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Reviews in the Neurosciences

Editor-in-Chief: Huston, Joseph P.

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Volume 26, Issue 3

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What do patients with epilepsy tell us about language dynamics? A review of fMRI studies

Monica Baciu / Marcela Perrone-Bertolotti
Published Online: 2015-02-27 | DOI: https://doi.org/10.1515/revneuro-2014-0074

Abstract

The objective of this review is to resume major neuroimaging findings on language organization and plasticity in patients with focal and refractory epilepsy, to discuss the effect of modulatory variables that should be considered alongside patterns of reorganization, and to propose possible models of language reorganization. The focal and refractory epilepsy provides a real opportunity to investigate various types of language reorganization in different conditions. The ‘chronic’ condition (induced by the epileptogenic zone or EZ) is associated with either recruitment of homologous regions of the opposite hemisphere or recruitment of intrahemispheric, nonlinguistic regions. In the ‘acute’ condition (neurosurgery and EZ resection), the initial interhemispheric shift (induced by the chronic EZ) could follow a reverse direction, back to the initial hemisphere. These different patterns depend on several modulatory factors and are associated with various levels of language performance. As a neuroimaging tool, functional magnetic resonance imaging enables the detailed investigation of both hemispheres simultaneously and allows for comparison with healthy controls, potentially creating a more comprehensive and more realistic picture of brain-language relations. Importantly, functional neuroimaging approaches demonstrate a good degree of concordance on a theoretical level, but also a considerable degree of individual variability, attesting to the clinical importance with these methods to establish, empirically, language localization in individual patients. Overall, the unique features of epilepsy, combined with ongoing advances in technology, promise further improvement in understanding of language substrate.

Keywords: epilepsy; fMRI; language; neuroimaging; plasticity; reorganization; specialization

General considerations

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).

Schematic representation of the classical methods used to quantify the hemispheric specialization, as assessed with fMRI.
Figure 1:

Schematic representation of the classical methods used to quantify the hemispheric specialization, as assessed with fMRI.

Schematic representation of language lateralization patterns: typical (LH dominance) and atypical (RH dominance and bilateral representation).
Figure 2:

Schematic representation of language lateralization patterns: typical (LH dominance) and atypical (RH dominance and bilateral representation).

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).

Illustration of the main patterns of language reorganization. (A) ‘Interhemispheric’: involvement of the nondominant hemisphere, which suggests that language networks do shift from the LH to the RH, most frequently to the homologous region. (B) ‘Crossed dissociation’: a partial shift of ‘eloquent regions’ to the RH. (C) ‘Intrahemispheric’: recruitment of other areas within the injured language-dominant hemisphere, mainly along the perisylvian fissure.
Figure 3:

Illustration of the main patterns of language reorganization.

(A) ‘Interhemispheric’: involvement of the nondominant hemisphere, which suggests that language networks do shift from the LH to the RH, most frequently to the homologous region. (B) ‘Crossed dissociation’: a partial shift of ‘eloquent regions’ to the RH. (C) ‘Intrahemispheric’: recruitment of other areas within the injured language-dominant hemisphere, mainly along the perisylvian fissure.

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.

Interindividual factors

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).

Illustration of cerebral networks involved in language operations and based on the unpublished data from our team. Phonological (yellow), semantic (red), and prosodic (green) networks are represented. IFG, inferior frontal gyrus; STG, superior temporal gyrus.
Figure 4:

Illustration of cerebral networks involved in language operations and based on the unpublished data from our team.

Phonological (yellow), semantic (red), and prosodic (green) networks are represented. IFG, inferior frontal gyrus; STG, superior temporal gyrus.

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.

Illustration of the effect of the EZ on hemisphere lateralization at the regional level. Two quantification methods were used (upper range: LI; lower range: percentage of MRI signal variation). Six patients (three females) with LH location of the EZ (LH-EZ) and six patients (two females) with RH location of the EZ (RH-EZ) performed a phonological task and a lexico-semantic task compared to a control condition (visual detection task) during an fMRI examination (3T MR scanner, Bruker MedSpec S300). Two separate random-effect group analyses with the contrast images (lexico-semantic vs. control; phonology vs. control) from the individual analyses by using one-sample t test were performed. Subsequently, predefined masks from the WFU PickAtlas allowed us to define two symmetrical (left and right) ROIs: IFG and STG. By comparing with healthy controls, our results suggest that patients with left EZ showed stronger recruitment of right STG; this involvement was stronger for phonological task than for lexico-semantic task. Similarly, patients with right EZ showed stronger bilateral involvement of STG region in both phonological and lexico-semantic tasks. With respect to IFG, the hemispheric location of the EZ, left or right, did not modulate the pattern of language lateralization. Overall, our results suggest that (a) patients were more atypically lateralized for language and (b) the EZ location within the predominant hemisphere for language (typically left) induces the supplementary recruitment of the nondominant hemisphere at the level of temporal regions. Although they need supplementary confirmation, our data support the hypothesis of interhemispheric reorganization of language at least in left EZ patients.
Figure 5:

Illustration of the effect of the EZ on hemisphere lateralization at the regional level.

Two quantification methods were used (upper range: LI; lower range: percentage of MRI signal variation). Six patients (three females) with LH location of the EZ (LH-EZ) and six patients (two females) with RH location of the EZ (RH-EZ) performed a phonological task and a lexico-semantic task compared to a control condition (visual detection task) during an fMRI examination (3T MR scanner, Bruker MedSpec S300). Two separate random-effect group analyses with the contrast images (lexico-semantic vs. control; phonology vs. control) from the individual analyses by using one-sample t test were performed. Subsequently, predefined masks from the WFU PickAtlas allowed us to define two symmetrical (left and right) ROIs: IFG and STG. By comparing with healthy controls, our results suggest that patients with left EZ showed stronger recruitment of right STG; this involvement was stronger for phonological task than for lexico-semantic task. Similarly, patients with right EZ showed stronger bilateral involvement of STG region in both phonological and lexico-semantic tasks. With respect to IFG, the hemispheric location of the EZ, left or right, did not modulate the pattern of language lateralization. Overall, our results suggest that (a) patients were more atypically lateralized for language and (b) the EZ location within the predominant hemisphere for language (typically left) induces the supplementary recruitment of the nondominant hemisphere at the level of temporal regions. Although they need supplementary confirmation, our data support the hypothesis of interhemispheric reorganization of language at least in left EZ patients.

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).

Predictive models of language reorganization. Interaction between hemispheres in healthy and patients. (A) Model of language organization in healthy subjects. At birth, both hemispheres possess equivalent potential to support language, but in only one hemisphere, generally the left, do language-related regions become active and result in the specialization of that hemisphere for language. The homologous RH regions remain potentially eloquent but are maintained in standby. They are inactive because of an inhibitory effect (blue line) of the active (LH) frontal and temporal regions. Bilateral excitatory interactions between hemispheres (red dashes) may occur. Given the excitatory-inhibitory interactions, the emergence of hemispheric specialization might be explained by the progressive involvement of inhibitory mechanisms exerted by the specialized language regions on the contralateral hemisphere. (B) Predictive model of language reorganization in pathological conditions. It shows that if the lesion or EZ is located in the vicinity of specialized active regions (temporal), it may disrupt the inhibitory mechanism such that the homologous standby regions become ‘active’ and take over the functions of the damaged LH regions. In other words, a functional shift of language to the ‘substitute specialized’ (right) hemisphere could occur. Moreover, this ‘shift’ could be regional (temporal) or might involve both frontal and temporal poles. Clearly, other factors such as the ASO, the size, and the precise location of the lesion could interact to produce other patterns of reorganization. (C) Possible model of language reorganization in patients with HS (right). In normal situations (left), the left hippocampus inhibits the unaffected right hippocampus (blue line). The intact left hippocampus (left image) in the language-dominant hemisphere may facilitate (via excitatory mechanisms; red lines) the activity of language regions in this hemisphere. Consequently, the dominant language regions might increase their inhibitory effect (blue lines) on the contralateral non-language-dominant hemisphere. In the case of left HS (right image), the excitatory effect exerted by the left hippocampus on the dominant language regions (red dashes) and the inhibitory effect of these regions (blue dashes) on the contralateral RH language regions may decrease. In addition, the left HS might lift the inhibition on the right hippocampus (blue dashes), leading to an increase in the excitatory effect of the right hippocampus on the ipsilateral language regions (red lines). In other words, memory could interact with ipsilateral and contralateral language regions to modulate language representation. Note: plain, increased effect; dashes, decreased effect; red, activation (excitatory effect); blue, deactivation (inhibitory effect).
Figure 6:

Predictive models of language reorganization.

