Human brain lesion-deficit inference remapped

GeoSPM: Geostatistical parametric mapping for medicine

The characteristics and determinants of health and disease are often organized in space, reflecting our spatially extended nature. Understanding the influence of such factors requires models capable of capturing spatial relations. Drawing on statistical parametric mapping, a framework for topological inference well established in the realm of neuroimaging, we propose and validate an approach to the spatial analysis of diverse clinical data-GeoSPM-based on differential geometry and random field theory. We evaluate GeoSPM across an extensive array of synthetic simulations encompassing diverse spatial relationships, sampling, and corruption by noise, and demonstrate its application on large-scale data from UK Biobank. GeoSPM is readily interpretable, can be implemented with ease by non-specialists, enables flexible modeling of complex spatial relations, exhibits robustness to noise and under-sampling, offers principled criteria of statistical significance, and is through computational efficiency readily scalable to large datasets. We provide a complete, open-source software implementation.

Structural disconnection-based prediction of poststroke depression

Poststroke depression (PSD) is a common complication of stroke. Brain network disruptions caused by stroke are potential biological determinants of PSD but their conclusive roles are unavailable. Our study aimed to identify the strategic structural disconnection (SDC) pattern for PSD at three months poststroke and assess the predictive value of SDC information. Our prospective cohort of 697 first-ever acute ischemic stroke patients were recruited from three hospitals in central China. Sociodemographic, clinical, psychological and neuroimaging data were collected at baseline and depression status was assessed at three months poststroke. Voxel-based disconnection-symptom mapping found that SDCs involving bilateral temporal white matter and posterior corpus callosum, as well as white matter next to bilateral prefrontal cortex and posterior parietal cortex, were associated with PSD. This PSD-specific SDC pattern was used to derive SDC scores for all participants. SDC score was an independent predictor of PSD after adjusting for all imaging and clinical-sociodemographic-psychological covariates (odds ratio, 1.25; 95% confidence interval, 1.07, 1.48; P = 0.006). Split-half replication showed the stability and generalizability of above results. When added to the clinical-sociodemographic-psychological prediction model, SDC score significantly improved the model performance and ranked the highest in terms of predictor importance. In conclusion, a strategic SDC pattern involving multiple lobes bilaterally is identified for PSD at 3 months poststroke. The SDC score is an independent predictor of PSD and may improve the predictive performance of the clinical-sociodemographic-psychological prediction model, providing new evidence for the brain-behavior mechanism and biopsychosocial theory of PSD.

Network-level prediction of set-shifting deterioration after lower-grade glioma resection

OBJECTIVE

The aim of this study was to predict set-shifting deterioration after resection of low-grade glioma.

METHODS

The authors retrospectively analyzed a bicentric series of 102 patients who underwent surgery for low-grade glioma. The difference between the completion times of the Trail Making Test parts B and A (TMT B-A) was evaluated preoperatively and 3-4 months after surgery. High dimensionality of the information related to the surgical cavity topography was reduced to a small set of predictors in four different ways: 1) overlap between surgical cavity and each of the 122 cortical parcels composing Yeo's 17-network parcellation of the brain; 2) Tractotron: disconnection by the cavity of the major white matter bundles; 3) overlap between the surgical cavity and each of Yeo's networks; and 4) disconets: signature of structural disconnection by the cavity of each of Yeo's networks. A random forest algorithm was implemented to predict the postoperative change in the TMT B-A z-score.

RESULTS

The last two network-based approaches yielded significant accuracies in left-out subjects (area under the receiver operating characteristic curve [AUC] approximately equal to 0.8, p approximately equal to 0.001) and outperformed the two alternatives. In single tree hierarchical models, the degree of damage to Yeo corticocortical network 12 (CC 12) was a critical node: patients with damage to CC 12 higher than 7.5% (cortical overlap) or 7.2% (disconets) had much higher risk to deteriorate, establishing for the first time a causal link between damage to this network and impaired set-shifting.

CONCLUSIONS

The authors' results give strong support to the idea that network-level approaches are a powerful way to address the lesion-symptom mapping problem, enabling machine learning-powered individual outcome predictions.

Structural disconnections associated with language impairments in chronic post-stroke aphasia using disconnectome maps

Inconsistent findings have been reported about the impact of structural disconnections on language function in post-stroke aphasia. This study investigated patterns of structural disconnections associated with chronic language impairments using disconnectome maps. Seventy-six individuals with post-stroke aphasia underwent a battery of language assessments and a structural MRI scan. Support-vector regression disconnectome-symptom mapping analyses were performed to examine the correlations between disconnectome maps, representing the probability of disconnection at each white matter voxel and different language scores. To further understand whether significant disconnections were primarily representing focal damage or a more extended network of seemingly preserved but disconnected areas beyond the lesion site, results were qualitatively compared to support-vector regression lesion-symptom mapping analyses. Part of the left white matter perisylvian network was similarly disconnected in 90% of the individuals with aphasia. Surrounding this common left perisylvian disconnectome, specific structural disconnections in the left fronto-temporo-parietal network were significantly associated with aphasia severity and with lower performance in auditory comprehension, syntactic comprehension, syntactic production, repetition and naming tasks. Auditory comprehension, repetition and syntactic processing deficits were related to disconnections in areas that overlapped with and extended beyond lesion sites significant in SVR-LSM analyses. In contrast, overall language abilities as measured by aphasia severity and naming seemed to be mostly explained by focal damage at the level of the insular and central opercular cortices, given the high overlap between SVR-DSM and SVR-LSM results for these scores. While focal damage seems to be sufficient to explain broad measures of language performance, the structural disconnections between language areas provide additional information on the neural basis of specific and persistent language impairments at the chronic stage beyond lesion volume. Leveraging routinely available clinical data, disconnectome mapping furthers our understanding of anatomical connectivity constraints that may limit the recovery of some language abilities in chronic post-stroke aphasia.

Efficient and effective assessment of deficits and their neural bases in stroke aphasia

OBJECTIVE

Multi-assessment batteries are necessary for diagnosing and quantifying the multifaceted deficits observed post-stroke. Extensive batteries are thorough but impractically long for clinical settings or large-scale research studies. Clinically-targeted "shallow" batteries superficially cover a wide range of language skills relatively quickly but can struggle to identify mild deficits or quantify the impairment level. Our aim was to compare these batteries across a large group of chronic stroke aphasia and to test a novel data-driven reduced version of an extensive battery that maintained sensitivity to mild impairment, ability to grade deficits and the underlying component structure.

METHODS

We tested 75 chronic left-sided stroke participants, spanning global to mild aphasia. The underlying structure of these three batteries was analysed using cross-validation and principal component analysis, in addition to univariate and multivariate lesion-symptom mapping.

RESULTS

This revealed a four-factor solution for the extensive and data-reduced batteries, identifying phonology, semantic skills, fluency and executive function in contrast to a two-factor solution using the shallow battery (language severity and cognitive severity). Lesion symptom mapping using participants' factor scores identified convergent neural structures for phonology (superior temporal gyrus), semantics (inferior temporal gyrus), speech fluency (precentral gyrus) and executive function (lateral occipitotemporal cortex). The two shallow battery components converged with the phonology and executive function clusters. In addition, we show that multivariate models could predict the component scores using neural data, however not for every component.

CONCLUSIONS

Overall, the data-driven battery appears to be an effective way to save time yet retain maintained sensitivity to mild impairment, ability to grade deficits and the underlying component structure observed in post-stroke aphasia.

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.

fMRI informed voxel-based lesion analysis to identify lesions associated with right-hemispheric activation in aphasia recovery

Several mechanisms have been attributed to post-stroke loss and recovery of language functions. However, the significance and timing of domain-general and homotopic right-hemispheric activation is controversial. We aimed to examine the effect of left-hemispheric lesion location and time post-stroke on right-hemispheric activation. Voxel-based lesion analyses were informed by auditory language-related fMRI activation of 71 patients with left middle cerebral artery stroke examined longitudinally in the acute, subacute and early chronic phase. Language activation was determined in several right-hemispheric regions of interest and served as regressor of interest for voxel-based lesion analyses. We found that an acute to chronic increase of language activation in the right supplementary motor area was associated with lesions to the left extreme capsule as part of the ventral language pathway. Importantly, this activation increase correlated significantly with improvement of out-of-scanner comprehension abilities. We interpret our findings in terms of successful domain-general compensation in patients with critical left frontotemporal disconnection due to damage to the ventral language pathway but relatively spared cortical language areas.

