Search

The contribution of age-related structural brain changes to the well-established link between aging and cognitive decline is not fully defined. While both age-related regional brain atrophy and cognitive decline have been extensively studied, the specific mediating role of age-related regional brain atrophy on cognitive functions is unclear. This study introduces an open-source software tool with a graphical user interface that streamlines advanced whole-brain mediation analyses, enabling researchers to systematically explore how the brain acts as a mediator in relationships between various behavioral and health outcomes. The tool is showcased by investigating regional brain volume as a mediator to determine the contribution of age-related brain volume loss toward cognition in healthy aging. We analyzed regional brain volumes and cognitive testing data (Montreal Cognitive Assessment [MoCA]) from a cohort of 131 neurologically healthy adult participants (mean age 50 ± 20.8 years, range 20-79, 73% females) drawn from the Aging Brain Cohort Study at the University of South Carolina. Using our open-source tool developed for evaluating brain-behavior associations across the brain and optimized for exploring mediation effects, we conducted a series of mediation analyses using participant age as the predictor variable, total MoCA and MoCA subtest scores as the outcome variables, and regional brain volume as potential mediators. Age-related atrophy within specific anatomical networks was found to mediate the relationship between age and cognition across multiple cognitive domains. Specifically, atrophy in bilateral frontal, parietal, and occipital areas, along with widespread subcortical regions mediated the effect of age on total MoCA scores. Various MoCA subscores were influenced by age through atrophy in distinct brain regions. These involved prefrontal regions, sensorimotor cortex, and parieto-occipital areas for executive function subscores, prefrontal and temporo-occipital regions, along with the caudate nucleus for attention and concentration subscores, frontal and parieto-occipital areas, alongside connecting subcortical areas such as the optic tract for visuospatial subscores and frontoparietal areas for language subscores. Brain-based mediation analysis offers a causal framework for evaluating the mediating role of brain structure on the relationship between age and cognition and provides a more nuanced understanding of cognitive aging than previously possible. By validating the applicability and effectiveness of this approach and making it openly available to the scientific community, we facilitate the exploration of causal mechanisms between variables mediated by the brain., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

In recent years, the relationship between age-related hearing loss, cognitive decline, and the risk of dementia has garnered significant attention. The significant variability in brain health and aging among individuals of the same chronological age suggests that a measure assessing how one's brain ages may better explain hearing-cognition links. The main aim of this study was to investigate the mediating role of Brain Age Gap (BAG) in the association between hearing impairment and cognitive function. This research included 185 participants aged 20-79 years. BAG was estimated based on the difference between participant's brain age (estimated based on their structural T1-weighted MRI scans) and chronological age. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA) test while hearing ability was measured using pure-tone thresholds (PTT) and words-in-noise (WIN) perception. Mediation analyses were used to examine the mediating role of BAG in the relationship between age-related hearing loss as well as difficulties in WIN perception and cognition. Participants with poorer hearing sensitivity and WIN perception showed lower MoCA scores, but this was an indirect effect. Participants with poorer performance on PTT and WIN tests had larger BAG (accelerated brain aging), and this was associated with poorer performance on the MoCA test. Mediation analyses showed that BAG partially mediated the relationship between age-related hearing loss and cognitive decline. This study enhances our understanding of the interplay among hearing loss, cognition, and BAG, emphasizing the potential value of incorporating brain age assessments in clinical evaluations to gain insights beyond chronological age, thus advancing strategies for preserving cognitive health in aging populations., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Inc.)

Premature brain aging is associated with poorer cognitive reserve and lower resilience to injury. When there are focal brain lesions, brain regions may age at different rates within the same individual. Therefore, we hypothesize that reduced gray matter volume within specific brain systems commonly associated with language recovery may be important for long-term aphasia severity. Here we show that individuals with stroke aphasia have a premature brain aging in intact regions of the lesioned hemisphere. In left domain-general regions, premature brain aging, gray matter volume, lesion volume and age were all significant predictors of aphasia severity. Increased brain age following a stroke is driven by the lesioned hemisphere. The relationship between brain age in left domain-general regions and aphasia severity suggests that degradation is possible to specific brain regions and isolated aging matters for behavior., (© 2024. The Author(s).)

Aphasia recovery after stroke depends on the condition of the remaining, extralesional brain network. Network control theory (NCT) provides a unique, quantitative approach to assess the interaction between brain networks. In this longitudinal, large-scale, whole-brain connectome study, we evaluated whether controllability measures of language-related regions are associated with treated aphasia recovery. Using probabilistic tractography and controlling for the effects of structural lesions, we reconstructed whole-brain diffusion tensor imaging (DTI) connectomes from 68 individuals (20 female, 48 male) with chronic poststroke aphasia who completed a three-week language therapy. Applying principles of NCT, we computed regional (1) average and (2) modal controllability, which decode the ability of a region to (1) spread control input through the brain network and (2) to facilitate brain state transitions. We tested the relationship between pretreatment controllability measures of 20 language-related left hemisphere regions and improvements in naming six months after language therapy using multiple linear regressions and a parsimonious elastic net regression model with cross-validation. Regional controllability of the inferior frontal gyrus (IFG) pars opercularis, pars orbitalis, and the anterior insula were associated with treatment outcomes independently of baseline aphasia severity, lesion volume, age, education, and network size. Modal controllability of the IFG pars opercularis was the strongest predictor of treated aphasia recovery with cross-validation and outperformed traditional graph theory, lesion load, and demographic measures. Regional NCT measures can reflect the status of the residual language network and its interaction with the remaining brain network, being able to predict language recovery after aphasia treatment. SIGNIFICANCE STATEMENT Predicting and understanding language recovery after brain injury remains a challenging, albeit a fundamental aspect of human neurology and neuroscience. In this study, we applied network control theory (NCT) to fully harness the concept of brain networks as dynamic systems and to evaluate their interaction. We studied 68 stroke survivors with aphasia who underwent imaging and longitudinal behavioral assessments coupled with language therapy. We found that the controllability of the inferior frontal regional network significantly predicted recovery in language production six months after treatment. Importantly, controllability outperformed traditional demographic, lesion, and graph-theoretical measures. Our findings shed light on the neurobiological basis of human language and can be translated into personalized rehabilitation approaches., (Copyright © 2022 the authors.)

The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Local field potentials (LFPs) encode visual information via variations in power at many frequencies. These variations are complex and depend on stimulus and cognitive state in ways that have yet to be fully characterized. Specifically, the frequencies (or combinations of frequencies) that most robustly encode specific types of visual information are not fully known. To address this knowledge gap, we used intracranial EEG to record LFPs at 858 widely distributed recording sites as human subjects (six males, five females) indicated whether briefly presented natural scenes depicted one of three attended object categories. Principal component analysis applied to power spectra of the LFPs near stimulus onset revealed a broadband component (1-100 Hz) and two narrowband components (1-8 and 8-30 Hz, respectively) that encoded information about both seen and attended categories. Interestingly, we found that seen and attended categories were not encoded with the same fidelity by these distinct spectral components. Model-based tuning and decoding analyses revealed that power variations along the broadband component were most sharply tuned and offered more accurate decoding for seen than for attended categories. Power along the narrowband delta-theta (1-8 Hz) component robustly decoded information about both seen and attended categories, while the alpha-beta (8-30 Hz) component was specialized for attention. We conclude that, when viewing natural scenes, information about the seen category is encoded via broadband and sub-gamma (<30 Hz) power variations, while the attended category is most robustly encoded in the sub-gamma range. More generally, these results suggest that power variation along different spectral components can encode qualitatively different kinds of visual information. SIGNIFICANCE STATEMENT In this article, we characterize how changes in visual stimuli depicting specific objects (cars, faces, and buildings) and changes in attention to those objects affect the frequency content of local field potentials in the human brain. In contrast to many previous studies that have investigated encoding by variations in power at high (>30 Hz) frequencies, we find that the most important variation patterns are broadband (i.e., distributed across multiple frequencies) and narrowband, but in lower frequencies (<30 Hz). Interestingly, we find that seen and attended categories are not encoded with the same fidelity by these distinct spectral encoding patterns, suggesting that power at different frequencies can encode qualitatively different kinds of information., (Copyright © 2020 the authors.)

