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.

Lifting cognition: a meta-analysis of effects of resistance exercise on cognition.

The health benefits of resistance exercises are well established; however, the effects of resistance training on cognition are not as well understood. The purpose of this meta-analysis was to evaluate the evidence of resistance exercise's effects on cognition. A systematic search identified 24 studies that were included in the analyses. These articles ranged in the protocols utilized and in how they studied the effects of resistance training on cognition. Four primary analyses were carried out to assess the effects of resistance exercise on cognitive outcomes: (1) composite cognitive scores, (2) screening measures of cognitive impairment, (3) measures of executive functions, and (4) measures of working memory. Results revealed positive effects of resistance training on composite cognitive scores (SMD 0.71, 95% CI 0.30-1.12), screening measures of cognitive impairment (SMD 1.28, 95% CI 0.39-2.18), and executive functions (SMD 0.39, 95% CI 0.04-0.74), but no effect on measures of working memory (SMD 0.151, 95% CI - 0.21 to 0.51). High heterogeneity was observed in all analyses. Resistance training appears to have positive effects on cognition; however, future research will need to determine why the effects are so variable.

The cost of switching between taxonomic and thematic semantics.

Current models and theories of semantic knowledge primarily capture taxonomic relationships (DOG and WOLF) and largely do not address the role of thematic relationships in semantic knowledge (DOG and LEASH). Recent evidence suggests that processing or representation of thematic relationships may be distinct from taxonomic relationships. If taxonomic and thematic relations are distinct, then there should be a cost associated with switching between them even when the task remains constant. This hypothesis was tested using two different semantic-relatedness judgment tasks: Experiment 1 used a triads task and Experiment 2 used an oddball task. In both experiments, participants were faster to respond when the same relationship appeared on consecutive trials than when the relationship types were different, even though the task remained the same and the specific relations were different on each trial. These results are consistent with the theory that taxonomic and thematic relations rely on distinct processes or representations.

A Pupillometric Examination of Cognitive Control in Taxonomic and Thematic Semantic Memory.

Semantic cognition includes taxonomic and thematic relationships, as well as control systems to retrieve and manipulate semantic knowledge to suit specific tasks or contexts. A recent report (Thompson et al., 2017) suggested that retrieving thematic relationships (i.e., relations based on participation in the same event or scenarios) requires more effort or cognitive control, especially when the relevant relations are weak, than retrieving identity relations that are based on sensory-motor features. It is not clear whether the same contrast applies to the broader set of taxonomic relations, which are also based on shared sensory-motor features. In this study we tested cognitive control requirements of retrieving taxonomic and thematic knowledge using a physiological measure of cognitive effort: pupil dilation. Participants completed a semantic relatedness judgement task that manipulated semantic type (thematic vs. taxonomic) and relatedness strength (high vs. low) of word pairs. Cognitive control in the similarity task was examined using task-evoked pupillary responses (TEPRs), as well as standard behavioral measures (reaction times and accuracy). Compared with high-strength relations, low-strength semantic relations elicited larger TERPs, slower reaction times, and lower accuracy, consistent with higher control demands. Compared to thematic relations, taxonomic relations also elicited larger TERPs and slower reaction times, suggesting that retrieving taxonomic relations required more cognitive effort. Critically, our pupillometric data indicated that controlled processing was particularly important for low-strength taxonomic pairs rather than low-strength thematic pairs. These findings indicate that semantic control demands are primarily determined by relatedness strength, not whether the relationship is taxonomic or thematic.

Corrections for multiple comparisons in voxel-based lesion-symptom mapping.

Voxel-based lesion-symptom mapping (VLSM) is an important method for basic and translational human neuroscience research. VLSM leverages modern neuroimaging analysis techniques to build on the classic approach of examining the relationship between location of brain damage and cognitive deficits. Testing an association between deficit severity and lesion status in each voxel involves very many individual tests and requires statistical correction for multiple comparisons. Several strategies have been adapted from analysis of functional neuroimaging data, though VLSM faces a more difficult trade-off between avoiding false positives and statistical power (missing true effects). We used simulated and real deficit scores from a sample of approximately 100 individuals with left hemisphere stroke to evaluate two such permutation-based approaches. Using permutation to set a minimum cluster size identified a region that systematically extended well beyond the true region, making it ill-suited to identifying brain-behavior relationships. In contrast, generalizing the standard permutation-based family-wise error correction approach provided a principled way to balance false positives and false negatives. Comparison with the widely-used parametric false discovery rate (FDR) correction showed that FDR produces anti-conservative results at smaller sample sizes (N = 30-60). An implementation of the continuous permutation-based FWER correction method described here is included in the lesymap package for lesion-symptom mapping (https://dorianps.github.io/LESYMAP/).

Taxonomic and thematic semantic systems.

Object concepts are critical for nearly all aspects of human cognition, from perception tasks like object recognition, to understanding and producing language, to making meaningful actions. Concepts can have 2 very different kinds of relations: similarity relations based on shared features (e.g., dog-bear), which are called "taxonomic" relations, and contiguity relations based on co-occurrence in events or scenarios (e.g., dog-leash), which are called "thematic" relations. Here, we report a systematic review of experimental psychology and cognitive neuroscience evidence of this distinction in the structure of semantic memory. We propose 2 principles that may drive the development of distinct taxonomic and thematic semantic systems: differences between which features determine taxonomic versus thematic relations, and differences in the processing required to extract taxonomic versus thematic relations. This review brings together distinct threads of behavioral, computational, and neuroscience research on semantic memory in support of a functional and neural dissociation, and defines a framework for future studies of semantic memory. (PsycINFO Database Record