Left-hemisphere lateralization for language and interhemispheric fiber tracking in patients with schizophrenia

Schizophrenia Research 165 (2015) 30–37

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Left-hemisphere lateralization for language and interhemispheric fiber tracking in patients with schizophrenia Elise Leroux a,b, Nicolas Delcroix c, Sonia Dollfus a,b,d,⁎ a

CHU de Caen, Service de Psychiatrie, Centre Esquirol, Caen F-14000, France CNRS, UMR 6301 ISTCT, ISTS Team, GIP CYCERON, Bd Henri Becquerel, BP5229, F-14074 Caen cedex, France CNRS, UMS 3408, GIP CYCERON, Bd Henri Becquerel, BP5229, F-14074 Caen cedex, France d Université de Caen Basse-Normandie, UFR de médecine (Medical School), Caen F-14000, France b c

a r t i c l e

i n f o

Article history: Received 29 July 2014 Received in revised form 24 February 2015 Accepted 22 March 2015 Available online 11 April 2015 Keywords: Diffusion tensor imaging (DTI) Tractography Functional left-lateralization Interhemispheric connectivity Language Schizophrenia

a b s t r a c t Background: It has been suggested that the degree of hemispheric specialization (HS) depends on the structural connectivity between the two hemispheres, that is to say the corpus callosum (CC). Studies, performed only on healthy participants, investigated this anatomo-functional relationship. Nevertheless, it has never been studied in schizophrenia. We therefore propose to study the anatomo-functional relationships between the integrity of interhemispheric connectivity and leftward functional lateralization for language in patients with schizophrenia compared with healthy participants, driven by a multimodal approach combining fMRI and DTI-based fiber tractography. We hypothesized that reduced leftward functional lateralization for language in patients with schizophrenia could be related to a callosal hypoconnectivity. Materials and methods: Seventeen patients based on the DSM-IV, and 17 controls were included. The functional laterality index and interhemispheric diffusion values between homologue temporal regions, belonging to the language network, were individually extracted in order to study the anatomo-functional relationships. Results: In the patients, higher mean and radial diffusivity (RD) values (thicker myelin sheaths) were associated with less leftward lateralization. In contrast, the controls presented higher RD values and lower fractional anisotropy values (axonal loss) with more leftward lateralization. Conclusions: Our study revealed a relationship between the CC and the HS for language, but did not provide evidence clarifying the direction of the relationship between callosal connectivity and functional lateralization for language. In particular, the present findings showed that the loss of integrity in interhemispheric callosal fibers was associated with reduced leftward cerebral dominance for language in patients with schizophrenia. © 2015 Elsevier B.V. All rights reserved.

1. Introduction The corpus callosum (CC) is the major commissure of white matter (WM) connecting the two cerebral hemispheres (Sperry, 1968). It consists of approximately 200–350 million fibers in humans, allowing the transfer of high-level cognitive, somatosensory and motor information through its various callosal pathways (Aboitiz and Zaidel, 1992; Aboitiz et al., 1992; Aboitiz and Montiel, 2003). In this respect, it is suggested that the CC plays a fundamental role in the development and maintenance of hemispheric specialization (HS) (Gazzaniga, 2000, 2005). The best documented HS concerns the leftward cerebral asymmetry underlying language functions (Broca, 1861). It has been

⁎ Corresponding author at: Centre Hospitalier Universitaire, Centre Esquirol, UMR 6301 CNRS CEA Université Caen Basse-Normandie, Caen F-14000, France. Tel.: +33 2 31 06 50 18; fax: +33 2 31 06 49 87. E-mail addresses: [email protected] (E. Leroux), [email protected] (N. Delcroix), [email protected] (S. Dollfus).

http://dx.doi.org/10.1016/j.schres.2015.03.028 0920-9964/© 2015 Elsevier B.V. All rights reserved.

suggested that the degree of HS depends on the structural connectivity between the two hemispheres, that is to say the CC (Ringo et al., 1994; Gazzaniga, 2000). Based on this assumption, a smaller CC corresponds to greater lateralization. In other words, interhemispheric connectivity may act as an essential anatomical substrate for HS, measured through functional asymmetries. Nevertheless, this hypothesis still has to be elucidated. Anatomical imaging studies revealed that, compared with controls, patients with schizophrenia showed WM structural and integrity modifications characterized by smaller CC size (Rotarska-Jagiela and Linden, 2008) associated with a reduced number of fibers (Freitag et al., 2013) and degree of myelination (Clemm von et al., 2014). The authors interpreted these findings as indicating lower interhemispheric connectivity. Knöchel et al. (2012), investigating the structure and integrity of CC, highlighted similar results suggesting interhemispheric hypoconnectivity in schizophrenia. With regard to HS for language, healthy right-handed participants showed a pattern of “typical” cerebral lateralization characterized by left hemisphere (LH) dominance for linguistic functions (Gazzaniga,

