Mapping human brain lesions and their functional consequences

Segregated circuits for phonemic and semantic fluency: A novel patient-tailored disconnection study

Phonemic and semantic fluency are neuropsychological tests widely used to assess patients' language and executive abilities and are highly sensitive tests in detecting language deficits in glioma patients. However, the networks that are involved in these tasks could be distinct and suggesting either a frontal (phonemic) or temporal (semantic) involvement. 42 right-handed patients (26 male, mean age = 52.5 years, SD=±13.3) were included in this retrospective study. Patients underwent awake (54.8%) or asleep (45.2%) surgery for low-grade (16.7%) or high-grade-glioma (83.3%) in the frontal (64.3%) or temporal lobe (35.7%) of the left (50%) or right (50%) hemisphere. Pre-operative tractography was reconstructed for each patient, with segmentation of the inferior fronto-occipital fasciculus (IFOF), arcuate fasciculus (AF), uncinate fasciculus (UF), inferior longitudinal fasciculus (ILF), third branch of the superior longitudinal fasciculus (SLF-III), frontal aslant tract (FAT), and cortico-spinal tract (CST). Post-operative percentage of damage and disconnection of each tract, based on the patients' surgical cavities, were correlated with verbal fluencies scores at one week and one month after surgery. Analyses of differences between fluency scores at these timepoints (before surgery, one week and one month after surgery) were performed; lesion-symptom mapping was used to identify the correlation between cortical areas and post-operative scores. Immediately after surgery, a transient impairment of verbal fluency was observed, that improved within a month. Left hemisphere lesions were related to a worse verbal fluency performance, being a damage to the left superior frontal or temporal gyri associated with phonemic or semantic fluency deficit, respectively. At a subcortical level, disconnection analyses revealed that fluency scores were associated to the involvement of the left FAT and the left frontal part of the IFOF for phonemic fluency, and the association was still present one month after surgery. For semantic fluency, the correlation between post-surgery performance emerged for the left AF, UF, ILF and the temporal part of the IFOF, but disappeared at the follow-up. This approach based on the patients' pre-operative tractography, allowed to trace for the first time a dissociation between white matter pathways integrity and verbal fluency after surgery for glioma resection. Our results confirm the involvement of a frontal anterior pathway for phonemic fluency and a ventral temporal pathway for semantic fluency. Finally, our longitudinal results suggest that the frontal executive pathway requires a longer interval to recover compared to the semantic one.

Lesion network mapping for symptom localization: recent developments and future directions

PURPOSE OF REVIEW

Focal lesions causing specific neurological or psychiatric symptoms can occur in multiple different brain locations, complicating symptom localization. Here, we review lesion network mapping, a technique used to aid localization by mapping lesion-induced symptoms to brain circuits rather than individual brain regions. We highlight recent examples of how this technique is being used to investigate clinical entities and identify therapeutic targets.

RECENT FINDINGS

To date, lesion network mapping has successfully been applied to more than 40 different symptoms or symptom complexes. In each case, lesion locations were combined with an atlas of human brain connections (the human connectome) to map heterogeneous lesion locations causing the same symptom to a common brain circuit. This approach has lent insight into symptoms that have been difficult to localize using other techniques, such as hallucinations, tics, blindsight, and pathological laughter and crying. Further, lesion network mapping has recently been applied to lesions that improve symptoms, such as tremor and addiction, which may translate into new therapeutic targets.

SUMMARY

Lesion network mapping can be used to map lesion-induced symptoms to brain circuits rather than single brain regions. Recent findings have provided insight into long-standing clinical mysteries and identified testable treatment targets for circuit-based and symptom-based neuromodulation.

Sex differences in the human brain: a roadmap for more careful analysis and interpretation of a biological reality

The presence, magnitude, and significance of sex differences in the human brain are hotly debated topics in the scientific community and popular media. This debate is largely fueled by studies containing strong, opposing conclusions: either little to no evidence exists for sex differences in human neuroanatomy, or there are small-to-moderate differences in the size of certain brain regions that are highly reproducible across cohorts (even after controlling for sex differences in average brain size). Our Commentary uses the specific comparison between two recent large-scale studies that adopt these opposing views-namely the review by Eliot and colleagues (2021) and the direct analysis of ~ 40k brains by Williams and colleagues (2021)-in an effort to clarify this controversy and provide a framework for conducting this research. First, we review observations that motivate research on sex differences in human neuroanatomy, including potential causes (evolutionary, genetic, and environmental) and effects (epidemiological and clinical evidence for sex-biased brain disorders). We also summarize methodological and empirical support for using structural MRI to investigate such patterns. Next, we outline how researchers focused on sex differences can better specify their study design (e.g., how sex was defined, if and how brain size was adjusted for) and results (by e.g., distinguishing sexual dimorphisms from sex differences). We then compare the different approaches available for studying sex differences across a large number of individuals: direct analysis, meta-analysis, and review. We stress that reviews do not account for methodological differences across studies, and that this variation explains many of the apparent inconsistencies reported throughout recent reviews (including the work by Eliot and colleagues). For instance, we show that amygdala volume is consistently reported as male-biased in studies with sufficient sample sizes and appropriate methods for brain size correction. In fact, comparing the results from multiple large direct analyses highlights small, highly reproducible sex differences in the volume of many brain regions (controlling for brain size). Finally, we describe best practices for the presentation and interpretation of these findings. Care in interpretation is important for all domains of science, but especially so for research on sex differences in the human brain, given the existence of broad societal gender-biases and a history of biological data being used justify sexist ideas. As such, we urge researchers to discuss their results from simultaneously scientific and anti-sexist viewpoints.

Recovery of neural dynamics criticality in personalized whole-brain models of stroke

The critical brain hypothesis states that biological neuronal networks, because of their structural and functional architecture, work near phase transitions for optimal response to internal and external inputs. Criticality thus provides optimal function and behavioral capabilities. We test this hypothesis by examining the influence of brain injury (strokes) on the criticality of neural dynamics estimated at the level of single participants using directly measured individual structural connectomes and whole-brain models. Lesions engender a sub-critical state that recovers over time in parallel with behavior. The improvement of criticality is associated with the re-modeling of specific white-matter connections. We show that personalized whole-brain dynamical models poised at criticality track neural dynamics, alteration post-stroke, and behavior at the level of single participants.

