Neuroanatomy of cerebellar mutism syndrome: the role of lesion location.

Approximately 25% of paediatric patients who undergo cerebellar tumour resection develop cerebellar mutism syndrome. Our group recently showed that damage to the cerebellar deep nuclei and superior cerebellar peduncles, which we refer to as the cerebellar outflow pathway, is associated with an increased risk of cerebellar mutism syndrome. Here, we tested whether these findings replicate in an independent cohort. We evaluated the relationship between lesion location and the development of cerebellar mutism syndrome in an observational study of 56 paediatric patients ranging from five months to 14 years of age who underwent cerebellar tumour resection. We hypothesized that individuals who developed cerebellar mutism syndrome after surgery, relative to those who did not, would have lesions that preferentially intersect with: (i) the cerebellar outflow pathway and (ii) a previously generated 'lesion-symptom map' of cerebellar mutism syndrome. Analyses were conducted in accordance with pre-registered hypotheses and analytic methods (https://osf.io/r8yjv/). We found supporting evidence for both hypotheses. Compared to patients who did not develop cerebellar mutism syndrome, patients with cerebellar mutism syndrome (n = 10) had lesions with greater overlap with the cerebellar outflow pathway (Cohen's d = 0.73, P = 0.05), and the cerebellar mutism syndrome lesion-symptom map (Cohen's d = 1.1, P = 0.004). These results strengthen the association of lesion location with the risk of developing cerebellar mutism syndrome and demonstrate generalizability across cohorts. These findings may help to inform the optimal surgical approach to paediatric cerebellar tumours.

Neuromodulation with Ultrasound: Hypotheses on the Directionality of Effects and a Community Resource.

Low-intensity Transcranial Ultrasound Stimulation (TUS) is a promising non-invasive technique for deep-brain stimulation and focal neuromodulation. Research with animal models and computational modelling has raised the possibility that TUS can be biased towards enhancing or suppressing neural function. Here, we first conduct a systematic review of human TUS studies for perturbing neural function and alleviating brain disorders. We then collate a set of hypotheses on the directionality of TUS effects and conduct an initial meta-analysis on the human TUS study reported outcomes to date (n = 32 studies, 37 experiments). We find that parameters such as the duty cycle show some predictability regarding whether the targeted area's function is likely to be enhanced or suppressed. Given that human TUS sample sizes are exponentially increasing, we recognize that results can stabilize or change as further studies are reported. Therefore, we conclude by establishing an Iowa-Newcastle (inTUS) resource for the systematic reporting of TUS parameters and outcomes to support further hypothesis testing for greater precision in brain stimulation and neuromodulation with TUS.

TMS provokes target-dependent intracranial rhythms across human cortical and subcortical sites.

BACKGROUND: Transcranial magnetic stimulation (TMS) is believed to alter ongoing neural activity and cause circuit-level changes in brain function. While the electrophysiological effects of TMS have been extensively studied with scalp electroencephalography (EEG), this approach generally evaluates low-frequency neural activity at the cortical surface. However, TMS can be safely used in patients with intracranial electrodes (iEEG), allowing for direct assessment of deeper and more localized oscillatory responses across the frequency spectrum. OBJECTIVE/HYPOTHESIS: Our study used iEEG to understand the effects of TMS on human neural activity in the spectral domain. We asked (1) which brain regions respond to cortically-targeted TMS, and in what frequency bands, (2) whether deeper brain structures exhibit oscillatory responses, and (3) whether the neural responses to TMS reflect evoked versus induced oscillations. METHODS: We recruited 17 neurosurgical patients with indwelling electrodes and recorded neural activity while patients underwent repeated trials of single-pulse TMS at either the dorsolateral prefrontal cortex (DLPFC) or parietal cortex. iEEG signals were analyzed using spectral methods to understand the oscillatory responses to TMS. RESULTS: Stimulation to DLPFC drove widespread low-frequency increases (3-8 Hz) in frontolimbic cortices and high-frequency decreases (30-110 Hz) in frontotemporal areas, including the hippocampus. Stimulation to parietal cortex specifically provoked low-frequency responses in the medial temporal lobe. While most low-frequency activity was consistent with phase-locked evoked responses, anterior frontal regions exhibited induced theta oscillations following DLPFC stimulation. CONCLUSIONS: By combining TMS with intracranial EEG recordings, our results suggest that TMS is an effective means to perturb oscillatory neural activity in brain-wide networks, including deeper structures not directly accessed by stimulation itself.