Objective: The distributed white matter network underlying language leads to difficulties in extracting clinically meaningful summaries of neural alterations leading to language impairment. Here we determine the predictive ability of the structural connectome (SC), compared with global measures of white matter tract microstructure and clinical data, to discriminate language impaired patients with temporal lobe epilepsy (TLE) from TLE patients without language impairment., Methods: T1- and diffusion-MRI, clinical variables (CVs), and neuropsychological measures of naming and verbal fluency were available for 82 TLE patients. Prediction of language impairment was performed using a robust tree-based classifier (XGBoost) for three models: (1) a CV-model which included demographic and epilepsy-related clinical features, (2) an atlas-based tract-model, including four frontotemporal white matter association tracts implicated in language (i.e., the bilateral arcuate fasciculus, inferior frontal occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus), and (3) a SC-model based on diffusion MRI. For the association tracts, mean fractional anisotropy was calculated as a measure of white matter microstructure for each tract using a diffusion tensor atlas (i.e., AtlasTrack). The SC-model used measurement of cortical-cortical connections arising from a temporal lobe subnetwork derived using probabilistic tractography. Dimensionality reduction of the SC was performed with principal components analysis (PCA). Each model was trained on 49 patients from one epilepsy center and tested on 33 patients from a different center (i.e., an independent dataset). Randomization was performed to test the stability of the results., Results: The SC-model yielded a greater area under the curve (AUC; .73) and accuracy (79%) compared to both the tract-model (AUC: .54, p < .001; accuracy: 70%, p < .001) and the CV-model (AUC: .59, p < .001; accuracy: 64%, p < .001). Within the SC-model, lateral temporal connections had the highest importance to model performance, including connections similar to language association tracts such as links between the superior temporal gyrus to pars opercularis. However, in addition to these connections many additional connections that were widely distributed, bilateral and interhemispheric in nature were identified as contributing to SC-model performance., Conclusion: The SC revealed a white matter network contributing to language impairment that was widely distributed, bilateral, and lateral temporal in nature. The distributed network underlying language may be why the SC-model has an advantage in identifying sub-components of the complex fiber networks most relevant for aspects of language performance., Competing Interests: Declaration of Competing Interest None., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Non-fluent speech is one of the most common impairments in post-stroke aphasia. The rehabilitation of non-fluent speech in aphasia is particularly challenging as patients are rarely able to produce and practice fluent speech production. Speech entrainment is a behavioural technique that enables patients with non-fluent aphasia to speak fluently. However, its mechanisms are not well understood and the level of improved fluency with speech entrainment varies among individuals with non-fluent aphasia. In this study, we evaluated the behavioural and neuroanatomical factors associated with better speech fluency with the aid of speech entrainment during the training phase of speech entrainment. We used a lesion-symptom mapping approach to define the relationship between chronic stroke location on MRI and the number of different words per second produced during speech entrainment versus picture description spontaneous speech. The behavioural variable of interest was the speech entrainment/picture description ratio, which, if ≥1, indicated an increase in speech output during speech entrainment compared to picture description. We used machine learning (shallow neural network) to assess the statistical significance and out-of-sample predictive accuracy of the neuroanatomical model, and its regional contributors. We observed that better assisted speech (higher speech entrainment/picture description ratio) was achieved by individuals who had preservation of the posterior middle temporal gyrus, inferior fronto-occipital fasciculus and uncinate fasciculus, while exhibiting lesions in areas typically associated with non-fluent aphasia, such as the superior longitudinal fasciculus, precentral, inferior frontal, supramarginal and insular cortices. Our findings suggest that individuals with dorsal stream damage but preservation of ventral stream structures are more likely to achieve more fluent speech with the aid of speech entrainment compared to spontaneous speech. This observation provides insight into the mechanisms of non-fluent speech in aphasia and has potential implications for future research using speech entrainment for rehabilitation of non-fluent aphasia., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: To investigate whether pre-articulatory neural activity could be used to predict correct vs. incorrect naming responses in individuals with post-stroke aphasia., Methods: We collected 64-channel high density electroencephalography (hdEEG) data from 5 individuals with chronic post-stroke aphasia (2 female/3 male, median age: 54 years) during naming of 80 concrete images. We applied machine learning on continuous wavelet transformed hdEEG data separately for alpha and beta energy bands (200 ms pre-stimulus to 1500 ms post-stimulus, but before articulation), and determined whether electrode/time-range/energy (ETE) combinations were predictive of correct vs incorrect responses for each participant., Results: The five participants correctly named between 30% and 70% of the 80 stimuli correctly. We observed that pre-articulatory scalp EEG ETE combinations could predict correct vs incorrect responses with accuracies ranging from 63% to 80%. For all but one participant, the prediction accuracies were statistically better than chance., Conclusions: Our findings indicate that pre-articulatory neural activity may be used to predict correct vs incorrect naming responses for some individuals with aphasia., Significance: The individualized pre-articulatory neural pattern associated with correct naming responses could be used to both predict naming problems in aphasia and lead to the development of brain stimulation strategies for treatment., (Copyright © 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

We aimed to identify neural regions where ischemia acutely after stroke is associated with impairment in phoneme discrimination, and to determine whether such deficits are associated with impairment of spoken word comprehension. We evaluated 33 patients within 48 h of left hemisphere ischemic stroke onset with tests of phoneme discrimination and word-picture matching. We identified Pearson correlations between accuracy in phoneme discrimination and accuracy of word comprehension and identified areas where the percentage of infarcted tissue was associated with severity of phoneme discrimination deficit. We found that 54% had deficits in phoneme discrimination relative to healthy controls. Accuracy in phoneme discrimination correlated with accuracy on word comprehension tests. Damage to left intraparietal sulcus and hypoperfusion and/or infarct of left superior temporal gyrus were associated with phoneme discrimination deficits acutely, although patients with these lesions showed improvement or resolution of the deficit by six months., (Copyright © 2019 Elsevier Inc. All rights reserved.)

