A Rose by Any Other Name: Mapping Taxonomic and Thematic Naming Errors Poststroke.

Understanding the neurobiology of semantic knowledge is a major goal of cognitive neuroscience. Taxonomic and thematic semantic knowledge are represented differently within the brain's conceptual networks, but the specific neural mechanisms remain unclear. Some neurobiological models propose that the anterior temporal lobe is an important hub for taxonomic knowledge, whereas the TPJ is especially involved in the representation of thematic knowledge. However, recent studies have provided divergent evidence. In this context, we investigated the neural correlates of taxonomic and thematic confrontation naming errors in 79 people with aphasia. We used three complementary lesion-symptom mapping (LSM) methods to investigate how structure and function in both spared and impaired brain regions relate to taxonomic and thematic naming errors. Voxel-based LSM mapped brain damage, activation-based LSM mapped BOLD signal in surviving tissue, and network-based LSM mapped white matter subnetwork integrity to error type. Voxel- and network-based lesion symptom mapping provided converging evidence that damage/disruption of the left mid-to-anterior temporal lobe was associated with a greater proportion of thematic naming errors. Activation-based lesion symptom mapping revealed that higher BOLD signal in the left anterior temporal lobe during an in-house naming task was associated with a greater proportion of taxonomic errors on the Philadelphia Naming Test administered outside of the scanner. A lower BOLD signal in the bilateral angular gyrus, precuneus, and right inferior frontal cortex was associated with a greater proportion of taxonomic errors. These findings provide novel evidence that damage to the anterior temporal lobe is especially related to thematic naming errors.

The Influence of Structural Brain Changes on Cognition in the Context of Healthy Aging: Exploring Mediation Effects Through gBAT-The Graphical Brain Association Tool.

The contribution of age-related structural brain changes to the well-established link between aging and cognitive decline is not fully defined. While both age-related regional brain atrophy and cognitive decline have been extensively studied, the specific mediating role of age-related regional brain atrophy on cognitive functions is unclear. This study introduces an open-source software tool with a graphical user interface that streamlines advanced whole-brain mediation analyses, enabling researchers to systematically explore how the brain acts as a mediator in relationships between various behavioral and health outcomes. The tool is showcased by investigating regional brain volume as a mediator to determine the contribution of age-related brain volume loss toward cognition in healthy aging. We analyzed regional brain volumes and cognitive testing data (Montreal Cognitive Assessment [MoCA]) from a cohort of 131 neurologically healthy adult participants (mean age 50 ± 20.8 years, range 20-79, 73% females) drawn from the Aging Brain Cohort Study at the University of South Carolina. Using our open-source tool developed for evaluating brain-behavior associations across the brain and optimized for exploring mediation effects, we conducted a series of mediation analyses using participant age as the predictor variable, total MoCA and MoCA subtest scores as the outcome variables, and regional brain volume as potential mediators. Age-related atrophy within specific anatomical networks was found to mediate the relationship between age and cognition across multiple cognitive domains. Specifically, atrophy in bilateral frontal, parietal, and occipital areas, along with widespread subcortical regions mediated the effect of age on total MoCA scores. Various MoCA subscores were influenced by age through atrophy in distinct brain regions. These involved prefrontal regions, sensorimotor cortex, and parieto-occipital areas for executive function subscores, prefrontal and temporo-occipital regions, along with the caudate nucleus for attention and concentration subscores, frontal and parieto-occipital areas, alongside connecting subcortical areas such as the optic tract for visuospatial subscores and frontoparietal areas for language subscores. Brain-based mediation analysis offers a causal framework for evaluating the mediating role of brain structure on the relationship between age and cognition and provides a more nuanced understanding of cognitive aging than previously possible. By validating the applicability and effectiveness of this approach and making it openly available to the scientific community, we facilitate the exploration of causal mechanisms between variables mediated by the brain.

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

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

The Two Word Test as a semantic benchmark for large language models.

