Studies of aphasic patients and postmortem observations resulted in the emergence of two fundamental statements about brain organization for language processing (Broca, 1865; Lichtheim, 1885; Geschwind, 1965; Wernicke, 1974): hemispheric lateralization (i.e., interhemispheric organization) and regional specialization (i.e., intrahemispheric organization). Traditional neurological models based on clinical data (i.e., analysis of deficits-lesion relationships) described two language poles located within the dominant hemisphere: an anterior or frontal pole involved in language production and a posterior (i.e., temporo-parietal) pole involved in language comprehension. According to these models, language depends on critical, ‘eloquent’ regions such as Broca’s and Wernicke’s areas, their damage inducing severe and irrevocable language deficits such as aphasia. Over the years, many authors (Démonet and Thierry, 2001; Poeppel and Hickok, 2004; Poeppel et al., 2012) have pointed out serious limitations to this model. For instance, impairment of nonessential/additional regions involved in language (‘auxiliary language regions’) may alter language functions because of their direct connections with the ‘essential language regions’ (Démonet and Thierry, 2001). Furthermore, as suggested by Poeppel et al. (2012), biological, linguistic, and psychological aspects of language are underspecified in the classical model (Poeppel and Hickok, 2004; Démonet et al., 2005; Price, 2010). This means that predictions about deficits-lesion relationships based on such models may be inaccurate (Démonet et al., 2005). Overall, the classical neuropsychological model implies that language is a rigid, inflexible, and monolithic function (Démonet and Thierry, 2001; Démonet et al., 2005).
More recently, the advent of neuroimaging methods has given us a broader perspective on language representation (Jallon, 1997; Baciu et al., 1999, 2005; Price, 2012). Neuroimaging methods have provided more precise function-to-structure mapping (Price, 2012) and suggested that language operations are supported by a large, flexible cerebral network (i.e., including areas located outside the classical language regions) distributed within and across hemispheres (Vigneau et al., 2011; Price, 2012). Moreover, the concept of hemispheric dominance has also evolved from dichotomized (left vs. right) processing toward the idea that continuous participation of both hemispheres is the norm (Jung-Beeman, 2005; Berl et al., 2014). According to this idea, the hemispheres interact continuously (Banich, 1995; Gazzaniga, 2000; Bloom and Hynd, 2005; van der Knaap and van der Ham, 2011; Perrone-Bertolotti et al., 2013a,b).
Several authors have recently reconsidered functional anatomy and proposed a hodotopical approach of the neural organization of language (De Benedictis and Duffau, 2011; Duffau et al., 2014). According to this approach, the central nervous system is considered as an integrated, wide, plastic network made up of cortical functional epicenters (i.e., ‘topic organization’) connected by both local and much longer white matter fibers (i.e., ‘hodological organization’; De Benedictis and Duffau, 2011). According to this view of brain organization, cognitive functioning reflects the processing of parallel streams of information, which are dynamically modulated across interactive, multimodal, widely distributed circuits (including cortico-cortical and cortico-subcortical circuits; Davies et al., 1998). This new approach is supported by recent clinical observations demonstrating that it is possible to safely remove regions traditionally considered inoperable without inducing permanent deficits (Duffau, 2010). Using electrical stimulation during surgery, Duffau (2012) showed that Broca’s area was not the area responsible for word production; in fact, word production was underpinned by a more complex network involving the ventral premotor cortex, the supramarginal gyrus, and the lateral part of the superior longitudinal fasciculus (which connects these two areas). This network also includes the anterior insula and the putamen (connected to the supramarginal gryus and ventral premotor cortex by vertical fibers). Such conceptual and methodological developments participate to refine the understanding of neural foundations of brain-language processing. Overall, this view conceives language representation as a dynamic, modular, and multifactorial phenomenon.
The pathological changes in functioning following a brain lesion may be considered an essential source of information about language organization and its modulation by diverse variables. Specifically, both focal and refractory epilepsy offer a unique opportunity to explore the cerebral plasticity of language. Neurosurgery is the only treatment capable of suppressing seizures during focal drug-resistant epilepsy (Noachtar and Borggraefe, 2009; Wrench et al., 2011) and typically consists of resecting, inactivating, or disconnecting the ‘epileptogenic zone’ or EZ (i.e., the area of cortex that is necessary and sufficient to initiating seizures in a particular patient; Rosenow and Lüders, 2001; Luders et al., 2006). Both focal and refractory epilepsy enable the evaluation of language organization before surgery (by a chronic mechanism induced by the epilepsy) and after surgery (by an acute mechanism induced by EZ removal or disconnection). This review presents several patterns of reorganization associated with these two mechanisms and the factors modulating them to provide a new insight into language plasticity and models of the neural organization and reorganization of language processing and the potential consequences for clinical practice.
