviewed here supports the hypothesis that captive elephants and cetaceans sustain impoverishment-related neural deficits and dysregulation similar to what has been documented in other species. Insofar as it is not possible to conduct the same kinds of experimental and functional neuroimaging studies in elephants and cetaceans as in other mammals, we have relied upon the method of triangulation to make inferences about the effects impoverished/captive environments have on elephants and cetaceans. Two of the three points in the triangle are known for captive elephants and cetaceans. First, they exhibit behavioral patterns and physical abnormalities similar to other mammals in impoverished environments. Second, they possess very similar, highly conserved, neurobiological systems as do other mammals for responding to impoverishment and chronic stress. Therefore, we infer the third point, namely that elephants and cetaceans sustain neurobiological insults from living in confined, artificial environments. When elephants and cetaceans are in impoverished environments, their brains likely are affected in a manner similar to all other species that have been examined under similar conditions. The evolutionary continuity in neural structures that exists across eutherians also strongly supports this conclusion.

To the extent that captive elephants and cetaceans experience poor welfare and insofar as our hypothesis about neural damage is valid, there are a couple of options available going forward. First, our hypothesis would be better addressed with neuroanatomical data on captive and free-ranging elephants and cetaceans. There are several brain bank collections for primate brains (e.g., The Primate Brain Bank, The UCLA Brain Bank) and one that includes dolphin specimens (e.g., Michigan State University’s Brain Biodiversity Bank). These kinds of efforts would be amplified and made more scientifically substantive, and facilitate more comparative analyses, if zoos and marine parks regularly contributed well-preserved postmortem brains to these projects. Unfortunately, there is currently little transparency or sharing of scientific information between many zoos/marine parks and the scientific community.

Second, insofar as most captive elephants and cetaceans cannot be “rewilded” for scientific and ethical reasons, the case can be made for transferring them to authentic sanctuaries, where they may live in a more natural environment. There are, for example, two elephant sanctuaries in the U.S. (https://www.pawsweb.org/; https://www.elephants.com/) and others around the world (e.g., https://globalelephants.org/overview/). Currently there is only one cetacean sanctuary in Iceland and it is housing only two beluga whales (https://belugasanctuary.sealifetrust.org/en/). Although more research is clearly needed, authentic sanctuaries report improved physical and psychological health in elephants after their arrival, including decreased frequency or extinction of stereotypies, reduced aggression toward keepers, muscle tone gain, and formation of social bonds between elephants with different social histories, including elephants who were abused, traumatized, or solitary for decades (Buckley 2009; Derby 2009). In closing, current evidence strongly suggests that zoos and marine parks currently provide impoverished environments that exact a neurobiological toll on elephants and cetaceans. Although systemic changes that address these welfare problems may be far off, continued scientific exploration of these issues appears warranted.


Corresponding author: Bob Jacobs,Department of Psychology, Laboratory of Quantitative Neuromorphology, Neuroscience Program, Colorado College, 14 E. Cache La Poudre, Colorado Spring, CO, 80903, USA, E-mail:

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

Ali, A.E., Wilson, Y.M., and Murphy, M. (2009). A single exposure to an enriched environment stimulates the activation of discrete neuronal populations in the brain of the fos-tau-lacZ mouse. Neurobiol. Learn. Mem. 92: 381–390, https://doi.org/10.1016/j.nlm.2009.05.004.Search in Google Scholar

Alt, S.R., Turner, J.D., Klok, M.D., Meijer, O.C., Lakke, E.A., Derijk, R.H., and Muller, C.P. (2010). Differential expression of glucocorticoid receptor transcripts in major depressive disorder is not epigenetically programmed. Psychoneuroendocrinology 35: 544–556, https://doi.org/10.1016/j.psyneuen.2009.09.001.Search in Google Scholar

Altman, J. and Das, G.D. (1964). Autoradiographic examination of the effects of enriched environment on the rate of glial multiplication in the adult rat brain. Nature 204: 1161–1163, https://doi.org/10.1038/2041161a0.Search in Google Scholar

Antonov, I., Antonova, I., Kandel, E.R., and Hawkins, R.D. (2001). The contribution of activity-dependent synaptic plasticity to classical conditioning in Aplysia. J. Neurosci. 21: 6413–6422, https://doi.org/10.1523/jneurosci.21-16-06413.2001.Search in Google Scholar

Arai, J.A. and Feig, L.A. (2011). Long-lasting and transgenerational effects of an environmental enrichment on memory formation. Brain Res. Bull. 85: 30–35, https://doi.org/10.1016/j.brainresbull.2010.11.003.Search in Google Scholar

Archie, E.A., Morrison, T.A., Foley, C.A., Moss, C.J., and Alberts, S.C. (2006). Dominance rank relationships among wild female African elephants, Loxodonta africana. Anim. Behav. 71: 117–127, https://doi.org/10.1016/j.anbehav.2005.03.023.Search in Google Scholar

Atkinson, S., Crocker, D., Houser, D., and Mashburn, K. (2015). Stress physiology in marine mammals: how well do they fit the terrestrial model? J. Comp. Physiol. B. 185: 463–486, https://doi.org/10.1007/s00360-015-0901-0.Search in Google Scholar

Autry, A.E. and Monteggia, L.M. (2012). Brain-derived neurotrophic factor and neuropsychiatric disorders. Pharmacol. Rev. 64: 238–258, https://doi.org/10.1124/pr.111.005108.Search in Google Scholar

Avery, S.N., Clauss, J.A., and Blackford, J.U. (2016). The human BNST: functional role in anxiety and addiction. Neuropsychopharm. Rev. 41: 126–141, https://doi.org/10.1038/npp.2015.185.Search in Google Scholar

Ayub, N., Benton, J.L., Zhang, Y., and Beltz, B.S. (2011). Environmental enrichment influences neuronal stem cells in the adult crayfish brain. Devel. Neurobiol. 71: 351–361, https://doi.org/10.1002/dneu.20864.Search in Google Scholar

Bahar, A., Kasimi, N.H.A., and Hambali, K. (2018). Home range and movement patterns of Asian elephant (Elephas maximus) in Gua Musang, Kelantan, Malaysia. Malay. Nat. J. 70: 221–232.Search in Google Scholar

Ball, N.J., Mercado, E.III, and Orduña, I. (2019). Enriched environments as a potential treatment for developmental disorders: a critical assessment. Front. Psychol. 10: 466, https://doi.org/10.3389/fpsyg.2019.00466.Search in Google Scholar

Balleine, B.W., Balleine, M.R., and Hikosaka, O. (2007). The role of the dorsal striatum in reward and decision-making. J. Neurosci. 27: 8161–8165, https://doi.org/10.1523/jneurosci.1554-07.2007.Search in Google Scholar

Banihashemi, L., Wallace, M.L., Peng, C.W., Stinley, M.M., Germain, A., and Herringa, R.J. (2020). Interactions between childhood maltreatment and combat exposure trauma on stress-related activity within the cingulate cortex: a pilot study. Mil. Psychol. 32: 176–185, https://doi.org/10.1080/08995605.2019.1702831.Search in Google Scholar

Bashaw, M.J., Bloomsmith, M.A., Marr, M., and Maple, T.L. (2003). To hunt or not to hunt? A feeding enrichment experiment with captive large felids. Zoo Biol. 22: 189–198, https://doi.org/10.1002/zoo.10065.Search in Google Scholar

Basso, J.C. and Suzuki, W.A. (2017). The effects of acute exercise on mood, cognition, neurophysiology, and neurochemical pathways: a review. Brain Plast. 2: 127–152, https://doi.org/10.3233/bpl-160040.Search in Google Scholar

Baxter, E. and Plowman, A.B. (2001). The effect of increasing dietary fibre on feeding, rumination and oral stereotypies in captive giraffes (Giraffa camelopardalis). Anim. Welf. 10: 281–290.Search in Google Scholar

Beaulieu, C. and Cynader, M. (1990). Effect of the richness of the environment on neurons in cat visual cortex. I. Receptive field properties. Dev. Brain Res. 53: 71–81, https://doi.org/10.1016/0165-3806(90)90125-i.Search in Google Scholar

Bechard, A.R., Cacodcar, N., King, M.S., and Lewis, M.H. (2016). How does environmental enrichment reduce repetitive motor behaviors? Neuronal activation and dendritic morphology in the indirect basal ganglia pathway of a mouse model. Behav. Brain Res. 299: 122–131, https://doi.org/10.1016/j.bbr.2015.11.029.Search in Google Scholar

Bertapelle, C., Polese, G., and Di Cosmo, A. (2017). Enriched environment increases PCNA and PARP1 levels in Octopus vulgaris central nervous system: first evidence of adult neurogenesis in Lophogtrochozoa. J. Exp. Zool. 328B: 347–359, https://doi.org/10.1002/jez.b.22735.Search in Google Scholar

Besedovsky, H.O. and del Rey, A. (1996). Immune-neuro-endocrine interactions: facts and hypotheses. Endocr. Rev. 17: 64–102, https://doi.org/10.1210/edrv-17-1-64.Search in Google Scholar

Bogart, S.L., Bennett, A.J., Schapiro, S.J., Reamer, L.A., and Hopkins, W.D. (2013). Different early rearing experiences have long-term effects on cortical organization in captive chimpanzees (Pan troglodytes). Dev. Sci. 17: 161–174, https://doi.org/10.1111/desc.12106.Search in Google Scholar

Boorer, M.K. (1972). Some aspects of stereotyped patterns of movement exhibited by zoo animals. Int. Zoo Yearbk. 12: 164–168, https://doi.org/10.1111/j.1748-1090.1972.tb02312.x.Search in Google Scholar

Bos, K.J., Zeanah, C.H., Smyke, A.T., Fox, N.A., and Nelson, C.A. (2010). Stereotypies in children with a history of early institutional care. Arch. Pediatr. Adolesc. Med. 164: 406–411, https://doi.org/10.1001/archpediatrics.2010.47.Search in Google Scholar

Bradshaw, G.A. (2007). Elephants in circuses: analysis of practice, policy, and future. Animals and Society Institute, Ann Arbor, MI.Search in Google Scholar

Brent, L., Lee, D.R., and Eichberg, J.W. (1989). Evaluation of two environment enrichment devices for singly caged chimpanzees (Pan troglodytes). Am. J. Primatol. Suppl. 1: 65–70.Search in Google Scholar

Brown, J.L., Bansiddhi, P., Khonmee, J., and Thitaram, C. (2020). Commonalities in management and husbandry factors important for health and welfare of captive elephants in North America and Thailand. Animals 10: 737, https://doi.org/10.3390/ani10040737.Search in Google Scholar

Brown, J.L., Carlstead, K., Bray, J.D., Dickey, D., and Farin, C. (2019). Individual and environmental risk factors associated with fecal glucocorticoid metabolite concentrations in zoo-housed Asian and African elephants. PLoS One 14: e0217326.10.1371/journal.pone.0217326Search in Google Scholar

Bryant, C., Rupniak, N., and Iversen, S. (1988). Effects of different environmental enrichment devices on cage stereotypies and autoaggression in captive cynomolgus monkeys. J. Med. Primatol. 17: 257–269, https://doi.org/10.1111/j.1600-0684.1988.tb00388.x.Search in Google Scholar

Buckley, C. (2009). Sanctuary: a fundamental requirement of wildlife management. In: Forthman, D.L., Kane, L.F., and Waldau, P. (Eds.), An elephant in the room: the science and well being of elephants in captivity. (Tufts University Cummings School of Veterinary Medicine’s Center for Animals and Public Policy), Medford, MA, pp. 191–197.Search in Google Scholar

