Connectome-based lesion-symptom mapping (CLSM): A novel approach to map neurological function

The Role of Anatomic Connectivity in Inhibitory Control Revealed by Combining Connectome-based Lesion-symptom Mapping with Event-related Potentials

Inhibitory control refers to the ability to suppress cognitive or motor processes. Current neurocognitive models indicate that this function mainly involves the anterior cingulate cortex and the inferior frontal cortex. However, how the communication between these areas influence inhibitory control performance and their functional response remains unknown. We addressed this question by injecting behavioral and electrophysiological markers of inhibitory control recorded during a Go/NoGo task as the 'symptoms' in a connectome-based lesion-symptom mapping approach in a sample of 96 first unilateral stroke patients. This approach enables us to identify the white matter tracts whose disruption by the lesions causally influences brain functional activity during inhibitory control. We found a central role of left frontotemporal and frontobasal intrahemispheric connections, as well as of the connections between the left temporoparietal and right temporal areas in inhibitory control performance. We also found that connections between the left temporal and right superior parietal areas modulate the conflict-related N2 event-related potential component and between the left temporal parietal area and right temporal and occipital areas for the inhibition P3 component. Our study supports the role of a distributed bilateral network in inhibitory control and reveals that combining lesion-symptom mapping approaches with functional indices of cognitive processes could shed new light on post-stroke functional reorganization. It may further help to refine the interpretation of classical electrophysiological markers of executive control in stroke patients.

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.

Hemispheric lateralization of language processing: insights from network-based symptom mapping and patient subgroups

The hemispheric laterality of language processing has become a hot topic in modern neuroscience. Although most previous studies have reported left-lateralized language processing, other studies found it to be bilateral. A previous neurocomputational model has proposed a unified framework to explain that the above discrepancy might be from healthy and patient individuals. This model posits an initial symmetry but imbalanced capacity in language processing for healthy individuals, with this imbalance contributing to language recovery disparities following different hemispheric injuries. The present study investigated this model by analyzing the lateralization patterns of language subnetworks across multiple attributes with a group of 99 patients (compared to nonlanguage processing) and examining the lateralization patterns of language subnetworks in subgroups with damage to different hemispheres. Subnetworks were identified using a whole-brain network-based lesion-symptom mapping method, and the lateralization index was quantitatively measured. We found that all the subnetworks in language processing were left-lateralized, while subnetworks in nonlanguage processing had different lateralization patterns. Moreover, diverse hemisphere-injury subgroups exhibited distinct language recovery effects. These findings provide robust support for the proposed neurocomputational model of language processing.

Network-based statistics distinguish anomic and Broca's aphasia

INTRODUCTION

Aphasia is a speech-language impairment commonly caused by damage to the left hemisphere. The neural mechanisms that underpin different types of aphasia and their symptoms are still not fully understood. This study aims to identify differences in resting-state functional connectivity between anomic and Broca's aphasia measured through resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

We used the network-based statistic (NBS) method, as well as voxel- and connectome-based lesion symptom mapping (V-, CLSM), to identify distinct neural correlates of the anomic and Broca's groups. To control for lesion effect, we included lesion volume as a covariate in both the NBS method and LSM.

RESULTS

NBS identified a subnetwork located in the dorsal language stream bilaterally, including supramarginal gyrus, primary sensory, motor, and auditory cortices, and insula. The connections in the subnetwork were weaker in the Broca's group than the anomic group. The properties of the subnetwork were examined through complex network measures, which indicated that regions in right inferior frontal sulcus, right paracentral lobule, and bilateral superior temporal gyrus exhibit intensive interaction. Left superior temporal gyrus, right postcentral gyrus, and left supramarginal gyrus play an important role in information flow and overall communication efficiency. Disruption of this network underlies the constellation of symptoms associated with Broca's aphasia. Whole-brain CLSM did not detect any significant connections, suggesting an advantage of NBS when thousands of connections are considered. However, CLSM identified connections that differentiated Broca's from anomic aphasia when analysis was restricted to a hypothesized network of interest.

DISCUSSION

We identified novel signatures of resting-state brain network differences between groups of individuals with anomic and Broca's aphasia. We identified a subnetwork of connections that statistically differentiated the resting-state brain networks of the two groups, in comparison with standard CLSM results that yielded isolated connections. Network-level analyses are useful tools for the investigation of the neural correlates of language deficits post-stroke.

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.

Lesion Network Mapping for Neurological Deficit in Acute Ischemic Stroke

OBJECTIVE

To create a comprehensive map of strategic lesion network localizations for neurological deficits, and identify prognostic neuroimaging biomarkers to facilitate the early detection of patients with a high risk of poor functional outcomes in acute ischemic stroke (AIS).

METHODS

In a large-scale multicenter study of 7,807 patients with AIS, we performed voxel-based lesion-symptom mapping, functional disconnection mapping (FDC), and structural disconnection mapping (SDC) to identify distinct lesion and network localizations for National Institutes of Health Stroke Scale (NIHSS) score. Impact scores were calculated based on the odds ratios or t-values of voxels from voxel-based lesion-symptom mapping, FDC, and SDC results. Ordinal regression models were used to investigate the predictive value of the impact scores on functional outcome (defined as the modified Rankin score at 3 months).

RESULTS

We constructed lesion, FDC, and SDC maps for each item of the NIHSS score, which provided insights into the neuroanatomical substrate and network localization of neurological function deficits after AIS. The lesion impact score of limb ataxia, the SDC impact score of limb deficit, and FDC impact score of sensation and dysarthria were significantly associated with modified Rankin Scale at 3 months. Adding the SDC impact score, FDC impact score, and lesion impact score to the NIHSS total score improved the performance in predicting functional outcomes, as compared with using the NIHSS score alone.

INTERPRETATION

We constructed comprehensive maps of strategic lesion network localizations for neurological deficits that were predictive of functional outcomes in AIS. These results may provide specifically localized targets for future neuromodulation therapies. ANN NEUROL 2023;94:572-584.

Mental flexibility depends on a largely distributed white matter network: Causal evidence from connectome-based lesion-symptom mapping

Mental flexibility (MF) refers to the capacity to dynamically switch from one task to another. Current neurocognitive models suggest that since this function requires interactions between multiple remote brain areas, the integrity of the anatomic tracts connecting these brain areas is necessary to maintain performance. We tested this hypothesis by assessing with a connectome-based lesion-symptom mapping approach the effects of white matter lesions on the brain's structural connectome and their association with performance on the trail making test, a neuropsychological test of MF, in a sample of 167 first unilateral stroke patients. We found associations between MF deficits and damage of i) left lateralized fronto-temporo-parietal connections and interhemispheric connections between left temporo-parietal and right parietal areas; ii) left cortico-basal connections; and iii) left cortico-pontine connections. We further identified a relationship between MF and white matter disconnections within cortical areas composing the cognitive control, default mode and attention functional networks. These results for a central role of white matter integrity in MF extend current literature by providing causal evidence for a functional interdependence among the regional cortical and subcortical structures composing the MF network. Our results further emphasize the necessity to consider connectomics in lesion-symptom mapping analyses to establish comprehensive neurocognitive models of high-order cognitive functions.

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.