Epilepsy and language plasticity as assessed by neuroimaging methods
Cerebral plasticity is a continuous process that allows remodeling of brain networks over the short, medium, and long term (Duffau, 2006). Generally speaking, plasticity is significant in phylogeny, ontogeny, and aging (Duffau, 2008). This notion refers to the broad concept of homeostasis applied to brain (Turrigiano and Nelson, 2000). Neural plasticity optimizes (Paillard, 1976) and stabilizes (Turrigiano and Nelson, 2004) cognitive functions. Neural changes that take place during development can be considered ‘natural plasticity,’ the basis of learning and memory (Cruikshank and Weinberger, 1996; Nobre and Plunkett, 1997; Neville and Bavelier, 1998). Brain lesions generate another type of plasticity – the pathologically induced plasticity (Benton and Tranel, 2000; Grafman, 2000). Both natural and pathologically induced plasticity are supported by similar neural mechanisms. Homeostatic synaptic plasticity is heavily involved in both natural and pathological plasticity. In fact, experimental findings suggest that the maintenance of an appropriate level of neural activity is determined by a set of homeostatic mechanisms that dynamically adjust synaptic strengths to promote stability (Turrigiano and Nelson, 2004; Turrigiano, 2007).
Epilepsy is a neurological disorder characterized by repeated spontaneous seizures, which start and end abruptly and may be associated with loss of consciousness (Jallon, 1997; Fisher et al., 2005). As mentioned in the previous section, refractory epilepsy represents an excellent neurological model for the assessment of cerebral reorganization. Approximately 35% of patients suffering from focal epilepsy have refractory epilepsy for which curative surgery may be considered (see Noachtar et al., 2003; Kahane, 2004 for a review of eligibility criteria for epilepsy surgery) if the EZ can be identified clearly and removed safely (Morris et al., 2008). Major functional regions must be spared to prevent postoperative cognitive deficits (see Hamberger, 2007 for a review). After clinical exploration and video-EEG recording of seizures, an assessment of hemispheric dominance with respect to language and memory is necessary before surgery can be planned (Bookheimer, 2007). The likelihood of atypical representation [bilateral or right-hemisphere (RH) dominance] of these functions is high in epilepsy patients (for a review, see Goldmann and Golby, 2005 and the next section for details).
Classically, the Wada test (intra-arterial amobarbital procedure) is used to determine the hemispheric dominance for language and evaluate the risk of postoperative amnesic syndrome in the case of temporal lobe epilepsy (TLE; Wada et al., 1975; Hamberger and Cole, 2011; Sharan et al., 2011). The Wada test is an invasive procedure; temporary anesthesia is induced in one cerebral hemisphere by the injection of sodium amobarbital (or a similar agent) into the internal carotid artery (Wada and Rasmussen, 1960). The exact procedure and scoring system vary among centers, but classically hemispheric anesthesia is verified by induced contralateral hemiplegia (see Hamberger and Cole, 2011 for more details). Language lateralization is assessed by means of language protocols that vary between centers. The protocols used comprise several tasks such as naming, repetition, language comprehension, reading, and automatic speech. Wada test results are often inconclusive (Binder, 1996; Bernal and Ardila, 2013; see also Janecek et al., 2013) and the test has limitations and drawbacks (Paola et al., 2004; Loddenkemper et al., 2008). According to a recent survey, the Wada test is no longer the first choice method for the assessment of hemispheric dominance in clinical practice (Baxendale and Thompson, 2010). Its main use is in patients with TLE. As the use of noninvasive functional magnetic resonance imaging (fMRI) to assess the hemispheric specialization of cognitive functions becomes more widespread in clinical practice, the use of the Wada test is likely to reduce further in the coming years.
Additionally, invasive functional mapping of the dominant hemisphere using electrical cortical stimulation (ECS) is carried out before and during surgery (Ojemann et al., 1989; Berger and Ojemann, 1992; Duffau et al., 1999; Zhang et al., 2013). ECS is used as a supplementary step to ensure the precise delimitation of language areas because of the increased intraindividual variability of language cortical representation (Ojemann and Whitaker, 1978). ECS is more likely to be used when the EZ is close to classical language areas in the language-dominant hemisphere. An important advantage of ECS is that it reveals essential language regions; the disadvantage is that this information can only be obtained for a small fraction of the brain.
Overall, although both the Wada test and ECS are considered gold standard methods for invasive presurgical and perisurgical mapping of language, they have limitations and drawbacks that explain why methods involving noninvasive techniques such as fMRI, have been developed (Binder, 1996; Bahn et al., 1997; Benson et al., 1999; Springer et al., 1999; Lehericy et al., 2000; Richardson, 2010; Rosazza et al., 2013). Indeed, fMRI can be used to detect atypical hemispheric language dominance of language and provides results consistent with the Wada test (Baciu et al., 2001, 2005; Woermann et al., 2003; Benke et al., 2006). fMRI has significant advantages over the Wada test; for instance, it can highlight dissociations between expressive and receptive areas across hemispheres (Baciu et al., 2003; Thivard et al., 2005; Lee et al., 2008; Perrone-Bertolotti et al., 2012a), which are difficult or impossible to unpick with the Wada test (Lee et al., 2008) or ECS. This suggests that neuroimaging noninvasive methods have a crucial role in mapping language (Hund-Georgiadis et al., 2001; Wellmer et al., 2008; Abbott et al., 2010). Furthermore, fMRI enables data from epileptic patients to be compared with that of healthy controls, providing a more comprehensive and more representative picture of brain-language relationships. Importantly, fMRI evaluation has demonstrated high degree of concordance with what is known of language representation at the theoretical level (Rodin et al., 2013), although a considerable degree of individual variability could be noticed, attesting to the clinical importance of these methods as a means of determining language localization in individual patients (Hamberger and Cole, 2011).
