Topological Embedding of Human Brain Networks with Applications to Dynamics of Temporal Lobe Epilepsy.

We introduce a novel, data-driven topological data analysis (TDA) approach for embedding brain networks into a lower-dimensional space in quantifying the dynamics of temporal lobe epilepsy (TLE) obtained from resting-state functional magnetic resonance imaging (rs-fMRI). This embedding facilitates the orthogonal projection of 0D and 1D topological features, allowing for the visualization and modeling of the dynamics of functional human brain networks in a resting state. We then quantify the topological disparities between networks to determine the coordinates for embedding. This framework enables us to conduct a coherent statistical inference within the embedded space. Our results indicate that brain network topology in TLE patients exhibits increased rigidity in 0D topology but more rapid flections compared to that of normal controls in 1D topology.

Structural brain morphometry differences and similarities between young patients with Crohn's disease in remission and healthy young and old controls.

Introduction: Crohn's disease (CD), one of the main phenotypes of inflammatory bowel disease (IBD), can affect any part of the gastrointestinal tract. It can impact the function of gastrointestinal secretions, as well as increasing the intestinal permeability leading to an aberrant immunological response and subsequent intestinal inflammation. Studies have reported anatomical and functional brain changes in Crohn's Disease patients (CDs), possibly due to increased inflammatory markers and microglial cells that play key roles in communicating between the brain, gut, and systemic immune system. To date, no studies have demonstrated similarities between morphological brain changes seen in IBD and brain morphometry observed in older healthy controls.. Methods: For the present study, twelve young CDs in remission (M = 26.08 years, SD = 4.9 years, 7 male) were recruited from an IBD Clinic. Data from 12 young age-matched healthy controls (HCs) (24.5 years, SD = 3.6 years, 8 male) and 12 older HCs (59 years, SD = 8 years, 8 male), previously collected for a different study under a similar MR protocol, were analyzed as controls. T1 weighted images and structural image processing techniques were used to extract surface-based brain measures, to test our hypothesis that young CDs have different brain surface morphometry than their age-matched young HCs and furthermore, appear more similar to older HCs. The phonemic verbal fluency (VF) task (the Controlled Oral Word Association Test, COWAT) (Benton, 1976) was administered to test verbal cognitive ability and executive control. Results/Discussion: On the whole, CDs had more brain regions with differences in brain morphometry measures when compared to the young HCs as compared to the old HCs, suggesting that CD has an effect on the brain that makes it appear more similar to old HCs. Additionally, our study demonstrates this atypical brain morphometry is associated with function on a cognitive task. These results suggest that even younger CDs may be showing some evidence of structural brain changes that demonstrate increased resemblance to older HC brains rather than their similarly aged healthy counterparts.

Unified topological inference for brain networks in temporal lobe epilepsy using the Wasserstein distance.

Persistent homology offers a powerful tool for extracting hidden topological signals from brain networks. It captures the evolution of topological structures across multiple scales, known as filtrations, thereby revealing topological features that persist over these scales. These features are summarized in persistence diagrams, and their dissimilarity is quantified using the Wasserstein distance. However, the Wasserstein distance does not follow a known distribution, posing challenges for the application of existing parametric statistical models. To tackle this issue, we introduce a unified topological inference framework centered on the Wasserstein distance. Our approach has no explicit model and distributional assumptions. The inference is performed in a completely data driven fashion. We apply this method to resting-state functional magnetic resonance images (rs-fMRI) of temporal lobe epilepsy patients collected from two different sites: the University of Wisconsin-Madison and the Medical College of Wisconsin. Importantly, our topological method is robust to variations due to sex and image acquisition, obviating the need to account for these variables as nuisance covariates. We successfully localize the brain regions that contribute the most to topological differences. A MATLAB package used for all analyses in this study is available at https://github.com/laplcebeltrami/PH-STAT.

T1-/T2-weighted ratio reveals no alterations to gray matter myelination in temporal lobe epilepsy.