While numerous studies have explored single-word naming, few have evaluated the behavioral and neural correlates of more naturalistic language, like connected speech, which we produce every day. Here, in a retrospective analysis of 120 participants at least six months following left hemisphere stroke, we evaluated the distribution of word errors (paraphasias) and associated brain damage during connected speech (picture description) and object naming. While paraphasias in connected speech and naming shared underlying neural substrates, analysis of the distribution of paraphasias suggested that lexical-semantic load is likely reduced during connected speech. Using voxelwise lesion-symptom mapping (VLSM), we demonstrated that verbal (real word: semantically related and unrelated) and sound (phonemic and neologistic) paraphasias during both connected speech and naming loaded onto the left hemisphere ventral and dorsal streams of language, respectively. Furthermore, for the first time using both connected speech and naming data, we localized semantically related paraphasias to more anterior left hemisphere temporal cortex and unrelated paraphasias to more posterior left temporal and temporoparietal cortex. The connected speech results, in particular, highlight a gradient of specificity as one translates visual recognition from left temporo-occipital cortex to posterior and subsequently anterior temporal cortex. The robustness of VLSM results for sound paraphasias derived during connected speech was notable, in that analyses performed on sound paraphasias from the connected speech task, and not the naming task, demonstrated significant results following removal of lesion volume variance and related apraxia of speech variance. Therefore, connected speech may be a particularly sensitive task on which to evaluate further lexical-phonological processing in the brain. The results presented here demonstrate the related, though different, distribution of paraphasias during connected speech, confirm that paraphasias arising in connected speech and single-word naming likely share neural origins, and endorse the need for continued evaluation of the neural substrates of connected speech processes., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Rapid advances in neuroimaging and network science have produced powerful tools and measures to appreciate human brain organization at multiple spatial and temporal scales. It is now possible to obtain increasingly meaningful representations of whole-brain structural and functional brain networks and to formally assess macroscale principles of network topology. In addition to its utility in characterizing healthy brain organization, individual variability, and life span-related changes, there is high promise of network neuroscience for the conceptualization and, ultimately, management of brain disorders. In the current review, we argue for a science of the human brain that, while strongly embracing macroscale connectomics, also recommends awareness of brain properties derived from meso- and microscale resolutions. Such features include MRI markers of tissue microstructure, local functional properties, as well as information from nonimaging domains, including cellular, genetic, or chemical data. Integrating these measures with connectome models promises to better define the individual elements that constitute large-scale networks, and clarify the notion of connection strength among them. By enriching the description of large-scale networks, this approach may improve our understanding of fundamental principles of healthy brain organization. Notably, it may also better define the substrate of prevalent brain disorders, including stroke, autism, as well as drug-resistant epilepsies that are each characterized by intriguing interactions between local anomalies and network-level perturbations.

Deficits in lexical retrieval are commonly observed in individuals with post-stroke aphasia. Successful lexical retrieval is related to lexical diversity, lexical sophistication, and phonological word properties; however, the crucial brain regions supporting these different features are not fully understood. We performed MRI-based lesion symptom mapping in 58 individuals with a chronic left hemisphere stroke to assess how regional damage relates to spoken discourse-extracted measures of lexical diversity, lexical sophistication, and phonological word properties. For discourse transcription and word feature analysis, we used the Computerized Language Analysis (CLAN) program, Stanford Core Natural Language Processing, Irvine Phonotactic Online Dictionary, Lexical Complexity Analyzer, and Gramulator. Lesions involving the left posterior insula and supramarginal gyri and inferior fronto-occipital fasciculus were significant predictors of utterances with, on average, lower lexical diversity. Low lexical sophistication was associated with damage to the left pole of the superior temporal gyrus. Production of words with lower phonological complexity (fewer phonemes, higher phonological similarity) was associated with damage to the left supramarginal gyrus. Our findings indicate that discourse-extracted features of lexical retrieval depend on the integrity of specific brain regions involving insular and peri-Sylvian areas. The identified regions provide insight into potentially underlying mechanisms of lexically diverse, sophisticated and phonologically complex words produced during discourse., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background Cardiovascular risk factor burden in the absence of clinical or radiological "events" is associated with mild cognitive impairment. Magnetic resonance imaging techniques exploring the integrity of neuronal fiber connectivity within white matter networks supporting cognitive processing could be used to measure the impact of cardiovascular disease on brain health and be used beyond bedside neuropsychological tests to detect subclinical changes and select or stratify participants for entry into clinical trials. Methods and Results We assessed the relationship between verbal IQ and brain network integrity and the effect of cardiovascular risk factors on network integrity by constructing whole-brain structural connectomes from magnetic resonance imaging diffusion images (N=60) from people with various degrees of cardiovascular risk factor burden. We measured axonal integrity by calculating network density and determined the effect of fiber loss on network topology and efficiency, using graph theory. Multivariate analyses were used to evaluate the relationship between cardiovascular risk factor burden, physical activity, age, education, white matter integrity, and verbal IQ . Reduced network density, resulting from a disproportionate loss of long-range white matter fibers, was associated with white matter network fragmentation ( r=-0.52, P<10 -4 ), lower global efficiency ( r=0.91, P<10 -20 ), and decreased verbal IQ (adjusted R 2 =0.23, P<10 -4 ). Conclusions Cardiovascular risk factors may mediate negative effects on brain health via loss of energy-dependent long-range white matter fibers, which in turn leads to disruption of the topological organization of the white matter networks, lowered efficiency, and reduced cognitive function.

Objective: We evaluated whether deep learning applied to whole-brain presurgical structural connectomes could be used to predict postoperative seizure outcome more accurately than inference from clinical variables in patients with mesial temporal lobe epilepsy (TLE)., Methods: Fifty patients with unilateral TLE were classified either as having persistent disabling seizures (SZ) or becoming seizure-free (SZF) at least 1 year after epilepsy surgery. Their presurgical structural connectomes were reconstructed from whole-brain diffusion tensor imaging. A deep network was trained based on connectome data to classify seizure outcome using 5-fold cross-validation., Results: Classification accuracy of our trained neural network showed positive predictive value (PPV; seizure freedom) of 88 ± 7% and mean negative predictive value (NPV; seizure refractoriness) of 79 ± 8%. Conversely, a classification model based on clinical variables alone yielded <50% accuracy. The specific features that contributed to high accuracy classification of the neural network were located not only in the ipsilateral temporal and extratemporal regions, but also in the contralateral hemisphere., Significance: Deep learning demonstrated to be a powerful statistical approach capable of isolating abnormal individualized patterns from complex datasets to provide a highly accurate prediction of seizure outcomes after surgery. Features involved in this predictive model were both ipsilateral and contralateral to the clinical foci and spanned across limbic and extralimbic networks., (Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.)

In most cases, aphasia is caused by strokes involving the left hemisphere, with more extensive damage typically being associated with more severe aphasia. The classical model of aphasia commonly adhered to in the Western world is the Wernicke-Lichtheim model. The model has been in existence for over a century, and classification of aphasic symptomatology continues to rely on it. However, far more detailed models of speech and language localization in the brain have been formulated. In this regard, the dual stream model of cortical brain organization proposed by Hickok and Poeppel is particularly influential. Their model describes two processing routes, a dorsal stream and a ventral stream, that roughly support speech production and speech comprehension, respectively, in normal subjects. Despite the strong influence of the dual stream model in current neuropsychological research, there has been relatively limited focus on explaining aphasic symptoms in the context of this model. Given that the dual stream model represents a more nuanced picture of cortical speech and language organization, cortical damage that causes aphasic impairment should map clearly onto the dual processing streams. Here, we present a follow-up study to our previous work that used lesion data to reveal the anatomical boundaries of the dorsal and ventral streams supporting speech and language processing. Specifically, by emphasizing clinical measures, we examine the effect of cortical damage and disconnection involving the dorsal and ventral streams on aphasic impairment. The results reveal that measures of motor speech impairment mostly involve damage to the dorsal stream, whereas measures of impaired speech comprehension are more strongly associated with ventral stream involvement. Equally important, many clinical tests that target behaviours such as naming, speech repetition, or grammatical processing rely on interactions between the two streams. This latter finding explains why patients with seemingly disparate lesion locations often experience similar impairments on given subtests. Namely, these individuals' cortical damage, although dissimilar, affects a broad cortical network that plays a role in carrying out a given speech or language task. The current data suggest this is a more accurate characterization than ascribing specific lesion locations as responsible for specific language deficits.5705668782001awx363media15705668782001.