Nevertheless, it is important to remember that the Wada test and fMRI do not provide identical information (Loring et al., 2014). Whereas fMRI can reveal the cerebral correlates of a given function, the Wada test is a better indicator of whether one specific hemisphere is necessary or essential for a given function.
Despite its undeniable advantages, several methodological fMRI issues should be considered in epilepsy patients. For instance, it is not completely clear how changes in the hemodynamic response function (HRF) are affected by the ongoing subcritical epileptic activity, as suggested by several studies (Baumgartner et al., 1998; Federico et al., 2005; Mäkiranta et al., 2005; Hawco et al., 2007; Moeller et al., 2008). The HRF in epileptic seizures may have different shapes and higher variability compared with the HRF for exogenous stimuli and may be slower for negative than for positive blood oxygenation level-dependent (BOLD) signals (Bagshaw et al., 2004). Long-lasting hemodynamic changes may occur several minutes before seizures (Baumgartner et al., 1998; Federico et al., 2005; Mäkiranta et al., 2005).
Additionally, the routine use of fMRI in the clinical environment is not systematically accompanied by the recording of subjects’ behavioral responses during task. This constitutes a serious limit because it prevents from corroborating the fMRI activation with the behavioral and cognitive scores obtained in the scanner and during the neuropsychological assessment, respectively. In a recent case report study (Perrone-Bertolotti et al., 2012a), we have shown that the correlation between the behavioral, neuropsychological, and cerebral scores allowed us to identify several patterns of language reorganization according to task and surgery; more importantly, it permitted us to identify the patterns of reorganization associated with efficient recovery of language.
Furthermore, other limitations of fMRI should be acknowledged in this framework. fMRI provides activation related to a task, but this activation does not necessarily mean that the activated region is essential for language. Indeed, several studies based on correlation between fMRI and ECS results showed a lack of reliability of functional neuroimaging (Giussani et al., 2010). Moreover, a major limitation when using fMRI alone is that this method maps cortical regions but no information is provided on the subcortical white matter. The assessment of white matter connectivity is essential within language networks. Indeed, in a recent study, De Benedictis and Duffau (2011) focused on the temporo-parieto-occipital junction, a complex region involved in many high-level cognitive functions, including language. These authors showed that a detailed anatomofunctional awareness of the white matter architecture in this area is mandatory when approaching intrinsic brain lesions to optimize surgical results and to minimize the postoperative morbidity. Moreover, Duffau et al. (2014) shows that white matter connectivity constitutes an important limitation of brain plasticity; it could explain the lack of recovery in patients with subcortical lesions (see also Ius et al., 2011). A recent review on recovery after stroke (Kiran, 2012) showed that changes in white matter connectivity modulates recovery in poststroke aphasia. Kiran (2012) suggests that inferior frontal gyrus (IFG) and middle temporal gyrus are ‘hub’ regions highly connected to other brain regions and the degree of language recovery is dependent on the structural integrity between these ‘hubs.’ Additionally, by using direct electrical stimulation in patients with gliomas, Papagno et al. (2011) showed the critical role of subcortical pathways as part of the neural circuits involved in language and more specifically in their study (i.e., in object naming). These authors highlighted the importance of subcortical connectivity in shaping cortical reorganization following perturbations of normal language function. In sum, the cortical mapping with fMRI shows limits to robustly map language in patients. Consequently, the information on the grey matter activation should be associated with information on the white matter connectivity between the activated regions. Indeed, this double approach – cortical and subcortical mapping – may limit the risk of either (a) language impairment after brain resection of cerebral areas appearing as activated with fMRI or (b) ineffective surgery with the maintenance of seizures if the patients are not selected for extensive surgery because of false-positive fMRI activation. All these elements should be considered when interpreting fMRI results in epilepsy patients.
Patterns of language reorganization
To identify the various patterns of reorganization, there are different methods to quantify the degree of hemispheric lateralization (see Seghier, 2008; see Figure 1). The typical left-hemisphere (LH) language lateralization (see Figure 2) may be modulated in neurological condition (Rasmussen and Milner, 1977; Springer et al., 1999), and language representation may be atypical in patients with disorders such as epilepsy (Billingsley et al., 2001; Adcock et al., 2003; Sabbah et al., 2003; Berl et al., 2005, 2014; Brázdil et al., 2005; Goldmann and Golby, 2005; Thiel et al., 2006; Lee et al., 2008; Rosenberger et al., 2009; Yu et al., 2011; Dijkstra and Ferrier, 2013).
Different patterns of language organization are described in the literature (Goldmann and Golby, 2005; Dijkstra and Ferrier, 2013; Berl et al., 2014). Here, we consider (see Figure 3) three atypical patterns of hemispheric lateralization. One atypical pattern is the RH dominance which suggests that language networks do ‘shift’ from the LH to the RH, usually between homologous regions (Gaillard et al., 2002; Thivard et al., 2005; Dijkstra and Ferrier, 2013; Berl et al., 2014). This pattern may be attributed to the removal or the reduction of normal transcallosal inhibition (Chiarello and Maxfield, 1996; Bloom and Hynd, 2005; van der Knaap and van der Ham, 2011) responsible for the LH dominance. In an experiment relevant to this hypothesis, Thiel et al. (2006) showed that the activation of right IFG increased after the suppression of activity in Broca’s area. Evidence for RH language abilities comes from observations of children without language impairment (Vining et al., 1997; Devlin et al., 2003; Loddenkemper et al., 2003) after left hemispherectomy (Hertz-Pannier et al., 2002; Liégeois et al., 2008) and in adults suffering from LH lesions (Krieg et al., 2013).
