White Matter Bundles Research Articles

White matter in temporal lobe epilepsy: clinico-pathological correlates of water diffusion abnormalities.

Using magnetic resonance imaging, it is possible to measure the behavior of diffusing water molecules, and the metrics derived can be used as indirect markers of tissue micro-architectural properties. Numerous reports have demonstrated that patients with temporal lobe epilepsy (TLE) have water diffusion abnormalities in several white matter structures located within and beyond the epileptogenic temporal lobe, showing that TLE is not a focal disorder, but rather a brain network disease. Differences in severity and spatial extent between patients with or without mesial temporal sclerosis (MTS), as well as differences related to hemispheric seizure onset, are suggestive of different pathophysiological mechanisms behind different forms of TLE, which in turn result in specific cognitive disabilities. The biological interpretation of diffusion abnormalities is based on a wealth of information from animal models of white matter damage, and is supported by recent reports that directly correlate diffusion metrics with histological characteristics of surgical specimens of TLE patients. Thus, there is now more evidence showing that the increased mean diffusivity (MD) and concomitant reductions of diffusion anisotropy that are frequently observed in several white matter bundles in TLE patients reflect reduced axonal density (increased extra-axonal space) due to smaller-caliber axons, and abnormalities in the myelin sheaths of the remaining axons. Whether these histological and diffusion features are a predisposing factor for epilepsy or secondary to seizures is still uncertain; some reports suggest the latter. This article summarizes recent findings in this field and provides a synopsis of the histological features seen most frequently in post-surgical specimens of TLE patients in an effort to aid the interpretation of white matter diffusion abnormalities.

Deferoxamine reduces intracerebral hemorrhage-induced white matter damage in aged rats

Iron contributes to c-Jun N-terminal kinases (JNK) activation in young rats and white matter injury in piglets after intracerebral hemorrhage (ICH). In the present study, we examined the effect of deferoxamine on ICH-induced white matter injury and JNK activation and in aged rats. Male Fischer 344 rats (18months old) had either an intracaudate injection of 100μl of autologous blood or a needle insertion (sham). The rats were treated with deferoxamine or vehicle with different regimen (dosage, duration and time window). White matter injury and activation of JNK were examined. We found that a dose of DFX should be at more than 10mg/kg for a therapeutic duration more than 2days with a therapeutic time window of 12h to reduce ICH-induced white matter loss at 2months. ICH-induced white matter injury was associated with JNK activation. The protein levels of phosphorylated-JNK (P-JNK) were upregulated at day-1 after ICH and then gradually decreased. P-JNK immunoreactivity was mostly located in white matter bundles. ICH-induced JNK activation was reduced by DFX treatment. This study demonstrated that DFX can reduce ICH-induced JNK activation and white matter damage.

Using Multimodal MRI Data to Classify Patients with First Episode Psychosis

Introduction currently, most of the classification studies of psychosis focused on chronic patients and employed single machine learning approaches. To overcome these limitations, we here compare, to our best knowledge for the first time, different classification methods of First Episode Psychosis (FEP) using multimodal imaging data exploited on several cortical and subcortical structures and white matter fiber bundles. Methods 23 FEP patients and 23 age-, gender-, and race-matched healthy participants were included in the study. An innovative multivariate approach based on Multiple Kernel Learning (MKL) methods was implemented on structural MRI (sMRI) and diffusion tensor imaging (DTI). Results MKL provides the best classification performances in comparison with the more widely used Support Vector Machine, enabling the definition of a reliable automatic decisional system based on the integration of multimodal imaging information. Our results show a discrimination accuracy greater than 90% between healthy subjects and patients with FEP. Regions with an accuracy greater than 70% on different imaging sources and measures were middle and superior frontal gyrus, parahippocampal gyrus, uncinate fascicles and cingulum. Conclusions this study shows that multivariate machine learning approaches integrating multimodal and multisource imaging data can classify FEP patients with high accuracy. Interestingly, specific grey matter structures and white matter bundles reach high classification reliability when using different imaging modalities and indices, potentially outlining a prefronto-limbic network impaired in FEP with particular regard to the right hemisphere.