Butti, C., Fordyce, E.R., Raghanti, M.A., Gu, X., Bonar, C.J., Wicinski, B.A., Wong, E.W., Roman, J., Brake, A., Eaves, E., et al.. (2014). The cerebral cortex of the pygmy hippopotamus, Hexaprotodon liberiensis (Cetartiodactyla, Hippopotamidae): implications for brain evolution in cetaceans. Anat. Rec. 297: 670–700, https://doi.org/10.1002/ar.22875.Search in Google Scholar

Butti, C., Janeway, C.M., Townshend, C., Wicinski, B.A., Reidenberg, J.S., Ridgway, S.H., Manger, P.R., Sherwood, C.C., Hof, P.R., and Jacobs, B. (2015). Neuronal morphology in cetartiodactyls. I. A comparative Golgi analysis of neuronal morphology in the bottlenose dolphin (Tursiops truncatus), the minke whale (Balaenoptera acutorostrata), and the humpback whale (Megaptera novaeangliae). Brain Struct. Funct. 220: 3339–3368, https://doi.org/10.1007/s00429-014-0860-3.Search in Google Scholar

Cabib, S. (2006). The neurobiology of stereotypy II: the role of stress. Stereotypic animal behavior. In: Mason, G., and Rushen, J. (Eds.), Fundamentals and applications to welfare, 2nd ed. (CABI), Wallingford, CT, pp. 227–255.10.1079/9780851990040.0227Search in Google Scholar

Calabresi, P., Picconi, B., Tozzi, A., Ghiglieri, V., and Di Filippo, M. (2014). Direct and indirect pathways of basal ganglia: a critical reappraisal. Nat. Neurosci. 17: 1022–1030, https://doi.org/10.1038/nn.3743.Search in Google Scholar

Capuron, L. and Miller, A.H. (2011). Immune system to brain signaling: neuropsychopharmacological implications. Pharmacol. Ther. 130: 226–238, https://doi.org/10.1016/j.pharmthera.2011.01.014.Search in Google Scholar

Carlstead, K. and Seidensticker, J. (1991). Seasonal variation in stereotypic pacing in an American black bear Ursus americanus. Behav. Process. 25: 155–161, https://doi.org/10.1016/0376-6357(91)90017-t.Search in Google Scholar

Carlstead, K., Seidensticker, J., and Baldwin, R. (1991). Environmental enrichment for zoo bears. Zoo Biol. 10: 3–16, https://doi.org/10.1002/zoo.1430100103.Search in Google Scholar

Ch’ng, S., Fu, J., Brown, R.M., McDougall, S.J., and Lawrence, A.J. (2018). The intersection of stress and reward: BNST modulation of aversive and appetitive states. Prog. Neuropsychopharmacol. Biol. Psychiatr. 87A: 108–125, https://doi.org/10.1016/j.pnpbp.2018.01.005.Search in Google Scholar

Chaouloff, F. (1989). Physical exercise and brain monoamines: a review. Acta Physiol. Scand. 137: 1–13, https://doi.org/10.1111/j.1748-1716.1989.tb08715.x.Search in Google Scholar

Chattarji, S., Tomar, A., Suvrathan, A., Ghosh, S., and Rahman, M.M. (2015). Neighborhood matters: divergent patterns of stress-induced plasticity across the brain. Nat. Neurosci. 18: 1364–1375, https://doi.org/10.1038/nn.4115.Search in Google Scholar

Christoffel, D.J., Golden, S.A., and Russo, S.J. (2011). Structural and synaptic plasticity in stress-related disorders. Rev. Neurosci. 22: 535–549, https://doi.org/10.1515/RNS.2011.044.Search in Google Scholar

Chugani, H.T., Behen, M.E., Muzik, O., Juhász, C., Nagy, F., and Chugani, D.C. (2001). Local brain functional activity following early deprivation: a study of postinstitutionalized Romanian orphans. Neuroimage 14: 1290–1301, https://doi.org/10.1006/nimg.2001.0917.Search in Google Scholar

Clegg, I.L. and Delfour, F. (2018). Can We assess marine mammal welfare in captivity and in the wild? Considering the example of bottlenose dolphins. Aquat. Mamm. 44: 181–200, https://doi.org/10.1578/am.44.2.2018.181.Search in Google Scholar

Clegg, I.L.K., and Butterworth, A. (2017). Assessing the welfare of pinnipeds. In: Butterworth, A. (Ed.), Marine mammal welfare. Springer, Cham, Switzerland, pp. 273–295.10.1007/978-3-319-46994-2_16Search in Google Scholar

Clegg, I.L.K., van Elk, C.E., and Delfour, F. (2017). Applying welfare science to bottlenose dolphins (Tursiops truncatus). Anim. Welf. 26: 165–176, https://doi.org/10.7120/09627286.26.2.165.Search in Google Scholar

Clubb, R. and Mason, G. (2002). A review of the welfare of zoo elephants in Europe. RSPCA, Horsham, West Sussex, UK.Search in Google Scholar

Clubb, R. and Mason, G. (2003). Captivity effects on wide-ranging carnivores. Nature 425: 473–474, https://doi.org/10.1038/425473a.Search in Google Scholar

Clubb, R. and Mason, G. (2007). Natural behavioural biology as a risk factor in carnivore welfare: how analysing species differences could help zoos improve enclosures. Appl. Anim. Behav. Sci. 102: 303–328, https://doi.org/10.1016/j.applanim.2006.05.033.Search in Google Scholar

Clubb, R., Rowcliffe, M., Lee, P., Mar, K.U., Moss, C., and Mason, G.J. (2008). Compromised survivorship in zoo elephants. Science 322: 1649, https://doi.org/10.1126/science.1164298.Search in Google Scholar

Clubb, R., Rowcliffe, M., Lee, P., Mar, K.U., Moss, C., and Mason, G.J. (2009). Fecundity and population viability in female zoo elephants: problems and possible solutions. Anim. Welf. 18: 237–247.Search in Google Scholar

Cozzi, B., Spagnoli, S., and Bruno, L. (2001). An overview of the central nervous system of the elephant through a critical appraisal of the literature published in the XIX and XX centuries. Brain Res. Bull. (Arch. Am. Art) 54: 219–227, https://doi.org/10.1016/s0361-9230(00)00456-1.Search in Google Scholar

Deecke, V.B. (2018). Dolphins and whales: taking the cognitive research out of the tanks and into the wild. In: Comparative Guide, A., Bueno-Guerra, N.F., and Amici (Eds.), Field and laboratory methods in animal cognition. Cambridge University Press, Cambridge, UK, pp. 146–176.10.1017/9781108333191.009Search in Google Scholar

de Pablos, R.M., Herrera, A.J., Espinosa-Oliva, A.M., Sarmiento, M., Muñoz, M.F., Machado, A., and Venero, J.L. (2014). Chronic stress enhances microglia activation and exacerbates death of nigral dopaminergic neurons under conditions of inflammation. J. Neuroinflammation 11: 34, https://doi.org/10.1186/1742-2094-11-34.Search in Google Scholar

de Silva, S., Ranjeewa, S.D.G., and Kryazhimskiy, S. (2011). The dynamics of social networks among female Asian elephants. BMC Ecol. 11: 17, https://doi.org/10.1186/1472-6785-11-17.Search in Google Scholar

del Arco, A., Segovia, G., Canales, J.J., Garrido, P., de Blas, M., García-Verdugo, J.M., and Mora, F. (2007). Environmental enrichment reduces the function of D1 dopamine receptors in the prefrontal cortex of the rat. J. Neural. Transm. 114: 43–48, https://doi.org/10.1007/s00702-006-0565-8.Search in Google Scholar

Denver, R.J. (2009). Structural and functional evolution of vertebrate neuroendocrine stress systems. Ann. N. Y. Acad. Sci. 1173: 1–16, https://doi.org/10.1111/j.1749-6632.2009.04433.x.Search in Google Scholar

Derby, P. (2009). Changes in social and biophysical environment yield improved physical and psychological health for captive elephants. An elephant in the room: the science and well-being of elephants in captivity. In: Forthman, D.L., Kane, L.F., and Waldau, P. (Eds.), An elephant in the room: the science and well being of elephants in captivity. Tufts University Cummings School of Veterinary Medicine’s Center for Animals and Public Policy, Medford, MA, pp. 198–207.Search in Google Scholar

Diamond, M.C. (1988). Enriching heredity: the impact of the environment on the anatomy of the brain. Free Press, New York.Search in Google Scholar

Diamond, M.C., Johnson, R.E., Protti, A.M., Ott, C., and Lajisa, L. (1985). Plasticity in the 904-day-old male rat cerebral cortex. Exp. Neurol. 87: 309–317, https://doi.org/10.1016/0014-4886(85)90221-3.Search in Google Scholar

Diamond, M.C., Krech, D., and Rosenzweig, M.R. (1964). The effects of an enriched environment on the histology of the rat cerebral cortex. J. Comp. Neurol. 123: 111–119, https://doi.org/10.1002/cne.901230110.Search in Google Scholar

Diamond, M.C., Lindner, B., and Raymond, A. (1967). Extensive cortical depth measurements and neuron size increases in the cortex of environmentally enriched rats. J. Comp. Neurol. 131: 357–364, https://doi.org/10.1002/cne.901310305.Search in Google Scholar

Dias-Ferreira, E., Sousa, J.C., Melo, I., Morgado, P., Mesquita, A.R., Cerqueira, J.J., Costa, R.M., and Sousa, N. (2009). Chronic stress causes frontostriatal reorganization and affects decision-making. Science 325: 621–625, https://doi.org/10.1126/science.1171203.Search in Google Scholar

Dierenfeld, E.S. (2006). Nutrition. In: Fowler, M.E., and Mikota, S.K. (Eds.), Biology, medicine, and surgery of elephants. Blackwell Publishing, Ames, Iowa, pp. 57–65.10.1002/9780470344484.ch6Search in Google Scholar

Dittrich, L. (1987). Observations on keeping the Pacific walrus Odobenus rosmarus divergens at hanover zoo. Int. Zoo Yearbk. 26: 163–170.10.1111/j.1748-1090.1987.tb03153.xSearch in Google Scholar

Draganski, B., Gaser, C., Busch, V., Schulerer, G., Bogdahn, U., and May, A. (2004). Neuroplasticity: changes in grey matter induced by training. Nature 427: 311–312, https://doi.org/10.1038/427311a.Search in Google Scholar

Edwards, K.L., Edes, A.N., and Brown, J.L. (2019). Stress, well-being and reproductive success. In: Holt, W.V., Brown, J.L., and Comizzoli, P. (Eds.), Reproductive sciences in animal conservation, 2nd ed. Springer, Cham, Switzerland, pp. 91–162.10.1007/978-3-030-23633-5_5Search in Google Scholar

Edwards, M.J., Lang, A.E., and Bhatia, K.P. (2012). Stereotypies: a critical appraisal and suggestion of a clinically useful definition. Mov. Dis. 27: 179–185, https://doi.org/10.1002/mds.23994.Search in Google Scholar

Elston, G.N. and Rosa, M.G.P. (1997). The occipitoparietal pathway of the macaque monkey: comparison of pyramidal cell morphology in layer III of functionally related cortical visual areas. Cereb. Cortex. 7: 432–452, https://doi.org/10.1093/cercor/7.5.432.Search in Google Scholar

Eluvathingal, T.J., Chugani, H.T., Behen, M.E., Juhász, C., Muzik, O., Maqbool, M., Chugani, D.C., and Makki, M. (2006). Abnormal brain connectivity in children after early severe socioemotional deprivation: a diffusion tensor imaging study. Pediatrics 117: 2093–2100, https://doi.org/10.1542/peds.2005-1727.Search in Google Scholar