Mapping correlated neurological deficits after stroke to distributed brain networks

Understanding the relationships between brain organization and behavior is a central goal of neuroscience. Traditional teaching emphasizes that the human cerebrum includes many distinct areas for which damage or dysfunction would lead to a unique and specific behavioral syndrome. This teaching implies that brain areas correspond to encapsulated modules that are specialized for specific cognitive operations. However, empirically, local damage from stroke more often produces one of a small number of clusters of deficits and disrupts brain-wide connectivity in a small number of predictable ways (relative to the vast complexity of behavior and brain connectivity). Behaviors that involve shared operations show correlated deficits following a stroke, consistent with a low-dimensional behavioral space. Because of the networked organization of the brain, local damage from a stroke can result in widespread functional abnormalities, matching the low dimensionality of behavioral deficit. In alignment with this, neurological disease, psychiatric disease, and altered brain states produce behavioral changes that are highly correlated across a range of behaviors. We discuss how known structural and functional network priors in addition to graph theoretical concepts such as modularity and entropy have provided inroads to understanding this more complex relationship between brain and behavior. This model for brain disease has important implications for normal brain-behavior relationships and the treatment of neurological and psychiatric diseases.

Academic skills after brain injury: A lifespan perspective

OBJECTIVES

This study investigated academic skills outcomes after brain injury and identified the influence of age and injury factors across the lifespan.

METHOD

Our sample included 651 participants with focal brain lesions. Math, reading, and spelling data from the Wide Range Achievement Test (WRAT) were used as the academic skills outcomes. Age of lesion onset ranged from 0 to 85 years old. Linear regressions were conducted to identify the relation between age and injury factors and academic skills outcomes. Lesion-symptom mapping was conducted to identify the brain areas that, when lesioned, were associated with deficits in academic skills.

RESULTS

A quadratic model of age of lesion onset significantly predicted math (R² = .28, p < .001), reading (R² = .29, p < .001), and spelling outcomes (R² = .32, p < .001), while accounting for various covariates. Education, sex, lesion size and laterality, etiology, and seizure history were additional reliable predictors of academic skills outcomes across the lifespan. Academic skill deficits were associated with damage to various brain areas across the left-hemisphere frontal, temporal, and parietal lobes, the insular area, and left- and right-hemisphere white matter.

CONCLUSIONS

This study supports age of lesion onset as a relevant predictor of academic skills after brain injury in a lifespan sample. Several other variables (e.g., education, sex, lesion characteristics, and seizure history) are notable in the prediction of outcomes across the lifespan. Future work could investigate more diverse samples and emphasize recruitment of early onset injuries to examine generalizability and potential critical periods for academic skills. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Systematic perturbation of an artificial neural network: A step towards quantifying causal contributions in the brain

Lesion inference analysis is a fundamental approach for characterizing the causal contributions of neural elements to brain function. This approach has gained new prominence through the arrival of modern perturbation techniques with unprecedented levels of spatiotemporal precision. While inferences drawn from brain perturbations are conceptually powerful, they face methodological difficulties. Particularly, they are challenged to disentangle the true causal contributions of the involved elements, since often functions arise from coalitions of distributed, interacting elements, and localized perturbations have unknown global consequences. To elucidate these limitations, we systematically and exhaustively lesioned a small artificial neural network (ANN) playing a classic arcade game. We determined the functional contributions of all nodes and links, contrasting results from sequential single-element perturbations with simultaneous perturbations of multiple elements. We found that lesioning individual elements, one at a time, produced biased results. By contrast, multi-site lesion analysis captured crucial details that were missed by single-site lesions. We conclude that even small and seemingly simple ANNs show surprising complexity that needs to be addressed by multi-lesioning for a coherent causal characterization.

Post-stroke outcomes predicted from multivariate lesion-behaviour and lesion network mapping

Clinicians and scientists alike have long sought to predict the course and severity of chronic post-stroke cognitive and motor outcomes, as the ability to do so would inform treatment and rehabilitation strategies. However, it remains difficult to make accurate predictions about chronic post-stroke outcomes due, in large part, to high inter-individual variability in recovery and a reliance on clinical heuristics rather than empirical methods. The neuroanatomical location of a stroke is a key variable associated with long-term outcomes, and because lesion location can be derived from routinely collected clinical neuroimaging data there is an opportunity to use this information to make empirically based predictions about post-stroke deficits. For example, lesion location can be compared to statistically weighted multivariate lesion-behaviour maps of neuroanatomical regions that, when damaged, are associated with specific deficits based on aggregated outcome data from large cohorts. Here, our goal was to evaluate whether we can leverage lesion-behaviour maps based on data from two large cohorts of individuals with focal brain lesions to make predictions of 12-month cognitive and motor outcomes in an independent sample of stroke patients. Further, we evaluated whether we could augment these predictions by estimating the structural and functional networks disrupted in association with each lesion-behaviour map through the use of structural and functional lesion network mapping, which use normative structural and functional connectivity data from neurologically healthy individuals to elucidate lesion-associated networks. We derived these brain network maps using the anatomical regions with the strongest association with impairment for each cognitive and motor outcome based on lesion-behaviour map results. These peak regional findings became the 'seeds' to generate networks, an approach that offers potentially greater precision compared to previously used single-lesion approaches. Next, in an independent sample, we quantified the overlap of each lesion location with the lesion-behaviour maps and structural and functional lesion network mapping and evaluated how much variance each could explain in 12-month behavioural outcomes using a latent growth curve statistical model. We found that each lesion-deficit mapping modality was able to predict a statistically significant amount of variance in cognitive and motor outcomes. Both structural and functional lesion network maps were able to predict variance in 12-month outcomes beyond lesion-behaviour mapping. Functional lesion network mapping performed best for the prediction of language deficits, and structural lesion network mapping performed best for the prediction of motor deficits. Altogether, these results support the notion that lesion location and lesion network mapping can be combined to improve the prediction of post-stroke deficits at 12-months.

Of networked lesions and lesioned networks

This scientific commentary refers to ‘Post-stroke outcomes predicted from multivariate lesion-behaviour and lesion network mapping’ by Bowren et al. (https://doi.org/10.1093/brain/awac010).

Structure and function of language networks in temporal lobe epilepsy

Individuals with temporal lobe epilepsy (TLE) may have significant language deficits. Language capabilities may further decline following temporal lobe resections. The language network, comprising dispersed gray matter regions interconnected with white matter fibers, may be atypical in individuals with TLE. This review explores the structural changes to the language network and the functional reorganization of language abilities in TLE. We discuss the importance of detailed reporting of patient's characteristics, such as, left- and right-sided focal epilepsies as well as lesional and nonlesional pathological subtypes. These factors can affect the healthy functioning of gray and/or white matter. Dysfunction of white matter and displacement of gray matter function could concurrently impact their ability, in turn, producing an interactive effect on typical language organization and function. Surgical intervention can result in impairment of function if the resection includes parts of this structure-function network that are critical to language. In addition, impairment may occur if language function has been reorganized and is included in a resection. Conversely, resection of an epileptogenic zone may be associated with recovery of cortical function and thus improvement in language function. We explore the abnormality of functional regions in a clinically applicable framework and highlight the differences in the underlying language network. Avoidance of language decline following surgical intervention may depend on tailored resections to avoid critical areas of gray matter and their white matter connections. Further work is required to elucidate the plasticity of the language network in TLE and to identify sub-types of language representation, both of which will be useful in planning surgery to spare language function.

Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence

Stroke ranks among the leading causes for morbidity and mortality worldwide. New and continuously improving treatment options such as thrombolysis and thrombectomy have revolutionized acute stroke treatment in recent years. Following modern rhythms, the next revolution might well be the strategic use of the steadily increasing amounts of patient-related data for generating models enabling individualized outcome predictions. Milestones have already been achieved in several health care domains, as big data and artificial intelligence have entered everyday life. The aim of this review is to synoptically illustrate and discuss how artificial intelligence approaches may help to compute single-patient predictions in stroke outcome research in the acute, subacute and chronic stage. We will present approaches considering demographic, clinical and electrophysiological data, as well as data originating from various imaging modalities and combinations thereof. We will outline their advantages, disadvantages, their potential pitfalls and the promises they hold with a special focus on a clinical audience. Throughout the review we will highlight methodological aspects of novel machine-learning approaches as they are particularly crucial to realize precision medicine. We will finally provide an outlook on how artificial intelligence approaches might contribute to enhancing favourable outcomes after stroke.

