Multivariate lesion symptom mapping for predicting trajectories of recovery from aphasia
Ontology highlight
ABSTRACT:
SUBMITTER:
PROVIDER: S-EPMC10873140 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Multivariate lesion-symptom mapping (MLSM) considers lesion information across the entire brain to predict impairments. The strength of this approach is also its weakness-considering many brain features together synergistically can uncover complex brain-behavior relationships but exposes a high-dimensional feature space that a model is expected to learn. Successfully distinguishing between features in this landscape can be difficult for models, particularly in the presence of irrelevant or redundant features. Here, we propose stable multivariate lesion-symptom mapping (sMLSM), which integrates the identification of reliable features with stability selection into conventional MLSM and describe our open-source MATLAB implementation. Usage is showcased with our publicly available dataset of chronic stroke survivors (N=167) and further validated in our independent public acute stroke dataset (N = 1106). We demonstrate that sMLSM eliminates inconsistent features highlighted by MLSM, reduces variation in feature weights, enables the model to learn more complex patterns of brain damage, and improves model accuracy for predicting aphasia severity in a way that tends to be robust regarding the choice of parameters for identifying reliable features. Critically, sMLSM more consistently outperforms predictions based on lesion size alone. This advantage is evident starting at modest sample sizes (N>75). Spatial distribution of feature importance is different in sMLSM, which highlights the features identified by univariate lesion symptom mapping while also implicating select regions emphasized by MLSM. Beyond improved prediction accuracy, sMLSM can offer deeper insight into reliable biomarkers of impairment, informing our understanding of neurobiology.
| S-EPMC11449259 | biostudies-literature
Project description:Sentence structure, or syntax, is potentially a uniquely creative aspect of the human mind. Neuropsychological experiments in the 1970s suggested parallel syntactic production and comprehension deficits in agrammatic Broca's aphasia, thought to result from damage to syntactic mechanisms in Broca's area in the left frontal lobe. This hypothesis was sometimes termed overarching agrammatism, converging with developments in linguistic theory concerning central syntactic mechanisms supporting language production and comprehension. However, the evidence supporting an association among receptive syntactic deficits, expressive agrammatism, and damage to frontal cortex is equivocal. In addition, the relationship among a distinct grammatical production deficit in aphasia, paragrammatism, and receptive syntax has not been assessed. We used lesion-symptom mapping in three partially overlapping groups of left-hemisphere stroke patients to investigate these issues: grammatical production deficits in a primary group of 53 subjects and syntactic comprehension in larger sample sizes (N = 130, 218) that overlapped with the primary group. Paragrammatic production deficits were significantly associated with multiple analyses of syntactic comprehension, particularly when incorporating lesion volume as a covariate, but agrammatic production deficits were not. The lesion correlates of impaired performance of syntactic comprehension were significantly associated with damage to temporal lobe regions, which were also implicated in paragrammatism, but not with the inferior and middle frontal regions implicated in expressive agrammatism. Our results provide strong evidence against the overarching agrammatism hypothesis. By contrast, our results suggest the possibility of an alternative grammatical parallelism hypothesis rooted in paragrammatism and a central syntactic system in the posterior temporal lobe.
| S-EPMC10631800 | biostudies-literature
Project description:Lesion-symptom mapping has become a cornerstone of neuroscience research seeking to localize cognitive function in the brain by examining the sequelae of brain lesions. Recently, multivariate lesion-symptom mapping methods have emerged, such as support vector regression, which simultaneously consider many voxels at once when determining whether damaged regions contribute to behavioral deficits (Zhang, Kimberg, Coslett, Schwartz, & Wang, ). Such multivariate approaches are capable of identifying complex dependences that traditional mass-univariate approach cannot. Here, we provide a new toolbox for support vector regression lesion-symptom mapping (SVR-LSM) that provides a graphical interface and enhances the flexibility and rigor of analyses that can be conducted using this method. Specifically, the toolbox provides cluster-level family-wise error correction via permutation testing, the capacity to incorporate arbitrary nuisance models for behavioral data and lesion data and makes available a range of lesion volume correction methods including a new approach that regresses lesion volume out of each voxel in the lesion maps. We demonstrate these new tools in a cohort of chronic left-hemisphere stroke survivors and examine the difference between results achieved with various lesion volume control methods. A strong bias was found toward brain wide lesion-deficit associations in both SVR-LSM and traditional mass-univariate voxel-based lesion symptom mapping when lesion volume was not adequately controlled. This bias was corrected using three different regression approaches; among these, regressing lesion volume out of both the behavioral score and the lesion maps provided the greatest sensitivity in analyses.
