Advanced lesion symptom mapping analyses and implementation as BCBtoolkit

Prediction of stroke severity: systematic evaluation of lesion representations

OBJECTIVE

To systematically evaluate which lesion-based imaging features and methods allow for the best statistical prediction of poststroke deficits across independent datasets.

METHODS

We utilized imaging and clinical data from three independent datasets of patients experiencing acute stroke (N1 = 109, N2 = 638, N3 = 794) to statistically predict acute stroke severity (NIHSS) based on lesion volume, lesion location, and structural and functional disconnection with the lesion location using normative connectomes.

RESULTS

We found that prediction models trained on small single-center datasets could perform well using within-dataset cross-validation, but results did not generalize to independent datasets (median R2 N1 = 0.2%). Performance across independent datasets improved using large single-center training data (R2 N2 = 15.8%) and improved further using multicenter training data (R2 N3 = 24.4%). These results were consistent across lesion attributes and prediction models. Including either structural or functional disconnection in the models outperformed prediction based on volume or location alone (P < 0.001, FDR-corrected).

INTERPRETATION

We conclude that (1) prediction performance in independent datasets of patients with acute stroke cannot be inferred from cross-validated results within a dataset, as performance results obtained via these two methods differed consistently, (2) prediction performance can be improved by training on large and, importantly, multicenter datasets, and (3) structural and functional disconnection allow for improved prediction of acute stroke severity.

White matter disconnection impacts proprioception post-stroke

Proprioceptive impairments occur in approximately 50-64% of people following stroke. While much is known about the grey matter structures underlying proprioception, our understanding of the white matter correlates of proprioceptive impairments is less well developed. It is recognised that behavioural impairments post-stroke are often the result of disconnection between wide-scale brain networks, however the disconnectome associated with proprioception post-stroke is unknown. In the current study, white matter disconnection was assessed in relation to performance on a robotic arm position matching (APM) task. Neuroimaging and robotic assessments of proprioception were collected for 203 stroke survivors, approximately 2-weeks post-stroke. The robotic assessment was performed in a KINARM Exoskeleton robotic device and consisted of a nine-target APM task. First, the relationship between white matter tract lesion load and performance on the APM task was assessed. Next, differences in the disconnectome between participants with and without impairments on the APM task were examined. Greater lesion load to the superior longitudinal fasciculus (SLF II and III), arcuate fasciculus (all segments) and fronto-insular tracts were associated with worse APM task performance. In those with APM task impairments, there was, additionally, disconnection of the posterior corpus callosum, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus and optic radiations. This study highlights an important perisylvian white matter network supporting proprioceptive processing in the human brain. It also identifies white matter tracts, important for relaying proprioceptive information from parietal and frontal brain regions, that are not traditionally considered proprioceptive in nature.

Metric comparison of connectome-based lesion-symptom mapping in post-stroke aphasia

Connectome-based lesion-symptom mapping relates behavioural impairments to disruption of structural brain connectivity. Connectome-based lesion-symptom mapping can be based on different approaches (diffusion MRI versus lesion mask), network scales (whole brain versus regions of interest) and measure types (tract-based, parcel-based, or network-based metrics). We evaluated the similarity of different connectome-based lesion-symptom mapping processing choices and identified factors that influence the results using multiverse analysis-the strategy of conducting and displaying the results of all reasonable processing choices. Metrics derived from lesion masks and diffusion-weighted images were tested for association with Boston Naming Test and Token Test performance in a sample of 50 participants with aphasia following left hemispheric stroke. 'Direct' measures were derived from diffusion-weighted images. 'Indirect' measures were derived by overlaying lesion masks on a white matter atlas. Parcel-based connectomes were constructed for the whole brain and regions of interest (14 language-relevant parcels). Numerous tract-based and network-based metrics were calculated. There was a high discrepancy across processing approaches (diffusion-weighted images versus lesion masks), network scales (whole brain versus regions of interest) and metric types. Results indicate weak correlations and different connectome-based lesion-symptom mapping results across the processing choices. Substantial methodological work is needed to validate the various decision points that arise when conducting connectome-based lesion-symptom mapping analyses. Multiverse analysis is a useful strategy for evaluating the similarity across different processing choices in connectome-based lesion-symptom mapping.

Clinical and structural disconnectome evaluation in a case of optic aphasia

Optic Aphasia (OA) and Associative Visual Agnosia (AVA) are neuropsychological disorders characterized by impaired naming on visual presentation. From a cognitive point of view, while stimulus identification is largely unimpaired in OA (where access to semantic knowledge is still possible), in AVA it is not. OA has been linked with right hemianopia and disconnection of the occipital right-hemisphere (RH) visual processing from the left hemisphere (LH) language areas.In this paper, we describe the case of AA, an 81-year-old housewife suffering from a deficit in naming visually presented stimuli after left occipital lesion and damage to the interhemispheric splenial pathway. AA has been tested through a set of tasks assessing different levels of visual object processing. We discuss behavioral performance as well as the pattern of lesion and disconnection in relation to a neurocognitive model adapted from Luzzatti and colleagues (1998). Despite the complexity of the neuropsychological picture, behavioral data suggest that semantic access from visual input is possible, while a lesion-based structural disconnectome investigation demonstrated the splenial involvement.Altogether, neuropsychological and neuroanatomical findings support the assumption of visuo-verbal callosal disconnection compatible with a diagnosis of OA.

Multimodal neuroimaging to characterize symptom-specific networks in movement disorders

Movement disorders, such as Parkinson's disease, essential tremor, and dystonia, are characterized by their predominant motor symptoms, yet diseases causing abnormal movement also encompass several other symptoms, including non-motor symptoms. Here we review recent advances from studies of brain lesions, neuroimaging, and neuromodulation that provide converging evidence on symptom-specific brain networks in movement disorders. Although movement disorders have traditionally been conceptualized as disorders of the basal ganglia, cumulative data from brain lesions causing parkinsonism, tremor and dystonia have now demonstrated that this view is incomplete. Several recent studies have shown that lesions causing a given movement disorder occur in heterogeneous brain locations, but disrupt common brain networks, which appear to be specific to each motor phenotype. In addition, findings from structural and functional neuroimaging in movement disorders have demonstrated that brain abnormalities extend far beyond the brain networks associated with the motor symptoms. In fact, neuroimaging findings in each movement disorder are strongly influenced by the constellation of patients' symptoms that also seem to map to specific networks rather than individual anatomical structures or single neurotransmitters. Finally, observations from deep brain stimulation have demonstrated that clinical changes, including both symptom improvement and side effects, are dependent on the modulation of large-scale networks instead of purely local effects of the neuromodulation. Combined, this multimodal evidence suggests that symptoms in movement disorders arise from distinct brain networks, encouraging multimodal imaging studies to better characterize the underlying symptom-specific mechanisms and individually tailor treatment approaches.

Using mechanistic knowledge to appraise contemporary approaches to the rehabilitation of upper limb function following stroke

It is a paradox of neurological rehabilitation that, in an era in which preclinical models have produced significant advances in our mechanistic understanding of neural plasticity, there is inadequate support for many therapies recommended for use in clinical practice. When the goal is to estimate the probability that a specific form of therapy will have a positive clinical effect, the integration of mechanistic knowledge (concerning 'the structure or way of working of the parts in a natural system') may improve the quality of inference. This is illustrated by analysis of three contemporary approaches to the rehabilitation of lateralized dysfunction affecting people living with stroke: constraint-induced movement therapy; mental practice; and mirror therapy. Damage to 'cross-road' regions of the structural (white matter) brain connectome generates deficits that span multiple domains (motor, language, attention and verbal/spatial memory). The structural integrity of these regions determines not only the initial functional status, but also the response to therapy. As structural disconnection constrains the recovery of functional capability, 'disconnectome' modelling provides a basis for personalized prognosis and precision rehabilitation. It is now feasible to refer a lesion delineated using a standard clinical scan to a (dis)connectivity atlas derived from the brains of other stroke survivors. As the individual disconnection pattern thus obtained suggests the functional domains most likely be compromised, a therapeutic regimen can be tailored accordingly. Stroke is a complex disorder that burdens individuals with distinct constellations of brain damage. Mechanistic knowledge is indispensable when seeking to ameliorate the behavioural impairments to which such damage gives rise.

