# Social and decision neuroscience of suicidal behavior

> **NIH NIH K01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $167,568

## Abstract

While the predisposition to suicidal behavior is complex, the interpersonal context plays a critical role both as a
trigger and a deterrent. Moreover, people who attempt suicide display chronic interpersonal dysfunction and an
impulsive and avoidant approach to social problems, prompting questions about the way they make social
decisions. Although psychological accounts of interpersonal deficits in suicide exist, these are not integrated
with neural mechanisms. Addressing this lacuna, the applicant, a cognitive psychologist, seeks to develop an
independent research program in computational psychiatry with a long-term goal of investigating neural
mechanisms of social decision-making that may underlie interpersonal dysfunction in suicide and other mental
disorders. In the laboratory, suicide attempters display a tendency toward short-sighted, negligent decisions
and heightened susceptibility to decision biases. This behavioral profile of decision incompetence is paralleled
by disrupted decision-related signals in the ventral prefronto-striatal circuit. The literature and our preliminary
studies also suggest that decision-related signals in this circuit are modulated by the social context, which can
at times counteract goal-directed, adaptive processing. Thus, the applicant’s short-term aim is to test a
conceptual model, wherein decision deficits in suicide attempters result from an interference of automatic
responses to the social context with goal-directed processes that subserve adaptive decision-making. The
applicant has developed a social exchange paradigm, which examines decision-making under disruptive social
influences, modeling one key aspect of the suicidal crisis. Her approach leverages formal learning theory and
builds on recent computational studies, dissecting social decision-making as an interaction of automatic and
goal-directed processes. The applicant will test the interference hypothesis in two cross-sectional case-control
studies of behavior (n=120) and neural decision-related signals (n=60). She will use reinforcement learning
(RL) models to contrast behavioral tendencies and neural decision-related signals in depressed suicide
attempters with non-suicidal depressed and healthy controls. This approach will elucidate individual differences
in the degree to which automatic responses to the social context interfere with goal-directed processes. This
research will serve as a platform for interdisciplinary training provided by experts in functional and structural
imaging (Aizenstein), suicide phenomenology (Dombrovski and Szanto), social and decision neuroscience
(Delgado), cortico-striatal circuitry (Frank), learning theory and computational modeling (Dombrovski and
Frank), and personality (Hallquist). The applicant will take advantage of neuroimaging facilities and extensive
research infrastructure at the University of Pittsburgh. The proposed study addresses the #1 question of
the Prioritized Research Agenda for Suicide Prevention...

## Key facts

- **NIH application ID:** 9976611
- **Project number:** 5K01MH110762-04
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Polina M Vanyukov
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $167,568
- **Award type:** 5
- **Project period:** 2017-07-19 → 2021-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9976611

## Citation

> US National Institutes of Health, RePORTER application 9976611, Social and decision neuroscience of suicidal behavior (5K01MH110762-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9976611. Licensed CC0.

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