Short-range functional connectivity in the limbic network is increased in patients with temporal lobe epilepsy (TLE), and recent studies have shown that cortical myelin content correlates with fMRI connectivity. We thus hypothesized that myelin may increase progressively in the epileptic network. We compared T1w/T2w gray matter myelin maps between TLE patients and age-matched controls and assessed relationships between myelin and aging. While both TLE patients and healthy controls exhibited increased T1w/T2w intensity with age, we found no evidence for significant group-level aberrations in overall myelin content or myelin changes through time in TLE.

Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge.

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.

Association of neighborhood deprivation with white matter connectome abnormalities in temporal lobe epilepsy.

OBJECTIVE: Social determinants of health, including the effects of neighborhood disadvantage, impact epilepsy prevalence, treatment, and outcomes. This study characterized the association between aberrant white matter connectivity in temporal lobe epilepsy (TLE) and disadvantage using a US census-based neighborhood disadvantage metric, the Area Deprivation Index (ADI), derived from measures of income, education, employment, and housing quality. METHODS: Participants including 74 TLE patients (47 male, mean age = 39.2 years) and 45 healthy controls (27 male, mean age = 31.9 years) from the Epilepsy Connectome Project were classified into ADI-defined low and high disadvantage groups. Graph theoretic metrics were applied to multishell connectome diffusion-weighted imaging (DWI) measurements to derive 162 × 162 structural connectivity matrices (SCMs). The SCMs were harmonized using neuroCombat to account for interscanner differences. Threshold-free network-based statistics were used for analysis, and findings were correlated with ADI quintile metrics. A decrease in cross-sectional area (CSA) indicates reduced white matter integrity. RESULTS: Sex- and age-adjusted CSA in TLE groups was significantly reduced compared to controls regardless of disadvantage status, revealing discrete aberrant white matter tract connectivity abnormalities in addition to apparent differences in graph measures of connectivity and network-based statistics. When comparing broadly defined disadvantaged TLE groups, differences were at trend level. Sensitivity analyses of ADI quintile extremes revealed significantly lower CSA in the most compared to least disadvantaged TLE group. SIGNIFICANCE: Our findings demonstrate (1) the general impact of TLE on DWI connectome status is larger than the association with neighborhood disadvantage; however, (2) neighborhood disadvantage, indexed by ADI, revealed modest relationships with white matter structure and integrity on sensitivity analysis in TLE. Further studies are needed to explore this relationship and determine whether the white matter relationship with ADI is driven by social drift or environmental influences on brain development. Understanding the etiology and course of the disadvantage-brain integrity relationship may serve to inform care, management, and policy for patients.

Application of data harmonization and tract-based spatial statistics reveals white matter structural abnormalities in pediatric patients with focal cortical dysplasia.

Our study assessed diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) in pediatric subjects with epilepsy secondary to Focal Cortical Dysplasia (FCD) to improve our understanding of structural network changes associated with FCD related epilepsy. We utilized a data harmonization (DH) approach to minimize confounding effects induced by MRI protocol differences. We also assessed correlations between DTI metrics and neurocognitive measures of the fluid reasoning index (FRI), verbal comprehension index (VCI), and visuospatial index (VSI). Data (n = 51) from 23 FCD patients and 28 typically developing controls (TD) scanned clinically on either 1.5T, 3T, or 3T-wide-bore MRI were retrospectively analyzed. Tract-based spatial statistics (TBSS) with threshold-free cluster enhancement and permutation testing with 100,000 permutations were used for statistical analysis. To account for imaging protocol differences, we employed non-parametric data harmonization prior to permutation testing. Our analysis demonstrates that DH effectively removed MRI protocol-based differences typical in clinical acquisitions while preserving group differences in DTI metrics between FCD and TD subjects. Furthermore, DH strengthened the association between DTI metrics and neurocognitive indices. Fractional anisotropy, MD, and RD metrics showed stronger correlation with FRI and VSI than VCI. Our results demonstrate that DH is an integral step to reduce the confounding effect of MRI protocol differences during the analysis of white matter tracts and highlights biological differences between FCD and healthy control subjects. Characterization of white matter changes associated with FCD-related epilepsy may better inform prognosis and treatment approaches.