Using in vivo functional and structural connectivity to predict chronic stroke aphasia deficits

Focal brain damage caused by stroke can result in aphasia and advances in cognitive neuroscience suggest that impairment may be associated with network-level disorder rather than just circumscribed cortical damage. Several studies have shown meaningful relationships between brain-behaviour using lesions; however, only a handful of studies have incorporated in vivo structural and functional connectivity. Patients with chronic post-stroke aphasia were assessed with structural (n = 68) and functional (n = 39) MRI to assess whether predicting performance can be improved with multiple modalities and if additional variance can be explained compared to lesion models alone. These neural measurements were used to construct models to predict four key language-cognitive factors: (i) phonology; (ii) semantics; (iii) executive function; and (iv) fluency. Our results showed that each factor (except executive ability) could be significantly related to each neural measurement alone; however, structural and functional connectivity models did not explain additional variance above the lesion models. We did find evidence that the structural and functional predictors may be linked to the core lesion sites. First, the predictive functional connectivity features were found to be located within functional resting-state networks identified in healthy controls, suggesting that the result might reflect functionally specific reorganization (damage to a node within a network can result in disruption to the entire network). Second, predictive structural connectivity features were located within core lesion sites, suggesting that multimodal information may be redundant in prediction modelling. In addition, we observed that the optimum sparsity within the regularized regression models differed for each behavioural component and across different imaging features, suggesting that future studies should consider optimizing hyperparameters related to sparsity per target. Together, the results indicate that the observed network-level disruption was predicted by the lesion alone and does not significantly improve model performance in predicting the profile of language impairment.

A narrative review of the anatomy and function of the white matter tracts in language production and comprehension

Much is known about the role of cortical areas in language processing. The shift towards network approaches in recent years has highlighted the importance of uncovering the role of white matter in connecting these areas. However, despite a large body of research, many of these tracts’ functions are not well-understood. We present a comprehensive review of the empirical evidence on the role of eight major tracts that are hypothesized to be involved in language processing (inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, extreme capsule, middle longitudinal fasciculus, superior longitudinal fasciculus, arcuate fasciculus, and frontal aslant tract). For each tract, we hypothesize its role based on the function of the cortical regions it connects. We then evaluate these hypotheses with data from three sources: studies in neurotypical individuals, neuropsychological data, and intraoperative stimulation studies. Finally, we summarize the conclusions supported by the data and highlight the areas needing further investigation.

Network-based statistics distinguish anomic and Broca aphasia

Aphasia is a speech-language impairment commonly caused by damage to the left hemisphere. Due to the complexity of speech-language processing, the neural mechanisms that underpin various symptoms between different types of aphasia are still not fully understood. We used the network-based statistic method to identify distinct subnetwork(s) of connections differentiating the resting-state functional networks of the anomic and Broca groups. We identified one such subnetwork that mainly involved the brain regions in the premotor, primary motor, primary auditory, and primary sensory cortices in both hemispheres. The majority of connections in the subnetwork were weaker in the Broca group than the anomic group. The network properties of the subnetwork were examined through complex network measures, which indicated that the regions in the superior temporal gyrus and auditory cortex bilaterally exhibit intensive interaction, and primary motor, premotor and primary sensory cortices in the left hemisphere play an important role in information flow and overall communication efficiency. These findings underlied articulatory difficulties and reduced repetition performance in Broca aphasia, which are rarely observed in anomic aphasia. This research provides novel findings into the resting-state brain network differences between groups of individuals with anomic and Broca aphasia. We identified a subnetwork of, rather than isolated, connections that statistically differentiate the resting-state brain networks of the two groups, in comparison with standard lesion symptom mapping results that yield isolated connections.

Neural substrates of interoceptive sensibility: An integrated study in normal and pathological functioning

In early studies interoception strictly referred to the awareness of visceral sensations, but recent theories have expanded this concept to denote the ongoing status of the body, including somatosensory feelings. Here, we integrated data from normal and pathological functioning to disclose neural underpinnings of interoceptive sensibility, taking into account the crucial distinction between visceral and somatosensory feelings. Twenty-seven healthy young individuals underwent structural MRI (including T1w images and DTI). Voxel-wise analyses of the gyrification index (GI) and fractional anisotropy (FA) data were performed to assess the relation between interoceptive sensibility and surface morphometry and anatomical connectivity. Thirty-three unilateral brain-damaged patients took part in this study for Voxel-Based Lesion-Symptom Mapping (VLSM) and track-wise hodological lesion-deficit analysis (TWH). All participants completed the Self-Awareness Questionnaire (SAQ), a self-report tool assessing interoceptive sensibility of visceral (F1) and somatosensory feelings (F2). Tract-Based Spatial Statistics showed that F2 was positively associated with FA in the bilateral anterior thalamic radiation, corticospinal tract, cingulum, forceps, inferior longitudinal, fronto-occipital, superior longitudinal, and uncinate fasciculi; no significant association was detected for F1. However, F1 was positively associated with GI in the left anterior cingulate cortex. VLSM showed that F1 mainly relies on the right posterior insula, whereas F2 is related mostly to subcortical nuclei and surrounding white matter in the right hemisphere. Accordingly, patients with disconnection of the anterior thalamic projection, corticospinal tract, inferior fronto-occipital, inferior longitudinal, uncinate and superior longitudinal fasciculus III showed lower scores on F2. Overall, results support the dissociation between interoceptive sensibility of visceral and somatosensory feelings.

Gesture meaning modulates the neural correlates of effector-specific imitation deficits in left hemisphere stroke

BACKGROUND

Previous studies on left hemisphere (LH) stroke patients reported effector-specific (hand, fingers, bucco-facial) differences in imitation performance. Furthermore, imitation performance differed between meaningless (ML) and meaningful (MF) gestures. Recent work suggests that a gesture's meaning impacts the body-part specificity of gesture imitation.

METHODS

We tested the hypothesis that the gesture's meaning (ML vs MF) affects the lesion correlates of effector-specific imitation deficits (here: bucco-facial vs arm/hand gestures) using behavioural data and support vector regression-based lesion-symptom mapping (SVR-LSM) in a large sample of 194 sub-acute LH stroke patients.

RESULTS

Behavioural data revealed a significant interaction between the effector used for imitation and the meaning of the imitated gesture. SVR-LSM analyses revealed shared lesion correlates for impaired imitation independent of effector or gesture meaning in the left supramarginal (SMG) and superior temporal gyri (STG). Besides, within the territory of the left middle cerebral artery, impaired imitation of bucco-facial gestures was associated with more anterior lesions, while arm/hand imitation deficits were associated with more posterior lesions. MF gestures were specifically associated with lesions in the left inferior frontal gyrus and the left insular region. Notably, an interaction of effector-specificity and gesture meaning was also present at the lesion level: A more pronounced difference in imitation performance between the effectors for ML (versus MF) gestures was associated with left-hemispheric lesions in the STG, SMG, putamen, precentral gyrus and white matter tracts.

CONCLUSION

The current behavioural data show that ML gestures are particularly sensitive in assessing effector-specific imitation deficits in LH stroke patients. Moreover, a gesture's meaning modulated the effector-specific lesion correlates of bucco-facial and arm/hand gesture imitation. Hence, it is crucial to consider gesture meaning in apraxia assessments.

The impact of etiology in lesion-symptom mapping - A direct comparison between tumor and stroke

INTRODUCTION

Lesion-symptom mapping is a key tool in understanding the relationship between brain structures and behavior. However, the behavioral consequences of lesions from different etiologies may vary because of how they affect brain tissue and how they are distributed. The inclusion of different etiologies would increase the statistical power but has been critically debated. Meanwhile, findings from lesion studies are a valuable resource for clinicians and used across different etiologies. Therefore, the main objective of the present study was to directly compare lesion-symptom maps for memory and language functions from two populations, a tumor versus a stroke population.

