# The contribution of aberrant anticipatory processing to spectrum depression and mania, and cognitive and emotional dysfunction in major depressive and bipolar disorders

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $631,229

## Abstract

Abstract
Mood disorders, including major depressive (MDD) and bipolar (BD), are highly disabling and affect 60 million
Americans. Depressive and manic symptoms impair episodic and working memory and overall psychosocial
functioning in affected individuals. We will use the mood spectrum approach and functional magnetic
resonance imaging to determine the relationship among continuous constructs of depression (ranging from no
depression to sub-threshold depression to syndromal depression) and mania (ranging from no mania to sub-
threshold mania to syndromal mania) symptoms, brain and behavior measures of episodic and working
memory, and psychosocial dysfunction across MDD and BD diagnoses. We propose that aberrant anticipatory
processing preceding performance on episodic and working memory tasks may be an important factor that
mediates the relationship between mood symptoms and functioning in individuals with MDD and BD. Healthy
individuals and those with MDD and BD will undergo clinical evaluation at baseline, 6, and 12 months. They
will be scanned at baseline and at 6 months. We expect to collect longitudinal neuroimaging and clinical data
from 150 individuals (across diagnoses). We will identify brain regions whose activation during anticipation of
happy, fear, and neutral faces correlates with episodic memory accuracy and lifetime and current depression
and mania spectrum symptoms and psychosocial functioning (Aim 1). We will identify brain regions that
differentially activate during anticipation of easy and difficult working memory tasks, and correlate with lifetime
and current depression and mania spectrum symptoms and psychosocial functioning (Aim 2). Quality of life for
affected individuals could be improved if it were possible to predict and prevent worsening of clinical symptoms
and decline in functioning. We will use multiple regression, mixed models, classification, trajectory, and path
analyses to examine the role of anticipatory processing in the relationship between longitudinal trajectories in
mood symptoms and brain and behavior measures of episodic and working memory and longitudinal
trajectories in psychosocial functioning (Aim 3). To compare dimensional and categorical approaches, we will
compare main neuroimaging and behavioral measures in MDD vs. BD, and perform a Group-by-Symptom
interaction analyses. We will also explore how anticipation strategies and affective bias contribute to clinical
and functional outcomes described above (Exploratory Aims). The proposed research will lay the foundation
for understanding neural correlates underlying longitudinal trajectories in mood spectrum symptoms and
psychosocial functioning in mood disorders. If the mediating role of anticipatory processing for clinical and
functional outcomes is confirmed, anticipatory processing may become a new treatment target for affected
individuals. Addressing dysfunctional anticipatory processing may help predict occurrence of syndromal
episodes of depress...

## Key facts

- **NIH application ID:** 9873074
- **Project number:** 5R01MH114870-03
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Anna Manelis
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $631,229
- **Award type:** 5
- **Project period:** 2018-04-01 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9873074

## Citation

> US National Institutes of Health, RePORTER application 9873074, The contribution of aberrant anticipatory processing to spectrum depression and mania, and cognitive and emotional dysfunction in major depressive and bipolar disorders (5R01MH114870-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9873074. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*