Interaction between hemispheres in healthy and patients. (A) Model of language organization in healthy subjects. At birth, both hemispheres possess equivalent potential to support language, but in only one hemisphere, generally the left, do language-related regions become active and result in the specialization of that hemisphere for language. The homologous RH regions remain potentially eloquent but are maintained in standby. They are inactive because of an inhibitory effect (blue line) of the active (LH) frontal and temporal regions. Bilateral excitatory interactions between hemispheres (red dashes) may occur. Given the excitatory-inhibitory interactions, the emergence of hemispheric specialization might be explained by the progressive involvement of inhibitory mechanisms exerted by the specialized language regions on the contralateral hemisphere. (B) Predictive model of language reorganization in pathological conditions. It shows that if the lesion or EZ is located in the vicinity of specialized active regions (temporal), it may disrupt the inhibitory mechanism such that the homologous standby regions become ‘active’ and take over the functions of the damaged LH regions. In other words, a functional shift of language to the ‘substitute specialized’ (right) hemisphere could occur. Moreover, this ‘shift’ could be regional (temporal) or might involve both frontal and temporal poles. Clearly, other factors such as the ASO, the size, and the precise location of the lesion could interact to produce other patterns of reorganization. (C) Possible model of language reorganization in patients with HS (right). In normal situations (left), the left hippocampus inhibits the unaffected right hippocampus (blue line). The intact left hippocampus (left image) in the language-dominant hemisphere may facilitate (via excitatory mechanisms; red lines) the activity of language regions in this hemisphere. Consequently, the dominant language regions might increase their inhibitory effect (blue lines) on the contralateral non-language-dominant hemisphere. In the case of left HS (right image), the excitatory effect exerted by the left hippocampus on the dominant language regions (red dashes) and the inhibitory effect of these regions (blue dashes) on the contralateral RH language regions may decrease. In addition, the left HS might lift the inhibition on the right hippocampus (blue dashes), leading to an increase in the excitatory effect of the right hippocampus on the ipsilateral language regions (red lines). In other words, memory could interact with ipsilateral and contralateral language regions to modulate language representation. Note: plain, increased effect; dashes, decreased effect; red, activation (excitatory effect); blue, deactivation (inhibitory effect).

Conclusions

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.

Acknowledgments

The authors thank Pr. Philippe Kahane for his valuable comments and suggestions on the manuscript.

References

  • Abbott, D.F., Waites, A.B., Lillywhite, L.M., and Jackson, G.D. (2010). fMRI assessment of language lateralization: an objective approach. NeuroImage 50, 1446–1455.PubMedCrossrefGoogle Scholar

  • Adcock, J.E., Wise, R.G., Oxbury, J.M., Oxbury, S.M., and Matthews, P.M. (2003). Quantitative fMRI assessment of the differences in lateralization of language-related brain activation in patients with temporal lobe epilepsy. NeuroImage 18, 423–438.PubMedCrossrefGoogle Scholar

  • Álvarez-Linera, J., Martín-Plasencia, P., Maestú, F., García de Sola, R., Iglesias, J., and Serrano, J.M. (2002). Dominancia hemisférica para el lenguaje y resonancia magnética funcional: comparación de tres tareas. Rev. Neurol. 35, 115–118.Google Scholar

  • Baciu, M., Rubin, C., Décorps, M.A., and Segebarth, C.M. (1999). Hemispheric language dominance testing by means of fMRI. J. Neuroimaging 9, 246–247.Google Scholar

  • Baciu, M., Kahane, P., Minotti, L., Charnallet, A., David, D., Le Bas, J.F., and Segebarth, C. (2001). Functional MRI assessment of the hemispheric predominance for language in epileptic patients using a simple rhyme detection task. Epileptic Disord. 3, 117–124.PubMedGoogle Scholar

  • Baciu, M., Watson, J., McDermott, K., Wetzel, R., Attarian, H., Moran, C., and Ojemann, J. (2003). Functional MRI reveals an interhemispheric dissociation of frontal and temporal language regions in a patient with focal epilepsy. Epilepsy Behav. 4, 776–780.CrossrefGoogle Scholar

  • Baciu, M., Watson, J.M., Maccotta, L., McDermott, K.B., Buckner, R.L., Gilliam, F.G., and Ojemann, J.G. (2005). Evaluating functional MRI procedures for assessing hemispheric language dominance in neurosurgical patients. Neuroradiology 47, 835–844.CrossrefPubMedGoogle Scholar

  • Backes, W.H., Deblaere, K., Vonck, K., Kessels, A.G., Boon, P., Hofman, P., Wilmink, J.T., Vingerhoets, G., Boon, P.A., Achten, R., et al. (2005). Language activation distributions revealed by fMRI in post-operative epilepsy patients: differences between left- and right-sided resections. Epilepsy Res. 66, 1–12.CrossrefGoogle Scholar

  • Bagshaw, A.P., Aghakhani, Y., Bénar, C.G., Kobayashi, E., Hawco, C., Dubeau, F., Pike, G.B., and Gotman, J. (2004). EEG-fMRI of focal epileptic spikes: analysis with multiple haemodynamic functions and comparison with gadolinium-enhanced MR angiograms. Hum. Brain Mapp. 22, 179–192.PubMedCrossrefGoogle Scholar

  • Bahn, M.M., Lin, W., Silbergeld, D.L., Miller, J.W., Kuppusamy, K., Cook, R.J., Hammer, G., Wetzel, R., and Cross 3rd, D. (1997). Localization of language cortices by functional MR imaging compared with intracarotid amobarbital hemispheric sedation. Am. J. Roentgenol. 169, 575–579.CrossrefGoogle Scholar

  • Banich, M.T. (1995). Interhemispheric interaction: mechanisms of unified processing. In: F.L. Kitterle, ed. Hemispheric Communication: Mechanisms and Models (Hillsdale: Lawrence Erlbaum Associates), pp. 271–300.Google Scholar

  • Baumgartner, C., Serles, W., Leutmezer, F., Pataraia, E., Aull, S., Czech, T., Pietrzyk, U., Relic, A., and Podreka, I. (1998). Preictal SPECT in temporal lobe epilepsy: regional cerebral blood flow is increased prior to electroencephalography-seizure onset. J. Nucl. Med. 39, 978–982.Google Scholar

  • Baxendale, S. and Thompson, P. (2010). Beyond localization: the role of traditional neuropsychological tests in an age of imaging. Epilepsia 51, 2225–2230.CrossrefGoogle Scholar

  • Baxendale, S., Thompson, P., Harkness, W., and Duncan, J. (2006). Predicting memory decline following epilepsy surgery: a multivariate approach. Epilepsia 47, 1887–1894.PubMedCrossrefGoogle Scholar

  • Beharelle, A.R., Dick, A.S., Josse, G., Solodkin, A., Huttenlocher, P.R., Levine, S.C., and Small, S.L. (2010). Left hemisphere regions are critical for language in the face of early left focal brain injury. Brain 133, 1707–1716.CrossrefGoogle Scholar

  • Benke, T., Köylü, B., Visani, P., Karner, E., Brenneis, C., Bartha, L., Trinka, E., Trieb, T., Felber, S., and Bauer, G. (2006). Language lateralization in temporal lobe epilepsy: a comparison between fMRI and the Wada test. Epilepsia 47, 1308–1319.PubMedCrossrefGoogle Scholar

  • Benson, R.R., FitzGerald, D.B., LeSueur, L.L., Kennedy, D.N., Kwong, K.K., Buchbinder, B.R., Davis, T.L., Weisskoff, R.M., Talavage, T.M., and Logan, W.J. (1999). Language dominance determined by whole brain functional MRI in patients with brain lesions. Neurology 52, 798.CrossrefPubMedGoogle Scholar

  • Benton, A. and Tranel, D. (2000). Historical notes on reorganization of function and neuroplasticity. In H.S. Levin and J. Grafman, editors. Cerebral Reorganization of Function After Brain Damage (New York: Oxford University Press), pp. 3–23.Google Scholar

  • Berger, M.S. and Ojemann, G. (1992). Intraoperative brain mapping techniques in neuro-oncology. Stereotact. Funct. Neurosci. 58, 153–161.CrossrefGoogle Scholar

  • Berl, M.M., Balsamo, L.M., Xu, B., Moore, E.N., Weinstein, S.L., Conry, J.A., Pearl, P.L., Sachs, B.C., Grandin, C.B., and Frattali, C. (2005). Seizure focus affects regional language networks assessed by fMRI. Neurology 65, 1604.CrossrefPubMedGoogle Scholar

  • Berl, M.M., Zimmaro, L.A., Khan, O.I., Dustin, I., Ritzl, E., Duke, E.S., Sepeta, L.N., Sato, S., Theodore, W.H., and Gaillard, W.D. (2014). Characterization of atypical language activation patterns in focal epilepsy. Ann. Neurol. 75, 33–42.PubMedCrossrefGoogle Scholar