E. Leroux et al. / Schizophrenia Research 165 (2015) 30–37

2000). Moreover, it has already been suggested that right-handedness is associated with left-hemispheric dominance for language (Knecht et al., 2000). These findings are less obvious in schizophrenia since about one third of patients present rightward lateralization for language (Dollfus et al., 2005). Previous studies, using functional magnetic resonance imaging (fMRI), suggested reduced leftward functional lateralization for language in patients with schizophrenia, owing to either increased right hemisphere activation (Sommer et al., 2001), decreased LH activation (Dollfus et al., 2005) or more bilateral activation (BleichCohen et al., 2012). Our previous work, based on a functional laterality index, highlighted decreased leftward hemispheric lateralization in patients with schizophrenia compared with controls, in a functional network specifically involved in a language task (Alary et al., 2013a; Royer et al., 2015). In addition, this reduced functional cerebral lateralization could be a biomarker for schizophrenia (Alary et al., 2013b). Consequently, in order to evaluate the relationships between leftward functional lateralization and the CC, in the current study we selected only participants with right-handedness associated with leftward functional lateralization for language. Few studies have addressed the question of a possible relationship between CC characteristics and leftward functional lateralization. Studies have only been conducted in healthy participants and they reported anatomo-functional relationships between the degree of leftward lateralization and CC features, but the results were still contradictory (Westerhausen et al., 2006; Josse et al., 2008; Haberling et al., 2011; Kompus et al., 2011). Westerhausen et al. (2006) showed that mean diffusivity (MD, measured by diffusion tensor imaging, DTI) was lower in the CC (meaning thicker myelin sheaths) in participants who were strongly left-lateralized for language, compared with moderately leftlateralized, bilateral or right-lateralized participants, but the groups did not differ with respect to the area of the CC. On the other hand, Josse et al. (2008), investigating only healthy participants with a null or negative lateralization index (suggesting no lateralization or leftward lateralization for language), found that the CC midsagittal surface area was positively correlated with left language lateralization in the posterior temporal and inferior frontal regions. Similarly, Kompus et al. (2011) revealed that anterior CC size was positively correlated with functional asymmetry for episodic encoding and retrieval in the frontal lobes, suggesting a larger anterior CC associated with a greater leftward asymmetry pattern. However, Haberling et al. (2011) highlighted findings somewhat in conflict with these previous works. Indeed, they showed lower integrity of the callosal area in healthy participants, through lower fractional anisotropy (FA) values (meaning axonal loss) associated with typical cerebral asymmetry, that is to say leftwardcerebral dominance for language. Thus, the light of these findings and to the best of our knowledge, this anatomo-functional relationship between interhemispheric callosal connectivity and the degree of functional lateralization for language has never been investigated in schizophrenia. Therefore, this study aimed to investigate the anatomo-functional relationships between the integrity of interhemispheric connectivity and leftward functional lateralization for language in patients with schizophrenia compared with healthy participants, driven by a multimodal approach combining fMRI and DTI-based fiber tractography. Otherwise, as a sexual dimorphism in the CC was described both in healthy individuals (Sacher et al., 2013) and in patients with schizophrenia (Crow et al., 2007), we evaluated these anatomo-functional relationships in taking into account the gender. We hypothesized that reduced leftward functional lateralization for language in patients with schizophrenia could be related to a callosal hypoconnectivity. In the present study, we propose to evaluate CC integrity through its interhemispheric callosal fibers, using DTI-based tractography which reflects the interhemispheric connectivity or communications more than CC area. The callosal fibers were specifically evaluated between the homologue temporal regions belonging to a language comprehension network. Moreover, we used a direct and robust measure of

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functional cerebral lateralization (Wilke and Lidzba, 2007) reflecting hemispheric lateralization for language.

2. Materials and methods 2.1. Participants Seventeen patients (13 males) diagnosed with schizophrenia (Diagnostic and Statistical Manual of Mental Disorder 4th edition, DSM-IV) were selected, based on a self-reportedly right-handed (Edinburgh Inventory score greater than + 33) (Oldfield, 1971) with leftward functional lateralization for language determinated by a functional lateralization index (see below data analyses). Seventeen healthy volunteers (13 males) were included in the study, which were matched for gender, age and level of education (Table 1). All patients were stabilized outpatients with no change in their treatment over the last month and only one was unmedicated. The psychopathological status of each patient was assessed with the Positive And Negative Syndrome Scale (PANSS) (Kay et al., 1987) and the Auditory Hallucination Rating Scale (AHRS) (Hoffman et al., 2003). The control group did not meet the criteria for lifetime psychotic disorders or substance dependence (including alcohol), as assessed by the MINI (Mini International Neuropsychiatric Interview).