Neural Substrates of Poststroke Depression: Current Opinions and Methodology Trends

Poststroke depression (PSD), affecting about one-third of stroke survivors, exerts significant impact on patients’ functional outcome and mortality. Great efforts have been made since the 1970s to unravel the neuroanatomical substrate and the brain-behavior mechanism of PSD. Thanks to advances in neuroimaging and computational neuroscience in the past two decades, new techniques for uncovering the neural basis of symptoms or behavioral deficits caused by focal brain damage have been emerging. From the time of lesion analysis to the era of brain networks, our knowledge and understanding of the neural substrates for PSD are increasing. Pooled evidence from traditional lesion analysis, univariate or multivariate lesion-symptom mapping, regional structural and functional analyses, direct or indirect connectome analysis, and neuromodulation clinical trials for PSD, to some extent, echoes the frontal-limbic theory of depression. The neural substrates of PSD may be used for risk stratification and personalized therapeutic target identification in the future. In this review, we provide an update on the recent advances about the neural basis of PSD with the clinical implications and trends of methodology as the main features of interest.

Subcortical Cognition: The Fruit Below the Rind

Cognitive neuroscience has highlighted the cerebral cortex while often overlooking subcortical structures. This cortical proclivity is found in basic and translational research on many aspects of cognition, especially higher cognitive domains such as language, reading, music, and math. We suggest that, for both anatomical and evolutionary reasons, multiple subcortical structures play substantial roles across higher and lower cognition. We present a comprehensive review of existing evidence, which indeed reveals extensive subcortical contributions in multiple cognitive domains. We argue that the findings are overall both real and important. Next, we advance a theoretical framework to capture the nature of (sub)cortical contributions to cognition. Finally, we propose how new subcortical cognitive roles can be identified by leveraging anatomical and evolutionary principles, and we describe specific methods that can be used to reveal subcortical cognition. Altogether, this review aims to advance cognitive neuroscience by highlighting subcortical cognition and facilitating its future investigation. Expected final online publication date for the Annual Review of Neuroscience, Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Functional differentiation in the language network revealed by lesion-symptom mapping

Theories of language organization in the brain commonly posit that different regions underlie distinct linguistic mechanisms. However, such theories have been criticized on the grounds that many neuroimaging studies of language processing find similar effects across regions. Moreover, condition by region interaction effects, which provide the strongest evidence of functional differentiation between regions, have rarely been offered in support of these theories. Here we address this by using lesion-symptom mapping in three large, partially-overlapping groups of aphasia patients with left hemisphere brain damage due to stroke (N = 121, N = 92, N = 218). We identified multiple measure by region interaction effects, associating damage to the posterior middle temporal gyrus with syntactic comprehension deficits, damage to posterior inferior frontal gyrus with expressive agrammatism, and damage to inferior angular gyrus with semantic category word fluency deficits. Our results are inconsistent with recent hypotheses that regions of the language network are undifferentiated with respect to high-level linguistic processing.

Controversy over the temporal cortical terminations of the left arcuate fasciculus: a reappraisal

The arcuate fasciculus has been considered a major dorsal fronto-temporal white matter pathway linking frontal language production regions with auditory perception in the superior temporal gyrus, the so-called Wernicke's area. In line with this tradition, both historical and contemporary models of language function have assigned primacy to superior temporal projections of the arcuate fasciculus. However, classical anatomical descriptions and emerging behavioural data are at odds with this assumption. On one hand, fronto-temporal projections to Wernicke's area may not be unique to the arcuate fasciculus. On the other hand, dorsal stream language deficits have been reported also for damage to middle, inferior and basal temporal gyri which may be linked to arcuate disconnection. These findings point to a reappraisal of arcuate projections in the temporal lobe. Here, we review anatomical and functional evidence regarding the temporal cortical terminations of the left arcuate fasciculus by incorporating dissection and tractography findings with stimulation data using cortico-cortical evoked potentials and direct electrical stimulation mapping in awake patients. Firstly, we discuss the fibers of the arcuate fasciculus projecting to the superior temporal gyrus and the functional rostro-caudal gradient in this region where both phonological encoding and auditory-motor transformation may be performed. Caudal regions within the temporoparietal junction may be involved in articulation and associated with temporoparietal projections of the third branch of the superior longitudinal fasciculus, while more rostral regions may support encoding of acoustic phonetic features, supported by arcuate fibres. We then move to examine clinical data showing that multimodal phonological encoding is facilitated by projections of the arcuate fasciculus to superior, but also middle, inferior and basal temporal regions. Hence, we discuss how projections of the arcuate fasciculus may contribute to acoustic (middle-posterior superior and middle temporal gyri), visual (posterior inferior temporal/fusiform gyri comprising the visual word form area) and lexical (anterior-middle inferior temporal/fusiform gyri in the basal temporal language area) information in the temporal lobe to be processed, encoded and translated into a dorsal phonological route to the frontal lobe. Finally, we point out surgical implications for this model in terms of the prediction and avoidance of neurological deficit.

Contribution of the medial eye field network to the voluntary deployment of visuospatial attention

Historically, the study of patients with spatial neglect has provided fundamental insights into the neural basis of spatial attention. However, lesion mapping studies have been unsuccessful in establishing the potential role of associative networks spreading on the dorsal-medial axis, mainly because they are uncommonly targeted by vascular injuries. Here we combine machine learning-based lesion-symptom mapping, disconnection analyses and the longitudinal behavioral data of 128 patients with well-delineated surgical resections. The analyses show that surgical resections in a location compatible with both the supplementary and the cingulate eye fields, and disrupting the dorsal-medial fiber network, are specifically associated with severely diminished performance on a visual search task (i.e., visuo-motor exploratory neglect) with intact performance on a task probing the perceptual component of neglect. This general finding provides causal evidence for a role of the frontal-medial network in the voluntary deployment of visuo-spatial attention.

Lesion symptom mapping of domain-specific cognitive impairments using routine imaging in stroke

INTRODUCTION

This large-scale lesion-symptom mapping study investigates the necessary neuro-anatomical substrates of 5 cognitive domains frequently affected post stroke: Language, Attention, Praxis, Number, and Memory. This study aims to demonstrate the validity of using routine clinical brain imaging and standard bedside cognitive screening data from a large, real-world patient cohort for lesion-symptom mapping.

PATIENTS AND METHODS

Behavioural cognitive screening data from the Oxford Cognitive Screen and routine clinical neuroimaging from 573 acute patients was used in voxel-based lesion-symptom mapping analyses. Patients were classed as impaired or not on each of the subtests within 5 cognitive domains.

RESULTS

Distinct patterns of lesion damage were associated with different domains. Language functions were associated with damage to left hemisphere fronto-temporal areas. Visuo-spatial functions were associated with damage to posterior occipital areas (Visual Field) and the right temporo-parietal region (Visual Neglect). Different memory impairments were linked to distinct voxel clusters within the left insular and opercular cortices. Deficits which were not associated with localised voxels (e.g. executive function, praxis) represent distributed, bilateral functions.

DISCUSSION

The standardised, brief Oxford Cognitive Screen was able to reliably differentiate distinct neural correlates critically involved in supporting domain-specific cognitive abilities.

CONCLUSION

By demonstrating and replicating known brain anatomy correlates within real-life clinical cohorts using routinely collected scans and standard bedside screens, we open up VLSM techniques to a wealth of clinically relevant studies which can capitalise on using existing clinical data.