Spatial neglect treatment: The brain's spatial-motor Aiming systems

Animal and human literature supports spatial-motor "Aiming" bias, a frontal-subcortical syndrome, as a core deficit in spatial neglect. However, spatial neglect treatment studies rarely assess Aiming errors. Two knowledge gaps result: spatial neglect rehabilitation studies fail to capture the impact on motor-exploratory aspects of functional disability. Also, across spatial neglect treatment studies, discrepant treatment effects may also result from sampling different proportions of patients with Aiming bias. We review behavioural evidence for Aiming spatial neglect, and demonstrate the importance of measuring and targeting Aiming bias for treatment, by reviewing literature on Aiming spatial neglect and prism adaptation treatment, and presenting new preliminary data on bromocriptine treatment. Finally, we review neuroanatomical and network disruption that may give rise to Aiming spatial neglect. Because Aiming spatial neglect predicts prism adaptation treatment response, assessment may broaden the ability of rehabilitation research to capture functionally-relevant disability. Frontal brain lesions predict both the presence of Aiming spatial neglect, and a robust response to some spatial neglect interventions. Research is needed that co-stratifies spatial neglect patients by lesion location and Aiming spatial neglect, to personalize spatial neglect rehabilitation and perhaps even open a path to spatial retraining as a means of promoting better mobility after stroke.

Brain lesions disrupting addiction map to a common human brain circuit

Drug addiction is a public health crisis for which new treatments are urgently needed. In rare cases, regional brain damage can lead to addiction remission. These cases may be used to identify therapeutic targets for neuromodulation. We analyzed two cohorts of patients addicted to smoking at the time of focal brain damage (cohort 1 n = 67; cohort 2 n = 62). Lesion locations were mapped to a brain atlas and the brain network functionally connected to each lesion location was computed using human connectome data (n = 1,000). Associations with addiction remission were identified. Generalizability was assessed using an independent cohort of patients with focal brain damage and alcohol addiction risk scores (n = 186). Specificity was assessed through comparison to 37 other neuropsychological variables. Lesions disrupting smoking addiction occurred in many different brain locations but were characterized by a specific pattern of brain connectivity. This pattern involved positive connectivity to the dorsal cingulate, lateral prefrontal cortex, and insula and negative connectivity to the medial prefrontal and temporal cortex. This circuit was reproducible across independent lesion cohorts, associated with reduced alcohol addiction risk, and specific to addiction metrics. Hubs that best matched the connectivity profile for addiction remission were the paracingulate gyrus, left frontal operculum, and medial fronto-polar cortex. We conclude that brain lesions disrupting addiction map to a specific human brain circuit and that hubs in this circuit provide testable targets for therapeutic neuromodulation.

Edge-centric analysis of stroke patients: An alternative approach for biomarkers of lesion recovery

Most neuroimaging studies of post-stroke recovery rely on analyses derived from standard node-centric functional connectivity to map the distributed effects in stroke patients. Here, given the importance of nonlocal and diffuse damage, we use an edge-centric approach to functional connectivity in order to provide an alternative description of the effects of this disorder. These techniques allow for the rendering of metrics such as normalized entropy, which describes the diversity of edge communities at each node. Moreover, the approach enables the identification of high amplitude co-fluctuations in fMRI time series. We found that normalized entropy is associated with stroke lesion severity and continually increases across the time of patients' recovery. Furthermore, high amplitude co-fluctuations not only relate to the lesion severity but are also associated with patients' level of recovery. The current study is the first edge-centric application for a clinical population in a longitudinal dataset and demonstrates how a different perspective for functional data analysis can further characterize topographic modulations of brain dynamics.

Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations

Schizophrenia patients with auditory verbal hallucinations (AVHs) are diseased groups of serious psychosis with still unknown etiology. The aim of this research was to identify the neurophysiological correlates of auditory verbal hallucinations. Revealing the neural correlates of auditory hallucination is not merely of great clinical significance, but it is also quite essential to study the pathophysiological correlates of schizophrenia. In this study, 25 Schizophrenia patients with AVHs (AVHs group, 23.2 ± 5.35 years), 52 Schizophrenia patients without AVHs (non-AVHs group, 25.79 ± 5.63 years) and 28 healthy subjects (NC group, 26.14 ± 5.45 years) were enrolled. Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. We found that schizophrenia patients with AVHs were characterized by significant decreased static functional connectivity and enhanced variability of dynamic functional connectivity (non-parametric permutation test, Bonferroni correction, p < 0.05). In addition, the AVHs group also demonstrated increased number of brain states, suggesting brain dynamics enhanced in these patients compared with the non-AVHs group. Our findings suggested that there were abnormalities in the connection of brain language regions in auditory verbal hallucinations. It appears that the interruption of connectivity from the language region might be critical to the pathological basis of AVHs.

Damage to the dorsolateral prefrontal cortex is associated with repetitive compulsive behaviors in patients with penetrating brain injury

Background

Damage to cortico-striato-thalamo-cortical (CSTC) circuits is associated with the development of repetitive behaviours in animals and humans. However, the types of repetitive behaviours that are developed after injury to these structures are poorly defined. This study examines the effect of damage to separate elements of CSTC circuits sustained by veterans of the Vietnam War on obsessions, compulsions, and tics.

Methods

We performed partial correlations (correcting for cognition, age, education, and global brain damage) between volume loss from traumatic brain injury in specific elements of CSTC circuits (lateral and medial orbitofrontal and dorsolateral prefrontal cortices, anterior cingulate cortex, thalamus, and basal ganglia) and scores on a modified version of the Yale-Brown Obsessive Compulsive Scale Symptom Checklist and the Yale Global Tic Severity Scale in 83 Vietnam war veterans with penetrating brain injuries at different sites throughout the brain.

Results

We found that volume loss in the left dorsolateral prefrontal cortex was associated with the development of compulsive behaviours (r=0.32, padj<0.05) whereas volume loss in the basal ganglia was associated with the development of tics (r=0.33, padj<0.05).

Conclusion

Our findings indicate that damage to specific CSTC elements can be associated with the development of compulsive behaviours and tics that are not necessarily accompanied by obsessions.

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.

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.

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.

Dissecting neuropathic from poststroke pain: the white matter within

ABSTRACT

Poststroke pain (PSP) is a heterogeneous term encompassing both central neuropathic (ie, central poststroke pain [CPSP]) and nonneuropathic poststroke pain (CNNP) syndromes. Central poststroke pain is classically related to damage in the lateral brainstem, posterior thalamus, and parietoinsular areas, whereas the role of white matter connecting these structures is frequently ignored. In addition, the relationship between stroke topography and CNNP is not completely understood. In this study, we address these issues comparing stroke location in a CPSP group of 35 patients with 2 control groups: 27 patients with CNNP and 27 patients with stroke without pain. Brain MRI images were analyzed by 2 complementary approaches: an exploratory analysis using voxel-wise lesion symptom mapping, to detect significant voxels damaged in CPSP across the whole brain, and a hypothesis-driven, region of interest-based analysis, to replicate previously reported sites involved in CPSP. Odds ratio maps were also calculated to demonstrate the risk for CPSP in each damaged voxel. Our exploratory analysis showed that, besides known thalamic and parietoinsular areas, significant voxels carrying a high risk for CPSP were located in the white matter encompassing thalamoinsular connections (one-tailed threshold Z > 3.96, corrected P value <0.05, odds ratio = 39.7). These results show that the interruption of thalamocortical white matter connections is an important component of CPSP, which is in contrast with findings from nonneuropathic PSP and from strokes without pain. These data can aid in the selection of patients at risk to develop CPSP who could be candidates to pre-emptive or therapeutic interventions.