  • Bernal, B. and Ardila, A. (2013). Bilateral representation of language: a critical review and analysis of some unusual cases. J. Neurolinguist. 1–18.Google Scholar

  • Billingsley, R.L., McAndrews, M.P., Crawley, A.P., and Mikulis, D.J. (2001). Functional MRI of phonological and semantic processing in temporal lobe epilepsy. Brain 124, 1218–27.CrossrefPubMedGoogle Scholar

  • Binder, J. (1996). Determination of language dominance using functional MRI: a comparison with the Wada test. Neurology 46, 978–984.CrossrefPubMedGoogle Scholar

  • Binder, J., Sabsevitz, D.S., Swanson, S.J., Hammeke, T.A., Raghavan, M., and Mueller, W.M. (2008). Use of preoperative functional MRI to predict verbal memory decline after temporal lobe epilepsy surgery. Epilepsia 49, 1377–1394.CrossrefPubMedGoogle Scholar

  • Bloom, J.S. and Hynd, G.W. (2005). The role of the corpus callosum in interhemispheric transfer of information: excitation or inhibition? Neuropsychol. Rev. 15, 59–71.PubMedCrossrefGoogle Scholar

  • Bonelli, S.B., Powell, R., Thompson, P.J., Yogarajah, M., Focke, N.K., Stretton, J., Vollmar, C., Symms, M.R., Price, C.J., Duncan, J.S., et al. (2011). Hippocampal activation correlates with visual confrontation naming: fMRI findings in controls and patients with temporal lobe epilepsy. Epilepsy Res. 95, 264–254.CrossrefGoogle Scholar

  • Bonelli, S.B., Thompson, P.J., Yogarajah, M., Vollmar, C., Powell, R.H.W., Symms, M.R., McEvoy, A.W., Micallef, C., Koepp, M.J., and Duncan, J.S. (2012). Imaging language networks before and after anterior temporal lobe resection: results of a longitudinal fMRI study. Epilepsia 53, 639–650.CrossrefPubMedGoogle Scholar

  • Bookheimer, S. (2007). Pre-surgical language mapping with functional magnetic resonance imaging. Neuropsychol. Rev. 17, 145–155.PubMedCrossrefGoogle Scholar

  • Brázdil, M., Zákopcan, J., Kuba, R., Fanfrdlová, Z., and Rektor, I. (2003). Atypical hemispheric language dominance in left temporal lobe epilepsy as a result of the reorganization of language functions. Epilepsy Behav. 4, 414–419.CrossrefPubMedGoogle Scholar

  • Brázdil, M., Chlebus, P., Mikl, M., Pazourkova, M., Krupa, P., and Rektor, I. (2005). Reorganization of language-related neuronal networks in patients with left temporal lobe epilepsy – an fMRI study. Eur. J. Neurol. 12, 268–275.CrossrefPubMedGoogle Scholar

  • Broca, P. (1865). Sur le siége de la faculté du langage articulé. Bull. Soc. Anthropol. 6, 377–393.CrossrefGoogle Scholar

  • Calvert, G.A., Brammer, M.J., Morris, R.G., Williams, S.C.R., King, N., and Matthews, P.M. (2000). Using fMRI to study recovery from acquired dysphasia. Brain Lang. 71, 391–399.CrossrefPubMedGoogle Scholar

  • Chelune, G.J., Naugle, R.I., Lüders, H., and Awad, I.A. (1991). Prediction of cognitive change as a function of preoperative ability status among temporal lobectomy patients seen at 6-month follow-up. Neurology 41, 399–399.CrossrefGoogle Scholar

  • Chiarello, C. and Maxfield, L. (1996). Varieties of interhemispheric inhibition, or how to keep a good hemisphere down. Brain Cognit. 30, 81–108.CrossrefGoogle Scholar

  • Chugani, H.T., Müller, R.A., and Chugani, D.C. (1996). Functional brain reorganization in children. Brain Dev. 18, 347–356.CrossrefPubMedGoogle Scholar

  • Cousin, E., Peyrin, C., Pichat, C., Lamalle, L., Le Bas, J., and Baciu, M. (2007). Functional MRI approach for assessing hemispheric predominance of regions activated by a phonological and a semantic task. Eur. J. Radiol. 63, 274–285.CrossrefGoogle Scholar

  • Cousin, E., Baciu, M., Pichat, C., Kahane, P., and Le Bas, J.F. (2008). Functional MRI evidence for language plasticity in adult epileptic patients: preliminary results. Neuropsych. Dis. Treat. 4, 235–246.Google Scholar

  • Crinion, J. and Price, C.J. (2005). Right anterior superior temporal activation predicts auditory sentence comprehension following aphasic stroke. Brain 128, 2858–2571.PubMedCrossrefGoogle Scholar

  • Crosson, B., McGregor, K., Gopinath, K.S., Conway, T.W., Benjamin, M., Chang, Y.-L., Moore, A.B., Raymer, A.M., Briggs, R.W., and Sherod, M.G. (2007). Functional MRI of language in aphasia: a review of the literature and the methodological challenges. Neuropsychol. Rev. 17, 157–177.PubMedCrossrefGoogle Scholar

  • Crosson, B., Moore, A.B., McGregor, K.M., Chang, Y.-L., Benjamin, M., Gopinath, K., Sherod, M.E., Wierenga, C.E., Peck, K.K., and Briggs, R.W. (2009). Regional changes in word-production laterality after a naming treatment designed to produce a rightward shift in frontal activity. Brain Lang. 111, 73–85.CrossrefPubMedGoogle Scholar

  • Cruikshank, S.J. and Weinberger, N.M. (1996). Evidence for the Hebbian hypothesis in experience-dependent physiological plasticity of neocortex: a critical review. Brain Res. Rev. 22, 191–228.CrossrefGoogle Scholar

  • David, O., Blauwblomme, T., Job, A.-S., Chabardès, S., Hoffmann, D., Minotti, L., and Kahane, P. (2011). Imaging the seizure onset zone with stereo-electroencephalography. Brain 134, 2898–2911.CrossrefPubMedGoogle Scholar

  • David, O., Job, A.-S., De Palma, L., Hoffmann, D., Minotti, L., and Kahane, P. (2013). Probabilistic functional tractography of the human cortex. NeuroImage 80, 307–317.CrossrefPubMedGoogle Scholar

  • Davies, K.G., Bell, B.D., Bush, A.J., and Wyler, A.R. (1998). Prediction of verbal memory loss in individuals after anterior temporal lobectomy. Epilepsia 39, 820–828.PubMedCrossrefGoogle Scholar

  • De Benedictis, A. and Duffau, H. (2011). Brain hodotopy: from esoteric concept to practical surgical applications. Neurosurgery 68, 1709–1723.PubMedCrossrefGoogle Scholar

  • Démonet, J.F. and Thierry, G. (2001). Language and brain: what is up? What is coming up? J. Clin. Exp. Neuropsychol. 23, 49–73.CrossrefGoogle Scholar

  • Démonet, J.F., Thierry, G., and Cardebat, D. (2005). Renewal of the neurophysiology of language: functional neuroimaging. Physiol. Rev. 85, 49–95.CrossrefPubMedGoogle Scholar

  • Devlin, A.M., Cross, J.H., Harkness, W., Chong, W.K., Harding, B., Vargha Khadem, F., and Neville, B.G.R. (2003). Clinical outcomes of hemispherectomy for epilepsy in childhood and adolescence. Brain 126, 556–566.PubMedCrossrefGoogle Scholar

  • Dijkstra, K.K. and Ferrier, C.H. (2013). Patterns and predictors of atypical language representation in epilepsy. J. Neurol. Neurosurg. Psychiatry 84, 379–385.CrossrefGoogle Scholar

  • Duffau, H. (2006). Brain plasticity: from pathophysiological mechanisms to therapeutic applications. J. Clin. Neurosci. 13, 885–897.CrossrefGoogle Scholar

  • Duffau, H. (2008). Brain plasticity and tumors. In J.D. Pickard, N. Akalan, C. Di Rocco, V. Dolenc, J. Lobo Antunes, J. Mooij, J. Schramm, and M. Sindou, editors. Advances and Technical Standards in Neurosurgery (New York: Springer), pp. 3–33.Google Scholar

  • Duffau, H. (2010). Introduction: surgery of gliomas in eloquent areas: from brain hodotopy and plasticity to functional neurooncology. Neurosurg. Focus 28, Intro. DOI: 10.3171/2009.12.PubMedCrossrefGoogle Scholar

  • Duffau, H. (2012). The challenge to remove diffuse low-grade gliomas while preserving brain functions. Acta Neurochir. 154, 569–574.CrossrefGoogle Scholar

