Neural Mechanisms of Pleasant and Unpleasant Mental States of Speaker versus Listener-An fMRI Study-

AbstractExtensive fMRI study of human lateral frontal cortex (LFC) has yet to yield a consensus mapping between discrete anatomy and psychological states, partly due to the difficulty of inferring mental states in individual studies. Here, we used a data-driven approach to generate a comprehensive functional-anatomical mapping of LFC from 11,406 neuroimaging studies. We identified putatively separable LFC regions on the basis of whole-brain co-activation, revealing 14 clusters organized into three whole-brain networks. Next, we used multivariate classification to identify the psychological states that best predicted activity in each sub-region, resulting in preferential psychological profiles. We observed large functional differences between networks, suggesting brain networks support distinct modes of processing. Within each network, however, we observed low functional specificity, suggesting discrete psychological states are not modularly organized. Our results are consistent with the view that individual LFC regions work as part of highly parallel, distributed networks to give rise to flexible, adaptive behavior.

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When implicit prosociality trumps selfishness: the neural valuation system underpins more optimal choices when learning to avoid harm to others than to oneself

10.31234/osf.io/q6psx ◽

2020 ◽

Author(s):

Lukas Lengersdorff ◽

Isabella Wagner ◽

Claus Lamm

Keyword(s):

Neural Mechanisms ◽

Temporoparietal Junction ◽

Fmri Study ◽

The Social ◽

Egocentric Bias ◽

Right Temporoparietal Junction ◽

Increased Sensitivity ◽

Self Harm ◽

Human Participants ◽

The Right

Humans learn quickly which actions cause them harm. As social beings, we also need to learn to avoid actions that hurt others. It is currently unknown if humans are as good at learning to avoid others' harm (prosocial learning) as they are at learning to avoid self-harm (self-relevant learning). Moreover, it remains unclear how the neural mechanisms of prosocial learning differ from those of self-relevant learning. In this fMRI study, 96 male human participants learned to avoid painful stimuli either for themselves or for another individual. We found that participants performed more optimally when learning for the other than for themselves. Computational modeling revealed that this could be explained by an increased sensitivity to subjective values of choice alternatives during prosocial learning. Increased value-sensitivity was further associated with empathic traits. On the neural level, higher value-sensitivity during prosocial learning was associated with stronger engagement of the ventromedial prefrontal cortex (VMPFC) during valuation. Moreover, the VMPFC exhibited higher connectivity with the right temporoparietal junction during prosocial, compared to self-relevant, choices. Our results suggest that humans are particularly adept at learning to protect others from harm. This ability appears implemented by neural mechanisms overlapping with those supporting self-relevant learning, but with the additional recruitment of structures associated to the social brain. Our findings contrasts with recent proposals that humans are egocentrically biased when learning to obtain monetary rewards for self or others. Prosocial tendencies may thus trump the egocentric bias in learning when another person's physical integrity is at stake.

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Brain Responses Underlying Anthropomorphism, Agency, and Social Attribution in Autism Spectrum Disorder

The Open Neuroimaging Journal ◽

10.2174/1874440001812010016 ◽

2018 ◽

Vol 12 (1) ◽

pp. 16-29 ◽

Cited By ~ 1

Author(s):

Carla J. Ammons ◽

Constance F. Doss ◽

David Bala ◽

Rajesh K. Kana

Keyword(s):

Autism Spectrum Disorder ◽

Social Movement ◽

Mental States ◽

Brain Regions ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Social Brain ◽

Social Attribution ◽

Brain Responses ◽

Fmri Study

Background:Theory of Mind (ToM), the ability to attribute mental states to oneself and others, is frequently impaired in Autism Spectrum Disorder (ASD) and may result from altered activation of social brain regions. Conversely, Typically Developing (TD) individuals overextend ToM and show a strong tendency to anthropomorphize and interpret biological motion in the environment. Less is known about how the degree of anthropomorphism influences intentional attribution and engagement of the social brain in ASD.Objective:This fMRI study examines the extent of anthropomorphism, its role in social attribution, and the underlying neural responses in ASD and TD using a series of human stick figures and geometrical shapes.Methods:14 ASD and 14 TD adults watched videos of stick figures and triangles interacting in random or socially meaningful ways while in an fMRI scanner. In addition, they completed out-of-scanner measures of ToM skill and real-world social deficits. Whole brain statistical analysis was performed for regression and within and between group comparisons of all conditions using SPM12’s implementation of the general linear model.Results:ToM network regions were activated in response to social movement and human-like characters in ASD and TD. In addition, greater ToM ability was associated with increased TPJ and MPFC activity while watching stick figures; whereas more severe social symptoms were associated with reduced right TPJ activation in response to social movement.Conclusion:These results suggest that degree of anthropomorphism does not differentially affect social attribution in ASD and highlights the importance of TPJ in ToM and social attribution.

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Investigation of working memory networks for verbal and rhythmic stimuli

10.1101/847038 ◽

2019 ◽

Author(s):

Joshua D. Hoddinott ◽

Dirk Schuit ◽

Jessica A. Grahn

Keyword(s):

Working Memory ◽

Basal Ganglia ◽

Significant Interaction ◽

Verbal Working Memory ◽

Neural Mechanisms ◽

Musical Rhythm ◽

Brain Responses ◽

Fmri Study ◽

Spontaneous Behavior ◽

With Memory

AbstractAuditory working memory is often conceived of as a unitary capacity, with memory for different auditory materials (syllables, pitches, rhythms) thought to rely on similar neural mechanisms. One spontaneous behavior observed in working memory studies is ‘chunking’. For example, individuals often recount digit sequences in groups, or chunks, of 3 to 4 digits, and this chunking improves performance. Chunking may also operate in musical rhythm, with beats acting as chunk boundaries for tones in rhythmic sequences. Similar to chunking, beat-based structure in rhythms also improves performance. Thus, beat processing may rely on the same mechanisms that underlie chunking of verbal material. The current fMRI study examined whether beat perception is a type of chunking, measuring brain responses to chunked and unchunked letter sequences relative to beat-based and nonbeat-based rhythmic sequences. Participants completed a sequence discrimination task, and comparisons between stimulus encoding, maintenance, and discrimination were made for both rhythmic and verbal sequences. Overall, rhythm and verbal working memory networks overlapped substantially. When comparing rhythmic and verbal conditions, rhythms activated basal ganglia, supplementary motor area, and anterior insula, compared to letter strings, during encoding and discrimination. Letter strings compared to rhythms activated bilateral auditory cortex during encoding, and parietal cortex, precuneus, and middle frontal gyri during discrimination. Importantly, there was a significant interaction in the basal ganglia during encoding: activation for beat-based rhythms was greater than for nonbeat-based rhythms, but verbal chunked and unchunked conditions did not differ. The significant interaction indicates that beat perception is not simply a case of chunking, suggesting a dissociation between beat processing and grouping mechanisms that warrants further exploration.

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