Impact of correction factors in human brain lesion-behavior inference

Localization and Network Connectivity of Lesions Causing Limb Ataxia in Patients With Stroke

BACKGROUND AND OBJECTIVES

Ataxia is primarily considered to originate from the cerebellum. However, it can manifest without obvious cerebellar damage, such as in anterior circulation stroke, leaving the mechanisms of ataxia unclear. The aim of this study was to investigate whether stroke lesions causing limb ataxia localize to a common brain network.

METHODS

In this prospective cohort study, adult patients with new-onset stroke with visible lesions on CT or MRI from Turku University Hospital, Finland, were clinically examined (1) after their stroke while still admitted to the hospital (baseline) and (2) 4 months later (follow-up) to assess limb ataxia. Lesion locations and their functional connectivity, computed using openly available data from 1,000 healthy volunteers from the Brain Genome Superstruct Project, were compared voxel-by-voxel across the whole brain between patients with and without ataxia, using voxel-based lesion-symptom mapping and lesion network mapping. The findings were confirmed in an independent stroke patient cohort with identical clinical assessments.

RESULTS

One hundred ninety-seven patients (mean age 67.2 years, 39%female) were included in this study. At baseline, 35 patients (68.3 years, 34%female) had and 162 (67.0 years, 40%female) did not have new-onset acute limb ataxia. At follow-up, additional 4 patients had developed late-onset limb ataxia, totalling to 39 patients (68.6 years, 36%female) with limb ataxia at any point. One hundred eighteen patients (66.2 years, 40%female) did not have ataxia at any point (n = 40 with missing follow-up data). Lesions in 54% of the patients with acute limb ataxia were located outside the cerebellum and cerebellar peduncles, and we did not find an association between specific lesion locations and ataxia. Lesions causing acute limb ataxia, however, were connected to a common network centered on the intermediate zone cerebellum and cerebellar peduncles (lesion connectivity in patients with vs without acute limb ataxia, pFWE < 0.05). The results were similar when comparing patients with and without ataxia at any point, and when excluding lesions in the cerebellum and cerebellar peduncles (pFWE < 0.05). The findings were confirmed in the independent stroke dataset (n = 96), demonstrating an OR of 2.27 (95% CI 1.32-3.91) for limb ataxia per standard deviation increase in limb ataxia network damage score.

DISCUSSION

Lesions causing limb ataxia occur in heterogeneous locations but localize to a common brain network.

The Aphasia Recovery Cohort, an open-source chronic stroke repository

Sharing neuroimaging datasets enables reproducibility, education, tool development, and new discoveries. Neuroimaging from many studies are publicly available, providing a glimpse into progressive disorders and human development. In contrast, few stroke studies are shared, and these datasets lack longitudinal sampling of functional imaging, diffusion imaging, as well as the behavioral and demographic data that encourage novel applications. This is surprising, as stroke is a leading cause of disability, and acquiring brain imaging is considered standard of care. The first release of the Aphasia Recovery Cohort includes imaging data, demographics and behavioral measures from 230 chronic stroke survivors who experienced aphasia. We also share scripts to illustrate how the imaging data can predict impairment. In conclusion, recent advances in machine learning thrive on large, diverse datasets. Clinical data sharing can contribute to improvements in automated detection of brain injury, identification of white matter hyperintensities, measures of brain health, and prognostic abilities to guide care.

Cortical and subcortical substrates of working memory in the right hemisphere: A connectome-based lesion-symptom mapping study

Working Memory (WM) is a cognitive system whose crucial role is to temporarily hold and manipulate information. Early studies suggest that verbal WM is typically associated with left hemisphere (LH) brain regions, while the processing of visuospatial information in WM more specifically depends on the right hemisphere (RH). However, recent evidence suggests a more complex network involving both hemispheres' prefrontal and posterior parietal cortices in these processes. Unfortunately, previous lesion studies often examined only one modality (either verbal, or visuospatial) or one hemisphere, which limits the possible conclusions regarding non-lateralized hemispheric involvement. Using connectome-based lesion-symptom mapping on a large sample of patients with left (LBD) and right (RBD) focal brain damage, we examined whether gray matter damage and white matter disconnections predict deficits of WM updating in an N-back task. Patients were examined with two WM tasks that differed regarding modality (verbal, spatial) and cognitive load (1-back, 2-back). Behavioral outcomes indicated that RBD patients showed significant deficits in WM updating, regardless of task modality or load. This observation was supported by whole-brain voxel-based analysis, revealing associations between WM deficits and gray matter clusters in the RH. Specifically, damage to the right lateral frontal cortex including the brain region homologous to Broca's area was associated with verbal WM deficits, while damage to the right inferior parietal lobe and posterior temporal cortex predicted spatial WM deficits. Additionally, white matter analyses identified severely impacted tracts in the RH, predicting deficits in both verbal and spatial WM. Our findings suggest that the mental manipulation of both verbal and visuospatial information in WM updating relies on the integrity of the RH, irrespective of the specific type of information held in mind.

The stroke outcome optimization project: Acute ischemic strokes from a comprehensive stroke center

Stroke is a leading cause of disability, and Magnetic Resonance Imaging (MRI) is routinely acquired for acute stroke management. Publicly sharing these datasets can aid in the development of machine learning algorithms, particularly for lesion identification, brain health quantification, and prognosis. These algorithms thrive on large amounts of information, but require diverse datasets to avoid overfitting to specific populations or acquisitions. While there are many large public MRI datasets, few of these include acute stroke. We describe clinical MRI using diffusion-weighted, fluid-attenuated and T1-weighted modalities for 1715 individuals admitted in the upstate of South Carolina, of whom 1461 have acute ischemic stroke. Demographic and impairment data are provided for 1106 of the stroke survivors from this cohort. Our validation demonstrates that machine learning can leverage the imaging data to predict stroke severity as measured by the NIH Stroke Scale/Score (NIHSS). We share not only the raw data, but also the scripts for replicating our findings. These tools can aid in education, and provide a benchmark for validating improved methods.