Mapping the human praxis network: an investigation of white matter disconnection in limb apraxia of gesture production

Left hemispheric cerebral stroke can cause apraxia, a motor cognitive disorder characterized by deficits of higher-order motor skills such as the failure to accurately produce meaningful gestures. This disorder provides unique insights into the anatomical and cognitive architecture of the human praxis system. The present study aimed to map the structural brain network that is damaged in apraxia. We assessed the ability to perform meaningful gestures with the hand in 101 patients with chronic left hemisphere stroke. Structural white matter fibre damage was directly assessed by diffusion tensor imaging and fractional anisotropy mapping. We used multivariate topographical inference on tract-based fractional anisotropy topographies to identify white matter disconnection associated with apraxia. We found relevant pathological white matter alterations in a densely connected fronto-temporo-parietal network of short and long association fibres. Hence, the findings suggest that heterogeneous topographical results in previous lesion mapping studies might not only result from differences in study design, but also from the general methodological limitations of univariate topographical mapping in uncovering the structural praxis network. A striking role of middle and superior temporal lobe disconnection, including temporo-temporal short association fibres, was found, suggesting strong involvement of the temporal lobe in the praxis network. Further, the results stressed the importance of subcortical disconnections for the emergence of apractic symptoms. Our study provides a fine-grain view into the structural connectivity of the human praxis network and suggests a potential value of disconnection measures in the clinical prediction of behavioural post-stroke outcome.

Neonatal arterial stroke location is associated with outcome at 2 years: a voxel-based lesion-symptom mapping study

OBJECTIVE

In contrast to motor impairments, the association between lesion location and cognitive or language deficits in patients with neonatal arterial ischaemic stroke remains largely unknown. We conducted a voxel-based lesion-symptom mapping cross-sectional study aiming to reveal neonatal arterial stroke location correlates of language, motor and cognitive outcomes at 2 years of age.

DESIGN

Prospective observational multicentre study.

SETTING

Six paediatric university hospitals in Spain.

PARTICIPANTS

We included 53 patients who had a neonatal arterial ischaemic stroke with neonatal MRI and who were followed up till 2 years of age.

MAIN OUTCOME MEASURES

We analysed five dichotomous clinical variables: speech therapy (defined as the need for speech therapy as established by therapists), gross motor function impairment, and the language, motor and cognitive Bayley scales. All the analyses were controlled for total lesion volume.

RESULTS

We found that three of the clinical variables analysed significantly correlated with neonatal stroke location. Speech therapy was associated with lesions located mainly at the left supramarginal gyrus (p=0.007), gross motor function impairment correlated with lesions at the left external capsule (p=0.044) and cognitive impairment was associated with frontal lesions, particularly located at the left inferior and middle frontal gyri (p=0.012).

CONCLUSIONS

The identification of these susceptible brain areas will allow for more precise prediction of neurological impairments on the basis of neonatal brain MRI.

Voxelwise structural disconnection mapping: Methodological validation and recommendations

Voxelwise disconnection mapping is a novel approach to disclose lesion-symptom relationships for symptoms caused by white matter disconnection. It uses MRI-based fiber tracking in healthy subjects seeded from patient’s focal brain lesions. Resulting individual disconnection maps can then be statistically associated with symptoms. Despite increasing use in the recent years, the validity of this approach remains to be investigated. In this study, we validated both, our own implementation and the implementation provided within BCBtoolkit. For technical validation, we used simulated symptoms based on overlap of 70 real stroke lesions with tracts from a white matter atlas. For clinical validation, paresis scores and lesions from 316 patients with stroke were used. We found that voxelwise disconnection mapping is technically valid and outperforms the standard voxel-based lesion-symptom mapping approach for symptoms caused by white matter disconnection. Supporting its clinical validity and utility, we were able to reproduce the known association between corticospinal tract damage and contralateral hemiparesis. In addition, we demonstrate that the validity can be substantially diminished by relatively minor methodological changes. Based on these results, we derive methodological recommendations for the future use of voxelwise disconnection mapping. Our study highlights the importance of validating novel methodological approaches in the rapidly evolving field of neuroimaging.

Tackling the Complexity of Lesion-Symptoms Mapping: How to Bridge the Gap Between Data Scientists and Clinicians?

Accurate and predictive lesion-symptoms mapping is a major goal in the field of clinical neurosciences. Recent studies have called for a reappraisal of the results given by the standard univariate voxel-based lesion-symptom mapping technique, emphasizing the need of developing multivariate methods. While the organization of large datasets and their analysis with machine learning (ML) approaches represents an opportunity to increase prediction accuracy, the complexity and dimensionality of the problem remain a major obstacle. Acknowledging the difficulty of inferring individual outcomes from the observation of spatial patterns of lesions, we propose here to base prediction on new individuals on models of brain connectivity, whereby the disruption of a given network predicts the occurrence of selective deficits. Well-suited ML tools are necessary to capture the relevant information from limited datasets and perform reliable inference.

Lesion covariance networks reveal proposed origins and pathways of diffuse gliomas

Diffuse gliomas have been hypothesized to originate from neural stem cells in the subventricular zone and develop along previously healthy brain networks. Here, we evaluated these hypotheses by mapping independent sources of glioma localization and determining their relationships with neurogenic niches, genetic markers and large-scale connectivity networks. By applying independent component analysis to lesion data from 242 adult patients with high- and low-grade glioma, we identified three lesion covariance networks, which reflect clusters of frequent glioma localization. Replicability of the lesion covariance networks was assessed in an independent sample of 168 glioma patients. We related the lesion covariance networks to important clinical variables, including tumour grade and patient survival, as well as genomic information such as molecular genetic subtype and bulk transcriptomic profiles. Finally, we systematically cross-correlated the lesion covariance networks with structural and functional connectivity networks derived from neuroimaging data of over 4000 healthy UK BioBank participants to uncover intrinsic brain networks that may that underlie tumour development. The three lesion covariance networks overlapped with the anterior, posterior and inferior horns of the lateral ventricles respectively, extending into the frontal, parietal and temporal cortices. These locations were independently replicated. The first lesion covariance network, which overlapped with the anterior horn, was associated with low-grade, isocitrate dehydrogenase -mutated/1p19q-codeleted tumours, as well as a neural transcriptomic signature and improved overall survival. Each lesion covariance network significantly coincided with multiple structural and functional connectivity networks, with the first bearing an especially strong relationship with brain connectivity, consistent with its neural transcriptomic profile. Finally, we identified subcortical, periventricular structures with functional connectivity patterns to the cortex that significantly matched each lesion covariance network. In conclusion, we demonstrated replicable patterns of glioma localization with clinical relevance and spatial correspondence with large-scale functional and structural connectivity networks. These results are consistent with prior reports of glioma growth along white matter pathways, as well as evidence for the coordination of glioma stem cell proliferation by neuronal activity. Our findings describe how the locations of gliomas relate to their proposed subventricular origins, suggesting a model wherein periventricular brain connectivity guides tumour development.

The strange role of brain lesion size in cognitive neuropsychology

The size of brain lesions is a variable that is frequently considered in cognitive neuropsychology. In particular, lesion-deficit inference studies often control for lesion size, and the association of lesion size with post-stroke cognitive deficits and its predictive value are studied. In the present article, the role of lesion size in cognitive deficits and its computational or design-wise consideration is discussed and questioned. First, I argue that the commonly discussed role or effect of lesion size in cognitive deficits eludes us. A generally valid understanding of the causal relation of lesion size, lesion location, and cognitive deficits is unachievable. Second, founded on the theory of causal inference, I argue that lesion size control is no generally appropriate covariate control. Instead, it is identified as a procedure with only situational benefits, which is supported by empirical data. This theoretical background is used to suggest possible research practices in lesion-deficit inference, post-stroke outcome prediction, and behavioural studies. Last, control for lesion size is put into a bigger historical context - it is identified to relate to a long-known association problem in neuropsychology, which was previously discussed from the perspectives of a mislocalisation in lesion-deficit mapping and the symptom complex approach.