Eriksen, N. and Pakkenberg, B. (2007). Total neocortical cell number in the mysticete brain. Anat. Rec. 290: 83–95, https://doi.org/10.1002/ar.20404.Search in Google Scholar

Fahnestock, M., Marchese, M., Head, E., Pop, V., Michalski, B., Milgram, W.N., and Cotman, C.W. (2012). BDNF increases with behavior enrichment and an antioxidant diet in the aged dog. Neurobiol. Aging 33: 546–554, https://doi.org/10.1016/j.neurobiolaging.2010.03.019.Search in Google Scholar

Ferchmin, P.A., Bennett, E.L., and Rosenzweig, M.R. (1975). Direct contact with enriched environment is required to alter cerebral weights in rats. J. Comp. Physiol. Psychol. 88: 360–367, https://doi.org/10.1037/h0076175.Search in Google Scholar

Fernandez, L.T., Bashaw, M.J., Sartor, R.L., Bouwens, N.R., and Maki, T.S. (2008). Tongue twisters: feeding enrichment to reduce oral stereotypy in giraffe. Zoo Biol. 27: 200–212, https://doi.org/10.1002/zoo.20180.Search in Google Scholar

Finlay, B.L. and Darlington, R.B. (1995). Linked regularities in the development and evolution of mammalian brains. Science 268: 1578–1584, https://doi.org/10.1126/science.7777856.Search in Google Scholar

Flies, A.S., Mansfield, L.S., Grant, C.K., Weldele, M.L., and Holekamp, K.E. (2015). Markedly elevated antibody responses in wild versus captive spotted hyenas show that environmental and ecological factors are important modulators of immunity. PLoS One 10: e0137679.10.1371/journal.pone.0137679Search in Google Scholar

Floeter, M.K. and Greenough, W.T. (1979). Cerebellar plasticity: modification of Purkinje cell structure by differential rearing in monkeys. Science 206: 227–229, https://doi.org/10.1126/science.113873.Search in Google Scholar

Fordyce, D.E. and Farrar, R.P. (1991). Physical activity effects on hippocampal and parietal cortical cholinergic function and spatial learning in F344 rats. Behav. Brain Res. 43: 115–123, https://doi.org/10.1016/s0166-4328(05)80061-0.Search in Google Scholar

Fowler, M.E. (2001). An overview of foot conditions in Asian and African elephants. In: Csuti, B., Sargent, E.L., and Bechert, U.S. (Eds.), The elephant’s foot: prevention and care of foot conditions in captive Asian and African elephants. Iowa State University Press, Ames, Iowa, pp. 3–8.10.1002/9780470292150.ch1Search in Google Scholar

Fowler, M.E. (2006a). Foot disorders. In: Fowler, M.E. and Mikota, S.K. (Eds.). Biology, medicine, and surgery of elephants. Blackwell Publishing, Ames, Iowa, pp. 271–290.10.1002/9780470344484.ch20Search in Google Scholar

Fowler, M.E. (2006b). Infectious diseases. In: Fowler, M.E. and Mikota, S.K. (Eds.). Biology, medicine, and surgery of elephants. Blackwell Publishing, Ames, Iowa, pp. 131–158.10.1002/9780470344484.ch11Search in Google Scholar

Frodl, T. and O’Keane, V. (2013). How does the brain deal with cumulative stress? A review with focus on developmental stress, HPA axis function and hippocampal structure in humans. Neurobiol. Dis. 52: 24–37, https://doi.org/10.1016/j.nbd.2012.03.012.Search in Google Scholar

Frohoff, T. (2018). Cetaceans and elephants: similar lives, treatment, and needs in captivity. In: Paper presented at the PAWS international captive wildlife conference. Los Angeles, CA, USA.Search in Google Scholar

Fuery, A., Leen, A.M., Peng, R., Wong, M.C., Liu, H., and Ling, P.D. (2018). Asian elephant T cell responses to elephant endotheliotropic herpesvirus. J. Virol. 92: e01951–17, https://doi.org/10.1128/JVI.01951-17.Search in Google Scholar

Gage, L.J. (2010). Cetacean medicine. In: Paper presented at the wild west veterinary conference. Reno, NV, USA.Search in Google Scholar

Gao, S. and Singer, H.S. (2013). Complex motor stereotypies: an evolving neurobiological concept. Future Neurol. 8: 273–285, https://doi.org/10.2217/fnl.13.4.Search in Google Scholar

Garey, L.J., Takács, J., Revishchin, A.V., and Hámori, J. (1989). Quantitative distribution of GABA-immunoreactive neurons in cetacean visual cortex is similar to that in land mammals. Brain Res. 485: 278–284, https://doi.org/10.1016/0006-8993(89)90571-4.Search in Google Scholar

Garner, J.P., Meehan, C.L., and Mench, J.A. (2003). Stereotypies in caged parrots, schizophrenia and autism: evidence for a common mechanism. Behav. Brain Res. 145: 125–134, https://doi.org/10.1016/s0166-4328(03)00115-3.Search in Google Scholar

Gaser, C. and Schlaug, G. (2003). Brain structures differ between musicians and non-musicians. J. Neurosci. 23: 9240–9245, https://doi.org/10.1523/jneurosci.23-27-09240.2003.Search in Google Scholar

Glezer, I.I., Hof, P.R., and Morgane, P.J. (1992). Calretinin-immunoreactive neurons in the primary visual cortex of dolphin and human brains. Brain Res. 595: 181–188, https://doi.org/10.1016/0006-8993(92)91047-i.Search in Google Scholar

Glezer, I.I., Hof, P.R., and Morgane, P.J. (1998). Comparative analysis of calcium-binding protein-immunoreactive neuronal populations in the auditory and visual systems of the bottlenose dolphin (Tursiops truncatus) and the macaque monkey (Macaca fascicularis). J. Chem. Neuroanat. 15: 203–237, https://doi.org/10.1016/s0891-0618(98)00022-2.Search in Google Scholar

Globus, A., Rosenzweig, M.R., Bennett, E.L., and Diamond, M.C. (1973). Effects of differential experience on dendritic spine counts in rat cerebral cortex. J. Comp. Physiol. Psychol. 82: 175–181, https://doi.org/10.1037/h0033910.Search in Google Scholar

Gomes, E.C., and Florida-James, G. (2016). Exercise and the immune system. In: Esser, E. (Ed.), Environmental influences on the immune system. Springer, Vienna, Austria, pp. 127–152.10.1007/978-3-7091-1890-0_6Search in Google Scholar

Goriounova, N.A., Heyer, D.B., Wilbers, R., Verhoog, M.B., Giugliano, M., Verbist, C., Obermayer, J., Kerkhofs, A., and Smeding, H. (2018). Large and fast human pyramidal neurons associate with intelligence. eLife 7: e41714, https://doi.org/10.7554/eLife.41714.Search in Google Scholar

Greco, B.J., Meehan, C., Heinsius, J., and Mench, J. (2017). Why pace? The influence of social, housing, management, life history, and demographic characteristics on locomotor stereotypy in zoo elephants. Appl. Anim. Behav. Sci. 194: 104–111, https://doi.org/10.1016/j.applanim.2017.05.003.Search in Google Scholar

Greco, B.J., Meehan, C.L., Hogan, J.N., Leighty, K.A., Mellen, J., Mason, G.J., and Mench, J.A. (2016). The days and nights of zoo elephants: using epidemiology to better understand stereotypic behavior of African elephants (Loxodonta africana) and Asian elephants (Elephas maximus) in North American zoos. PloS One 11: e0144276, https://doi.org/10.1371/journal.pone.0144276.Search in Google Scholar

Greene, W., Dierenfeld, E.G., and Mikota, S. (2019). A review of Asian and African elephant gastrointestinal anatomy, physiology and pharmacology. J. Zoo Aquar. Res. 7: 1–14.Search in Google Scholar

Greenough, W.T., Volkmar, F.R., and Juraska, J.M. (1973). Effects of rearing complexity on dendritic branching in frontolateral and temporal cortex of the rat. Exp. Neurol. 41: 371–378, https://doi.org/10.1016/0014-4886(73)90278-1.Search in Google Scholar

Grindrod, J.A.E. and Cleaver, J.A. (2001). Environmental enrichment reduces the performance of stereotypic circling behaviour in captive common seals (Phoca vitulina). Anim. Welf. 10: 53–63.Search in Google Scholar

Groh, C. and Rössler, W. (2020). Analysis of synaptic microcircuits in the mushroom bodies of the honeybee. Insects 11: 43, https://doi.org/10.3390/insects11010043.Search in Google Scholar

Guidi, J., Lucente, M., Sonino, N., and Fava, G.A. (2021). Allostatic load and its impact on health: a systematic review. Psychother. Psychosom. 90: 11–27, https://doi.org/10.1159/000510696.Search in Google Scholar

Habas, C. (2021). Functional connectivity of the cognitive cerebellum. Front. Syst. Neurosci. 15: 642225, https://doi.org/10.3389/fnsys.2021.642225.Search in Google Scholar

Hall, F.S., Wilkinson, L.S., Humby, T., Inglis, W., Kendall, D.A., Marsden, C.A., and Robbins, T.W. (1998). Isolation rearing in rats: pre- and postsynaptic changes in striatal dopaminergic systems. Pharmacol., Biochem. Behav. 59: 859–872, https://doi.org/10.1016/s0091-3057(97)00510-8.Search in Google Scholar

Hanson, A., Grisham, W., Sheh, C., Annese, J., and Ridgway, S. (2013). Quantitative examination of the bottlenose dolphin cerebellum. Anat. Rec. 296: 1215–1228, https://doi.org/10.1002/ar.22726.Search in Google Scholar

Harvey, N., Daly, C., Clark, N., Ransford, E., Wallace, S., and Yon, L. (2018). Social interactions in two groups of zoo-housed adult female Asian Elephants (Elephas maximus) that differ in relatedness. Animals 8: 132, https://doi.org/10.3390/ani8080132.Search in Google Scholar

Hawkley, L.C., Cole, S.W., Capitanio, J.P., Norman, G.J., and Cacioppo, J.C. (2012). Effects of social isolation on glucocorticoid regulation in social mammals. Horm. Behav. 62: 314–323, https://doi.org/10.1016/j.yhbeh.2012.05.011.Search in Google Scholar

He, S., Ma, J., Liu, N., and Yu, X. (2010). Early enriched environment promotes neonatal GABAergic neurotransmission and accelerates synapse maturation. J. Neurosci. 30: 7910–7916, https://doi.org/10.1523/jneurosci.6375-09.2010.Search in Google Scholar

Hebb, D.O. (1947). The effects of early experience on problem- solving at maturity. Am. Psychol. 2: 306–307.Search in Google Scholar

Heisz, J.J., Clark, I.B., Bonin, K., and Paolucci, E.M. (2017). The effects of physical exercise and cognitive training on memory and neurotrophic factors. J. Cog. Neurosci: 1895–1907, https://doi.org/10.1162/jocn_a_01164.Search in Google Scholar

Henderson, J.V. and Waran, N.K. (2001). Reducing equine stereotypies using an equiball. Anim. Welf. 10: 73–80.Search in Google Scholar

Henderson, N. (1970). Brain weight increases resulting from environmental enrichment: a directional dominance in mice. Science 169: 776–778, https://doi.org/10.1126/science.169.3947.776.Search in Google Scholar

Herculano-Houzel, S. (2009). The human brain in numbers: a linearly scaled-up primate brain. Front. Human Neurosci. 3: 31, https://doi.org/10.3389/neuro.09.031.2009.Search in Google Scholar