Large language models (LLMs) have shown remarkable abilities recently, including passing advanced professional exams and demanding benchmark tests. This performance has led many to suggest that they are close to achieving humanlike or "true" understanding of language, and even artificial general intelligence (AGI). Here, we provide a new open-source benchmark, the Two Word Test (TWT), that can assess semantic abilities of LLMs using two-word phrases in a task that can be performed relatively easily by humans without advanced training. Combining multiple words into a single concept is a fundamental linguistic and conceptual operation routinely performed by people. The test requires meaningfulness judgments of 1768 noun-noun combinations that have been rated as meaningful (e.g., baby boy) or as having low meaningfulness (e.g., goat sky) by human raters. This novel test differs from existing benchmarks that rely on logical reasoning, inference, puzzle-solving, or domain expertise. We provide versions of the task that probe meaningfulness ratings on a 0-4 scale as well as binary judgments. With both versions, we conducted a series of experiments using the TWT on GPT-4, GPT-3.5, Claude-3-Optus, and Gemini-1-Pro-001. Results demonstrated that, compared to humans, all models performed relatively poorly at rating meaningfulness of these phrases. GPT-3.5-turbo, Gemini-1.0-Pro-001 and GPT-4-turbo were also unable to make binary discriminations between sensible and nonsense phrases, with these models consistently judging nonsensical phrases as making sense. Claude-3-Opus made a substantial improvement in binary discrimination of combinatorial phrases but was still significantly worse than human performance. The TWT can be used to understand and assess the limitations of current LLMs, and potentially improve them. The test also reminds us that caution is warranted in attributing "true" or human-level understanding to LLMs based only on tests that are challenging for humans.

Discourse- and lesion-based aphasia quotient estimation using machine learning.

Discourse is a fundamentally important aspect of communication, and discourse production provides a wealth of information about linguistic ability. Aphasia commonly affects, in multiple ways, the ability to produce discourse. Comprehensive aphasia assessments such as the Western Aphasia Battery-Revised (WAB-R) are time- and resource-intensive. We examined whether discourse measures can be used to estimate WAB-R Aphasia Quotient (AQ), and whether this can serve as an ecologically valid, less resource-intensive measure. We used features extracted from discourse tasks using three AphasiaBank prompts involving expositional (picture description), story narrative, and procedural discourse. These features were used to train a machine learning model to predict the WAB-R AQ. We also compared and supplemented the model with lesion location information from structural neuroimaging. We found that discourse-based models could estimate AQ well, and that they outperformed models based on lesion features. Addition of lesion features to the discourse features did not improve the performance of the discourse model substantially. Inspection of the most informative discourse features revealed that different prompt types taxed different aspects of language. These findings suggest that discourse can be used to estimate aphasia severity, and provide insight into the linguistic content elicited by different types of discourse prompts.

Proper and common names in the semantic system.

Proper names are an important part of language and communication. They are thought to have a special status due to their neuropsychological and psycholinguistic profile. To what extent proper names rely on the same semantic system as common names is not clear. In an fMRI study, we presented the same group of participants with both proper and common names to compare the associated activations. Both person and place names, as well as personally familiar and famous names were used, and compared with words representing concrete and abstract concepts. A whole-brain analysis was followed by a detailed analysis of subdivisions of four regions of interest known to play a central role in the semantic system: angular gyrus, anterior temporal lobe, posterior cingulate complex, and medial temporal lobe. We found that most subdivisions within these regions bilaterally were activated by both proper names and common names. The bilateral perirhinal and right entorhinal cortex showed a response specific to proper names, suggesting an item-specific role in retrieving person and place related information. While activation to person and place names overlapped greatly, place names were differentiated by activating areas associated with spatial memory and navigation. Person names showed greater right hemisphere involvement compared to places, suggesting a wider range of associations. Personally familiar names showed stronger activation bilaterally compared to famous names, indicating representations that are enhanced by autobiographic and episodic details. Both proper and common names are processed in the wider semantic system that contains associative, episodic, and spatial components. Processing of proper names is characterized by a somewhat stronger involvement these components, rather than by a fundamentally different system.

Temporal features of concepts are grounded in time perception neural networks: An EEG study.

Experimental evidence suggests that modality-specific concept features such as action, motion, and sound partially rely on corresponding action/perception neural networks in the human brain.Little is known, however, about time-related features of concepts. We examined whether temporal features of concepts recruit networks that subserve time perception in the brain in an EEG study using event and object nouns. Results showed significantly larger ERPs for event duration vs object size judgments over right parietal electrodes, a region associated with temporal processing. Additionally, alpha/beta (10-15 Hz) neural oscillation showed a stronger desynchronization for event duration compared to object size in the right parietal electrodes. This difference was not seen in control tasks comparing event vs object valence, suggesting that it is not likely to reflect a general difference between event and object nouns. These results indicate that temporal features of words may be subserved by time perception circuits in the human brain.