The second atypical pattern of language organization is crossed lateralization within hemispheres (Figure 3), indicating a partial ‘shift’ of classical language regions to the RH (Kurthen, 1992; Baciu et al., 2003; Ries et al., 2004; Dijkstra and Ferrier, 2013). The Wada test results from 148 epileptic patients showed that receptive and productive language areas were differently affected during the test, indicating that expressive language can be supported by one hemisphere, whereas the other hemisphere supports receptive language or vice versa (Kurthen, 1992).
fMRI has also provided evidence for the existence of this pattern (Baciu et al., 2003; Lee et al., 2008). Ries et al. (2004) reported the case of a patient with focal left TLE who showed right lateralization of temporal regions (near the homologous regions of the EZ), although the frontal regions remained left lateralized. Thivard et al. (2005) observed similar patterns in a group of TLE patients; similarly, Baciu et al. (2003) reported the case of a patient with left frontal focal epilepsy with right frontal and left temporal lateralization. Taken together, these results suggest that the language system is based on interhemispheric and intrahemispheric connections (see, for instance, Stephan et al., 2005, 2007). In patients with an EZ located in the vicinity of a language area of the dominant hemisphere, there may be a local reduction in interhemispheric inhibition and a corresponding increase of activity in the homologous region in the nondominant hemisphere. This suggests that language dominance should be assessed at regional rather than hemispheric level, a point recently emphasized by Berl et al. (2014).
The third atypical pattern presented in Figure 3 is the intrahemispheric reorganization based on the recruitment of cortical regions in the ‘injured’ dominant hemisphere for language, that are not classically devoted to language. Data from epilepsy patients undergoing invasive electrical stimulation mapping (Ojemann et al., 1989) and noninvasive fMRI (Mbwana et al., 2009; Perrone-Bertolotti et al., 2012a) have provided little evidence of this pattern of functional reorganization. Rosenberger et al. (2009) showed that patients with LH EZ could recruit LH areas outside the classical ‘eloquent regions’ to ensure efficient language processing (Mbwana et al., 2009; Perrone-Bertolotti et al., 2012a). Nevertheless, the intrahemispheric pattern of reorganization is more difficult to explore with classical fMRI analysis methods. Indeed, Mbwana et al. (2009) pointed out that comparisons of patients and healthy subjects are constrained by a priori assumptions and reliance on the preselection of cerebral regions (i.e., a ‘regions of interest’ or ROI approach). Rosenberger et al. (2009) pointed out that visual, qualitative comparisons are subjective and typical group analyses are limited by a lack of data on the heterogeneity of the patient sample. For these reasons, the incidence of intrahemisphere reorganization may be underestimated or masked, which would explain the small amount of relevant evidence in the literature. This may be considered a limitation, and to overcome it, Mbwana et al. (2009) investigated interhemispheric and intrahemispheric reorganization in epilepsy patients using the data-driven method allowing to assess interindividual variability. These authors used fMRI to collect data from 45 patients with TLE during performance of an auditory task; several interhemispheric and intrahemispheric patterns of organization were observed; temporal regions showed an intrahemispheric organization, particularly in the postero-superior temporal sulcus (MNI coordinates, 52, 72, 10) adjacent to classical temporal language areas. Interestingly, it was the youngest patients and patients with the shortest duration of epilepsy who showed an intrahemispheric pattern. These results suggest that several factors may affect the emergence of a specific compensatory pattern.
Clearly, the atypical representation of language occurs more frequently in epilepsy patients than in healthy subjects (Rasmussen and Milner, 1977; Adcock et al., 2003; Brázdil et al., 2003; Helmstaedter et al., 2006; Janszky et al., 2006; Berl et al., 2014). For instance, Berl et al. (2014) reported an atypical pattern in 2.5% of healthy subjects and 24.5% of patients with epilepsy. More interesting, these authors showed that there were multiple forms of atypical pattern. Data-driven cluster analysis and assessment of laterality at the regional level (IFG and Wernicke’s area) revealed six different patterns of atypical representation: one symmetrical bilateral pattern, two crossed hemisphere dissociation patterns, and three RH lateralization patterns (for details, see Berl et al., 2014). This paper is interesting, as it introduced new details on the patterns of reorganization, going beyond the three patterns of organization, which had been reported previously, and emphasizing the importance of assessing lateralization at the regional rather than hemispheric level. These authors also explored the modulation of the patterns by several variables (including demographic and pathological factors). Overall, their findings were consistent with those reported in other studies (Adcock et al., 2003; Brázdil et al., 2003; Helmstaedter et al., 2006; Janszky et al., 2006).
Factors modulating language plasticity in epilepsy patients
Several factors explain the high prevalence of atypical representation of language (Chugani et al., 1996). These factors may include demographic and clinical characteristics of patients, such as the age at which the lesion or epileptic seizures occur (Vargha-Khadem et al., 1997; Staudt et al., 2001; Hertz-Pannier et al., 2002; Liégeois et al., 2004; Brázdil et al., 2005; Tracy et al., 2009), the size, location, and lateralization of the EZ (Adcock et al., 2003; Backes et al., 2005; Berl et al., 2005; Karunanayaka et al., 2011), frequency of interictal epileptiform discharges (Janszky et al., 2003, 2006), gender (Strauss et al., 1992; Helmstaedter et al., 2004), handedness (Berl et al., 2014), and individual differences in potential plasticity (Zatorre, 2013). Furthermore, the pattern of organization may be different before and after surgery (Helmstaedter et al., 2006; Bonelli et al., 2012; Perrone-Bertolotti et al., 2012a).