The presence, nature and network characteristics of behavioural phenotypes in temporal lobe epilepsy.

The relationship between temporal lobe epilepsy and psychopathology has had a long and contentious history with diverse views regarding the presence, nature and severity of emotional-behavioural problems in this patient population. To address these controversies, we take a new person-centred approach through the application of unsupervised machine learning techniques to identify underlying latent groups or behavioural phenotypes. Addressed are the distinct psychopathological profiles, their linked frequency, patterns and severity and the disruptions in morphological and network properties that underlie the identified latent groups. A total of 114 patients and 83 controls from the Epilepsy Connectome Project were administered the Achenbach System of Empirically Based Assessment inventory from which six Diagnostic and Statistical Manual of Mental Disorders-oriented scales were analysed by unsupervised machine learning analytics to identify latent patient groups. Identified clusters were contrasted to controls as well as to each other in order to characterize their association with sociodemographic, clinical epilepsy and morphological and functional imaging network features. The concurrent validity of the behavioural phenotypes was examined through other measures of behaviour and quality of life. Patients overall exhibited significantly higher (abnormal) scores compared with controls. However, cluster analysis identified three latent groups: (i) unaffected, with no scale elevations compared with controls (Cluster 1, 37%); (ii) mild symptomatology characterized by significant elevations across several Diagnostic and Statistical Manual of Mental Disorders-oriented scales compared with controls (Cluster 2, 42%); and (iii) severe symptomatology with significant elevations across all scales compared with controls and the other temporal lobe epilepsy behaviour phenotype groups (Cluster 3, 21%). Concurrent validity of the behavioural phenotype grouping was demonstrated through identical stepwise links to abnormalities on independent measures including the National Institutes of Health Toolbox Emotion Battery and quality of life metrics. There were significant associations between cluster membership and sociodemographic (handedness and education), cognition (processing speed), clinical epilepsy (presence and lifetime number of tonic-clonic seizures) and neuroimaging characteristics (cortical volume and thickness and global graph theory metrics of morphology and resting-state functional MRI). Increasingly dispersed volumetric abnormalities and widespread disruptions in underlying network properties were associated with the most abnormal behavioural phenotype. Psychopathology in these patients is characterized by a series of discrete latent groups that harbour accompanying sociodemographic, clinical and neuroimaging correlates. The underlying neurobiological patterns suggest that the degree of psychopathology is linked to increasingly dispersed abnormal brain networks. Similar to cognition, machine learning approaches support a novel developing taxonomy of the comorbidities of epilepsy.

Unified Topological Inference for Brain Networks in Temporal Lobe Epilepsy Using the Wasserstein Distance.

Persistent homology offers a powerful tool for extracting hidden topological signals from brain networks. It captures the evolution of topological structures across multiple scales, known as filtrations, thereby revealing topological features that persist over these scales. These features are summarized in persistence diagrams, and their dissimilarity is quantified using the Wasserstein distance. However, the Wasserstein distance does not follow a known distribution, posing challenges for the application of existing parametric statistical models. To tackle this issue, we introduce a unified topological inference framework centered on the Wasserstein distance. Our approach has no explicit model and distributional assumptions. The inference is performed in a completely data driven fashion. We apply this method to resting-state functional magnetic resonance images (rs-fMRI) of temporal lobe epilepsy patients collected from two different sites: the University of Wisconsin-Madison and the Medical College of Wisconsin. Importantly, our topological method is robust to variations due to sex and image acquisition, obviating the need to account for these variables as nuisance covariates. We successfully localize the brain regions that contribute the most to topological differences. A MATLAB package used for all analyses in this study is available at https://github.com/laplcebeltrami/PH-STAT.

Genetic and environmental influence on resting state networks in young male and female adults: a cartographer mapping study.