METHODS

Data from two different studies were combined. Both the brain tumor (N = 196) and stroke (N = 147) patient populations underwent neuropsychological testing and an MRI, pre-operatively for the tumor population and within three months after stroke. For this study, we selected two internationally widely used standardized cognitive tasks, the Rey Auditory Verbal Learning Test and the Verbal Fluency Test. We used a state-of-the-art machine learning-based, multivariate voxel-wise approach to produce lesion-symptom maps for these cognitive tasks for both populations separately and combined.

RESULTS

Our lesion-symptom mapping results for the separate patient populations largely followed the expected neuroanatomical pattern based on previous literature. Substantial differences in lesion distribution hindered direct comparison. Still, in brain areas with adequate coverage in both groups, considerable LSM differences between the two populations were present for both memory and fluency tasks. Post-hoc analyses of these locations confirmed that the cognitive consequences of focal brain damage varied between etiologies.

CONCLUSION

The differences in the lesion-symptom maps between the stroke and tumor population could partly be explained by differences in lesion volume and topography. Despite these methodological limitations, both the lesion-symptom mapping results and the post-hoc analyses confirmed that etiology matters when investigating the cognitive consequences of lesions with lesion-symptom mapping. Therefore, caution is advised with generalizing lesion-symptom results across etiologies.

Disconnectomics to unravel the network underlying deficits of spatial exploration and attention

Spatial attention and exploration are related to a predominantly right hemispheric network structure. However, the areas of the brain involved and their exact role is still debated. Spatial neglect following right hemispheric stroke lesions has been frequently viewed as a model to study these processes in humans. Previous investigations on the anatomical basis on spatial neglect predominantly focused on focal brain damage and lesion-behaviour mapping analyses. This approach might not be suited to detect remote areas structurally spared but which might contribute to the behavioural deficit. In the present study of a sample of 203 right hemispheric stroke patients, we combined connectome lesion-symptom mapping with multivariate support vector regression to unravel the complex and disconnected network structure in spatial neglect. We delineated three central nodes that were extensively disconnected from other intrahemispheric areas, namely the right superior parietal lobule, the insula, and the temporal pole. Additionally, the analysis allocated central roles within this network to the inferior frontal gyrus (pars triangularis and opercularis), right middle temporal gyrus, right temporal pole and left and right orbitofrontal cortices, including interhemispheric disconnection. Our results suggest that these structures-although not necessarily directly damaged-might play a role within the network underlying spatial neglect in humans.

Behavioural and neural structure of fluent speech production deficits in aphasia

Deficits in fluent speech production following left hemisphere stroke are a central concern because of their impact on patients' lives and the insight they provide about the neural organization of language processing. Fluent speech production requires the rapid coordination of phonological, semantic, and syntactic processing, so this study examined how deficits in connected speech relate to these language sub-systems. Behavioural data (N = 69 participants with aphasia following left hemisphere stroke) consisted of a diverse and comprehensive set of narrative speech production measures and measures of overall severity, semantic deficits, and phonological deficits. These measures were entered into a principal component analysis with bifactor rotation-a latent structure model where each item loads on a general factor that reflects what is common among the items, and orthogonal factors that explain variance not accounted for by the general factor. Lesion data were available for 58 of the participants, and each factor score was analysed with multivariate lesion-symptom mapping. Effects of connectivity disruption were evaluated using robust regression with tract disconnection or graph theoretic measures of connectivity as predictors. The principal component analysis produced a four-factor solution that accounted for 70.6% of the variance in the data, with a general factor corresponding to the overall severity and length and complexity of speech output (complexity factor), a lexical syntax factor, and independent factors for Semantics and Phonology. Deficits in the complexity of speech output were associated with a large temporo-parietal region, similar to overall aphasia severity. The lexical syntax factor was associated with damage in a relatively small set of fronto-parietal regions which may reflect the recruitment of control systems to support retrieval and correct usage of lexical items that primarily serve a syntactic rather than semantic function. Tract-based measures of connectivity disruption were not statistically associated with the deficit scores after controlling for overall lesion volume. Language network efficiency and average clustering coefficient within the language network were significantly associated with deficit scores after controlling for overall lesion volume. These results highlight overall severity as the critical contributor to fluent speech in post-stroke aphasia, with a dissociable factor corresponding to lexical syntax.

Early white matter connectivity and plasticity in post stroke aphasia recovery

A disruption of white matter connectivity is negatively associated with language (recovery) in patients with aphasia after stroke, and behavioral gains have been shown to coincide with white matter neuroplasticity. However, most brain-behavior studies have been carried out in the chronic phase after stroke, with limited generalizability to earlier phases. Furthermore, few studies have investigated neuroplasticity patterns during spontaneous recovery (i.e., not related to a specific treatment) in the first months after stroke, hindering the investigation of potential early compensatory mechanisms. Finally, the majority of previous research has focused on damaged left hemisphere pathways, while neglecting the potential protective value of their right hemisphere counterparts for language recovery. To address these outstanding issues, we present a longitudinal study of thirty-two patients with aphasia (21 males and 11 females, M = 69.47 years, SD = 10.60 years) who were followed up for a period of 1 year with test moments in the acute (1-2 weeks), subacute (3-6 months) and chronic phase (9-12 months) after stroke. Constrained Spherical Deconvolution-based tractography was performed in the acute and subacute phase to measure Fiber Bundle Capacity (FBC), a quantitative connectivity measure that is valid in crossing fiber regions, in the bilateral dorsal arcuate fasciculus (AF) and the bilateral ventral inferior fronto-occipital fasciculus (IFOF). First, concurrent analyses revealed positive associations between the left AF and phonology, and between the bilateral IFOF and semantics in the acute - but not subacute - phase, supporting the dual-stream language model. Second, neuroplasticity analyses revealed a decrease in connection density of the bilateral AF - but not the IFOF - from the acute to the subacute phase, possibly reflecting post stroke white matter degeneration in areas adjacent to the lesion. Third, predictive analyses revealed no contribution of acute FBC measures to the prediction of later language outcomes over and above the initial language scores, suggesting no added value ofthe diffusion measures for languageprediction. Our study provides new insights on (changes in) connectivity of damaged and undamaged language pathways in patients with aphasia in the first months after stroke, as well as if/how such measures are related to language outcomes at different stages of recovery. Individual results are discussed in the light of current frameworks of language processing and aphasia recovery.

Neural network bases of thematic semantic processing in language production

Semantic processing is a central component of language and cognition. The anterior temporal lobe is postulated to be a key hub for semantic processing, but the posterior temporoparietal cortex is also involved in thematic associations during language. It is possible that these regions act in concert and depend on an anteroposterior network linking the temporal pole with posterior structures to support thematic semantic processing during language production. We employed connectome-based lesion-symptom mapping to examine the causal relationship between lesioned white matter pathways and thematic processing language deficits among individuals with post-stroke aphasia. Seventy-nine adults with chronic aphasia completed the Philadelphia Naming Test, and semantic errors were coded as either thematic or taxonomic to control for taxonomic errors. Controlling for nonverbal conceptual-semantic knowledge as measured by the Pyramids and Palm Trees Test, lesion size, and the taxonomic error rate, thematic error rate was associated with loss of white matter connections from the temporal pole traversing in peri-Sylvian regions to the posterior cingulate and the insula. These findings support the existence of a distributed network underlying thematic relationship processing in language as opposed to discrete cortical areas.