Several factors that modulate language networks in patients with epilepsy are described below. We have grouped them into two categories: (1) ‘interindividual factors’ related to individual characteristics and pathological features and (2) ‘intraindividual factors’ and methodological considerations including experimental characteristics (tasks, fMRI parameters) that may modulate the patterns of activation.
In this section, we discuss the age of seizure onset (ASO), the gender, the size, type, and location of the EZ, the extent of hippocampal sclerosis (HS), and the type of surgery. They are presented and grouped as a whole corpus of modulation, as they usually interact with each other to modulate language representation.
The ‘ASO’ is one of the most influential modulatory factors. It is considered the primary cause of atypical language representation development (Pataraia et al., 2004; Brázdil et al., 2005; Yuan et al., 2006). There is a consensus that children have higher potential brain plasticity than adults (Vargha-Khadem et al., 1997). Early ASO is more likely than late ASO to be accompanied by atypical language lateralization (Brázdil et al., 2003). This effect is consistent with the normal language development (i.e., increased hemispheric specialization with age for both language production and comprehension; Holland et al., 2001; Plante et al., 2006; Szaflarski et al., 2006; Ressel et al., 2008; Lidzba et al., 2011). However, there is no consensus on exactly how ASO affects language reorganization. ASO may modulate reorganization at either interhemispheric level (Staudt et al., 2002; Liégeois et al., 2004) or intrahemispheric level (Rasmussen and Milner, 1977; Chugani et al., 1996). Early ASO may induce two types of reorganization, either intrahemispheric pattern (Hamberger et al., 2003) or interhemispheric pattern (i.e., bilateral or RH lateralization; Staudt et al., 2002; Voets et al., 2006; Liégeois et al., 2008; Tillema et al., 2008; Tivarus et al., 2012). Late ASO does not disrupt the typical hemispheric lateralization of language (LH dominance; Brázdil et al., 2003). It was suggested that injury or seizures in the dominant LH may force the brain to activate preexisting networks in the non-language-dominant hemisphere or to reveal new functional regions on the RH, which can then compensate for LH dysfunction (Yuan et al., 2006). Importantly, similar language reorganization was observed later in life, in teenagers (Loddenkemper et al., 2003) and adults (Helmstaedter et al., 2006) with late ASO (Perrone-Bertolotti et al., 2012b), suggesting that ASO may interact with other pathological factors.
The ‘localization and type of lesion’ can also modulate reorganization. In a recent study by Möddel et al. (2009), bilateral Wada tests were administered to a large sample of 445 patients. Language representation was classified as left dependent, right dependent, bilateral dependent (speech arrest after both left and right injections), or bilateral independent (speech not arrested after either injection). The handedness and the anatomical site of lesion (based on MRI) were compared across these groups. Lesions were classified as ‘early’ (congenital) or ‘late’ (acquired after birth) neocortical lesions or HS. The majority of patients (78%) were LH predominant. Interestingly, right-handed patients, with and without LH lesions, showed similar language patterns. Left-handed patients with no cerebral damage detectable by MRI were not different from the right-handed patients. However, language representation in left-handed patients with early left lesions was most likely right dependent (46%), whereas, in left-handed patients with late left lesions, it was most likely bilateral dependent (37%). The majority of patients with left HS had bilateral-dependent (33%) or left-dependent (33%) language representation. These results provide evidence that RH dominance is associated with early cerebral lesions. According to these authors, bilateral-dependent language may be an indication of defectively maintained RH dominance following late LH insult, which occurred when LH dominance had already started to develop. Bilateral-dependent language may also occur as a normal developmental variant, resulting in functional language representation distributed across both hemispheres. Converging results suggest that large, early LH lesions tend to be associated with RH shift (Hertz-Pannier et al., 2002), whereas later-occurring, smaller lesions tend to be associated with intrahemispheric reorganization. Some authors have suggested that the lateralization of the EZ is the determining factor in language reorganization in patients with TLE. Patients with left EZ are more likely to show atypical language representation than healthy subjects or patients with right EZ (Adcock et al., 2003; Backes et al., 2005; Berl et al., 2005; Schwarz and Pauli, 2009; Karunanayaka et al., 2011). Similarly, Brázdil et al. (2003) found that atypical organization was more common in patients with left TLE (23.1%) than patients with right TLE (0%). More recently, Wong et al. (2009) investigated patients with right and left TLE before and after surgery. These patients showed atypical interhemispheric organization reflected in the significant involvement of the right inferior and middle frontal gyri. In addition, the left TLE patients showed weak correlations between neuropsychological scores and neuronal activity in classical language areas. According to these authors, these results suggest interhemispheric reorganization in both categories of patients, together with supplementary involvement of other regions in the ipsilateral hemisphere. After surgery, patients with left TLE showed decreased activity in frontal regions as well as lower neuropsychological scores that were more strongly correlated with the activity of atypical language areas such as the superior parietal lobule. In right TLE patients, the language network was similar before and after surgery. Taken together, these results suggest that there are various patterns of interhemispheric reorganization and that the pattern may depend at least partly on EZ lateralization. Reorganization seems to be especially significant in frontal regions (see also Lee et al., 2008). Additionally, ‘surgery’ may affect the type of reorganization. Helmstaedter et al. (2006) conducted a study in patients who received surgery to the medial temporal region to treat epilepsy. There was variability in postsurgical reorganization; one patient showed bilateral representation before surgery and LH representation after surgery. Changes in lateralization were correlated with neuropsychological scores and behavioral performance (see also Perrone-Bertolotti et al., 2012a; Janecek et al., 2013). Supplementary studies should be performed to investigate why surgery modifies language network representation in some patients but not in others and to determine exactly how surgery interacts with other factors and with cognitive and behavioral performance.