Spatiotemporal characteristics of the neural representation of event concepts.

Events are a fundamentally important part of our understanding of the world. How lexical concepts denoting events are represented in the brain remains controversial. We conducted two experiments using event and object nouns matched on a range of psycholinguistic variables, including concreteness, to examine spatial and temporal characteristics of event concepts. Both experiments used magnitude and valence tasks on event and object nouns. The fMRI experiment revealed a distributed set of regions for events, including the angular gyrus, anterior temporal lobe, and posterior cingulate across tasks. In the EEG experiment, events and objects differed in amplitude within the 300-500 ms window. Together these results shed light into the spatiotemporal characteristics of event concept representation and show that event concepts are represented in the putative hubs of the semantic system. While these hubs are typically associated with object semantics, they also represent events, and have a likely role in temporal integration.

Network-based statistics distinguish anomic and Broca aphasia.

Aphasia is a speech-language impairment commonly caused by damage to the left hemisphere. Due to the complexity of speech-language processing, the neural mechanisms that underpin various symptoms between different types of aphasia are still not fully understood. We used the network-based statistic method to identify distinct subnetwork(s) of connections differentiating the resting-state functional networks of the anomic and Broca groups. We identified one such subnetwork that mainly involved the brain regions in the premotor, primary motor, primary auditory, and primary sensory cortices in both hemispheres. The majority of connections in the subnetwork were weaker in the Broca group than the anomic group. The network properties of the subnetwork were examined through complex network measures, which indicated that the regions in the superior temporal gyrus and auditory cortex bilaterally exhibit intensive interaction, and primary motor, premotor and primary sensory cortices in the left hemisphere play an important role in information flow and overall communication efficiency. These findings underlied articulatory difficulties and reduced repetition performance in Broca aphasia, which are rarely observed in anomic aphasia. This research provides novel findings into the resting-state brain network differences between groups of individuals with anomic and Broca aphasia. We identified a subnetwork of, rather than isolated, connections that statistically differentiate the resting-state brain networks of the two groups, in comparison with standard lesion symptom mapping results that yield isolated connections.

Network-based statistics distinguish anomic and Broca's aphasia.

INTRODUCTION: Aphasia is a speech-language impairment commonly caused by damage to the left hemisphere. The neural mechanisms that underpin different types of aphasia and their symptoms are still not fully understood. This study aims to identify differences in resting-state functional connectivity between anomic and Broca's aphasia measured through resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: We used the network-based statistic (NBS) method, as well as voxel- and connectome-based lesion symptom mapping (V-, CLSM), to identify distinct neural correlates of the anomic and Broca's groups. To control for lesion effect, we included lesion volume as a covariate in both the NBS method and LSM. RESULTS: NBS identified a subnetwork located in the dorsal language stream bilaterally, including supramarginal gyrus, primary sensory, motor, and auditory cortices, and insula. The connections in the subnetwork were weaker in the Broca's group than the anomic group. The properties of the subnetwork were examined through complex network measures, which indicated that regions in right inferior frontal sulcus, right paracentral lobule, and bilateral superior temporal gyrus exhibit intensive interaction. Left superior temporal gyrus, right postcentral gyrus, and left supramarginal gyrus play an important role in information flow and overall communication efficiency. Disruption of this network underlies the constellation of symptoms associated with Broca's aphasia. Whole-brain CLSM did not detect any significant connections, suggesting an advantage of NBS when thousands of connections are considered. However, CLSM identified connections that differentiated Broca's from anomic aphasia when analysis was restricted to a hypothesized network of interest. DISCUSSION: We identified novel signatures of resting-state brain network differences between groups of individuals with anomic and Broca's aphasia. We identified a subnetwork of connections that statistically differentiated the resting-state brain networks of the two groups, in comparison with standard CLSM results that yielded isolated connections. Network-level analyses are useful tools for the investigation of the neural correlates of language deficits post-stroke.

Cerebral blood flow in patients recovered from mild COVID-19.