Indirect structural disconnection-symptom mapping

In vivo tracking of white matter fibres catalysed a modern perspective on the pivotal role of brain connectome disruption in neuropsychological deficits. However, the examination of white matter integrity in neurological patients by diffusion-weighted magnetic resonance imaging bears conceptual limitations and is not widely applicable, as it requires imaging-compatible patients and resources beyond the capabilities of many researchers. The indirect estimation of structural disconnection offers an elegant and economical alternative. For this approach, a patient's structural lesion information and normative connectome data are combined to estimate different measures of lesion-induced structural disconnection. Using one of several toolboxes, this method is relatively easy to implement and is even available to scientists without expertise in fibre tracking analyses. Nevertheless, the anatomo-behavioural statistical mapping of structural brain disconnection requires analysis steps that are not covered by these toolboxes. In this paper, we first review the current state of indirect lesion disconnection estimation, the different existing measures, and the available software. Second, we aim to fill the remaining methodological gap in statistical disconnection-symptom mapping by providing an overview and guide to disconnection data and the statistical mapping of their relationship to behavioural measurements using either univariate or multivariate statistical modelling. To assist in the practical implementation of statistical analyses, we have included software tutorials and analysis scripts.

Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study

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Individual disconnectome maps generated using a template of 7T MRI data.

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Disconnectome maps conceptualize distal brain network aberrations.

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Using lesions maps from our MS cohort, we produced individual disconnectome maps.

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Serum neurofilament light levels were associated with disconnectome maps.

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Voxel-wise analyses revealed interesting association with serum neurofilament light levels.

Background and Objectives

Connectivity-based approaches incorporating the distribution and magnitude of the extended brain network aberrations caused by lesions may offer higher sensitivity for axonal damage in patients with multiple sclerosis (MS) than conventional lesion characteristics. Using individual brain disconnectome mapping, we tested the longitudinal associations between putative imaging-based brain network aberrations and levels of serum neurofilament light chain (NfL) as a neuroaxonal injury biomarker.

Methods

MS patients (n = 312, mean age 42.9 years, 71 % female) and healthy controls (HC) (n = 59, mean age 39.9 years, 78 % female) were prospectively enrolled at four European MS centres, and reassessed after two years (MS, n = 242; HC, n = 30). Post-processing of 3 Tesla (3 T) MRI data was performed at one centre using a harmonized pipeline, and disconnectome maps were calculated using BCBtoolkit based on individual lesion maps. Global disconnectivity (GD) was defined as the average disconnectome probability in each patient’s white matter. Serum NfL concentrations were measured by single molecule array (Simoa). Robust linear mixed models (rLMM) with GD or T2-lesion volume (T2LV) as dependent variables, patient as a random factor, serum NfL, age, sex, timepoint for visit, diagnosis, treatment, and center as fixed factors were run.

Results

rLMM revealed significant associations between GD and serum NfL (t = 2.94, p = 0.003), age (t = 4.21, p = 2.5 × 10⁻⁵), and longitudinal changes in NfL (t = -2.29, p = 0.02), but not for sex (t = 0.63, p = 0.53) or treatments (t = 0.80–0.83, p = 0.41–0.42). Voxel-wise analyses revealed significant associations between dysconnectivity in cerebellar and brainstem regions and serum NfL (t = 7.03, p < 0.001).

Discussion

In our prospective multi-site MS cohort, rLMMs demonstrated that the extent of global and regional brain disconnectivity is sensitive to a systemic biomarker of axonal damage, serum NfL, in patients with MS. These findings provide a neuroaxonal correlate of advanced disconnectome mapping and provide a platform for further investigations of the functional and potential clinical relevance of brain disconnectome mapping in patients with brain disorders.

Simulated Attack Reveals How Lesions Affect Network Properties in Poststroke Aphasia

Aphasia is a prevalent cognitive syndrome caused by stroke. The rarity of premorbid imaging and heterogeneity of lesion obscures the links between the local effects of the lesion, global anatomic network organization, and aphasia symptoms. We applied a simulated attack approach in humans to examine the effects of 39 stroke lesions (16 females) on anatomic network topology by simulating their effects in a control sample of 36 healthy (15 females) brain networks. We focused on measures of global network organization thought to support overall brain function and resilience in the whole brain and within the left hemisphere. After removing lesion volume from the network topology measures and behavioral scores [the Western Aphasia Battery Aphasia Quotient (WAB-AQ), four behavioral factor scores obtained from a neuropsychological battery, and a factor sum], we compared the behavioral variance accounted for by simulated poststroke connectomes to that observed in the randomly permuted data. Global measures of anatomic network topology in the whole brain and left hemisphere accounted for 10% variance or more of the WAB-AQ and the lexical factor score beyond lesion volume and null permutations. Streamline networks provided more reliable point estimates than FA networks. Edge weights and network efficiency were weighted most highly in predicting the WAB-AQ for FA networks. Overall, our results suggest that global network measures provide modest statistical value beyond lesion volume when predicting overall aphasia severity, but less value in predicting specific behaviors. Variability in estimates could be induced by premorbid ability, deafferentation and diaschisis, and neuroplasticity following stroke.SIGNIFICANCE STATEMENT Poststroke, the remaining neuroanatomy maintains cognition and supports recovery. However, studies often use small, cross-sectional samples that cannot fully model the interactions between lesions and other variables that affect networks in stroke. Alternate methods are required to account for these effects. "Simulated attack" models are computational approaches that apply virtual damage to the brain and measure their putative consequences. Using a simulated attack model, we estimated how simulated damage to anatomic networks could account for language performance. Overall, our results reveal that global network measures can provide modest statistical value predicting overall aphasia severity, but less value in predicting specific behaviors. These findings suggest that more theoretically precise network models could be necessary to robustly predict individual outcomes in aphasia.

Canonical Sentence Processing and the Inferior Frontal Cortex: Is There a Connection?

The role of left inferior frontal cortex (LIFC) in canonical sentence comprehension is controversial. Many studies have found involvement of LIFC in sentence production or complex sentence comprehension, but negative or mixed results are often found in comprehension of simple or canonical sentences. We used voxel-, region-, and connectivity-based lesion symptom mapping (VLSM, RLSM, CLSM) in left-hemisphere chronic stroke survivors to investigate canonical sentence comprehension while controlling for lexical-semantic, executive, and phonological processes. We investigated how damage and disrupted white matter connectivity of LIFC and two other language-related regions, the left anterior temporal lobe (LATL) and posterior temporal-inferior parietal area (LpT-iP), affected sentence comprehension. VLSM and RLSM revealed that LIFC damage was not associated with canonical sentence comprehension measured by a sensibility judgment task. LIFC damage was associated instead with impairments in a lexical semantic similarity judgment task with high semantic/executive demands. Damage to the LpT-iP, specifically posterior middle temporal gyrus (pMTG), predicted worse sentence comprehension after controlling for visual lexical access, semantic knowledge, and auditory-verbal short-term memory (STM), but not auditory single-word comprehension, suggesting pMTG is vital for auditory language comprehension. CLSM revealed that disruption of left-lateralized white-matter connections from LIFC to LATL and LpT-iP was associated with worse sentence comprehension, controlling for performance in tasks related to lexical access, auditory word comprehension, and auditory-verbal STM. However, the LIFC connections were accounted for by the lexical semantic similarity judgment task, which had high semantic/executive demands. This suggests that LIFC connectivity is relevant to canonical sentence comprehension when task-related semantic/executive demands are high.