  • Duffau, H. (2014). The huge plastic potential of adult brain and the role of connectomics: new insights provided by serial mappings in glioma surgery. Cortex 58, 325–337.PubMedCrossrefGoogle Scholar

  • Duffau, H., Capelle, L., Sichez, J.P., Faillot, T., Abdennour, L., Law Koune, J.D., Dadoun, S., Bitar, A., Arthuis, F., and Van Effenterre, R. (1999). Intra-operative direct electrical stimulations of the central nervous system: the Salpetriere experience with 60 patients. Acta Neurochir. 141, 1157–1167.CrossrefGoogle Scholar

  • Duffau, H., Moritz-Gasser, S., and Mandonnet, E. (2014). A re-examination of neural basis of language processing: proposal of a dynamic hodotopical model from data provided by brain stimulation mapping during picture naming. Brain Lang. 131, 1–10.PubMedCrossrefGoogle Scholar

  • Elkana, O., Frost, R., Kramer, U., Ben-Bashat, D., Hendler, T., Schmidt, D., and Schweiger, A. (2011). Cerebral reorganization as a function of linguistic recovery in children: an fMRI study. Cortex 47, 202–216.PubMedCrossrefGoogle Scholar

  • Engström, M., Ragnehed, M., Lundberg, P., and Soderfeldt, B. (2004). Paradigm design of sensory-motor and language tests in clinical fMRI. Clin. Neurophysiol. 34, 267–277.CrossrefGoogle Scholar

  • Federico, P., Abbott, D.F., Briellmann, R.S., Harvey, A.S., and Jackson, G.D. (2005). Functional MRI of the pre-ictal state. Brain 128, 1811–1817.PubMedCrossrefGoogle Scholar

  • Fisher, R.S., Boas, W.E., Blume, W., Elger, C., Genton, P., Lee, P., and Engel, J. Jr. (2005). Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE). Epilepsia 46, 470–472.PubMedCrossrefGoogle Scholar

  • Gaillard, W.D., Balsamo, L., Xu, B., Grandin, C.B., Braniecki, S.H., Papero, P.H., Weinstein, S., Conry, J., Pearl, P.L., Sachs, B, et al. (2002). Language dominance in partial epilepsy patients identified with an fMRI reading task. Neurology 59, 256–265.PubMedCrossrefGoogle Scholar

  • Gazzaniga, M.S. (2000). Cerebral specialization and interhemispheric communication: does the corpus callosum enable the human condition? Brain 123, 1293–1326.CrossrefPubMedGoogle Scholar

  • Geschwind, N. (1965). Disconnexion syndromes in animals and man. Brain 88, 237–294.PubMedCrossrefGoogle Scholar

  • Giussani, C., Roux, F.-E., Ojemann, J., Sganzerla, E.P., Pirillo, D., and Papagno, C. (2010). Is preoperative functional magnetic resonance imaging reliable for language areas mapping in brain tumor surgery? Review of language functional magnetic resonance imaging and direct cortical stimulation correlation studies. Neurosurgery 66, 113–120.PubMedCrossrefGoogle Scholar

  • Gleissner, U., Helmstaedter, C., Schramm, J., and Elger, C.E. (2004). Memory outcome after selective amygdalohippocampectomy in patients with temporal lobe epilepsy: one-year follow-up. Epilepsia 45, 960–962.PubMedCrossrefGoogle Scholar

  • Goldmann, R.E. and Golby, A.J. (2005). Atypical language representation in epilepsy: implications for injury-induced reorganization of brain function. Epilepsy Behav. 6, 473–487.CrossrefPubMedGoogle Scholar

  • Grafman, J. (2000). Conceptualizing functional neuroplasticity. J. Commun. Disord. 33, 345–356.CrossrefGoogle Scholar

  • Hamamé, C.M., Vidal, J.R., Ossandón, T., Jerbi, K., Dalal, S.S., Minotti, L., Bertrand, O., Kahane, P., and Lachaux, J.-P. (2012). Reading the mind’s eye: online detection of visuo-spatial working memory and visual imagery in the inferior temporal lobe. NeuroImage 59, 872–879.CrossrefGoogle Scholar

  • Hamamé, C.M., Alario, F., Llorens, A., Liégeois-Chauvel, C., and Trébuchon-Da Fonseca, A. (2014). High frequency gamma activity in the left hippocampus predicts visual object naming performance. Brain Lang. 135, 104–114.CrossrefGoogle Scholar

  • Hamberger, M.J. (2007). Cortical language mapping in epilepsy: a critical review. Neuropsychol. Rev. 17, 477–489.PubMedCrossrefGoogle Scholar

  • Hamberger, M.J. and Cole, J. (2011). Language organization and reorganization in epilepsy. Neuropsychol. Rev. 21, 240–251.PubMedCrossrefGoogle Scholar

  • Hamberger, M.J., Seidel, W.T., Goodman, R.R., Perrine, K., and McKhann, G.M. (2003). Temporal lobe stimulation reveals anatomic distinction between auditory naming processes. Neurology 60, 1478–1483.PubMedCrossrefGoogle Scholar

  • Hamberger, M.J., Seidel, W.T., Goodman, R.R., Williams, A., Perrine, K., Devinsky, O., and McKhann, G.M. (2007). Evidence for cortical reorganization of language in patients with hippocampal sclerosis. Brain 130, 2942–2950.PubMedCrossrefGoogle Scholar

  • Hawco, C.S., Bagshaw, A.P., Lu, Y., Dubeau, F., and Gotman, J. (2007). BOLD changes occur prior to epileptic spikes seen on scalp EEG. NeuroImage 35, 1450–1458.PubMedCrossrefGoogle Scholar

  • Helmstaedter, C., Brosch, T., Kurthen, M., and Elger, C.E. (2004). The impact of sex and language dominance on material specific memory before and after left temporal lobe surgery. Brain 127, 1518–1525.CrossrefPubMedGoogle Scholar

  • Helmstaedter, C., Fritz, N.E., González Pérez, P.A., Elger, C.E., and Weber, B. (2006). Shift-back of right into left hemisphere language dominance after control of epileptic seizures: evidence for epilepsy driven functional cerebral organization. Epilepsy Res. 70, 257–262.CrossrefPubMedGoogle Scholar

  • Hermann, B.P., Seidenberg, M., Dohan Jr., F.C., Wyler, A.R., Haltiner, A., Bobholz, J., and Perrine, A. (1995). Reports by patients and their families of memory change after left anterior temporal lobectomy: relationship to degree of hippocampal sclerosis. Neurosurgery 36, 39–45.CrossrefPubMedGoogle Scholar

  • Hertz-Pannier, L. (1997). Noninvasive assessment of language dominance in children and adolescents with functional MRI: a preliminary study. Neurology 48, 1003–1012.CrossrefGoogle Scholar

  • Hertz-Pannier, L., Chiron, C., Jambaque, I., Renaux-Kieffer, V., Moortele, P.-F.V.d., Delalande, O., Fohlen, M., Brunelle, F., and Bihan, D.L. (2002). Late plasticity for language in a child’s non-dominant hemisphere: a pre- and post-surgery fMRI study. Brain 125, 361–372.CrossrefGoogle Scholar

  • Hocking, J., McMahon, K.L., and de Zubicaray, G.I. (2009). Semantic context and visual feature effects in object naming: an fMRI study using arterial spin labeling. J. Cognit. Neurosci. 21, 1571–1583.Google Scholar

  • Holland, S.K., Plante, E., Weber Byars, A., Strawsburg, R.H., Schmithorst, V.J., and Ball, W.S. (2001). Normal fMRI brain activation patterns in children performing a verb generation task. NeuroImage 14, 837–843.CrossrefPubMedGoogle Scholar

  • Hund-Georgiadis, M., Lex, U., and Von Cramon, D.Y. (2001). Language dominance assessment by means of fMRI: contributions from task design, performance, and stimulus modality. J. Magn. Reson. Imaging 13, 668–675.CrossrefGoogle Scholar

  • Ius, T., Angelini, E., Thiebaut de Schotten, M., Mandonnet, E., and Duffau, H. (2011). Evidence for potentials and limitations of brain plasticity using an atlas of functional resectability of WHO grade II gliomas: towards a “minimal common brain”. NeuroImage 56, 992–1000.CrossrefGoogle Scholar

  • Jallon, P. (1997). Les épilepsies: définition, épidémiologie, classification, facteurs de risques et traitements. Rev. Neuropsychol. 7, 135–149.Google Scholar

  • Janecek, J.K., Swanson, S.J., Sabsevitz, D.S., Hammeke, T.A., Raghavan, M., E. Rozman, M., and Binder, J.R. (2013). Language lateralization by fMRI and Wada testing in 229 patients with epilepsy: rates and predictors of discordance. Epilepsia 54, 314–322.CrossrefPubMedGoogle Scholar