Normative connectome-based analysis of sensorimotor deficits in acute subcortical stroke

The interrelation between acute ischemic stroke, persistent disability, and uncertain prognosis underscores the need for improved methods to predict clinical outcomes. Traditional approaches have largely focused on analysis of clinical metrics, lesion characteristics, and network connectivity, using techniques such as resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI). However, these methods are not routinely used in acute stroke diagnostics. This study introduces an innovative approach that not only considers the lesion size in relation to the National Institutes of Health Stroke Scale (NIHSS score), but also evaluates the impact of disrupted fibers and their connections to cortical regions by introducing a disconnection value. By identifying fibers traversing the lesion and estimating their number within predefined regions of interest (ROIs) using a normative connectome atlas, our method bypasses the need for individual DTI scans. In our analysis of MRI data (T1 and T2) from 51 patients with acute or subacute subcortical stroke presenting with motor or sensory deficits, we used simple linear regression to assess the explanatory power of lesion size and disconnection value on NIHSS score. Subsequent hierarchical multiple linear regression analysis determined the incremental value of disconnection metrics over lesion size alone in relation to NIHSS score. Our results showed that models incorporating the disconnection value accounted for more variance than those based solely on lesion size (lesion size explained 44% variance, disconnection value 60%). Furthermore, hierarchical regression revealed a significant improvement (p < 0.001) in model fit when adding the disconnection value, confirming its critical role in stroke assessment. Our approach, which integrates a normative connectome to quantify disconnections to cortical regions, provides a significant improvement in assessing the current state of stroke impact compared to traditional measures that focus on lesion size. This is achieved by taking into account the lesion's location and the connectivity of the affected white matter tracts, providing a more comprehensive assessment of stroke severity as reflected in the NIHSS score. Future research should extend the validation of this approach to larger and more diverse populations, with a focus on refining its applicability to clinical assessment and long-term outcome prediction.

Predictors of cognition after glioma surgery: connectotomy, structure-function phenotype, plasticity

Determining preoperatively the maximal extent of resection that would preserve cognitive functions is the core challenge of brain tumour surgery. Over the past decade, the methodological framework to achieve this goal has been thoroughly renewed: the population-level topographically-focused voxel-based lesion-symptom mapping has been progressively overshadowed by machine learning (ML) algorithmics, in which the problem is framed as predicting cognitive outcomes in a patient-specific manner from a typically large set of variables. However, the choice of these predictors is of utmost importance, as they should be both informative and parsimonious. In this perspective, we first introduce the concept of connectotomy: instead of parameterizing resection topography through the status (intact/resected) of a huge number of voxels (or parcels) paving the whole brain in the Cartesian 3D-space, the connectotomy models the resection in the connectivity space, by computing a handful number of networks disconnection indices, measuring how the structural connectivity sustaining each network of interest was hit by the resection. This connectivity-informed reduction of dimensionality is a necessary step for efficiently implementing ML tools, given the relatively small number of patient-examples in available training datasets. We further argue that two other major sources of interindividual variability must be considered to improve the accuracy with which outcomes are predicted: the underlying structure-function phenotype and neuroplasticity, for which we provide an in-depth review and propose new ways of determining relevant predictors. We finally discuss the benefits of our approach for precision surgery of glioma.

Peaglet: A user-friendly probabilistic Kernel density estimation of intracranial cortical and subcortical stimulation sites

BACKGROUND

Data on human brain function obtained with direct electrical stimulation (DES) in neurosurgical patients have been recently integrated and combined with modern neuroimaging techniques, allowing a connectome-based approach fed by intraoperative DES data. Within this framework is crucial to develop reliable methods for spatial localization of DES-derived information to be integrated within the neuroimaging workflow.

NEW METHOD

To this aim, we applied the Kernel Density Estimation for modelling the distribution of DES sites from different patients into the MNI space. The algorithm has been embedded in a MATLAB-based User Interface, Peaglet. It allows an accurate probabilistic weighted and unweighted estimation of DES sites location both at cortical level, by using shortest path calculation along the brain 3D geometric topology, and subcortical level, by using a volume-based approach.

RESULTS

We applied Peaglet to investigate spatial estimation of cortical and subcortical stimulation sites provided by recent brain tumour studies. The resulting NIfTI maps have been anatomically investigated with neuroimaging open-source tools.

COMPARISON WITH EXISTING METHODS

Peaglet processes differently cortical and subcortical data following their distinguishing geometrical features, increasing anatomical specificity of DES-related results and their reliability within neuroimaging environments.

CONCLUSIONS

Peaglet provides a robust probabilistic estimation of the cortical and subcortical distribution of DES sites going beyond a region of interest approach, respecting cortical and subcortical intrinsic geometrical features. Results can be easily integrated within the neuroimaging workflow to drive connectomic analysis.

A preliminary study of white matter disconnections underlying deficits in praxis in left hemisphere stroke patients

Limb apraxia is a higher-order motor disorder often occurring post-stroke, which affects skilled actions. It is assessed through tasks involving gesture production or pantomime, recognition, meaningless gesture imitation, complex figure drawing, single and multi-object use. A two-system model for the organisation of actions hypothesizes distinct pathways mediating praxis deficits via conceptual, 'indirect', and perceptual 'direct' routes to action. Traditional lesion- symptom mapping techniques have failed to identify these distinct routes. We assessed 29 left hemisphere stroke patients to investigate white matter disconnections on deficits of praxis tasks from the Birmingham Cognitive Screening. White matter disconnection maps derived from patients' structural T1 lesions were created using a diffusion-weighted healthy participant dataset acquired from the human connectome project (HCP). Initial group-level regression analyses revealed significant disconnection between occipital lobes via the splenium of the corpus callosum and involvement of the inferior longitudinal fasciculus in meaningless gesture imitation deficits. There was a trend of left fornix disconnection in gesture production deficits. Further, voxel-wise Bayesian Crawford single-case analyses performed on two patients with the most severe meaningless gesture imitation and meaningful gesture production deficits, respectively, confirmed distinct posterior interhemispheric disconnection, for the former, and disconnections between temporal and frontal areas via the fornix, rostrum of the corpus callosum and anterior cingulum, for the latter. Our results suggest distinct pathways associated with perceptual and conceptual deficits akin to 'direct' and 'indirect' action routes, with some patients displaying both. Larger studies are needed to validate and elaborate on these findings, advancing our understanding of limb apraxia.

What I think she thinks about my paralysed body: Social inferences about disability-related content in anosognosia for hemiplegia

The neuropsychological disorder of anosognosia for hemiplegia (AHP) can offer unique insights into the neurocognitive processes of body consciousness and representation. Previous studies have found associations between selective social cognition deficits and anosognosia. In this study, we examined how such social cognition deficits may directly interact with representations of one's body as disabled in AHP. We used a modified set of previously validated Theory of Mind (ToM) stories to create disability-related content that was related to post-stroke paralysis and to investigate differences between right hemisphere damage patients with (n = 19) and without (n = 19) AHP. We expected AHP patients to perform worse than controls when trying to infer paralysis-related mental states in the paralysis-related ToM stories and explored whether such differences depended on the inference patients were asked to perform (e.g. self or other referent perspective-taking). Using an advanced structural neuroimaging technique, we expected selective social cognitive deficits to be associated with posterior parietal cortex lesions and deficits in self-referent perspective-taking in paralysis-related mentalising to be associated with frontoparietal disconnections. Group- and individual-level results revealed that AHP patients performed worse than HP controls when trying to infer paralysis-related mental states. Exploratory lesion analysis results revealed some of the hypothesised lesions, but also unexpected white matter disconnections in the posterior body and splenium of the corpus collosum associated with a self-referent perspective-taking in paralysis-related ToM stories. The study has implications for the multi-layered nature of body awareness, including abstract, social perspectives and beliefs about the body.

Indirect functional connectivity does not predict overall survival in glioblastoma

BACKGROUND

Lesion network mapping (LNM) is a popular framework to assess clinical syndromes following brain injury. The classical approach involves embedding lesions from patients into a normative functional connectome and using the corresponding functional maps as proxies for disconnections. However, previous studies indicated limited predictive power of this approach in behavioral deficits. We hypothesized similarly low predictiveness for overall survival (OS) in glioblastoma (GBM).

METHODS

A retrospective dataset of patients with GBM was included (n = 99). Lesion masks were registered in the normative space to compute disconnectivity maps. The brain functional normative connectome consisted in data from 173 healthy subjects obtained from the Human Connectome Project. A modified version of the LNM was then applied to core regions of GBM masks. Linear regression, classification, and principal component (PCA) analyses were conducted to explore the relationship between disconnectivity and OS. OS was considered both as continuous and categorical (low, intermediate, and high survival) variable.

RESULTS

The results revealed no significant associations between OS and network disconnection strength when analyzed at both voxel-wise and classification levels. Moreover, patients stratified into different OS groups did not exhibit significant differences in network connectivity patterns. The spatial similarity among the first PCA of network maps for each OS group suggested a lack of distinctive network patterns associated with survival duration.

