The role of medial prefrontal cortex in motivated social cognition

University Of Texas At Austin, Austin TX

Investigators

Abstract

This project explores the neural mechanisms that permit us to evaluate ourselves in the way we would like. Self-evaluation is a core social-cognitive process that affects healthcare decisions, emotional well-being, interpersonal relations, and productivity at school and work. If we deny a problem exists or view our abilities through rose-colored glasses, we are not likely to seek help or allow adequate time to perform a task. Disordered self-evaluation is a feature of many mental health issues such as depression, schizophrenia, and autism. Currently little is know about how self-evaluation is affected by neurobiological development in the general population or the neurobiological impairments associated with disorders. Our lack of knowledge stems from the fact that neural models of self-evaluation trail far behind psychological models. Thus, there is a great need to develop neurobiological models of self-evaluation. The proposed project will use a combination of fMRI, psychological theory, and computational modeling to address two critical bottlenecks that impede development of neural models of self-processing. First, the studies will illuminate the neural architecture of motivational influences on self-evaluation. Motivational influences on self-evaluation play a fundamental role in psychological models yet are currently ignored by neuroscience. Additionally, the studies will disentangle a critical confound present in most of the existing research on self-evaluation. Specifically, the project will examine whether the medial prefrontal cortex, the region most consistently associated with self-evaluation, serves to support socioemotional processing or cognitive properties of social evaluation. Results will transform our conceptualization of the neural basis of disorders such as depression, schizophrenia, and autism which feature disordered self-evaluation but are currently only understood through neural models of other processes. The results will bridge gaps between psychological and neurocognitive models to inform the next generation of self-evaluation research as well as inform related inquiries into reward-processing, selective attention, and decision-making.