TLE is often accompanied by HS reflected in reduced hippocampal volume and an increased T2 MRI signal (Sisodiya et al., 1997). Although medial temporal regions such as hippocampus are mainly associated with memory functions (Scoville and Milner, 1957; Squire and Zola-Morgan, 1991; Lech and Suchan, 2013), a handful of neuroimaging studies have found increased hippocampal activity during language production (Pihlajamaki et al., 2000; Binder et al., 2008; Hocking et al., 2009; Whitney et al., 2009; Bonelli et al., 2011; Hamamé et al., 2014). Typically, lateralization of language and verbal memory are correlated (Binder et al., 2008). There is also evidence that an EZ in or near the hippocampal region but distant from temporal language regions may modulate the lateralization of language representation (Weber et al., 2006; Hamberger et al., 2007). Compared with patients without HS, patients with HS are more likely to show atypical hemispheric lateralization of language (Pataraia et al., 2004; Powell et al., 2008; Labudda et al., 2010; Richardson, 2010) and have better language functioning (Chelune et al., 1991; Hermann et al., 1995; Davies et al., 1998; Stroup et al., 2003; Gleissner et al., 2004; Baxendale et al., 2006; Lineweaver et al., 2006). As suggested by Knecht (2004), the hippocampus may be crucial to the implementation of hemispheric lateralization for language, and fronto-temporal language network functioning may be altered if the hippocampus is injured. Weber et al. (2006) showed that left HS is more frequently associated with atypical language representation than a lesion in another location, such as the frontal or neocortical temporal regions. Liégeois et al. (2004) suggested that left HS was associated with the transfer of language functions to the RH (interhemispheric reorganization; i.e., induction of atypical language organization; Binder et al., 2008; Labudda et al., 2010). The accounts of such interhemispheric reorganization refer to verbal memory and a language compensatory mechanism (Binder et al., 2008). Furthermore, given the extensive connections between the hippocampus and the fronto-temporo-parietal language network, it is reasonable to suggest that learning and memory processes play a significant role in language lateralization and reorganization.
The influence of ‘gender’ on language reorganization has received much less attention and the reported results are controversial (Strauss et al., 1992; Kurthen et al., 1997; Janszky et al., 2003; Helmstaedter et al., 2004). For instance, Helmstaedter et al. (2004) assessed gender differences in language representation in left TLE patients. Wada tests administered before surgery indicated that the sample included patients with typical organization and patients with atypical organization. These authors reported that females were more likely to be atypically lateralized than males, a result consistent with a report by Kurthen et al. (1997) but in disagreement with Strauss et al. (1992), who found the opposite pattern (males more likely to be atypically lateralized than females), and Janszky et al. (2003), who found no evidence of gender differences in language lateralization (Billingsley et al., 2001). Helmstaedter et al. (2004) suggested that the difference in findings might be explained by the interaction of gender with other modulatory factors; indeed, they also reported that the correlation between an atypical pattern of language lateralization and ASO varied according to gender. In females, both patterns of atypical lateralization (bilateral and right lateralized) seem to be correlated with early ASO (∼7 years old), whereas, in males, atypical RH lateralization was associated with early ASO (∼3 years) and atypical bilateral representation was mostly observed with late ASO (∼12 years; i.e., later than in females).
Some very general conclusions can be drawn at this point: (a) early ASO is more frequently associated with interhemispheric organization that other atypical patterns of organization; however, interhemispheric reorganization is also observed at other stages of life (adolescence and adulthood); (b) the probability of interhemispheric reorganization is higher when the EZ is in the hemisphere specialized for language; (c) HS facilitates interhemispheric reorganization; (d) females are more likely to show interhemispheric reorganization than males, but the type of reorganization also depends on the ASO; and (e) interactions between factors should be considered (Saltzman-Benaiah et al., 2003; Tracy et al., 2009; Perrone-Bertolotti et al., 2012b).
Intraindividual factors and methodological considerations
Language representation also depends on factors related to features of the procedures used in the experimental evaluation of language. We consider here the type of language task used, paradigms, stimuli, and parameters for fMRI testing.