Right and left neglect are not anatomically homologous: A voxel-lesion symptom mapping study

Visuospatial neglect is a heterogenous syndrome which can occur following damage to either right or left hemisphere areas. This study employs voxel-lesion symptom mapping to identify the neural correlates of left and right egocentric and allocentric neglect in a large acute stroke cohort. A cohort of 446 acute stroke survivors (age = 26-95, 44% female) completed neuropsychological neglect assessment and routine clinical imaging. Similar to previous investigations, left egocentric and left allocentric neglect were associated with damage to distinct clusters of voxels within the posterior parietal and temporo-parietal junction areas. Unlike previous investigations, right egocentric neglect was found to most strongly associated with damage to more posterior voxels within left occipital cortical areas. Right allocentric neglect was found to be most strongly associated with damage to the anterior limb of the left internal capsule. Interestingly, the right hemisphere homologues of the areas implicated in right-lateralised neglect were not overlapping with those associated with left neglect impairment. This dissociation was present across both egocentric and allocentric neglect impairment. The results of this investigation suggest that right egocentric/allocentric neglect should not be characterised as a consequence of damage to left-hemisphere homologues of the right hemisphere attentional systems. These findings support the characterisation of visuospatial neglect as a heterogenous cluster of impairments rather than a unitary syndrome and provide novel insight into the neural correlates of spatial attention.

Content Word Production during Discourse in Aphasia: Deficits in Word Quantity, Not Lexical-Semantic Complexity

Although limited and reduced connected speech production is one, if not the most, prominent feature of aphasia, few studies have examined the properties of content words produced during discourse in aphasia, in comparison to the many investigations of single-word production. In this study, we used a distributional analysis approach to investigate the properties of content word production during discourse by 46 participants spanning a wide range of chronic poststroke aphasia and 20 neurotypical adults, using different stimuli that elicited three discourse genres (descriptive, narrative, and procedural). Initially, we inspected the discourse data with respect to the quantity of production, lexical-semantic diversity, and psycholinguistic features (frequency and imageability) of content words. Subsequently, we created a "lexical-semantic landscape," which is sensitive to subtle changes and allowed us to evaluate the pattern of changes in discourse production across groups. Relative to neurotypical adults, all persons with aphasia (both fluent and nonfluent) showed significant reduction in the quantity and diversity of production, but the lexical-semantic complexity of word production directly mirrored neurotypical performance. Specifically, persons with aphasia produced the same rate of nouns/verbs, and their discourse samples covered the full range of word frequency and imageability, albeit with reduced word quantity. These findings provide novel evidence that, unlike in other disorders (e.g., semantic dementia), discourse production in poststroke aphasia has relatively preserved lexical-semantic complexity but demonstrates significantly compromised quantity of content word production. Voxel-wise lesion-symptom mapping using both univariate and multivariate approaches revealed left frontal regions particularly the pars opercularis, insular cortex, and central and frontal opercular cortices supporting word retrieval during connected speech, irrespective of their word class or lexical-semantic complexity.

The frontal aslant tract and its role in executive functions: a quantitative tractography study in glioma patients

Focal white matter lesions can cause cognitive impairments due to disconnections within or between networks. There is some preliminary evidence that there are specific hubs and fiber pathways that should be spared during surgery to retain cognitive performance. A tract potentially involved in important higher-level cognitive processes is the frontal aslant tract. It roughly connects the posterior parts of the inferior frontal gyrus and the superior frontal gyrus. Functionally, the left frontal aslant tract has been associated with speech and the right tract with executive functions. However, there currently is insufficient knowledge about the right frontal aslant tract’s exact functional importance. The aim of this study was to investigate the role of the right frontal aslant tract in executive functions via a lesion-symptom approach. We retrospectively examined 72 patients with frontal glial tumors and correlated measures from tractography (distance between tract and tumor, and structural integrity of the tract) with cognitive test performances. The results indicated involvement of the right frontal aslant tract in shifting attention and letter fluency. This involvement was not found for the left tract. Although this study was exploratory, these converging findings contribute to a better understanding of the functional frontal subcortical anatomy. Shifting attention and letter fluency are important for healthy cognitive functioning, and when impaired they may greatly influence a patient’s wellbeing. Further research is needed to assess whether or not damage to the right frontal aslant tract causes permanent cognitive impairments, and consequently identifies this tract as a critical pathway that should be taken into account during neurosurgical procedures.

Multi-model mapping of phonemic fluency

The voluntary generation of non-overlearned responses is usually assessed with phonemic fluency. Like most frontal tasks, it draws upon different complex processes and systems whose precise nature is still incompletely understood. Many claimed aspects regarding the pattern of phonemic fluency performance and its underlying anatomy remain controversial. Major limitations of past investigations include small sample size, scant analysis of phonemic output and methodologically insufficient lesion analysis approaches. We investigated a large number of patients with focal unilateral right or left frontal (n = 110) or posterior (n = 100) or subcortical (n = 65) lesions imaged with magnetic resonance or computed tomography and compared their performance on the number of overall responses, words produced over time, extremely infrequent/unknown words and inappropriate words generated. We also employed, for the first time parcel-based lesion-symptom mapping, tract-wise statistical analysis as well as Bayesian multi-variate analysis based on meta-analytically defined functional region of interest, including their interactions. We found that left frontal damage was associated with greater impairment than right frontal or posterior damage on overall fluency performance, suggesting that phonemic fluency shows specificity to frontal lesions. We also found that subcorticals, similar to frontals, performed significantly worse than posteriors on overall performance suggesting that subcortical regions are also involved. However, only frontal effects were found for words produced over time, extremely infrequent/unknown and inappropriate words. Parcel-based lesion-symptom mapping analysis found that worse fluency performance was associated with damage to the posterior segment of the left frontal middle and superior gyrus, the left dorsal anterior cingulate gyrus and caudate nucleus. Tract-wise statistical analysis revealed that disconnections of left frontal tracts are critical. Bayesian multi-variate models of lesions and disconnectome maps implicated left middle and inferior frontal and left dorsomedial frontal regions. Our study suggests that a set of well localized left frontal areas together with subcortical regions and several left frontal tracts are critical for word generation. We speculate that a left lateralized network exists. It involves medial, frontal regions supporting the process of 'energization', which sustains activation for the duration of the task and middle and inferior frontal regions concerned with 'selection', required due to the competition produced by associated stored words, respectively. The methodology adopted represents a promising and empirically robust approach in furthering our understanding of the neurocognitive architecture underpinning executive processes.

Reclassifying stroke lesion anatomy

Cognitive and behavioural outcomes in stroke reflect the interaction between two complex anatomically-distributed patterns: the functional organization of the brain and the structural distribution of ischaemic injury. Conventional outcome models—for individual prediction or population-level inference—commonly ignore this complexity, discarding anatomical variation beyond simple characteristics such as lesion volume. This sets a hard limit on the maximum fidelity such models can achieve. High-dimensional methods can overcome this problem, but only at prohibitively large data scales. Drawing on one of the largest published collections of anatomically-registered imaging of acute stroke—N = 1333—here we use non-linear dimensionality reduction to derive a succinct latent representation of the anatomical patterns of ischaemic injury, agglomerated into 21 distinct intuitive categories. We compare the maximal predictive performance it enables against both simpler low-dimensional and more complex high-dimensional representations, employing multiple empirically-informed ground truth models of distributed structure–outcome relationships. We show our representation sets a substantially higher ceiling on predictive fidelity than conventional low-dimensional approaches, but lower than that achievable within a high-dimensional framework. Where descriptive simplicity is a necessity, such as within clinical care or research trials of modest size, the representation we propose arguably offers a favourable compromise of compactness and fidelity.

Game-theoretical mapping of fundamental brain functions based on lesion deficits in acute stroke

Lesion analysis is a fundamental and classical approach for inferring the causal contributions of brain regions to brain function. However, many studies have been limited by the shortcomings of methodology or clinical data. Aiming to overcome these limitations, we here use an objective multivariate approach based on game theory, Multi-perturbation Shapley value Analysis, in conjunction with data from a large cohort of 394 acute stroke patients, to derive causal contributions of brain regions to four principal functional components of the widely used National Institutes of Health Stroke Score measure. The analysis was based on a high-resolution parcellation of the brain into 294 grey and white matter regions. Through initial lesion symptom mapping for identifying all potential candidate regions and repeated iterations of the game-theoretical approach to remove non-significant contributions, the analysis derived the smallest sets of regions contributing to each of the four principal functional components as well as functional interactions among the regions. Specifically, the factor 'language and consciousness' was related to contributions of cortical regions in the left hemisphere, including the prefrontal gyrus, the middle frontal gyrus, the ventromedial putamen and the inferior frontal gyrus. Right and left motor functions were associated with contributions of the left and right dorsolateral putamen and the posterior limb of the internal capsule, correspondingly. Moreover, the superior corona radiata and the paracentral lobe of the right hemisphere as well as the right caudal area 23 of the cingulate gyrus were mainly related to left motor function, while the prefrontal gyrus, the external capsule and the sagittal stratum fasciculi of the left hemisphere contributed to right motor function. Our approach demonstrates a practically feasible strategy for applying an objective lesion inference method to a high-resolution map of the human brain and distilling a small, characteristic set of grey and white matter structures contributing to fundamental brain functions. In addition, we present novel findings of synergistic interactions between brain regions that provide insight into the functional organization of brain networks.