BACKGROUND AND PURPOSE: Cerebral hypoperfusion has been described in both severe and mild forms of symptomatic Coronavirus Disease 2019 (COVID-19) infection. The purpose of this study was to investigate global and regional cerebral blood flow (CBF) in asymptomatic COVID-19 patients. METHODS: Cases with mild COVID-19 infection and age-, sex-, and race-matched healthy controls were drawn from the Aging Brain Consortium at The University of South Carolina data repository. Demographics, risk factors, and data from the Montreal Cognitive Assessment were collected. Mean CBF values for gray matter (GM), white matter (WM), and the whole brain were calculated by averaging CBF values of standard space-normalized CBF image values falling within GM and WM masks. Whole brain region of interest-based analyses were used to create standardized CBF maps and explore differences between groups. RESULTS: Twenty-eight cases with prior mild COVID-19 infection were compared with 28 controls. Whole-brain CBF (46.7 ± 5.6 vs. 49.3 ± 3.7, p = .05) and WM CBF (29.3 ± 2.6 vs. 31.0 ± 1.6, p = .03) were noted to be significantly lower in COVID-19 cases as compared to controls. Predictive models based on these data predicted COVID-19 group membership with a high degree of accuracy (85.2%, p < .001), suggesting CBF patterns are an imaging marker of mild COVID-19 infection. CONCLUSION: In this study, lower WM CBF, as well as widespread regional CBF changes identified using quantitative MRI, was found in mild COVID-19 patients. Further studies are needed to determine the reliability of this newly identified COVID-19 brain imaging marker and determine what drives these CBF changes.

Lower socioeconomic status is associated with premature brain aging.

BACKGROUND: Premature age-related brain changes may be influenced by physical health factors. Lower socioeconomic status (SES) is often associated with poorer physical health. In this study, we aimed to investigate the relationship between SES and premature brain aging. METHODS: Brain age was estimated from T1-weighted images using BrainAgeR in 217 participants from the ABC@UofSC Repository. The difference between brain and chronological age (BrainGAP) was calculated. Multiple regression models were used to predict BrainGAP with age, SES, body mass index, diabetes, hypertension, sex, race, and education as predictors. SES was calculated from size-adjusted household income and the cost of living. RESULTS: Fifty-five participants (25.35%) had greater brain age than chronological age (premature brain aging). Multiple regression models revealed that age, sex, and SES were significant predictors of BrainGAP with lower SES associated with greater BrainGAP (premature brain aging). CONCLUSIONS: This study demonstrates that lower SES is an independent contributor to premature brain aging. This may provide additional insight into the mechanisms associated with brain health, cognition, and resilience to neurological injury.

Canonical Sentence Processing and the Inferior Frontal Cortex: Is There a Connection?

The role of left inferior frontal cortex (LIFC) in canonical sentence comprehension is controversial. Many studies have found involvement of LIFC in sentence production or complex sentence comprehension, but negative or mixed results are often found in comprehension of simple or canonical sentences. We used voxel-, region-, and connectivity-based lesion symptom mapping (VLSM, RLSM, CLSM) in left-hemisphere chronic stroke survivors to investigate canonical sentence comprehension while controlling for lexical-semantic, executive, and phonological processes. We investigated how damage and disrupted white matter connectivity of LIFC and two other language-related regions, the left anterior temporal lobe (LATL) and posterior temporal-inferior parietal area (LpT-iP), affected sentence comprehension. VLSM and RLSM revealed that LIFC damage was not associated with canonical sentence comprehension measured by a sensibility judgment task. LIFC damage was associated instead with impairments in a lexical semantic similarity judgment task with high semantic/executive demands. Damage to the LpT-iP, specifically posterior middle temporal gyrus (pMTG), predicted worse sentence comprehension after controlling for visual lexical access, semantic knowledge, and auditory-verbal short-term memory (STM), but not auditory single-word comprehension, suggesting pMTG is vital for auditory language comprehension. CLSM revealed that disruption of left-lateralized white-matter connections from LIFC to LATL and LpT-iP was associated with worse sentence comprehension, controlling for performance in tasks related to lexical access, auditory word comprehension, and auditory-verbal STM. However, the LIFC connections were accounted for by the lexical semantic similarity judgment task, which had high semantic/executive demands. This suggests that LIFC connectivity is relevant to canonical sentence comprehension when task-related semantic/executive demands are high.