Here we illustrate how investigation of individuals acutely after stroke, before structure/function reorganization through recovery or rehabilitation, can be helpful in answering questions about the role of specific brain regions in language functions. Although there is converging evidence from a variety of sources that the left posterior-superior temporal gyrus plays some role in spoken word comprehension, its precise role in this function has not been established. We hypothesized that this region is essential for distinguishing between semantically related words, because it is critical for linking the spoken word to the complete semantic representation. We tested this hypothesis in 127 individuals with 48 hours of acute ischemic stroke, before the opportunity for reorganization or recovery. We identified tissue dysfunction (acute infarct and/or hypoperfusion) in gray and white matter parcels of the left hemisphere, and we evaluated the association between rate of semantic errors in a word-picture verification tasks and extent of tissue dysfunction in each region. We found that after correcting for lesion volume and multiple comparisons, the rate of semantic errors correlated with the extent of tissue dysfunction in left posterior-superior temporal gyrus and retrolenticular white matter., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.)

We investigated the brain network involved in speech sensorimotor processing by studying patients with post-stroke aphasia using an altered auditory feedback (AAF) paradigm. We combined lesion-symptom-mapping analysis and behavioral testing to examine the pervasiveness of speech sensorimotor deficits and their relationship with cortical damage. Sixteen participants with aphasia and sixteen neurologically intact individuals completed a speech task under AAF. The task involved producing speech vowel sounds under the real-time pitch-shifted auditory feedback alteration. This task provided an objective measure for each individual's ability to compensate for mismatch (error) in speech auditory feedback. Results indicated that compensatory speech responses to AAF were significantly diminished in participants with aphasia compared with control. We observed that within the aphasic group, subjects with lower scores on the speech repetition task exhibited greater degree of diminished responses. Lesion-symptom-mapping analysis revealed that the onset phase (50-150 ms) of diminished AAF responses were predicted by damage to auditory cortical regions within the superior and middle temporal gyrus, whereas the rising phase (150-250 ms) and the peak (250-350 ms) of diminished AAF responses were predicted with damage to the inferior frontal gyrus and supramarginal gyrus areas, respectively. These findings suggest that damage to the auditory, motor, and auditory-motor integration networks are associated with impaired sensorimotor function for speech error processing. We suggest that a sensorimotor integration network, as revealed by brain regions related to temporal specific components of AAF responses, is related to speech processing and specific aspects of speech impairment, notably repetition deficits, in individuals with aphasia., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Lesion-symptom mapping is often employed to define brain structures that are crucial for human behavior. Even though poststroke deficits result from gray matter damage as well as secondary white matter loss, the impact of structural disconnection is overlooked by conventional lesion-symptom mapping because it does not measure loss of connectivity beyond the stroke lesion. This study describes how traditional lesion mapping can be combined with structural connectome lesion symptom mapping (CLSM) and connectome dynamics lesion symptom mapping (CDLSM) to relate residual white matter networks to behavior. Using data from a large cohort of stroke survivors with aphasia, we observed improved prediction of aphasia severity when traditional lesion symptom mapping was combined with CLSM and CDLSM. Moreover, only CLSM and CDLSM disclosed the importance of temporal-parietal junction connections in aphasia severity. In summary, connectome measures can uniquely reveal brain networks that are necessary for function, improving the traditional lesion symptom mapping approach.

Several dual route models of human speech processing have been proposed suggesting a large-scale anatomical division between cortical regions that support motor-phonological aspects vs. lexical-semantic aspects of speech processing. However, to date, there is no complete agreement on what areas subserve each route or the nature of interactions across these routes that enables human speech processing. Relying on an extensive behavioral and neuroimaging assessment of a large sample of stroke survivors, we used a data-driven approach using principal components analysis of lesion-symptom mapping to identify brain regions crucial for performance on clusters of behavioral tasks without a priori separation into task types. Distinct anatomical boundaries were revealed between a dorsal frontoparietal stream and a ventral temporal-frontal stream associated with separate components. Collapsing over the tasks primarily supported by these streams, we characterize the dorsal stream as a form-to-articulation pathway and the ventral stream as a form-to-meaning pathway. This characterization of the division in the data reflects both the overlap between tasks supported by the two streams as well as the observation that there is a bias for phonological production tasks supported by the dorsal stream and lexical-semantic comprehension tasks supported by the ventral stream. As such, our findings show a division between two processing routes that underlie human speech processing and provide an empirical foundation for studying potential computational differences that distinguish between the two routes., Competing Interests: The authors declare no conflict of interest.

Anxiety disorders represent a prevalent psychiatric comorbidity in both adults and children with epilepsy for which the etiology remains controversial. Neurobiological contributions have been suggested, but only limited evidence suggests abnormal brain volumes particularly in children with epilepsy and anxiety. Since the brain develops in an organized fashion, covariance analyses between different brain regions can be investigated as a network and analyzed using graph theory methods. We examined 46 healthy children (HC) and youth with recent onset idiopathic epilepsies with ( n  = 24) and without ( n  = 62) anxiety disorders. Graph theory (GT) analyses based on the covariance between the volumes of 85 cortical/subcortical regions were investigated. Both groups with epilepsy demonstrated less inter-modular relationships in the synchronization of cortical/subcortical volumes compared to controls, with the epilepsy and anxiety group presenting the strongest modular organization. Frontal and occipital regions in non-anxious epilepsy, and areas throughout the brain in children with epilepsy and anxiety, showed the highest centrality compared to controls. Furthermore, most of the nodes correlating to amygdala volumes were subcortical structures, with the exception of the left insula and the right frontal pole, which presented high betweenness centrality (BC); therefore, their influence in the network is not necessarily local but potentially influencing other more distant regions. In conclusion, children with recent onset epilepsy and anxiety demonstrate large scale disruptions in cortical and subcortical brain regions. Network science may not only provide insight into the possible neurobiological correlates of important comorbidities of epilepsy, but also the ways that cortical and subcortical disruption occurs.

Purpose: Post-stroke aphasia is typically associated with ischemic damage to cortical areas or with loss of connectivity among spared brain regions. It remains unclear whether the participation of spared brain regions as networks hubs affects the severity of aphasia., Methods: We evaluated language performance and magnetic resonance imaging from 44 participants with chronic aphasia post-stroke. The individual structural brain connectomes were constructed from diffusion tensor. Hub regions were defined in accordance with the rich club classification and studied in relation with language performance., Results: Number of remaining left hemisphere rich club nodes was associated with aphasia, including comprehension, repetition and naming sub-scores. Importantly, among participants with relative preservation of regions of interest for language, aphasia severity was lessened if the region was not only spared, but also participated in the remaining network as a rich club node: Brodmann area (BA) 44/45 - repetition (p = 0.009), BA 39 - repetition (p = 0.045) and naming (p <  0.01), BA 37 - fluency (p <  0.001), comprehension (p = 0.025), repetition (p <  0.001) and naming (p <  0.001)., Conclusions: Disruption of language network structural hubs is directly associated with aphasia severity after stroke.