Table 1 Characteristics of participants. Characteristics

Gender Males N (%) Age (years) (m ± SD) [range] Education level (years of education) (m ± SD) [range] Comprehension score (m ± SD) [range] Type of medication Atypical N (%) Typical N (%) Duration of illness (years) (m ± SD) [range] Chlorpromazine equivalent (mg/day) (m ± SD) [range] PANSS subtypes N (%) Residual Positive Negative PANSS positive subscale (m ± SD) [range] PANSS negative subscale (m ± SD) [range] PANSS general subscale (m ± SD) [range] PANSS total (m ± SD) [range]

Patients with schizophrenia N = 17

Controls N = 17

13 (76.5%)

13 (76.5%)

34.8 ± 8.5 [20.8; 59.6]

36.5 ± 9.5 [24.5; 56.1]

1 Pearson chi-square test 0.59 t-test

12.4 ± 2.2 [9; 17]

12.7 ± 2.1 [10; 17]

0.76 t-test

8.9 ± 4.6 [2; 17]

15.1 ± 3.6 [7.5; 19]

0.0001* t-test

12 (70.6%) 5 (29.4%)

–

–

10.7 ± 6.7 [1; 28]

–

–

321.8 ± 269,4 [0; 1060]

–

–

13 3 1

–

–

11.9 ± 4.7 [7; 23]

–

–

13.2 ± 4.7 [8; 24]

–

–

24.4 ± 5.3 [17; 35]

–

–

49.5 ± 11.3 [35; 80]

–

–

5.2 ± 10.1 [0; 32]

–

–

p-Value

AHRS (m ± SD) [range]

Significance level at p b 0.05 with * for significant p-value. PANSS: Positive And Negative Syndrome Scale; AHRS: Auditory Hallucination Rating Scale; m: mean; SD: standard deviation.

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E. Leroux et al. / Schizophrenia Research 165 (2015) 30–37

The patients were recruited from the University Hospital (Caen), and healthy volunteers were recruited from the community. All participants were free of auditory deficits, neurological disorders and cerebral abnormalities. Participants gave their informed, written consent, in accordance with the Declaration of Helsinki, and the local ethics committee (Comité de Protection des Personnes Nord-Ouest, France) approved the experimental protocol. 2.2. Language task The experimental paradigm consisted of listening to a factual story in French, the native language of the participants. The reference task was listening to the same story in Tamil, an unknown language for all participants. The presentation of stimuli followed a block design, with nine alternating, 32-second blocks of speech in either Tamil or French (Tzourio-Mazoyer et al., 1998; Dollfus et al., 2005). Participants were instructed to passively and attentively listen to the story with their eyes closed. Shortly after scanning, the participants were asked to answer a questionnaire (maximal score of 20), in order to ensure their involvement in the task. The comprehension scores of the French story were significantly lower in the patients than in the controls (Table 1). 2.3. Data acquisition 2.3.1. Anatomical and functional magnetic resonance imaging (fMRI) data Neuroimaging data were acquired on a 3 T scanner (Intera Achieva 3T Quasar Dual, Philips Medical System, Netherlands) equipped with an 8-element receive head coil. Three-dimensional highresolution T1-weighted brain volumes were acquired (3D-FFE-TFE sequence, 256 × 256 matrix size with 180 contiguous slices, field of view (FOV) = 256 mm, 1 mm isotropic resolution, sagittal slice orientation, repetition time (TR) = 20 ms, echo time (TE) = 4.6 ms, flip angle (FA) = 10°, inversion time (TI) = 800 ms, SENSE factor = 2). In addition, a T2-weighted scan was acquired for each participant (T2-TSE sequence, 256 × 256 matrix size with 81 contiguous slices, FOV = 256 mm, 2 mm isotropic resolution, sagittal slice orientation, TR = 5500 ms, TE = 80 ms, FA = 90°, SENSE factor = 2). To determine the T2*-weighted functional volumes, an EPI-BOLD sequence was applied (64 × 64 matrix size with 31 contiguous slices, FOV = 240 mm, 3.75 mm isotropic resolution, axial slice orientation, TR = 2000 ms; TE = 35 ms; FA = 80°). 2.3.2. Diffusion tensor imaging (DTI) data Diffusion-weighted images (DWI) were obtained using a DWI sequence (112 × 112 matrix size with 70 contiguous slices, FOV = 224 mm, 2 mm isotropic resolution, axial slice orientation, TR = 8500 ms, TE = 81 ms, FA = 90°, SENSE factor = 2.5 to improve the signal to noise ratio (SNR)). The encoding protocol included 21 different non-collinear directions (gradient factor b = 1000 s/mm2), and one image without diffusion weighting used as reference volume (b = 0 s/mm2, b0 image). This set of 21 directions was acquired twice per participant by reversing the polarity of gradients (Hasan and Alexander, 2002). Thus, the protocol resulted in 42 DWI, acquired in 8 min. 2.4. Data analyses 2.4.1. Anatomical and fMRI data The pre-processing of these data used SPM5 software subroutines (Statistical Parametric Mapping, Wellcome Department of Cognitive Neurology, London, UK, http://www.fil.ion.ucl.ac.uk/spm), allowing us to obtain classical anatomical and functional images in MNI space (Montreal Neurological Institute, Canada). The normalization parameters were chosen by default.