Network localization of pediatric lesion-induced dystonia.

Objective: Dystonia is a movement disorder defined by involuntary muscle contractions leading to abnormal postures or twisting and repetitive movements. Classically dystonia has been thought of as a disorder of the basal ganglia, but newer results in idiopathic dystonia and lesion-induced dystonia in adults point to broader motor network dysfunction spanning the basal ganglia, cerebellum, premotor cortex, sensorimotor, and frontoparietal regions. It is unclear whether a similar network is shared between different etiologies of pediatric lesion-induced dystonia. Methods: Three cohorts of pediatric patients with lesion-induced dystonia were identified. The lesion etiologies included hypoxia, kernicterus, and stroke versus comparison subjects with acquired lesions not associated with dystonia. Multivariate lesion-symptom mapping and lesion network mapping were used to evaluate the anatomy and networks associated with dystonia. Results: Multivariate lesion-symptom mapping showed that lesions of the putamen (stroke: r = 0.50, p <0.01; hypoxia, r = 0.64, p <0.001) and globus pallidus (kernicterus, r = 0.61, p <0.01) were associated with dystonia. Lesion network mapping using normative connectome data from healthy children demonstrated that these regional findings occurred within a common brain-wide network that involves the basal ganglia, anterior and medial cerebellum, and cortical regions that overlap the cingulo-opercular and somato-cognitive-action networks. Interpretation: We interpret these findings as novel evidence for a unified dystonia brain network that involves the somato-cognitive-action network, which is involved in higher order coordination of movement. Elucidation of this network gives insight into the functional origins of dystonia and provides novel targets to investigate for therapeutic intervention.

Effects of transcranial magnetic stimulation on the human brain recorded with intracranial electrocorticography.

Transcranial magnetic stimulation (TMS) is increasingly used as a noninvasive technique for neuromodulation in research and clinical applications, yet its mechanisms are not well understood. Here, we present the neurophysiological effects of TMS using intracranial electrocorticography (iEEG) in neurosurgical patients. We first evaluated safety in a gel-based phantom. We then performed TMS-iEEG in 22 neurosurgical participants with no adverse events. We next evaluated intracranial responses to single pulses of TMS to the dorsolateral prefrontal cortex (dlPFC) (N = 10, 1414 electrodes). We demonstrate that TMS is capable of inducing evoked potentials both locally within the dlPFC and in downstream regions functionally connected to the dlPFC, including the anterior cingulate and insular cortex. These downstream effects were not observed when stimulating other distant brain regions. Intracranial dlPFC electrical stimulation had similar timing and downstream effects as TMS. These findings support the safety and promise of TMS-iEEG in humans to examine local and network-level effects of TMS with higher spatiotemporal resolution than currently available methods.

Supra-second interval timing in bipolar disorder: examining the role of disorder sub-type, mood, and medication status.

BACKGROUND: Widely reported by bipolar disorder (BD) patients, cognitive symptoms, including deficits in executive function, memory, attention, and timing are under-studied. Work suggests that individuals with BD show impairments in interval timing tasks, including supra-second, sub-second, and implicit motor timing compared to the neuronormative population. However, how time perception differs within individuals with BD based on disorder sub-type (BDI vs II), depressed mood, or antipsychotic medication-use has not been thoroughly investigated. The present work administered a supra-second interval timing task concurrent with electroencephalography (EEG) to patients with BD and a neuronormative comparison group. As this task is known to elicit frontal theta oscillations, signal from the frontal (Fz) lead was analyzed at rest and during the task. RESULTS: Results suggest that individuals with BD show impairments in supra-second interval timing and reduced frontal theta power during the task compared to neuronormative controls. However, within BD sub-groups, neither time perception nor frontal theta differed in accordance with BD sub-type, depressed mood, or antipsychotic medication use. CONCLUSIONS: This work suggests that BD sub-type, depressed mood status or antipsychotic medication use does not alter timing profile or frontal theta activity. Together with previous work, these findings point to timing impairments in BD patients across a wide range of modalities and durations indicating that an altered ability to assess the passage of time may be a fundamental cognitive abnormality in BD.

