# Prediction Error and Affective Salience Abnormalities in Aging and Late-Life Depression

> **NIH NIH K01** · WEILL MEDICAL COLL OF CORNELL UNIV · 2024 · $177,070

## Abstract

PROJECT SUMMARY
The goal of this K01 Mentored Research Scientist Career Development Award is to provide the candidate with
the conceptual knowledge and technical skills needed to pursue an independent research career as a
computational cognitive neuroscientist focused on aging and late-life mood disorders. The candidate has a
strong background in cognitive paradigm design and functional neuroimaging methodology, and an evolving
interest in computational modeling of cognitive and affective dysfunctions in depressed older adults. The
research study will use computational approaches to clarify disrupted mechanisms of reward and salience
processes and may lead to findings that can serve as data-driven targets for future personalized treatments.
The proposed training consists of formal courses, structured tutorials, and hands-on methodological instruction
intended to strengthen the candidate's understanding and development of computational models for the study
of Positive Valence Systems (PVS) abnormalities in aging and late-life depression. Her mentoring team
consists of accomplished investigators who will provide guidance and training in neurobiological and
computational approaches for the study of reward and salience abnormalities.
The research study complements the candidate's training plan, as it focuses on PVS dysfunctions that may
contribute to reward processing abnormalities in normal aging and late-life depression. It is based on the
prediction that aging-related abnormalities in reward circuits interacting with neurobiological abnormalities of
depression may alter reward expectancy and reward responsiveness, leading depressed older adults to assign
greater affective salience to negative stimuli. Accordingly, the study proposes to investigate the impact of the
effects of aging and depressive symptoms on prediction error encoding of affectively salient stimuli at three
levels of analysis: circuits, behavior, and self-report. The participants will be older adults aged 60-85 years with
major depression (N = 34, stratified into two levels of severity) or no history or presence of psychopathology (N
= 34).
The proposed study will use task-based fMRI and computational modeling to examine how the dynamic
interaction of age and late-life depressive symptomatology influences neural network functions and the
resulting reward and salience processing behaviors. This study and the studies to follow promise to identify
personalized behavioral and neurobiological targets for much-needed interventions. This work is timely, as
advances in cognitive remediation, brain stimulation, and targeted behavioral interventions are becoming
increasingly capable of influencing selective neurobiological functions and associated behaviors.

## Key facts

- **NIH application ID:** 10738809
- **Project number:** 5K01MH118480-05
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** Lindsay Victoria
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $177,070
- **Award type:** 5
- **Project period:** 2019-12-20 → 2025-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10738809

## Citation

> US National Institutes of Health, RePORTER application 10738809, Prediction Error and Affective Salience Abnormalities in Aging and Late-Life Depression (5K01MH118480-05). Retrieved via AI Analytics 2026-06-14 from https://api.ai-analytics.org/grant/nih/10738809. Licensed CC0.

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