Two post-processing steps were performed to calculate the functional laterality indices (FLIs) during our paradigm of interest in each participant: 2.4.1.1. Seed region obtention. From the functional data, the first step consisted of generating, for each participant, a map of the blood oxygen level-dependent (BOLD) signal contrast between the data obtained from the stimuli in French and Tamil, using SPM5. In the second step, a mean functional map was generated from the individual contrast maps for the whole population, i.e. patients with schizophrenia and controls (SPM5, one-sample t-test, threshold at p b 0.05 and corrected by family wise-error, FWE, n = 34). The regions on this mean functional map were reported conventionally in the language comprehension network (Vigneau et al., 2006, 2011; Price, 2010; Mar, 2011). Finally, this mean t-map was flipped to obtain a symmetrical functional mask, allowing us to extract the left and right homologue temporal regions used as seed regions for the following analyses (determined according to Mori's gray and white matter (GM and WM) atlas) (Mori and van, 2007) (Fig. 1). From the anatomical data, the corpus callosum (CC) was segmented in order to be used as ROI in the following analyses, allowing us to reconstruct the anatomical interhemispheric connectivity. The automated in-house segmentation method was used to extract the CC over a thickness of 10 mm, from individual WM probability maps generated in MNI space. 2.4.1.2. FLI calculation in seed regions. FLI calculation in the symmetrical temporal mask (left and right temporal clusters belonging to the language network) was computed from the Wilke and Lidzba laterality toolbox (2007), based on functional contrasts previously processed. This method applies a bootstrap algorithm to calculate FLIs at different thresholds, yielding a robust estimate of the true data distribution. A lateralization index was calculated, based on the weighted mean activation values from individual contrasts. We took into account the 5000 most activated voxels in both the left and right temporal mask, discarding clusters of less than 100 voxels, based on the following formula: FLIs = 100 × ((R − L) / (R + L)), where R and L represent the activations from individual contrasts in the right and left temporal mask, respectively. A negative index corresponded to a leftward lateralization (FLIs b 0) and a positive index to a rightward lateralization (FLIs ≥ 0). 2.4.2. DTI data First, the pre-processing of these data used FSL software subroutines (FLIRT, FMRIB Software Library, Oxford, UK, http://www.fmrib.ox.ac.uk/ fsl) allowing us to obtain diffusion maps of FA and RD (radial diffusivity), MD (in mm2/s) for each participant (DTIFIT, FMRIB's Diffusion Toolbox — FDT). FA represents the coefficient of variation of three eigenvalues of the diffusion tensor. FA is interpreted as an index of the number and density of axons or the directionality of water diffusivity into fibers (coherence). RD corresponds to perpendicular diffusivity, and is represented by the average between the second and third eigenvalues of the diffusion tensor (λ2 + λ3 / 2). MD corresponds to the mean diffusivity and is represented by the average of three eigenvalues (λ1 + λ2 + λ3 / 3). These latter two parameters are interpreted as myelination markers (Basser and Pierpaoli, 1996; Pierpaoli et al., 2001). Second, using the DWI, fiber tracking between the left temporal cluster and the right temporal cluster, crossing the CC (transferred into the DTI space), was reconstructed for each participant in native space using a probabilistic tractography method based on a multifiber model using routine parameters implemented in FSL (number of samples = 5000; curvature threshold = 0.2; maximum number of steps = 2000; step length (mm) = 0.5; FMRIB's Diffusion Toolbox — FDT) (Behrens et al., 2003; Smith et al., 2004). Compared with deterministic tractography, the applied probabilistic method allowed us to overcome a crossing-fiber effect since it estimates in each voxel a probability distribution of each fiber direction and calculates the possible