Dysfunctional Tissue Correlates of Unrelated Naming Errors in Acute Left Hemisphere Stroke

Most naming error lesion-symptom mapping (LSM) studies have focused on semantic and/or phonological errors. Anomic individuals also produce unrelated word errors, which may be linked to semantic or modality-independent lexical deficits. To investigate the neural underpinnings of rarely-studied unrelated errors, we conducted LSM analyses in 100 individuals hospitalized with a left hemisphere stroke who completed imaging protocols and language assessments. We used least absolute shrinkage and selection operator regression to capture relationships between naming errors and dysfunctional brain tissue metrics (regional damage or hypoperfusion in vascular territories) in two groups: participants with and without impaired single-word auditory comprehension. Hypoperfusion-particularly within the parietal lobe-was an important error predictor, especially for the unimpaired group. In both groups, higher unrelated error proportions were associated with primarily ventral stream damage, the language route critical for processing meaning. Nonetheless, brain metrics implicated in unrelated errors were distinct from semantic error correlates.

Intellectual awareness of naming abilities in people with chronic post-stroke aphasia

Anosognosia, or lack of self-awareness, is often present following neurological injury and can result in poor functional outcomes. The specific phenomenon of intellectual awareness, the knowledge that a function is impaired in oneself, has not been widely studied in post-stroke aphasia. We aim to identify behavioral and neural correlates of intellectual awareness by comparing stroke survivors' self-reports of anomia to objective naming performance and examining lesion sites. Fifty-three participants with chronic aphasia without severe comprehension deficits rated their naming ability and completed a battery of behavioral tests. We calculated the reliability and accuracy of participant self-ratings, then examined the relationship of poor intellectual awareness to speech, language, and cognitive measures. We used support vector regression lesion-symptom mapping (SVR-LSM) to determine lesion locations associated with impaired and preserved intellectual awareness. Reliability and accuracy of self-ratings varied across the participants. Poor intellectual awareness was associated with reduced performance on tasks that rely on semantics. Our SVR-LSM results demonstrated that anterior inferior frontal lesions were associated with poor awareness, while mid-superior temporal lesions were associated with preserved awareness. An anterior-posterior gradient was evident in the unthresholded lesion-symptom maps. While many people with chronic aphasia and relatively intact comprehension can accurately and reliably report the severity of their anomia, others overestimate, underestimate, or inconsistently estimate their naming abilities. Clinicians should consider this when administering self-rating scales, particularly when semantic deficits or anterior inferior frontal lesions are present. Administering self-ratings on multiple days may be useful to check the reliability of patient perceptions.

Anatomy of phonemic and semantic fluency: A lesion and disconnectome study in 1231 stroke patients

Disturbances of semantic and phonemic fluency are common after brain damage, as a manifestation of language, executive, or memory dysfunction. Lesion-symptom mapping (LSM) studies can provide fundamental insights in shared and distinct anatomical correlates of these cognitive functions and help to understand which patients suffer from these deficits. We performed a multivariate support vector regression-based lesion-symptom mapping and structural disconnection study on semantic and phonemic fluency in 1231 patients with acute ischemic stroke. With the largest-ever LSM study on verbal fluency we achieved almost complete brain lesion coverage. Lower performance on both fluency types was related to left hemispheric frontotemporal and parietal cortical regions, and subcortical regions centering on the left thalamus. Distinct correlates for phonemic fluency were the anterior divisions of middle and inferior frontal gyri. Distinct correlates for semantic fluency were the posterior regions of the middle and inferior temporal gyri, parahippocampal and fusiform gyri and triangular part of the inferior frontal gyrus. The disconnectome-based analyses additionally revealed phonemic fluency was associated with a more extensive frontoparietal white matter network, whereas semantic fluency was associated with disconnection of the fornix, mesiotemporal white matter, splenium of the corpus callosum. These results provide the most detailed outline of the anatomical correlates of phonemic and semantic fluency to date, stress the crucial role of subcortical regions and reveal a novel dissociation in the left temporal lobe.

Strategies for feature extraction from structural brain imaging in lesion-deficit modelling

High‐dimensional modelling of post‐stroke deficits from structural brain imaging is highly relevant to basic cognitive neuroscience and bears the potential to be translationally used to guide individual rehabilitation measures. One strategy to optimise model performance is well‐informed feature selection and representation. However, different feature representation strategies were so far used, and it is not known what strategy is best for modelling purposes. The present study compared the three common main strategies: voxel‐wise representation, lesion‐anatomical componential feature reduction and region‐wise atlas‐based feature representation. We used multivariate, machine‐learning‐based lesion‐deficit models to predict post‐stroke deficits based on structural lesion data. Support vector regression was tuned by nested cross‐validation techniques and tested on held‐out validation data to estimate model performance. While we consistently found the numerically best models for lower‐dimensional, featurised data and almost always for principal components extracted from lesion maps, our results indicate only minor, non‐significant differences between different feature representation styles. Hence, our findings demonstrate the general suitability of all three commonly applied feature representations in lesion‐deficit modelling. Likewise, model performance between qualitatively different popular brain atlases was not significantly different. Our findings also highlight potential minor benefits in individual fine‐tuning of feature representations and the challenge posed by the high, multifaceted complexity of lesion data, where lesion‐anatomical and functional criteria might suggest opposing solutions to feature reduction.

Analysis of morphological characteristics of IDH-mutant/wildtype brain tumors using whole-lesion phenotype analysis

Background

Although IDH-mutant tumors aggregate to the frontotemporal regions, the clustering pattern of IDH-wildtype tumors is less clear. As voxel-based lesion-symptom mapping (VLSM) has several limitations for solid lesion mapping, a new technique, whole-lesion phenotype analysis (WLPA), is developed. We utilize WLPA to assess spatial clustering of tumors with IDH mutation from The Cancer Genome Atlas and The Cancer Imaging Archive.

Methods

The degree of tumor clustering segmented from T1 weighted images is measured to every other tumor by a function of lesion similarity to each other via the Hausdorff distance. Each tumor is ranked according to the degree to which its neighboring tumors show identical phenotypes, and through a permutation technique, significant tumors are determined. VLSM was applied through a previously described method.

Results

A total of 244 patients of mixed-grade gliomas (WHO II-IV) are analyzed, of which 150 were IDH-wildtype and 139 were glioblastomas. VLSM identifies frontal lobe regions that are more likely associated with the presence of IDH mutation but no regions where IDH-wildtype was more likely to be present. WLPA identifies both IDH-mutant and -wildtype tumors exhibit statistically significant spatial clustering.

Conclusion

WLPA may provide additional statistical power when compared with VLSM without making several potentially erroneous assumptions. WLPA identifies tumors most likely to exhibit particular phenotypes, rather than producing anatomical maps, and may be used in conjunction with VLSM to understand the relationship between tumor morphology and biologically relevant tumor phenotypes.

Dissociable Mechanisms of Verbal Working Memory Revealed through Multivariate Lesion Mapping

Two maintenance mechanisms with separate neural systems have been suggested for verbal working memory: articulatory-rehearsal and non-articulatory maintenance. Although lesion data would be key to understanding the essential neural substrates of these systems, there is little evidence from lesion studies that the two proposed mechanisms crucially rely on different neuroanatomical substrates. We examined 39 healthy adults and 71 individuals with chronic left-hemisphere stroke to determine if verbal working memory tasks with varying demands would rely on dissociable brain structures. Multivariate lesion-symptom mapping was used to identify the brain regions involved in each task, controlling for spatial working memory scores. Maintenance of verbal information relied on distinct brain regions depending on task demands: sensorimotor cortex under higher demands and superior temporal gyrus (STG) under lower demands. Inferior parietal cortex and posterior STG were involved under both low and high demands. These results suggest that maintenance of auditory information preferentially relies on auditory-phonological storage in the STG via a nonarticulatory maintenance when demands are low. Under higher demands, sensorimotor regions are crucial for the articulatory rehearsal process, which reduces the reliance on STG for maintenance. Lesions to either of these regions impair maintenance of verbal information preferentially under the appropriate task conditions.