Herculano-Houzel, S., Avelino-de-Souza, K., Neves, K., Porfírio, J., Messeder, D., Mattos Feijó, L., Maldonado, J., and Manger, P.R. (2014). The elephant brain in numbers. Front. Neuroanat. 8: 46, https://doi.org/10.3389/fnana.2014.00046.Search in Google Scholar

Hof, P.R., Chanis, R., and Marino, L. (2005). Cortical complexity in cetacean brains. Anat. Rec. 287: 1142–1152, https://doi.org/10.1002/ar.a.20258.Search in Google Scholar

Holler, S., Köstinger, G., Martin, K.A.C., Schulknecht, F.P., and Stratford, K.J. (2021). Structure and function of a neocortical synapse. Nature 591: 111–116, https://doi.org/10.1038/s41586-020-03134-2.Search in Google Scholar

Holtmaat, A. and Svoboda, K. (2009). Experience-dependent structural synaptic plasticity in the mammalian brain. Nat. Rev. Neurosci. 10: 647–658, https://doi.org/10.1038/nrn2699.Search in Google Scholar

Horowitz, A., Fan, X., Bieri, G., Smith, L.K., Sanchez-Diaz, C.I., Schroer, A.B., Gontier, G., Casaletto, K.B., Kramer, J.H., Williams, K.E., et al.. (2020). Blood factors transfer beneficial effects of exercise on neurogenesis and cognition to the aged brain. Science 369: 167–173, https://doi.org/10.1126/science.aaw2622.Search in Google Scholar

Hosey, G., Melfi, V., and Ward, S.J. (2020). Problematic animals in the zoo: the issue of Charismatic Megafauna. In: Angelici, F., and Rossi, L. (Eds.), Problematic wildlife II. Springer, Cham, Switzerland, pp. 485–508.10.1007/978-3-030-42335-3_15Search in Google Scholar

Issa, R.I. and Griffin, T.M. (2012). Pathobiology of obesity and osteoarthritis: integrating biomechanics and inflammation. Pathobiol. Aging Age Relat. Dis. 2: 1, https://doi.org/10.3402/pba.v2i0.17470.Search in Google Scholar

Jackson, J., Childs, D.Z., Mar, K.U., Htut, W., and Lummaa, V. (2019). Long-term trends in wild-capture and population dynamics point to an uncertain future for captive elephants. Proc. R. Soc. B 286: 20182810, https://doi.org/10.1098/rspb.2018.2810.Search in Google Scholar

Jacobs, B., Garcia, M.E., Shea-Shumsky, N.B., Tennison, M.E., Schall, M., Saviano, M.S., Tummino, T.A., Bull, A.J., Driscoll, L.L., Raghanti, M.A., et al.. (2018). Comparative morphology of gigantopyramidal neurons in primary motor cortex across mammals. J. Comp. Neurol. 526: 496–536, https://doi.org/10.1002/cne.24349.Search in Google Scholar

Jacobs, B., Harland, T., Kennedy, D., Schall, M., Wicinski, B., Butti, C., Hof, P.R., Sherwood, C.C., and Manger, P.R. (2015). The neocortex of cetartiodactyls. II. Neuronal morphology of the visual and motor cortices in the giraffe (Giraffa camelopardalis). Brain Struct. Funct. 220: 2851–2872, https://doi.org/10.1007/s00429-014-0830-9.Search in Google Scholar

Jacobs, B., Johnson, N., Wahl, D., Schall, M., Maseko, B.C., Lewandowski, A., Raghanti, M.A., Wicinski, B., Butti, C., Hopkins, W.D., et al.. (2014). Comparative neuronal morphology of cerebellar cortex in afrotherians, primates, cetartiodactyls, and carnivores. Front. Neuroanat. 8: 24, https://doi.org/10.3389/fnana.2014.00024.Search in Google Scholar

Jacobs, B., Lubs, J., Hannan, M., Anderson, K., Butti, C., Sherwood, C.C., Hof, P.R., and Manger, P.R. (2011). Neuronal morphology in the African elephant (Loxodonta africana) neocortex. Brain Struct. Funct. 215: 273–298, https://doi.org/10.1007/s00429-010-0288-3.Search in Google Scholar

Jacobs, B., Schall, M., Prather, M., Kapler, E., Driscoll, L., Baca, S., Jacobs, J., Ford, K., Wainwright, M., and Treml, M. (2001). Regional dendritic and spine variation in human cerebral cortex: a quantitative Golgi study. Cerebr. Cortex 11: 558–571, https://doi.org/10.1093/cercor/11.6.558.Search in Google Scholar

Jacobs, B., Schall, M., and Scheibel, A.B. (1993). A quantitative dendritic analysis of Wernicke’s area in humans. II. Gender, hemispheric, and environmental factors. J. Comp. Neurol. 327: 97–111, https://doi.org/10.1002/cne.903270108.Search in Google Scholar

Jett, J. and Ventre, J. (2012). Orca (Orcinus orca) captivity and vulnerability to mosquito transmitted viruses. J. Mar. Anim. Ecol 5: 9–16.Search in Google Scholar

Jett, J., Visser, I.N., Ventre, J., Waltz, J., and Loch, C. (2017). Tooth damage in captive orcas (Orcinus orca). Arch. Oral Biol. 84: 151–160, https://doi.org/10.1016/j.archoralbio.2017.09.031.Search in Google Scholar

Kagan, R., Allard, S., and Carter, S. (2018). What is the future for zoos and aquariums? J. Appl. Anim. Welfare Sci. 21: 59–70, https://doi.org/10.1080/10888705.2018.1514302.Search in Google Scholar

Katz, H.B. and Davies, C.A. (1984). Effects of differential environments on the cerebral anatomy of rats as a function of previous and subsequent housing conditions. Exp. Neurol. 83: 274–287, https://doi.org/10.1016/s0014-4886(84)90098-0.Search in Google Scholar

Kellar, N.M., Catelani, K.N., Robbins, M.N., Trego, M.L., Allen, C.D., Danil, K., and Chivers, S.J. (2015). Blubber cortisol: a potential tool for assessing stress response in free-ranging dolphins without effects due to sampling. PloS One 10: e0115257, https://doi.org/10.1371/journal.pone.0115257.Search in Google Scholar

Kelly, J.R., Borre, Y., O’Brien, C., Patterson, E., Aidy, S.E., Deane, J., Kennedy, P.J., Beers, S., Scott, K., Moloney, G., et al.. (2016). Transferring the blues: depression-associated gut microbiota induces neurobehavioural changes in the rat. J. Psychiatr. Res. 82: 109–118, https://doi.org/10.1016/j.jpsychires.2016.07.019.Search in Google Scholar

Kempermann, G., Georg Kuhn, H., and Gage, F.H. (1997). More hippocampal neurons in adult mice living in an enriched environment. Nature 386: 493–495, https://doi.org/10.1038/386493a0.Search in Google Scholar

Khadpekar, Y., Selvaraj, I., Sha, A., and Kamalanathan, M. (2020). Clinical management of intestinal impaction and colic in an Asian elephant. Gajah 51: 26–30.Search in Google Scholar

Kishida, T., Thewissen, J., Hayakawa, T., Imai, H., and Agata, K. (2015). Aquatic adaptation and the evolution of smell and taste in whales. Zool. Lett. 1: 9, https://doi.org/10.1186/s40851-014-0002-z.Search in Google Scholar

Kleim, J.A., Swain, R.A., Armstrong, K.A., Napper, R.M.A., Jones, T.A., and Greenough, W.T. (1998). Selective synaptic plasticity within the cerebellar cortex following complex motor skill learning. Neurobiol. Learn. Mem. 69: 274–289, https://doi.org/10.1006/nlme.1998.3827.Search in Google Scholar

Koenigs, M. and Grafman, J. (2009). Posttraumatic stress disorder: the role of medial prefrontal cortex and amygdala. Neuroscientist 15: 540–548, https://doi.org/10.1177/1073858409333072.Search in Google Scholar

Kozorovitskiy, Y., Gross, C.G., Kopil, C., Battaglia, L., McBreen, M., Stranahan, A.M., and Gould, E. (2005). Experience induces structural and biochemical changes in the adult primate brain. Proc. Nat. Acad. Sci. USA 102: 17478–17482, https://doi.org/10.1073/pnas.0508817102.Search in Google Scholar

La Torre, J.C. (1968). Effect of differential environmental enrichment on brain weight and on acetylcholinesterase and cholinesterase activities in mice. Exp. Neurol. 22: 493–503, https://doi.org/10.1016/0014-4886(68)90144-1.Search in Google Scholar

Lahdenperä, M., Mar, K.U., Courtiol, A., and Lummaa, V. (2018). Differences in age-specific mortality between wild-caught and captive-born Asian elephants. Nat. Commun. 9: 3023, https://doi.org/10.1038/s41467-018-05515-8.Search in Google Scholar

Lambert, K., Hyer, M., Bardi, M., Rzucidlo, A., Scott, S., Terhune-Cotter, B., Hazelgrove, A., Silva, I., and Kinsley, C. (2016). Natural-enriched environments lead to enhanced environmental engagement and altered neurobiological resilience. Neuroscience 330: 386–394, https://doi.org/10.1016/j.neuroscience.2016.05.037.Search in Google Scholar

Lambert, K.G., Nelson, R.J., Javanovic, T., and Cerdá, M. (2015). Brains in the city: neurobiological effects of urbanization. Neurosci. Biobehav. Rev. 58: 107–122, https://doi.org/10.1016/j.neubiorev.2015.04.007.Search in Google Scholar

Langen, M., Dienke, B., Noordermeer, S.D., Nederveen, H., van Engeland, H., and Durston, S. (2014). Changes in the development of striatum are involved in repetitive behavior in autism. Biol. Psychiatr. 76: 405–411, https://doi.org/10.1016/j.biopsych.2013.08.013.Search in Google Scholar

Langen, M., Durston, S., Kas, M.J.H., van Engeland, H., Staal, W.G., and Neurosci (2011a). The neurobiology of repetitive behavior: of men. BioBehav. Rev. 35: 356–365, https://doi.org/10.1016/j.neubiorev.2010.02.005.Search in Google Scholar

Langen, M., Kas, M.J.H., Staal, W.G., van Engeland, H., Durston, S., and Neurosci (2011b). The neurobiology of repetitive behavior: of mice. BioBehav. Rev. 35: 345–355, https://doi.org/10.1016/j.neubiorev.2010.02.004.Search in Google Scholar

Latham, N.R. and Mason, G. (2010). Frustration and perseveration in stereotypic captive animals: is a taste of enrichment worse than none at all? Behav. Brain Res. 211: 96–104, https://doi.org/10.1016/j.bbr.2010.03.018.Search in Google Scholar

Law, G. and Kitchener, A.C. (2017). Environmental enrichment for Killer whales Orcinus orca at zoological institutions: untried and untested. Int. Zoo Yearbk. 51: 232–247, https://doi.org/10.1111/izy.12152.Search in Google Scholar

Laws, N., Ganswindt, A., Heistermann, M., Harris, M., Harris, S., and Chris Sherwin, C. (2007). A case study: fecal corticosteroid and behavior as indicators of welfare during relocation of an Asian elephant. J. Appl. Anim. Welfare Sci. 10: 349–358, https://doi.org/10.1080/10888700701555600.Search in Google Scholar

Lecorps, B., Weary, D.M., and von Keyserlingk, M.A.G. (2021). Captivity-induced depression in animals. Trends Cognit. Sci. 25: 539–541, https://doi.org/10.1016/j.tics.2021.03.010.Search in Google Scholar

LeDoux, J.E. (1994). The amygdala: Contributions to fear and stress. Semin. Neurosci. 6: 231–237, https://doi.org/10.1006/smns.1994.1030.Search in Google Scholar

