# Novel neural circuit biomarkers of depression response to computer-augmented CBT

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2020 · $550,593

## Abstract

Every year more than 20% (55 million) of the adult American population suffers from major depression. (MDD).
While effective treatments are available, depression remains under-diagnosed and under-treated, in part due
to cost and availability of treatment. In the current application in response to NIMH NOT-14-007 we propose a
clinical trial to study potential novel biomarkers of depression treatment response rather than to test efficacy of
an efficient, cost-effective form of computer-augmented cognitive behavioral therapy (CCBT) which already
has proven efficacy. We present pilot data supporting CBT-induced improvements in functional connectivity
and task-induced activation in MDD. We also have found in previous work that this model of CCBT, known as
Good Days Ahead (GDA), has efficacy for MDD that is not inferior to conventional individual CBT therapy
across 8 and 16 weeks of treatment, despite reducing average therapist contact from 16 hours to less than 5
hours. We now propose that this new variation of cognitive therapy, which substitutes intensive, computer-
administered skills training for hours of therapist contact, will engage the same brain targets we have
previously seen with CBT. We hypothesize that it is rehearsal time during which an individual actively engages
in corrective skills training that “mends” the brain connectivity and promotes recovery. We will recruit a total of
60 patients with MDD and 40 matched comparison healthy participants from the outpatient clinics of the
Hospitals of the University of Pennsylvania. To take into account the impact of nonspecific factors, half of the
MDD participants will be randomized to receive CCBT immediately after baseline assessments and half will
first receive 8 weeks of Depression Care Management (DCM) (a clinically responsible alternative to a
traditional wait-list control group that includes support and clinical management) before subsequently receiving
CCBT.
Aim 1: Compare baseline resting state functional connectivity and task-induced activity between MDD
and controls. Aim 2: Assess CCBT treatment effects on resting state functional connectivity and task-
induced activation in MDD comparing CCBT-treated participants to DCM –treated participants.
Exploratory Aim: 1a:Predict the effects of baseline imaging measures on treatment outcomes; 1b:
Predict the effects of baseline executive function on treatment outcomes.

## Key facts

- **NIH application ID:** 9908160
- **Project number:** 5R01MH110939-04
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** YVETTE I SHELINE
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $550,593
- **Award type:** 5
- **Project period:** 2017-06-05 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9908160

## Citation

> US National Institutes of Health, RePORTER application 9908160, Novel neural circuit biomarkers of depression response to computer-augmented CBT (5R01MH110939-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9908160. Licensed CC0.

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