  • Janszky, J., Jokeit, H., Heinemann, D., Schulz, R., Woermann, F.G., and Ebner, A. (2003). Epileptic activity influences the speech organization in medial temporal lobe epilepsy. Brain 126, 2043–2051.PubMedCrossrefGoogle Scholar

  • Janszky, J., Mertens, M., Janszky, I., Ebner, A., and Woermann, F.G. (2006). Left sided interictal epileptic activity induces shift of language lateralization in temporal lobe epilepsy: an fMRI study. Epilepsia 47, 921–927.CrossrefPubMedGoogle Scholar

  • Jensen, E.J., Hargreaves, I., Bass, A., Pexman, P., Goodyear, B.G., and Federico, P. (2011). Cortical reorganization and reduced efficiency of visual word recognition in right temporal lobe epilepsy: a functional MRI study. Epilepsy Res. 93, 155–163.CrossrefPubMedGoogle Scholar

  • Jerbi, K., Ossandon, T., Hamame, C.M., Senova, S., Dalal, S.S., Jung, J., Minotti, L., Bertrand, O., Berthoz, A., and Kahane, P. (2009). Tasks related gamma-band dynamics from an intracerebral perspective: review and implications for surface EEG and MEG. Hum. Brain Mapp. 30, 1758–1771.CrossrefGoogle Scholar

  • Jerbi, K., Vidal, J.R., Ossandon, T., Dalal, S.S., Jung, J., Hoffmann, D., Minotti, L., Bertrand, O., Kahane, P., and Lachaux, J.-P. (2010). Exploring the electrophysiological correlates of the default-mode network with intracerebral EEG. Front. Syst. Neurosci. 4, 27.PubMedGoogle Scholar

  • Jung-Beeman, M. (2005). Bilateral brain processes for comprehending natural language. Trends Cognit. Sci. 9, 512–518.Google Scholar

  • Kahane, P. (2004). Epilepsy surgery in adult patients: for whom? Rev. Neurol. 160, 5S179–5S184.CrossrefGoogle Scholar

  • Karunanayaka, P., Kim, K.K., Holland, S.K., and Szaflarski, J.P. (2011). The effects of left or right hemispheric epilepsy on language networks investigated with semantic decision fMRI task and independent component analysis. Epilepsy Behav. 20, 623–632.PubMedCrossrefGoogle Scholar

  • Kiran, S. (2012). What is the nature of poststroke language recovery and reorganization? ISRN Neurol. 2012, 786872.PubMedGoogle Scholar

  • Knecht, S. (2004). Does language lateralization depend on the hippocampus? Brain 127, 1217–1218.CrossrefPubMedGoogle Scholar

  • Knopman, D.S., Selnes, O.A., Niccum, N., Rubens, A.B., Yock, D., and Larson, D. (1983). A longitudinal study of speech fluency in aphasia: CT correlates of recovery and persistent nonfluency. Neurology 3, 1170–1178.CrossrefGoogle Scholar

  • Krieg, S.M., Sollmann, N., Hauck, T., Ille, S., Foerschler, A., Meyer, B., and Ringel, F. (2013). Functional language shift to the right hemisphere in patients with language-eloquent brain tumors. PLoS One 8, e75403.Google Scholar

  • Kurthen, M. (1992). The intra-carotid amobarbital test: indications, procedure, results. Nervenarzt 63, 713–724.PubMedGoogle Scholar

  • Kurthen, M., Helmstaedter, C., Elger, C.E., and Linke, D.B. (1997). Sex differences in cerebral language dominance in complex-partial epilepsy. Naturwissenschaften 84, 131–133.CrossrefPubMedGoogle Scholar

  • Labudda, K., Mertens, M., Aengenendt, J., Ebner, A., and Woermann, F.G. (2010). Presurgical language fMRI activation correlates with postsurgical verbal memory decline in left-sided temporal lobe epilepsy. Epilepsy Res. 92, 258–261.PubMedCrossrefGoogle Scholar

  • Lachaux, J., Rudrauf, D., and Kahane, P. (2003). Intracranial EEG and human brain mapping. J. Physiol. (Paris) 97, 613–628.CrossrefGoogle Scholar

  • Lachaux, J., Fonlupt, P., Kahane, P., Minotti, L., Hoffmann, D., Bertrand, O., and Baciu, M. (2007a). Relationship between task-related gamma oscillations and BOLD signal: new insights from combined fMRI and intracranial EEG. Hum. Brain Mapp. 28, 1368–1375.PubMedCrossrefGoogle Scholar

  • Lachaux, J., Jerbi, K., Bertrand, O., Minotti, L., Hoffmann, D., Schoendorff, B., and Kahane, P. (2007b). A blueprint for real-time functional mapping via human intracranial recordings. PLoS One 2, e1094.Google Scholar

  • Lachaux, J., Vidal, J.R., Ossandon, T., Jerbi, K., and Kahane, P. (2009). In-depth human brain mapping: systematic and personalized investigation of multiple functional networks with intra-cerebral EEG. NeuroImage 47, S134.CrossrefGoogle Scholar

  • Lachaux, J., Axmacher, N., Mormann, F., Halgren, E., and Crone, N.E. (2012). High-frequency neural activity and human cognition: past, present and possible future of intracranial EEG research. Prog. Neurobiol. 98, 279–301.PubMedCrossrefGoogle Scholar

  • Lech, R.K. and Suchan, B. (2013). The medial temporal lobe: memory and beyond. Behav. Brain Res. 254, 45–49.CrossrefPubMedGoogle Scholar

  • Lee, D., Swanson, S.J., Sabsevitz, D.S., Hammeke, T.A., Scott Winstanley, F., Possing, E.T., and Binder, J.R. (2008). Functional MRI and Wada studies in patients with interhemispheric dissociation of language functions. Epilepsy Behav. 13, 350–356.CrossrefPubMedGoogle Scholar

  • Lehericy, S., Cohen, L., Bazin, B., Samson, S., Giacomini, E., Rougetet, R., Hertz-Pannier, L., Le Bihan, D., Marsault, C., and Baulac, M. (2000). Functional MR evaluation of temporal and frontal language dominance compared with the Wada test. Neurology 54, 1625–1633.PubMedCrossrefGoogle Scholar

  • Lichtheim, L. (1885). On aphasia. Brain 7, 433–484.CrossrefGoogle Scholar

  • Lidzba, K., Schwilling, E., Grodd, W., Krägeloh-Mann, I., and Wilke, M. (2011). Language comprehension vs. language production: age effects on fMRI activation. Brain Lang. 119, 6–15.PubMedCrossrefGoogle Scholar

  • Liégeois, F., Connelly, A., Cross, J.H., Boyd, S.G., Gadian, D.G., Vargha Khadem, F., and Baldeweg, T. (2004). Language reorganization in children with early onset lesions of the left hemisphere: an fMRI study. Brain 127, 1229–1236.PubMedCrossrefGoogle Scholar

  • Liégeois, F., Connelly, A., Baldeweg, T., and Vargha-Khadem, F. (2008). Speaking with a single cerebral hemisphere: fMRI language organization after hemispherectomy in childhood. Brain Lang. 106, 195–203.PubMedCrossrefGoogle Scholar

  • Lineweaver, T.T., Morris, H.H., Naugle, R.I., Najm, I.M., Diehl, B., and Bingaman, W. (2006). Evaluating the contributions of state-of-the-art assessment techniques to predicting memory outcome after unilateral anterior temporal lobectomy. Epilepsia 47, 1895–1903.CrossrefPubMedGoogle Scholar

  • Loddenkemper, T., Wyllie, E., Lardizabal, D., Stanford, L.D., and Bingaman, W. (2003). Late language transfer in patients with Rasmussen encephalitis. Epilepsia 44, 870–871.PubMedCrossrefGoogle Scholar

  • Loddenkemper, T., Morris, H.H., and Moddel, G. (2008). Complications during the Wada test. Epilepsy Behav. 13, 551–553.PubMedCrossrefGoogle Scholar

  • Loring, D.W., Gaillard, W.D., Bookheimer, S.Y., Meador, K.J., and Ojemann, J.G. (2014). Cortical cartography reveals political and physical maps. Epilepsia 55, 633–637.PubMedCrossrefGoogle Scholar

  • Luders, H.O., Najm, I., Nair, D., Widdess-Walsh, P., and Bingman, W. (2006). The epileptogenic zone: general principles. Epileptic Disord. 8, S1–S9.PubMedGoogle Scholar