Although fMRI is now considered a reliable noninvasive technique for the determination of cerebral language representation, activation patterns should be interpreted cautiously given that they are highly dependent on language tasks (see Figure 4) and paradigms (Hund-Georgiadis et al., 2001; Álvarez-Linera et al., 2002; Engström et al., 2004; Wilke et al., 2010; Pillai and Zaca, 2011). Invasive methods such as ECS show that the stimulation of specific cortical sites can impair one specific language operation (e.g., naming) but not another (e.g., reading). This evidence highlights the critical influence of the type of task that is used to identify language activation (Ojemann, 1983; Schwartz et al., 1996). Baciu et al. (2005) evaluated the concordance of results obtained with the gold-standard methods (Wada test and ECS) and with fMRI for four language tasks in epileptic patients. They showed that a semantic task (meaningful related words) was more accurate to quantify the hemispheric representation of language (100% agreement between methods) than the other three language tasks (word stem completion: 80% agreement, living-nonliving categorization: 65% agreement, and phonological tasks: 63% agreement).
Other neuroimaging studies, which explored the effect of linguistic operations (Tracy et al., 2009; Perrone-Bertolotti et al., 2012b; Rosazza et al., 2013), suggested that these linguistic operations should be considered separately, as they induce various degrees of interhemispheric and intrahemispheric representation. The language tasks typically used in TLE for mapping language are semantic (Sabsevitz et al., 2003; Cousin et al., 2007) and phonological (Bahn et al., 1997; Baciu et al., 2001, 2005; Cousin et al., 2008) decision, word generation (Bahn et al., 1997; Hertz-Pannier, 1997; Lehericy et al., 2000), sentence reading (Rutten et al., 2000; Gaillard et al., 2002), and naming (Trebuchon-Da Fonseca et al., 2009; Ralph et al., 2012). Ideally, to identify all the substrates associated with all language operations, mapping should use an exhaustive battery of tasks, something that is currently difficult to achieve in practice, given the short time available for an examination and other specific limits on work with patients. A compromise should be made between the number of tasks used, their relationship to language representation, and the duration of the fMRI examination. In practice, phonological and lexico-semantic tasks are usually used to maximize the amount of relevant data. Semantic tasks induce more bilateral activation than phonological tasks (Springer et al., 1999). Billingsley et al. (2001) assessed temporal lobe reorganization in left and right TLE using phonological and semantic tasks. They showed that the pattern of temporal lobe reorganization was mainly indicated by the semantic task, whereas the phonological task resulted in specific prefrontal activation. Prefrontal activation in phonological task was interpreted as evidence of greater effort required by this task. It has also been found useful to use tasks that distinguish between language production and perception. Overall, a considerable amount of evidence suggests that there is variation in intrahemispheric representation across individuals and across tasks (Seghier et al., 2004; Tzourio-Mazoyer et al., 2004). The reported peaks of activation vary among studies and distinct subregions dedicated to a specific language operation (e.g., phonological or lexico-semantic) may be found within a single frontal or temporal region (Figure 4).
The lateralization of frontal and temporal language regions varies according to language tasks and population (see Figure 5 and the authors’ unpublished data). Figure 5 shows in the top part the evolution of the regional (frontal and temporal) lateralization index (LI) calculated for a phonological task and a lexico-semantic task according to the p values of statistical significance of activation in healthy controls and epileptic patients (right and left EZ lateralization). Frontal LIs were positive for both populations and both tasks, suggesting left frontal lateralization. Temporal LIs were positive for both tasks in healthy subjects, suggesting left temporal lateralization, but mostly negative in patients, suggesting more atypical lateralization of temporal regions. The bottom part of Figure 5 shows similar results obtained with another quantification method (percentage of MRI signal change). Overall, Figure 5 illustrates the importance of considering and interpreting activation according to task, brain region, and hemisphere.
Possible models of language reorganization
All previously mentioned factors make a complex contribution to cerebral organization of language. Crucially, their effects are complementary rather than additive. There is no single way for the brain to reorganize; instead, cerebral correlates of language are rather flexible and can adapt to changing circumstances, exhibiting individual characteristics and differences. Moreover, behavioral performance and neurocognitive score should also be considered in the evaluation of the efficiency of reorganization (Baxendale and Thompson, 2010). Neuroimaging results should always be interpreted in the context of a broader evaluation, including neuropsychological and behavioral tests (Berl et al., 2005; Helmstaedter et al., 2006; Bonelli et al., 2011; Perrone-Bertolotti et al., 2012a).
Major questions to be considered include which pattern of reorganization is efficient and determining how it might be possible to predict efficient patterns. Answering these questions could help with the development of appropriate language rehabilitation methods and thus have benefits for clinical practice. Previous reports on the role of the nondominant hemisphere after injury have produced controversial and inconsistent results (Marsh et al., 2006; Crosson et al., 2009). According to some authors, the participation of the nondominant hemisphere is required during reorganization (Calvert et al., 2000; Crinion and Price, 2005; Pulvermüller et al., 2005; Jensen et al., 2011) at least during the early stages of recovery (Knopman et al., 1983; Weiller et al., 1995; Elkana et al., 2011). Other studies suggested that the dominant hemisphere is essential for (Crosson et al., 2007) reorganization (Saur et al., 2006) and that efficacious recovery (to normal language performance) requires the involvement of perilesional areas in the dominant hemisphere (Beharelle et al., 2010). Crosson et al. (2007) suggested that the dominant hemisphere is required for recovery from small lesions, whereas the nondominant hemisphere is involved in recovery from large lesions. Pulvermüller et al. (2005) proposed that a brief but intense rehabilitation could modify neurophysiological activity by reinforcing internal connections in neural networks dedicated to word processing, such that these networks become easier to activate and their frequent solicitations result in the extension of activity to adjacent neurons. Furthermore, recent evidence suggests that language regions may be modulated via ‘top-down’ mechanisms (i.e., by higher-level, executive functions; Perrone-Bertolotti et al., 2012b, 2014; Yvert et al., 2012). This type of interaction could also affect reorganization and should be considered in developing novel rehabilitation methods for reactivating language systems after injury.