Background: Representations of objects and actions in everyday speech are usually materialized as nouns and verbs, two grammatical classes that constitute the core elements of language. Given their very distinct roles in singling out objects (nouns) or referring to transformative actions (verbs), they likely rely on distinct brain circuits., Method: We tested this hypothesis by conducting network-based lesion-symptom mapping in 38 patients with chronic stroke to the left hemisphere. We reconstructed the individual brain connectomes from probabilistic tractography applied to magnetic resonance imaging and obtained measures of production of words referring to objects and actions from narrative discourse elicited by picture naming tasks., Results: Words for actions were associated with a frontal network strongly engaging structures involved in motor control and programming. Words for objects, instead, were related to a posterior network spreading across the occipital, posterior inferior temporal, and parietal regions, likely related with visual processing and imagery, object recognition, and spatial attention/scanning. Thus, each of these networks engaged brain areas typically involved in cognitive and sensorimotor experiences equivalent to the function served by each grammatical class (e.g. motor areas for verbs, perception areas for nouns)., Conclusions: The finding that the two major grammatical classes in human speech rely on two dissociable networks has both important theoretical implications for the neurobiology of language and clinical implications for the assessment and potential rehabilitation and treatment of patients with chronic aphasia due to stroke.

The assessment of neural networks in epilepsy has become increasingly relevant in the context of translational research, given that localized forms of epilepsy are more likely to be related to abnormal function within specific brain networks, as opposed to isolated focal brain pathology. It is notable that variability in clinical outcomes from epilepsy treatment may be a reflection of individual patterns of network abnormalities. As such, network endophenotypes may be important biomarkers for the diagnosis and treatment of epilepsy. Despite its exceptional potential, measuring abnormal networks in translational research has been thus far constrained by methodologic limitations. Fortunately, recent advancements in neuroscience, particularly in the field of connectomics, permit a detailed assessment of network organization, dynamics, and function at an individual level. Data from the personal connectome can be assessed using principled forms of network analyses based on graph theory, which may disclose patterns of organization that are prone to abnormal dynamics and epileptogenesis. Although the field of connectomics is relatively new, there is already a rapidly growing body of evidence to suggest that it can elucidate several important and fundamental aspects of abnormal networks to epilepsy. In this article, we provide a review of the emerging evidence from connectomics research regarding neural network architecture, dynamics, and function related to epilepsy. We discuss how connectomics may bring together pathophysiologic hypotheses from conceptual and basic models of epilepsy and in vivo biomarkers for clinical translational research. By providing neural network information unique to each individual, the field of connectomics may help to elucidate variability in clinical outcomes and open opportunities for personalized medicine approaches to epilepsy. Connectomics involves complex and rich data from each subject, thus collaborative efforts to enable the systematic and rigorous evaluation of this form of "big data" are paramount to leverage the full potential of this new approach., (Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.)

X-linked monocarboxylate transporter 8 (MCT8) deficiency results from a loss-of-function mutation in the monocarboxylate transporter 8 gene, located on chromosome Xq13.2 (Allan-Herndon-Dudley syndrome). Affected boys present early in life with neurodevelopment delays but have pleasant dispositions and commonly have elevated serum triiodothyronine. They also have marked axial hypotonia and quadriparesis but surprisingly little spasticity early in their disease course. They do, however, have subtle involuntary movements, most often dystonia. The combination of hypotonia and dystonia presents a neurorehabilitation challenge and explains why spasticity-directed therapies have commonly produced suboptimal responses. Our aim was to better define the spectrum of motor disability and to elucidate the neuroanatomic basis of the motor impairments seen in MCT8 deficiency using clinical observation and brain magnetic resonance imaging (MRI) in a cohort of 6 affected pediatric patients. Our findings identified potential imaging biomarkers and suggest that rehabilitation efforts targeting dystonia may be more beneficial than those targeting spasticity in the prepubertal pediatric MCT8 deficiency population., (© The Author(s) 2015.)

Recent years have witnessed a paradigm shift in the study and conceptualization of epilepsy, which is increasingly understood as a network-level disorder. An emblematic case is temporal lobe epilepsy (TLE), the most common drug-resistant epilepsy that is electroclinically defined as a focal epilepsy and pathologically associated with hippocampal sclerosis. In this review, we will summarize histopathological, electrophysiological, and neuroimaging evidence supporting the concept that the substrate of TLE is not limited to the hippocampus alone, but rather is broadly distributed across multiple brain regions and interconnecting white matter pathways. We will introduce basic concepts of graph theory, a formalism to quantify topological properties of complex systems that has recently been widely applied to study networks derived from brain imaging and electrophysiology. We will discuss converging graph theoretical evidence indicating that networks in TLE show marked shifts in their overall topology, providing insight into the neurobiology of TLE as a network-level disorder. Our review will conclude by discussing methodological challenges and future clinical applications of this powerful analytical approach., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objective: We examined whether individual neuronal architecture obtained from the brain connectome can be used to estimate the surgical success of anterior temporal lobectomy (ATL) in patients with temporal lobe epilepsy (TLE)., Methods: We retrospectively studied 35 consecutive patients with TLE who underwent ATL. The structural brain connectome was reconstructed from all patients using presurgical diffusion MRI. Network links in patients were standardized as Z scores based on connectomes reconstructed from healthy controls. The topography of abnormalities in linkwise elements of the connectome was assessed on subnetworks linking ipsilateral temporal with extratemporal regions. Predictive models were constructed based on the individual prevalence of linkwise Z scores >2 and based on presurgical clinical data., Results: Patients were more likely to achieve postsurgical seizure freedom if they exhibited fewer abnormalities within a subnetwork composed of the ipsilateral hippocampus, amygdala, thalamus, superior frontal region, lateral temporal gyri, insula, orbitofrontal cortex, cingulate, and lateral occipital gyrus. Seizure-free surgical outcome was predicted by neural architecture alone with 90% specificity (83% accuracy), and by neural architecture combined with clinical data with 94% specificity (88% accuracy)., Conclusions: Individual variations in connectome topography, combined with presurgical clinical data, may be used as biomarkers to better estimate surgical outcomes in patients with TLE., (© 2015 American Academy of Neurology.)

With recent advances in computational analyses of structural neuroimaging, it is possible to comprehensively map neural connectivity, i.e., the brain connectome. The architectural organization of the connectome is believed to play an important role in several biological processes. Central to the conformation of the connectome are connectivity hubs, which are likely to be organized in accordance with the rich club phenomenon, as evidenced by graph theory analyses of neural architecture. It is yet unclear whether rich club connectivity hubs are consistently organized in the same anatomical framework across healthy adults. We constructed the brain connectome from 43 healthy adults, based on T1-weighted and diffusion tensor MRI data. Probabilistic fiber tractography was used to evaluate connectivity between each possible pair of cortical anatomical regions of interest. Connectivity hubs were identified in accordance with the rich club phenomenon applied to binarized matrices, and the variability in frequency of hub participation was assessed node-wise across all subjects. The anatomical location of nodes participating in rich club networks was fairly consistent across subjects. The most common locations for rich club nodes were identified in integrative areas, such as the cingulate and pericingulate regions, medial aspect of the occipital areas and precuneus; or else, they were found in important and specialized brain regions (such as the oribitofrontal cortex, caudate, fusiform gyrus, and hippocampus). Marked anatomical consistency exists across healthy brains in terms of nodal participation and location of rich club networks. The consistency of connections between integrative areas and specialized brain regions highlights a fundamental connectivity pattern shared among healthy brains. We propose that approaching brain connectivity with this framework of anatomical consistencies may have clinical implications for early detection of individual variability.