HD-tDCS of primary and higher-order motor cortex affects action word processing.

The contribution of action-perception systems of the brain to lexical semantics remains controversial. Here, we used high-definition transcranial direct current stimulation (HD-tDCS) in healthy adults to examine the role of primary (left hand motor area; HMA) and higher-order (left anterior inferior parietal lobe; aIPL) action areas in action-related word processing (action verbs and manipulable nouns) compared to non-action-related control words (non-action verbs and non-manipulable nouns). We investigated stimulation-related effects at three levels of semantic processing: subliminal, implicit, and explicit. Broadly, we found that stimulation of HMA and aIPL resulted in relative facilitation of action-related language processing compared to non-action. HMA stimulation facilitated action verb processing in subliminal and implicit task contexts, suggesting that HMA helps represent action verbs even in semantically shallow tasks. HMA stimulation also facilitated manipulable noun comprehension in an explicit semantic task, suggesting that HMA contributes to manipulable noun comprehension when semantic demands are high. aIPL stimulation facilitated both manipulable noun and action verb processing during an implicit task. We suggest that both HMA and aIPL play a functional role in action semantics. HMA plays a general role in the semantics of actions and manipulable objects, while aIPL is important only when visuo-motor coordination is required for the action.

Effects of social isolation on quality of life in elderly adults.

Prolonged periods of social isolation are known to have significant negative health consequences and reduce quality of life, an effect that is particularly pronounced in older populations. Despite the known deleterious effects of social isolation, a key component of the response to the COVID-19 pandemic has been the issuance of stay at home and/or shelter in place orders. Relatively little is known about the potential effects these periods of social isolation could have on older adults, and less still is known about potential risk factors or protective factors that modulate these effects. Here, we describe results from a longitudinal study in which we measured quality of life both prior to and immediately following a one-month period of social isolation associated with the issuance and revocation of a shelter in place order (April 6, 2020 through May 4, 2020) in the state of South Carolina. Healthy adult participants (N = 62) between the ages of 60 and 80 who had already completed quality of life questionnaires prior to isolation again completed the questionnaires following a one-month order to shelter in place. Quality of life significantly decreased during the social isolation period, with older participants showing the greatest declines. Participants with higher levels of physical activity and better physical/mental health going into the isolation period tended to show greater decreases in quality of life over time. These results highlight the negative consequences of even short bouts of social isolation for the elderly and suggest that reductions in social contact related to COVID-19 may have significant effects on mental health and emotional well-being, at least among older individuals.

White matter hyperintensity load is associated with premature brain aging.

BACKGROUND: Brain age is an MRI-derived estimate of brain tissue loss that has a similar pattern to aging-related atrophy. White matter hyperintensities (WMHs) are neuroimaging markers of small vessel disease and may represent subtle signs of brain compromise. We tested the hypothesis that WMHs are independently associated with premature brain age in an original aging cohort. METHODS: Brain age was calculated using machine-learning on whole-brain tissue estimates from T1-weighted images using the BrainAgeR analysis pipeline in 166 healthy adult participants. WMHs were manually delineated on FLAIR images. WMH load was defined as the cumulative volume of WMHs. A positive difference between estimated brain age and chronological age (BrainGAP) was used as a measure of premature brain aging. Then, partial Pearson correlations between BrainGAP and volume of WMHs were calculated (accounting for chronological age). RESULTS: Brain and chronological age were strongly correlated (r(163)=0.932, p<0.001). There was significant negative correlation between BrainGAP scores and chronological age (r(163)=-0.244, p<0.001) indicating that younger participants had higher BrainGAP (premature brain aging). Chronological age also showed a positive correlation with WMH load (r(163)=0.506, p<0.001) indicating older participants had increased WMH load. Controlling for chronological age, there was a statistically significant relationship between premature brain aging and WMHs load (r(163)=0.216, p=0.003). Each additional year in brain age beyond chronological age corresponded to an additional 1.1mm3 in WMH load. CONCLUSIONS: WMHs are an independent factor associated with premature brain aging. This finding underscores the impact of white matter disease on global brain integrity and progressive age-like brain atrophy.