We propose a unique, minimal assumption, approach based on variance analyses (compared with standard approaches) to investigate genetic influence on individual differences on the functional connectivity of the brain using 65 monozygotic and 65 dizygotic healthy young adult twin pairs' low-frequency oscillation resting state functional Magnetic Resonance Imaging (fMRI) data from the Human Connectome Project. Overall, we found high number of genetically-influenced functional (GIF) connections involving posterior to posterior brain regions (occipital/temporal/parietal) implicated in low-level processes such as vision, perception, motion, categorization, dorsal/ventral stream visuospatial, and long-term memory processes, as well as high number across midline brain regions (cingulate) implicated in attentional processes, and emotional responses to pain. We found low number of GIF connections involving anterior to anterior/posterior brain regions (frontofrontal > frontoparietal, frontotemporal, frontooccipital) implicated in high-level processes such as working memory, reasoning, emotional judgment, language, and action planning. We found very low number of GIF connections involving subcortical/noncortical networks such as basal ganglia, thalamus, brainstem, and cerebellum. In terms of sex-specific individual differences, individual differences in males were more genetically influenced while individual differences in females were more environmentally influenced in terms of the interplay of interactions of Task positive networks (brain regions involved in various task-oriented processes and attending to and interacting with environment), extended Default Mode Network (a central brain hub for various processes such as internal monitoring, rumination, and evaluation of self and others), primary sensorimotor systems (vision, audition, somatosensory, and motor systems), and subcortical/noncortical networks. There were >8.5-19.1 times more GIF connections in males than females. These preliminary (young adult cohort-specific) findings suggest that individual differences in the resting state brain may be more genetically influenced in males and more environmentally influenced in females; furthermore, standard approaches may suggest that it is more substantially nonadditive genetics, rather than additive genetics, which contribute to the differences in sex-specific individual differences based on this young adult (male and female) specific cohort. Finally, considering the preliminary cohort-specific results, based on standard approaches, environmental influences on individual differences may be substantially greater than that of genetics, for either sex, frontally and brain-wide. [Correction added on 10 May 2023, after first online publication: added: functional Magnetic Resonance Imaging. Added: individual differences in, twice. Added statement between furthermore … based on standard approaches.].

Late dominance of the right hemisphere during narrative comprehension.

PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral multilobar cortical network. The superior temporal resolution of magnetoencephalography (MEG) makes it an attractive tool to investigate the dynamics of how different neuroanatomic substrates engage during narrative comprehension. Using beta-band power changes as a marker of cortical engagement, we studied MEG responses during an auditory story comprehension task in 31 healthy adults. The protocol consisted of two runs, each interleaving 7 blocks of the story comprehension task with 15 blocks of an auditorily presented math task as a control for phonological processing, working memory, and attention processes. Sources at the cortical surface were estimated with a frequency-resolved beamformer. Beta-band power was estimated in the frequency range of 16-24 Hz over 1-sec epochs starting from 400 msec after stimulus onset until the end of a story or math problem presentation. These power estimates were compared to 1-second epochs of data before the stimulus block onset. The task-related cortical engagement was inferred from beta-band power decrements. Group-level source activations were statistically compared using non-parametric permutation testing. A story-math contrast of beta-band power changes showed greater bilateral cortical engagement within the fusiform gyrus, inferior and middle temporal gyri, parahippocampal gyrus, and left inferior frontal gyrus (IFG) during story comprehension. A math-story contrast of beta power decrements showed greater bilateral but left-lateralized engagement of the middle frontal gyrus and superior parietal lobule. The evolution of cortical engagement during five temporal windows across the presentation of stories showed significant involvement during the first interval of the narrative of bilateral opercular and insular regions as well as the ventral and lateral temporal cortex, extending more posteriorly on the left and medially on the right. Over time, there continued to be sustained right anterior ventral temporal engagement, with increasing involvement of the right anterior parahippocampal gyrus, STG, MTG, posterior superior temporal sulcus, inferior parietal lobule, frontal operculum, and insula, while left hemisphere engagement decreased. Our findings are consistent with prior imaging studies of narrative comprehension, but in addition, they demonstrate increasing right-lateralized engagement over the course of narratives, suggesting an important role for these right-hemispheric regions in semantic integration as well as social and pragmatic inference processing.