  • Mäkiranta, M., Ruohonen, J., Suominen, K., Niinimäki, J., Sonkajärvi, E., Kiviniemi, V., Seppänen, T., Alahuhta, S., Jäntti, V., and Tervonen, O. (2005). BOLD signal increase preceeds EEG spike activity – a dynamic penicillin induced focal epilepsy in deep anesthesia. NeuroImage 27, 715–724.PubMedCrossrefGoogle Scholar

  • Marsh, E.B., Hillis, A.E., and Aage, R.M. (2006). Recovery from aphasia following brain injury: the role of reorganization. Prog. Brain Res. 157, 143–156.CrossrefPubMedGoogle Scholar

  • Mbwana, J., Berl, M.M., Ritzl, E.K., Rosenberger, L., Mayo, J., Weinstein, S., Conry, J.A., Pearl, P.L., Shamim, S., Moore, E.N, et al. (2009). Limitations to plasticity of language network reorganization in localization related epilepsy. Brain 132, 347–356.PubMedCrossrefGoogle Scholar

  • Möddel, G., Lineweaver, T., Schuele, S.U., Reinholz, J., and Loddenkemper, T. (2009). Atypical language lateralization in epilepsy patients. Epilepsia 50, 1505–1516.PubMedCrossrefGoogle Scholar

  • Moeller, F., Siebner, H.R., Wolff, S., Muhle, H., Granert, O., Jansen, O., Stephani, U., and Siniatchkin, M. (2008). Simultaneous EEG-fMRI in drug-naive children with newly diagnosed absence epilepsy. Epilepsia 49, 1510–1519.CrossrefPubMedGoogle Scholar

  • Morris, H., Najm, I., and Kahane, P. (2008). Epilepsy Surgery: Patient Selection (London: Informa Healthcare).Google Scholar

  • Neville, H.J. and Bavelier, D. (1998). Neural organization and plasticity of language. Curr. Opin. Neurobiol. 8, 254–258.PubMedCrossrefGoogle Scholar

  • Noachtar, S. and Borggraefe, I. (2009). Epilepsy surgery: a critical review. Epilepsy Behav. 15, 66–72.CrossrefPubMedGoogle Scholar

  • Noachtar, S., Winkler, P.A., and Lüders, H. (2003). Surgical therapy of epilepsy. In E. Science, eds. (Neurological Disorders: Course and Treatment), pp. 235–244.Google Scholar

  • Nobre, A.C. and Plunkett, K. (1997). The neural system of language: structure and development. Curr. Opin. Neurobiol. 7, 262–268.PubMedCrossrefGoogle Scholar

  • Ojemann, G. (1983). The intrahemispheric organization of human language, derived with electrical stimulation techniques. Trends Neurosci. 6, 184–189.CrossrefGoogle Scholar

  • Ojemann, G. and Whitaker, H.A. (1978). Language localization and variability. Brain Lang. 6, 239–260.CrossrefPubMedGoogle Scholar

  • Ojemann, G., Ojemann, J., Lettich, E., and Berger, M. (1989). Cortical language localization in left, dominant hemisphere. An electrical stimulation mapping investigation in 117 patients. J. Neurosurg. 71, 316–326.CrossrefGoogle Scholar

  • Paillard, J. (1976). Réflexions sur l’usage du concept de plasticité en neurobiologie. J. Psychol. Normal. Pathol. 1, 33–47.Google Scholar

  • Paola, L., Mäder, M.J., Germiniani, F., Coral, P., Zavala, J.A.A., Watzo, D.J., Kanegusuku, J., Silvado, C.E.S., and Werneck, L.C. (2004). Bizarre behavior during intracarotid sodium amytal testing (Wada test): are they predictable? Arq. Neuro-Psiquiat. 62, 444–448.CrossrefGoogle Scholar

  • Papagno, C., Gallucci, M., Casarotti, A., Castellano, A., Falini, A., Fava, E., Giussani, C., Carrabba, G., Bello, L., and Caramazza, A. (2011). Connectivity constraints on cortical reorganization of neural circuits involved in object naming. NeuroImage 55, 1306–1313.CrossrefPubMedGoogle Scholar

  • Pataraia, E., Simos, P., Castillo, E., Billingsley-Marshall, R., McGregor, A., Breier, J., Sarkari, S., and Papanicolaou, A. (2004). Reorganization of language-specific cortex in patients with lesions or mesial temporal epilepsy. Neurology 63, 1825–1832.PubMedCrossrefGoogle Scholar

  • Perrone-Bertolotti, M., Kujala, J., Vidal, J.R., Hamame, C.M., Ossandon, T., Bertrand, O., Minotti, L., Kahane, P., Jerbi, K., and Lachaux, J.-P. (2012a). How silent is silent reading? Intracerebral evidence for top-down activation of temporal voice areas during reading. J. Neurosci. 32, 17554–17562.CrossrefGoogle Scholar

  • Perrone-Bertolotti, M., Zoubrinetzky, R., Yvert, G., Le Bas, J., and Baciu, M. (2012b). Functional MRI and neuropsychological evidence for language plasticity before and after surgery in one patient with left temporal lobe epilepsy. Epilepsy Behav. 23, 81–86.CrossrefGoogle Scholar

  • Perrone-Bertolotti, M., Lemonnier, S., and Baciu, M. (2013a). Behavioral evidence for inter-hemispheric cooperation during a lexical decision task: a divided visual field experiment. Front. Hum. Neurosci. 7, 316.Google Scholar

  • Perrone-Bertolotti, M., Lemonnier, S., Bonniot, C., and Baciu, M. (2013b). Hemisphere specialisation and inter-hemispheric cooperation during a phonological task: effect of lexicality as assessed by the divided visual field approach. Laterality Asymmet. Body Brain Cognit. 18, 216–230.CrossrefGoogle Scholar

  • Perrone-Bertolotti, M., Vidal, J.R., De Palma, L., Hamamé, C.M., Ossandon, T., Kahane, P., Minotti, L., Bertrand, O., and Lachaux, J.P. (2014). Turning visual shapes into sounds: early stages of reading acquisition revealed in the ventral occipitotemporal cortex. NeuroImage 90, 298–307.CrossrefGoogle Scholar

  • Pihlajamaki, M., Tanila, H., Hanninen, T., Kononen, M., Laaskso, M., Partanen, K., Soininen, H., and Aronen, H. (2000). Verbal fluency activates the left medial temporal lobe: a functional magnetic resonance imaging study. Ann. Neurol. 47, 470–476.CrossrefPubMedGoogle Scholar

  • Pillai, J.J. and Zaca, D. (2011). Relative utility for hemispheric lateralization of different clinical fMRI activation tasks within a comprehensive language paradigm battery in brain tumor patients as assessed by both threshold-dependent and threshold-independent analysis methods. NeuroImage 54, S136–S145.CrossrefGoogle Scholar

  • Plante, E., Holland, S.K., and Schmithorst, V.J. (2006). Prosodic processing by children: an fMRI study. Brain Lang. 97, 332–342.CrossrefPubMedGoogle Scholar

  • Poeppel, D. and Hickok, G. (2004). Towards a new functional anatomy of language. Cognition 92, 1–12.CrossrefPubMedGoogle Scholar

  • Poeppel, D., Emmorey, K., Hickok, G., and Pylkkänen, L. (2012). Towards a new neurobiology of language. J. Neurosci. 32, 14125–14131.CrossrefGoogle Scholar

  • Powell, H.W.R., Richardson, M.P., Symms, M.R., Boulby, P.A., Thompson, P.J., Duncan, J.S., and Koepp, M.J. (2008). Preoperative fMRI predicts memory decline following anterior temporal lobe resection. J. Neurol. Neurosurg. Psychiatry 79, 686.CrossrefGoogle Scholar

  • Price, C.J. (2010). The anatomy of language: a review of 100 fMRI studies published in 2009. Ann. NY Acad. Sci. 1191, 62–88.CrossrefGoogle Scholar

  • Price, C.J. (2012). A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading. NeuroImage 62, 816–847.CrossrefPubMedGoogle Scholar

  • Pulvermüller, F., Hauk, O., Zohsel, K., Neininger, B., and Mohr, B. (2005). Therapy-related reorganization of language in both hemispheres of patients with chronic aphasia. NeuroImage 28, 481–489.PubMedCrossrefGoogle Scholar

  • Ralph, M.A.L., Ehsan, S., Baker, G.A., and Rogers, T.T. (2012). Semantic memory is impaired in patients with unilateral anterior temporal lobe resection for temporal lobe epilepsy. Brain 135, 242–258.CrossrefGoogle Scholar

  • Rasmussen, T. and Milner, B. (1977). The role of early left brain injury in determining lateralization of cerebral speech functions. Ann. NY Acad. Sci. 299, 355–369.CrossrefGoogle Scholar