CONCLUSIONS

Compared with indirect structural measures, functional indirect mapping does not provide significant predictive power for OS in patients with GBM. These findings are consistent with previous research that demonstrated the limitations of indirect functional measures in predicting clinical outcomes, underscoring the need for more comprehensive methodologies and a deeper understanding of the factors influencing clinical outcomes in this challenging disease.

Predicting functional impairments with lesion-derived disconnectome mapping: Validation in stroke patients with motor deficits

Focal structural damage to white matter tracts can result in functional deficits in stroke patients. Traditional voxel-based lesion-symptom mapping is commonly used to localize brain structures linked to neurological deficits. Emerging evidence suggests that the impact of structural focal damage may extend beyond immediate lesion sites. In this study, we present a disconnectome mapping approach based on support vector regression (SVR) to identify brain structures and white matter pathways associated with functional deficits in stroke patients. For clinical validation, we utilized imaging data from 340 stroke patients exhibiting motor deficits. A disconnectome map was initially derived from lesions for each patient. Bootstrap sampling was then employed to balance the sample size between a minority group of patients exhibiting right or left motor deficits and those without deficits. Subsequently, SVR analysis was used to identify voxels associated with motor deficits (p < .005). Our disconnectome-based analysis significantly outperformed alternative lesion-symptom approaches in identifying major white matter pathways within the corticospinal tracts associated with upper-lower limb motor deficits. Bootstrapping significantly increased the sensitivity (80%-87%) for identifying patients with motor deficits, with a minimum lesion size of 32 and 235 mm3 for the right and left motor deficit, respectively. Overall, the lesion-based methods achieved lower sensitivities compared with those based on disconnection maps. The primary contribution of our approach lies in introducing a bootstrapped disconnectome-based mapping approach to identify lesion-derived white matter disconnections associated with functional deficits, particularly efficient in handling imbalanced data.

Hayling and stroop tests tap dissociable deficits and network-level neural correlates

Although many executive function screens have been developed, it is not yet clear whether these assessments are equally effective in detecting post-stroke deficits of initiation and inhibition. This study presents a comparative analysis of the Stroop and Hayling tests aiming to evaluate whether these tests measure the same underlying cognitive functions and to identify the neural correlates of the deficits detected by both tasks. Sixty six stroke survivors and 70 healthy ageing controls completed the Hayling and Stroop tests. Stroke patients were found to exhibit qualitative performance differences across analogous Stroop and Hayling Test metrics intended to tap initiation and inhibition. The Stroop test was found to have high specificity to abnormal performance, but low sensitivity relative to the Hayling Test. Minimal overlap was present between the network-level correlates of analogous Stroop and Hayling Test metrics. Hayling Task strategy use metrics were significantly associated with distinct patterns of disconnection in stroke survivors, providing novel insight into the neural correlates of fine-grained behavioural patterns. Overall, these findings strongly suggest that the functions tapped by the Stroop and Hayling Test are both behaviourally and anatomically dissociable. The Hayling Test was found to offer improved sensitivity and detail relative to the Stroop test. This novel demonstration of the Hayling Test within the stroke population suggests that this task represents an effective measure for quantifying post-stroke initiation and inhibition deficits.

Enhancing Cognitive Performance Prediction through White Matter Hyperintensity Connectivity Assessment: A Multicenter Lesion Network Mapping Analysis of 3,485 Memory Clinic Patients

Introduction

White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating cognitive health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. We propose that lesion network mapping (LNM), enables to infer if brain networks are connected to lesions, and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed this approach to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks.

Methods & results

We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity across 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. The capacity of total and regional WMH volumes and LNM scores in predicting cognitive function was compared using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention and executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater disruptive effects of WMH on regional connectivity, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance.

Conclusion

Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network effects, particularly in attentionrelated brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.

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.

The emergence of multiscale connectomics-based approaches in stroke recovery

Stroke is a leading cause of adult disability. Understanding stroke damage and recovery requires deciphering changes in complex brain networks across different spatiotemporal scales. While recent developments in brain readout technologies and progress in complex network modeling have revolutionized current understanding of the effects of stroke on brain networks at a macroscale, reorganization of smaller scale brain networks remains incompletely understood. In this review, we use a conceptual framework of graph theory to define brain networks from nano- to macroscales. Highlighting stroke-related brain connectivity studies at multiple scales, we argue that multiscale connectomics-based approaches may provide new routes to better evaluate brain structural and functional remapping after stroke and during recovery.

Graphs and the idiographic brain

This scientific commentary refers to ‘Integrating direct electrical brain stimulation with the human connectome’ by Coletta et al. (https://doi.org/10.1093/brain/awad402).

Disruption of the left anterior ventrolateral temporal cortex along with the inferior longitudinal fasciculus impairs the ability to retrieve famous face names: Evidence from three longitudinal case studies

The cortical distribution of the proper name (PN) retrieval network has been widely studied contrary to its connectional anatomy. Here, we report the case of three patients with a low-grade glioma damaging the mid-to-anterior part of the left temporal lobe. A longitudinal behavioural assessment showed that the surgery caused a long-lasting decline in PN retrieval performances in all patients. Furthermore, a detailed analysis of surgery-related structural disconnections revealed that interruption of the inferior longitudinal fasciculus was the unique common denominator.

The prefrontal cortex: from monkey to man

The prefrontal cortex is so important to human beings that, if deprived of it, our behaviour is reduced to action-reactions and automatisms, with no ability to make deliberate decisions. Why does the prefrontal cortex hold such importance in humans? In answer, this review draws on the proximity between humans and other primates, which enables us, through comparative anatomical-functional analysis, to understand the cognitive functions we have in common and specify those that distinguish humans from their closest cousins. First, a focus on the lateral region of the prefrontal cortex illustrates the existence of a continuum between rhesus monkeys (the most studied primates in neuroscience) and humans for most of the major cognitive functions in which this region of the brain plays a central role. This continuum involves the presence of elementary mental operations in the rhesus monkey (e.g. working memory or response inhibition) that are constitutive of 'macro-functions' such as planning, problem-solving and even language production. Second, the human prefrontal cortex has developed dramatically compared to that of other primates. This increase seems to concern the most anterior part (the frontopolar cortex). In humans, the development of the most anterior prefrontal cortex is associated with three major and interrelated cognitive changes: (i) a greater working memory capacity, allowing for greater integration of past experiences and prospective futures; (ii) a greater capacity to link discontinuous or distant data, whether temporal or semantic; and (iii) a greater capacity for abstraction, allowing humans to classify knowledge in different ways, to engage in analogical reasoning or to acquire abstract values that give rise to our beliefs and morals. Together, these new skills enable us, among other things, to develop highly sophisticated social interactions based on language, enabling us to conceive beliefs and moral judgements and to conceptualize, create and extend our vision of our environment beyond what we can physically grasp. Finally, a model of the transition of prefrontal functions between humans and non-human primates concludes this review.

The effects of occipital and parietal tDCS on chronic visual field defects after brain injury

Introduction

Homonymous visual field defects (HVFDs) following acquired brain lesions affect independent living by hampering several activities of everyday life. Available treatments are intensive and week- or month-long. Transcranial Direct current stimulation (tDCS), a plasticity-modulating non-invasive brain stimulation technique, could be combined with behavioral trainings to boost their efficacy or reduce treatment duration. Some promising attempts have been made pairing occipital tDCS with visual restitution training, however less is knows about which area/network should be best stimulated in association with compensatory approaches, aimed at improving exploratory abilities, such as multisensory trainings.

Methods

In a proof-of-principle, sham-controlled, single-blind study, 15 participants with chronic HVFDs underwent four one-shot sessions of active or sham anodal tDCS applied over the ipsilesional occipital cortex, the ipsilesional or contralesional posterior parietal cortex. tDCS was delivered during a compensatory multisensory (audiovisual) training. Before and immediately after each tDCS session, participants carried out a visual detection task, and two visual search tasks (EF and Triangles search tests). Accuracy (ACC) and response times (RTs) were analyzed with generalized mixed models. We investigated differences in baseline performance, clinical-demographic and lesion factors between tDCS responders and non-responders, based on post-tDCS behavioral improvements. Lastly, we conducted exploratory analyses to compare left and right brain-damaged participants.

Results

RTs improved after active ipsilesional occipital and parietal tDCS in the visual search tasks, while no changes in ACC were detected. Responders to ipsilesional occipital tDCS (Triangle task) had shorter disease duration and smaller lesions of the parietal cortex and the superior longitudinal fasciculus. On the other end, on the EF test, those participants with larger damage of the temporo-parietal cortex or the fronto-occipital white matter tracts showed a larger benefit from contralesional parietal tDCS. Overall, the visual search RTs improvements were larger in participants with right-sided hemispheric lesions.