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.

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.

Outcome Prediction of Patients with Intracerebral Hemorrhage by Measurement of Lesion Volume in the Corticospinal Tract on Computed Tomography

Objective:

This study investigated the potential utility of computed tomography for outcome prediction in patients with intracerebral hemorrhage.

Methods:

Patients with putaminal and/or thalamic hemorrhage for whom computed tomography images were acquired in our hospital emergency room soon after onset were retrospectively enrolled. Outcome measurements were obtained at discharge from the convalescent rehabilitation ward of our affiliated hospital. Hemiparesis was evaluated using the total score of the motor component of the Stroke Impairment Assessment Set (SIAS-motor; null to full, 0 to 25), the motor component of the Functional Independence Measure (FIM-motor; null to full, 13 to 91), and the total length of hospital stay. After registration of the computed tomography images to the standard brain, the volumes of the hematoma lesions located in the corticospinal tract were calculated. The correlation between the corticospinal tract lesion volumes and the outcome measurements was assessed using Spearman’s rank correlation test.

Results:

Thirty patients were entered into the final analytical database. Corticospinal tract lesion volumes ranged from 0.002 to 4.302 ml (median, 1.478). SIAS-motor scores ranged from 0 to 25 (median, 20), FIM-motor scores ranged from 15 to 91 (median, 80.5), and the total length of hospital stay ranged from 31 to 194 days (median, 106.5). All correlation tests were statistically significant (P <0.01). The strongest correlation was for SIAS-motor total (R=–0.710), followed by FIM-motor (R=–0.604) and LOS (R=0.493).

Conclusions:

These findings suggest that conventional computed tomography images may be useful for outcome prediction in patients with intracerebral hemorrhage.

Deep learning-based detection and segmentation of diffusion abnormalities in acute ischemic stroke

Background

Accessible tools to efficiently detect and segment diffusion abnormalities in acute strokes are highly anticipated by the clinical and research communities.

Methods

We developed a tool with deep learning networks trained and tested on a large dataset of 2,348 clinical diffusion weighted MRIs of patients with acute and sub-acute ischemic strokes, and further tested for generalization on 280 MRIs of an external dataset (STIR).

Results

Our proposed model outperforms generic networks and DeepMedic, particularly in small lesions, with lower false positive rate, balanced precision and sensitivity, and robustness to data perturbs (e.g., artefacts, low resolution, technical heterogeneity). The agreement with human delineation rivals the inter-evaluator agreement; the automated lesion quantification of volume and contrast has virtually total agreement with human quantification.

Conclusion

Our tool is fast, public, accessible to non-experts, with minimal computational requirements, to detect and segment lesions via a single command line. Therefore, it fulfills the conditions to perform large scale, reliable and reproducible clinical and translational research.

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.

Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA

BACKGROUND

Previous multimodal neuroimaging studies analyzed each dataset independently in subjective cognitive decline (SCD) and mild cognitive impairment (MCI), missing the cross-information. Multi-modal fusion analysis can provide more integral and comprehensive information regarding the brain. There has been a paucity of research on fusion analysis of sMRI and DTI in SCD and MCI.

MATERIALS AND METHODS

In the present study, we conducted fusion analysis of structural MRI and DTI by applying multimodal canonical correlation analysis with joint independent component analysis (mCCA-jICA) to capture the cross-information of gray matter (GM) and white matter (WM) in 62 SCD patients, 99 MCI patients, and 70 healthy controls (HCs). We further analyzed correlations between the mixing coefficients of mCCA-jICA and neuropsychological scores among the three groups.

RESULTS

A set of joint-discriminative independent components of GM and fractional anisotropy (FA) exhibited significant links between SCD and HCs, as well as between MCI and HCs. The covariant abnormalities primarily involved the frontal lobe/middle temporal gyrus/calcarine sulcus-anterior thalamic radiation/superior longitudinal fasciculus in SCD, and middle temporal gyrus/ fusiform gyrus/caudate necleus-forceps minor/anterior thalamic radiation in MCI. There was no significant difference between SCD and MCI groups.

CONCLUSIONS

The covariant GM-WM abnormalities in SCD and MCI were found in specific brain regions involved in cognitive processing, which confirms the simultaneous GM and WM changes underlying cognitive decline. These findings suggest that multimodal fusion analysis allows for a more comprehensive understanding of the association among different types of brain tissues and its crucial role in the neuropathological mechanism of SCD and MCI.

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 Visuospatial and Sensorimotor Functions of Posterior Parietal Cortex in Drawing Tasks: A Review

Drawing is a comprehensive skill that primarily involves visuospatial processing, eye-hand coordination, and other higher-order cognitive functions. Various drawing tasks are widely used to assess brain function. The neuropsychological basis of drawing is extremely sophisticated. Previous work has addressed the critical role of the posterior parietal cortex (PPC) in drawing, but the specific functions of the PPC in drawing remain unclear. Functional magnetic resonance imaging and electrophysiological studies found that drawing activates the PPC. Lesion-symptom mapping studies have shown an association between PPC injury and drawing deficits in patients with global and focal cerebral pathology. These findings depicted a core framework of the fronto-parietal network in drawing tasks. Here, we review neuroimaging and electrophysiological studies applying drawing paradigms and discuss the specific functions of the PPC in visuospatial and sensorimotor aspects. Ultimately, we proposed a hypothetical model based on the dorsal stream. It demonstrates the organization of a PPC-centered network for drawing and provides systematic insights into drawing for future neuropsychological research.

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.

Anatomical correlates of recovery in apraxia: A longitudinal lesion-mapping study in stroke patients

OBJECTIVE

This study investigates the clinical course of recovery of apraxia after left-hemisphere stroke and the underlying neuroanatomical correlates for persisting or recovering deficits in relation to the major processing streams in the network for motor cognition.