Widespread cortical functional disconnection in gliomas: an individual network mapping approach

Assessment of impaired/preserved cortical regions in brain tumours is typically performed via intraoperative direct brain stimulation of eloquent areas or task-based functional MRI. One main limitation is that they overlook distal brain regions or networks that could be functionally impaired by the tumour.

This study aims: 1) to investigate the impact of brain tumours on the cortical synchronization of brain networks measured with resting-state functional magnetic resonance imaging (resting-state networks) both near the lesion and remotely; 2) to test whether potential changes in resting state networks correlate with cognitive status.

The sample included twenty-four glioma patients (mean age 58.1 ± 16.4y) with different pathological staging. We developed a new method for single subject localization of resting state networks abnormalities. First, we derived the spatial pattern of the main resting state networks by means of the group guided independent component analysis. This was informed by a high-resolution resting state networks template derived from an independent sample of healthy controls. Second, we developed a spatial similarity index to measure differences in network topography and strength between healthy controls and individual brain tumour patients. Next, we investigated the spatial relationship between altered networks and tumour location. Finally, multivariate analyses related cognitive scores across multiple cognitive domains (attention, language, memory, decision making) with patterns of multi-network abnormality.

We found that brain gliomas cause broad alterations of resting state networks topography that occurred mainly in structurally normal regions outside the tumour and oedema region. Cortical regions near the tumour often showed normal synchronization. Finally, multi-network abnormalities predicted attention deficits.

Overall, we present a novel method for the functional localization of resting state networks abnormalities in individual glioma patients. These abnormalities partially explain cognitive disabilities and shall be carefully navigated during surgery.

Lesion correlates of auditory sentence comprehension deficits in post-stroke aphasia

Auditory sentence comprehension requires coordination of multiple levels of processing: auditory-phonological perception, lexical-semantic comprehension, syntactic parsing and discourse construction, as well as executive functions such as verbal working memory (WM) and cognitive control. This study examined the lesion correlates of sentence comprehension deficits in post-stroke aphasia, building on prior work on this topic by using a different and clinically-relevant measure of sentence comprehension (the Token Test) and multivariate (SCCAN) and connectome-based lesion-symptom mapping methods. The key findings were that lesions in the posterior superior temporal lobe and inferior frontal gyrus (pars triangularis) were associated with sentence comprehension deficits, which was observed in both mass univariate and multivariate lesion-symptom mapping. Graph theoretic measures of connectome disruption were not statistically significantly associated with sentence comprehension deficits after accounting for overall lesion size.

Study protocol: retrospectively mining multisite clinical data to presymptomatically predict seizure onset for individual patients with Sturge-Weber

INTRODUCTION

Secondary analysis of hospital-hosted clinical data can save time and cost compared with prospective clinical trials for neuroimaging biomarker development. We present such a study for Sturge-Weber syndrome (SWS), a rare neurovascular disorder that affects 1 in 20 000-50 000 newborns. Children with SWS are at risk for developing neurocognitive deficit by school age. A critical period for early intervention is before 2 years of age, but early diagnostic and prognostic biomarkers are lacking. We aim to retrospectively mine clinical data for SWS at two national centres to develop presymptomatic biomarkers.

METHODS AND ANALYSIS

We will retrospectively collect clinical, MRI and neurocognitive outcome data for patients with SWS who underwent brain MRI before 2 years of age at two national SWS care centres. Expert review of clinical records and MRI quality control will be used to refine the cohort. The merged multisite data will be used to develop algorithms for abnormality detection, lesion-symptom mapping to identify neural substrate and machine learning to predict individual outcomes (presence or absence of seizures) by 2 years of age. Presymptomatic treatment in 0-2 years and before seizure onset may delay or prevent the onset of seizures by 2 years of age, and thereby improve neurocognitive outcomes. The proposed work, if successful, will be one of the largest and most comprehensive multisite databases for the presymptomatic phase of this rare disease.

ETHICS AND DISSEMINATION

This study involves human participants and was approved by Boston Children's Hospital Institutional Review Board: IRB-P00014482 and IRB-P00025916 Johns Hopkins School of Medicine Institutional Review Board: NA_00043846. Participants gave informed consent to participate in the study before taking part. The Institutional Review Boards at Kennedy Krieger Institute and Boston Children's Hospital approval have been obtained at each site to retrospectively study this data. Results will be disseminated by presentations, publication and sharing of algorithms generated.

Prediction of Communication Impairment in Children With Bilateral Cerebral Palsy Using Multivariate Lesion- and Connectome-Based Approaches: Protocol for a Multicenter Prospective Cohort Study

BACKGROUND

Bilateral cerebral palsy (BCP) is the most common type of CP in children and is often accompanied by different degrees of communication impairment. Several studies have attempted to identify children at high risk for communication impairment. However, most prediction factors are qualitative and subjective and may be influenced by rater bias. Individualized objective diagnostic and/or prediction methods are still lacking, and an effective method is urgently needed to guide clinical diagnosis and treatment. The aim of this study is to develop and validate an objective, individual-based model for the prediction of communication impairment in children with BCP by the time they enter school.

METHODS

A multicenter prospective cohort study will be conducted in four Chinese hospitals. A total of 178 children with BCP will undergo advanced brain magnetic resonance imaging (MRI) at baseline (corrected age, before the age of 2 years). At school entry, communication performance will be assessed by a communication function classification system (CFCS). Three-quarters of children with BCP will be allocated as a training cohort, whereas the remaining children will be allocated as a test cohort. Multivariate lesion- and connectome-based approaches, which have shown good predictive ability of language performance in stroke patients, will be applied to extract features from MR images for each child with BCP. Multiple machine learning models using extracted features to predict communication impairment for each child with BCP will be constructed using data from the training cohort and externally validated using data from the test cohort. Prediction accuracy across models in the test cohort will be statistically compared.

DISCUSSION

The findings of the study may lead to the development of several translational tools that can individually predict communication impairment in children newly diagnosed with BCP to ensure that these children receive early, targeted therapeutic intervention before they begin school.

TRIAL REGISTRATION

The study has been registered with the Chinese Clinical Trial Registry (ChiCTR2100049497).

The role of disrupted structural connectivity in aphasia

Lesion-based studies are among the most informative approaches to determine a critical relationship between a particular brain region and specific function. Importantly, brain lesions cause disconnection of other brain areas that appear to be intact and may cause functional deficits in these regions due to a lack of afferent projections. If only the location of necrosis and gliosis after the stroke is considered to be the lesion, the full spectrum of brain dysfunction is only partly assessed, and there is a high probability that incomplete region-to-function inferences are made. In this chapter we (1) outline how structural connectivity can be measured in individuals with stroke, and (2) provide an overview of the importance of disrupted structural connectivity in aphasia. We conclude that connection-based and region/voxel-based symptom mapping yield complementary information and together provide an in-depth picture of brain and function relationships.