Structural asymmetry of whole brain white matter (WM) pathways, i.e., the connectome, has been demonstrated using fiber tractography based on diffusion tensor imaging (DTI). However, DTI-based tractography fails to resolve axonal fiber bundles that intersect within an imaging voxel, and therefore may not fully characterize the extent of asymmetry. The goal of this study was to assess structural asymmetry with tractography based on diffusional kurtosis imaging (DKI), which improves upon DTI-based tractography by delineating intravoxel crossing fibers. DKI images were obtained from 42 healthy subjects. By using automatic segmentation, gray matter (GM) was parcellated into anatomically defined regions of interest (ROIs). WM pathways were reconstructed with both DKI- and DTI-based tractography. The connectivity between the ROIs was quantified with the streamlines connecting the ROIs. The asymmetry index (AI) was utilized to quantify hemispheric differences in the connectivity of cortical ROIs and of links interconnecting cortical ROIs. Our results demonstrated that leftward asymmetrical ROIs and links were observed in frontal, parietal, temporal lobes, and insula. Rightward asymmetrical ROI and links were observed in superior frontal lobe, cingulate cortex, fusiform, putamen, and medial temporal lobe. Interestingly, these observed structural asymmetries were incompletely identified with DTI-based tractography. These results suggest that DKI-based tractography can improve the identification of asymmetrical connectivity patterns, thereby serving as an additional tool in the evaluation of the structural bases of functional lateralization., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Recent neuroimaging and behavioral studies have revealed that children with new onset epilepsy already exhibit brain structural abnormalities and cognitive impairment. How the organization of large-scale brain structural networks is altered near the time of seizure onset and whether network changes are related to cognitive performances remain unclear. Recent studies also suggest that regional brain volume covariance reflects synchronized brain developmental changes. Here, we test the hypothesis that epilepsy during early-life is associated with abnormalities in brain network organization and cognition. We used graph theory to study structural brain networks based on regional volume covariance in 39 children with new-onset seizures and 28 healthy controls. Children with new-onset epilepsy showed a suboptimal topological structural organization with enhanced network segregation and reduced global integration compared with controls. At the regional level, structural reorganization was evident with redistributed nodes from the posterior to more anterior head regions. The epileptic brain network was more vulnerable to targeted but not random attacks. Finally, a subgroup of children with epilepsy, namely those with lower IQ and poorer executive function, had a reduced balance between network segregation and integration. Taken together, the findings suggest that the neurodevelopmental impact of new onset childhood epilepsies alters large-scale brain networks, resulting in greater vulnerability to network failure and cognitive impairment., (Copyright © 2014 Wiley Periodicals, Inc.)

Background: The extent of brain damage in chronic stroke patients is traditionally defined as the necrotic tissue observed on magnetic resonance image (MRI). However, patients often exhibit symptoms suggesting that functional impairment may affect areas beyond the cortical necrotic lesion, for example, when cortical symptoms ensue after subcortical damage. This observation suggests that disconnection or diaschisis can lead to remote cortical dysfunction that can be functionally equivalent to direct cortical lesions. Objective. To directly measure subcortical disconnection after stroke., Methods: We describe a principled approach utilizing the whole brain connectome reconstructed from diffusion MRI to evaluate the reduction of apparent white matter fiber density in the hemisphere affected by the stroke compared with the spared hemisphere., Results: In eight chronic stroke patients, we observed subcortical disconnection extending beyond the location of tissue necrosis and affecting major white matter pathways underlying the necrotic area., Conclusions: We suggest that it is possible to detect and quantify previously unappreciated areas of subcortical and cortical disconnection. Specifically, this method can be used to evaluate the relationship between lesion location and symptoms, with emphasis on a connectivity-based approach.

Purpose: Patients with medial temporal lobe epilepsy (MTLE) exhibit structural brain damage involving gray matter (GM) and white matter (WM). The mechanisms underlying tissue loss in MTLE are unclear and may be associated with a combination of seizure excitotoxicity and WM vulnerability. The goal of this study was to investigate whether late-myelinating WM tracts are more vulnerable to injury in MTLE compared with early myelinating tracts., Methods: Diffusional kurtosis imaging scans were obtained from 25 patients with MTLE and from 36 matched healthy controls. Diffusion measures from regions of interest (ROIs) for both late- and early myelinating WM tracts were analyzed. Regional Z-scores were computed with respect to normal controls to compare WM in early myelinating tracts versus late-myelinating tracts., Key Findings: We observed that late-myelinating tracts exhibited a larger decrease in mean, axial, and radial kurtosis compared with early myelinating tracts. We also observed that the change in radial kurtosis was more pronounced in late-myelinating tracts ipsilateral to the side of seizure onset., Significance: These results suggest a developmentally based preferential susceptibility of late-myelinating WM tracts to damage in MTLE. Brain injury in epilepsy may be due to the pathologic effects of seizures in combination with regional WM vulnerability., (Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.)

Spatial normalization reshapes an individual's brain to match the shape and size of a template image. This is a crucial step required for group-level statistical analyses. The most popular standard templates are derived from MRI scans of young adults. We introduce specialized templates that allow normalization algorithms to be applied to stroke-aged populations. First, we developed a CT template: while this is the dominant modality for many clinical situations, there are no modern CT templates and popular algorithms fail to successfully normalize CT scans. Importantly, our template was based on healthy individuals with ages similar to what is commonly seen in stroke (mean 65 years old). This template allows studies where only CT scans are available. Second, we derived a MRI template that approximately matches the shape of our CT template as well as processing steps that aid the normalization of scans from older individuals (including lesion masking and the ability to generate high quality cortical renderings despite brain injury). The benefit of this strategy is that the resulting templates can be used in studies where mixed modalities are present. We have integrated these templates and processing algorithms into a simple SPM toolbox (http://www.mricro.com/clinical-toolbox/spm8-scripts)., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Lesion-symptom mapping studies are based upon the assumption that behavioral impairments are directly related to structural brain damage. Given what is known about the relationship between perfusion deficits and impairment in acute stroke, attributing specific behavioral impairments to localized brain damage leaves much room for speculation, as impairments could also reflect abnormal neurovascular function in brain regions that appear structurally intact on traditional CT and MRI scans. Compared to acute stroke, the understanding of cerebral perfusion in chronic stroke is far less clear. Utilizing arterial spin labeling (ASL) MRI, we examined perfusion in 17 patients with chronic left hemisphere stroke. The results revealed a decrease in left hemisphere perfusion, primarily in peri-infarct tissue. There was also a strong relationship between increased infarct size and decreased perfusion. These findings have implications for lesion-symptom mapping studies as well as research that relies on functional MRI to study chronic stroke.