Conclusion

The present result shows the facilitatory effects of occipital and parietal tDCS combined with compensatory multisensory training on visual field exploration in HVFDs, suggesting a potential for the development of new neuromodulation treatments to improve visual scanning behavior in brain-injured patients.

Lesion mapping and functional characterization of hemiplegic children with different patterns of hand manipulation

Brain damage in children with unilateral cerebral palsy (UCP) affects motor function, with varying severity, making it difficult the performance of daily actions. Recently, qualitative and semi-quantitative methods have been developed for lesion classification, but studies on mild to moderate hand impairment are lacking. The present study aimed to characterize lesion topography and preserved brain areas in UCP children with specific patterns of hand manipulation. A homogeneous sample of 16 UCP children, aged 9 to 14 years, was enrolled in the study. Motor assessment included the characterization of the specific pattern of hand manipulation, by means of unimanual and bimanual measures (Kinematic Hand Classification, KHC; Manual Ability Classification System, MACS; House Functional Classification System, HFCS; Melbourne Unilateral Upper Limb Assessment, MUUL; Assisting Hand Assessment, AHA). The MRI morphological study included multiple methods: (a) qualitative lesion classification, (b) semi-quantitative classification (sq-MRI), (c) voxel-based morphometry comparing UCP and typically developed children (VBM-DARTEL), and (d) quantitative brain tissue segmentation (q-BTS). In addition, functional MRI was used to assess spared functional activations and cluster lateralization in the ipsilesional and contralesional hemispheres of UCP children during the execution of simple movements and grasping actions with the more affected hand. Lesions most frequently involved the periventricular white matter, corpus callosum, posterior limb of the internal capsule, thalamus, basal ganglia and brainstem. VMB-DARTEL analysis allowed to detect mainly white matter lesions. Both sq-MRI classification and q-BTS identified lesions of thalamus, brainstem, and basal ganglia. In particular, UCP patients with synergic hand pattern showed larger involvement of subcortical structures, as compared to those with semi-functional hand. Furthermore, sparing of gray matter in basal ganglia and thalamus was positively correlated with MUUL and AHA scores. Concerning white matter, q-BTS revealed a larger damage of fronto-striatal connections in patients with synergic hand, as compared to those with semi-functional hand. The volume of these connections was correlated to unimanual function (MUUL score). The fMRI results showed that all patients, but one, including those with cortical lesions, had activation in ipsilesional areas, regardless of lesion timing. Children with synergic hand showed more lateralized activation in the ipsilesional hemisphere both during grasping and simple movements, while children with semi-functional hand exhibited more bilateral activation during grasping. The study demonstrates that lesion localization, rather than lesion type based on the timing of their occurrence, is more associated with the functional level of hand manipulation. Overall, the preservation of subcortical structures and white matter can predict a better functional outcome. Future studies integrating different techniques (structural and functional imaging, TMS) could provide further evidence on the relation between brain reorganization and specific pattern of manipulation in UCP children.

Tract-wise microstructural analysis informs on current and future disability in early multiple sclerosis

OBJECTIVES

Microstructural characterization of patients with multiple sclerosis (MS) has been shown to correlate better with disability compared to conventional radiological biomarkers. Quantitative MRI provides effective means to characterize microstructural brain tissue changes both in lesions and normal-appearing brain tissue. However, the impact of the location of microstructural alterations in terms of neuronal pathways has not been thoroughly explored so far. Here, we study the extent and the location of tissue changes probed using quantitative MRI along white matter (WM) tracts extracted from a connectivity atlas.

METHODS

We quantified voxel-wise T1 tissue alterations compared to normative values in a cohort of 99 MS patients. For each WM tract, we extracted metrics reflecting tissue alterations both in lesions and normal-appearing WM and correlated these with cross-sectional disability and disability evolution after 2 years.

RESULTS

In early MS patients, T1 alterations in normal-appearing WM correlated better with disability evolution compared to cross-sectional disability. Further, the presence of lesions in supratentorial tracts was more strongly associated with cross-sectional disability, while microstructural alterations in infratentorial pathways yielded higher correlations with disability evolution. In progressive patients, all major WM pathways contributed similarly to explaining disability, and correlations with disability evolution were generally poor.

CONCLUSIONS

We showed that microstructural changes evaluated in specific WM pathways contribute to explaining future disability in early MS, hence highlighting the potential of tract-wise analyses in monitoring disease progression. Further, the proposed technique allows to estimate WM tract-specific microstructural characteristics in clinically compatible acquisition times, without the need for advanced diffusion imaging.

Stratified predictions of upper limb motor outcomes after stroke

Introduction

Longitudinal observations of upper limb motor recovery after stroke have suggested that certain subgroups may exhibit distinct recovery patterns. Here we sought to examine whether the predictive ability for post-stroke upper limb motor outcomes could be enhanced by applying conventional stratification strategies.

Method

For 60 individuals who suffered the first stroke, upper limb motor impairment was assessed with the upper extremity Fugl-Meyer assessment (UE-FMA) at 2 weeks as a baseline and then 3 months post-stroke. Brain structural damage at baseline was assessed by MRI data-derived markers ranging from traditional lesion size to the lesion load and to the disconnectome. Linear regression models for predicting upper limb motor outcomes (UE-FMA score at 3 months post-stroke) based on baseline upper limb motor impairment (UE-FMA score at 2 weeks post-stroke), brain structural damage, and their combinations were generated, and those with the best predictive performance were determined for individual subgroups stratified according to initial impairment (severe and non-severe), lesion location (cortical and non-cortical), and neurophysiological status (motor evoked potential-positive and motor evoked potential-negative).

Results

The best predictions were made by baseline upper limb motor impairment alone for subgroups with less functional impairment (non-severe) or less structural involvement (non-cortical), but by the combination of baseline upper limb motor impairment and brain structural damage for the other subgroups. The predictive models tailored for subgroups determined according to initial impairment and neurophysiological status yielded a smaller overall error than that for the whole group in upper limb motor outcome predictions.

Discussion

The predictive ability for upper limb motor outcomes could be enhanced beyond the one-size-fits-all model for all individuals with stroke by applying specific stratification strategies, with stratification according to initial impairment being the most promising. We expect that predictive models tailored for individual subgroups could lead closer to the personalized prognosis of upper limb motor outcomes after stroke.

Voxel-based dysconnectomic brain morphometry with computed tomography in Down syndrome

OBJECTIVE

Alzheimer's disease (AD) is a major health concern for aging adults with Down syndrome (DS), but conventional diagnostic techniques are less reliable in those with severe baseline disability. Likewise, acquisition of magnetic resonance imaging to evaluate cerebral atrophy is not straightforward, as prolonged scanning times are less tolerated in this population. Computed tomography (CT) scans can be obtained faster, but poor contrast resolution limits its function for morphometric analysis. We implemented an automated analysis of CT scans to characterize differences across dementia stages in a cross-sectional study of an adult DS cohort.

METHODS

CT scans of 98 individuals were analyzed using an automatic algorithm. Voxel-based correlations with clinical dementia stages and AD plasma biomarkers (phosphorylated tau-181 and neurofilament light chain) were identified, and their dysconnectomic patterns delineated.

RESULTS

Dementia severity was negatively correlated with gray (GM) and white matter (WM) volumes in temporal lobe regions, including parahippocampal gyri. Dysconnectome analysis revealed an association between WM loss and temporal lobe GM volume reduction. AD biomarkers were negatively associated with GM volume in hippocampal and cingulate gyri.

INTERPRETATION

Our automated algorithm and novel dysconnectomic analysis of CT scans successfully described brain morphometric differences related to AD in adults with DS, providing a new avenue for neuroimaging analysis in populations for whom magnetic resonance imaging is difficult to obtain.

Network Reorganization for Neurophysiological and Behavioral Recovery Following Stroke

Stroke continues to be the main cause of motor disability worldwide. While rehabilitation has been promised to improve recovery after stroke, efficacy in clinical trials has been mixed. We need to understand the cortical recombination framework to understand how biomarkers for neurophysiological reorganized neurotechnologies alter network activity. Here, we summarize the principles of the movement network, including the current evidence of changes in the connections and function of encephalic regions, recovery from stroke and the therapeutic effects of rehabilitation. Overall, improvements or therapeutic effects in limb motor control following stroke are correlated with the effects of interhemispheric competition or compensatory models of the motor supplementary cortex. This review suggests that future research should focus on cross-regional communication and provide fundamental insights into further treatment and rehabilitation for post-stroke patients.