E. Leroux et al. / Schizophrenia Research 165 (2015) 30–37

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Fig. 1. Temporal interhemispheric connectivity for the whole population (n = 34). The temporal interhemispheric mean tract (in yellow) in 34 participants (p b 0.05 corrected by family wise error, FWE) was constructed between the left and right homologue temporal regions (in blue) belonging to the language network, crossing the splenium of the corpus callosum (in green).

existence of multiple fiber directions within each voxel (Behrens et al., 2007). As shown in Fig. 1, the temporal interhemispheric mean tract for the whole population (n = 34) is in accordance with the literature (Westerhausen et al., 2009). Each tract was thresholded at 10% to remove artifacts due to noise. Thirdly, a fully automated in-house normalization method was applied to each participant to register both individual diffusion maps and interhemispheric temporal tracts in the MNI space. The native T2weighted volume of each participant was registered rigidly onto the T1 acquisition, creating an rT2 image. Then, at the same time, the individual diffusion b0 image was registered rigidly and non-linearly spatially normalized onto the rT2 image. The linear registration parameters were chosen by default, whereas the spatial normalization parameters were different to optimize registration (cutoff = 45, regulation = 1, nits = 16, smooth = 0/0, tri-linear interpolation). The transformation matrix resulting from this spatial registration was combined with the transformation matrix that transferred the individual T1weighted images in the MNI space. The vector field resulting from the combination of two transformation matrices was thus applied to the individual diffusion maps and tracts to transfer them directly into standard space. Thus, this optimized registration procedure, which was applied to all participants, allowed us to overcome geometric distortions acquired with the EPI-sequence during scan acquisition, and minimize the partial volume effects observed in the MNI space. Finally, regarding DTI data post-processing, the mean values for all diffusion parameters (FA, RD and MD) were extracted in the temporal interhemispheric tract in each participant.

individual normalized comprehension score (NCS) = (individual score − mean score) / mean standard deviation. To test group differences in anatomo-functional relationships, analyses of covariance (ANCOVAs) were performed to determine the relationships between the diffusion parameters (FA, RD and MD extracted in the temporal interhemispheric tracts) and FLIs (determined between the left and right temporal clusters belonging to the language network). Three ANCOVAs were run with diffusion data as dependent variables, with the group and FLIs as independent variables. Interaction with the group × FLIs was tested and NCS as well as gender were used as covariables. As the women groups were too small (n = 4 in each group) to test an interaction between gender and groups, a similar statistical analysis without gender as covariable was carried out only in men (n = 26). To test the anatomo-functional relationships in each group, intra-group correlation analyses were also computed (r: Pearson correlation coefficient). We also conducted correlation analyses (Pearson) to evaluate the relationships between anatomical and functional variables and positive, negative, and general psychopathology sub-scores and total PANSS scores. We did not test the relationship between imaging variables and hallucination scores from the AHRS scale because only four patients presented auditory hallucinations. All statistical analyses were performed with JMP v9.0 Software (SAS Institute, Inc., Cary, NC). The significance level was set at p b 0.05 in all analyses.

2.5. Statistical analyses

3.1. Results in the whole population

A standard normal distribution transformation in each group was computed in order to normalize the comprehension score distribution:

Inter-group analyses revealed differences in FA and RD mean values in the temporal interhemispheric tracts between patients with

3. Results

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E. Leroux et al. / Schizophrenia Research 165 (2015) 30–37