| S-EPMC6647024 | biostudies-literature
Project description:BackgroundAphasia is one of the most common causes of post-stroke disabilities. As the symptoms and impact of post-stroke aphasia are heterogeneous, it is important to understand how topographical lesion heterogeneity in patients with aphasia is associated with different domains of language impairments. Here, we aim to provide a comprehensive overview of neuroanatomical basis in post-stroke aphasia through coordinate based meta-analysis of voxel-based lesion-symptom mapping studies.MethodsWe performed a meta-analysis of lesion-symptom mapping studies in post-stroke aphasia. We obtained coordinate-based structural neuroimaging data for 2,007 individuals with aphasia from 25 studies that met predefined inclusion criteria.ResultsOverall, our results revealed that the distinctive patterns of lesions in aphasia are associated with different language functions and tasks. Damage to the insular-motor areas impaired speech with preserved comprehension and a similar pattern was observed when the lesion covered the insular-motor and inferior parietal lobule. Lesions in the frontal area severely impaired speaking with relatively good comprehension. The repetition-selective deficits only arise from lesions involving the posterior superior temporal gyrus. Damage in the anterior-to-posterior temporal cortex was associated with semantic deficits.ConclusionThe association patterns of lesion topography and specific language deficits provide key insights into the specific underlying language pathways. Our meta-analysis results strongly support the dual pathway model of language processing, capturing the link between the different symptom complexes of aphasias and the different underlying location of damage.
| S-EPMC9112051 | biostudies-literature
Project description:Connectome-based lesion-symptom mapping relates behavioural impairments to disruption of structural brain connectivity. Connectome-based lesion-symptom mapping can be based on different approaches (diffusion MRI versus lesion mask), network scales (whole brain versus regions of interest) and measure types (tract-based, parcel-based, or network-based metrics). We evaluated the similarity of different connectome-based lesion-symptom mapping processing choices and identified factors that influence the results using multiverse analysis-the strategy of conducting and displaying the results of all reasonable processing choices. Metrics derived from lesion masks and diffusion-weighted images were tested for association with Boston Naming Test and Token Test performance in a sample of 50 participants with aphasia following left hemispheric stroke. 'Direct' measures were derived from diffusion-weighted images. 'Indirect' measures were derived by overlaying lesion masks on a white matter atlas. Parcel-based connectomes were constructed for the whole brain and regions of interest (14 language-relevant parcels). Numerous tract-based and network-based metrics were calculated. There was a high discrepancy across processing approaches (diffusion-weighted images versus lesion masks), network scales (whole brain versus regions of interest) and metric types. Results indicate weak correlations and different connectome-based lesion-symptom mapping results across the processing choices. Substantial methodological work is needed to validate the various decision points that arise when conducting connectome-based lesion-symptom mapping analyses. Multiverse analysis is a useful strategy for evaluating the similarity across different processing choices in connectome-based lesion-symptom mapping.
| S-EPMC11420983 | biostudies-literature
Project description:Lesion location is an important determinant for post-stroke cognitive impairment. Although several 'strategic' brain regions have previously been identified, a comprehensive map of strategic brain regions for post-stroke cognitive impairment is lacking due to limitations in sample size and methodology. We aimed to determine strategic brain regions for post-stroke cognitive impairment by applying multivariate lesion-symptom mapping in a large cohort of 410 acute ischemic stroke patients. Montreal Cognitive Assessment at three to six months after stroke was used to assess global cognitive functioning and cognitive domains (memory, language, attention, executive and visuospatial function). The relation between infarct location and cognition was assessed in multivariate analyses at the voxel-level and the level of regions of interest using support vector regression. These two assumption-free analyses consistently identified the left angular gyrus, left basal ganglia structures and the white matter around the left basal ganglia as strategic structures for global cognitive impairment after stroke. A strategic network involving several overlapping and domain-specific cortical and subcortical structures was identified for each of the cognitive domains. Future studies should aim to develop even more comprehensive infarct location-based models for post-stroke cognitive impairment through multicenter studies including thousands of patients.
| S-EPMC6092771 | biostudies-literature
Project description:Stroke has a deleterious impact on quality of life. However, it is less well known if stroke lesions in different brain regions are associated with reduced quality of life (QoL). We therefore investigated this association by multivariate lesion-symptom mapping. We analyzed magnetic resonance imaging and clinical data from the WAKE-UP trial. European Quality of Life 5 Dimensions (EQ-5D) 3 level questionnaires were completed 90 days after stroke. Lesion symptom mapping was performed using a multivariate machine learning algorithm (support vector regression) based on stroke lesions 22-36 h after stroke. Brain regions with significant associations were explored in reference to white matter tracts. Of 503 randomized patients, 329 were included in the analysis (mean age 65.4 years, SD 11.5; median NIHSS = 6, IQR 4-9; median EQ-5D score 90 days after stroke 1, IQR 0-4, median lesion volume 3.3 ml, IQR 1.1-16.9 ml). After controlling for lesion volume, significant associations between lesions and EQ-5D score were detected for the right putamen, and internal capsules of both hemispheres. Multivariate lesion inference analysis revealed an association between injuries of the cortico-spinal tracts with worse self-reported quality of life 90 days after stroke in comparably small stroke lesions, extending previous reports of the association of striato-capsular lesions with worse functional outcome. Our findings are of value to identify patients at risk of impaired QoL after stroke.