Translingual neural stimulation affects resting-state functional connectivity in mild-moderate traumatic brain injury.

BACKGROUND AND PURPOSE: Traumatic brain injury (TBI) can lead to movement and balance deficits. In addition to physical therapy, brain-based neurorehabilitation efforts have begun to show promise in improving these deficits. The present study investigated the effectiveness of translingual neural stimulation (TLNS) on patients with mild-to-moderate TBI (mmTBI) and related brain connectivity using a resting-state functional connectivity (RSFC) approach. METHODS: Resting-state images with 5-min on GE750 3T scanner were acquired from nine participants with mmTBI. Paired t-test was used for calculating changes in RSFC and behavioral scores before and after the TLNS intervention. The balance and movement performances related to mmTBI were evaluated by Sensory Organization Test (SOT) and Dynamic Gait Index (DGI). RESULTS: Compared to pre-TLNS intervention, significant behavioral changes in SOT and DGI were observed. The analysis revealed increased RSFC between the left postcentral gyrus and left inferior parietal lobule and left Brodmann Area 40, as well as the increased RSFC between the right culmen and right declive, indicating changes due to TLNS treatment. However, there were no correlations between the sensory/somatomotor (or visual or cerebellar) network and SOT/DGI behavioral performance. CONCLUSIONS: Although the limited sample size may have led to lack of significant correlations with functional assessments, these results provide preliminary evidence that TLNS in conjunction with physical therapy can induce brain plasticity in TBI patients with balance and movement deficits.

Alterations in white matter microstructural properties after lingual strength exercise in patients with dysphagia.

OBJECTIVES: Central nervous system effects of lingual strengthening exercise to treat dysphagia remain largely unknown. This pilot study measured changes in microstructural white matter to capture alterations in neural signal processing following lingual strengthening exercise. METHODS: Diffusion-weighted images were acquired from seven participants with dysphagia of varying etiologies, before and after lingual strengthening exercise (20 reps, 3×/day, 3 days/week, 8 weeks), using a 10-min diffusion sequence (9 b0, 56 directions with b1000) on GE750 3T scanner. Tract-Based Spatial Statistics evaluated voxel-based group differences for fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity and local diffusion homogeneity (LDH). Paired t-tests evaluated treatment differences on each metric (P < 0.05). RESULTS: After lingual strengthening exercise, lingual pressure generation increased (avg increase = 46.1 hPa; nonsignificant P = 0.52) with these changes in imaging metrics: (1) decrease in fractional anisotropy, forceps minor; (2) increase in mean diffusivity, right inferior fronto-occipital fasciculus (IFOF); (3) decrease in mean diffusivity, left uncinate fasciculus; (4) decrease in axial diffusivity, both left IFOF and left uncinate fasciculus; (5) increase in LDH, right anterior thalamic radiation and (6) decrease in LDH, temporal portion of right superior longitudinal fasciculus. There was a positive correlation between diffusion tensor imaging metrics and change in lingual pressure generation in left IFOF and the temporal portion of right superior longitudinal fasciculus. CONCLUSIONS: These findings suggest that lingual strengthening exercise can induce changes in white matter structural and functional properties in a small group of patients with dysphagia of heterogeneous etiologies. These procedures should be repeated with a larger group of patients to improve interpretation of overall lingual strengthening exercise effects on cortical structure and function.

Characterizing the relationship between lesion-activation distance using fMRI and verbal measures in brain tumor patients.