The Fornix in Mild Cognitive Impairment and Alzheimer’s Disease

The fornix is an integral white matter bundle located in the medial diencephalon and is part of the limbic structures. It serves a vital role in memory functions and as such has become the subject of recent research emphasis in Alzheimer’s disease (AD) and mild cognitive impairment (MCI). As the characteristic pathological processes of AD progress, structural and functional changes to the medial temporal lobes and other regions become evident years before clinical symptoms are present. Though gray matter atrophy has been the most studied, degradation of white matter structures especially the fornix may precede these and has become detectable with use of diffusion tensor imaging (DTI) and other complimentary imaging techniques. Recent research utilizing DTI measurement of the fornix has shown good discriminability of diagnostic groups, particularly early and preclinical, as well as predictive power for incident MCI and AD. Stimulating and modulating fornix function by the way of DBS has been an exciting new area as pharmacological therapeutics has been slow to develop.

White matter lesional predictors of chronic visual neglect: a longitudinal study.

Chronic visual neglect prevents brain-damaged patients from returning to an independent and active life. Detecting predictors of persistent neglect as early as possible after the stroke is therefore crucial to plan the relevant interventions. Neglect signs do not only depend on focal brain lesions, but also on dysfunction of large-scale brain networks connected by white matter bundles. We explored the relationship between markers of axonal degeneration occurring after the stroke and visual neglect chronicity. A group of 45 patients with unilateral strokes in the right hemisphere underwent cognitive testing for neglect twice, first at the subacute phase (<3 months after onset) and then at the chronic phase (>1 year). For each patient, magnetic resonance imaging including diffusion sequences was performed at least 4 months after the stroke. After masking each patient's lesion, we used tract-based spatial statistics to obtain a voxel-wise statistical analysis of the fractional anisotropy data. Twenty-seven patients had signs of visual neglect at initial testing. Only 10 of these patients had recovered from neglect at follow-up. When compared with patients without neglect, the group including all subacute neglect patients had decreased fractional anisotropy in the second (II) and third (III) branches of the right superior longitudinal fasciculus, as well as in the splenium of the corpus callosum. The subgroup of chronic patients showed reduced fractional anisotropy in a portion the splenium, the forceps major, which provides interhemispheric communication between regions of the occipital lobe and of the superior parietal lobules. The severity of neglect correlated with fractional anisotropy values in superior longitudinal fasciculus II/III for subacute patients and in its caudal portion for chronic patients. Our results confirm a key role of fronto-parietal disconnection in the emergence and chronic persistence of neglect, and demonstrate an implication of caudal interhemispheric disconnection in chronic neglect. Splenial disconnection may prevent fronto-parietal networks in the left hemisphere from resolving the activity imbalance with their right hemisphere counterparts, thus leading to persistent neglect.

Automated multi-subject fiber clustering of mouse brain using dominant sets.

Mapping of structural and functional connectivity may provide deeper understanding of brain function and disfunction. Diffusion Magnetic Resonance Imaging (DMRI) is a powerful technique to non-invasively delineate white matter (WM) tracts and to obtain a three-dimensional description of the structural architecture of the brain. However, DMRI tractography methods produce highly multi-dimensional datasets whose interpretation requires advanced analytical tools. Indeed, manual identification of specific neuroanatomical tracts based on prior anatomical knowledge is time-consuming and prone to operator-induced bias. Here we propose an automatic multi-subject fiber clustering method that enables retrieval of group-wise WM fiber bundles. In order to account for variance across subjects, we developed a multi-subject approach based on a method known as Dominant Sets algorithm, via an intra- and cross-subject clustering. The intra-subject step allows us to reduce the complexity of the raw tractography data, thus obtaining homogeneous neuroanatomically-plausible bundles in each diffusion space. The cross-subject step, characterized by a proper space-invariant metric in the original diffusion space, enables the identification of the same WM bundles across multiple subjects without any prior neuroanatomical knowledge. Quantitative analysis was conducted comparing our algorithm with spectral clustering and affinity propagation methods on synthetic dataset. We also performed qualitative analysis on mouse brain tractography retrieving significant WM structures. The approach serves the final goal of detecting WM bundles at a population level, thus paving the way to the study of the WM organization across groups.