Leggio, M.G., Mandolesi, L., Federico, F., Spirito, F., Ricci, B., Gelfo, F., and Petrosini, L. (2005). Environmental enrichment promotes improved spatial abilities and enhanced dendritic growth in the rat. Behav. Brain Res. 163: 78–90, https://doi.org/10.1016/j.bbr.2005.04.009.Search in Google Scholar

Lenhardt, J. (2006). Husbandry. In: Fowler, M.E., and Mikota, S.K. (Eds.), Biology, medicine, and surgery of elephants. Blackwell Publishing, Ames, Iowa, pp. 45–56.10.1002/9780470344484.ch5Search in Google Scholar

Lenhart, L., Nagele, M., Steiger, R., Beliveau, B., Skalla, E., Zamarian, L., Gizewski, E.R., Benke, T., Delazer, M., and Scherfler, C. (2021). Occupation-related effects on motor cortex thickness among older, cognitive healthy individuals. Brain Struct. Funct. 226: 1023–1030, https://doi.org/10.1007/s00429-021-02223-w.Search in Google Scholar

Leszek, J., Barreto, G.E., Gasiorowski, K., Koutsouraki, E., Avila-Rodrigues, M., and Aliev, G. (2016). Inflammatory mechanisms and oxidative stress as key factors responsible for progression of neurodegeneration: role of brain innate immune system. CNS Neurol. Disord. Drug Targets 15: 329–336, https://doi.org/10.2174/1871527315666160202125914.Search in Google Scholar

Lewis, M.H., Presti, M.F., Lewis, J.B., and Turner, C.A. (2006). The neurobiology of stereotypy I: environmental complexity. In: Mason, G., and Rushen, J. (Eds.), Stereotypic animal behavior: fundamentals and applications to welfare, 2nd ed. CABI, Wallingford, UK, pp. 190–226.10.1079/9780851990040.0190Search in Google Scholar

Liang, J., Wang, H., Zeng, Y., Qu, Y., Liu, Q., Zhao, F., Duan, J., Jiang, Y., Li, S., and Ying, J. (2021). Physical exercise promotes brain remodeling by regulating epigenetics, neuroplasticity and neurotrophins. Rev. Neurosci. 32: 615–629, https://doi.org/10.1515/revneuro-2020-0099.Search in Google Scholar

Limacher-Burrell, A., Bhagwandin, A., Maseko, B.C., and Manger, P.R. (2018). Nuclear organization of the African elephant (Loxodonta africana) amygdaloid complex: an unusual mammalian amygdala. Brain Struct. Funct. 223: 1191–1216, https://doi.org/10.1007/s00429-017-1555-3.Search in Google Scholar

Lindsay, K. (2017). Solitary elephants in Japan, Available at: https://elephantsinjapan.com/wp-content/uploads/2017/08/EIJ_Final_report_ENG_web.pdf.Search in Google Scholar

Lott, R., and Williamson, C. (2017). Cetaceans in captivity. In: Butterworth, A. (Ed.), Marine mammal welfare, 17. Springer, Cham, Switzerland, pp. 161–181.10.1007/978-3-319-46994-2_11Search in Google Scholar

Lupien, S.J., McEwen, B.S., Gunnar, M.R., and Heim, C. (2009). Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nat. Rev. Neurosci. 10: 434–445, https://doi.org/10.1038/nrn2639.Search in Google Scholar

Lutz, C., Well, A., and Novak, M. (2003). Stereotypic and self-injurious behavior in rhesus macaques: a survey and retrospective analysis of environment and early experience. Am. J. Primatol. 60: 1–15, https://doi.org/10.1002/ajp.10075.Search in Google Scholar

Lyashchenko, K.P., Greenwald, R., Esfandiari, J., Olsen, J.H., Ball, R., Dumonceaux, G., Dunker, F., Buckley, C., Richard, M., Murray, S., et al.. (2006). Tuberculosis in elephants: antibody responses to defined antigens of Mycobacterium tuberculosis, potential for early diagnosis, and monitoring of treatment. Clin. Vaccine Immunol. 13: 722–732, https://doi.org/10.1128/cvi.00133-06.Search in Google Scholar

Lyn, H., Bahe, H., Broadway, M.S., Samuelson, M.M., Shelley, J.K., Hoffland, T., Jarvis, E., Pulis, K., Shannon, D., and Solangi, M. (2020). When is enrichment enriching? Effective enrichment and unintended consequences in bottlenose dolphins (Tursiops truncatus). Int. J. Comp. Psychol. 33, https://doi.org/10.46867/ijcp.2020.33.04.01.Search in Google Scholar

Maier, S.F. and Seligman, M.E.P. (2016). Learned helplessness at fifty: insights from neuroscience. Psychol. Rev. 123: 349–367, https://doi.org/10.1037/rev0000033.Search in Google Scholar

Manger, P.R. (2006). An examination of cetacean brain structure with a novel hypothesis correlating thermogenesis to the evolution of a big brain. Biol. Rev. Camb. Philos. Soc. 81: 293–338, https://doi.org/10.1017/s1464793106007019.Search in Google Scholar

Manger, P.R., Patzke, N., Spocter, M.A., Bhagwandin, A., Karlsson, K.Æ., Bertelsen, M.F., Alagaili, A.N., Bennett, N.C., Mohammed, O.B., Herculano-Houzel, S., et al.. (2021). Amplification of potential thermogenetic mechanisms in cetacean brains compared to artiodactyl brains. Sci. Rep. 11: 5486, https://doi.org/10.1038/s41598-021-84762-0.Search in Google Scholar

Manger, P.R., Pillay, P., Madeko, B.C., Bhagwandin, A., Gravett, N., Moon, D.-J., Jillani, N., and Hemingway, J. (2009). Acquisition of brains from the African elephant (Loxodonta africana): perfusion-fixation and dissection. J. Neurosci. Methods 179: 16–21, https://doi.org/10.1016/j.jneumeth.2009.01.001.Search in Google Scholar

Manger, P.R., Spocter, M.A., and Patzke, N. (2013). The evolutions of large brain size in mammals: the ‘over-700-gram club quartet’. Brain Behav. Evol. 82: 68–78, https://doi.org/10.1159/000352056.Search in Google Scholar

Marino, L. (2009). Brain size evolution. In: Perrin, W.F., Würsig, B., and Thewissen, H. (Eds.), Encyclopedia of marine mammals, 2nd ed. Academic Press, London, UK, pp. 149–152.10.1016/B978-0-12-373553-9.00039-0Search in Google Scholar

Marino, L. (2015). The brain-structure and function. In: Johnson, C., and Herzing, D. (Eds.), Dolphin communication and cognition. MIT Press, Cambridge, MA, pp. 3–18.Search in Google Scholar

Marino, L. (2020). Mental health issues in captive cetaceans. In: McMillan, F.D. (Ed.), Mental health and well-being in animals, 2nd ed. CABI, Wallingford, UK, pp. 315–327.10.1079/9781786393401.0315Search in Google Scholar

Marino, L., Butti, C., Connor, R.C., Fordyce, R.E., Herman, L.M., Hof, P.R., Lefebvre, L., Lusseau, D., McCowan, B., Nimchinsky, E.A., et al.. (2008). A claim in search of evidence: reply to Manger’s thermogenesis hypothesis of cetacean brain structure. Biol. Rev. Biol. Proc. Camb. Phil. Soc. 83: 417–440, https://doi.org/10.1111/j.1469-185X.2008.00049.x.Search in Google Scholar

Marino, L., Rilling, J.K., Lin, S.K., and Ridgway, S.H. (2000). Relative volume of the cerebellum in the bottlenose dolphin and comparison with anthropoid primates. Brain Behav. Evol. 56: 204–211, https://doi.org/10.1159/000047205.Search in Google Scholar

Marino, L., Rose, N.A., Visser, I.N., Rally, H., Ferdowsian, H., and Slootsky, V. (2020). The harmful effects of captivity and chronic stress on the well-being of orcas (Orcinus orca). J. Vet. Behav. 35: 69–82, https://doi.org/10.1016/j.jveb.2019.05.005.Search in Google Scholar

Markowitz, H. (1982). Behavioral enrichment in the zoo. Van Nostrand- Reinhold, New York.Search in Google Scholar

Martin, L.J., Spicer, D.M., Lewis, M.H., Gluck, J.P., and Cork, L.C. (1991). Social deprivation of infant rhesus monkeys alters the chemoarchitecture of the brain: I. Subcortical regions. J. Neurosci. 11: 3344–3358, https://doi.org/10.1523/jneurosci.11-11-03344.1991.Search in Google Scholar

Maseko, B.C., Jacobs, B., Spocter, M.A., Sherwood, C.C., Hof, P.R., and Manger, P.R. (2012). Qualitative and qualitative aspects of the microanatomy of the African elephant cerebellar cortex. Brain Behav. Evol. 81: 40–55, https://doi.org/10.1159/000345565.Search in Google Scholar

Maseko, B.C., Patzke, N., Fuxe, K., and Manger, P.R. (2013). Architectural organization of the African elephant diencephalon and brainstem. Brain Behav. Evol. 82: 83–128, https://doi.org/10.1159/000352004.Search in Google Scholar

Mason, G.J. (2010). Species differences in responses to captivity: stress, welfare and the comparative method. Trends Ecol. Evol. 25: 713–721, https://doi.org/10.1016/j.tree.2010.08.011.Search in Google Scholar

Mason, G.J. and Rushen, J. (2008). Stereotypic animal behaviour: fundamentals and applications to welfare, 2nd ed. CABI, Oxfordshire, U.K.Search in Google Scholar

Mason, G.J. and Veasey, J.S. (2010). What do population-level welfare indices suggest about the well-being of zoo elephants? Zoo Biol. 29: 256–273, https://doi.org/10.1002/zoo.20303.Search in Google Scholar

Matthews, C.J.D., Luque, S.P., Petersen, S.D., Andrews, R.D., and Ferguson, S.H. (2011). Satellite tracking of a killer whale (Orcinus orca) in the eastern Canadian Arctic documents ice avoidance and rapid, long-distance movement into the North Atlantic. Polar Biol. 34: 1091–1096, https://doi.org/10.1007/s00300-010-0958-x.Search in Google Scholar

Mazzaro, L.M., Johnson, S.P., Fair, P.A., Bossart, G., Carlin, K.P., Jensen, E.D., Smith, C.R., Andrews, G.A., Chavey, P.S., and Venn-Watson, S. (2012). Iron indices in bottlenose dolphins (Tursiops truncatus). Comp. Med. 62: 508–515.Search in Google Scholar

McBride, S.D. and Hemmings, A. (2005). Altered mesoaccumbens and nigro-striatal dopamine physiology is associated with stereotypy development in a non-rodent species. Behav. Brain Res. 159: 113–118, https://doi.org/10.1016/j.bbr.2004.10.014.Search in Google Scholar

McBride, S.D. and Hemmings, A. (2009). A neurologic perspective of equine stereotypy. J. Equine Vet. Sci. 29: 10–16, https://doi.org/10.1016/j.jevs.2008.11.008.Search in Google Scholar

McBride, S.D. and Parker, M.O. (2015). The disrupted basal ganglia and behavioural control: an integrative cross-domain perspective of spontaneous stereotypy. Behav. Brain Res. 276: 45–58, https://doi.org/10.1016/j.bbr.2014.05.057.Search in Google Scholar

McEwen, B.S. (2001). Plasticity of the hippocampus: adaptation to chronic stress and allostatic load. Ann. N. Y. Acad. Sci. 933: 265–277, https://doi.org/10.1111/j.1749-6632.2001.tb05830.x.Search in Google Scholar