Automated Measurement of Cerebral Hemorrhagic Contusions and Outcomes After Traumatic Brain Injury in the TRACK-TBI Study

Importance

Because withdrawal of life-sustaining therapy based on perceived poor prognosis is the most common cause of death after moderate or severe traumatic brain injury (TBI), the accuracy of clinical prognoses is directly associated with mortality. Although the location of brain injury is known to be important for determining recovery potential after TBI, the best available prognostic models, such as the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) score, do not currently incorporate brain injury location.

Objective

To test whether automated measurement of cerebral hemorrhagic contusion size and location is associated with improved prognostic performance of the IMPACT score.

Design, Setting, and Participants

This prognostic cohort study was performed in 18 US level 1 trauma centers between February 26, 2014, and August 8, 2018. Adult participants aged 17 years or older from the US-based Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study with moderate or severe TBI (Glasgow Coma Scale score 3-12) and contusions detected on brain computed tomography (CT) scans were included. The data analysis was performed between January 2023 and February 2024.

Exposures

Labeled contusions detected on CT scans using Brain Lesion Analysis and Segmentation Tool for Computed Tomography (BLAST-CT), a validated artificial intelligence algorithm.

Main Outcome and Measure

The primary outcome was a Glasgow Outcome Scale-Extended (GOSE) score of 4 or less at 6 months after injury. Whether frontal or temporal lobe contusion volumes improved the performance of the IMPACT score was tested using logistic regression and area under the receiver operating characteristic curve comparisons. Sparse canonical correlation analysis was used to generate a disability heat map to visualize the strongest brainwide associations with outcomes.

Results

The cohort included 291 patients with moderate or severe TBI and contusions (mean [SD] age, 42 [18] years; 221 [76%] male; median [IQR] emergency department arrival Glasgow Coma Scale score, 5 [3-10]). Only temporal contusion volumes improved the discrimination of the IMPACT score (area under the receiver operating characteristic curve, 0.86 vs 0.84; P = .03). The data-derived disability heat map of contusion locations showed that the strongest association with unfavorable outcomes was within the bilateral temporal and medial frontal lobes.

Conclusions and Relevance

These findings suggest that CT-based automated contusion measurement may be an immediately translatable strategy for improving TBI prognostic models.

The disengagement deficit after right-hemisphere damage: Distinct roles of lateral frontal and parietal damage

An influential model of spatial attention postulates three main attention-orienting mechanisms: disengagement, shifting, and engagement. Early research linked disengagement deficits with superior parietal damage, regardless of hemisphere or presence of spatial neglect. Subsequent studies supported the involvement of more ventral parietal regions, especially in the right hemisphere, and linked spatial neglect to deficient disengagement from ipsilateral cues. However, previous lesion studies faced serious limitations, such as small sample sizes and the lack of brain-injured controls without neglect. Additionally, some studies employed symbolic cues or used long cue-target intervals, which may fail to reveal impaired disengagement. We here used a machine-learning approach to conduct lesion-symptom mapping (LSM) on 89 patients with focal cerebral lesions to the left (LH) or right (RH) cerebral hemisphere. A group of 54 healthy participants served as controls. The paradigm used to uncover disengagement deficits employed non-predictive cues presented in the visual periphery and at short cue-target intervals, targeting exogenous attention. The main factors of interest were group (healthy participants, LH, RH), target position (left, right hemifield) and cue validity (valid, invalid). LSM-analyses were performed on two indices: the validity effect, computed as the absolute difference between reaction times (RTs) following invalid compared to valid cues, and the disengagement deficit, determined by the difference between contralesional and ipsilesional validity effects. While LH patients showed general slowing of RTs to contralesional targets, only RH patients exhibited a disengagement deficit from ipsilesional cues. LSM associated the validity effect with a right lateral frontal cluster, which additionally affected subcortical white matter of the right arcuate fasciculus, the corticothalamic pathway, and the superior longitudinal fasciculus. In contrast, the disengagement deficit was related to damage involving the right temporoparietal junction. Thus, our results support the crucial role of right inferior parietal and posterior temporal regions for attentional disengagement, but also emphasize the importance of lateral frontal regions, for the reorienting of attention.

Ground-truth validation of uni- and multivariate lesion inference approaches

Lesion analysis aims to reveal the causal contributions of brain regions to brain functions. Various strategies have been used for such lesion inferences. These approaches can be broadly categorized as univariate or multivariate methods. Here we analysed data from 581 patients with acute ischaemic injury, parcellated into 41 Brodmann areas, and systematically investigated the inferences made by two univariate and two multivariate lesion analysis methods via ground-truth simulations, in which we defined a priori contributions of brain areas to assumed brain function. Particularly, we analysed single-region models, with only single areas presumed to contribute functionally, and multiple-region models, with two contributing regions that interacted in a synergistic, redundant or mutually inhibitory mode. The functional contributions could vary in proportion to the lesion damage or in a binary way. The analyses showed a considerably better performance of the tested multivariate than univariate methods in terms of accuracy and mis-inference error. Specifically, the univariate approaches of Lesion Symptom Mapping as well as Lesion Symptom Correlation mis-inferred substantial contributions from several areas even in the single-region models, and also after accounting for lesion size. By contrast, the multivariate approaches of Multi-Area Pattern Prediction, which is based on machine learning, and Multi-perturbation Shapley value Analysis, based on coalitional game theory, delivered consistently higher accuracy and specificity. Our findings suggest that the tested multivariate approaches produce largely reliable lesion inferences, without requiring lesion size consideration, while the application of the univariate methods may yield substantial mis-localizations that limit the reliability of functional attributions.