The search of the "intact" structural and functional brain systems as a paradigm shift in schizophrenia research

The search of the structural and functional brain characteristics is one of the most studied directions in the modern biological psychiatry. However, in spite of the numerous studies the results are still controversial. As the necessity of the shift of the current paradigm in schizophrenia research evolves it has been suggested to discriminate not only abnormal but stable functioning neuronal circuits as well. Consequently, the aim is formulated as the search of the minimal brain damage sufficient for disease development. Author analyzed the auditory oddball P300 latency (as a marker of information processing speed), N-acetylaspartate level in the dorsolateral prefrontal cortex (as a marker of neuronal integrity in this brain area) and fractional anisotropy of the fasciculus uncindtus which connects the frontal and temporal lobes (as a marker of white matter bundles microstructure) in 30 patients with schizophrenia and 27 healthy people. The findings showed that all the tested characteristics are not "obligatory" for schizophrenia.

The Classical Pathways of Occipital Lobe Epileptic Propagation Revised in the Light of White Matter Dissection.

The clinical evidences of variable epileptic propagation in occipital lobe epilepsy (OLE) have been demonstrated by several studies. However the exact localization of the epileptic focus sometimes represents a problem because of the rapid propagation to frontal, parietal, or temporal regions. Each white matter pathway close to the supposed initial focus can lead the propagation towards a specific direction, explaining the variable semiology of these rare epilepsy syndromes. Some new insights in occipital white matter anatomy are herein described by means of white matter dissection and compared to the classical epileptic patterns, mostly based on the central position of the primary visual cortex. The dissections showed a complex white matter architecture composed by vertical and longitudinal bundles, which are closely interconnected and segregated and are able to support specific high order functions with parallel bidirectional propagation of the electric signal. The same sublobar lesions may hyperactivate different white matter bundles reemphasizing the importance of the ictal semiology as a specific clinical demonstration of the subcortical networks recruited. Merging semiology, white matter anatomy, and electrophysiology may lead us to a better understanding of these complex syndromes and tailored therapeutic options based on individual white matter connectivity.

In vivo DTI tractography of the rat brain: an atlas of the main tracts in Paxinos space with histological comparison

Diffusion tensor imaging (DTI) is a magnetic resonance modality that permits to characterize the orientation and integrity of white matter (WM). DTI-based tractography techniques, allowing the virtual reconstruction of WM tract pathways, have found wide application in preclinical neurological research. Recently, anatomically detailed rat brain atlases including DTI data were constructed from ex vivo DTI images, but tractographic atlases of normal rats in vivo are still lacking. We propose here a probabilistic tractographic atlas of the main WM tracts in the healthy rat brain based on in vivo DTI acquisition. Our study was carried out on 10 adult female Sprague–Dawley rats using a 7T preclinical scanner. The MRI protocol permitted a reliable reconstruction of the main rat brain bundles: corpus callosum, cingulum, external capsule, internal capsule, anterior commissure, optic tract. The reconstructed fibers were compared with histological data, proving the viability of in vivo DTI tractography in the rat brain with the proposed acquisition and processing protocol. All the data were registered to a rat brain template in the coordinate system of the commonly used atlas by Paxinos and Watson; then the individual tracts were binarized and averaged, obtaining a probabilistic atlas in Paxinos–Watson space of the main rat brain WM bundles. With respect to the recent high-resolution MRI atlases, the resulting tractographic atlas, available online, provides complementary information about the average anatomical position of the considered WM tracts and their variability between normal animals. Furthermore, reference values for the main DTI-derived parameters, mean diffusivity and fractional anisotropy, were provided. Both these results can be used as references in preclinical studies on pathological rat models involving potential alterations of WM.