Anterolateral temporal lobe localization of dysnomia after temporal lobe epilepsy surgery.

Objectives: To evaluate what factors influence naming ability after temporal lobectomy in patients with drug-resistant epilepsy. Methods: 85 participants with drug-resistant epilepsy who underwent temporal lobe (TL) resective surgery were retrospectively identified (49 left TL and 36 right TL). Naming ability was assessed before and >3 months post-surgery using the Boston Naming Test (BNT).Multivariate lesion-symptom mapping was performed to evaluate whether lesion location related to naming deficits. Multiple regression analyses were conducted to examine if other patient characteristics were significantly associated with pre-to post-surgery changes in naming ability. Results: Lesion laterality and location were important predictors of post-surgical naming performance. Naming performance significantly improved after right temporal lobectomy ( p = 0.015) while a decrement in performance was observed following left temporal lobectomy ( p = 0.002). Lesion-symptom mapping showed the decline in naming performance was associated with surgical resection of the anterior left middle temporal gyrus (Brodmann area 21, r =0.41, p = <.001). For left hemisphere surgery, later onset of epilepsy was associated with a greater reduction in post-surgical naming performance ( p = 0.01). Significance: There is a wide range of variability in outcomes for naming ability after temporal lobectomy, from significant improvements to decrements observed. If future studies support the association of left anterior middle temporal gyrus resection and impaired naming this may help in surgical planning and discussions of prognosis.

A randomized trial comparing beam F3 and 5.5 cm targeting in rTMS treatment of depression demonstrates similar effectiveness.

BACKGROUND: The Beam F3 and 5.5 cm methods are the two most common targeting strategies for localizing the left dorsolateral prefrontal cortex (DLPFC) treatment site in repetitive transcranial magnetic stimulation (rTMS) protocols. This prospective, randomized, double-blind comparative effectiveness trial assesses the clinical outcomes for these two methods in a naturalistic sample of patients with major depressive disorder (MDD) undergoing clinical rTMS treatment. METHODS: 105 adult patients with MDD (mean age = 43.2; range = 18-73; 66% female) were randomized to receive rTMS to the Beam F3 (n = 58) or 5.5 cm (n = 47) target. Between group differences from pre-to post-treatment were evaluated with the Patient Health Questionnaire-9 (PHQ-9) [primary outcome measure], Generalized Anxiety Disorder-7 (GAD-7), and clinician-administered Montgomery-Åsberg Depression Scale (MADRS). Primary treatment endpoint was completion of daily treatment series. RESULTS: Per-protocol analyses showed no statistically significant differences on any measure between the 5.5 cm and F3 groups (all p ≥ 0.50), including percent improvement (PHQ-9: 39% vs. 39%; GAD-7: 34% vs. 27%; MADRS: 40% vs. 38%), response rate (PHQ-9: 37% vs. 43%; GAD-7: 27% vs. 30%; MADRS: 43% vs. 43%), and remission rate (PHQ-9: 22% vs. 21%; MADRS: 20% vs. 19%). Post hoc analysis of anxiety symptom change while controlling for depression severity suggested more favorable anxiolytic effects with 5.5 cm targeting (p = 0.03). CONCLUSIONS: Similar antidepressant effects were observed with DLFPC rTMS using either the Beam F3 or 5.5 cm targeting method, supporting clinical equipoise in MDD patients with head circumference ≤ 60 cm. Comparison to MRI-based targeting and differential effects on anxiety symptoms require further investigation. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03378570.

Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes.

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9±18.0 years; time since stroke 12.2±0.2 months; normalised motor score 0.7±0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.

TMS provokes target-dependent intracranial rhythms across human cortical and subcortical sites.