McEwen, B.S. (2016). Stress-induced remodeling of hippocampal CA3 pyramidal neurons. Brain Res. 1645: 50–54, https://doi.org/10.1016/j.brainres.2015.12.043.Search in Google Scholar

McEwen, B.S. (2017). Neurobiological and systemic effects of chronic stress. Chron. Stress: 1–11.10.1177/2470547017692328Search in Google Scholar

McEwen, B.S., Bowles, N.P., Gray, J.D., Hill, M.N., Hunter, R.G., Karatsoreos, I.N., and Nasca, C. (2015). Mechanisms of stress in the brain. Nat. Neurosci. 18: 1353–1363, https://doi.org/10.1038/nn.4086.Search in Google Scholar

McEwen, B.S., Nasca, C., and Gray, J. (2016). Stress effects on neuronal structure: hippocampus, amygdala, and prefrontal cortex. Neuropsychopharmacology 41: 3–23, https://doi.org/10.1038/npp.2015.171.Search in Google Scholar

McLeod, T.M., Lopez-Figueroa, A.L., and Lopez-Figueroa, M.O. (2001). Nitric oxide, stress, and depression. Psychopharmacol. Bull. 35: 24–41.Search in Google Scholar

McPhee, M.E., and Carlstead, K. (2010). The importance of maintaining natural behaviors in captive mammals. In: Kleiman, D.G., Thompson, K.V., and Baer, C.K. (Eds.), Wild mammals in captivity: principles and techniques for zoo management, 2nd ed. University of Chicago Press, Chicago, IL, pp. 303–313.Search in Google Scholar

Meehan, C.L., Garner, J.P., and Mench, J.A. (2004). Environmental enrichment and development of cage stereotypy in Orange-winged Amazon parrots (Amazona amazonica). Dev. Psychobiol. 44: 209–218, https://doi.org/10.1002/dev.20007.Search in Google Scholar

Melendez, R.I., Gregory, M.L., Bardo, M.T., and Kaliva, P.W. (2004). Impoverished rearing environment alters metabotropic glutamate receptor expression and function in the prefrontal cortex. Neuropsychopharmacology 29: 1980–1987, https://doi.org/10.1038/sj.npp.1300507.Search in Google Scholar

Melleu, F.F., Pinheiro, M.V., Lino-de-Oliveira, C., and Marino-Neto, J. (2016). Defensive behaviors and porencephalic neurogenesis in pigeons (Columba livia) are affected by environmental enrichment in adulthood. Brain Struct. Funct. 221: 2287–2301, https://doi.org/10.1007/s00429-015-1043-6.Search in Google Scholar

Mendez, M.F., Shapira, J.S., and Miller, B.L. (2005). Stereotypical movements and frontotemporal dementia. Mov. Disord. 20: 742–745, https://doi.org/10.1002/mds.20465.Search in Google Scholar

Mikota, S.K. and Maslow, J.N. (2011). Tuberculosis at the human-animal interface: an emerging disease of elephants. Tuberculosis 91: 208–211, https://doi.org/10.1016/j.tube.2011.02.007.Search in Google Scholar

Miller, L.J., Chase, M.J., and Hacker, C.E. (2016). A comparison of walking rates between wild and zoo African elephants. J. Appl. Anim. Welfare Sci. 19: 271–279, https://doi.org/10.1080/10888705.2015.1137755.Search in Google Scholar

Mitra, R., Jadhav, S., McEwen, B.S., Vyas, A., and Chattarji, S. (2005). Stress duration modulates the spatiotemporal patterns of spine formation in the basolateral amygdala. Proc. Nat. Acad. Sci. USA 102: 9371–9376, https://doi.org/10.1073/pnas.0504011102.Search in Google Scholar

Miura, H., Qiao, H., and Ohta, T. (2002). Attenuating effects of the isolated rearing condition on increased brain serotonin and dopamine turnover elicited by novelty stress. Brain Res. 926: 10–17, https://doi.org/10.1016/s0006-8993(01)03201-2.Search in Google Scholar

Mizoguchi, K., Ishige, A., Aburada, M., and Tabira, T. (2003). Chronic stress attenuates glucocorticoid negative feedback: involvement of the prefrontal cortex and hippocampus. Neuroscience 119: 887–897, https://doi.org/10.1016/s0306-4522(03)00105-2.Search in Google Scholar

Møllgaard, K., Diamond, M.C., Bennett, E.L., Rosenzweig, M.R., and Lindner, B. (1971). Quantitative synaptic changes with differential experience in rat brain. Int. J. Neurosci. 2: 113–128, https://doi.org/10.3109/00207457109148764.Search in Google Scholar

Morfeld, K.A., Meehan, C.L., Hogan, J.N., and Brown, J.L. (2016). Assessment of body condition in African (Loxodonta africana) and Asian (Elephas maximus) elephants in North American zoos and management practices associated with high body condition scores. PloS One 11: e0155146, https://doi.org/10.1371/journal.pone.0155146.Search in Google Scholar

Morrens, M., Hulstijn, W., Lewi, P.J., De Hert, M., and Sabbe, B.G.C. (2006). Stereotypy in schizophrenia. Schizophr. Res. 84: 397–404, https://doi.org/10.1016/j.schres.2006.01.024.Search in Google Scholar

Mumtaz, F., Khan, M.I., Zubair, M., and Dehpour, A.R. (2018). Neurobiology and consequences of social isolation stress in animal model—a comprehensive review. Biomed. Pharmacother. 105: 1205–1222, https://doi.org/10.1016/j.biopha.2018.05.086.Search in Google Scholar

Murínová, J., Nataša, H., Magdaléna, C., and Igor, R. (2017). The evidence for altered BDNF expression in the brain of rats reared or housed in social isolation: a systematic review. Front. Behav. Neurosci. 11: 101, https://doi.org/10.3389/fnbeh.2017.00101.Search in Google Scholar

Nair, A. and Bonneau, R.H. (2006). Stress-induced elevation of glucocorticoids increases microglia proliferation through NMDA receptor activation. J. Neuroimmunol. 171: 72–85, https://doi.org/10.1016/j.jneuroim.2005.09.012.Search in Google Scholar

Naka, F., Shiga, T., Yaguchi, M., and Okado, N. (2002). An enriched environment increases noradrenaline concentration in the mouse brain. Brain Res. 924: 124–126, https://doi.org/10.1016/s0006-8993(01)03257-7.Search in Google Scholar

Narducci, R., Baroncelli, L., Sansevero, G., Begenisic, T., Prontere, C., Sale, A., Cenni, M.C., Berardi, N., and Maffei, L. (2018). Early impoverished environment delays the maturation of cerebral cortex. Sci. Rep. 8: 1187, https://doi.org/10.1038/s41598-018-19459-y.Search in Google Scholar

Neidl, R., Schneider, A., Bousiges, O., Majchrzak, M., Barbelivien, A., Barbelivien, A.P., Dorgans, K., Doussau, F., Loeffler, J.-P., Cassel, J.-C., et al.. (2016). Late-life environmental enrichment induces acetylation events and nuclear factor κB-dependent regulations in the hippocampus of aged rats showing improved plasticity and learning. J. Neurosci. 36: 4351–4361, https://doi.org/10.1523/jneurosci.3239-15.2016.Search in Google Scholar

Ngene, S., Okello, M.M., Mukeka, J., Muya, S., Njumbi, S., and Isiche, J. (2017). Home range sizes and space use of African elephants (Loxodonta africana) in the Southern Kenya and Northern Tanzania borderland landscape. Int. J. Biodivers. Conserv. 9: 9–26.10.5897/IJBC2016.1033Search in Google Scholar

Ngwenya, A., Patzke, N., Ihunwo, A.O., and Manger, P.R. (2011). Organisation and chemical neuroanatomy of the African elephant (Loxodonta africana) olfactory bulb. Brain Struct. Funct. 216: 403–416, https://doi.org/10.1007/s00429-011-0316-y.Search in Google Scholar

Nikolaev, E., Kaczmarek, L., Zhu, S.W., Winblad, B., and Mohammed, A.H. (2002). Environmental manipulation differentially alters c-Fos expression in amygdaloid nuclei following aversive conditioning. Brain Res. 957: 91–98, https://doi.org/10.1016/s0006-8993(02)03606-5.Search in Google Scholar

Nikolova, Y.S., Misquitta, K.A., Rocco, B.R., Prevot, T.D., Knodt, A.R., Ellegood, J., Voineskos, A.N., Lerch, J.P., Hariri, A.R., Sibille, E., et al.. (2018). Shifting priorities: highly conserved behavioral and brain network adaptations to chronic stress across species. Transl. Psychiatry 8: 26, https://doi.org/10.1038/s41398-017-0083-5.Search in Google Scholar

Nithianantharajah, J. and Hannan, A.J. (2006). Enriched environments, experience-dependent plasticity and disorders of the nervous system. Nat. Rev. Neurosci. 7: 697–709, https://doi.org/10.1038/nrn1970.Search in Google Scholar

Noda, K., Akiyoshi, H., Aoki, M., Shimada, T., and Ohashi, F. (2007). Relationship between transportation stress and polymorphonuclear cell functions of bottlenose dolphins, Tursiops truncates. J. Vet. Med. Sci. 69: 379–383, https://doi.org/10.1292/jvms.69.379.Search in Google Scholar

O’Corry-Crowe, G., Suydam, R., Quakenbush, L., Smith, T.G., Lydersen, C., Kovacs, K.M., Orr, J., Harwood, L., Litovka, D., and Ferrer, T. (2020). Group structure and kinship in beluga whale societies. Sci. Rep. 10: 1–21, https://doi.org/10.1038/s41598-020-67314-w.Search in Google Scholar

Oelschläger, H.H.A., Haas-Rioth, M., Fung, C., Ridgway, S.H., and Knauth, M. (2008). Morphology and evolutionary biology of the dolphin (Delphinus sp.) brain-MR imaging and conventional histology. Brain Behav. Evol. 71: 68–86, https://doi.org/10.1159/000110495.Search in Google Scholar

Oelschläger, H.H.A., and Oelschläger, J.S. (2009). Brains. In: Perrin, W.F., Würsig, B., and Thewissen, H. (Eds.), Encyclopedia of marine mammals, 2nd ed. Academic Press, London, UK, pp. 134–149.10.1016/B978-0-12-373553-9.00038-9Search in Google Scholar

Oelschläger, H.H.A., Ridgway, S.H., and Knauth, M. (2010). Cetacean brain evolution: dwarf sperm whale (Kogia sima) and common dolphin (Delphinus delphis)–an investigation with high-resolution 3D MRI. Brain Behav. Evol. 75: 33–62, https://doi.org/10.1159/000293601.Search in Google Scholar

Ohno, Y., Akune, Y., Inoshima, Y., and Kano, R. (2019). First isolation of voriconazole-resistant Candida albicans, C. tropicalis, and Aspergillus niger from the blowholes of bottlenose dolphins (Tursiops truncatus). J. Vet. Med. Sci. 81: 1628–1631, https://doi.org/10.1292/jvms.18-0749.Search in Google Scholar

Olijslagers, J.E., De Kloet, E.R., Elgersma, Y., Van Woerden, G.M., Joëls, M., and Karst, H. (2008). Rapid changes in hippocampal CA1 pyramidal cell function via pre- as well as postsynaptic membrane mineralocorticoid receptors. Eur. J. Neurosci. 27: 2542–2550, https://doi.org/10.1111/j.1460-9568.2008.06220.x.Search in Google Scholar