Purpose: It is unclear whether extrahippocampal brain damage in patients with medial temporal lobe epilepsy (MTLE) is a homogeneous phenomenon, as most data relates to the average volume reduction in groups of patients. This study aimed to evaluate where and how much atrophy is to be expected in an individual patient with MTLE., Methods: High-resolution T(1) magnetic resonance imaging (MRI) was obtained from 23 consecutive patients with unilateral MTLE and from a matched control group. Parametric tests of voxel-based gray matter volume evaluated mean regional atrophy in MTLE compared with controls. Gray matter images were then submitted to a voxel by voxel calculation of the fitted receiver operating characteristic (ROC) curve area, plotting the sensitivity versus 1-specificity for a binary classifier (MTLE vs. controls). The area under the curve (AUC) was calculated for each voxel and a resulting three-dimensional map of gray matter voxel-wise AUCs was obtained., Results: On average, patients with MTLE showed atrophy in the ipsilateral hippocampus and on a limbic network. Elevated AUC was demonstrated in the ipsilateral hippocampus and medial temporal lobe, the ipsilateral thalamus and occipitotemporal cortex, the ipsilateral cerebellum, the cingulate, the contralateral insula, and the occipitoparietal and dorsolateral prefrontal cortex., Conclusion: This study suggests that the medial temporal lobe, occipitotemporal areas, the cerebellum, the cingulate cortex, the ipsilateral insula, and thalamus are more likely to be atrophied in randomly selected patients with MTLE. Structures such as the orbitofrontal cortex, the contralateral medial temporal areas and insula, the putamen, and the caudate may be atrophied, but not as consistently., (Wiley Periodicals, Inc. © 2010 International League Against Epilepsy.)

Understanding the neural mechanism that supports preserved language processing in aphasia has implications for both basic and applied science. This study examined brain activation associated with correct picture naming in 15 patients with aphasia. We contrasted each patient's activation to the activation observed in a neurologically healthy control group, allowing us to identify regions with unusual activity patterns. The results revealed that increased activation in preserved left hemisphere areas is associated with better naming performance in aphasia. This relationship was linear in nature; progressively less cortical activation was associated with greater severity of anomia. These findings are consistent with others who suggests that residual language function following stroke relies on preserved cortical areas in the left hemisphere.

Neuroimaging studies suggest that a fronto-parietal network is activated when we expect visual information to appear at a specific spatial location. Here we examined whether a similar network is involved for auditory stimuli. We used sparse fMRI to infer brain activation while participants performed analogous visual and auditory tasks. On some trials, participants were asked to discriminate the elevation of a peripheral target. On other trials, participants made a nonspatial judgment. We contrasted trials where the participants expected a peripheral spatial target to those where they were cued to expect a central target. Crucially, our statistical analyses were based on trials where stimuli were anticipated but not presented, allowing us to directly infer perceptual orienting independent of perceptual processing. This is the first neuroimaging study to use an orthogonal-cuing paradigm (with cues predicting azimuth and responses involving elevation discrimination). This aspect of our paradigm is important, as behavioral cueing effects in audition are classically only observed when participants are asked to make spatial judgments. We observed similar fronto-parietal activation for both vision and audition. In a second experiment that controlled for stimulus properties and task difficulty, participants made spatial and temporal discriminations about musical instruments. We found that the pattern of brain activation for spatial selection of auditory stimuli was remarkably similar to what we found in our first experiment. Collectively, these results suggest that the neural mechanisms supporting spatial attention are largely similar across both visual and auditory modalities.

Experimental animal studies have shown that physical exercise, associated with planning and execution of complex movements, are related to changes in brain structure. In humans, changes in cortical tissue density in relation to physical activity are yet to be fully determined and quantified. We investigated differences on gray matter volume in judo players by using voxel-based morphometry. Comparison between a group of eight internationally competitive judo players and a group of 18 healthy controls showed a significantly higher gray matter tissue density in brain areas of judo players.

Two primary areas of damage have been implicated in apraxia of speech (AOS) based on the time post-stroke: (1) the left inferior frontal gyrus (IFG) in acute patients, and (2) the left anterior insula (aIns) in chronic patients. While AOS is widely characterized as a disorder in motor speech planning, little is known about the specific contributions of each of these regions in speech. The purpose of this study was to investigate cortical activation during speech production with a specific focus on the aIns and the IFG in normal adults. While undergoing sparse fMRI, 30 normal adults completed a 30-minute speech-repetition task consisting of three-syllable nonwords that contained either (a) English (native) syllables or (b) non-English (novel) syllables. When the novel syllable productions were compared to the native syllable productions, greater neural activation was observed in the aIns and IFG, particularly during the first 10 min of the task when novelty was the greatest. Although activation in the aIns remained high throughout the task for novel productions, greater activation was clearly demonstrated when the initial 10 min was compared to the final 10 min of the task. These results suggest increased activity within an extensive neural network, including the aIns and IFG, when the motor speech system is taxed, such as during the production of novel speech. We speculate that the amount of left aIns recruitment during speech production may be related to the internal construction of the motor speech unit such that the degree of novelty/automaticity would result in more or less demands respectively. The role of the IFG as a storehouse and integrative processor for previously acquired routines is also discussed.

Recent evidence supports increased cortical activity and impaired brain connectivity in autism, but the structural correlates of these abnormalities are not yet defined. We performed a voxel based morphometry analysis of brain MRI from patients with autism selected from a group of 103 subjects with pervasive developmental disorders. Twelve male patients with mean age of 12.4 +/- 4 years were compared with 16 matched controls. Patients with autism exhibited increase in gray matter in medial and dorsolateral frontal areas, in the lateral and medial parts of the temporal lobes, in the parietal lobes, cerebellum and claustrum. Patients also showed decrease in frontal, parietal, temporal and occipital white matter. The combination of enlarged cortex and reduced white matter is possibly the structural basis of some symptoms of classic autism.

Background: The mechanisms guiding the progression of neuronal damage in patients with Huntington disease (HD) are not completely understood. It is unclear whether the genotype--that is, the length of the expanded CAG repeat--guides the location and speed of grey matter decline once HD is clinically manifested. Moreover, the relationship between cortical and subcortical grey matter atrophy and the severity of motor symptoms of HD is controversial., Objectives: In this article, we longitudinally studied, over the period of 1 year, a cohort of 49 patients with HD. We investigated: first, the clinical relevance of regional progressive grey matter atrophy; and second, the relationship between the ratio of atrophy progression and genotype., Methods: The length of the expanded CAG repeat was quantified for all patients and the United Huntington's Disease Rating Scale (UHDRS) was used to rate the severity of clinical symptoms. Grey matter atrophy was determined using voxel-based morphometry (VBM) of brain MRI. Progression of atrophy was quantified in 37 patients who were submitted to two different MRI scans, the second scan 1 year later than the first., Results: Overall, patients exhibited progressive atrophy involving the caudate, pallidum, putamen, insula, cingulate cortex, cerebellum, orbitofrontal cortex, medial temporal lobes and middle frontal gyri. Patients with a larger UHDRS score exhibited selective atrophy of the caudate, thalamus, midbrain, insula and frontal lobes. Patients with longer, expanded CAG repeat sequences showed faster rates and more widespread atrophy, particularly those patients with more than 55 expanded CAG repeats., Conclusions: These results confirm that brain atrophy progresses after the clinical onset of HD and that regional atrophy is related to symptom severity. Moreover, our results also indicate that intensity and rate of progression of brain atrophy are more pronounced in patients with larger, expanded CAG repeat sequences.

Motor training results in performance improvement. It is not yet fully understood the extent to which functional improvement is reflected in changes in brain structure. To investigate the presence and degree of structural brain plasticity induced by long-term bimanual motor activity, we studied 17 right-handed professional typists with average duration of typing practice of 11 years. Using optimized voxel-based morphometry, we correlated the duration of practice and grey matter volume. Regions of interest were applied using 116 previously segmented predefined brain sites. We found a significant positive regression between grey matter volume and duration of practice in brain regions related to the programming of motor tasks. Long-term bimanual training may increase grey matter volume in the brains of professional typists.