Transcranial magnetic stimulation (TMS) is increasingly deployed in the treatment of neuropsychiatric illness, under the presumption that stimulation of specific cortical targets can alter ongoing neural activity and cause circuit-level changes in brain function. While the electrophysiological effects of TMS have been extensively studied with scalp electroencephalography (EEG), this approach is most useful for evaluating low-frequency neural activity at the cortical surface. As such, little is known about how TMS perturbs rhythmic activity among deeper structures - such as the hippocampus and amygdala - and whether stimulation can alter higher-frequency oscillations. Recent work has established that TMS can be safely used in patients with intracranial electrodes (iEEG), allowing for direct neural recordings at sufficient spatiotemporal resolution to examine localized oscillatory responses across the frequency spectrum. To that end, we recruited 17 neurosurgical patients with indwelling electrodes and recorded neural activity while patients underwent repeated trials of single-pulse TMS at several cortical sites. Stimulation to the dorsolateral prefrontal cortex (DLPFC) drove widespread low-frequency increases (3-8Hz) in frontolimbic cortices, as well as high-frequency decreases (30-110Hz) in frontotemporal areas, including the hippocampus. Stimulation to parietal cortex specifically provoked low-frequency responses in the medial temporal lobe. While most low-frequency activity was consistent with brief evoked responses, anterior frontal regions exhibited induced theta oscillations following DLPFC stimulation. Taken together, we established that non-invasive stimulation can (1) provoke a mixture of low-frequency evoked power and induced theta oscillations and (2) suppress high-frequency activity in deeper brain structures not directly accessed by stimulation itself.

Functional geometry of auditory cortical resting state networks derived from intracranial electrophysiology.

Understanding central auditory processing critically depends on defining underlying auditory cortical networks and their relationship to the rest of the brain. We addressed these questions using resting state functional connectivity derived from human intracranial electroencephalography. Mapping recording sites into a low-dimensional space where proximity represents functional similarity revealed a hierarchical organization. At a fine scale, a group of auditory cortical regions excluded several higher-order auditory areas and segregated maximally from the prefrontal cortex. On mesoscale, the proximity of limbic structures to the auditory cortex suggested a limbic stream that parallels the classically described ventral and dorsal auditory processing streams. Identities of global hubs in anterior temporal and cingulate cortex depended on frequency band, consistent with diverse roles in semantic and cognitive processing. On a macroscale, observed hemispheric asymmetries were not specific for speech and language networks. This approach can be applied to multivariate brain data with respect to development, behavior, and disorders.

Supra-second interval timing in bipolar disorder: examining the role of disorder sub-type, mood, and medication status.

Background : Widely reported by bipolar disorder (BD) patients, cognitive symptoms, including deficits in executive function, memory, attention, and timing are under-studied. Work suggests that individuals with BD show impairments in interval timing tasks, including supra-second, sub-second, and implicit motor timing compared to the neuronormative population. However, how time perception differs within individuals with BD based on BD sub-type (BDI vs II), mood, or antipsychotic medication-use has not been thoroughly investigated. The present work administered a supra-second interval timing task concurrent with electroencephalography (EEG) to patients with BD and a neuronormative comparison group. As this task is known to elicit frontal theta oscillations, signal from the frontal (Fz) lead was analyzed at rest and during the task. Results : Results suggest that individuals with BD show impairments in supra-second interval timing and reduced frontal theta power compared during the task to neuronormative controls. However, within BD sub-groups, neither time perception nor frontal theta differed in accordance with BD sub-type, mood, or antipsychotic medication use. Conclusions : his work suggests that BD sub-type, mood status or antipsychotic medication use does not alter timing profile or frontal theta activity. Together with previous work, these findings point to timing impairments in BD patients across a wide range of modalities and durations indicating that an altered ability to assess the passage of time may be a fundamental cognitive abnormality in BD.

High-dimensional multivariate autoregressive model estimation of human electrophysiological data using fMRI priors.