METHODS

90 patients were examined during the acute (4.74 ± 2.73 days) and chronic (14.3 ± 15.39 months) stage after left-hemisphere stroke for deficits in meaningless imitation, as well as production and conceptual errors in tool use pantomime. Lesion correlates for persisting or recovering deficits were analyzed with an extension of the non-parametric Brunner-Munzel rank-order test for multi-factorial designs (two-way repeated-measures ANOVA) using acute images.

RESULTS

Meaningless imitation and tool use production deficits persisted into the chronic stage. Conceptual errors in tool use pantomime showed an almost complete recovery. Imitation errors persisted after occipitotemporal and superior temporal lesions in the dorso-dorsal stream. Chronic pantomime production errors were related to the supramarginal gyrus, the key structure of the ventro-dorsal stream. More anterior lesions in the ventro-dorsal stream (ventral premotor cortex) were additionally associated with poor recovery of production errors in pantomime. Conceptual errors in pantomime after temporal and supramarginal gyrus lesions persisted into the chronic stage. However, they resolved completely when related to angular gyrus or insular lesions.

CONCLUSION

The diverging courses of recovery in different apraxia tasks can be related to different mechanisms. Critical lesions to key structures of the network or entrance areas of the processing streams lead to persisting deficits in the corresponding tasks. Contrary, lesions located outside the core network but inducing a temporary network dysfunction allow good recovery e.g., of conceptual errors in pantomime. The identification of lesion correlates for different long-term recovery patterns in apraxia might also allow early clinical prediction of the course of recovery.

Strategic infarct locations for post-stroke cognitive impairment: a pooled analysis of individual patient data from 12 acute ischaemic stroke cohorts

BACKGROUND

Post-stroke cognitive impairment (PSCI) occurs in approximately half of people in the first year after stroke. Infarct location is a potential determinant of PSCI, but a comprehensive map of strategic infarct locations predictive of PSCI is unavailable. We aimed to identify infarct locations most strongly predictive of PSCI after acute ischaemic stroke and use this information to develop a prediction model.

METHODS

In this large-scale multicohort lesion-symptom mapping study, we pooled and harmonised individual patient data from 12 cohorts through the Meta-analyses on Strategic Lesion Locations for Vascular Cognitive Impairment using Lesion-Symptom Mapping (Meta VCI Map) consortium. The identified cohorts (as of Jan 1, 2019) comprised patients with acute symptomatic infarcts on CT or MRI (with available infarct segmentations) and a cognitive assessment up to 15 months after acute ischaemic stroke onset. PSCI was defined as performance lower than the fifth percentile of local normative data, on at least one cognitive domain on a multidomain neuropsychological assessment or on the Montreal Cognitive Assessment. Voxel-based lesion-symptom mapping (VLSM) was used to calculate voxel-wise odds ratios (ORs) for PSCI that were mapped onto a three-dimensional brain template to visualise PSCI risk per location. For the prediction model of PSCI risk, a location impact score on a 5-point scale was derived from the VLSM results on the basis of the mean voxel-wise coefficient (ln[OR]) within each patient's infarct. We did combined internal-external validation by leave-one-cohort-out cross-validation for all 12 cohorts using logistic regression. Predictive performance of a univariable model with only the location impact score was compared with a multivariable model with addition of other clinical PSCI predictors (age, sex, education, time interval between stroke onset and cognitive assessment, history of stroke, and total infarct volume). Testing of visual ratings was done by three clinicians, and accuracy, inter-rater reliability, and intra-rater reliability were assessed with Cohen's weighted kappa.

FINDINGS

In our sample of 2950 patients (mean age 66·8 years [SD 11·6]; 1157 [39·2%] women), 1286 (43·6%) had PSCI. We achieved high lesion coverage of the brain in our analyses (86·9%). Infarcts in the left frontotemporal lobes, left thalamus, and right parietal lobe were strongly associated with PSCI (after false discovery rate correction, q<0·01; voxel-wise ORs >20). On cross-validation, the location impact score showed good correspondence, based on visual assessment of goodness of fit, between predicted and observed risk of PSCI across cohorts after adjusting for cohort-specific PSCI occurrence. Cross-validations showed that the location impact score by itself had similar performance to the combined model with other PSCI predictors, while allowing for easy visual assessment. Therefore the univariable model with only the location impact score was selected as the final model. Correspondence between visual ratings and actual location impact score (Cohen's weighted kappa: range 0·88-0·92), inter-rater agreement (0·85-0·87), and intra-rater agreement (for a single rater, 0·95) were all high.

INTERPRETATION

To the best of our knowledge, this study provides the first comprehensive map of strategic infarct locations associated with risk of PSCI. A location impact score was derived from this map that robustly predicted PSCI across cohorts. Furthermore, we developed a quick and reliable visual rating scale that might in the future be applied by clinicians to identify individual patients at risk of PSCI.

FUNDING

The Netherlands Organisation for Health Research and Development.

Lesions causing hallucinations localize to one common brain network

The brain regions responsible for hallucinations remain unclear. We studied 89 brain lesions causing hallucinations using a recently validated technique termed lesion network mapping. We found that hallucinations occurred following lesions to a variety of different brain regions, but these lesion locations fell within a single functionally connected brain network. This network was defined by connectivity to the cerebellar vermis, inferior cerebellum (bilateral lobule X), and the right superior temporal sulcus. Within this single hallucination network, additional connections with the lesion location dictated the sensory modality of the hallucination: lesions causing visual hallucinations were connected to the lateral geniculate nucleus in the thalamus while lesions causing auditory hallucinations were connected to the dentate nucleus in the cerebellum. Our results suggest that lesions causing hallucinations localize to a single common brain network, but additional connections within this network dictate the sensory modality, lending insight into the causal neuroanatomical substrate of hallucinations.

Association of Lesion Location and Depressive Symptoms Poststroke

BACKGROUND AND PURPOSE

Poststroke depression is a common stroke sequel, yet its neurobiological substrates are still unclear. We sought to determine whether specific lesion locations are associated with depressive symptoms after stroke.

METHODS

In a prospective study, 270 patients with first ever stroke were repeatedly tested with the depression subscale of the Hospital Anxiety and Depression Scale within the first 4 weeks and 6 months after stroke. Voxel-based lesion behavior mapping based on clinical imaging was performed to test for associations between symptoms of depression and lesion locations.

RESULTS

Frequency of poststroke depression (Hospital Anxiety and Depression Scale-D score >7) after 6 months was 19.6%. Higher Hospital Anxiety and Depression Scale-D scores for depression within the first 4 weeks were the only independent predictor for poststroke depression after 6 months in a multiple logistic regression also including age, sex, lesion volume, stroke severity, Barthel-Index, and the anxiety subscale of the Hospital Anxiety and Depression Scale. Nonparametric permutation-test based voxel-based lesion behavior mapping identified a cluster of voxels mostly within the left ventrolateral prefrontal cortex where lesions were significantly associated with more depressive symptoms after 6 months. No such association was observed within the right hemisphere despite better lesion coverage.