Park, S.Y., Lee, K., Cho, Y., Lim, S.R., Kwon, H., Han, J.E., and Kim, J.H. (2020). Emergence of third-generation cephalosporin-resistant Morganella morganii in a captive breeding dolphin in South Korea. Animals 10: 2052, https://doi.org/10.3390/ani10112052.Search in Google Scholar

Parolisi, R., Bruno, C., and Bonfanti, L. (2018). Humans and dolphins: decline and fall of adult neurogenesis. Front. Neurosci. 12: 497, https://doi.org/10.3389/fnins.2018.00497.Search in Google Scholar

Patel, P.D., Lopez, J.F., Lyons, D.M., Burke, S., Wallace, M., and Schatzberg, A.F. (2000). Glucocorticoid and mineralocorticoid receptor mRNA expression in squirrel monkey brain. J. Psychiatr. Res. 34: 383–392, https://doi.org/10.1016/s0022-3956(00)00035-2.Search in Google Scholar

Patzke, N., Olaleye, O., Haagensen, M., Hof, P.R., Ihunwo, A.O., and Manger, P.R. (2014). Organization and chemical neuroanatomy of the African elephant (Loxodonta africanus) hippocampus. Brain Struct. Funct. 216: 403–416, https://doi.org/10.1007/s00429-013-0587-6.Search in Google Scholar

Patzke, N., Spocter, M.A., Karlsson, K.Æ., Bertelsen, M.F., Haagensen, M., Chawana, R., Streicher, S., Kaswera, C., Gilissen, E., Alagaili, A.N., et al.. (2015). In contrast to many other mammals, cetaceans have relatively small hippocampi that appear to lack adult neurogenesis. Brain Struct. Funct. 220: 361–383, https://doi.org/10.1007/s00429-013-0660-1.Search in Google Scholar

Perrin, K.L., Nielson, S.S., Martinussen, T., and Bertelsen, M.F. (2021). Quantification and risk factor analysis of elephant endotheliotropic herpesvirus-haemorrhagic disease fatalities in Asian elephants Elephas maximus in Europe (1985-2017). J. Zoo Aquar. Res. 9: 8–13.Search in Google Scholar

Péter, Z., Oliphant, M.E., and Fernandez, T.V. (2017). Motor stereotypies: a pathophys, Available at: https://doi.org/10.3389/fnins.2017.00171.Search in Google Scholar

Pham, T.M., Winblad, B., Granholm, A.-C., and Mohammed, A.H. (2002). Environmental influences on brain neurotrophins in rats. Pharmcol. Biochem. Behav. 73: 167–175, https://doi.org/10.1016/s0091-3057(02)00783-9.Search in Google Scholar

Poirier, C. and Bateson, M. (2017). Pacing stereotypies in laboratory rhesus macaques: implications for animal welfare and the validity of neuroscientific findings. Neurosci. Biobehav. Rev. 83: 508–515, https://doi.org/10.1016/j.neubiorev.2017.09.010.Search in Google Scholar

Poole, J.H., and Granli, P. (2009). Mind and movement: meeting the interests of elephants. In: Forthman, D.L., Kane, L.F., and Waldau, P. (Eds.), An elephant in the room: the science and well being of elephants in captivity. Tufts University Cummings School of Veterinary Medicine’s Center for Animals and Public Policy, Medford, MA, pp. 2–21.Search in Google Scholar

Radley, J., Morilak, D., Viau, V., and Campeau, S. (2015). Chronic stress and brain plasticity: mechanisms underlying adaptive and maladaptive changes and implications for stress-related CNS disorders. Neurosci. Biobehav. Rev. 58: 79–91, https://doi.org/10.1016/j.neubiorev.2015.06.018.Search in Google Scholar

Rampon, C., Jiang, C.H., Dong, H., Tang, Y.-P., Lockhart, D.J., Schultz, P.G., Tsien, J.Z., and Hu, Y. (2000). Effects of environmental enrichment on gene expression in the brain. Proc. Nat. Acad. Sci. USA 97: 12880–12884, https://doi.org/10.1073/pnas.97.23.12880.Search in Google Scholar

Rasmuson, S., Olsson, T., Henriksson, B.G., Kelly, P.A.T., Holmes, M.C., Seckl, J.R., and Mohammed, A.H. (1998). Environmental enrichment selectively increases 5-HT1A receptor mRNA expression and binding in the rat hippocampus. Brain Res. Mol. Brain Res. 53: 285–290, https://doi.org/10.1016/s0169-328x(97)00317-3.Search in Google Scholar

Reidarson, T.H., García-Párraga, D., and Wiederhold, N.P. (2018). Marine mammal mycoses. In: Gulland, F.M.D., Dierauf, L.A., and Whitman, K.L. (Eds.), CRC handbook of marine mammal medicine. CRC Press, Boca Raton, FL, pp. 389–423.Search in Google Scholar

Reynolds, S. and Berridge, K. (2008). Emotional environments retune the valence of appetitive versus fearful functions in nucleus accumbens. Nat. Neurosci. 11: 423–425, https://doi.org/10.1038/nn2061.Search in Google Scholar

Riddle, H.S. and Stremme, C. (2011). Captive elephants: an overview. J. Threat. Taxa 3: 1826–1836, https://doi.org/10.11609/jott.o2620.1826-36.Search in Google Scholar

Robeck, T.R., O’Brien, J.K., and Atkinson, S. (2018). Reproduction. In: Dierauf, L.A., and Gulland, F.M.D. (Eds.), CRC handbook of marine mammal medicine. CRC Press, Boca Raton, FL, pp. 169–207.10.1201/9781420041637.ch11Search in Google Scholar

Rose, N.A. and Parsons, E.C.M. (2019). The case against marine mammals in captivity, 5th ed. Animal Welfare Institute and World Animal Protection, Washington, DC.Search in Google Scholar

Rosen, D.A.S., and Worthy, G.A.J. (2018). Nutrition and energetics. In: Dierauf, L.A., and Gulland, F.M.D. (Eds.), CRC handbook of marine mammal medicine. CRC Press, Boca Raton, FL, pp. 309–335.Search in Google Scholar

Rosenzweig, M.R. and Bennett, E.L. (1969). Effects of differential environments on brain weights and enzyme activities in gerbils, rats, and mice. Dev. Psychobiol. 2: 87–95, https://doi.org/10.1002/dev.420020208.Search in Google Scholar

Rosenzweig, M.R. and Bennett, E.L. (1972). Cerebral changes in rats exposed individually to an enriched environment. J. Comp. Physiol. Psychol. 80: 304–313, https://doi.org/10.1037/h0032978.Search in Google Scholar

Roth, G. and Dicke, U. (2005). Evolution of the brain and intelligence. Trends Cognit. Sci. 9: 250–257, https://doi.org/10.1016/j.tics.2005.03.005.Search in Google Scholar

Sapolsky, R.M., Romero, L.M., and Munck, A.U. (2000). How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr. Rev. 21: 55–89, https://doi.org/10.1210/edrv.21.1.0389.Search in Google Scholar

Scaccianoce, S., Del Bianco, P., Paolone, G., Caprioli, D., Modafferi, A.M.E., Nencini, P., and Badiani, A. (2006). Social isolation selectively reduces hippocampal brain-derived neurotrophic factor without altering plasma corticosterone. Behav. Brain Res. 168: 323–325, https://doi.org/10.1016/j.bbr.2005.04.024.Search in Google Scholar

Schaftenaar, W., Reid, C., Martina, B., Fickel, J., and Osterhaus, A.D.M.E. (2010). Nonfatal clinical presentation of elephant endotheliotropic herpes virus discovered in a group of captive Asian elephants (Elephas maximus). J. Zoo Wildl. Med. 41: 626–632, https://doi.org/10.1638/2009-0217.1.Search in Google Scholar

Scharf, I., Stoldt, M., Libbrecht, R., Höpfner, A.L., Jongepier, E., Kever, M., and Foitzik, S. (2021). Social isolation causes downregulation of immune and stress response genes and behavioural changes in a social insect. Mol. Ecol 30: 2378–2389, https://doi.org/10.1111/mec.15902.Search in Google Scholar

Schedlowski, M. and Schmidt, R.E. (1996). Streß und Immunsystem [Stress and the immune system]. Sci. Nat. 83: 214–220, https://doi.org/10.1007/bf01143326.Search in Google Scholar

Scheibel, A.B., Conrad, T., Perdue, S., Tomiyasu, U., and Wechsler, A. (1990). A quantitative study of dendrite complexity in selected areas of the human cerebral cortex. Brain Cognit. 12: 85–101, https://doi.org/10.1016/0278-2626(90)90006-a.Search in Google Scholar

Schmid, J. (1995). Behavioural effects of keeping Circus elephants in Paddocks. In: Spooner, N.G., and Whitear, J.A. (Eds.), Proceedings of the eighth UK elephant workshop. North of England Zoological Society, Chester, UK, pp. 19–27.Search in Google Scholar

Schmid, J., Heisterman, M., Gansloßer, U., and Hodges, J.K. (2001). Introduction of foreign female Asian elephants (Elephas maximus) into an existing group: behavioral reactions and changes in cortisol levels. Anim. Welf. 10: 357–372.Search in Google Scholar

Schneider, J.S., Lee, M.H., Anderson, D.W., Zuck, L., and Lidsky, T.I. (2001). Enriched environment during development is protective against lead-induced neurotoxicity. Brain Res. 896: 48–55, https://doi.org/10.1016/s0006-8993(00)03249-2.Search in Google Scholar

Schubert, M.I., Porkess, M.V., Dashdorj, N., Fone, K.C.F., and Auer, D.P. (2009). Effects of social isolation rearing on the limbic brain: a combined behavioral and magnetic resonance imaging volumetry study in rats. Neuroscience 159: 21–30, https://doi.org/10.1016/j.neuroscience.2008.12.019.Search in Google Scholar

Schulkin, J. (2011). Evolutionary conservation of glucocorticoids and corticotropin releasing hormone: behavioral and physiological adaptations. Brain Res. 1392: 27–46, https://doi.org/10.1016/j.brainres.2011.03.055.Search in Google Scholar

Seeber, P.A., Morrison, T., Ortega, A., East, M.L., Greenwood, A.D., and Czirják, C.A. (2020). Immune differences in captive and free-ranging zebras (Equus zebra and E. quagga). Mamm. Biol. 100: 155–164, https://doi.org/10.1007/s42991-020-00006-0.Search in Google Scholar

Segovia, G., del Arco, A., and Mora, F. (2009). Environmental enrichment, prefrontal cortex, stress, and aging of the brain. J. Neural. Transm. 116: 1007–1016, https://doi.org/10.1007/s00702-009-0214-0.Search in Google Scholar

Seid, M.A. and Junge, E. (2016). Social isolation and brain development in the ant Camponotus floridanus. Sci. Nat. 103: 42, https://doi.org/10.1007/s00114-016-1364-1.Search in Google Scholar

Serra, M., Sanna, E., Mostallino, M.C., and Biggio, G. (2007). Social isolation stress and neuroactive steroids. Eur. Neuropsychopharmacol 17: 1–11, https://doi.org/10.1016/j.euroneuro.2006.03.004.Search in Google Scholar

Sforzo, G.A., Seeger, T.F., Pert, C.B., Pert, A., and Dotson, C.O. (1986). In vivo opioid receptor occupation in the rat brain following exercise. Med. Sci. Sports Exerc. 18: 380–384, https://doi.org/10.1249/00005768-198608000-00003.Search in Google Scholar

Sharman, D.F., Mann, S.P., Fry, J.P., Banns, H., and Stephens, D.B. (1982). Cerebral dopamine metabolism and stereotyped behaviour in early-weaned piglets. Neuroscience 7: 1937–1944, https://doi.org/10.1016/0306-4522(82)90008-2.Search in Google Scholar