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

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

Behavioral and neuroanatomical correlates of facial emotion processing in post-stroke depression

BACKGROUND

Emotion processing deficits are known to accompany depressive symptoms and are often seen in stroke patients. Little is known about the influence of post-stroke depressive (PSD) symptoms and specific brain lesions on altered emotion processing abilities and how these phenomena develop over time. This potential relationship may impact post-stroke rehabilitation of neurological and psychosocial function. To address this scientific gap, we investigated the relationship between PSD symptoms and emotion processing abilities in a longitudinal study design from the first days post-stroke into the early chronic phase.

METHODS

Twenty-six ischemic stroke patients performed an emotion processing task on videos with emotional faces ('happy,' 'sad,' 'anger,' 'fear,' and 'neutral') at different intensity levels (20%, 40%, 60%, 80%, 100%). Recognition accuracies and response times were measured, as well as scores of depressive symptoms (Montgomery-Åsberg Depression Rating Scale). Twenty-eight healthy participants matched in age and sex were included as a control group. Whole-brain support-vector regression lesion-symptom mapping (SVR-LSM) analyses were performed to investigate whether specific lesion locations were associated with the recognition accuracy of specific emotion categories.

RESULTS

Stroke patients performed worse in overall recognition accuracy compared to controls, specifically in the recognition of happy, sad, and fearful faces. Notably, more depressed stroke patients showed an increased processing towards specific negative emotions, as they responded significantly faster to angry faces and recognized sad faces of low intensities significantly more accurately. These effects obtained for the first days after stroke partly persisted to follow-up assessment several months later. SVR-LSM analyses revealed that inferior and middle frontal regions (IFG/MFG) and insula and putamen were associated with emotion-recognition deficits in stroke. Specifically, recognizing happy facial expressions was influenced by lesions affecting the anterior insula, putamen, IFG, MFG, orbitofrontal cortex, and rolandic operculum. Lesions in the posterior insula, rolandic operculum, and MFG were also related to reduced recognition accuracy of fearful facial expressions, whereas recognition deficits of sad faces were associated with frontal pole, IFG, and MFG damage.

CONCLUSION

PSD symptoms facilitate processing negative emotional stimuli, specifically angry and sad facial expressions. The recognition accuracy of different emotional categories was linked to brain lesions in emotion-related processing circuits, including insula, basal ganglia, IFG, and MFG. In summary, our study provides support for psychosocial and neural factors underlying emotional processing after stroke, contributing to the pathophysiology of PSD.

Unraveling glioblastoma diversity: Insights into methylation subtypes and spatial relationships

Background

The purpose of this study was to elucidate the relationship between distinct brain regions and molecular subtypes in glioblastoma (GB), focusing on integrating modern statistical tools and molecular profiling to better understand the heterogeneity of Isocitrate Dehydrogenase wild-type (IDH-wt) gliomas.

Methods

This retrospective study comprised 441 patients diagnosed with new IDH-wt glioma between 2009 and 2020 at Heidelberg University Hospital. The diagnostic process included preoperative magnetic resonance imaging and molecular characterization, encompassing IDH-status determination and subclassification, through DNA-methylation profiling. To discern and map distinct brain regions associated with specific methylation subtypes, a support-vector regression-based lesion-symptom mapping (SVR-LSM) was employed. Lesion maps were adjusted to 2 mm³ resolution. Significance was assessed with beta maps, using a threshold of P < .005, with 10 000 permutations and a cluster size minimum of 100 voxels.

Results

Of 441 initially screened glioma patients, 423 (95.9%) met the inclusion criteria. Following DNA-methylation profiling, patients were classified into RTK II (40.7%), MES (33.8%), RTK I (18%), and other methylation subclasses (7.6%). Between molecular subtypes, there was no difference in tumor volume. Using SVR-LSM, distinct brain regions correlated with each subclass were identified: MES subtypes were associated with left-hemispheric regions involving the superior temporal gyrus and insula cortex, RTK I with right frontal regions, and RTK II with 3 clusters in the left hemisphere.

Conclusions

This study linked molecular diversity and spatial features in glioblastomas using SVR-LSM. Future studies should validate these findings in larger, independent cohorts to confirm the observed patterns.

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

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

Mechanisms and neuroanatomy of response selection in tool and non-tool action tasks: Evidence from left-hemisphere stroke

The ability to select between potential actions is central to the complex process of tool use. After left hemisphere stroke, individuals with limb apraxia make more hand action errors when gesturing the use of tools with conflicting hand actions for grasping-to-move and use (e.g., screwdriver) relative to tools that are grasped-to-move and used with the same hand action (e.g., hammer). Prior research indicates that this grasp-use interference effect is driven by abnormalities in the competitive action selection process. The goal of this project was to determine whether common mechanisms and neural substrates support the competitive selection of task-appropriate responses in both tool and non-tool domains. If so, the grasp-use interference effect in a tool use gesturing task should be correlated with response interference effects in the classic Eriksen flanker and Simon tasks, and at least partly overlapping neural regions should subserve the 3 tasks. Sixty-four left hemisphere stroke survivors (33 with apraxia) participated in the tool- and non-tool interference tasks and underwent T1 anatomical MRI. There were robust grasp-use interference effects (grasp-use conflict test) and response interference effects (Eriksen flanker and Simon tasks), but these effects were not correlated. Lesion-symptom mapping analyses showed that lesions to the left inferior parietal lobule, ventral premotor cortex, and insula were associated with grasp-use interference. Lesions to the left inferior parietal lobule, postcentral gyrus, insula, caudate, and putamen were associated with response interference in the Eriksen flanker task. Lesions to the left caudate and putamen were also associated with response interference in the Simon task. Our results suggest that the selection of hand posture for tool use is mediated by distinct cognitive mechanisms and partly distinct neuroanatomic substrates from those mapping a stimulus to an appropriate motor response in non-tool domains.