Damage to Broca's area does not contribute to long-term speech production outcome after stroke

Broca's area in the posterior half of the left inferior frontal gyrus has long been thought to be critical for speech production. The current view is that long-term speech production outcome in patients with Broca's area damage is best explained by the combination of damage to Broca's area and neighbouring regions including the underlying white matter, which was also damaged in Paul Broca's two historic cases. Here, we dissociate the effect of damage to Broca's area from the effect of damage to surrounding areas by studying long-term speech production outcome in 134 stroke survivors with relatively circumscribed left frontal lobe lesions that spared posterior speech production areas in lateral inferior parietal and superior temporal association cortices. Collectively, these patients had varying degrees of damage to one or more of nine atlas-based grey or white matter regions: Brodmann areas 44 and 45 (together known as Broca's area), ventral premotor cortex, primary motor cortex, insula, putamen, the anterior segment of the arcuate fasciculus, uncinate fasciculus and frontal aslant tract. Spoken picture description scores from the Comprehensive Aphasia Test were used as the outcome measure. Multiple regression analyses allowed us to tease apart the contribution of other variables influencing speech production abilities such as total lesion volume and time post-stroke. We found that, in our sample of patients with left frontal damage, long-term speech production impairments (lasting beyond 3 months post-stroke) were solely predicted by the degree of damage to white matter, directly above the insula, in the vicinity of the anterior part of the arcuate fasciculus, with no contribution from the degree of damage to Broca's area (as confirmed with Bayesian statistics). The effect of white matter damage cannot be explained by a disconnection of Broca's area, because speech production scores were worse after damage to the anterior arcuate fasciculus with relative sparing of Broca's area than after damage to Broca's area with relative sparing of the anterior arcuate fasciculus. Our findings provide evidence for three novel conclusions: (i) Broca's area damage does not contribute to long-term speech production outcome after left frontal lobe strokes; (ii) persistent speech production impairments after damage to the anterior arcuate fasciculus cannot be explained by a disconnection of Broca's area; and (iii) the prior association between persistent speech production impairments and Broca's area damage can be explained by co-occurring white matter damage, above the insula, in the vicinity of the anterior part of the arcuate fasciculus.

Insular Cortex Mediates Attentional Capture by Behaviorally Relevant Stimuli after Damage to the Right Temporoparietal Junction

The right temporoparietal junction (rTPJ) and insula both play a key role for the processing of relevant stimuli. However, while both have been conceived as neural "switches" that detect salient events and redirect the focus of attention, it remains unclear how these brain regions interact to achieve this behavioral goal. Here, we tested human participants with focal left-hemispheric or right-hemispheric lesions in a spatial cuing task that requires participants to react to lateralized stimuli preceded by a distracter that shares or does not share a relevant feature with the target. Using machine learning to identify significant lesion-behavior relationships, we found that rTPJ damage produces distinctive, pathologically increased attentional capture, but only by relevant distracters. Functional connectivity analyses revealed that the degree of capture is positively associated with a functional connection between insula and rTPJ, together with functional isolation of the rTPJ from right dorsal prefrontal cortex (dPFC). These findings suggest a mechanistic model where the insula-rTPJ connection constitutes a crucial functional unit that breaks attentional focus upon detection of behaviorally relevant events, while the dPFC appears to attune this activity.

Influence of stroke infarct location on quality of life assessed in a multivariate lesion-symptom mapping study

Stroke has a deleterious impact on quality of life. However, it is less well known if stroke lesions in different brain regions are associated with reduced quality of life (QoL). We therefore investigated this association by multivariate lesion-symptom mapping. We analyzed magnetic resonance imaging and clinical data from the WAKE-UP trial. European Quality of Life 5 Dimensions (EQ-5D) 3 level questionnaires were completed 90 days after stroke. Lesion symptom mapping was performed using a multivariate machine learning algorithm (support vector regression) based on stroke lesions 22-36 h after stroke. Brain regions with significant associations were explored in reference to white matter tracts. Of 503 randomized patients, 329 were included in the analysis (mean age 65.4 years, SD 11.5; median NIHSS = 6, IQR 4-9; median EQ-5D score 90 days after stroke 1, IQR 0-4, median lesion volume 3.3 ml, IQR 1.1-16.9 ml). After controlling for lesion volume, significant associations between lesions and EQ-5D score were detected for the right putamen, and internal capsules of both hemispheres. Multivariate lesion inference analysis revealed an association between injuries of the cortico-spinal tracts with worse self-reported quality of life 90 days after stroke in comparably small stroke lesions, extending previous reports of the association of striato-capsular lesions with worse functional outcome. Our findings are of value to identify patients at risk of impaired QoL after stroke.

A low-dimensional structure of neurological impairment in stroke

Neurological deficits following stroke are traditionally described as syndromes related to damage of a specific area or vascular territory. Recent studies indicate that, at the population level, post-stroke neurological impairments cluster in three sets of correlated deficits across different behavioural domains. To examine the reproducibility and specificity of this structure, we prospectively studied first-time stroke patients (n = 237) using a bedside, clinically applicable, neuropsychological assessment and compared the behavioural and anatomical results with those obtained from a different prospective cohort studied with an extensive neuropsychological battery. The behavioural assessment at 1-week post-stroke included the Oxford Cognitive Screen and the National Institutes of Health Stroke Scale. A principal component analysis was used to reduce variables and describe behavioural variance across patients. Lesions were manually segmented on structural scans. The relationship between anatomy and behaviour was analysed using multivariate regression models. Three principal components explained ≈50% of the behavioural variance across subjects. PC1 loaded on language, calculation, praxis, right side neglect and memory deficits; PC2 loaded on left motor, visual and spatial neglect deficits; PC3 loaded on right motor deficits. These components matched those obtained with a more extensive battery. The underlying lesion anatomy was also similar. Neurological deficits following stroke are correlated in a low-dimensional structure of impairment, related neither to the damage of a specific area or vascular territory. Rather they reflect widespread network impairment caused by focal lesions. These factors showed consistency across different populations, neurobehavioural batteries and, most importantly, can be described using a combination of clinically applicable batteries (National Institutes of Health Stroke Scale and Oxford Cognitive Screen). They represent robust behavioural biomarkers for future stroke population studies.

Outcome after acute ischemic stroke is linked to sex-specific lesion patterns

Acute ischemic stroke affects men and women differently. In particular, women are often reported to experience higher acute stroke severity than men. We derived a low-dimensional representation of anatomical stroke lesions and designed a Bayesian hierarchical modeling framework tailored to estimate possible sex differences in lesion patterns linked to acute stroke severity (National Institute of Health Stroke Scale). This framework was developed in 555 patients (38% female). Findings were validated in an independent cohort (n = 503, 41% female). Here, we show brain lesions in regions subserving motor and language functions help explain stroke severity in both men and women, however more widespread lesion patterns are relevant in female patients. Higher stroke severity in women, but not men, is associated with left hemisphere lesions in the vicinity of the posterior circulation. Our results suggest there are sex-specific functional cerebral asymmetries that may be important for future investigations of sex-stratified approaches to management of acute ischemic stroke.

Generative lesion pattern decomposition of cognitive impairment after stroke

Cognitive impairment is a frequent and disabling sequela of stroke. There is however incomplete understanding of how lesion topographies in the left and right cerebral hemisphere brain interact to cause distinct cognitive deficits. We integrated machine learning and Bayesian hierarchical modelling to enable a hemisphere-aware analysis of 1080 acute ischaemic stroke patients with deep profiling ∼3 months after stroke. We show the relevance of the left hemisphere in the prediction of language and memory assessments and relevance of the right hemisphere in the prediction of visuospatial functioning. Global cognitive impairments were equally well predicted by lesion topographies from both sides. Damage to the hippocampal and occipital regions on the left was particularly informative about lost naming and memory functions, while damage to these regions on the right was linked to lost visuospatial functioning. Global cognitive impairment was predominantly linked to lesioned tissue in the supramarginal and angular gyrus, the post-central gyrus as well as the lateral occipital and opercular cortices of the left hemisphere. Hence, our analysis strategy uncovered that lesion patterns with unique hemispheric distributions are characteristic of how cognitive capacity is lost due to ischaemic brain tissue damage.