CONCLUSIONS

Lesions in the left ventrolateral prefrontal cortex increase the risk of depressive symptoms 6 months poststroke. Lesions within the right hemisphere are unrelated to depressive symptoms. Recognition of left frontal lesions as a risk factor should help in the early diagnosis of poststroke depression through better risk stratification. The results are in line with evidence from functional imaging and noninvasive brain stimulation in patients without focal brain damage indicating that dysfunction in the left lateral prefrontal cortex contributes to depressive disorders.

Post-stroke cognitive impairment on the Mini-Mental State Examination primarily relates to left middle cerebral artery infarcts

Background

Post-stroke cognitive impairment can occur after damage to various brain regions, and cognitive deficits depend on infarct location. The Mini-Mental State Examination (MMSE) is still widely used to assess post-stroke cognition, but it has been criticized for capturing only certain cognitive deficits. Along these lines, it might be hypothesized that cognitive deficits as measured with the MMSE primarily involve certain infarct locations.

Aims

This comprehensive lesion-symptom mapping study aimed to determine which acute infarct locations are associated with post-stroke cognitive impairment on the MMSE.

Methods

We examined associations between impairment on the MMSE (<5th percentile; normative data) and infarct location in 1198 patients (age 67 ± 12 years, 43% female) with acute ischemic stroke using voxel-based lesion-symptom mapping. As a frame of reference, infarct patterns associated with impairments in individual cognitive domains were determined, based on a more detailed neuropsychological assessment.

Results

Impairment on the MMSE was present in 420 patients (35%). Large voxel clusters in the left middle cerebral artery territory and thalamus were significantly (p < 0.01) associated with cognitive impairment on the MMSE, with highest odds ratios (>15) in the thalamus and superior temporal gyrus. In comparison, domain-specific impairments were related to various infarct patterns across both hemispheres including the left medial temporal lobe (verbal memory) and right parietal lobe (visuospatial functioning).

Conclusions

Our findings indicate that post-stroke cognitive impairment on the MMSE primarily relates to infarct locations in the left middle cerebral artery territory. The MMSE is apparently less sensitive to cognitive deficits that specifically relate to other locations.

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.

An empirical comparison of univariate versus multivariate methods for the analysis of brain-behavior mapping

Lesion symptom mapping (LSM) tools are used on brain injury data to identify the neural structures critical for a given behavior or symptom. Univariate lesion symptom mapping (ULSM) methods provide statistical comparisons of behavioral test scores in patients with and without a lesion on a voxel by voxel basis. More recently, multivariate lesion symptom mapping (MLSM) methods have been developed that consider the effects of all lesioned voxels in one model simultaneously. In the current study, we provide a much-needed systematic comparison of several ULSM and MLSM methods, using both synthetic and real data to identify the potential strengths and weaknesses of both approaches. We tested the spatial precision of each LSM method for both single and dual (network type) anatomical target simulations across anatomical target location, sample size, noise level, and lesion smoothing. Additionally, we performed false positive simulations to identify the characteristics associated with each method's spurious findings. Simulations showed no clear superiority of either ULSM or MLSM methods overall, but rather highlighted specific advantages of different methods. No single method produced a thresholded LSM map that exclusively delineated brain regions associated with the target behavior. Thus, different LSM methods are indicated, depending on the particular study design, specific hypotheses, and sample size. Overall, we recommend the use of both ULSM and MLSM methods in tandem to enhance confidence in the results: Brain foci identified as significant across both types of methods are unlikely to be spurious and can be confidently reported as robust results.

The anatomy of spatial neglect after posterior cerebral artery stroke

Spatial neglect is a common consequence of stroke in the territory of the right middle cerebral artery. Damage to a perisylvian fronto-temporo-parietal network has been demonstrated to underlie this disorder. Less common, stroke to the posterior cerebral artery territory may also lead to spatial neglect. This study aimed to uncover the anatomical underpinnings of spatial neglect after posterior cerebral artery infarction. A sample of 50 posterior cerebral artery infarct patients was screened for spatial neglect. Neural correlates of neglect were investigated both with voxel-based lesion behaviour mapping and with region-of-interest analyses. Brain damage neither to the splenium, nor to the parahippocampal gyrus, nor to the thalamus was predictive of spatial neglect. Only damage to the perisylvian fronto-temporo-parietal network of spatial neglect was significantly associated with neglect severity. We conclude that both posterior and middle cerebral artery stroke induce spatial neglect after damage to the same perisylvian brain network. The findings contradict previous theories that postulated neural correlates of spatial neglect specifically supplied by the posterior cerebral artery. In posterior cerebral artery stroke patients, affected parts of this network are located at the border zone between the posterior and middle cerebral artery territories. Inter-individual variability in the localization of the border between both artery territories appears to mediate the occurrence of spatial neglect after posterior cerebral artery stroke.

Disconnection somewhere down the line: Multivariate lesion-symptom mapping of the line bisection error

Line Bisection is a simple task frequently used in stroke patients to diagnose disorders of spatial perception characterized by a directional bisection bias to the ipsilesional side. However, previous anatomical and behavioural findings are contradictory, and the diagnostic validity of the line bisection task has been challenged. We hereby aimed to re-analyse the anatomical basis of pathological line bisection by using multivariate lesion-symptom mapping and disconnection-symptom mapping based on support vector regression in a sample of 163 right hemispheric acute stroke patients. In line with some previous studies, we observed that pathological line bisection was related to more than a single focal lesion location. Cortical damage primarily to right parietal areas, particularly the inferior parietal lobe, including the angular gyrus, as well as damage to the right basal ganglia contributed to the pathology. In contrast to some previous studies, an involvement of frontal cortical brain areas in the line bisection task was not observed. Subcortically, damage to the right superior longitudinal fasciculus (I, II and III) and arcuate fasciculus as well as the internal capsule was associated with line bisection errors. Moreover, white matter damage of interhemispheric fibre bundles, such as the anterior commissure and posterior parts of the corpus callosum projecting into the left hemisphere, was predictive of pathological deviation in the line bisection task.