  • Ressel, V., Wilke, M., Lidzba, K., Lutzenberger, W., and Krägeloh-Mann, I. (2008). Increases in language lateralization in normal children as observed using magnetoencephalography. Brain Lang. 106, 167–176.PubMedCrossrefGoogle Scholar

  • Richardson, M. (2010). Current themes in neuroimaging of epilepsy: brain networks, dynamic phenomena, and clinical relevance. Clin. Neurophysiol. 121, 1153–1175.PubMedCrossrefGoogle Scholar

  • Ries, M., Boop, F.A., Griebel, M.L., Zou, P., Phillips, N.S., Johnson, S.C., Williams, J., Helton, K.J., and Ogg, R.J. (2004). Functional MRI and Wada determination of language lateralization: a case of crossed dominance. Epilepsia 45, 85–89.CrossrefPubMedGoogle Scholar

  • Rodin, D., Bar-Yosef, O., Smith, M.L., Kerr, E., Morris, D., and Donner, E.J. (2013). Language dominance in children with epilepsy: concordance of fMRI with intracarotid amytal testing and cortical stimulation. Epilepsy Behav. 29, 7–12.PubMedCrossrefGoogle Scholar

  • Rosazza, C., Ghielmetti, F., Minati, L., Vitali, P., Giovagnoli, A.R., Deleo, F., Didato, G., Parente, A., Marras, C., and Bruzzone, M.G. (2013). Preoperative language lateralization in temporal lobe epilepsy (TLE) predicts peri-ictal, pre-and post-operative language performance: an fMRI study. NeuroImage 3, 73–83.CrossrefGoogle Scholar

  • Rosenberger, L.R., Zeck, J., Berl, M.M., Moore, E.N., Ritzl, E.K., Shamim, S., Weinstein, S.L., Conry, J.A., Pearl, P.L., and Sato, S. (2009). Interhemispheric and intrahemispheric language reorganization in complex partial epilepsy. Neurology 72, 1830–1836.CrossrefPubMedGoogle Scholar

  • Rosenow, F. and Lüders, H. (2001). Presurgical evaluation of epilepsy. Brain 124, 1683–1700.CrossrefPubMedGoogle Scholar

  • Rutten, G.-J., van Rijen, P., van Veelen, C., and Ramsey, N. (2000). Test-retest reliability of fMRI measurement of language lateralization is improved by combined task analysis. NeuroImage 11, S325.CrossrefGoogle Scholar

  • Sabbah, P., Chassoux, F., Leveque, C., Landre, E., Baudoin-Chial, S., Devaux, B., Mann, M., Godon-Hardy, S., Nioche, C., Aït-Ameur, A., et al. (2003). Functional MR imaging in assessment of language dominance in epileptic patients. NeuroImage 18, 460–467.CrossrefGoogle Scholar

  • Sabsevitz, D., Swanson, S., Hammeke, T., Spanaki, M., Possing, E., Morris, G., Mueller, W., and Binder, J. (2003). Use of preoperative functional neuroimaging to predict language deficits from epilepsy surgery. Neurology 60, 1788–1792.CrossrefPubMedGoogle Scholar

  • Saltzman-Benaiah, J., Scott, K., and Smith, M.L. (2003). Factors associated with atypical speech representation in children with intractable epilepsy. Neuropsychologia 41, 1967–1974.CrossrefGoogle Scholar

  • Saur, D., Lange, R., Baumgaertner, A., Schraknepper, V., Willmes, K., Rijntjes, M., and Weiller, C. (2006). Dynamics of language reorganization after stroke. Brain 129, 1371–1384.CrossrefPubMedGoogle Scholar

  • Schwartz, T.H., Ojemann, G., Haglund, M.M., and Lettich, E. (1996). Cerebral lateralization of neuronal activity during naming, reading and line-matching. Cognit. Brain Res. 4, 263–273.CrossrefGoogle Scholar

  • Schwarz, M. and Pauli, E. (2009). Postoperative speech processing in temporal lobe epilepsy: functional relationship between object naming, semantics and phonology. Epilepsy Behav. 16, 629–633.PubMedCrossrefGoogle Scholar

  • Scoville, W.B. and Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions. J. Neurol. Neurosurg. Psychiatry 20, 11–21.CrossrefGoogle Scholar

  • Seghier, M.L. (2008). Laterality index in functional MRI: methodological issues. Magn. Reson. Imaging 26, 594–601.CrossrefPubMedGoogle Scholar

  • Seghier, M.L., Lazeyras, F., Pegna, A.J., Annoni, J.M., Zimine, I., Mayer, E., Michel, C.M., and Khateb, A. (2004). Variability of fMRI activation during a phonological and semantic language task in healthy subjects. Hum. Brain Mapp. 23, 140–155.CrossrefPubMedGoogle Scholar

  • Sharan, A., Ooi, Y.C., Langfitt, J., and Sperling, M.R. (2011). Intracarotid amobarbital procedure for epilepsy surgery. Epilepsy Behav. 20, 209–213.CrossrefPubMedGoogle Scholar

  • Sisodiya, S.M., Moran, N., Free, S.L., Kitchen, N.D., Stevens, J.M., Harkness, W.F.J., Fish, D.R., and Shorvon, S.D. (1997). Correlation of widespread preoperative magnetic resonance imaging changes with unsuccessful surgery for hippocampal sclerosis. Ann. Neurol. 41, 490–496.CrossrefPubMedGoogle Scholar

  • Springer, J.A., Binder, J.R., Hammeke, T.A., Swanson, S.J., Frost, J.A., Bellgowan, P.S.F., Brewer, C.C., Perry, H.M., Morris, G.L., and Mueller, W.M. (1999). Language dominance in neurologically normal and epilepsy subjects: a functional MRI study. Brain 122, 2033–2046.CrossrefPubMedGoogle Scholar

  • Squire, L.R. and Zola-Morgan, S. (1991). The medial temporal lobe memory system. Science 253, 1380–1386.CrossrefGoogle Scholar

  • Staudt, M., Grodd, W., Niemann, G., Wildgruber, D., Erb, M., and Krägeloh-Mann, I. (2001). Early left periventricular brain lesions induce right hemispheric organization of speech. Neurology 57, 122–125.CrossrefPubMedGoogle Scholar

  • Staudt, M., Lidzba, K., Grodd, W., Wildgruber, D., Erb, M., and Krägeloh-Mann, I. (2002). Right-hemispheric organization of language following early left-sided brain lesions: functional MRI topography. NeuroImage 16, 954–967.CrossrefPubMedGoogle Scholar

  • Stephan, K.E., Penny, W.D., Marshall, J.C., Fink, G.R., and Friston, K.J. (2005). Investigating the functional role of callosal connections with dynamic causal models. Ann. NY Acad. Sci. 1064, 16–36.CrossrefGoogle Scholar

  • Stephan, K.E., Marshall, J.C., Penny, W.D., Friston, K.J., and Fink, G.R. (2007). Interhemispheric integration of visual processing during task-driven lateralization. J. Neurosci. 27, 3512–3522.CrossrefGoogle Scholar

  • Strauss, E., Wada, J., and Goldwater, B. (1992). Sex differences in interhemispheric reorganization of speech. Neuropsychologia 30, 353–359.PubMedCrossrefGoogle Scholar

  • Stroup, E., Langfitt, J., Berg, M., McDermott, M., Pilcher, W., and Como, P. (2003). Predicting verbal memory decline following anterior temporal lobectomy (ATL). Neurology 60, 1266–1273.CrossrefPubMedGoogle Scholar

  • Szaflarski, J.P., Holland, S.K., Schmithorst, V.J., and Byars, A.W. (2006). fMRI study of language lateralization in children and adults. Hum. Brain Mapp. 27, 202–212.PubMedCrossrefGoogle Scholar

  • Thiel, A., Habedank, B., Herholz, K., Kessler, J., Winhuisen, L., Haupt, W.F., and Heiss, W.-D. (2006). From the left to the right: how the brain compensates progressive loss of language function. Brain Lang. 98, 57–65.CrossrefPubMedGoogle Scholar

  • Thivard, L., Hombrouck, J., Tézenas du Montcel, S., Delmaire, C., Cohen, L., Samson, S., Dupont, S., Chiras, J., Baulac, M., and Lehéricy, S. (2005). Productive and perceptive language reorganization in temporal lobe epilepsy. NeuroImage 24, 841–851.CrossrefGoogle Scholar

  • Tillema, J.-M., Byars, A.W., Jacola, L.M., Schapiro, M.B., Schmithorst, V.J., Szaflarski, J.P., and Holland, S.K. (2008). Reprint of “Cortical reorganization of language functioning following perinatal left MCA stroke”. Brain Lang. 106, 184–194.PubMedCrossrefGoogle Scholar