Thalamocortical disconnection involved in pusher syndrome

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

Mapping Lesion-Related Epilepsy to a Human Brain Network

Importance

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

Objective

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

Design, Setting, and Participants

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

Main Outcomes and Measures

Epilepsy or no epilepsy.

Results

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

Conclusions and Relevance

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

Anatomical and functional predictors of disorientation after first-ever brain damage

BACKGROUND AND OBJECTIVES

Disorientation is a frequent consequence of acute brain injury or diffuse disorders, such as confusional states or dementia. Its anatomical correlates are debated. Impaired memory as its commonly assumed mechanism predicts that disorientation is associated with medial temporal damage. The alternative is that disorientation reflects defective orbitofrontal reality filtering (ORFi) - a specific failure to identify whether thoughts or memories refer to present reality or not. The latter is a function of the posterior orbitofrontal cortex and connected structures. This study examined the mechanisms and anatomical basis of disorientation in an unselected group of patients with first-ever subacute brain injury.

METHODS

Participants hospitalized for neurorehabilitation were asked to participate in this observational cohort study if they had first-ever organic hemispheric brain dysfunction as evident in a localizable brain lesion or verbal amnesia (often without localizable brain damage). Orientation to time, place, situation and person was tested with a 20-items questionnaire. To identify the mechanisms of disorientation, we determined its correlations with executive tasks, verbal episodic memory, and ORFi in all patients. ORFi was examined with a continuous recognition task, which measures learning and item recognition in the first run, and ORFi as reflected in the increase of false positive responses in the second run (temporal context confusion). Lesions of patients having localizable brain damage were manually delineated and normalized before entering multivariate lesion-symptom-mapping (LSM) to determine anatomical predictors of orientation.

RESULTS

Eighty-four patients (61.1 ± 14.4 years, 29 women) were included. Among measures of memory and executive functioning, a step-wise regression retained temporal context confusion (R = -0.71, p < 0.0001), item recognition (R = 0.67, p < 0.0001) and delayed free recall (R = 0.63, p < 0.0001) as significant predictors of orientation. LSM was possible in 67 participants; it revealed an association of disorientation with damage of the right OFC and the bilateral head of the caudate nucleus.

CONCLUSION

Disorientation in non-confused, non-demented patients with first-ever brain damage is associated with impaired orbitofrontal reality filtering and memory dysfunction, but not with executive dysfunction. Its main anatomical determinant is damage to the orbitofrontal cortex and its subcortical relay, the head of the caudate.

Mapping spoken language and cognitive deficits in post-stroke aphasia

Aphasia is an acquired disorder caused by damage, most commonly due to stroke, to brain regions involved in speech and language. While language impairment is the defining symptom of aphasia, the co-occurrence of non-language cognitive deficits and their importance in predicting rehabilitation and recovery outcomes is well documented. However, people with aphasia (PWA) are rarely tested on higher-order cognitive functions, making it difficult for studies to associate these functions with a consistent lesion correlate. Broca's area is a particular brain region of interest that has long been implicated in speech and language production. Contrary to classic models of speech and language, cumulative evidence shows that Broca's area and surrounding regions in the left inferior frontal cortex (LIFC) are involved in, but not specific to, speech production. In this study we aimed to explore the brain-behaviour relationships between tests of cognitive skill and language abilities in thirty-six adults with long-term speech production deficits caused by post-stroke aphasia. Our findings suggest that non-linguistic cognitive functions, namely executive functions and verbal working memory, explain more of the behavioural variance in PWA than classical language models imply. Additionally, lesions to the LIFC, including Broca's area, were associated with non-linguistic executive (dys)function, suggesting that lesions to this area are associated with non-language-specific higher-order cognitive deficits in aphasia. Whether executive (dys)function - and its neural correlate in Broca's area - contributes directly to PWA's language production deficits or simply co-occurs with it, adding to communication difficulties, remains unclear. These findings support contemporary models of speech production that place language processing within the context of domain-general perception, action and conceptual knowledge. An understanding of the covariance between language and non-language deficits and their underlying neural correlates will inform better targeted aphasia treatment and outcomes.

Bayesian lesion-deficit inference with Bayes factor mapping: Key advantages, limitations, and a toolbox

Statistical lesion-symptom mapping is largely dominated by frequentist approaches with null hypothesis significance testing. They are popular for mapping functional brain anatomy but are accompanied by some challenges and limitations. The typical analysis design and the structure of clinical lesion data are linked to the multiple comparison problem, an association problem, limitations to statistical power, and a lack of insights into evidence for the null hypothesis. Bayesian lesion deficit inference (BLDI) could be an improvement as it collects evidence for the null hypothesis, i.e. the absence of effects, and does not accumulate α-errors with repeated testing. We implemented BLDI by Bayes factor mapping with Bayesian t-tests and general linear models and evaluated its performance in comparison to frequentist lesion-symptom mapping with a permutation-based family-wise error correction. We mapped the voxel-wise neural correlates of simulated deficits in an in-silico-study with 300 stroke patients, and the voxel-wise and disconnection-wise neural correlates of phonemic verbal fluency and constructive ability in 137 stroke patients. Both the performance of frequentist and Bayesian lesion-deficit inference varied largely across analyses. In general, BLDI could find areas with evidence for the null hypothesis and was statistically more liberal in providing evidence for the alternative hypothesis, i.e. the identification of lesion-deficit associations. BLDI performed better in situations in which the frequentist method is typically strongly limited, for example with on average small lesions and in situations with low power, where BLDI also provided unprecedented transparency in terms of the informative value of the data. On the other hand, BLDI suffered more from the association problem, which led to a pronounced overshoot of lesion-deficit associations in analyses with high statistical power. We further implemented a new approach to lesion size control, adaptive lesion size control, that, in many situations, was able to counter the limitations imposed by the association problem, and increased true evidence both for the null and the alternative hypothesis. In summary, our results suggest that BLDI is a valuable addition to the method portfolio of lesion-deficit inference with some specific and exclusive advantages: it deals better with smaller lesions and low statistical power (i.e. small samples and effect sizes) and identifies regions with absent lesion-deficit associations. However, it is not superior to established frequentist approaches in all respects and therefore not to be seen as a general replacement. To make Bayesian lesion-deficit inference widely accessible, we published an R toolkit for the analysis of voxel-wise and disconnection-wise data.