Classification of first-episode psychosis: a multi-modal multi-feature approach integrating structural and diffusion imaging.

Currently, most of the classification studies of psychosis focused on chronic patients and employed single machine learning approaches. To overcome these limitations, we here compare, to our best knowledge for the first time, different classification methods of first-episode psychosis (FEP) using multi-modal imaging data exploited on several cortical and subcortical structures and white matter fiber bundles. 23 FEP patients and 23 age-, gender-, and race-matched healthy participants were included in the study. An innovative multivariate approach based on multiple kernel learning (MKL) methods was implemented on structural MRI and diffusion tensor imaging. MKL provides the best classification performances in comparison with the more widely used support vector machine, enabling the definition of a reliable automatic decisional system based on the integration of multi-modal imaging information. Our results show a discrimination accuracy greater than 90 % between healthy subjects and patients with FEP. Regions with an accuracy greater than 70 % on different imaging sources and measures were middle and superior frontal gyrus, parahippocampal gyrus, uncinate fascicles, and cingulum. This study shows that multivariate machine learning approaches integrating multi-modal and multisource imaging data can classify FEP patients with high accuracy. Interestingly, specific grey matter structures and white matter bundles reach high classification reliability when using different imaging modalities and indices, potentially outlining a prefronto-limbic network impaired in FEP with particular regard to the right hemisphere.

Deformation of the corona radiata and internal capsule in normal pressure hydrocephalus

Background and purposeThe pathophysiology of the clinical manifestations in normal pressure hydrocephalus (NPH) remains obscure. Ventricular dilatation could generate forces on the paracentral fibers of the corona radiata (CR), hence interfering with their function and producing the classical clinical triad. The analysis of the regional displacement and deformation of the white matter bundles, forming the corona radiata and internal capsule, may clarify the relationship between ventricular dilatation and clinical manifestations in NPH. MethodAn experimental finite element (FE) analysis was used to simulate ventricular dilatation in 3 dimensions (3D) and to calculate the strain and deformation on the surrounding parenchyma. Magnetic resonance diffusion tensor imaging-based white matter tractography was then applied to retrieve the displacement and deformation exerted along various fiber bundles of the corona radiata and internal capsule. Anterior and posterior limb displacements and elongations were compared using a paired samples t-test. ResultsThe internal capsule, hence the corona radiata, of each cerebral hemisphere was segmented into anterior and posterior limbs. Mean displacements and elongations were calculated for each limb. Mean displacement was significantly larger in the anterior limb whereas mean deformation was larger in the posterior limb (P<0.01). ConclusionThe present simulation demonstrates that ventricular dilatation does not have a homogeneous effect on the periventricular fibre tracts, with a particular load on the corticospinal tract. The affection of this tract remains thereby a potential factor in the generation of the NPH gait disorders.

Organising white matter in a brain without corpus callosum fibres

Isolated corpus callosum dysgenesis (CCD) is a congenital malformation which occurs during early development of the brain. In this study, we aimed to identify and describe its consequences beyond the lack of callosal fibres, on the morphology, microstructure and asymmetries of the main white matter bundles with diffusion imaging and fibre tractography. Seven children aged between 9 and 13 years old and seven age- and gender-matched control children were studied. First, we focused on bundles within the mesial region of the cerebral hemispheres: the corpus callosum, Probst bundles and cingulum which were selected using a conventional region-based approach. We demonstrated that the Probst bundles have a wider connectivity than the previously described rostrocaudal direction, and a microstructure rather distinct from the cingulum but relatively close to callosal remnant fibres. A sigmoid bundle was found in two partial ageneses. Second, the corticospinal tract, thalamic radiations and association bundles were extracted automatically via an atlas of adult white matter bundles to overcome bias resulting from a priori knowledge of the bundles' anatomical morphology and trajectory. Despite the lack of callosal fibres and the colpocephaly observed in CCD, all major white matter bundles were identified with a relatively normal morphology, and preserved microstructure (i.e. fractional anisotropy, mean diffusivity) and asymmetries. Consequently the bundles' organisation seems well conserved in brains with CCD. These results await further investigations with functional imaging before apprehending the cognition variability in children with isolated dysgenesis.

