# Regulating Emotional Responses to Spoken Comments and Visual Images Across the Affective Instability Spectrum: An fMRI Study

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2020 · $607,656

## Abstract

Project Abstract
Emotionally distressing, aversive or painful experiences are a part of everyday life
experience. Crucial to emotional resilience is the capacity to voluntarily regulate one’s
emotional reaction to such experiences. Some people, however, have difficulty
modulating their emotional reactions and are subject to sudden, extreme emotional
states, especially in response to interpersonal events. This vulnerability, referred to as
affective instability (AI), is prototypic of borderline personality disorder (BPD), but is
found across a range of psychiatric disorders, and is prevalent, occuring in about 14% of
the population. The mechanisms underlying affective instability are not well understood,
but there is evidence that adaptive emotion regulation strategies used by healthy
individuals are impaired in those with BPD and other disorders characterized by
affective instability, and that the brain circuits that typically support these regulation
strategies are dysfunctional. This study is designed to determine the extent to which two
emotion regulation strategies, cognitive reapprasial and attentional distraction, are
dysfunctional across a spectrum of individuals with varying degrees of AI. It will use
functional neuroimaging (fMRI) to assess the functioning of underlying brain circuits as
these regulation strategies are implemented. In addition to studying AI across a
spectrum of disorders, this study will also focus on how spoken emotion is regulated.
To date, the strategies of cognitive reappraisal and attentional distraction have been
examined as they modulate emotion conveyed via still pictures, but not emotion
conveyed by speech directed at the subject, yet the spoken word is one of the most
important channels of emotional communication in interpersonal interaction and
therefore particularly relevant to AI. The present study will address this knowledge gap.
To achieve these aims this project will collect behavioral, physiologic, and functional
imagng (fMRI) data as subjects, spanning the full range of AI, employ cognitive
reapprasial and attentional distraction to down-regulate their responses to negative
emotional cues and cogntive reappraisal to upregulate their responses to positive cues.
The same subjects will apply these strategies to emotion presented via both pictures and
the spoken word. We will examine activation of brain regions of interest and functionally
connected circuits implicated in emotion regulation, as well as skin conductance and
pupillary dilation responses, in addition to behavioral responses.

## Key facts

- **NIH application ID:** 9967104
- **Project number:** 5R01MH109730-05
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Harold W Koenigsberg
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $607,656
- **Award type:** 5
- **Project period:** 2016-09-23 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9967104

## Citation

> US National Institutes of Health, RePORTER application 9967104, Regulating Emotional Responses to Spoken Comments and Visual Images Across the Affective Instability Spectrum: An fMRI Study (5R01MH109730-05). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/9967104. Licensed CC0.

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