Disconnection in a left-hemispheric temporo-parietal network impairs multiplication fact retrieval

Arithmetic fact retrieval has been suggested to recruit a left-lateralized network comprising perisylvian language areas, parietal areas such as the angular gyrus (AG), and non-neocortical structures such as the hippocampus. However, the underlying white matter connectivity of these areas has not been evaluated systematically so far. Using simple multiplication problems, we evaluated how disconnections in parietal brain areas affected arithmetic fact retrieval following stroke. We derived disconnectivity measures by jointly considering data from n = 73 patients with acute unilateral lesions in either hemisphere and a white-matter tractography atlas (HCP-842) using the Lesion Quantification Toolbox (LQT). Whole-brain voxel-based analysis indicated a left-hemispheric cluster of white matter fibers connecting the AG and superior temporal areas to be associated with a fact retrieval deficit. Subsequent analyses of direct gray-to-gray matter disconnections revealed that disconnections of additional left-hemispheric areas (e.g., between the superior temporal gyrus and parietal areas) were significantly associated with the observed fact retrieval deficit. Results imply that disconnections of parietal areas (i.e., the AG) with language-related areas (i.e., superior and middle temporal gyri) seem specifically detrimental to arithmetic fact retrieval. This suggests that arithmetic fact retrieval recruits a widespread left-hemispheric network and emphasizes the relevance of white matter connectivity for number processing.

Use of multi-perturbation Shapley analysis in lesion studies of functional networks: The case of upper limb paresis

Understanding the impact of variation in lesion topography on the expression of functional impairments following stroke is important, as it may pave the way to modeling structure-function relations in statistical terms while pointing to constraints for adaptive remapping and functional recovery. Multi-perturbation Shapley-value analysis (MSA) is a relatively novel game-theoretical approach for multivariate lesion-symptom mapping. In this methodological paper, we provide a comprehensive explanation of MSA. We use synthetic data to assess the method's accuracy and perform parameter optimization. We then demonstrate its application using a cohort of 107 first-event subacute stroke patients, assessed for upper limb (UL) motor impairment (Fugl-Meyer Assessment scale). Under the conditions tested, MSA could correctly detect simulated ground-truth lesion-symptom relationships with a sensitivity of 75% and specificity of ~90%. For real behavioral data, MSA disclosed a strong hemispheric effect in the relative contribution of specific regions-of-interest (ROIs): poststroke UL motor function was mostly contributed by damage to ROIs associated with movement planning (supplementary motor cortex and superior frontal gyrus) following left-hemispheric damage (LHD) and by ROIs associated with movement execution (primary motor and somatosensory cortices and the ventral brainstem) following right-hemispheric damage (RHD). Residual UL motor ability following LHD was found to depend on a wider array of brain structures compared to the residual motor ability of RHD patients. The results demonstrate that MSA can provide a unique insight into the relative importance of different hubs in neural networks, which is difficult to obtain using standard univariate methods.

Tubers Affecting the Fusiform Face Area Are Associated with Autism Diagnosis

OBJECTIVE

Tuberous sclerosis complex (TSC) is associated with focal brain "tubers" and a high incidence of autism spectrum disorder (ASD). The location of brain tubers associated with autism may provide insight into the neuroanatomical substrate of ASD symptoms.

METHODS

We delineated tuber locations for 115 TSC participants with ASD (n = 31) and without ASD (n = 84) from the Tuberous Sclerosis Complex Autism Center of Excellence Research Network. We tested for associations between ASD diagnosis and tuber burden within the whole brain, specific lobes, and at 8 regions of interest derived from the ASD neuroimaging literature, including the anterior cingulate, orbitofrontal and posterior parietal cortices, inferior frontal and fusiform gyri, superior temporal sulcus, amygdala, and supplemental motor area. Next, we performed an unbiased data-driven voxelwise lesion symptom mapping (VLSM) analysis. Finally, we calculated the risk of ASD associated with positive findings from the above analyses.

RESULTS

There were no significant ASD-related differences in tuber burden across the whole brain, within specific lobes, or within a priori regions derived from the ASD literature. However, using VLSM analysis, we found that tubers involving the right fusiform face area (FFA) were associated with a 3.7-fold increased risk of developing ASD.

INTERPRETATION

Although TSC is a rare cause of ASD, there is a strong association between tuber involvement of the right FFA and ASD diagnosis. This highlights a potentially causative mechanism for developing autism in TSC that may guide research into ASD symptoms more generally. ANN NEUROL 2023;93:577-590.