Alzheimer's disease and the fornix.

Alzheimer’s disease (AD) is the most common form of neurodegenerative dementia. Researchers have long been focused on the cortical pathology of AD, since the most important pathologic features are the senile plaques found in the cortex, and the neurofibrillary tangles and neuronal loss that begin in the entorhinal cortex and the hippocampus. In addition to these gray matter (GM) structures, histopathological studies indicate that the white matter (WM) is also a good target for both the early diagnosis of AD and for monitoring disease progression. The fornix is a WM bundle that constitutes a core element of the limbic circuits, and is one of the most important anatomical structures related to memory. Functional and anatomical features of the fornix have naturally captured researchers’ attention as possible diagnostic and prognostic markers of AD. Indeed, neurodegeneration of the fornix has been histologically observed in AD, and growing evidence indicates that the alterations seen in the fornix are potentially a good marker to predict future conversion from mild cognitive impairment (MCI) to AD, and even from cognitively normal individuals to AD. The degree of alteration is correlated with the degree of memory impairment, indicating the potential for the use of the fornix as a functional marker. Moreover, there have been attempts to stimulate the fornix using deep brain stimulation (DBS) to augment cognitive function in AD, and ongoing research has suggested positive effects of DBS on brain glucose metabolism in AD patients. On the other hand, disease specificity for fornix degeneration, methodologies to evaluate fornix degeneration, and the clinical significance of the fornix DBS, especially for the long-term impact on the quality of life, are mostly unknown and need to be elucidated.

Alterations in fiber pathways reveal brain tumor typology: a diffusion tractography study.

Conventional structural Magnetic Resonance (MR) techniques can accurately identify brain tumors but do not provide exhaustive information about the integrity of the surrounding/embedded white matter (WM). In this study, we used Diffusion-Weighted (DW) MRI tractography to explore tumor-induced alterations of WM architecture without any a priori knowledge about the fiber paths under consideration. We used deterministic multi-fiber tractography to analyze 16 cases of histologically classified brain tumors (meningioma, low-grade glioma, high-grade glioma) to evaluate the integrity of WM bundles in the tumoral region, in relation to the contralateral unaffected hemisphere. Our new tractographic approach yielded measures of WM involvement which were strongly correlated with the histopathological features of the tumor (r = 0.83, p = 0.0001). In particular, the number of affected fiber tracts were significantly (p = 0.0006) different among tumor types. Our method proposes a new application of diffusion tractography for the detection of tumor aggressiveness in those cases in which the lesion does not involve any major/known WM paths and when a priori information about the local fiber anatomy is lacking.

Multimodal fMRI Resting-State Functional Connectivity in Granulin Mutations: The Case of Fronto-Parietal Dementia

BackgroundMonogenic dementias represent a great opportunity to trace disease progression from preclinical to symptomatic stages. Frontotemporal Dementia related to Granulin (GRN) mutations presents a specific framework of brain damage, involving fronto-temporal regions and long inter-hemispheric white matter bundles. Multimodal resting-state functional MRI (rs-fMRI) is a promising tool to carefully describe disease signature from the earliest disease phase.ObjectiveTo define local connectivity alterations in GRN related pathology moving from the presymptomatic (asymptomatic GRN mutation carriers) to the clinical phase of the disease (GRN- related Frontotemporal Dementia).MethodsThirty-one GRN Thr272fs mutation carriers (14 patients with Frontotemporal Dementia and 17 asymptomatic carriers) and 38 healthy controls were recruited. Local connectivity measures (Regional Homogeneity (ReHo), Fractional Amplitude of Low Frequency Fluctuation (fALFF) and Degree Centrality (DC)) were computed, considering age and gender as nuisance variables as well as the influence of voxel-level gray matter atrophy.ResultsAsymptomatic GRN carriers had selective reduced ReHo in the left parietal region and increased ReHo in frontal regions compared to healthy controls. Considering Frontotemporal Dementia patients, all measures (ReHo, fALFF and DC) were reduced in inferior parietal, frontal lobes and posterior cingulate cortex. Considering GRN mutation carriers, an inverse correlation with age in the posterior cingulate cortex, inferior parietal lobule and orbitofrontal cortex was found.Conclusions GRN pathology is characterized by functional brain network alterations even decades before the clinical onset; they involve the parietal region primarily and then spread to the anterior regions of the brain, supporting the concept of molecular nexopathies.