Multivariate autoregressive (MVAR) model estimation enables assessment of causal interactions in brain networks. However, accurately estimating MVAR models for high-dimensional electrophysiological recordings is challenging due to the extensive data requirements. Hence, the applicability of MVAR models for study of brain behavior over hundreds of recording sites has been very limited. Prior work has focused on different strategies for selecting a subset of important MVAR coefficients in the model to reduce the data requirements of conventional least-squares estimation algorithms. Here we propose incorporating prior information, such as resting state functional connectivity derived from functional magnetic resonance imaging, into MVAR model estimation using a weighted group least absolute shrinkage and selection operator (LASSO) regularization strategy. The proposed approach is shown to reduce data requirements by a factor of two relative to the recently proposed group LASSO method of Endemann et al (Neuroimage 254:119057, 2022) while resulting in models that are both more parsimonious and more accurate. The effectiveness of the method is demonstrated using simulation studies of physiologically realistic MVAR models derived from intracranial electroencephalography (iEEG) data. The robustness of the approach to deviations between the conditions under which the prior information and iEEG data is obtained is illustrated using models from data collected in different sleep stages. This approach allows accurate effective connectivity analyses over short time scales, facilitating investigations of causal interactions in the brain underlying perception and cognition during rapid transitions in behavioral state.

Neuroanatomy of Cerebellar Mutism Syndrome: The Role of Lesion Location.

Approximately 25% of pediatric patients who undergo cerebellar tumor resection develop cerebellar mutism syndrome (CMS). Our group recently showed that damage to the cerebellar deep nuclei and superior cerebellar peduncles, which we refer to as the cerebellar outflow pathway, is associated with increased risk of CMS. Here, we tested whether these findings replicate in an independent cohort. We evaluated the relationship between lesion location and the development of CMS in an observational study of 56 pediatric patients who underwent cerebellar tumor resection. We hypothesized that individuals that developed CMS after surgery (CMS+), relative to those that did not (CMS-) would have lesions that preferentially intersected with: 1) the cerebellar outflow pathway, and 2) a previously generated 'lesion-symptom map' of CMS. Analyses were conducted in accordance with pre-registered hypotheses and analytic methods (https://osf.io/r8yjv/). We found supporting evidence for both hypotheses. Compared with CMS- patients, CMS + patients (n = 10) had lesions with greater overlap with the cerebellar outflow pathway (Cohen's d = .73, p = .05), and the CMS lesion-symptom map (Cohen's d = 1.1, p = .004). These results strengthen the association of lesion location with risk of developing CMS and demonstrate generalizability across cohorts. These findings may help to inform the optimal surgical approach to pediatric cerebellar tumors.

Localization of a Medial Temporal Lobe-Precuneus Network for Time Orientation.

OBJECTIVE: Time orientation is a fundamental cognitive process in which one's personal sense of time is matched with a universal reference. Time orientation is commonly assessed through mental status examination, yet its neural correlates remain unclear. Large lesions have been associated with deficits in time orientation, but the regional anatomy implicated in time disorientation is not well established. The current study investigates the anatomy of time disorientation and its network correlates in patients with focal brain lesions. METHODS: Time orientation was assessed 3 months or more after lesion onset using the Benton Temporal Orientation Test (BTOT) in 550 patients with acquired, focal brain lesions, 39 of whom were impaired. Multivariate lesion-symptom mapping and lesion network mapping were used to evaluate the anatomy and networks associated with time disorientation. Performance on a variety of neuropsychological tests was compared between the time oriented and time disoriented group. RESULTS: Lesion-symptom mapping showed that lesions of the precuneus, medial temporal lobes (MTL), and occipito-temporal cortex were associated with time disorientation (r = 0.264, p < 0.001). Lesion network mapping using normative connectome data demonstrated that these regional findings occurred along a network that includes white and gray matter connecting the precuneus and MTL. There was a strong behavioral and anatomical association of time disorientation with memory impairment, such that the 2 processes could not be fully disentangled. INTERPRETATION: We interpret these findings as novel evidence for a network involving the precuneus and the medial temporal lobe in supporting time orientation. ANN NEUROL 2023;94:421-433.

Sustained, Effortless Weight Loss after Damage to the Left Frontoinsular Cortex: A Case Report.

This case report highlights a possible consequence of damage to the left frontoinsular region. A 53-year-old woman with chronic obesity and headaches presented with seizure, leading to the discovery and resection of a large sphenoid wing meningioma. Postoperative brain imaging revealed loss of the left frontoinsular cortex and portions of the underlying white matter, claustrum, and striatum. Throughout her adult life, this patient had tried and failed to lose weight, but after surgery, she no longer desired to eat large meals, and without effort, her body mass index decreased from 38.6 (85th percentile) to 24.9 (25th percentile). Combined with previous research implicating the insular cortex in interoception, appetite, and drug-related urges, her reduced hunger and effortless weight loss after resection of the left frontoinsular cortex suggest that this region of the human brain may play a role in hunger-related urges that contribute to overeating.