Language Recovery after Brain Injury: A Structural Network Control Theory Study

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

Independent contributions of structural and functional connectivity: Evidence from a stroke model

Altered functional connectivity is related to severity of language impairment in poststroke aphasia. However, it is not clear whether this finding specifically reflects loss of functional coherence, or more generally, is related to decreased structural connectivity due to cortical necrosis. The aim of the current study was to investigate this issue by factoring out structural connectivity from functional connectivity measures and then relating the residual data to language performance poststroke. Ninety-seven participants with a history of stroke were assessed using language impairment measures (Auditory Verbal Comprehension and Spontaneous Speech scores from the Western Aphasia Battery–Revised) and MRI (structural, diffusion tensor imaging, and resting-state functional connectivity). We analyzed the association between functional connectivity and language and controlled for multiple potential neuroanatomical confounders, namely structural connectivity. We identified functional connections within the left hemisphere ventral stream where decreased functional connectivity, independent of structural connectivity, was associated with speech comprehension impairment. These connections exist in frontotemporal and temporoparietal regions. Our results suggest poor speech comprehension in aphasia is at least partially caused by loss of cortical synchrony in a left hemisphere ventral stream network and is not only reflective of localized necrosis or structural connectivity.

Association Between Anatomical Location of Surgically Induced Lesions and Postoperative Seizure Outcome in Temporal Lobe Epilepsy

BACKGROUND AND OBJECTIVES

To determine the association between surgical lesions of distinct gray and white structures and connections with favorable postoperative seizure outcomes.

METHODS

Patients with drug-resistant temporal lobe epilepsy (TLE) from 3 epilepsy centers were included. We employed a voxel-based and connectome-based mapping approach to determine the association between favorable outcomes and surgery-induced temporal lesions. Analyses were conducted controlling for multiple confounders, including total surgical resection/ablation volume, hippocampal volumes, side of surgery, and site where the patient was treated.

RESULTS

The cohort included 113 patients with TLE (54 women; 86 right-handed; mean age at seizure onset 16.5 years [SD 11.9]; 54.9% left) who were 61.1% free of disabling seizures (Engel Class 1) at follow-up. Postoperative seizure freedom in TLE was associated with (1) surgical lesions that targeted the hippocampus as well as the amygdala-piriform cortex complex and entorhinal cortices; (2) disconnection of temporal, frontal, and limbic regions through loss of white matter tracts within the uncinate fasciculus, anterior commissure, and fornix; and (3) functional disconnection of the frontal (superior and middle frontal gyri, orbitofrontal region) and temporal (superior and middle pole) lobes.

DISCUSSION

Better postoperative seizure freedom is associated with surgical lesions of specific structures and connections throughout the temporal lobes. These findings shed light on the key components of epileptogenic networks in TLE and constitute a promising source of new evidence for future improvements in surgical interventions.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that for patients with TLE, postoperative seizure freedom is associated with surgical lesions of specific temporal lobe structures and connections.

Disruptions of the Human Connectome Associated With Hemispatial Neglect

BACKGROUND AND OBJECTIVES

Hemispatial neglect is a heterogeneous and complex disorder that can be classified by frame of reference for "left" vs "right," including viewer-centered neglect (VCN, affecting the contralesional side of the view), stimulus-centered neglect (SCN, affecting the contralesional side of the stimulus, irrespective of its location with respect to the viewer), or both. We investigated the effect of acute stroke lesions on the connectivity of neural networks that underlie VCN or SCN.

METHODS

A total of 174 patients within 48 hours of acute right hemispheric infarct underwent a detailed hemispatial neglect assessment that included oral reading, scene copy, line cancellation, gap detection, horizontal line bisection tests, and MRI. Each patient's connectivity map was generated. We performed a linear association analysis between network connectivity strength and continuous measures of neglect to identify lesion-induced disconnections associated with the presence or severity of VCN and SCN. Results were corrected for multiple comparisons.

RESULTS

About 42% of the participants with right hemisphere stroke had at least one type of neglect. The presence of any type of neglect was associated with lesions to tracts connecting the right inferior parietal cortex, orbitofrontal cortex, and right thalamus to other right-hemispheric structures. VCN only was strongly associated with tracts connecting the right putamen to other brain regions and tracts connecting right frontal regions with other brain regions. The presence of both types of neglect was most strongly associated with tracts connecting the right inferior and superior parietal cortex to other brain regions and those connecting left or right mesial temporal cortex to other brain regions.

DISCUSSION

Our study provides new evidence for the specific white matter tracts where disruption can cause hemispatial neglect in a relatively large number of participants and homogeneous time after onset. We obtained MRI and behavioral testing acutely, before the opportunity for rehabilitation or substantial recovery.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that damage to specific white matter tracts identified on MRI are associated with the presence of neglect following right hemispheric stroke.

Structural disconnection of the posterior medial frontal cortex reduces speech error monitoring

Optimal performance in any task relies on the ability to detect and correct errors. The anterior cingulate cortex and the broader posterior medial frontal cortex (pMFC) are active during error processing. However, it is unclear whether damage to the pMFC impairs error monitoring. We hypothesized that successful error monitoring critically relies on connections between the pMFC and broader cortical networks involved in executive functions and the task being monitored. We tested this hypothesis in the context of speech error monitoring in people with post-stroke aphasia. Diffusion weighted images were collected in 51 adults with chronic left-hemisphere stroke and 37 age-matched control participants. Whole-brain connectomes were derived using constrained spherical deconvolution and anatomically-constrained probabilistic tractography. Support vector regressions identified white matter connections in which lost integrity in stroke survivors related to reduced error detection during confrontation naming. Lesioned connections to the bilateral pMFC were related to reduce error monitoring, including many connections to regions associated with speech production and executive function. We conclude that connections to the pMFC support error monitoring. Error monitoring in speech production is supported by the structural connectivity between the pMFC and regions involved in speech production, comprehension, and executive function. Interactions between pMFC and other task-relevant processors may similarly be critical for error monitoring in other task contexts.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Isolating the white matter circuitry of the dorsal language stream: Connectome-Symptom Mapping in stroke induced aphasia

The application of ℓ1-regularized machine learning models to high-dimensional connectomes offers a promising methodology to assess clinical-anatomical correlations in humans. Here, we integrate the connectome-based lesion-symptom mapping framework with sparse partial least squares regression (sPLS-R) to isolate elements of the connectome associated with speech repetition deficits. By mapping over 2,500 connections of the structural connectome in a cohort of 71 stroke-induced cases of aphasia presenting with varying left-hemisphere lesions and repetition impairment, sPLS-R was trained on 50 subjects to algorithmically identify connectomic features on the basis of their predictive value. The highest ranking features were subsequently used to generate a parsimonious predictive model for speech repetition whose predictions were evaluated on a held-out set of 21 subjects. A set of 10 short- and long-range parieto-temporal connections were identified, collectively delineating the broader circuitry of the dorsal white matter network of the language system. The strongest contributing feature was a short-range connection in the supramarginal gyrus, approximating the cortical localization of area Spt, with parallel long-range pathways interconnecting posterior nodes in supramarginal and superior temporal cortex with anterior nodes in both ventral and-notably-in dorsal premotor cortex, respectively. The collective disruption of these pathways indexed repetition performance in the held-out set of participants, suggesting that these impairments might be characterized as a parietotemporal disconnection syndrome impacting cortical area Spt and its associated white matter circuits of the frontal lobe as opposed to being purely a disconnection of the arcuate fasciculus.