We investigated whether structural white matter abnormalities, in the form of disruption of axonal coherence and integrity as measured with diffusion tensor imaging (DTI), constitute an underlying pathological mechanism of idiopathic dystonia (ID), independent of genotype status. We studied seven subjects with ID: all had cervical dystonia as their main symptom (one patient also had spasmodic dysphonia and two patients had concurrent generalized dystonia, both DYT1-negative). We compared DTI MR images of patients with 10 controls, evaluating differences in mean diffusivity (MD) and fractional anisotropy (FA). ID was associated with increased FA values in the thalamus and adjacent white matter, and in the white matter underlying the middle frontal gyrus. ID was also associated with increase in MD in adjacent white matter to the pallidum and putamen bilaterally, left caudate, and in subcortical hemispheric regions, including the postcentral gyrus. Abnormal FA and MD in patients with ID indicate that abnormal axonal coherence and integrity contribute to the pathophysiology of dystonia. These findings suggest that ID is not only a functional disorder, but also associated with structural brain changes. Impaired connectivity and disrupted flow of information may contribute to the impairment of motor planning and regulation in dystonia.

Background: Structural neuroimaging studies have consistently shown a pattern of extra-hippocampal atrophy in patients with left and right drug-refractory medial temporal lobe epilepsy (MTLE). However, it is not yet completely understood how extra-hippocampal atrophy is related to hippocampal atrophy. Moreover, patients with left MTLE often exhibit more intense cognitive impairment, and subtle brain asymmetries have been reported in patients with left MTLE versus right MTLE but have not been explored in a controlled study., Objectives: To investigate the association between extra-hippocampal and hippocampal atrophy in patients with MTLE, and the effect of side of hippocampal atrophy on extra-hippocampal atrophy., Methods: Voxel-based morphometry analyses of magnetic resonance images of the brain were performed to determine the correlation between regional extra-hippocampal grey matter volume and hippocampal grey matter volume. The results from 36 patients with right and left MTLE were compared, and results from the two groups were compared with those from 49 healthy controls., Results: Compared with controls, patients with MTLE showed a more intense correlation between hippocampal grey matter volume and regional grey matter volume in locations such as the contralateral hippocampus, bilateral parahippocampal gyri and frontal and parietal areas. Compared with right MTLE, patients with left MTLE exhibited a wider area of atrophy related to hippocampal grey matter loss, encompassing both the contralateral and ipsilateral hemispheres, particularly affecting the contralateral hippocampus., Conclusions: Our results suggest that left hippocampal atrophy is associated with a larger degree of extra-hippocampal atrophy. This may help to explain the more intense cognitive impairment usually observed in these patients.

Cerebral atrophy has been described to occur in systemic lupus erythematosus (SLE) with variable frequency. The aim of this study was to determine white and gray matter abnormalities in brain magnetic resonance imaging (MRI) of patients with SLE and to determine if these abnormalities progress over a one-year period. Seventy-five patients with SLE and 44 healthy age and sex-matched controls were enrolled in this study. T1-weighted volumetric images were used for voxel based morphometry (VBM) analyses. SLE patients exhibited a significant reduction in white matter and gray matter volume compared to controls (p=0.001). Follow-up images, after an average interval of 19 months, revealed a progressive white matter and gray matter atrophy (p=0.001). Reduced white and gray matter volume was associated with disease duration and the presence of antiphospholipid antibodies. Patients with severe cognitive impairment had a more pronounced white and gray matter reduction than patients with moderate cognitive impairment. Total corticosteroid dose was associated with gray matter reduction and not with white matter loss in SLE patients. We concluded that brain tissue loss associated with SLE is significant and progresses over a relatively short period of time. Disease duration, the presence of antiphospholipid antibodies and cognitive impairment were associated with white and gray matter loss. Corticosteroid was associated only with gray matter atrophy.

Hippocampal sclerosis is the most common abnormality associated with medial temporal lobe epilepsy (MTLE). Converging evidence supports that hippocampal sclerosis progresses with time. However, it is unclear whether extrahippocampal atrophy in patients with MTLE, similarly to hippocampal sclerosis, is an unremitting progressive process. In this article, we investigate the relationship between duration of epilepsy and gray matter concentration reduction in patients with MTLE within and outside the hippocampus. We employed a voxel-based morphometry study of MRI of the entire brain of 36 patients with drug refractory MTLE and 49 neurologically healthy age-matched controls. We performed a voxel-based parametric and nonparametric investigation of the association between gray matter concentration, age and duration of epilepsy. We complemented the investigation by extracting the gray matter concentration of regions of interest (ROIs) within the limbic system, and we investigated the association between the gray matter concentration on the ROIs and duration of epilepsy. Patients with MTLE exhibited gray matter concentration reduction that is negatively correlated with the duration of epilepsy within the ipsilateral hippocampus, temporal lobes as well as extratemporal limbic structures that are closely connected with the hippocampus. In conclusion, longer duration of refractory epilepsy was associated with a more intense hippocampal and extrahippocampal atrophy in patients with MTLE. The mechanism of progressive neuronal damage in MTLE may be related to active seizure activity within a limbic network, and early seizure control may prevent further brain atrophy in patients with refractory MTLE.

Purpose: Many patients with focal cortical dysplasia (FCD) continue to have seizures after surgical treatment. The usual explanation for the poor surgical outcome is the presence of residual dysplastic tissue missed by the preoperative neuroimaging investigation and therefore not resected during surgery. We apply a voxel-based morphometry (VBM) analysis to the magnetic resonance imaging (MRI) scans from patients with epilepsy and visually detected FCD to investigate whether (a) VBM is able to detect gray-matter concentration (GMC) abnormalities in patients with FCD, and (b) whether the extent of GMC abnormalities in the brain of these patients differs from the regions observed by using visual inspection., Methods: We studied 11 patients with visually detected FCD (eight of them with histologic confirmation of FCD). The GMC from each one of these patients was compared with the mean GMC from a control group of 96 normal healthy subjects by using an optimized VBM protocol., Results: Ten of 11 patients showed statistically significant GMC excess, and among patients with GMC excess, only one showed GMC excess that was not exactly correspondent to the visually detected FCD. Seven patients exhibited excess in GMC extending beyond the area of visually detected FCD., Conclusions: This preliminary neuroimaging study suggests that (a) VBM can detect GMC excess in patients with FCD, and (b) GMC excess in these patients can extend to brain areas not visually defined as abnormal. Abnormal areas detected by VBM can possibly correspond to mild malformations of cortical development, supporting the notion that the surgical refractoriness observed in patients with FCD can be due to the incomplete resection of the dysplastic tissue.

Objective: To investigate the pattern of perfusion abnormalities in ictal and interictal brain perfusion SPECT images (BSI) from patients with temporal lobe epilepsy (TLE)., Method: It was acquired interictal and ictal BSI from 24 patients with refractory TLE. BSIs were analyzed by visual inspection and statistical parametric mapping (SPM2). Statistical analysis compared the patients group to a control group of 50 volunteers. The images from patients with left-TLE were left-right flipped., Results: It was not observed significant perfusional differences in interictal scans with SPM. Ictal BSI in SPM analysis revealed hyperperfusion within ipsilateral temporal lobe (epileptogenic focus) and also contralateral parieto-occipital region, ipsilateral posterior cingulate gyrus, occipital lobes and ipsilateral basal ganglia. Ictal BSI also showed areas of hypoperfusion., Conclusion: In a group analysis of ictal BSI of patients with TLE, voxel-wise analysis detects a network of distant regions of perfusional alteration which may play active role in seizure genesis and propagation.