Comprehensive voxel-wise, tract-based, and network lesion mapping reveals unique architectures of right and left visuospatial neglect

Visuospatial neglect is a common, post-stroke cognitive impairment which is widely considered to be a disconnection syndrome. However, the patterns of disconnectivity associated with visuospatial neglect remain unclear. Here, we had 480 acute stroke survivors [age = 72.8 (SD = 13.3), 44.3% female, 7.5 days post-stroke (SD = 11.3)] undertake routine clinical imaging and standardised visuospatial neglect testing. The data were used to conduct voxel-wise, tract-level, and network-level lesion-mapping analyses aimed at localising the neural correlates of left and right egocentric (body-centred) and allocentric (object-centred) visuospatial neglect. Only minimal anatomical homogeneity was present between the correlates of right and left egocentric neglect across all analysis types. This finding challenges previous work suggesting that right and left visuospatial neglect are anatomically homologous, and instead suggests that egocentric neglect may involve damage to a shared, but hemispherically asymmetric attention network. By contrast, egocentric and allocentric neglect was associated with disconnectivity in a distinct but overlapping set of network edges, with both deficits related to damage across the dorsal and ventral attention networks. Critically, this finding suggests that the distinction between egocentric and allocentric neglect is unlikely to reflect a simple dichotomy between dorsal versus ventral networks dysfunction, as is commonly asserted. Taken together, the current findings provide a fresh perspective on the neural circuitry involved in regulating visuospatial attention, and provide important clues to understanding the cognitive and perceptual processes involved in this common and debilitating neuropsychological syndrome.

Impaired discourse content in aphasia is associated with frontal white matter damage

Aphasia is a common consequence of stroke with severe impacts on employability, social interactions and quality of life. Producing discourse-relevant information in a real-world setting is the most important aspect of recovery because it is critical to successful communication. This study sought to identify the lesion correlates of impaired production of relevant information in spoken discourse in a large, unselected sample of participants with post-stroke aphasia. Spoken discourse (n = 80) and structural brain scans (n = 66) from participants with aphasia following left hemisphere stroke were analysed. Each participant provided 10 samples of spoken discourse elicited in three different genres, and 'correct information unit' analysis was used to quantify the informativeness of speech samples. The lesion correlates were identified using multivariate lesion-symptom mapping, voxel-wise disconnection and tract-wise analyses. Amount and speed of relevant information were highly correlated across different genres and with total lesion size. The analyses of lesion correlates converged on the same pattern: impaired production of relevant information was associated with damage to anterior dorsal white matter pathways, specifically the arcuate fasciculus, frontal aslant tract and superior longitudinal fasciculus. Damage to these pathways may be a useful biomarker for impaired informative spoken discourse and informs development of neurorehabilitation strategies.

Multiple sclerosis lesions that impair memory map to a connected memory circuit

BACKGROUND

Nearly 1 million Americans are living with multiple sclerosis (MS) and 30-50% will experience memory dysfunction. It remains unclear whether this memory dysfunction is due to overall white matter lesion burden or damage to specific neuroanatomical structures. Here we test if MS memory dysfunction is associated with white matter lesions to a specific brain circuit.

METHODS

We performed a cross-sectional analysis of standard structural images and verbal memory scores as assessed by immediate recall trials from 431 patients with MS (mean age 49.2 years, 71.9% female) enrolled at a large, academic referral center. White matter lesion locations from each patient were mapped using a validated algorithm. First, we tested for associations between memory dysfunction and total MS lesion volume. Second, we tested for associations between memory dysfunction and lesion intersection with an a priori memory circuit derived from stroke lesions. Third, we performed mediation analyses to determine which variable was most associated with memory dysfunction. Finally, we performed a data-driven analysis to derive de-novo brain circuits for MS memory dysfunction using both functional (n = 1000) and structural (n = 178) connectomes.

RESULTS

Both total lesion volume (r = 0.31, p < 0.001) and lesion damage to our a priori memory circuit (r = 0.34, p < 0.001) were associated with memory dysfunction. However, lesion damage to the memory circuit fully mediated the association of lesion volume with memory performance. Our data-driven analysis identified multiple connections associated with memory dysfunction, including peaks in the hippocampus (T = 6.05, family-wise error p = 0.000008), parahippocampus, fornix and cingulate. Finally, the overall topography of our data-driven MS memory circuit matched our a priori stroke-derived memory circuit.

CONCLUSIONS

Lesion locations associated with memory dysfunction in MS map onto a specific brain circuit centered on the hippocampus. Lesion damage to this circuit fully mediated associations between lesion volume and memory. A circuit-based approach to mapping MS symptoms based on lesions visible on standard structural imaging may prove useful for localization and prognosis of higher order deficits in MS.

White Matter Tract Density Index Prediction Model of Overall Survival in Glioblastoma

Importance

The prognosis of overall survival (OS) in patients with glioblastoma (GBM) may depend on the underlying structural connectivity of the brain.

Objective

To examine the association between white matter tracts affected by GBM and patients' OS by means of a new tract density index (TDI).

Design, Setting, and Participants

This prognostic study in patients with a histopathologic diagnosis of GBM examined a discovery cohort of 112 patients who underwent surgery between February 1, 2015, and November 30, 2020 (follow-up to May 31, 2023), in Italy and 70 patients in a replicative cohort (n = 70) who underwent surgery between September 1, 2012, and November 30, 2015 (follow-up to May 31, 2023), in Germany. Statistical analyses were performed from June 1, 2021, to May 31, 2023. Thirteen and 12 patients were excluded from the discovery and the replicative sets, respectively, because of magnetic resonance imaging artifacts.

Exposure

The density of white matter tracts encompassing GBM.

Main Outcomes and Measures

Correlation, linear regression, Cox proportional hazards regression, Kaplan-Meier, and prediction analysis were used to assess the association between the TDI and OS. Results were compared with common prognostic factors of GBM, including age, performance status, O6-methylguanine-DNA methyltransferase methylation, and extent of surgery.

Results

In the discovery cohort (n = 99; mean [SD] age, 62.2 [11.5] years; 29 female [29.3%]; 70 male [70.7%]), the TDI was significantly correlated with OS (r = -0.34; P < .001). This association was more stable compared with other prognostic factors. The TDI showed a significant regression pattern (Cox: hazard ratio, 0.28 [95% CI, 0.02-0.55; P = .04]; linear: t = -2.366; P = .02). and a significant Kaplan-Meier stratification of patients as having lower or higher OS based on the TDI (log-rank test = 4.52; P = .03). Results were confirmed in the replicative cohort (n = 58; mean [SD] age, 58.5 [11.1] years, 14 female [24.1%]; 44 male [75.9%]). High (24-month cutoff) and low (18-month cutoff) OS was predicted based on the TDI computed in the discovery cohort (accuracy = 87%).

Conclusions and Relevance

In this study, GBMs encompassing regions with low white matter tract density were associated with longer OS. These findings indicate that the TDI is a reliable presurgical outcome predictor that may be considered in clinical trials and clinical practice. These findings support a framework in which the outcome of GBM depends on the patient's brain organization.

The need for hemispheric separation in pairwise structural disconnection studies

The development of new approaches indirectly measuring the structural disconnectome has recently led to an increase in studies investigating pairwise structural disconnections following brain damage. Previous studies jointly analyzed patients with left hemispheric and patients with right hemispheric lesions when investigating a behavior of interest. An alternative approach would be to perform analyses separated by hemisphere, which has been applied in only a minority of studies to date. The present simulation study investigated whether joint or separate analyses (or both equally) are appropriate to reveal the ground truth disconnections. In fact, both approaches resulted in very different patterns of disconnection. In contrast to analyses separated by hemisphere, joint analyses introduced a bias to the disadvantage of intra-hemispheric disconnections. Intra-hemispheric disconnections were statistically underpowered in the joint analysis and thus surpassed the significance threshold with more difficulty compared to inter-hemispheric disconnections. This statistical imbalance was also shown by a greater number of significant inter-hemispheric than significant intra-hemispheric disconnections. This bias from joint analyses is based on mechanisms similar to those underlying the "partial injury problem." We therefore conclude that pairwise structural disconnections in patients with unilateral left hemispheric and with unilateral right hemispheric lesions exhibiting a specific behavior (or disorder) of interest should be studied separately by hemisphere rather than in a joint analysis.