Neural bases of elements of syntax during speech production in patients with aphasia

The ability to string together words into a structured arrangement capable of conveying nuanced information is key to speech production. The assessment of the neural bases for structuring sentences has been challenged by the need of experts to delineate the aberrant morphosyntactic structures in aphasic speech. Most studies have relied on focused tasks with limited ecological validity. We characterized syntactic complexity during connected speech produced by patients with chronic post-stroke aphasia. We automated this process by employing Natural Language Processing (NLP). We conducted voxel-based and connectome-based lesion-symptom mapping to identify brain regions crucially associated with sentence production and syntactic complexity. Posterior-inferior aspects of left frontal and parietal lobes, as well as white matter tracts connecting these areas, were essential for syntactic complexity, particularly the posterior inferior frontal gyrus. These findings suggest that sentence structuring during word production depends on the integrity of Broca's area and the dorsal stream of language processing.

Suggestions for Improving the Investigation of Gesture in Aphasia

Purpose When we speak, we gesture, and indeed, persons with aphasia gesture more frequently. The reason(s) for this is still being investigated, spurring an increase in the number of studies of gesture in persons with aphasia. As the number of studies increases, so too does the need for a shared set of best practices for gesture research in aphasia. After briefly reviewing the importance and use of gesture in persons with aphasia, this viewpoint puts forth methodological and design considerations when evaluating gesture in persons with aphasia. Method & Results We explore several different design and methodological considerations for gesture research specific to persons with aphasia, such as video angle specifications, data collection techniques, and analysis considerations. The goal of these suggestions is to develop transparent and reproducible methods for evaluating gesture in aphasia to build a solid foundation for continued work in this area. Conclusions We have proposed that it is critical to evaluate multimodal communication in a methodologically robust way to facilitate increased knowledge about the relationship of gesture to spoken language, cognition, and to other aspects of living with aphasia and recovery from aphasia. We conclude by postulating future directions for gesture research in aphasia.

Cortical disconnection in temporal lobe epilepsy

A critical concept in neurology is cortical disconnection, in which seemingly normal gray matter can have reduced function due to loss of white matter (WM) connections. White matter damage has been extensively described in temporal lobe epilepsy (TLE), but the anatomical distribution of cortical disconnection in TLE is not fully characterized. Here, we studied 221 participants (64 left-TLE, 55 right-TLE, 102 controls) from three different epilepsy treatment centers. We employed a group connectometry diffusion imaging tractography approach to identify WM fibers with reduced integrity in TLE. We then assessed the anatomical distribution of the gray matter endpoint projections of abnormal fibers to map the anatomical pattern of disconnections. As expected, left- and right-TLE were associated with multiple WM pathways with reduced integrity, which were associated with extensive cortical disconnection involving predominantly limbic structures. Controlling for medial temporal gray matter atrophy, cortical disconnection of the left cingulum and the thalamus as well as disconnection of the bilateral putamen and the amygdala was associated with lower verbal memory immediate recall. In conclusion, our results support that cortical disconnection is an underappreciated but pervasive phenomenon in TLE, and cortical disconnection of limbic structures beyond the medial temporal regions is related to verbal memory performance.

Brain network hubs and cognitive performance of survivors of childhood infratentorial tumors

BACKGROUND

Childhood infratentorial tumor patients frequently suffer from long-term cognitive deficits. As each constituent of their treatment can lead to neurotoxicity, cascade effects can lead to profound reorganization of the underlying brain network, the so-called 'connectome'. However, to date, few studies have assessed the relationship between brain network topology, the functional role of network hubs (i.e. highly connected regions), and neurocognitive outcomes in adult survivors of childhood infratentorial tumors.

METHODS

In this cross-sectional study, childhood infratentorial tumor survivors (n = 21: pilocytic astrocytoma (n = 8), ependymoma (n = 1) and medulloblastoma (n = 12)) and healthy controls (n = 21) were recruited. Using multishell diffusion-weighted MRI, microstructural organization and topology of supratentorial white matter was investigated; using a voxel-based approach, a fixel-based analysis, and a graph theoretical approach. In addition, neurocognitive subscales of the WAIS-IV intelligence test, and their relationship with nodal strength and network efficiency metrics were assessed.

RESULTS

Similar to earlier studies, we observed widespread decreases in fractional anisotropy (FA) in patients compared to controls, based on voxel-based analyses. In addition, the fixel-based analyses dissociated macro- from microstructural changes, which were encountered in in infratentorial versus supratentorial brain areas, respectively. Finally, regional reorganization (i.e. differences in local efficiency) occurred mainly in hubs, which suggests a specific vulnerability of these areas. These hubs were not only mostly affected, but also most strongly correlated with the intelligence subscales.

CONCLUSION

This study suggests that network hubs are functionally important for intellectual outcomes in infratentorial tumor survivors. Furthermore, these regions could be the primary targets of treatment toxicity. Validation of this specific hypothesis in larger samples is required.

White matter network of oral word reading identified by network-based lesion-symptom mapping

Oral word reading is supported by a neural subnetwork that includes gray matter regions and white matter tracts connected by the regions. Traditional methods typically determine the reading-relevant focal gray matter regions or white matter tracts rather than the reading-relevant global subnetwork. The present study developed a network-based lesion-symptom mapping (NLSM) method to identify the reading-relevant global white matter subnetwork in 84 brain-damaged patients. The global subnetwork was selected among all possible subnetworks because its global efficiency exhibited the best explanatory power for patients' reading scores. This reading subnetwork was left lateralized and included 7 gray matter regions and 15 white matter tracts. Moreover, the reading subnetwork had additional explanatory power for the patients' reading performance after eliminating the effects of reading-related local regions and tracts. These findings refine the reading neuroanatomical architecture and indicate that the NLSM can be a better method for revealing behavior-specific subnetworks.

Mechanisms Underlying Disorders of Consciousness: Bridging Gaps to Move Toward an Integrated Translational Science

Aim

In order to successfully detect, classify, prognosticate, and develop targeted therapies for patients with disorders of consciousness (DOC), it is crucial to improve our mechanistic understanding of how severe brain injuries result in these disorders.

Methods

To address this need, the Curing Coma Campaign convened a Mechanisms Sub-Group of the Coma Science Work Group (CSWG), aiming to identify the most pressing knowledge gaps and the most promising approaches to bridge them.

Results

We identified a key conceptual gap in the need to differentiate the neural mechanisms of consciousness per se, from those underpinning connectedness to the environment and behavioral responsiveness. Further, we characterised three fundamental gaps in DOC research: (1) a lack of mechanistic integration between structural brain damage and abnormal brain function in DOC; (2) a lack of translational bridges between micro- and macro-scale neural phenomena; and (3) an incomplete exploration of possible synergies between data-driven and theory-driven approaches.

Conclusion

In this white paper, we discuss research priorities that would enable us to begin to close these knowledge gaps. We propose that a fundamental step towards this goal will be to combine translational, multi-scale, and multimodal data, with new biomarkers, theory-driven approaches, and computational models, to produce an integrated account of neural mechanisms in DOC. Importantly, we envision that reciprocal interaction between domains will establish a “virtuous cycle,” leading towards a critical vantage point of integrated knowledge that will enable the advancement of the scientific understanding of DOC and consequently, an improvement of clinical practice.