Multi-parametric evaluation of the white matter maturation.

In vivo evaluation of the brain white matter maturation is still a challenging task with no existing gold standards. In this article we propose an original approach to evaluate the early maturation of the white matter bundles, which is based on comparison of infant and adult groups using the Mahalanobis distance computed from four complementary MRI parameters: quantitative qT1 and qT2 relaxation times, longitudinal λ║ and transverse λ⊥ diffusivities from diffusion tensor imaging. Such multi-parametric approach is expected to better describe maturational asynchrony than conventional univariate approaches because it takes into account complementary dependencies of the parameters on different maturational processes, notably the decrease in water content and the myelination. Our approach was tested on 17 healthy infants (aged 3- to 21-week old) for 18 different bundles. It finely confirmed maturational asynchrony across the bundles: the spino-thalamic tract, the optic radiations, the cortico-spinal tract and the fornix have the most advanced maturation, while the superior longitudinal and arcuate fasciculi, the anterior limb of the internal capsule and the external capsule have the most delayed maturation. Furthermore, this approach was more reliable than univariate approaches as it revealed more maturational relationships between the bundles and did not violate a priori assumptions on the temporal order of the bundle maturation. Mahalanobis distances decreased exponentially with age in all bundles, with the only difference between them explained by different onsets of maturation. Estimation of these relative delays confirmed that the most dramatic changes occur during the first post-natal year.Electronic supplementary materialThe online version of this article (doi:10.1007/s00429-014-0881-y) contains supplementary material, which is available to authorized users.

Tract-based spatial statistics of diffusion tensor imaging after corpus callosotomy in relation to seizure recurrence.

To delineate microstructural changes in transected white matter tracts after corpus callosotomy in relation to seizure recurrence using tract-based spatial statistics of diffusion tensor imaging (DTI-TBSS). We retrospectively included 12 total corpus callosotomy patients who had undergone serial pre- and postoperative DTI studies. The first postoperative DTI was performed within 6 months after callosotomy. The second postoperative DTI was performed in five patients with seizure recurrence (symptomatic group) and in seven patients without seizure recurrence (asymptomatic group) after 1 year following surgery. Group comparisons of fractional anisotropy (FA) with age- and sex-matched controls were performed in a whole brain voxel-wise manner using DTI-TBSS. The first postoperative DTI-TBSS showed a significant FA decrease in the entire corpus callosum in all patients. The second postoperative DTI-TBSS showed that a significant FA decrease remained in the entire corpus callosum in the asymptomatic group. However, in the symptomatic group, no significant decrease of FA was observed in some parts of the posterior body and splenium of the corpus callosum, although there was still a significant FA decrease in the genu of the corpus callosum. Using DTI-TBSS analysis, we characterized and visualized microstructural white matter changes over time in relation to seizure recurrence in callosotomy patients, suggesting that reorganization of some transected white matter tracts may be related to seizure recurrence. DTI-TBSS analysis can provide reliable and useful information about the state of white matter bundles affected by corpus callosotomy in a noninvasive manner.