The neuroanatomy of visuospatial neglect: A systematic review and analysis of lesion-mapping methodology

While visuospatial neglect is commonly associated with damage to the right posterior parietal cortex, neglect is an anatomically heterogenous syndrome. This project presents a systematic review of 34 lesion-mapping studies reporting on the anatomical correlates of neglect. Specifically, the reported correlates of egocentric versus allocentric, acute versus chronic, personal versus extra-personal, and left versus right hemisphere neglect are summarised. The quality of each included lesion-mapping analysis was then evaluated to identify methodological factors which may help account for the reported variance in correlates of neglect. Overall, the existing literature strongly suggests that egocentric and allocentric neglect represent anatomically dissociable conditions and that the anatomy of these conditions may not be entirely homologous across hemispheres. Studies which have compared the anatomy of acute versus chronic neglect have found that these conditions are associated with distinct lesion loci, while studies comparing the correlates of peripersonal/extrapersonal neglect are split as to whether these neglect subtypes are anatomically dissociable. The included studies employed a wide range of lesion-mapping analysis techniques, each producing results of varying quality and generalisability. This review concludes that the reported underlying anatomical correlates of heterogeneous visuospatial neglect vary considerably. Future, high quality studies are needed to investigate patterns of disconnection associated with clearly defined forms of visuospatial neglect in large and representative samples.

Presurgical Executive Functioning in Low-Grade Glioma Patients Cannot Be Topographically Mapped

Executive dysfunctions have a high prevalence in low-grade glioma patients and may be the result of structural disconnections of particular subcortical tracts and/or networks. However, little research has focused on preoperative low-grade glioma patients. The frontotemporoparietal network has been closely linked to executive functions and is substantiated by the superior longitudinal fasciculus. The aim of this study was to investigate their role in executive functions in low-grade glioma patients. Patients from two neurological centers were included with IDH-mutated low-grade gliomas. The sets of preoperative predictors were (i) distance between the tumor and superior longitudinal fasciculus, (ii) structural integrity of the superior longitudinal fasciculus, (iii) overlap between tumor and cortical networks, and (iv) white matter disconnection of the same networks. Linear regression and random forest analyses were performed. The group of 156 patients demonstrated significantly lower performance than normative samples and had a higher prevalence of executive impairments. However, both regression and random forest analyses did not demonstrate significant results, meaning that neither structural, cortical network overlap, nor network disconnection predictors explained executive performance. Overall, our null results indicate that there is no straightforward topographical explanation of executive performance in low-grade glioma patients. We extensively discuss possible explanations, including plasticity-induced network-level equipotentiality. Finally, we stress the need for the development of novel methods to unveil the complex and interacting mechanisms that cause executive deficits in low-grade glioma patients.

A presurgical voxel-wise predictive model for cerebellar mutism syndrome in children with posterior fossa tumors

BACKGROUND

This study aimed to investigate cerebellar mutism syndrome (CMS)-related voxels and build a voxel-wise predictive model for CMS.

METHODS

From July 2013 to January 2022, 188 pediatric patients diagnosed with posterior fossa tumor were included in this study, including 38 from a prospective cohort recruited between 2020 and January 2022, and the remaining from a retrospective cohort recruited in July 2013-Aug 2020. The retrospective cohort was divided into the training and validation sets; the prospective cohort served as a prospective validation set. Voxel-based lesion symptoms were assessed to identify voxels related to CMS, and a predictive model was constructed and tested in the validation and prospective validation sets.

RESULTS

No significant differences were detected among these three data sets in CMS rate, gender, age, tumor size, tumor consistency, presence of hydrocephalus and paraventricular edema. Voxels related to CMS were mainly located in bilateral superior and inferior cerebellar peduncles and the superior part of the cerebellum. The areas under the curves for the model in the training, validation and prospective validation sets were 0.889, 0.784 and 0.791, respectively.

CONCLUSIONS

Superior and inferior cerebellar peduncles and the superior part of the cerebellum were related to CMS, especially the right side, and voxel-based lesion-symptom analysis could provide valuable predictive information before surgery.

Clinical presentation and neural correlates of stroke-associated spatial delusions

BACKGROUND AND PURPOSE

Incongruent beliefs about self-localization in space markedly disturb patients' behavior. Spatial delusions, or reduplicative paramnesias, are characterized by a firm conviction of place reduplication, transformation, or mislocation. Evidence suggests they are frequent after right hemisphere lesions, but comprehensive information about their clinical features is lacking.

METHODS

We prospectively screened 504 acute right-hemisphere stroke patients for the presence of spatial delusions. Their behavioral and clinical features were systematically assessed. Then, we analyzed the correlation of their duration with the magnitude of structural disruption of belief-associated functional networks. Finally, we described the syndrome subtypes and evaluated whether the clinical categorization would be predicted by the structural disruption of familiarity-associated functional networks using an unsupervised k-means clustering algorithm.

RESULTS

Sixty patients with spatial delusions were identified and fully characterized. Most (93%) localized the misidentified places closer to home than the hospital. The median time duration was 3 days (interquartile range = 1-7 days), and it was moderately correlated with the magnitude of structural-functional decoupling of belief-associated functional networks (r = 0.39, p = 0.02; beta coefficient regressing for lesion volume = 3.18, p = 0.04). Each clinical subtype had characteristic response patterns, which were reported, and representative examples were provided. Clustering based on structural disruption of familiarity- and unfamiliarity-associated functional networks poorly matched the clinical categorization (lesion: Rand index = 0.47; structural disconnection: Rand index = 0.51).