The Impact of Covariates in Voxel-Wise Lesion-Symptom Mapping

Background: Voxel-wise lesion-symptom mapping (VLSM) is a statistical technique to infer the structure-function relationship in patients with cerebral strokes. Previous VLSM research suggests that it is important to adjust for various confounders such as lesion size to minimize the inflation of true effects. The aim of this work is to investigate the regional impact of covariates on true effects in VLSM. Methods: A total of 222 follow-up datasets of acute ischemic stroke patients with known NIH Stroke Scale (NIHSS) score at 48-h post-stroke were available for this study. Patient age, lesion volume, and follow-up imaging time were tested for multicollinearity using variance inflation factor analysis and used as covariates in VLSM analyses. Covariate importance maps were computed from the VLSM results by standardizing the beta coefficients of general linear models. Results: Covariates were found to have distinct regional importance with respect to lesion eloquence in the brain. Age has a relatively higher importance in the superior temporal gyrus, inferior parietal lobule, and in the pre- and post-central gyri. Volume explains more variability in the opercular area of the insula, inferior frontal gyrus, and caudate. Follow-up imaging time accounts for most of the variance in the globus pallidus, ventromedial- and dorsolateral putamen, dorsal caudate, pre-motor thalamus, and the dorsal insula. Conclusions: This is the first study investigating and revealing distinctive regional patterns of importance for covariates typically used in VLSM. These covariate importance maps can improve our understanding of the lesion-deficit relationships in patients and could prove valuable for patient-specific treatment and rehabilitation planning.

Accuracy and practical aspects of semi- and fully automatic segmentation methods for resected brain areas

Purpose

Precise segmentation of brain lesions is essential for neurological research. Specifically, resection volume estimates can aid in the assessment of residual postoperative tissue, e.g. following surgery for glioma. Furthermore, behavioral lesion-symptom mapping in epilepsy relies on accurate delineation of surgical lesions. We sought to determine whether semi- and fully automatic segmentation methods can be applied to resected brain areas and which approach provides the most accurate and cost-efficient results.

Methods

We compared a semi-automatic (ITK-SNAP) with a fully automatic (lesion_GNB) method for segmentation of resected brain areas in terms of accuracy with manual segmentation serving as reference. Additionally, we evaluated processing times of all three methods. We used T1w, MRI-data of epilepsy patients (n = 27; 11 m; mean age 39 years, range 16–69) who underwent temporal lobe resections (17 left).

Results

The semi-automatic approach yielded superior accuracy (p < 0.001) with a median Dice similarity coefficient (mDSC) of 0.78 and a median average Hausdorff distance (maHD) of 0.44 compared with the fully automatic approach (mDSC 0.58, maHD 1.32). There was no significant difference between the median percent volume difference of the two approaches (p > 0.05). Manual segmentation required more human input (30.41 min/subject) and therefore inferring significantly higher costs than semi- (3.27 min/subject) or fully automatic approaches (labor and cost approaching zero).

Conclusion

Semi-automatic segmentation offers the most accurate results in resected brain areas with a moderate amount of human input, thus representing a viable alternative compared with manual segmentation, especially for studies with large patient cohorts.

Assessing and mapping language, attention and executive multidimensional deficits in stroke aphasia

There is growing awareness that aphasia following a stroke can include deficits in other cognitive functions and that these are predictive of certain aspects of language function, recovery and rehabilitation. However, data on attentional and executive (dys)functions in individuals with stroke aphasia are still scarce and the relationship to underlying lesions is rarely explored. Accordingly in this investigation, an extensive selection of standardized non-verbal neuropsychological tests was administered to 38 individuals with chronic post-stroke aphasia, in addition to detailed language testing and MRI. To establish the core components underlying the variable patients’ performance, behavioural data were explored with rotated principal component analyses, first separately for the non-verbal and language tests, then in a combined analysis including all tests. Three orthogonal components for the non-verbal tests were extracted, which were interpreted as shift-update, inhibit-generate and speed. Three components were also extracted for the language tests, representing phonology, semantics and speech quanta. Individual continuous scores on each component were then included in a voxel-based correlational methodology analysis, yielding significant clusters for all components. The shift-update component was associated with a posterior left temporo-occipital and bilateral medial parietal cluster, the inhibit-generate component was mainly associated with left frontal and bilateral medial frontal regions, and the speed component with several small right-sided fronto-parieto-occipital clusters. Two complementary multivariate brain-behaviour mapping methods were also used, which showed converging results. Together the results suggest that a range of brain regions are involved in attention and executive functioning, and that these non-language domains play a role in the abilities of patients with chronic aphasia. In conclusion, our findings confirm and extend our understanding of the multidimensionality of stroke aphasia, emphasize the importance of assessing non-verbal cognition in this patient group and provide directions for future research and clinical practice. We also briefly compare and discuss univariate and multivariate methods for brain-behaviour mapping.

Post-stroke cognitive deficits rarely come alone: Handling co-morbidity in lesion-behaviour mapping

Post‐stroke behavioural symptoms often correlate and systematically co‐occur with each other, either because they share cognitive processes, or because their neural correlates are often damaged together. Thus, neuropsychological symptoms often share variance. Many previous lesion‐behaviour mapping studies aimed to methodologically consider this shared variance between neuropsychological variables. A first group of studies controlled the behavioural target variable for the variance explained by one or multiple other variables to obtain a more precise mapping of the target variable. A second group of studies focused on the shared variance of multiple variables itself with the aim to map neural correlates of cognitive processes that are shared between the original variables. In the present study, we tested the validity of these methods by using real lesion data and both real and simulated data sets. We show that the variance that is shared between post‐stroke behavioural variables is ambiguous, and that mapping procedures that consider this variance are prone to biases and artefacts. We discuss under which conditions such procedures could still be used and what alternative approaches exist.

Functional anomaly mapping reveals local and distant dysfunction caused by brain lesions

The lesion method has been important for understanding brain-behavior relationships in humans, but has previously used maps based on structural damage. Lesion measurement based on structural damage may label partly damaged but functional tissue as abnormal, and moreover, ignores distant dysfunction in structurally intact tissue caused by deafferentation, diaschisis, and other processes. A reliable method to map functional integrity of tissue throughout the brain would provide a valuable new approach to measuring lesions. Here, we use machine learning on four dimensional resting state fMRI data obtained from left-hemisphere stroke survivors in the chronic period of recovery and control subjects to generate graded maps of functional anomaly throughout the brain in individual patients. These functional anomaly maps identify areas of obvious structural lesions and are stable across multiple measurements taken months and even years apart. Moreover, the maps identify functionally anomalous regions in structurally intact tissue, providing a direct measure of remote effects of lesions on the function of distant brain structures. Multivariate lesion-behavior mapping using functional anomaly maps replicates classic behavioral localization, identifying inferior frontal regions related to speech fluency, lateral temporal regions related to auditory comprehension, parietal regions related to phonology, and the hand area of motor cortex and descending corticospinal pathways for hand motor function. Further, this approach identifies relationships between tissue function and behavior distant from the structural lesions, including right premotor dysfunction related to ipsilateral hand movement, and right cerebellar regions known to contribute to speech fluency. Brain-wide maps of the functional effects of focal lesions could have wide implications for lesion-behavior association studies and studies of recovery after brain injury.

