The dorsal, parietal visual stream is activated when seeing objects, but the exact nature of parietal object representations is still under discussion. Here we test 2 specific hypotheses. First, parietal cortex is biased to host some representations more than others, with a different bias compared with ventral areas. A prime example would be object action representations. Second, parietal cortex forms a general multiple-demand network with frontal areas, showing similar task effects and representational content compared with frontal areas. To differentiate between these hypotheses, we implemented a human neuroimaging study with a stimulus set that dissociates associated object action from object category while manipulating task context to be either action- or category-related. Representations in parietal as well as prefrontal areas represented task-relevant object properties (action representations in the action task), with no sign of the irrelevant object property (category representations in the action task). In contrast, irrelevant object properties were represented in ventral areas. These findings emphasize that human parietal cortex does not preferentially represent particular object properties irrespective of task, but together with frontal areas is part of a multiple-demand and content-rich cortical network representing task-relevant object properties.
Observed touch interactions provide useful information on how others communicate with the external world. Previous studies revealed shared neural circuits between the direct experience and the passive observation of simple touch, such as being stroked/slapped. Here, we investigate the complexity of the neural representations underlying the understanding of others' socio-affective touch interactions. Importantly, we use a recently developed touch database that contains a larger range of more complex social and non-social touch interactions. Participants judged affective aspects of each touch event and were scanned while watching the same videos. Using correlational multivariate pattern analysis methods, we obtained neural similarity matrices in 18 regions of interest from five different networks: somatosensory, pain, the theory of mind, visual and motor regions. Among them, four networks except motor cortex represent the social nature of the touch, whereas fine-detailed affective information is reflected in more targeted areas such as social brain regions and somatosensory cortex. Lastly, individual social touch preference at the behavioral level was correlated with the involvement of somatosensory areas on representing affective information, suggesting that individuals with higher social touch preference exhibit stronger vicarious emotional responses to others' social touch experiences. Together, these results highlight the overall complexity and the individual modulation of the distributed neural representations underlying the processing of observed socio-affective touch.
Brain disorders are often investigated in isolation, but very different conclusions might be reached when studies directly contrast multiple disorders. Here, we illustrate this in the context of specific learning disorders, such as dyscalculia and dyslexia. While children with dyscalculia show deficits in arithmetic, children with dyslexia present with reading difficulties. Furthermore, the comorbidity between dyslexia and dyscalculia is surprisingly high. Different hypotheses have been proposed on the origin of these disorders (number processing deficits in dyscalculia, phonological deficits in dyslexia) but these have never been directly contrasted in one brain imaging study. Therefore, we compared the brain activity of children with dyslexia, children with dyscalculia, children with comorbid dyslexia/dyscalculia and healthy controls during arithmetic in a design that allowed us to disentangle various processes that might be associated with the specific or common neural origins of these learning disorders.Participants were 62 children aged 9 to 12, 39 of whom had been clinically diagnosed with a specific learning disorder (dyscalculia and/or dyslexia). All children underwent fMRI scanning while performing an arithmetic task in different formats (dot arrays, digits and number words). At the behavioral level, children with dyscalculia showed lower accuracy when subtracting dot arrays, and all children with learning disorders were slower in responding compared to typically developing children (especially in symbolic formats). However, at the neural level, analyses pointed towards substantial neural similarity between children with learning disorders: Control children demonstrated higher activation levels in frontal and parietal areas than the three groups of children with learning disorders, regardless of the disorder. A direct comparison between the groups of children with learning disorders revealed similar levels of neural activation throughout the brain across these groups. Multivariate subject generalization analyses were used to statistically test the degree of similarity, and confirmed that the neural activation patterns of children with dyslexia, dyscalculia and dyslexia/dyscalculia were highly similar in how they deviated from neural activation patterns in control children. Collectively, these results suggest that, despite differences at the behavioral level, the brain activity profiles of children with different learning disorders during arithmetic may be more similar than initially thought.
Two hypotheses have been proposed about the etiology of neurodevelopmental learning disorders, such as dyslexia and dyscalculia: representation impairments and disrupted access to representations. We implemented a multi-method brain imaging approach to directly investigate these representation and access hypotheses in dyscalculia, a highly prevalent but understudied neurodevelopmental disorder in learning to calculate. We combined several magnetic resonance imaging methods and analyses, including univariate and multivariate analyses, functional and structural connectivity. Our sample comprised 24 adults with dyscalculia and 24 carefully matched controls. Results showed a clear deficit in the non-symbolic magnitude representations in parietal, temporal and frontal regions, as well as hyper-connectivity in visual brain regions in adults with dyscalculia. Dyscalculia in adults was thereby related to both impaired number representations and altered connectivity in the brain. We conclude that dyscalculia is related to impaired number representations as well as altered access to these representations.
Multi-voxel pattern analyses (MVPA) are often performed on unsmoothed data, which is very different from the general practice of large smoothing extents in standard voxel-based analyses. In this report, we studied the effect of smoothing on MVPA results in a motor paradigm. Subjects pressed four buttons with two different fingers of the two hands in response to auditory commands. Overall, independent of the degree of smoothing, correlational MVPA showed distinctive patterns for the different hands in all studied regions of interest (motor cortex, prefrontal cortex, and auditory cortices). With regard to the effect of smoothing, our findings suggest that results from correlational MVPA show a minor sensitivity to smoothing. Moderate amounts of smoothing (in this case, 1−4 times the voxel size) improved MVPA correlations, from a slight improvement to large improvements depending on the region involved. None of the regions showed signs of a detrimental effect of moderate levels of smoothing. Even higher amounts of smoothing sometimes had a positive effect, most clearly in low-level auditory cortex. We conclude that smoothing seems to have a minor positive effect on MVPA results, thus researchers should be mindful about the choices they make regarding the level of smoothing.
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