schizophrenia and controls (ANCOVAs, degrees of freedom = 5, 33; FA: p = 0.030; mean ± standard deviation (m ± SD) and [range]: 0.55 ± 0.026 [0.52; 0.62] for the patient group and 0.57 ± 0.023 [0.54; 0.62] for the control group; RD: p = 0.043; patients: 0.73 ± 0.077 [0.58; 0.86] and controls: 0.67 ± 0.084 [0.51; 0.84]). The patients had a significantly decreased FA, which was associated with a significant increase in RD compared with the controls. The ANCOVAs also showed that anatomo-functional relationships between diffusion data within the temporal interhemispheric connectivity and FLIs were significantly different between the two groups for FA, RD and MD (FA: p = 0.0089; RD: p = 0.0027; MD: p = 0.0096; Fig. 2). Intra-group analyses demonstrated that patients with schizophrenia showed significant, positive relationships between RD and MD mean values and FLIs (RD: r = 0.51, p = 0.035; MD: r = 0.49, p = 0.048), suggesting higher MD or RD associated with less leftward lateralization. In contrast, the controls presented a significant negative relationship between the mean RD values and FLIs (r = −0.48, p = 0.049), suggesting higher RD values with greater leftward lateralization but they did not present significant relationships between the MD values and FLIs (r = −0.40, p = 0.11). A significant, positive relationship between the mean FA values and FLIs was also highlighted in the controls (r = 0.51, p = 0.037), interpreted as lower FA values associated with higher leftward lateralization. This relationship between FA and FLIs was not significant in patients (r = −0.38, p = 0.13). Correlation analyses between diffusion parameters, FLIs, and clinical symptoms in patients with schizophrenia revealed significant, negative correlations between mean FA values and negative (r = − 0.54, p = 0.026) and general psychopathology sub-scores (r = − 0.48, p = 0.050) and total PANSS scores (r = − 0.49, p = 0.044). No other significant correlations were detected (p N 0.05). 3.2. Additional results only in men Overall, the results were similar to those in the whole population: inter-group analyses revealed differences between men controls and men with schizophrenia in FA and a trend for RD (ANCOVAs, degrees of freedom = 4, 25; FA: p = 0.015; 0.55 ± 0.027 [0.52; 0.62] for the patients and 0.57 ± 0.025 [0.54; 0.62] for the controls; RD: p = 0.063; patients: 0.73 ± 0.085 [0.58; 0.86] and controls: 0.67 ± 0.094 [0.51; 0.84]). The men with schizophrenia had a significantly decreased FA, which was associated with an increase in RD (a trend) compared with men controls. The ANCOVAs also showed significant differences in anatomo-functional relationships between the two groups for FA, RD and MD (FA: p = 0.012; RD: p = 0.0048; MD: p = 0.015). Intra-group analyses demonstrated that men with schizophrenia showed significant, positive relationships between RD and MD mean values and FLIs (RD: r = 0.62, p = 0.025; MD: r = 0.59, p = 0.034), suggesting higher MD or RD associated with less leftward lateralization.

In contrast, the controls presented a negative relationship (a trend) between RD and FLIs (r = −0.53, p = 0.063), suggesting higher RD with greater leftward lateralization but no relationship with MD (r = −0.43, p = 0.14). A significant, positive relationship between FA and FLIs was also highlighted in the men controls (r = 0.59, p = 0.033), interpreted as lower FA associated with higher leftward lateralization. This relationship was not significant in men with schizophrenia (r = −0.45, p = 0.13). Correlation analyses between diffusion parameters, FLIs, and clinical symptoms in men with schizophrenia revealed significant, negative correlations between FA and negative (r = −0.56, p = 0.045) and general psychopathology sub-scores (a trend) (r = −0.53, p = 0.066) and total PANSS scores (r = −0.57, p = 0.043). No other significant correlations were detected (p N 0.05). 4. Discussion This multimodal imaging study is the first to show a direct relationship between the integrity of interhemispheric callosal connectivity and leftward functional cerebral lateralization for language in schizophrenia. The main result of this study, revealed in patients with schizophrenia, was that leftward functional lateralization was positively correlated to RD and MD, suggesting that reduced leftward cerebral lateralization might be accompanied by altered transcallosal connectivity. These results were observed both in all patients with schizophrenia and also in the men subgroup. 4.1. Interhemispheric integrity From a strictly anatomical point of view, the present results highlighted a WM integrity disturbance in a specific temporal interhemispheric tract in patients with schizophrenia compared with healthy participants. This abnormality was indicated by decreased FA and increased RD. In agreement with our findings, neuroimaging studies showed lower callosal integrity (through FA or RD) in either the whole CC (Miyata et al., 2010; Knochel et al., 2012; Freitag et al., 2013) or, more specifically, in the splenium region (Kyriakopoulos et al., 2008; Clemm von et al., 2014; Holleran et al., 2014; Balevich et al., 2015). These results were congruent with the investigated interhemispheric tract, since its projection, connecting homologue temporal cortical regions, crosses the splenium region. The interhemispheric tract displayed in the present study respects the structural CC topographical organization, which is coherent with functional cortical topography (Hofer and Frahm, 2006), and is in agreement with one study that highlighted an identical tract (Westerhausen et al., 2009). Nevertheless, our findings were partially comparable with the other studies. One explanation of this discrepancy is the different CC measurements, mainly area in other studies, a measurement that could not be specific to a

Fig. 2. Relationship between temporal interhemispheric connectivity and leftward language lateralization. Anatomo-functional relationships between diffusion data within the temporal interhemispheric tract and FLIs (functional laterality indices), calculated between the left and right homologue temporal regions were significantly different between the two groups for FA, RD and MD (FA: p = 0.011; RD: p = 0.046; MD: p = 0.014; ANCOVAs).