Multi-label segmentation of white matter structures: Application to neonatal brains

Accurate and consistent segmentation of brain white matter bundles at neonatal stage plays an important role in understanding brain development and detecting white matter abnormalities for the prediction of psychiatric disorders. Due to the complexity of white matter anatomy and the spatial resolution of diffusion-weighted MR imaging, multiple fiber bundles can pass through one voxel. The goal of this study is to assign one or multiple anatomical labels of white matter bundles to each voxel to reflect complex white matter anatomy of the neonatal brain. For this, we develop a supervised multi-label k-nearest neighbor (ML-kNN) classification algorithm in Riemannian diffusion tensor spaces. Our ML-kNN considers diffusion tensors lying on the Log-Euclidean Riemannian manifold of symmetric positive definite (SPD) matrices and their corresponding vector space as feature space. The ML-kNN utilizes the maximum a posteriori (MAP) principle to make the prediction of white matter labels by reasoning with the labeling information derived from the neighbors without assuming any probabilistic distribution of the features. We show that our approach automatically learns the number of white matter bundles at a location and provides anatomical annotation of the neonatal white matter. In addition, our approach also provides the binary mask for individual white matter bundles to facilitate tract-based statistical analysis in clinical studies. We apply this method to automatically segment 13 white matter bundles of the neonatal brain and examine the segmentation accuracy against semi-manual labels derived from tractography.

Microanatomical study of the insular perforating arteries.

The insular perforating arteries originate from the middle cerebral artery. They have only been very partially described up to now. In the literature, they come from the M2 segment and three types are listed: the short, medium and long perforators. The first two types supply the claustrum as well as the external and extreme capsules. We describe the anatomy of long perforating insular arteries and their arterial contribution to the main white matter bundles of the oval center of Vieussens. Twenty adult cadaveric hemispheres were studied after perfusion of the arteries and veins with colored latex. The arteries were dissected and photographed under an operating microscope. The long insular perforating arteries come from the M2 segment or from the junction of the M2 and M3 segments and sometimes from the M3 segment. They often perforate the insular cortex on the top of the posterior short insular gyrus and the insular long gyri, or in the superior peri-insular sulcus, before coming together in the oval center. At this level, they give arterial contribution to the main white matter bundles such as corticospinal and corticonuclear tracts for motricity, and the arcuate fasciculus and the occipitofrontal tract for language in the dominant hemisphere. These perforating arteries have to be carefully respected during insular surgery to avoid neurologic weakness.

Sentence processing and verbal working memory in a white-matter-disconnection patient

The Arcuate Fasciculus/Superior Longitudinal Fasciculus (AF/SLF) is the white-matter bundle that connects posterior superior temporal and inferior frontal cortex. Its causal functional role in sentence processing and verbal working memory is currently under debate. While impairments of sentence processing and verbal working memory often co-occur in patients suffering from AF/SLF damage, it is unclear whether these impairments result from shared white-matter damage to the verbal-working-memory network. The present study sought to specify the behavioral consequences of focal AF/SLF damage for sentence processing and verbal working memory, which were assessed in a single patient suffering from a cleft-like lesion spanning the deep left superior temporal gyrus, sparing most surrounding gray matter. While tractography suggests that the ventral fronto-temporal white-matter bundle is intact in this patient, the AF/SLF was not visible to tractography. In line with the hypothesis that the AF/SLF is causally involved in sentence processing, the patient׳s performance was selectively impaired on sentences that jointly involve both complex word orders and long word-storage intervals. However, the patient was unimpaired on sentences that only involved long word-storage intervals without involving complex word orders. On the contrary, the patient performed generally worse than a control group across standard verbal-working-memory tests. We conclude that the AF/SLF not only plays a causal role in sentence processing, linking regions of the left dorsal inferior frontal gyrus to the temporo-parietal region, but moreover plays a crucial role in verbal working memory, linking regions of the left ventral inferior frontal gyrus to the left temporo-parietal region. Together, the specific sentence-processing impairment and the more general verbal-working-memory impairment may imply that the AF/SLF subserves both sentence processing and verbal working memory, possibly pointing to the AF and SLF respectively supporting each.