# Combining Electrophysiological, Behavioral and Psychological Measures to Target Mechanisms of Emotion Processing and Regulation During Cognitive Behavior Therapy in Depression

> **NIH NIH R21** · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · 2020 · $437,525

## Abstract

PROJECT SUMMARY
This R21 application aims to clarify the neurobiological mechanisms by which change occurs during cognitive
behavior therapy (CBT) for major depressive disorder (MDD). This hypothesis-driven study will explore the
association between the psychological constructs of psychological mindedness (PM) and mindfulness (M) during
the time course of CBT for MDD, and its relationship to electrophysiological and behavioral measures of automatic
(i.e. stimulus-driven or bottom-up) emotion processing. This objective is motivated by the following rationale: PM
and M represent different meta-cognitive processes of self-knowledge deemed critical for emotion regulation (ER)
and CBT success. Event-related potentials (ERPs) to salient affective pictures reflect different stages of motivated
attention. Using advanced analytic EEG techniques, we have linked these stages to the hierarchical activation of
`emotional' brain regions along the occipitotemporal ventral stream, ranging from preconscious stimulus
categorization (right secondary visual cortex, right temporoparietal junction) to conscious appraisal (posterior
cingulate cortex, ventromedial cortex). Importantly, blunted ERP responses to emotionally-arousing stimuli have
been observed in clinical depression, and hypoactivation of right temporoparietal and dorsolateral prefrontal
regions normalize after successful antidepressant or electroconvulsive treatment. A dichotic emotion recognition
test, which provides an auditory measure of bottom-up emotion processing in form of a left ear (right hemisphere)
advantage for recognizing the emotional intonation of speech patterns, has revealed behavioral deficits in MDD
patients. Moreover, an increased right ear advantage for verbal stimuli (left hemisphere) is seen in CBT
responders. Employing a sample of 60 MDD patients randomly assigned to CBT or nonspecific supportive therapy
(placebo), we will obtain psychological, electrophysiological, behavioral and clinical outcome measures of response
to 12 weeks of CBT in a pre-post treatment design to determine: (1) when and where in the brain automatic
emotion processing is altered by CBT; (2) if changes in emotional responding are moderated or mediated by meta-
cognitive processes of self-knowledge; and, (3) if these measures, alone or in combination, have promise as
markers of CBT treatment response. Existing ERP and behavioral data for healthy adults (HC) obtained using the
same experimental protocols will provide normative (yardstick) data. This study brings together experienced clinical
psychologists and psychiatrists doing treatment and research in depression with investigators having expertise
in affective neuroscience and electrophysiological studies in MDD. It will provide a critical new step for outlining
the affective-cognitive and neurophysiological mechanisms of ER by which change through CBT occurs. Apart from
their theoretical relevance, the findings of this project will also aid in developing nov...

## Key facts

- **NIH application ID:** 10057049
- **Project number:** 1R21MH121915-01A1
- **Recipient organization:** NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
- **Principal Investigator:** Ralf Jürgen Kayser
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $437,525
- **Award type:** 1
- **Project period:** 2020-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10057049

## Citation

> US National Institutes of Health, RePORTER application 10057049, Combining Electrophysiological, Behavioral and Psychological Measures to Target Mechanisms of Emotion Processing and Regulation During Cognitive Behavior Therapy in Depression (1R21MH121915-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10057049. Licensed CC0.

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