White matter tract disconnection in Gerstmann's syndrome: Insights from a single case study

It has been suggested that Gerstmann's syndrome is the result of subcortical disconnection rather than emerging from damage of a multifunctional brain region within the parietal lobe. However, patterns of white matter tract disconnection following parietal damage have been barely investigated. This single case study allows characterising Gerstmann's syndrome in terms of disconnected networks. We report the case of a left parietal patient affected by Gerstmann's tetrad: agraphia, acalculia, left/right orientation problems, and finger agnosia. Lesion mapping, atlas-based estimation of probability of disconnection, and DTI-based tractography revealed that the lesion was mainly located in the superior parietal lobule, and it caused disruption of both intraparietal tracts passing through the inferior parietal lobule (e.g., tracts connecting the angular, supramarginal, postcentral gyri, and the superior parietal lobule) and fronto-parietal long tracts (e.g., the superior longitudinal fasciculus). The lesion site appears to be located more superiorly as compared to the cerebral regions shown active by other studies during tasks impaired in the syndrome, and it reached the subcortical area potentially critical in the emergence of the syndrome, as hypothesised in previous studies. Importantly, the reconstruction of tracts connecting regions within the parietal lobe indicates that this critical subcortical area is mainly crossed by white matter tracts connecting the angular gyrus and the superior parietal lobule. Taken together, these findings suggest that this case study might be considered as empirical evidence of Gerstmann's tetrad caused by disconnection of intraparietal white matter tracts.

Thalamocortical disconnection involved in pusher syndrome

The presence of both isolated thalamic and isolated cortical lesions have been reported in the context of pusher syndrome-a disorder characterized by a disturbed perception of one's own upright body posture, following unilateral left- or right-sided stroke. In recent times, indirect quantification of functional and structural disconnection increases the knowledge derived from focal brain lesions by inferring subsequent brain network damage from the respective lesion. We applied both measures to a sample of 124 stroke patients to investigate brain disconnection in pusher syndrome. Our results suggest a hub-like function of the posterior and lateral portions of the thalamus in the perception of one's own postural upright. Lesion network symptom mapping investigating functional disconnection indicated cortical diaschisis in cerebellar, frontal, parietal and temporal areas in patients with thalamic lesions suffering from pusher syndrome, but there was no evidence for functional diaschisis in pusher patients with cortical stroke and no evidence for the convergence of thalamic and cortical lesions onto a common functional network. Structural disconnection mapping identified posterior thalamic disconnection to temporal, pre-, post- and paracentral regions. Fibre tracking between the thalamic and cortical pusher lesion hotspots indicated that in cortical lesions of patients with pusher syndrome, it is disconnectivity to the posterior thalamus caused by accompanying white matter damage, rather than the direct cortical lesions themselves, that lead to the emergence of pusher syndrome. Our analyses thus offer the first evidence for a direct thalamo-cortical (or cortico-thalamic) interconnection and, more importantly, shed light on the location of the respective thalamo-cortical disconnections. Pusher syndrome seems to be a consequence of direct damage or of disconnection of the posterior thalamus.

Mapping Lesion-Related Epilepsy to a Human Brain Network

Importance

It remains unclear why lesions in some locations cause epilepsy while others do not. Identifying the brain regions or networks associated with epilepsy by mapping these lesions could inform prognosis and guide interventions.

Objective

To assess whether lesion locations associated with epilepsy map to specific brain regions and networks.

Design, Setting, and Participants

This case-control study used lesion location and lesion network mapping to identify the brain regions and networks associated with epilepsy in a discovery data set of patients with poststroke epilepsy and control patients with stroke. Patients with stroke lesions and epilepsy (n = 76) or no epilepsy (n = 625) were included. Generalizability to other lesion types was assessed using 4 independent cohorts as validation data sets. The total numbers of patients across all datasets (both discovery and validation datasets) were 347 with epilepsy and 1126 without. Therapeutic relevance was assessed using deep brain stimulation sites that improve seizure control. Data were analyzed from September 2018 through December 2022. All shared patient data were analyzed and included; no patients were excluded.

Main Outcomes and Measures

Epilepsy or no epilepsy.

Results

Lesion locations from 76 patients with poststroke epilepsy (39 [51%] male; mean [SD] age, 61.0 [14.6] years; mean [SD] follow-up, 6.7 [2.0] years) and 625 control patients with stroke (366 [59%] male; mean [SD] age, 62.0 [14.1] years; follow-up range, 3-12 months) were included in the discovery data set. Lesions associated with epilepsy occurred in multiple heterogenous locations spanning different lobes and vascular territories. However, these same lesion locations were part of a specific brain network defined by functional connectivity to the basal ganglia and cerebellum. Findings were validated in 4 independent cohorts including 772 patients with brain lesions (271 [35%] with epilepsy; 515 [67%] male; median [IQR] age, 60 [50-70] years; follow-up range, 3-35 years). Lesion connectivity to this brain network was associated with increased risk of epilepsy after stroke (odds ratio [OR], 2.82; 95% CI, 2.02-4.10; P < .001) and across different lesion types (OR, 2.85; 95% CI, 2.23-3.69; P < .001). Deep brain stimulation site connectivity to this same network was associated with improved seizure control (r, 0.63; P < .001) in 30 patients with drug-resistant epilepsy (21 [70%] male; median [IQR] age, 39 [32-46] years; median [IQR] follow-up, 24 [16-30] months).

Conclusions and Relevance

The findings in this study indicate that lesion-related epilepsy mapped to a human brain network, which could help identify patients at risk of epilepsy after a brain lesion and guide brain stimulation therapies.

Fronto-parietal networks shape human conscious report through attention gain and reorienting

How do attention and consciousness interact in the human brain? Rival theories of consciousness disagree on the role of fronto-parietal attentional networks in conscious perception. We recorded neural activity from 727 intracerebral contacts in 13 epileptic patients, while they detected near-threshold targets preceded by attentional cues. Clustering revealed three neural patterns: first, attention-enhanced conscious report accompanied sustained right-hemisphere fronto-temporal activity in networks connected by the superior longitudinal fasciculus (SLF) II-III, and late accumulation of activity (>300 ms post-target) in bilateral dorso-prefrontal and right-hemisphere orbitofrontal cortex (SLF I-III). Second, attentional reorienting affected conscious report through early, sustained activity in a right-hemisphere network (SLF III). Third, conscious report accompanied left-hemisphere dorsolateral-prefrontal activity. Task modeling with recurrent neural networks revealed multiple clusters matching the identified brain clusters, elucidating the causal relationship between clusters in conscious perception of near-threshold targets. Thus, distinct, hemisphere-asymmetric fronto-parietal networks support attentional gain and reorienting in shaping human conscious experience.

Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain

Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain's white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.

Reliability and validity of DTI-based indirect disconnection measures

White matter connections enable the interaction within and between brain networks. Brain lesions can cause structural disconnections that disrupt networks and thereby cognitive functions supported by them. In recent years, novel methods have been developed to quantify the extent of structural disconnection after focal lesions, using tractography data from healthy controls. These methods, however, are indirect and their reliability and validity have yet to be fully established. In this study, we present our implementation of this approach, in a tool supplemented by uncertainty metrics for the predictions overall and at voxel-level. These metrics give an indication of the reliability and are used to compare predictions with direct measures from patients' diffusion tensor imaging (DTI) data in a sample of 95 first-ever stroke patients. Results show that, except for small lesions, the tool can predict fiber loss with high reliability and compares well to direct patient DTI estimates. Clinical utility of the method was demonstrated using lesion data from a subset of patients suffering from hemianopia. Both tract-based measures outperformed lesion localization in mapping visual field defects and showed a network consistent with the known anatomy of the visual system. This study offers an important contribution to the validation of structural disconnection mapping. We show that indirect measures of structural disconnection can be a reliable and valid substitute for direct estimations of fiber loss after focal lesions. Moreover, based on these results, we argue that indirect structural disconnection measures may even be preferable to lower-quality single subject diffusion MRI when based on high-quality healthy control datasets.

Prediction of behavioral deficits in acute stroke from lesion and structural disconnection mapping

Prediction of behavioral deficits in stroke relies on understanding the distribution of focal damage as well as the distribution of the underlying functional anatomy. Using structural or functional magnetic resonance imaging, previous studies investigated the predictive performance of imaging biomarkers for behavioral deficits in stroke patients. However, only focal lesion information or functional connectivity information alone was used in the modelling, with a small sample size and on a specific behavioral deficit domain. In this study, we investigated the prediction of behavioral deficits in acute stroke using both focal lesion patterns and structural disconnection mapping on a cohort of 551 ischemic stroke patients within one week post symptom onset. Five behavioral deficits domains, including motor, cognitive, visual, somatosensory and coordination deficits, were investigated. A probabilistic map of lesion-induced structural "disconnectome" map was created to estimate the degree of structural disconnection due to lesions. In the predictive modelling, both lesion volume and location and distant structural disconnections were included in combination with the clinical information. The results showed that improved prediction performance was achieved when considering both focal lesion patterns and global lesion-induced structural disconnections for all five behavioral deficits groups. Distinct lesion maps were obtained for each behavioral deficit, providing insights into neurobiological mechanisms of stroke functional impairment.

