The specific goals of the research study proposed for this fellowship are to use functional magnetic resonance imaging (fMRI) to gain a better understanding of the neural mechanisms underlying emotional acceptance as an emotion regulation technique, while simultaneously providing invaluable training in the use of fMRI as a research tool. Through the use of fMRI, the proposed study will examine patterns of activation and de-activation in neural structures while engaging in emotional acceptance as an emotion regulation strategy in a clinical sample. Specifically, this study will examine the following: 1) activation of specific regions of interest (ROIs;amygdala, insula, hippocampus, anterior cingulate cortex, orbitofrontal cortex, prefrontal cortex) of an """"""""Accept"""""""" condition relative to """"""""Attend"""""""" and """"""""Suppress"""""""" conditions during a negative emotion induction;2) differences in patterns of activation in these two conditions between those who have and have not undergone skills training in emotional acceptance as an emotion regulation strategy;and 3) the relationship between changes in patterns of activation and self-reported changes in the subjective experience of negative emotion. Skills training in emotional acceptance skills will be based upon procedures currently used in the Unified Protocol for the Treatment of Emotional Disorders (Barlow, Allen, Ellard &Fairholme, 2008), and will be carried out over five, 1-hour sessions prior to a post-treatment imaging session. The broader aim of this study is to bridge affective neuroscience and emotion regulation research to investigate the neural mechanisms associated with emotional acceptance to gain a better understanding of the ultimate utility of this approach as applied to the treatment of anxiety and mood disorders.

Public Health Relevance

Anxiety and mood disorders disrupt the lives of millions of Americans, with lifetime prevelance rates for anxiety disorders estimated at 29% of the population, and mood disorders at 21% (Kessler et al., 2005). Further, anxiety disorders alone represent a cost to this country of over $42 billion annually (Greenberg et al., 1999). It is hoped that by understanding how emotion regulation strategies such as emotional acceptance affect communication between cortical and limbic structures during emotional processing, we might gain a better understanding not only of the etiology of anxiety and mood disorders at a neural level, but also of how to effectively ameliorate or correct maladaptive emotional processing in these disorders using a unified, transdiagnostic approach. The experience of conducting this study will provide a strong foundation from which to pursue long-term career goals - to bridge affective neuroscience and emotion regulation research to improve psychosocial treatments for anxiety and mood disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Predoctoral Individual National Research Service Award (F31)
Project #
1F31MH084422-01A1
Application #
7676945
Study Section
Special Emphasis Panel (ZRG1-F12B-N (20))
Program Officer
Rubio, Mercedes
Project Start
2009-05-08
Project End
2012-05-07
Budget Start
2009-05-08
Budget End
2010-05-07
Support Year
1
Fiscal Year
2009
Total Cost
$32,516
Indirect Cost
Name
Boston University
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
049435266
City
Boston
State
MA
Country
United States
Zip Code
02215
Ellard, Kristen K; Barlow, David H; Whitfield-Gabrieli, Susan et al. (2017) Neural correlates of emotion acceptance vs worry or suppression in generalized anxiety disorder. Soc Cogn Affect Neurosci 12:1009-1021
Ellard, Kristen K; Deckersbach, Thilo; Sylvia, Louisa G et al. (2012) Transdiagnostic treatment of bipolar disorder and comorbid anxiety with the unified protocol: a clinical replication series. Behav Modif 36:482-508
Hofmann, Stefan G; Ellard, Kristen K; Siegle, Greg J (2012) Neurobiological correlates of cognitions in fear and anxiety: a cognitive-neurobiological information-processing model. Cogn Emot 26:282-99