E. Leroux et al. / Schizophrenia Research 165 (2015) 30–37

particular fiber bundle connecting two regions. Otherwise, some studies used tract-based spatial statistics, based on a hypothesis-free (whole brain analyses) which restricts analyses of tracts to only a WM “skeleton”. Others used either voxel-based analyses or ROI approaches (the midsagittal surface area or volume of the CC) that are not representative of callosal projections. On the other hand, in schizophrenia, a positive correlation has been highlighted between CC structure (volume) and integrity (FA) (Rotarska-Jagiela and Linden, 2008). Thus, this loss of integrity within the temporal interhemispheric tract in patients with schizophrenia, observed in the present study, could induce an alteration in signal propagation through demyelination (increased RD) and axonal loss (decreased FA) of these callosal fibers (See Leroux et al., 2013). Regarding clinical symptom evaluation, among patients with schizophrenia, we found negative correlations between mean FA values and negative and general psychopathology sub-scores and total PANSS scores. This suggests that the global severity of illness and the severity of negative symptoms (NS) are associated with a disturbance of WM in the temporal interhemispheric tract. These results were in accordance with previous findings highlighting a negative correlation between FA values in the splenium or the temporal lobe WM and negative PANSS sub-scores (Mitelman et al., 2007; Michael et al., 2008; Balevich et al., 2015). The demonstrated impairment of WM tracts between the posterior temporal regions supports the idea that WM abnormalities are not only located in the tracts connecting the frontal regions as often reported (Wheeler and Voineskos, 2014) but also probably diffuse throughout the brain, particularly in patients with NS. 4.2. Left-hemisphere dominance and interhemispheric integrity Regarding the relationship between the interhemispheric callosal tract and the leftward lateralization for language, in healthy controls, this study highlighted the fact that participants with more leftward lateralization had lower FA associated with a higher RD, which could result in hypoconnectivity within the temporal interhemispheric tract (meaning fewer callosal fibers). In accordance with our results, Häberling et al. (2011) emphasized that left-cerebral dominance for language, also based on a robust laterality index, was associated with lower FA values throughout the CC, suggesting reduced transcallosal communication. However, these findings were in opposition with others, which revealed that left-hemisphere dominance for language in healthy participants was linked to a larger CC area (Josse et al., 2008) or greater integrity (Westerhausen et al., 2006). From these observations, all the aforementioned authors have attempted to advance suggestions about the functional role of the CC, with two opposing theories (Bloom and Hynd, 2005; Nowicka and Tacikowski, 2011; van der Knaap and van der Ham, 2011). Thus, the findings of Josse et al. (2008) and Westerhausen et al. (2006) support the predictions of the inhibitory model, which presumes that the CC maintains independent processing between the two hemispheres, hindering activity in the opposite hemisphere and causing greater connectivity to increase laterality effects. On the contrary, the findings of Häberling et al. (2011) reinforce the excitatory model postulating that the CC shares and integrates information between hemispheres, causing greater connectivity to decrease laterality effects. However, any such interpretation of the functional role of interhemispheric connections remains speculative. Firstly, because the results previously presented are very heterogenic, and secondly, because the CC is a very complex structure composed of several transcallosal channels varying in the number, size, composition and destination of these fibers (LaMantia and Rakic, 1990; Aboitiz and Zaidel, 1992). Thus, its functional role may differ according to the task in question (i.e. cognitive process involved), which involves a particular transcallosal channel. Beyond the functional role of the CC, the direction of the relationship between structure and function remains elusive, and there exists much