A comparison of lesion mapping analyses based on CT versus MR imaging in stroke

It is commonly asserted that MRI-derived lesion masks outperform CT-derived lesion masks in lesion-mapping analysis. However, no quantitative analysis has been conducted to support or refute this claim. This study reports an objective comparison of lesion-mapping analyses based on CT- and MRI-derived lesion masks to clarify how input imaging type may ultimately impact analysis results. Routine CT and MRI data were collected from 85 acute stroke survivors. These data were employed to create binarized lesion masks and conduct lesion-mapping analyses on simulated behavioral data. Following standard lesion-mapping analysis methodology, each voxel or region of interest (ROI) were considered as the underlying "target" within CT and MRI data independently. The resulting thresholded z-maps were compared between matched CT- and MRI-based analyses. Paired MRI- and CT-derived lesion masks were found to exhibit significant variance in location, overlap, and size. In ROI-level simulations, both CT and MRI-derived analyses yielded low Dice similarity coefficients, but CT analyses yielded a significantly higher proportion of results which overlapped with target ROIs. In single-voxel simulations, MRI-based lesion mapping was able to include more voxels than CT-based analyses, but CT-based analysis results were closer to the underlying target voxel. Simulated lesion-symptom mapping results yielded by paired CT and MRI lesion-symptom mapping analyses demonstrated moderate agreement in terms of Dice coefficient when systematic differences in cluster size and lesion overlay are considered. Overall, these results suggest that CT and MR-derived lesion-symptom mapping results do not reliably differ in accuracy. This finding is critically important as it suggests that future studies can employ CT-derived lesion masks if these scans are available within the appropriate time-window.

Interpreting and validating complexity and causality in lesion-symptom prognoses

This paper considers the steps needed to generate pragmatic and interpretable lesion-symptom mappings that can be used for clinically reliable prognoses. The novel contributions are 3-fold. We first define and inter-relate five neurobiological and five methodological constraints that need to be accounted for when interpreting lesion-symptom associations and generating synthetic lesion data. The first implication is that, because of these constraints, lesion-symptom mapping needs to focus on probabilistic relationships between Lesion and Symptom, with Lesion as a multivariate spatial pattern, Symptom as a time-dependent behavioural profile and evidence that Lesion raises the probability of Symptom. The second implication is that in order to assess the strength of probabilistic causality, we need to distinguish between causal lesion sites, incidental lesion sites, spared but dysfunctional sites and intact sites, all of which might affect the accuracy of the predictions and prognoses generated. We then formulate lesion-symptom mappings in logical notations, including combinatorial rules, that are then used to evaluate and better understand complex brain-behaviour relationships. The logical and theoretical framework presented applies to any type of neurological disorder but is primarily discussed in relationship to stroke damage. Accommodating the identified constraints, we discuss how the 1965 Bradford Hill criteria for inferring probabilistic causality, post hoc, from observed correlations in epidemiology-can be applied to lesion-symptom mapping in stroke survivors. Finally, we propose that rather than rely on post hoc evaluation of how well the causality criteria have been met, the neurobiological and methodological constraints should be addressed, a priori, by changing the experimental design of lesion-symptom mappings and setting up an open platform to share and validate the discovery of reliable and accurate lesion rules that are clinically useful.

Thalamostriatal disconnection underpins long-term seizure freedom in frontal lobe epilepsy surgery

Around 50% of patients undergoing frontal lobe surgery for focal drug-resistant epilepsy become seizure free post-operatively; however, only about 30% of patients remain seizure free in the long-term. Early seizure recurrence is likely to be caused by partial resection of the epileptogenic lesion, whilst delayed seizure recurrence can occur even if the epileptogenic lesion has been completely excised. This suggests a coexistent epileptogenic network facilitating ictogenesis in close or distant dormant epileptic foci. As thalamic and striatal dysregulation can support epileptogenesis and disconnection of cortico-thalamostriatal pathways through hemispherotomy or neuromodulation can improve seizure outcome regardless of focality, we hypothesize that projections from the striatum and the thalamus to the cortex may contribute to this common epileptogenic network. To this end, we retrospectively reviewed a series of 47 consecutive individuals who underwent surgery for drug-resistant frontal lobe epilepsy. We performed voxel-based and tractography disconnectome analyses to investigate shared patterns of disconnection associated with long-term seizure freedom. Seizure freedom after 3 and 5 years was independently associated with disconnection of the anterior thalamic radiation and anterior cortico-striatal projections. This was also confirmed in a subgroup of 29 patients with complete resections, suggesting these pathways may play a critical role in supporting the development of novel epileptic networks. Our study indicates that network dysfunction in frontal lobe epilepsy may extend beyond the resection and putative epileptogenic zone. This may be critical in the pathogenesis of delayed seizure recurrence as thalamic and striatal networks may promote epileptogenesis and disconnection may underpin long-term seizure freedom.

Brain structural and functional correlates of the heterogenous progression of mixed transcortical aphasia

Mixed transcortical aphasia (MTCA) is characterized by non-fluent speech and comprehension deficits coexisting with preserved repetition. MTCA may evolve to less severe variants of aphasias or even to full language recovery. Mechanistically, MCTA has traditionally been attributed to a disconnection between the spared left perisylvian language network (PSLN) responsible for preserved verbal repetition, and damaged left extrasylvian networks, which are responsible for language production and comprehension impairments. However, despite significant advances in in vivo neuroimaging, the structural and functional status of the PSLN network in MTCA and its evolution has not been investigated. Thus, the aim of the present study is to examine the status of the PSLN, both in terms of its functional activity and structural integrity, in four cases who developed acute post-stroke MTCA and progressed to different types of aphasia. For it, we conducted a neuroimaging-behavioral study performed in the chronic stage of four patients. The behavioral profile of MTCA persisted in one patient, whereas the other three patients progressed to less severe types of aphasias. Neuroimaging findings suggest that preserved verbal repetition in MTCA does not always depend on the optimal status of the PSLN and its dorsal connections. Instead, the right hemisphere or the left ventral pathway may also play a role in supporting verbal repetition. The variability in the clinical evolution of MTCA may be explained by the varying degree of PSLN alteration and individual premorbid neuroanatomical language substrates. This study offers a fresh perspective of MTCA through the lens of modern neuroscience and unveils novel insights into the neural underpinnings of repetition.

Associations of lesion location, structural disconnection, and functional diaschisis with depressive symptoms post stroke

Introduction

Post-stroke depressive symptoms (PSDS) are common and relevant for patient outcome, but their complex pathophysiology is ill understood. It likely involves social, psychological and biological factors. Lesion location is a readily available information in stroke patients, but it is unclear if the neurobiological substrates of PSDS are spatially localized. Building on previous analyses, we sought to determine if PSDS are associated with specific lesion locations, structural disconnection and/or localized functional diaschisis.

Methods

In a prospective observational study, we examined 270 patients with first-ever stroke with the Hospital Anxiety and Depression Scale (HADS) around 6 months post-stroke. Based on individual lesion locations and the depression subscale of the HADS we performed support vector regression lesion-symptom mapping, structural-disconnection-symptom mapping and functional lesion network-symptom-mapping, in a reanalysis of this previously published cohort to infer structure-function relationships.

Results

We found that depressive symptoms were associated with (i) lesions in the right insula, right putamen, inferior frontal gyrus and right amygdala and (ii) structural disconnection in the right temporal lobe. In contrast, we found no association with localized functional diaschisis. In addition, we were unable to confirm a previously described association between depressive symptom load and a network damage score derived from functional disconnection maps.

Discussion

Based on our results, and other recent lesion studies, we see growing evidence for a prominent role of right frontostriatal brain circuits in PSDS.

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke

BACKGROUND AND OBJECTIVES

Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance. We hypothesized that more lesion damage would result in older brain age, which would in turn be associated with poorer outcomes. Related, we expected that brain age would mediate the relationship between lesion damage and outcomes. Finally, we hypothesized that structural brain resilience, which we define in the context of stroke as younger brain age given matched lesion damage, would differentiate people with good vs poor outcomes.

METHODS

We conducted a cross-sectional observational study using a multisite dataset of 3-dimensional brain structural MRIs and clinical measures from the ENIGMA Stroke Recovery. Brain age was calculated from 77 neuroanatomical features using a ridge regression model trained and validated on 4,314 healthy controls. We performed a 3-step mediation analysis with robust mixed-effects linear regression models to examine relationships between brain age, lesion damage, and stroke outcomes. We used propensity score matching and logistic regression to examine whether brain resilience predicts good vs poor outcomes in patients with matched lesion damage.