Functional resonance magnetic imaging (fMRI) allows for identification of eloquent cortex in pre-treatment planning. Previous studies have shown a correlation among lesion to activation distance (LAD) measures and morbidity and mortality. This study investigates the relationship between LAD, well-established language centers (Wernicke's and Broca's), and language performance measures. We included a sample population of brain tumor patients that received language fMRI (verbal fluency and sentence verification) for pre-treatment assessment (n = 51). LAD to the nearest language area was measured and divided into groups ≤ 10 mm and > 10 mm. Verbal fluency scores were compared between these groups. Additionally, patients were divided into similar groups based on LAD to either Broca's or Wernicke's areas, and the verbal fluency scores and sentence verification accuracy (n = 29) were subsequently compared between groups. Brain tumor patients with LAD ≤ 10 mm to either language area had significantly lower verbal fluency scores (p = 0.028). The difference in verbal fluency scores between groups with LAD ≤ 10 mm and > 10 mm to Wernicke's area trends toward significance (p = 0.067). The sentence verification accuracy was significantly lower in patients with LAD ≤ 10 mm to either language area (p = 0.039). These findings suggest that there exists a significant relationship between LAD to language centers and measures; greater language deficits are seen when LAD ≤ 10 mm.

Differences in Diffusion Tensor Imaging White Matter Integrity Related to Verbal Fluency Between Young and Old Adults.

Throughout adulthood, the brain undergoes an array of structural and functional changes during the typical aging process. These changes involve decreased brain volume, reduced synaptic density, and alterations in white matter (WM). Although there have been some previous neuroimaging studies that have measured the ability of adult language production and its correlations to brain function, structural gray matter volume, and functional differences between young and old adults, the structural role of WM in adult language production in individuals across the life span remains to be thoroughly elucidated. This study selected 38 young adults and 35 old adults for diffusion tensor imaging (DTI) and performed the Controlled Oral Word Association Test to assess verbal fluency (VF). Tract-Based Spatial Statistics were employed to evaluate the voxel-based group differences of diffusion metrics for the values of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and local diffusion homogeneity (LDH) in 12 WM regions of interest associated with language production. To investigate group differences on each DTI metric, an analysis of covariance (ANCOVA) controlling for sex and education level was performed, and the statistical threshold was considered at p < 0.00083 (0.05/60 labels) after Bonferroni correction for multiple comparisons. Significant differences in DTI metrics identified in the ANCOVA were used to perform correlation analyses with VF scores. Compared to the old adults, the young adults had significantly (1) increased FA values on the bilateral anterior corona radiata (ACR); (2) decreased MD values on the right ACR, but increased MD on the left uncinate fasciculus (UF); and (3) decreased RD on the bilateral ACR. There were no significant differences between the groups for AD or LDH. Moreover, the old adults had only a significant correlation between the VF score and the MD on the left UF. There were no significant correlations between VF score and DTI metrics in the young adults. This study adds to the growing body of research that WM areas involved in language production are sensitive to aging.

Ipsilesional Mu Rhythm Desynchronization Correlates With Improvements in Affected Hand Grip Strength and Functional Connectivity in Sensorimotor Cortices Following BCI-FES Intervention for Upper Extremity in Stroke Survivors.

Stroke is a leading cause of acquired long-term upper extremity motor disability. Current standard of care trajectories fail to deliver sufficient motor rehabilitation to stroke survivors. Recent research suggests that use of brain-computer interface (BCI) devices improves motor function in stroke survivors, regardless of stroke severity and chronicity, and may induce and/or facilitate neuroplastic changes associated with motor rehabilitation. The present sub analyses of ongoing crossover-controlled trial NCT02098265 examine first whether, during movements of the affected hand compared to rest, ipsilesional Mu rhythm desynchronization of cerebral cortical sensorimotor areas [Brodmann's areas (BA) 1-7] is localized and tracks with changes in grip force strength. Secondly, we test the hypothesis that BCI intervention results in changes in frequency-specific directional flow of information transmission (direct path functional connectivity) in BA 1-7 by measuring changes in isolated effective coherence (iCoh) between cerebral cortical sensorimotor areas thought to relate to electrophysiological signatures of motor actions and motor learning. A sample of 16 stroke survivors with right hemisphere lesions (left hand motor impairment), received a maximum of 18-30 h of BCI intervention. Electroencephalograms were recorded during intervention sessions while outcome measures of motor function and capacity were assessed at baseline and completion of intervention. Greater desynchronization of Mu rhythm, during movements of the impaired hand compared to rest, were primarily localized to ipsilesional sensorimotor cortices (BA 1-7). In addition, increased Mu desynchronization in the ipsilesional primary motor cortex, Post vs. Pre BCI intervention, correlated significantly with improvements in hand function as assessed by grip force measurements. Moreover, the results show a significant change in the direction of causal information flow, as measured by iCoh, toward the ipsilesional motor (BA 4) and ipsilesional premotor cortices (BA 6) during BCI intervention. Significant iCoh increases from ipsilesional BA 4 to ipsilesional BA 6 were observed in both Mu [8-12 Hz] and Beta [18-26 Hz] frequency ranges. In summary, the present results are indicative of improvements in motor capacity and behavior, and they are consistent with the view that BCI-FES intervention improves functional motor capacity of the ipsilesional hemisphere and the impaired hand.