Implications of age at lesion onset for neuropsychological outcomes: A systematic review focusing on focal brain lesions.

Theories of the relation between age at lesion onset and outcomes posit different views of the young brain: resilient and plastic (i.e., the so-called "Kennard Principle"), or vulnerable (i.e., the Early Vulnerability Hypothesis). There is support for both perspectives in previous research and questions about the "best" or "worst" times to sustain brain injury remain. Here, we present a systematic review investigating the influence of age at focal brain lesion onset on cognitive functioning. This systematic review identifies and qualitatively synthesizes empirical studies from 1985 to 2021 that investigated age at lesion onset as a variable of interest associated with neuropsychological outcomes. A total of 45 studies were identified from PubMed, PsycINFO, and CINAHL databases. Almost all studies indicated that brain injury earlier in the developmental period predicts worse cognitive outcomes when compared to onset either later in the developmental period or in adulthood. More specifically, the overwhelming majority of studies support an "earlier is worse" model for domains of intellect, processing speed, attention and working memory, visuospatial and perceptual skills, and learning and memory. Relatively more variability in outcomes exists for domains of language and executive functioning. Outcomes for all domains are influenced by various other age and injury variables (e.g., lesion size, lesion laterality, chronicity, a history of epilepsy). Continued interdisciplinary understanding and communication about the influence of age at lesion onset on neuropsychological outcomes will aid in promoting the best possible outcomes for patients.

Latent disconnectome prediction of long-term cognitive-behavioural symptoms in stroke.

Stroke significantly impacts the quality of life. However, the long-term cognitive evolution in stroke is poorly predictable at the individual level. There is an urgent need to better predict long-term symptoms based on acute clinical neuroimaging data. Previous works have demonstrated a strong relationship between the location of white matter disconnections and clinical symptoms. However, rendering the entire space of possible disconnection-deficit associations optimally surveyable will allow for a systematic association between brain disconnections and cognitive-behavioural measures at the individual level. Here we present the most comprehensive framework, a composite morphospace of white matter disconnections (disconnectome) to predict neuropsychological scores 1 year after stroke. Linking the latent disconnectome morphospace to neuropsychological outcomes yields biological insights that are available as the first comprehensive atlas of disconnectome-deficit relations across 86 scores-a Neuropsychological White Matter Atlas. Our novel predictive framework, the Disconnectome Symptoms Discoverer, achieved better predictivity performances than six other models, including functional disconnection, lesion topology and volume modelling. Out-of-sample prediction derived from this atlas presented a mean absolute error below 20% and allowed personalize neuropsychological predictions. Prediction on an external cohort achieved an R2 = 0.201 for semantic fluency. In addition, training and testing were replicated on two external cohorts achieving an R2 = 0.18 for visuospatial performance. This framework is available as an interactive web application (http://disconnectomestudio.bcblab.com) to provide the foundations for a new and practical approach to modelling cognition in stroke. We hope our atlas and web application will help to reduce the burden of cognitive deficits on patients, their families and wider society while also helping to tailor future personalized treatment programmes and discover new targets for treatments. We expect our framework's range of assessments and predictive power to increase even further through future crowdsourcing.

White matter disconnection of left multiple demand network is associated with post-lesion deficits in cognitive control.

Cognitive control modulates other cognitive functions to achieve internal goals and is important for adaptive behavior. Cognitive control is enabled by the neural computations distributed over cortical and subcortical areas. However, due to technical challenges in recording neural activity from the white matter, little is known about the anatomy of white matter tracts that coordinate the distributed neural computations that support cognitive control. Here, we leverage a large sample of human patients with focal brain lesions (n = 643) and investigate how lesion location and connectivity profiles account for variance in cognitive control performance. We find that lesions in white matter connecting left frontoparietal regions of the multiple demand network reliably predict deficits in cognitive control performance. These findings advance our understanding of the white matter correlates of cognitive control and provide an approach for incorporating network disconnection to predict deficits following lesions.