RESULTS

We examined 963 patients across 38 cohorts. Greater lesion damage was associated with older brain age (β = 0.21; 95% CI 0.04-0.38, p = 0.015), which in turn was associated with poorer outcomes, both in the sensorimotor domain (β = -0.28; 95% CI -0.41 to -0.15, p < 0.001) and across multiple domains of function (β = -0.14; 95% CI -0.22 to -0.06, p < 0.001). Brain age mediated 15% of the impact of lesion damage on sensorimotor performance (95% CI 3%-58%, p = 0.01). Greater brain resilience explained why people have better outcomes, given matched lesion damage (odds ratio 1.04, 95% CI 1.01-1.08, p = 0.004).

DISCUSSION

We provide evidence that younger brain age is associated with superior poststroke outcomes and modifies the impact of focal damage. The inclusion of imaging-based assessments of brain age and brain resilience may improve the prediction of poststroke outcomes compared with focal injury measures alone, opening new possibilities for potential therapeutic targets.

Neural Substrates of Psychomotor Speed Deficits in Cerebral Small Vessel Disease: A Brain Disconnectome Mapping Study

It remains unknown which factors influence how brain disconnectivity derived from White Matter Hyperintensity (WMH) lesions leads to psychomotor speed dysfunction, one of the earliest and most common cognitive manifestations in the cerebral Small Vessel Disease (cSVD) population. While the burden of WMH has been strongly linked to psychomotor speed performance, the effect that different locations and volumes of WMH may have on cSVD-related cognitive impairment remains unclear. Therefore, we aimed to explore (1) whether global WMH, deep WMH (DWMH), and periventricular (PVWMH) volumes display different psychomotor speed associations; (2) whether tract-specific WMH volume shows stronger cognitive associations compared with global measures of WMH volume; (3) whether specific patterns of WMH location lead to different degrees of disconnectivity. Using the BCBToolkit, we investigated which pattern of distribution and which locations of WMH lesion result in impaired psychomotor speed in a well-characterized sample (n = 195) of cSVD patients without dementia. Two key findings emerge from our study. First, global (and not tract-specific) measures of WMH volume were associated with psychomotor speed performance. Second, disconnection maps revealed the involvement of callosal tracts, association and projection fibers, and frontal and parietal cortical brain areas related to psychomotor speed, while the lesion location influenced such associations. In conclusion, psychomotor deficits are affected differently by WMH burden and topographic distribution through brain disconnection in non-demented cSVD patients.

Functional architecture of executive processes: Evidence from verbal fluency and lesion mapping in stroke patients

The functional organization and related anatomy of executive functions are still largely unknown and were examined in the present study using a verbal fluency task. The objective of this study was to determine the cognitive architecture of a fluency task and related voxelwise anatomy in the GRECogVASC cohort and fMRI based meta-analytical data. First, we proposed a model of verbal fluency in which two control processes, lexico-semantic strategic search process and attention process, interact with semantic and lexico-phonological output processes. This model was assessed by testing 404 patients and 775 controls for semantic and letter fluency, naming, and processing speed (Trail Making test part A). Regression (R² = .276 and .3, P = .0001, both) and structural equation modeling (CFI: .88, RMSEA: .2, SRMR: .1) analyses supported this model. Second, voxelwise lesion-symptom mapping and disconnectome analyses demonstrated fluency to be associated with left lesions of the pars opercularis, lenticular nucleus, insula, temporopolar region, and a large number of tracts. In addition, a single dissociation showed specific association of letter fluency with the pars triangularis of F3. Disconnectome mapping showed the additional role of disconnection of left frontal gyri and thalamus. By contrast, these analyses did not identify voxels specifically associated with lexico-phonological search processes. Third, meta-analytic fMRI data (based on 72 studies) strikingly matched all structures identified by the lesion approach. These results support our modeling of the functional architecture of verbal fluency based on two control processes (strategic search and attention) operating on semantic and lexico-phonologic output processes. Multivariate analysis supports the prominent role of the temporopolar area (BA 38) in semantic fluency and the F3 triangularis area (BA 45) in letter fluency. Finally, the lack of voxels specifically dedicated to strategic search processes could be due to a distributed organization of executive functions warranting further studies.

Neural correlates of verbal fluency revealed by longitudinal T1, T2 and FLAIR imaging in stroke

Diffusion-weighted imaging has been widely used in the research on post-stroke verbal fluency but acquiring diffusion data is not always clinically feasible. Achieving comparable reliability for detecting brain variables associated with verbal fluency impairments, based on more readily available anatomical, non-diffusion images (T1, T2 and FLAIR), enables clinical practitioners to have complementary neurophysiological information at hand to facilitate diagnosis and treatment of language impairment. Meanwhile, although the predominant focus in the stroke recovery literature has been on cortical contributions to verbal fluency, it remains unclear how subcortical regions and white matter disconnection are related to verbal fluency. Our study thus utilized anatomical scans of ischaemic stroke survivors (n = 121) to identify longitudinal relationships between subcortical volume, white matter tract disconnection, and verbal fluency performance at 3- and 12-months post-stroke. Subcortical grey matter volume was derived from FreeSurfer. We used an indirect probabilistic approach to quantify white matter disconnection in terms of disconnection severity, the proportion of lesioned voxel volume to the total volume of a tract, and disconnection probability, the probability of the overlap between the stroke lesion and a tract. These disconnection variables of each subject were identified based on the disconnectome map of the BCBToolkit. Using a linear mixed multiple regression method with 5-fold cross-validations, we correlated the semantic and phonemic fluency scores with longitudinal measurements of subcortical grey matter volume and 22 bilateral white matter tracts, while controlling for demographic variables (age, sex, handedness and education), total brain volume, lesion volume, and cortical thickness. The results showed that the right subcortical grey matter volume was positively correlated with phonemic fluency averaged over 3 months and 12 months. The finding generalized well on the test data. The disconnection probability of left superior longitudinal fasciculus II and left posterior arcuate fasciculus was negatively associated with semantic fluency only on the training data, but the result aligned with our previous study using diffusion scans in the same clinical population. In sum, our results presented evidence that routinely acquired anatomical scans can serve as a reliable source for deriving neural variables of post-stroke verbal fluency performance. The use of this method might provide an ecologically valid and more readily implementable analysis tool.

Joint impact on attention, alertness and inhibition of lesions at a frontal white matter crossroad

In everyday life, information from different cognitive domains-such as visuospatial attention, alertness and inhibition-needs to be integrated between different brain regions. Early models suggested that completely segregated brain networks control these three cognitive domains. However, more recent accounts, mainly based on neuroimaging data in healthy participants, indicate that different tasks lead to specific patterns of activation within the same, higher-order and 'multiple-demand' network. If so, then a lesion to critical substrates of this common network should determine a concomitant impairment in all three cognitive domains. The aim of the present study was to critically investigate this hypothesis, i.e. to identify focal stroke lesions within the network that can concomitantly affect visuospatial attention, alertness and inhibition. We studied an unselected sample of 60 first-ever right-hemispheric, subacute stroke patients using a data-driven, bottom-up approach. Patients performed 12 standardized neuropsychological and oculomotor tests, four per cognitive domain. A principal component analysis revealed a strong relationship between all three cognitive domains: 10 of 12 tests loaded on a first, common component. Analysis of the neuroanatomical lesion correlates using different approaches (i.e. voxel-based and tractwise lesion-symptom mapping, disconnectome maps) provided convergent evidence on the association between severe impairment of this common component and lesions at the intersection of superior longitudinal fasciculus II and III, frontal aslant tract and, to a lesser extent, the putamen and inferior fronto-occipital fasciculus. Moreover, patients with a lesion involving this region were significantly more impaired in daily living cognition, which provides an ecological validation of our results. A probabilistic functional atlas of the multiple-demand network was performed to confirm the potential relationship between patients' lesion substrates and observed cognitive impairments as a function of the multiple-demand network connectivity disruption. These findings show, for the first time, that a lesion to a specific white matter crossroad can determine a concurrent breakdown in all three considered cognitive domains. Our results support the multiple-demand network model, proposing that different cognitive operations depend on specific collaborators and their interaction, within the same underlying neural network. Our findings also extend this hypothesis by showing (i) the contribution of superior longitudinal fasciculus and frontal aslant tract to the multiple-demand network; and (ii) a critical neuroanatomical intersection, crossed by a vast amount of long-range white matter tracts, many of which interconnect cortical areas of the multiple-demand network. The vulnerability of this crossroad to stroke has specific cognitive and clinical consequences; this has the potential to influence future rehabilitative approaches.