CONCLUSIONS

The systematic characterization of the peculiar clinical features of stroke-associated spatial delusions may improve the syndrome diagnosis and clinical approaches. The novel evidence about their neural correlates fosters the clarification of the pathophysiology of delusional misidentifications.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

Leveraging manifold learning techniques to explore white matter anomalies: An application of the TractLearn pipeline in epilepsy

An accurate description of brain white matter anatomy in vivo remains a challenge. However, technical progress allows us to analyze structural variations in an increasingly sophisticated way. Current methods of processing diffusion MRI data now make it possible to correct some limiting biases. In addition, the development of statistical learning algorithms offers the opportunity to analyze the data from a new perspective. We applied newly developed tractography models to extract quantitative white matter parameters in a group of patients with chronic temporal lobe epilepsy. Furthermore, we implemented a statistical learning workflow optimized for the MRI diffusion data - the TractLearn pipeline - to model inter-individual variability and predict structural changes in patients. Finally, we interpreted white matter abnormalities in the context of several other parameters reflecting clinical status, as well as neuronal and cognitive functioning for these patients. Overall, we show the relevance of such a diffusion data processing pipeline for the evaluation of clinical populations. The "global to fine scale" funnel statistical approach proposed in this study also contributes to the understanding of neuroplasticity mechanisms involved in refractory epilepsy, thus enriching previous findings.

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.

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.

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).

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.

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.

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.

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.

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.

Causal Prefrontal Contributions to Stop-Signal Task Performance in Humans

The frontal lobes have long been implicated in inhibitory control, but a full understanding of the underlying mechanisms remains elusive. The stop-signal task has been widely used to probe instructed response inhibition in cognitive neuroscience. The processes involved have been modeled and related to putative brain substrates. However, there has been surprisingly little human lesion research using this task, with the few existing studies implicating different prefrontal regions. Here, we tested the effects of focal prefrontal damage on stop-signal task performance in a large sample of people with chronic focal damage affecting the frontal lobes (n = 42) and demographically matched healthy individuals (n = 60). Patients with damage to the left lateral, right lateral, dorsomedial, or ventromedial frontal lobe had slower stop-signal RT compared to healthy controls. There were systematic differences in the patterns of impairment across frontal subgroups: Those with damage to the left or right lateral and dorsomedial frontal lobes, but not those with ventromedial frontal damage, were slower than controls to "go" as well as to stop. These findings suggest that multiple prefrontal regions make necessary but distinct contributions to stop-signal task performance. As a consequence, stop-signal RT slowing is not strongly localizing within the frontal lobes.

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.

Are visual working memory and episodic memory distinct processes? Insight from stroke patients by lesion-symptom mapping

Working memory and episodic memory are two different processes, although the nature of their interrelationship is debated. As these processes are predominantly studied in isolation, it is unclear whether they crucially rely on different neural substrates. To obtain more insight in this, 81 adults with sub-acute ischemic stroke and 29 elderly controls were assessed on a visual working memory task, followed by a surprise subsequent memory test for the same stimuli. Multivariate, atlas- and track-based lesion-symptom mapping (LSM) analyses were performed to identify anatomical correlates of visual memory. Behavioral results gave moderate evidence for independence between discriminability in working memory and subsequent memory, and strong evidence for a correlation in response bias on the two tasks in stroke patients. LSM analyses suggested there might be independent regions associated with working memory and episodic memory. Lesions in the right arcuate fasciculus were more strongly associated with discriminability in working memory than in subsequent memory, while lesions in the frontal operculum in the right hemisphere were more strongly associated with criterion setting in subsequent memory. These findings support the view that some processes involved in working memory and episodic memory rely on separate mechanisms, while acknowledging that there might also be shared processes.

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

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

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.

Tuber Locations Associated with Infantile Spasms Map to a Common Brain Network

OBJECTIVE

Approximately 50% of patients with tuberous sclerosis complex develop infantile spasms, a sudden onset epilepsy syndrome associated with poor neurological outcomes. An increased burden of tubers confers an elevated risk of infantile spasms, but it remains unknown whether some tuber locations confer higher risk than others. Here, we test whether tuber location and connectivity are associated with infantile spasms.

METHODS

We segmented tubers from 123 children with (n = 74) and without (n = 49) infantile spasms from a prospective observational cohort. We used voxelwise lesion symptom mapping to test for an association between spasms and tuber location. We then used lesion network mapping to test for an association between spasms and connectivity with tuber locations. Finally, we tested the discriminability of identified associations with logistic regression and cross-validation as well as statistical mediation.

RESULTS

Tuber locations associated with infantile spasms were heterogenous, and no single location was significantly associated with spasms. However, >95% of tuber locations associated with spasms were functionally connected to the globi pallidi and cerebellar vermis. These connections were specific compared to tubers in patients without spasms. Logistic regression found that globus pallidus connectivity was a stronger predictor of spasms (odds ratio [OR] = 1.96, 95% confidence interval [CI] = 1.10-3.50, p = 0.02) than tuber burden (OR = 1.65, 95% CI = 0.90-3.04, p = 0.11), with a mean receiver operating characteristic area under the curve of 0.73 (±0.1) during repeated cross-validation.

INTERPRETATION

Connectivity between tuber locations and the bilateral globi pallidi is associated with infantile spasms. Our findings lend insight into spasm pathophysiology and may identify patients at risk. ANN NEUROL 2021;89:726-739.

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.