Domains of Health-Related Quality of Life Are Associated With Specific Deficits and Lesion Locations in Chronic Aphasia

BACKGROUND

Health-related quality of life (HRQL) in stroke survivors is related to numerous factors, but more research is needed to delineate factors related to HRQL in people with aphasia.

OBJECTIVE

To examine the relationship between HRQL and demographic factors, impairment-based measures, and lesion characteristics in chronic aphasia.

METHODS

A total of 41 left-hemisphere stroke survivors with aphasia underwent cognitive testing and magnetic resonance imaging. To address relationships with demographic and impairment-based measures, test scores were entered into a principal component analysis (PCA) and multiple linear regression was performed for overall and domain (physical, communication, psychosocial) scores of the Stroke and Aphasia Quality of Life Scale (SAQOL-39g). Independent variables included factor scores from the PCA, motricity, lesion volume, depressed mood, and demographic variables. To address relationships with lesion location, multivariate support vector regression lesion-symptom mapping (SVR-LSM) was used to localize lesions associated with SAQOL-39g scores.

RESULTS

The PCA yielded 3 factors, which were labeled Language Production, Nonlinguistic Cognition, and Language Comprehension. Multiple linear regression revealed that depression symptoms predicted lower SAQOL-39g average and domain scores. Lower motricity scores predicted lower SAQOL-39g average and physical scores, and lower Language Production factor scores predicted lower communication scores. SVR-LSM demonstrated that basal ganglia lesions were associated with lower physical scores, and inferior frontal lesions were associated with lower psychosocial scores.

CONCLUSIONS

HRQL in chronic left-hemisphere stroke survivors with aphasia relates to lesion location, depression symptoms, and impairment-based measures. This information may help identify individuals at risk for specific aspects of low HRQL and facilitate targeted interventions to improve well-being.

Convergence of heteromodal lexical retrieval in the lateral prefrontal cortex

Lexical retrieval requires selecting and retrieving the most appropriate word from the lexicon to express a desired concept. Few studies have probed lexical retrieval with tasks other than picture naming, and when non-picture naming lexical retrieval tasks have been applied, both convergent and divergent results emerged. The presence of a single construct for auditory and visual processes of lexical retrieval would influence cognitive rehabilitation strategies for patients with aphasia. In this study, we perform support vector regression lesion-symptom mapping using a brain tumor model to test the hypothesis that brain regions specifically involved in lexical retrieval from visual and auditory stimuli represent overlapping neural systems. We find that principal components analysis of language tasks revealed multicollinearity between picture naming, auditory naming, and a validated measure of word finding, implying the existence of redundant cognitive constructs. Nonparametric, multivariate lesion-symptom mapping across participants was used to model accuracies on each of the four language tasks. Lesions within overlapping clusters of 8,333 voxels and 21,512 voxels in the left lateral prefrontal cortex (PFC) were predictive of impaired picture naming and auditory naming, respectively. These data indicate a convergence of heteromodal lexical retrieval within the PFC.

The extreme capsule and aphasia: proof-of-concept of a new way relating structure to neurological symptoms

We present anatomy-based symptom-lesion mapping to assess the association between lesions of tracts in the extreme capsule and aphasia. The study cohort consisted of 123 patients with acute left-hemispheric stroke without a lesion of language-related cortical areas of the Stanford atlas of functional regions of interest. On templates generated through global fibre tractography, lesions of the extreme capsule and of the arcuate fascicle were quantified and correlated with the occurrence of aphasia (n = 18) as defined by the Token Test. More than 15% damage of the slice plane through the extreme capsule was a strong independent predictor of aphasia in stroke patients, odds ratio 16.37, 95% confidence interval: 3.11–86.16, P < 0.01. In contrast, stroke lesions of >15% in the arcuate fascicle were not associated with aphasia. Our results support the relevance of a ventral pathway in the language network running through the extreme capsule.

Lesions that do or do not impair digit span: a study of 816 stroke survivors

Prior studies have reported inconsistency in the lesion sites associated with verbal short-term memory impairments. Here we asked: How many different lesion sites can account for selective impairments in verbal short-term memory that persist over time, and how consistently do these lesion sites impair verbal short-term memory? We assessed verbal short-term memory impairments using a forward digit span task from the Comprehensive Aphasia Test. First, we identified the incidence of digit span impairments in a sample of 816 stroke survivors (541 males/275 females; age at stroke onset 56 ± 13 years; time post-stroke 4.4 ± 5.2 years). Second, we studied the lesion sites in a subgroup of these patients (n = 39) with left hemisphere damage and selective digit span impairment-defined as impaired digit span with unimpaired spoken picture naming and spoken word comprehension (tests of speech production and speech perception, respectively). Third, we examined how often these lesion sites were observed in patients who either had no digit span impairments or digit span impairments that co-occurred with difficulties in speech perception and/or production tasks. Digit span impairments were observed in 222/816 patients. Almost all (199/222 = 90%) had left hemisphere damage to five small regions in basal ganglia and/or temporo-parietal areas. Even complete damage to one or more of these five regions was not consistently associated with persistent digit span impairment. However, when the same regions were spared, only 5% (23/455) presented with digit span impairments. These data suggest that verbal short-term memory impairments are most consistently associated with damage to left temporo-parietal and basal ganglia structures. Sparing of these regions very rarely results in persistently poor verbal short-term memory. These findings have clinical implications for predicting recovery of verbal short-term memory after stroke.

Multivariate machine learning-based language mapping in glioma patients based on lesion topography

Diffusive and progressive tumor infiltration within language-related areas of the brain induces functional reorganization. However, the macrostructural basis of subsequent language deficits is less clear. To address this issue, lesion topography data from 137 preoperative patients with left cerebral language-network gliomas (81 low-grade gliomas and 56 high-grade gliomas), were adopted for multivariate machine-learning-based lesion-language mapping analysis. We found that tumor location in the left posterior middle temporal gyrus-a bottleneck where both dorsal and ventral language pathways travel-predicted deficits of spontaneous speech (cluster size = 1356 mm³, false discovery rate corrected P < 0.05) and naming scores (cluster size = 1491 mm³, false discovery rate corrected P < 0.05) in the high-grade glioma group. In contrast, no significant lesion-language mapping results were observed in the low-grade glioma group, suggesting a large functional reorganization. These findings suggest that in patients with gliomas, the macrostructural plasticity mechanisms that modulate brain-behavior relationships depend on glioma grade.

The neural basis for mental state attribution: A voxel-based lesion mapping study

The ability to infer other persons' mental states, "Theory of Mind" (ToM), is a key function of social cognition and is needed when interpreting the intention of others. ToM is associated with a network of functionally related regions, with reportedly key prominent hubs located in the dorsolateral prefrontal cortex (dlPFC) and the temporoparietal junction (TPJ). The involvement of (mainly the right) TPJ in ToM is based primarily on functional imaging studies that provide correlational evidence for brain-behavior associations. In this lesion study, we test whether certain brain areas are necessary for intact ToM performance. We investigated individuals with penetrating traumatic brain injury (n = 170) and healthy matched controls (n = 30) using voxel-based lesion-symptom mapping (VLSM) and by measuring the impact of a given lesion on white matter disconnections. ToM performance was compared between five patient groups based on lesion location: right TPJ, left TPJ, right dlPFC, left dlPFC, and other lesion, as well as healthy controls. The only group to present with lower ToM abilities was the one with lesions in the right dlPFC. Similarly, VLSM analysis revealed a main cluster in the right frontal middle gyrus and a secondary cluster in the left inferior parietal gyrus. Last, we found that disconnection of the left inferior longitudinal fasciculus and right superior longitudinal fasciculus were associated with poor ToM performance. This study highlights the importance of lesion studies in complementing functional neuroimaging findings and supports the assertion that the right dlPFC is a key region mediating mental state attribution.