| S-EPMC8241844 | biostudies-literature
Project description:Clinicians and scientists alike have long sought to predict the course and severity of chronic post-stroke cognitive and motor outcomes, as the ability to do so would inform treatment and rehabilitation strategies. However, it remains difficult to make accurate predictions about chronic post-stroke outcomes due, in large part, to high inter-individual variability in recovery and a reliance on clinical heuristics rather than empirical methods. The neuroanatomical location of a stroke is a key variable associated with long-term outcomes, and because lesion location can be derived from routinely collected clinical neuroimaging data there is an opportunity to use this information to make empirically based predictions about post-stroke deficits. For example, lesion location can be compared to statistically weighted multivariate lesion-behaviour maps of neuroanatomical regions that, when damaged, are associated with specific deficits based on aggregated outcome data from large cohorts. Here, our goal was to evaluate whether we can leverage lesion-behaviour maps based on data from two large cohorts of individuals with focal brain lesions to make predictions of 12-month cognitive and motor outcomes in an independent sample of stroke patients. Further, we evaluated whether we could augment these predictions by estimating the structural and functional networks disrupted in association with each lesion-behaviour map through the use of structural and functional lesion network mapping, which use normative structural and functional connectivity data from neurologically healthy individuals to elucidate lesion-associated networks. We derived these brain network maps using the anatomical regions with the strongest association with impairment for each cognitive and motor outcome based on lesion-behaviour map results. These peak regional findings became the 'seeds' to generate networks, an approach that offers potentially greater precision compared to previously used single-lesion approaches. Next, in an independent sample, we quantified the overlap of each lesion location with the lesion-behaviour maps and structural and functional lesion network mapping and evaluated how much variance each could explain in 12-month behavioural outcomes using a latent growth curve statistical model. We found that each lesion-deficit mapping modality was able to predict a statistically significant amount of variance in cognitive and motor outcomes. Both structural and functional lesion network maps were able to predict variance in 12-month outcomes beyond lesion-behaviour mapping. Functional lesion network mapping performed best for the prediction of language deficits, and structural lesion network mapping performed best for the prediction of motor deficits. Altogether, these results support the notion that lesion location and lesion network mapping can be combined to improve the prediction of post-stroke deficits at 12-months.
| S-EPMC9630711 | biostudies-literature
Project description:BackgroundIt remains widely accepted that spontaneous recovery from aphasia is largely limited to the first related factors. This has direct implications for acute and chronic interventions for aphasia. few months following stroke. A few recent studies challenge this view, revealing that some individuals' language abilities improve even during the chronic stage.AimsTo identify prognostic indicators of long-term aphasia recovery.Methods & proceduresEighteen people with aphasia initially evaluated in the chronic stage were retested at least one year later. The Western Aphasia Battery-Revised (WAB-R) Aphasia Quotient (AQ) was used to quantify changes in language impairment. Prognostic factors included those related to the patient (demographic, psychosocial), stroke (lesion volume and location), and treatment (medical, rehabilitative).Outcomes & resultsTwelve participants improved and 6 remained stable or declined. Linear regression analysis revealed that lesion volume predicted long-term language gains, with smaller lesions yielding greater improvements. Individuals who did not improve were more likely to have lesions encompassing critical frontal and temporoparietal cortical regions and interconnecting white matter pathways. Exploratory regression analysis of psychosocial and treatment-related factors revealed a positive relationship between improvement and satisfaction with life participation, and a negative relationship between improvement and perceived impairment severity. Critically, psychosocial and treatment-related factors significantly improved model fit over lesion volume, suggesting that these factors add predictive value to determining long-term aphasia prognosis.ConclusionsLong-term aphasia recovery is multidetermined by a combination of stroke-, psychosocial-, and treatment-related factors. This has direct implications for acute and chronic interventions for aphasia.
| S-EPMC9855303 | biostudies-literature
Project description:BackgroundPatients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the associations between executive, semantic, and language production functions.FindingsHere, we provide, for the first time, a set of complementary solutions for measuring the impact of a given lesion on the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesions, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency.ConclusionsThe combination of structural and functional connectivity together with cortical thickness estimates reveal the remote effects of brain lesions, provide for the identification of the affected networks, and strengthen our understanding of their relationship with cognitive and behavioral measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1].
| S-EPMC5863218 | biostudies-literature