Neural network bases of thematic semantic processing in language production.

Semantic processing is a central component of language and cognition. The anterior temporal lobe is postulated to be a key hub for semantic processing, but the posterior temporoparietal cortex is also involved in thematic associations during language. It is possible that these regions act in concert and depend on an anteroposterior network linking the temporal pole with posterior structures to support thematic semantic processing during language production. We employed connectome-based lesion-symptom mapping to examine the causal relationship between lesioned white matter pathways and thematic processing language deficits among individuals with post-stroke aphasia. Seventy-nine adults with chronic aphasia completed the Philadelphia Naming Test, and semantic errors were coded as either thematic or taxonomic to control for taxonomic errors. Controlling for nonverbal conceptual-semantic knowledge as measured by the Pyramids and Palm Trees Test, lesion size, and the taxonomic error rate, thematic error rate was associated with loss of white matter connections from the temporal pole traversing in peri-Sylvian regions to the posterior cingulate and the insula. These findings support the existence of a distributed network underlying thematic relationship processing in language as opposed to discrete cortical areas.

HD-tDCS over motor cortex facilitates figurative and literal action sentence processing.

The extent to which action and perception systems of the brain are involved in semantic comprehension remains controversial. Whether figurative language, such as metaphors and idioms, is grounded in sensory-motor systems is especially contentious. Here, we used high-definition transcranial direct current stimulation (HD-tDCS) in healthy adults to examine the role of the left-hemisphere motor cortex during the comprehension of action sentences, relative to comprehension of sentences with visual verbs. Action sentences were divided into three types: literal, metaphoric, or idiomatic. This allowed us to ask whether processing of action verbs used in figurative contexts relies on motor cortex. The results revealed that action sentence comprehension response times were facilitated relative to the visual sentence control. Significant interaction relative to visual sentences was observed for literal, metaphoric, and idiomatic action sentences with HD-tDCS of the motor cortex. These results suggest that the left motor cortex is functionally involved in action sentence comprehension. Furthermore, this involvement exists when the action content of the sentences is figurative, for both idiomatic and metaphoric cases. The results provide evidence for functional links between conceptual and action systems of the brain.

Dissociating action and abstract verb comprehension post-stroke.

The neural bases of action and abstract concept representations remain a topic of debate. While several lines of research provide evidence for grounding of action-related conceptual content into sensory-motor systems, results of traditional lesion-deficit studies have been somewhat inconsistent. Further, few studies have directly compared the neural substrates of action and relatively abstract verb comprehension post-stroke. Here, we investigated the impact of the disruption of two neural networks on comprehension of action and relatively abstract verbs in 48 unilateral left-hemisphere stroke patients using two methodologies: 1) lesion-deficit association and 2) resting-state functional connectivity (RSFC) analyses. Disruption of RSFC between the left inferior frontal gyrus and right hemisphere primary and secondary sensory-motor areas predicted greater relative impairment of action semantics. Voxel-based lesion-symptom mapping revealed that damage to frontal white matter, extending towards the inferior frontal gyrus, also predicted greater relative impairment of action semantics. On the other hand, damage to the left anterior middle temporal gyrus significantly impaired the more abstract category relative to action. These findings support the view that action and non-action/abstract semantic processing rely on partially dissociable brain networks, with action concepts relying more heavily on sensory-motor areas. The results also have wider implications for lesion-deficit association studies and show how the contralateral hemisphere can play a compensatory role following unilateral stroke.

Concepts within reach: Action performance predicts action language processing in stroke.

The relationship between the brain's conceptual or semantic and sensory-motor systems remains controversial. Here, we tested manual and conceptual abilities of 41 chronic stroke patients in order to examine their relationship. Manual abilities were assed through a reaching task using an exoskeleton robot. Semantic abilities were assessed with implicit as well as explicit semantic tasks, for both verbs and nouns. The results show that that the degree of selective impairment for action word processing was predicted by the degree of impairment in reaching performance. Moreover, the implicit semantic measures showed a correlation with a global reaching parameter, while the explicit semantic similarity judgment task predicted performance in action initiation. These results suggest that action concepts are dynamically grounded through motoric simulations, and that more details are simulated for more explicit semantic tasks. This is evidence for a close and causal relationship between sensory-motor and conceptual systems of the brain.