  • Tivarus, M.E., Starling, S.J., Newport, E.L., and Langfitt, J.T. (2012). Homotopic language reorganization in the right hemisphere after early left hemisphere injury. Brain Lang. 123, 1–10.CrossrefPubMedGoogle Scholar

  • Tracy, J.I., Waldron, B., Glosser, D., Sharan, A., Mintzer, S., Zangaladze, A., Skidmore, C., Siddiqui, I., Caris, E., and Sperling, M.R. (2009). Hemispheric lateralization and language skill coherence in temporal lobe epilepsy. Cortex 45, 1178–1189.CrossrefPubMedGoogle Scholar

  • Trebuchon-Da Fonseca, A., Guedj, E., Alario, F.X., Laguitton, V., Mundler, O., Chauvel, P., and Liegeois-Chauvel, C. (2009). Brain regions underlying word finding difficulties in temporal lobe epilepsy. Brain 132, 2772–2784.CrossrefGoogle Scholar

  • Turrigiano, G.G. (2007). Homeostatic signaling: the positive side of negative feedback. Curr. Opin. Neurobiol. 17, 318–324.PubMedCrossrefGoogle Scholar

  • Turrigiano, G.G. and Nelson, S.B. (2000). Hebb and homeostasis in neuronal plasticity. Curr. Opin. Neurobiol. 10, 358–364.CrossrefPubMedGoogle Scholar

  • Turrigiano, G.G. and Nelson, S.B. (2004). Homeostatic plasticity in the developing nervous system. Nat. Rev. Neurosci. 5, 97–107.PubMedCrossrefGoogle Scholar

  • Tzourio-Mazoyer, N., Josse, G., Crivello, F., and Mazoyer, B. (2004). Interindividual variability in the hemispheric organization for speech. NeuroImage 21, 422–435.CrossrefGoogle Scholar

  • van der Knaap, L.J. and van der Ham, I.J.M. (2011). How does the corpus callosum mediate interhemispheric transfer? A review. Behav. Brain Res. 223, 211–221.CrossrefGoogle Scholar

  • Vargha-Khadem, F., Carr, L.J., Isaacs, E., Brett, E., Adams, C., and Mishkin, M. (1997). Onset of speech after left hemispherectomy in a nine-year-old boy. Brain 120, 159–182.CrossrefGoogle Scholar

  • Vidal, J., Hamame, C., Jerbi, K., Dalal, S., Ciumas, C., Perrone-Bertolotti, M., Ossandon, T., Minotti, L., Kahane, P., and Lachaux, J. (2011). Localizing cognitive functions in epilepsy with intracranial gamma-band dynamic responses. In C. Helmstaedter, M. Lassonde, B. Hermann, P. Kahane, and A. Arzimanoglou, editors. Neuropsychology in the Care of People with Epilepsy (Paris: John Libbey Eurotext).Google Scholar

  • Vigneau, M., Beaucousin, V., Hervé, P.Y., Jobard, G., Petit, L., Crivello, F., Mellet, E., Zago, L., Mazoyer, B., and Tzourio-Mazoyer, N. (2011). What is right-hemisphere contribution to phonological, lexico-semantic, and sentence processing? Insights from a meta-analysis. NeuroImage 54, 577–593.CrossrefPubMedGoogle Scholar

  • Vining, E.P.G., Freeman, J.M., Pillas, D.J., Uematsu, S., Carson, B.S., Brandt, J., Boatman, D., Pulsifer, M.B., and Zuckerberg, A. (1997). Why would you remove half a brain? The outcome of 58 children after hemispherectomy – the Johns Hopkins experience: 1968 to 1996. Pediatrics 100, 163.CrossrefGoogle Scholar

  • Voets, N.L., Adcock, J.E., Flitney, D.E., Behrens, T.E.J., Hart, Y., Stacey, R., Carpenter, K., and Matthews, P.M. (2006). Distinct right frontal lobe activation in language processing following left hemisphere injury. Brain 129, 754–766.CrossrefPubMedGoogle Scholar

  • Wada, J. and Rasmussen, T. (1960). Intracarotid injection of sodium amytal for the lateralization of cerebral speech dominance. J. Neurosurg. 17, 266–282.CrossrefGoogle Scholar

  • Wada, J., Clarke, R., and Hamm, A. (1975). Cerebral hemispheric asymmetry in humans: cortical speech zones in 100 adult and 100 infant brains. Arch. Neurol. 32, 239–246.CrossrefPubMedGoogle Scholar

  • Weber, B., Wellmer, J., Reuber, M., Mormann, F., Weis, S., Urbach, H., Ruhlmann, J., Elger, C.E., and Fernández, G. (2006). Left hippocampal pathology is associated with atypical language lateralization in patients with focal epilepsy. Brain 129, 346–351.PubMedGoogle Scholar

  • Weiller, C., Isensee, C., Rijntjes, M., Huber, W., Müller, S., Bier, D., Dutschka, K., Woods, R.P., Noth, J., and Diener, H.C. (1995). Recovery from Wernicke’s aphasia: a positron emission tomographic study. Ann. Neurol. 37, 723–732.CrossrefGoogle Scholar

  • Wellmer, J., Weber, B., Weis, S., Klaver, P., Urbach, H., Reul, J., Fernandez, G., and Elger, C.E. (2008). Strongly lateralized activation in language fMRI of atypical dominant patients – implications for presurgical work-up. Epilepsy Res. 80, 67–76.PubMedCrossrefGoogle Scholar

  • Wernicke, C. (1974). Der aphasische symptomenkomplex (Breslau: Cohen and Weigert).Google Scholar

  • Whitney, C., Weis, S., Krings, T., Huber, W., Grossman, M., and Kircher, T. (2009). Task-dependent modulations of prefrontal and hippocampal activity during intrinsic word production. J. Cognit. Neurosci. 21, 697–712.Google Scholar

  • Wilke, M., Pieper, T., Lindner, K., Dushe, T., Holthausen, H., and Krägeloh-Mann, I. (2010). Why one task is not enough: functional MRI for atypical language organization in two children. Eur. J. Paediatr. Neurol. 14, 474–478.CrossrefGoogle Scholar

  • Woermann, F.G., Jokeit, H., Luerding, R., Freitag, H., Schulz, R., Guertler, S., Okujava, M., Wolf, P., Tuxhorn, I., and Ebner, A. (2003).0 Language lateralization by Wada test and fMRI in 100 patients with epilepsy. Neurology 61, 699–701.PubMedCrossrefGoogle Scholar

  • Wong, S.W.H., Jong, L., Bandur, D., Bihari, F., Yen, Y.F., Takahashi, A.M., Lee, D.H., Steven, D.A., Parrent, A.G., and Pigott, S.E. (2009). Cortical reorganization following anterior temporal lobectomy in patients with temporal lobe epilepsy. Neurology 73, 518–525.CrossrefPubMedGoogle Scholar

  • Wrench, J.M., Matsumoto, R., Inoue, Y., and Wilson, S.J. (2011). Current challenges in the practice of epilepsy surgery. Epilepsy Behav. 22, 23–31.CrossrefPubMedGoogle Scholar

  • Yu, A., Wang, X., Xu, G., Li, Y., Qin, W., Li, K., and Wang, Y. (2011). A functional MRI study of language networks in left medial temporal lobe epilepsy. Eur. J. Radiol. 80, 441–444.CrossrefPubMedGoogle Scholar

  • Yuan, W., Szaflarski, J.P., Schmithorst, V.J., Schapiro, M., Byars, A.W., Strawsburg, R.H., and Holland, S.K. (2006). fMRI shows atypical language lateralization in pediatric epilepsy patients. Epilepsia 47, 593–600.CrossrefPubMedGoogle Scholar

  • Yvert, G., Perrone-Bertolotti, M., Baciu, M., and David, O. (2012). Dynamic causal modeling of spatiotemporal integration of phonological and semantic processes: an electroencephalographic study. J. Neurosci. 32, 4297–4306.CrossrefGoogle Scholar

  • Zatorre, R.J. (2013). Predispositions and plasticity in music and speech learning: neural correlates and implications. Science 342, 585–589.CrossrefPubMedGoogle Scholar

  • Zhang, X., Zhang, G., Yu, T., Ni, D., Cai, L., Qiao, L., Du, W., and Li, Y. (2013). Surgical treatment for epilepsy involving language cortices: a combined process of electrical cortical stimulation mapping and intra-operative continuous language assessment. Seizure 22, 780–786.CrossrefPubMedGoogle Scholar

About the article

Corresponding author: Monica Baciu, Université Grenoble Alpes, LPNC UMR 5105, CNRS, B.P. 47, F-38040 Grenoble Cedex 9, France; e-mail:


Received: 2014-10-22

Accepted: 2014-11-20

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.

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©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

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