Degradation of Praxis Brain Networks and Impaired Comprehension of Manipulable Nouns in Stroke

Distributed brain systems contribute to representation of semantic knowledge. Whether sensory and motor systems of the brain are causally involved in representing conceptual knowledge is an especially controversial question. Here, we tested 57 chronic left-hemisphere stroke patients using a semantic similarity judgment task consisting of manipulable and nonmanipulable nouns. Three complementary methods were used to assess the neuroanatomical correlates of semantic processing: voxel-based lesion-symptom mapping, resting-state functional connectivity, and gray matter fractional anisotropy. The three measures provided converging evidence that injury to the brain networks required for action observation, execution, planning, and visuomotor coordination are associated with specific deficits in manipulable noun comprehension relative to nonmanipulable items. Damage or disrupted connectivity of areas such as the middle posterior temporal gyrus, anterior inferior parietal lobe, and premotor cortex was related specifically to the impairment of manipulable noun comprehension. These results suggest that praxis brain networks contribute especially to the comprehension of manipulable object nouns.

Revisiting the Functional Anatomy of the Human Brain: Toward a Meta-Networking Theory of Cerebral Functions

For more than one century, brain processing was mainly thought in a localizationist framework, in which one given function was underpinned by a discrete, isolated cortical area, and with a similar cerebral organization across individuals. However, advances in brain mapping techniques in humans have provided new insights into the organizational principles of anatomo-functional architecture. Here, we review recent findings gained from neuroimaging, electrophysiological, as well as lesion studies. Based on these recent data on brain connectome, we challenge the traditional, outdated localizationist view and propose an alternative meta-networking theory. This model holds that complex cognitions and behaviors arise from the spatiotemporal integration of distributed but relatively specialized networks underlying conation and cognition (e.g., language, spatial cognition). Dynamic interactions between such circuits result in a perpetual succession of new equilibrium states, opening the door to considerable interindividual behavioral variability and to neuroplastic phenomena. Indeed, a meta-networking organization underlies the uniquely human propensity to learn complex abilities, and also explains how postlesional reshaping can lead to some degrees of functional compensation in brain-damaged patients. We discuss the major implications of this approach in fundamental neurosciences as well as for clinical developments, especially in neurology, psychiatry, neurorehabilitation, and restorative neurosurgery.

Hippocampal diaschisis contributes to anosognosia for hemiplegia: Evidence from lesion network-symptom-mapping

Anosognosia for hemiplegia (AHP) is known to be associated with lesions to the motor system combined with varying lesions to the right insula, premotor cortex, parietal lobe or hippocampus. Due to this widespread cortical lesion distribution, AHP can be understood best as a network disorder. We used lesion maps and behavioral data (n ​= ​49) from two previous studies on AHP and performed a lesion network-symptom-mapping (LNSM) analysis. This new approach permits the identification of relationships between behavior and regions connected to the lesion site based on normative functional connectome data. In a first step, using ordinary voxel-based lesion-symptom mapping, we found an association of AHP with lesions in the right posterior insula. This is in accordance with previous studies. Applying LNSM, we were able to additionally identify a region in the right posterior hippocampus where AHP was associated with significantly higher normative lesion connectivity. Notably, this region was spared by infarction in all patients. We therefore argue that remote neuronal dysfunction caused by disrupted functional connections between the lesion site and the hippocampus (i.e. diaschisis) contributed to the phenotype of AHP. An indirect affection of the hippocampus may lead to memory deficits which, in turn, impair the stable encoding of updated beliefs on the bodily state thus contributing to the multifactorial phenomenon of AHP.

Looking beyond the face area: lesion network mapping of prosopagnosia

Damage to the right fusiform face area can disrupt the ability to recognize faces, a classic example of how damage to a specialized brain region can disrupt a specialized brain function. However, similar symptoms can arise from damage to other brain regions, and face recognition is now thought to depend on a distributed brain network. The extent of this network and which regions are critical for facial recognition remains unclear. Here, we derive this network empirically based on lesion locations causing clinically significant impairments in facial recognition. Cases of acquired prosopagnosia were identified through a systematic literature search and lesion locations were mapped to a common brain atlas. The network of brain regions connected to each lesion location was identified using resting state functional connectivity from healthy participants (n = 1000), a technique termed lesion network mapping. Lesion networks were overlapped to identify connections common to lesions causing prosopagnosia. Reproducibility was assessed using split-half replication. Specificity was assessed through comparison with non-specific control lesions (n = 135) and with control lesions associated with symptoms other than prosopagnosia (n = 155). Finally, we tested whether our facial recognition network derived from clinically evident cases of prosopagnosia could predict subclinical facial agnosia in an independent lesion cohort (n = 31). Our systematic literature search identified 44 lesions causing prosopagnosia, only 29 of which intersected the right fusiform face area. However, all 44 lesion locations fell within a single brain network defined by connectivity to the right fusiform face area. Less consistent connectivity was found to other face-selective regions. Surprisingly, all 44 lesion locations were also functionally connected, through negative correlation, with regions in the left frontal cortex. This connectivity pattern was highly reproducible and specific to lesions causing prosopagnosia. Positive connectivity to the right fusiform face area and negative connectivity to left frontal regions were independent predictors of prosopagnosia and predicted subclinical facial agnosia in an independent lesion cohort. We conclude that lesions causing prosopagnosia localize to a single functionally connected brain network defined by connectivity to the right fusiform face area and to left frontal regions. Implications of these findings for models of facial recognition deficits are discussed.

A Human Depression Circuit Derived From Focal Brain Lesions

BACKGROUND

Focal brain lesions can lend insight into the causal neuroanatomical substrate of depression in the human brain. However, studies of lesion location have led to inconsistent results.

METHODS

Five independent datasets with different lesion etiologies and measures of postlesion depression were collated (N = 461). Each 3-dimensional lesion location was mapped to a common brain atlas. We used voxel lesion symptom mapping to test for associations between depression and lesion locations. Next, we computed the network of regions functionally connected to each lesion location using a large normative connectome dataset (N = 1000). We used these lesion network maps to test for associations between depression and connected brain circuits. Reproducibility was assessed using a rigorous leave-one-dataset-out validation. Finally, we tested whether lesion locations associated with depression fell within the same circuit as brain stimulation sites that were effective for improving poststroke depression.