Consequence of stroke for feature recall and binding in visual working memory

Visual memory for objects involves the integration, or binding, of individual features into a coherent representation. We used a novel approach to assess feature binding, using a delayed-reproduction task in combination with computational modeling and lesion analysis. We assessed stroke patients and neurotypical controls on a visual working memory task in which spatial arrays of colored disks were presented. After a brief delay, participants either had to report the color of one disk cued by its location or the location of one disk cued by its color. Our results demonstrate that, in the controls, report imprecision and swap errors (non-target reports) can be explained by a single source of variability. Stroke patients showed an overall decrease in memory precision for both color and location, with only limited evidence for deviations from the predicted relationship between report precision and swap errors. These deviations were primarily deficits in reporting items rather than selecting items based on the cue. Atlas-based lesion-symptom mapping showed that selection and reporting deficits, precision in reporting color, and precision in reporting location were associated with different lesion profiles. Deficits in binding are associated with lesions in the left somatosensory cortex, deficits in the precision of reporting color with bilateral fronto-parietal regions, and no anatomical substrates were identified for precision in reporting location. Our results converge with previous reports that working memory representations are widely distributed in the brain and can be found across sensory, parietal, temporal, and prefrontal cortices. Stroke patients demonstrate mostly subtle impairments in visual working memory, perhaps because representations from different areas in the brain can partly compensate for impaired encoding in lesioned areas. These findings contribute to understanding of the relation between memorizing features and their bound representations.

Support vector machine based aphasia classification of transcranial magnetic stimulation language mapping in brain tumor patients

Repetitive TMS (rTMS) allows for non-invasive and transient disruption of local neuronal functioning. We used machine learning approaches to assess whether brain tumor patients can be accurately classified into aphasic and non-aphasic groups using their rTMS language mapping results as input features. Given that each tumor affects the subject-specific language networks differently, resulting in heterogenous rTMS functional mappings, we propose the use of machine learning strategies to classify potential patterns of rTMS language mapping results. We retrospectively included 90 patients with left perisylvian world health organization (WHO) grade II-IV gliomas that underwent presurgical navigated rTMS language mapping. Within our cohort, 29 of 90 (32.2%) patients suffered from at least mild aphasia as shown in the Aachen Aphasia Test based Berlin Aphasia Score (BAS). After spatial normalization to MNI 152 of all rTMS spots, we calculated the error rate (ER) in each stimulated cortical area (28 regions of interest, ROI) by automated anatomical labeling parcellation (AAL3) and IIT. We used a support vector machine (SVM) to classify significant areas in relation to aphasia. After feeding the ROIs into the SVM model, it revealed that in addition to age (w = 2.98), the ERs of the left supramarginal gyrus (w = 3.64), left inferior parietal gyrus (w = 2.28) and right pars triangularis (w = 1.34) contributed more than other features to the model. The model's sensitivity was 86.2%, the specificity was 82.0%, the overall accuracy was 85.5% and the AUC was 89.3%. Our results demonstrate an increased vulnerability of right inferior pars triangularis to rTMS in aphasic patients due to left perisylvian gliomas. This finding points towards a functional relevant involvement of the right pars triangularis in response to aphasia. The tumor location feature, specified by calculating overlaps with white and grey matter atlases, did not affect the SVM model. The left supramarginal gyrus as a feature improved our SVM model the most. Additionally, our results could point towards a decreasing potential for neuroplasticity with age.

Multimodal comprehension in left hemisphere stroke patients

Hand gestures, imagistically related to the content of speech, are ubiquitous in face-to-face communication. Here we investigated people with aphasia's (PWA) processing of speech accompanied by gestures using lesion-symptom mapping. Twenty-nine PWA and 15 matched controls were shown a picture of an object/action and then a video-clip of a speaker producing speech and/or gestures in one of the following combinations: speech-only, gesture-only, congruent speech-gesture, and incongruent speech-gesture. Participants' task was to indicate, in different blocks, whether the picture and the word matched (speech task), or whether the picture and the gesture matched (gesture task). Multivariate lesion analysis with Support Vector Regression Lesion-Symptom Mapping (SVR-LSM) showed that benefit for congruent speech-gesture was associated with 1) lesioned voxels in anterior fronto-temporal regions including inferior frontal gyrus (IFG), and sparing of posterior temporal cortex and lateral temporal-occipital regions (pTC/LTO) for the speech task, and 2) conversely, lesions to pTC/LTO and sparing of anterior regions for the gesture task. The two tasks did not share overlapping voxels. Costs from incongruent speech-gesture pairings were associated with lesioned voxels in these same anterior (for the speech task) and posterior (for the gesture task) regions, but crucially, also shared voxels in superior temporal gyrus (STG) and middle temporal gyrus (MTG), including the anterior temporal lobe. These results suggest that IFG and pTC/LTO contribute to extracting semantic information from speech and gesture, respectively; however, they are not causally involved in integrating information from the two modalities. In contrast, regions in anterior STG/MTG are associated with performance in both tasks and may thus be critical to speech-gesture integration. These conclusions are further supported by associations between performance in the experimental tasks and performance in tests assessing lexical-semantic processing and gesture recognition.

White matter hyperintensities at critical crossroads for executive function and verbal abilities in small vessel disease

The presence of white matter lesions in patients with cerebral small vessel disease (SVD) is among the main causes of cognitive decline. We investigated the relation between white matter hyperintensity (WMH) locations and executive and language abilities in 442 SVD patients without dementia with varying burden of WMH. We used Stroop Word Reading, Stroop Color Naming, Stroop Color‐Word Naming, and Category Fluency as language measures with varying degrees of executive demands. The Symbol Digit Modalities Test (SDMT) was used as a control task, as it measures processing speed without requiring language use or verbal output. A voxel‐based lesion–symptom mapping (VLSM) approach was used, corrected for age, sex, education, and lesion volume. VLSM analyses revealed statistically significant clusters for tests requiring language use, but not for SDMT. Worse scores on all tests were associated with WMH in forceps minor, thalamic radiations and caudate nuclei. In conclusion, an association was found between WMH in a core frontostriatal network and executive‐verbal abilities in SVD, independent of lesion volume and processing speed. This circuitry underlying executive‐language functioning might be of potential clinical importance for elderly with SVD. More detailed language testing is required in future research to elucidate the nature of language production difficulties in SVD.