Brain-Computer Interface Training With Functional Electrical Stimulation: Facilitating Changes in Interhemispheric Functional Connectivity and Motor Outcomes Post-stroke.

While most survivors of stroke experience some spontaneous recovery and receive treatment in the subacute setting, they are often left with persistent impairments in upper limb sensorimotor function which impact autonomy in daily life. Brain-Computer Interface (BCI) technology has shown promise as a form of rehabilitation that can facilitate motor recovery after stroke, however, we have a limited understanding of the changes in functional connectivity and behavioral outcomes associated with its use. Here, we investigate the effects of EEG-based BCI intervention with functional electrical stimulation (FES) on resting-state functional connectivity (rsFC) and motor outcomes in stroke recovery. 23 patients post-stroke with upper limb motor impairment completed BCI intervention with FES. Resting-state functional magnetic resonance imaging (rs-fMRI) scans and behavioral data were collected prior to intervention, post- and 1-month post-intervention. Changes in rsFC within the motor network and behavioral measures were investigated to identify brain-behavior correlations. At the group-level, there were significant increases in interhemispheric and network rsFC in the motor network after BCI intervention, and patients significantly improved on the Action Research Arm Test (ARAT) and SIS domains. Notably, changes in interhemispheric rsFC from pre- to both post- and 1 month post-intervention correlated with behavioral improvements across several motor-related domains. These findings suggest that BCI intervention with FES can facilitate interhemispheric connectivity changes and upper limb motor recovery in patients after stroke.

Comparison of Language and Memory Lateralization by Functional MRI and Wada Test in Epilepsy.

The intracarotid sodium amobarbital procedure (ISAP or Wada test) lateralizes cerebral functions to the cerebral hemispheres preoperatively. Functional magnetic resonance imaging (fMRI) is increasingly used to characterize preoperative language and memory lateralization. In this study, concordance of fMRI with Wada was examined in patients with medically intractable seizures. The relationship of the distance between the epileptogenic focus to functional activation area with patients' post-operative deficits in language was also analyzed. 27 epilepsy patients with preoperative fMRI and Wada data were analyzed using established fMRI paradigms for language and memory. Activation of Broca's and Wernicke's areas were measured in three dimensions. Language and memory lateralization were determined, and standard neuropsychiatry Wada test procedures were used for comparison. The shortest distance between a language area to the border of surgical focus (LAD) was also measured and compared with postoperative language deficits. Our study found that concordance between fMRI and Wada testing was 0.41 (Kappa's 'fair to good' concordance) for language dominance and 0.1 (Kappa's 'poor' concordance) for memory. No significant correlation was found between LAD and post-op language deficit (p=0.439). A correlation was found between LAD and post-op memory deficit (p=0.049; the further distance from surgical lesion to language area is associated with less post-operative memory loss). Females demonstrated significantly increased postoperative seizure improvement (Fisher's p-value=0.0296; female=8; male=6). A significant association between handedness (right-handed subjects) and postoperative seizure improvement was found (p=0.02) as well as a significant trend for interaction of gender and handedness on postoperative seizure improvement (p=0.09). Overall, our results demonstrate fMRI as a useful preoperative adjunct to Wada testing for language lateralization in patients with medically intractable seizures.