Shin, L. and Liberzon, I. (2010). The neurocircuitry of fear, stress, and anxiety disorders. Neuropsychopharmacology 35: 169–191, https://doi.org/10.1038/npp.2009.83.Search in Google Scholar

Shipman, M.L. and Green, J.T. (2020). Cerebellum and cognition: does the rodent cerebellum participate in cognitive functions? Neurobiol. Learn. Mem. 170: 106996, https://doi.org/10.1016/j.nlm.2019.02.006.Search in Google Scholar

Shukla, V., and Sadananda, M. (2021). Social isolation-induced effects on male-specific courtship behaviours and dendritic architecture in associative forebrain areas in Zebra finches (Taeniopygia guttata). Avian Biol. Res 14: 59–68, https://doi.org/10.1177/1758155921997982.Search in Google Scholar

Singer, H.S. (2013). Motor control, habits, complex motor stereotypies, and Tourette syndrome. Ann. N.Y. Acad. Sci. 1304: 22–31, https://doi.org/10.1111/nyas.12281.Search in Google Scholar

Sirevaag, A.M. and Greenough, W.T. (1985). Differential rearing effects on rat visual cortex synapses. II. Synaptic morphometry. Dev. Brain Res. 19: 215–226, https://doi.org/10.1016/0165-3806(85)90193-2.Search in Google Scholar

Skórzewska, A., Lehner, M., Wisłowska-Stanek, A., Turzyńskaa, D., Sobolewskaa, A., Krząścik, P., and Płaźnik, A. (2015). GABAergic control of the activity of the central nucleus of the amygdala in low- and high-anxiety rats. Neuropharmacology 99: 566–576, https://doi.org/10.1016/j.neuropharm.2015.08.039.Search in Google Scholar

Smaers, J.B., Turner, A.H., Gómez-Robles, A., and Sherwood, C.C. (2018). A cerebellar substrate for cognition evolved multiple times independently in mammals. eLife 7: e35696, https://doi.org/10.7554/eLife.35696.Search in Google Scholar

Smith, B.P. and Litchfield, C.A. (2010). An empirical case study examining effectiveness of environmental enrichment in two captive Australian sea lions (Neophoca cinerea). J. Appl. Anim. Welfare Sci. 13: 103–122, https://doi.org/10.1080/10888700903371863.Search in Google Scholar

Spoon, T. and Romano, T. (2012). Neuroimmunological response of beluga whales (Delphinapterus leucas) to translocation and a novel social environment. Brain Behav. Immun. 26: 122–131, https://doi.org/10.1016/j.bbi.2011.08.003.Search in Google Scholar

Stoskopf, M.K. (2015). Environmental diseases of marine mammals. In: Line, S. and Moses, M.A. (Eds.). Merck veterinary manual online. Kenilworth Merck and Co, New Jersey, Available at: https://www.merckvetmanual.com/exotic-and-laboratory-animals/marine-mammals/environmental-diseases-of-marine-mammals# (Accessed 31 March 2021).Search in Google Scholar

Strand, D.A., Utne-Palm, A.C., Jakobsen, P.J., Braithwaite, V.A., Jensen, K.H., and Salvanes, A.G.V. (2010). Enrichment promotes learning in fish. Mar. Ecol. Prog. Ser. 412: 273–282, https://doi.org/10.3354/meps08682.Search in Google Scholar

Swaisgood, R.R., White, A.M., Zhou, X., Zhang, H., Zhang, G., Wei, R., Hare, V.J., Tepper, E.M., and Lindburg, D.G. (2001). A quantitative assessment of the efficacy of an environmental enrichment programme for giant pandas. Anim. Behav. 61: 447, https://doi.org/10.1006/anbe.2000.1610.Search in Google Scholar

Taylor, V.J. and Poole, T.B. (1998). Captive breeding and infant mortality in Asian elephants: a comparison between twenty western zoos and three eastern elephant centers. Zoo Biol. 17: 311–332, https://doi.org/10.1002/(sici)1098-2361(1998)17:4<311::aid-zoo5>3.0.co;2-c.10.1002/(SICI)1098-2361(1998)17:4<311::AID-ZOO5>3.0.CO;2-CSearch in Google Scholar

Temudo, T., Oliveira, P., Santos, M., Dias, K., Vieira, J., Moreira, A., Calado, E., Carrilho, I., Oliveira, G., Levy, A., et al.. (2007). Stereotypies in Rett syndrome: analysis of 83 patients with and without detected MECP2 mutations. Neurology 68: 1183–1187, https://doi.org/10.1212/01.wnl.0000259086.34769.78.Search in Google Scholar

Therrien, C.L., Gaster, L., Cunningham-Smith, P., and Manire, C.A. (2007). Experimental evaluation of environmental enrichment of sea turtles. Zoo Biol. 26: 407–416, https://doi.org/10.1002/zoo.20145.Search in Google Scholar

Thurmond, V.A. (2001). The point of triangulation. J. Nurs. Scholarsh. 33: 253–258, https://doi.org/10.1111/j.1547-5069.2001.00253.x.Search in Google Scholar

Turner, C.A. and Lewis, M.H. (2003). Environmental enrichment: effects on stereotyped behavior and neurotrophin levels. Physiol. Behav. 80: 259–266, https://doi.org/10.1016/j.physbeh.2003.07.008.Search in Google Scholar

Turner, C.A., Lewis, M.H., and King, M.A. (2003). Environmental enrichment: effects on stereotyped behavior and dendritic morphology. Dev. Psychobiol. 43: 20–27, https://doi.org/10.1002/dev.10116.Search in Google Scholar

Turner, C.A., Yang, M.C., and Lewis, M.H. (2002). Environmental enrichment: effects on stereotyped behavior and regional neuronal metabolic activity. Brain Res. 938: 15–21, https://doi.org/10.1016/s0006-8993(02)02472-1.Search in Google Scholar

Tynan, T.J., Naicker, S., Hinwood, M., Nalivaiko, E., Buller, K.M., Pow, D.V., Day, T.A., and Walker, F.R. (2010). Chronic stress alters the density and morphology of microglia in a subset of stress-responsive brain regions. Brain Behav. Immun. 24: 1058–1068, https://doi.org/10.1016/j.bbi.2010.02.001.Search in Google Scholar

Ugaz, R.C., Valdez, R.A., Romano, M.C., and Galindo, F. (2013). Behavior and salivary cortisol of captive dolphins (Tursiops truncatus) kept in open and closed facilities. J. Vet. Behav. 8: 285–290, https://doi.org/10.1016/j.jveb.2012.10.006.Search in Google Scholar

Van Bressem, M.-F., Van Waerebeek, K., and Duignan, P.J. (2018). Epidemiology of tattoo skin disease in captive common bottlenose dolphins (Tursiops truncatus): are males more vulnerable than females? J. Appl. Anim. Welfare Sci. 21: 305–315, https://doi.org/10.1080/10888705.2017.1421076.Search in Google Scholar

van Praag, H., Kempermann, G., and Gage, F.H. (2000). Neural consequences of environmental enrichment. Nat. Rev. Neurosci. 1: 191–198, https://doi.org/10.1038/35044558.Search in Google Scholar

Vance, E.A., Archie, E.A., and Moss, C.J. (2009). Social networks in African elephants. Comput. Math Organ. Theory 15: 273, https://doi.org/10.1007/s10588-008-9045-z.Search in Google Scholar

Varman, D.R., Marimuthu, G., and Rajan, K.E. (2012). Environmental enrichment exerts anxiolytic effects in the Indian field mouse (Mus booduga). Appl. Anim. Behav. Sci. 136: 167–173, https://doi.org/10.1016/j.applanim.2011.12.003.Search in Google Scholar

Veena, J., Srikumar, B.N., Mahati, K., Bhagya, V., Raju, T.R., and Shankaranarayana Rao, B.S. (2009). Enriched environment restores hippocampal cell proliferation and ameliorates cognitive deficits in chronically stressed rats. J. Neurosci. Res. 87: 831–843, https://doi.org/10.1002/jnr.21907.Search in Google Scholar

Venn-Watson, S.K., Benham, C., Carlin, K., DeRienzo, D., and St. Leger, J. (2012). Hemochromatosis and fatty liver disease: building evidence for insulin resistance in bottlenose dolphins (Tursiops truncatus). J. Zoo Wildl. Med. 43: S35–S47, https://doi.org/10.1638/2011-0146.1.Search in Google Scholar

Venn-Watson, S.K., Smith, C.R., Stevenson, S., Parry, C., Daniels, R., Jensen, E., Cendejas, V., Balmer, B., Janech, M., Neely, B.A., et al.. (2013). Blood-based indicators of insulin resistance and metabolic syndrome in bottlenose dolphins (Tursiops truncatus). Front. Endocrinol. 4: 136, https://doi.org/10.3389/fendo.2013.00136.Search in Google Scholar

Volkmar, F.R. and Greenough, W.T. (1972). Rearing complexity affects branching of dendrites in the visual cortex of the rat. Science 176: 1445–1447, https://doi.org/10.1126/science.176.4042.1445.Search in Google Scholar

Vyas, A., Mitra, R., Shankaranarayana Rao, B.S., and Chattarji, S. (2002). Chronic stress induces contrasting patterns of dendritic remodeling in hippocampal and amygdaloid neurons. J. Neurosci. 22: 6810–6818, https://doi.org/10.1523/jneurosci.22-15-06810.2002.Search in Google Scholar

Vyas, S., Rodrigues, A.J., Silva, J.M., Tronche, F., Almeida, O.F., Sousa, N., and Sotiropoulos, I. (2016). Chronic stress and glucocorticoids: from neuronal plasticity to neurodegeneration. Neural Plast. 2016: ID6391686, https://doi.org/10.1155/2016/6391686.Search in Google Scholar

Wall, J., Wittemyer, G., Klinkenberg, B., LeMay, V., and Douglas-Hamilton, I. (2013). Characterizing properties and drivers of long distance movements by elephants (Loxodonta africana) in the Gourma. Mali. Biol. Cons 157: 60–68, https://doi.org/10.1016/j.biocon.2012.07.019.Search in Google Scholar

Walsh, R.N. (1981). Effects of environmental complexity and deprivation on brain anatomy and histology: a review. Int. J. Neurosci. 12: 33–51, https://doi.org/10.3109/00207458108990671.Search in Google Scholar

Warling, A., Uchida, R., Shin, H., Dodelson, C., Garcia, M.E., Shea-Shumsky, N.B., Svirsky, S., Pothast, M., Kelley, H., Schumann, C.M., et al.. (2020). Putative dendritic correlates of chronic traumatic encephalopathy: a preliminary quantitative Golgi exploration. J. Comp. Neurol. 529: 1308–1326, https://doi.org/10.1002/cne.25022.Search in Google Scholar

Wilkes, B.J. and Lewis, M.H. (2018). The neural circuitry of restricted repetitive behavior: magnetic resonance imaging in neurodevelopmental disorders and animal models. Neurosci. BioBehav. Rev. 92: 152–171, https://doi.org/10.1016/j.neubiorev.2018.05.022.Search in Google Scholar

Wrona, D. (2006). Neural-immune interactions: an integrative view of the bidirectional relationship between the brain and immune systems. J. Neuroimmunol. 172: 38–58, https://doi.org/10.1016/j.jneuroim.2005.10.017.Search in Google Scholar

Zuckerman, J.M. and Assimos, D.G. (2009). Hypocitraturia: pathophysiology and medical management. Rev. Urol. 11: 134–144.Search in Google Scholar

Received: 2021-07-26
Accepted: 2021-09-02
Published Online: 2021-09-16

© 2021 Bob Jacobs et al., published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.