A data-driven approach to post-stroke aphasia classification and lesion-based prediction

Aphasia is an acquired impairment in the production or comprehension of language, typically caused by left hemisphere stroke. The subtyping framework used in clinical aphasiology today is based on the Wernicke-Lichtheim model of aphasia formulated in the late 19th century, which emphasizes the distinction between language production and comprehension. The current study used a data-driven approach that combined modern statistical, machine learning, and neuroimaging tools to examine behavioural deficit profiles and their lesion correlates and predictors in a large cohort of individuals with post-stroke aphasia. First, individuals with aphasia were clustered based on their behavioural deficit profiles using community detection analysis (CDA) and these clusters were compared with the traditional aphasia subtypes. Random forest classifiers were built to evaluate how well individual lesion profiles predict cluster membership. The results of the CDA analyses did not align with the traditional model of aphasia in either behavioural or neuroanatomical patterns. Instead, the results suggested that the primary distinction in aphasia (after severity) is between phonological and semantic processing rather than between production and comprehension. Further, lesion-based classification reached 75% accuracy for the CDA-based categories and only 60% for categories based on the traditional fluent/non-fluent aphasia distinction. The results of this study provide a data-driven basis for a new approach to classification of post-stroke aphasia subtypes in both research and clinical settings.

Grey and white matter network disruption is associated with sensory deficits after stroke

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Somatosensory deficits occur in about 60% of patients after ischaemic stroke.

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Clinical and imaging data of 101 ischaemic stroke patients were analysed.

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Stroke lesions may disrupt grey (GM) and/or white matter (WM) network.

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Lesion volume explains 23% of sensory deficit variance; GM / WM disruption adds 14%

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Subnetwork of postcentral, supramarginal, transverse temporal gyri involved.

Somatosensory deficits after ischaemic stroke are common and can occur in patients with lesions in the anterior parietal cortex and subcortical nuclei. It is less clear to what extent damage to white matter tracts within the somatosensory system may contribute to somatosensory deficits after stroke. We compared the roles of cortical damage and disruption of subcortical white matter tracts as correlates of somatosensory deficit after ischaemic stroke.

Clinical and imaging data were assessed in incident stroke patients. Somatosensory deficits were measured using a standardized somatosensory test. Remote effects were quantified by projecting the MRI-based segmented stroke lesions onto a predefined atlas of white matter connectivity. Direct ischaemic damage to grey matter was computed by lesion overlap with grey matter areas. The association between lesion impact scores and sensory deficit was assessed statistically.

In 101 patients, median sensory score was 188/193 (97.4%). Lesion volume was associated with somatosensory deficit, explaining 23.3% of variance. Beyond this, the stroke-induced grey and white matter disruption within a subnetwork of the postcentral, supramarginal, and transverse temporal gyri explained an additional 14% of the somatosensory outcome variability. On mutual comparison, white matter network disruption was a stronger predictor than grey matter damage.

Ischaemic damage to both grey and white matter are structural correlates of acute somatosensory disturbance after ischaemic stroke. Our data suggest that white matter integrity of a somatosensory network of primary and secondary cortex is a prerequisite for normal processing of somatosensory inputs and might be considered as an additional parameter for stroke outcome prediction in the future.

A connectome-based approach to assess motor outcome after neonatal arterial ischemic stroke

Objective

Studies of motor outcome after Neonatal Arterial Ischemic Stroke (NAIS) often rely on lesion mapping using MRI. However, clinical measurements indicate that motor deficit can be different than what would solely be anticipated by the lesion extent and location. Because this may be explained by the cortical disconnections between motor areas due to necrosis following the stroke, the investigation of the motor network can help in the understanding of visual inspection and outcome discrepancy. In this study, we propose to examine the structural connectivity between motor areas in NAIS patients compared to healthy controls in order to define the cortical and subcortical connections that can reflect the motor outcome.

Methods

Thirty healthy controls and 32 NAIS patients with and without Cerebral Palsy (CP) underwent MRI acquisition and manual assessment. The connectome of all participants was obtained from T1‐weighted and diffusion‐weighted imaging.

Results

Significant disconnections in the lesioned and contra‐lesioned hemispheres of patients were found. Furthermore, significant correlations were detected between the structural connectivity metric of specific motor areas and manuality assessed by the Box and Block Test (BBT) scores in patients.

Interpretation

Using the connectivity measures of these links, the BBT score can be estimated using a multiple linear regression model. In addition, the presence or not of CP can also be predicted using the KNN classification algorithm. According to our results, the structural connectome can be an asset in the estimation of gross manual dexterity and can help uncover structural changes between brain regions related to NAIS.

Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions

Lesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brain's structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions.

Damage to the structural connectome reflected in resting-state fMRI functional connectivity

The relationship between structural and functional connectivity has been mostly examined in intact brains. Fewer studies have examined how differences in structure as a result of injury alters function. In this study we analyzed the relationship of structure to function across patients with stroke among whom infarcts caused heterogenous structural damage. We estimated relationships between distinct brain regions of interest (ROIs) from functional MRI in two pipelines. In one analysis pipeline, we measured functional connectivity by using correlation and partial correlation between 114 cortical ROIs. We found fMRI-BOLD partial correlation was altered at more edges as a function of the structural connectome (SC) damage, relative to the correlation. In a second analysis pipeline, we limited our analysis to fMRI correlations between pairs of voxels for which we possess SC information. We found that voxel-level functional connectivity showed the effect of structural damage that we could not see when examining correlations between ROIs. Further, the effects of structural damage on functional connectivity are consistent with a model of functional connectivity, diffusion, which expects functional connectivity to result from activity spreading over multiple edge anatomical paths.

Neural substrates of subcortical aphasia in subacute stroke: Voxel-based lesion symptom mapping study

Subcortical aphasia develops as a result of damage to subcortical brain areas without loss of cortical functions. Although earlier voxel-based lesion-symptom mapping (VLSM) studies have shown possible neural correlates for aphasia, it remains to be clarified which brain regions are associated with subcortical aphasia. The aim of this study was to investigate the neural substrates associated with subcortical aphasia in patients with stroke using VLSM and atlas-based analyses to explore the involvement of white matter tracts and subcortical structures. Fifty patients with subacute subcortical stroke without cortical involvement were retrospectively enrolled: 24 with and 26 without aphasia. We performed VLSM and atlas-based analyses of the patients' fluid-attenuated inversion recovery images and found that the left perisylvian white matter, left fronto-occipital fasciculus, uncinate fasciculus, and forceps minor were significantly more greatly affected in the aphasia than in the non-aphasia group. The left anterior thalamic radiation, cingulum (cingulate gyrus), and superior longitudinal fasciculus also showed higher involvement in this group (marginal significance). Among the subcortical regions, the left caudate and putamen were more greatly involved in the aphasia group. Our findings confirm language processing as one of the integrated sensory-motor processes that occur in the region around the left sylvian fissure. Our atlas-based analysis approach can be used to complement VLSM analyses.

Rapid Quantification of White Matter Disconnection in the Human Brain

With an estimated five million new stroke survivors every year and a rapidly aging population suffering from hyperintensities and diseases of presumed vascular origin that affect white matter and contribute to cognitive decline, it is critical that we understand the impact of white matter damage on brain structure and behavior. Current techniques for assessing the impact of lesions consider only location, type, and extent, while ignoring how the affected region was connected to the rest of the brain. Regional brain function is a product of both local structure and its connectivity. Therefore, obtaining a map of white matter disconnection is a crucial step that could help us predict the behavioral deficits that patients exhibit. In the present work, we introduce a new practical method for computing lesion-based white matter disconnection maps that require only moderate computational resources. We achieve this by creating diffusion tractography models of the brains of healthy adults and assessing the connectivity between small regions. We then interrupt these connectivity models by projecting patients' lesions into them to compute predicted white matter disconnection. A quantified disconnection map can be computed for an individual patient in approximately 35 seconds using a single core CPU-based computation. In comparison, a similar quantification performed with other tools provided by MRtrix3 takes 5.47 minutes.