RESULTS

Lesion locations associated with depression were highly heterogeneous, and no single brain region was consistently implicated. However, these same lesion locations mapped to a connected brain circuit, centered on the left dorsolateral prefrontal cortex. Results were robust to leave-one-dataset-out cross-validation. Finally, our depression circuit derived from brain lesions aligned with brain stimulation sites that were effective for improving poststroke depression.

CONCLUSIONS

Lesion locations associated with depression fail to map to a specific brain region but do map to a specific brain circuit. This circuit may have prognostic utility in identifying patients at risk for poststroke depression and therapeutic utility in refining brain stimulation targets.

Grey and white matter substrates of action naming

Despite a persistent interest in verb processing, data on the neural underpinnings of verb retrieval are fragmentary. The present study is the first to analyze the contributions of both grey and white matter damage affecting verb retrieval through action naming in stroke. We used voxel-based lesion-symptom mapping (VLSM) with an action naming task in 40 left-hemisphere stroke patients. Within the grey matter, we revealed the critical involvement of the left precentral and inferior frontal gyri, insula, and parts of basal ganglia. An overlay of white matter tract probability masks on the VLSM lesion map revealed involvement of left-hemisphere long and short association tracts with terminations in the frontal areas; and several projection tracts. The involvement of these structures is interpreted in the light of existing picture naming models, semantic control processes, and the embodiment cognition framework. Our results stress the importance of both cortico-cortical and cortico-subcortical networks of language processing.

The impact of ischemic stroke on connectivity gradients

The functional organization of the brain can be represented as a low-dimensional space that reflects its macroscale hierarchy. The dimensions of this space, described as connectivity gradients, capture the similarity of areas' connections along a continuous space. Studying how pathological perturbations with known effects on functional connectivity affect these connectivity gradients provides support for their biological relevance. Previous work has shown that localized lesions cause widespread functional connectivity alterations in structurally intact areas, affecting a network of interconnected regions. By using acute stroke as a model of the effects of focal lesions on the connectome, we apply the connectivity gradient framework to depict how functional reorganization occurs throughout the brain, unrestricted by traditional definitions of functional network boundaries. We define a three-dimensional connectivity space template based on functional connectivity data from healthy controls. By projecting lesion locations into this space, we demonstrate that ischemic strokes result in dimension-specific alterations in functional connectivity over the first week after symptom onset. Specifically, changes in functional connectivity were captured along connectivity Gradients 1 and 3. The degree of functional connectivity change was associated with the distance from the lesion along these connectivity gradients (a measure of functional similarity) regardless of the anatomical distance from the lesion. Together, these results provide support for the biological validity of connectivity gradients and suggest a novel framework to characterize connectivity alterations after stroke.

Lesion location impact on functional recovery of the hemiparetic upper limb

The effect of stroke topography on the recovery of hemiparetic upper limb (HUL) function is unclear due to limitations in previous studies-examination of lesion effects only in one point of time, or grouping together patients with left and right hemispheric damage (LHD, RHD), or disregard to different lesion impact on proximal and distal operations. Here we used voxel-based lesion symptom mapping (VLSM) to investigate the impact of stroke topography on HUL function taking into consideration the effects of (a) assessment time (subacute, chronic phases), (b) side of damaged hemisphere (left, right), (c) HUL part (proximal, distal). HUL function was examined in 3 groups of patients-Subacute (n = 130), Chronic (n = 66), and Delta (n = 49; patients examined both in the subacute and chronic phases)-using the proximal and distal sub-divisions of the Fugl-Meyer (FM) and the Box and Blocks (B&B) tests. HUL function following LHD tended to be affected in the subacute phase mainly by damage to white matter tracts, the putamen and the insula. In the chronic phase, a similar pattern was shown for B&B performance, whereas FM performance was affected by damage only to the white matter tracts. HUL function following RHD was affected in both phases, mainly by damage to the basal ganglia, white matter tracts and the insula, along with a restricted effect of damage to other cortical structures. In the chronic phase HUL function following RHD was affected also by damage to the thalamus. In the small Delta groups the following trends were found: In LHD patients, delayed motor recovery, captured by the B&B test, was affected by damage to the sensory-motor cortex, white matter association fibers and parts of the perisilvian cortex. In the RHD patients of the Delta group, delayed motor recovery was affected by damage to white matter projection fibers. Proximal and distal HUL functions examined in LHD patients (both in the subacute and chronic phases) tended to be affected by similar structures-mainly white matter projection tracts. In RHD patients, a distinction between proximal and distal HUL functions was found in the subacute but not in the chronic phase, with proximal and distal HUL functions affected by similar subcortical and cortical structures, except for an additional impact of damage to the superior temporal cortex and the retro-lenticular internal capsule only on proximal HUL function. The current study suggests the existence of important differences between the functional neuroanatomy underlying motor recovery following left and right hemisphere damage. A trend for different lesion effects was shown for residual proximal and distal HUL motor control. The study corroborates earlier findings showing an effect of the time after stroke onset (subacute, chronic) on the results of VLSM analyses. Further studies with larger sample size are required for the validation of these results.

Localizing parkinsonism based on focal brain lesions

Bradykinesia, rigidity, and tremor frequently co-occur, a clinical syndrome known as parkinsonism. Because this syndrome is commonly seen in Parkinson's disease, symptoms are often attributed to cell loss in the substantia nigra. However, parkinsonism occurs in several other neurological disorders and often fails to correlate with nigrostriatal pathology, raising the question of which brain region(s) cause this syndrome. Here, we studied cases of new-onset parkinsonism following focal brain lesions. We identified 29 cases, only 31% of which hit the substantia nigra. Lesions were located in a variety of different cortical and subcortical locations. To determine whether these heterogeneous lesion locations were part of a common brain network, we leveraged the human brain connectome and a recently validated technique termed lesion network mapping. Lesion locations causing parkinsonism were functionally connected to a common network of regions including the midbrain, basal ganglia, cingulate cortex, and cerebellum. The most sensitive and specific connectivity was to the claustrum. This lesion connectivity pattern matched atrophy patterns seen in Parkinson's disease, progressive supranuclear palsy, and multiple system atrophy, suggesting a shared neuroanatomical substrate for parkinsonism. Lesion connectivity also predicted medication response and matched the pattern of effective deep brain stimulation, suggesting relevance as a treatment target. Our results, based on causal brain lesions, lend insight into the localization of parkinsonism, one of the most common syndromes in neurology. Because many patients with parkinsonism fail to respond to dopaminergic medication, these results may aid the development of alternative treatments.10.1093/brain/awy161_video1awy161media15815555971001.