Network, clinical and sociodemographic features of cognitive phenotypes in temporal lobe epilepsy.

This study explored the taxonomy of cognitive impairment within temporal lobe epilepsy and characterized the sociodemographic, clinical and neurobiological correlates of identified cognitive phenotypes. 111 temporal lobe epilepsy patients and 83 controls (mean ages 33 and 39, 57% and 61% female, respectively) from the Epilepsy Connectome Project underwent neuropsychological assessment, clinical interview, and high resolution 3T structural and resting-state functional MRI. A comprehensive neuropsychological test battery was reduced to core cognitive domains (language, memory, executive, visuospatial, motor speed) which were then subjected to cluster analysis. The resulting cognitive subgroups were compared in regard to sociodemographic and clinical epilepsy characteristics as well as variations in brain structure and functional connectivity. Three cognitive subgroups were identified (intact, language/memory/executive function impairment, generalized impairment) which differed significantly, in a systematic fashion, across multiple features. The generalized impairment group was characterized by an earlier age at medication initiation (P < 0.05), fewer patient (P < 0.001) and parental years of education (P < 0.05), greater racial diversity (P < 0.05), and greater number of lifetime generalized seizures (P < 0.001). The three groups also differed in an orderly manner across total intracranial (P < 0.001) and bilateral cerebellar cortex volumes (P < 0.01), and rate of bilateral hippocampal atrophy (P < 0.014), but minimally in regional measures of cortical volume or thickness. In contrast, large-scale patterns of cortical-subcortical covariance networks revealed significant differences across groups in global and local measures of community structure and distribution of hubs. Resting-state fMRI revealed stepwise anomalies as a function of cluster membership, with the most abnormal patterns of connectivity evident in the generalized impairment group and no significant differences from controls in the cognitively intact group. Overall, the distinct underlying cognitive phenotypes of temporal lobe epilepsy harbor systematic relationships with clinical, sociodemographic and neuroimaging correlates. Cognitive phenotype variations in patient and familial education and ethnicity, with linked variations in total intracranial volume, raise the question of an early and persisting socioeconomic-status related neurodevelopmental impact, with additional contributions of clinical epilepsy factors (e.g., lifetime generalized seizures). The neuroimaging features of cognitive phenotype membership are most notable for disrupted large scale cortical-subcortical networks and patterns of functional connectivity with bilateral hippocampal and cerebellar atrophy. The cognitive taxonomy of temporal lobe epilepsy appears influenced by features that reflect the combined influence of socioeconomic, neurodevelopmental and neurobiological risk factors.

Brain aging in temporal lobe epilepsy: Chronological, structural, and functional.

The association of epilepsy with structural brain changes and cognitive abnormalities in midlife has raised concern regarding the possibility of future accelerated brain and cognitive aging and increased risk of later life neurocognitive disorders. To address this issue we examined age-related processes in both structural and functional neuroimaging among individuals with temporal lobe epilepsy (TLE, N = 104) who were participants in the Epilepsy Connectome Project (ECP). Support vector regression (SVR) models were trained from 151 healthy controls and used to predict TLE patients' brain ages. It was found that TLE patients on average have both older structural (+6.6 years) and functional (+8.3 years) brain ages compared to healthy controls. Accelerated functional brain age (functional - chronological age) was mildly correlated (corrected P = 0.07) with complex partial seizure frequency and the number of anti-epileptic drug intake. Functional brain age was a significant correlate of declining cognition (fluid abilities) and partially mediated chronological age-fluid cognition relationships. Chronological age was the only positive predictor of crystallized cognition. Accelerated aging is evident not only in the structural brains of patients with TLE, but also in their functional brains. Understanding the causes of accelerated brain aging in TLE will be clinically important in order to potentially prevent or mitigate their cognitive deficits.