The final aim of this type of research is to develop predictive models of efficient language reorganization, which can be used in fundamental research and clinical practice. Figure 6 illustrates several possible predictive models.
For instance, an epileptic patient with early ASO may show a significant interhemispheric functional shift in language; this may occur rapidly, given that learning abilities and synaptic plasticity are high in early childhood and interhemispheric inhibitory mechanisms are immature, less rigid, and easier to modulate. In this specific context, a ‘substitute specialized’ hemisphere, usually the RH, may be capable of supporting optimal language functions; with a late ASO, during adulthood, for instance, one would expect the interhemispheric functional shift and language processing by the ‘substitute specialized’ hemisphere to result in suboptimal functioning, as learning abilities and synaptic plasticity are reduced, and inhibitory mechanisms are much more settled, mature, and rigid in adults. In this situation, one might expect that additional regions in the hemisphere ipsilateral to the EZ would be also recruited to support language functions. In terms of patterns, this mechanism would be classified as either an atypical (bilateral, if the interhemispheric shift is equivalent to the recruitment of additional ipsilateral regions) or a typical (left dominance, if the interhemispheric shift is insufficient with respect to the additional recruitment of ipsilateral regions) pattern of reorganization. The models of language reorganization in patients with drug-resistant epilepsy should also account for the effect of surgery. EZ removal or inactivation may be followed by a reactivation of inhibitory interhemispheric mechanisms. The extent of reactivation may vary according to modulatory factors such as the ASO and the initial location of the EZ. With an early ASO, the ‘substitute specialized’ hemisphere might remain dominant for language given that inhibitory mechanisms are weak, in which case the shift back will not occur. If the ASO is late, the reactivation of inhibitory interhemispheric (left-to-right) mechanisms might be stronger, and a shift of language functions back to the ‘initial specialized’ hemisphere may be essential to support efficient language functions (Helmstaedter et al., 2006; Perrone-Bertolotti et al., 2012a).
Research on patients with epilepsy has contributed significantly to the neuroscience of language organization and reorganization and provided support for the idea that language and its cerebral networks are not rigid but flexible and modifiable across the lifespan. The domain of reorganization in pathological condition takes into account the hodotopic perspective (Duffau et al., 2014). The cerebral dynamics, which relies on continuous interaction between ascending (afferent, bottom-up) and descending (efferent, top-down) information and between language and other cognitive functions, should be considered. The role of white matter connectivity seems to be essential in the recovery process (Ius et al., 2011; Duffau, 2014) and should be extensively evaluated. Longitudinal and multimodal evaluations seem to be crucial in these patients. Unlike research in stroke patients, in patients with epilepsy, it is possible to assess the multiple mechanisms of reorganization at different times, including ‘chronic’ reorganization induced by the epilepsy, ‘acute’ reorganization induced by surgery, and ‘subacute’ and ‘secondary chronic’ reorganization several months or years after surgery. This multimodal approach to evaluate the representation of language is standard for the assessment of language plasticity in epilepsy in our clinical environment (Baciu et al., 2001; Lachaux et al., 2007a, 2012; Jerbi et al., 2010; David et al., 2011, 2013; Vidal et al., 2011; Perrone-Bertolotti et al., 2014). In practice, patients undergo extensive behavioral, neuropsychological, functional, and structural neuroimaging examination. Moreover, precise cognitive maps are obtained for each of them via intracranial EEG recording with a standardized battery of cognitive tasks (ISD Project, Grenoble-Lyon, France; Jerbi et al., 2009; Lachaux et al., 2003, 2009). Intracranial mapping measures γ-band activity and performs time-frequency analyses (Lachaux et al., 2012) and applied in real-time conditions (Lachaux et al., 2007b; Hamamé et al., 2012). Furthermore, it is of interest to quantify the epileptic network. By means of high-frequency oscillations (60–100 Hz) recording, the epileptogenicity in individual patients alongside their onset of seizures and propagation are recorded. All these approaches permit researchers to obtain multiple categories of data, which are then interpreted in correlation and could bring to light new ways to assess the interaction between neurophysiopathological and cognitive processes. Perrone-Bertolotti et al. (2012a) showed that language representation varies according to task (phonology and semantics) and surgery; moreover, fMRI results should be interpreted in correlation with neuropsychological scores, and only several patterns of reorganization are associated with efficient recovery. David et al. (2013) developed a connectivity atlas of language network based on the recording of brain activity in epileptic patients. Overall, the problem of language representation in physiological condition and reorganization in pathological condition is opened, as many questions remain unanswered.
The authors thank Pr. Philippe Kahane for his valuable comments and suggestions on the manuscript.
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About the article
Published Online: 2015-02-27
Published in Print: 2015-06-01
Citation Information: Reviews in the Neurosciences, Volume 26, Issue 3, Pages 323–341, ISSN (Online) 2191-0200, ISSN (Print) 0334-1763, DOI: https://doi.org/10.1515/revneuro-2014-0074.
©2015, Monica Baciu et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0