Publications by authors named "Sneha Shashidhara"

In the human brain, a multiple-demand (MD) network plays a key role in cognitive control, with core components in lateral frontal, dorsomedial frontal and lateral parietal cortex, and multivariate activity patterns that discriminate the contents of many cognitive activities. In prefrontal cortex of the behaving monkey, different cognitive operations are associated with very different patterns of neural activity, while details of a particular stimulus are encoded as small variations on these basic patterns (Sigala et al, 2008). Here, using the advanced fMRI methods of the Human Connectome Project and their 360-region cortical parcellation, we searched for a similar result in MD activation patterns.

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Theoretical models suggest that executive functions rely on both domain-general and domain-specific processes. Supporting this view, prior brain imaging studies have revealed that executive activations converge and diverge within broadly characterized brain networks. However, the lack of precise anatomical mappings has impeded our understanding of the interplay between domain-general and domain-specific processes.

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Domestic violence, especially intimate partner violence (IPV), is an important issue worldwide, especially in India. Those that experience it may not always be able to come forward or have access to the required social support to act against it. We use National Family Health Survey data ( = 66,013 women) to create machine learning models which can predict IPV instances with a recall of 78%.

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Recent functional MRI studies identified sensory-biased regions across much of the association cortices and cerebellum. However, their anatomical relationship to multiple-demand (MD) regions, characterized as domain-general due to their coactivation during multiple cognitive demands, remains unclear. For a better anatomical delineation, we used multimodal MRI techniques of the Human Connectome Project to scan subjects performing visual and auditory versions of a working memory (WM) task.

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Selection and integration of information based on current goals is fundamental for goal-directed behavior. Reward motivation has been shown to improve behavioral performance, yet the neural mechanisms that link motivation and control processes, and in particular its effect on context-dependent information processing, remain unclear. We used functional magnetic resonance imaging (fMRI) in 24 human volunteers (13 females) to test whether reward motivation enhances the coding of task-relevant information across the frontoparietal cortex, as would be predicted based on previous experimental evidence and theoretical accounts.

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A decline in declarative or explicit memory has been extensively characterized in cognitive aging and is a hallmark of cognitive impairments. However, whether and how implicit perceptual memory varies with aging or cognitive impairment is unclear. Here, we compared implicit perceptual memory and explicit memory measures in three groups of participants: (1) 59 healthy young volunteers (20-30 years); (2) 269 healthy old volunteers (50-90 years) and (3) 21 patients with mild cognitive impairment, i.

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How does organized cognition arise from distributed brain activity? Recent analyses of fluid intelligence suggest a core process of cognitive focus and integration, organizing the components of a cognitive operation into the required computational structure. A cortical 'multiple-demand' (MD) system is closely linked to fluid intelligence, and recent imaging data define nine specific MD patches distributed across frontal, parietal, and occipitotemporal cortex. Wide cortical distribution, relative functional specialization, and strong connectivity suggest a basis for cognitive integration, matching electrophysiological evidence for binding of cognitive operations to their contents.

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The frontoparietal "multiple-demand" (MD) control network plays a key role in goal-directed behavior. Recent developments of multivoxel pattern analysis (MVPA) for fMRI data allow for more fine-grained investigations into the functionality and properties of brain systems. In particular, MVPA in the MD network was used to gain better understanding of control processes such as attentional effects, adaptive coding, and representation of multiple task-relevant features, but overall low decoding levels have limited its use for this network.

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A distributed, frontoparietal "multiple-demand" (MD) network is involved in tasks of many different kinds. Integrated activity across this network may be needed to bind together the multiple features of a mental control program (Duncan, 2013). Previous data suggest that, especially with low cognitive load, there may be some differentiation between MD regions (e.

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