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debate regarding the different possible explanations for the relationship between the CC and the HS. One possibility is that functional lateralization determines callosal anatomical connectivity. We can speculate that healthy controls with a stronger functional lateralization for language require lesser interhemispheric connectivity, which is in accordance with previous reports that cerebral lateralization is essentially ordained from birth and does not evolve thereafter (Hellige, 1993). A second possibility is that CC connectivity determines functional lateralization. Indeed, many studies focused on HS origins have defended this idea based on the evolutionary theory. It has been suggested that the development of brain lateralization might be driven by an increase in interhemispheric conduction time induced by the increase in brain size (Ringo et al., 1994; Jancke et al., 1997; Rilling and Insel, 1999; Gazzaniga, 2000; Olivares et al., 2001; Aboitiz et al., 2003). In order to compensate for the increase in brain size with evolution, the transfer of information across longer distances in larger brains (i.e. from one hemisphere to the other) led to axonal pruning, reducing the degree of interhemispheric connectivity and, on the contrary, facilitating the development of intrahemispheric communications in order to promote local networks which are specialized and optimized for particular cognitive functions. Thus, our results in healthy participants fit this hypothesis where temporal interhemispheric connectivity was reduced in participants who were extremely leftward-lateralized. On the other hand, we revealed a different pattern in schizophrenia. Indeed, we showed that reduced leftward functional lateralization for language in patients with schizophrenia was correlated to altered callosal integrity, reflecting less and/or slower interhemispheric communication between the two hemispheres. On the contrary, the most leftward-lateralized patients displayed more communication within their interhemispheric circuitry, which could be due to faulty pruning mechanisms. Otherwise, we also revealed similar findings in the men subgroup with schizophrenia. Witelson and Nowakowski (1991) suggested that the course of loss of callosal axons was associated with a sex-related influence, specifying that the left out axons make men right. These results could be extrapolated from our findings as left out axons (i.e. fewer callosal fiber, which are demyelinated; decreased FA and increased RD/MD, respectively) make men with schizophrenia less lateralized and less able to comprehend speech than men who are more lateralized and do not have schizophrenia. Whether differences between men and women in healthy participants were reported as reversed compared with patients with schizophrenia (Highley et al., 1999; Savadjiev et al., 2014), our results observed both in the whole population and in the men subgroup were not in favor of such differences. Indeed, whether men have a greater intrahemispheric connectivity or lower FA in the CC and women a predominant interhemispheric connectivity (Ingalhalikar et al., 2014) or higher FA in the CC as described elsewhere (Kanaan et al., 2014), we would have found significant results in the men groups but not in the whole sample. However, the small group of women did not allow us to test reversed relationships between patients with schizophrenia and healthy participants. A third possible explanation is that WM integrity deficit may not be directly related to a reduced functional lateralization. Indeed, the CC deficits observed in schizophrenia could be a part of global WM deficits, which develop much later than language lateralization and therefore would not necessarily be related to the degree of lateralization. Indeed, the age at which the mean cerebral FA reaches its maximum overlaps with the mean age of onset of schizophrenia (Kochunov et al., 2011). However, structural brain asymmetries are evident in utero (Bishop, 2013). For example, the leftward asymmetry of planum temporale, underlying the left hemispheric dominance for language, is established by 31 weeks of gestation (Chi et al., 1977). The reduced leftward hemispheric lateralization and WM disturbance observed in schizophrenia (Razafimandimby et al., 2009; Wheeler and Voineskos, 2014) suggest distinct causes underlying these abnormalities. Indeed, we can speculate that certain genes may be involved in both processes, as suggested in recent reports (Crow, 2012; Goudriaan et al., 2014).

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4.3. Limits of the study The major limit of this study concerned the small size of women group that did not allow us to test reversed anatomo-functional gender differences in patients with schizophrenia and healthy participants. Thus, the potential inverse pattern in the anatomo-functional relationships between men and women in the healthy participants and the patients with schizophrenia are still unclear. Future works are necessary in order to determinate whether a sexual dimorphism could also explain the disturbed relationship between laterality and interhemispheric connectivity in patients with schizophrenia. In conclusion, this present study was performed to complete the large-scale disorganization patterns observed in schizophrenia. The results revealed a relationship between the CC and the HS for language, but did not provide evidence clarifying the direction of the relationship between callosal connectivity and functional lateralization for language. In particular, the present findings showed that the loss of integrity in interhemispheric callosal fibers was associated with reduced leftward cerebral dominance for language in patients with schizophrenia. Role of funding source This work was supported by the French Health Ministry in a ‘Programme Hospitalier de Recherche Clinique (PHRC, APR, R06-5)’. Funding sources were not involved in the study design, collection, analysis and interpretation of data, writing the report or the decision to submit the paper for publication. Contributors Professor Sonia Dollfus designed the study. Professors Sonia Dollfus, Perrine Brazo and Pascal Delamillieure recruited and evaluated the patients. Mrs. Annick Razafimandimby and Pr. Sonia Dollfus acquired the scans. Mrs. Elise Leroux reviewed the literature. Mrs. Elise Leroux and Mr. Nicolas Delcroix managed analyses and undertook the statistical analyses. Pr. Sonia Dollfus and Mrs. Elise Leroux interpreted the data. Dr. Elise Leroux wrote the first draft of the manuscript. Pr. Sonia Dollfus revised it and all the authors have approved the final manuscript. Conflict of interest The authors have declared that there are no conflicts of interest in relation to the participants or personnel involved in this study or the financial organization. Acknowledgments We thank A. Razafimandimby for technical assistance, F. Lamberton for his collaboration with regard to the DTI sequences and data pre-processing, Drs. P. Brazo and P. Delamillieure for their clinical contribution and N. Tzourio-Mazoyer for providing the language task. We also thank the French Health Ministry that funded this research as a ‘Programme Hospitalier de Recherche Clinique (PHRC)’.

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