# Individual differences through self-reinforcement of suboptimal strategies

> **NIH NIH DP1** · PRINCETON UNIVERSITY · 2024 · $1,148,000

## Abstract

Project Summary/Abstract
What produces individual differences in behavior? This fundamental question has classically been given two
answers: nature and nurture. Here, we suggest that those two answers, while both critical and correct, are
insufficient to fully explain individual variability. Instead, we propose that the vast differences in behavior
between individuals arise in part from different individuals forming different reward associations within the
same environment. This results from the fact that the world is complex and high-dimensional, in that there are
almost always multiple possible actions or events that could be attributed to reward. Given the key role of
dopamine neurons as the brain’s positive feedback system for behavioral control, the specific hypothesis is that
small differences across individuals in initial conditions ultimately produce large differences in which features of
the environment that the individual attributes to reward. This hypothesis is inspired in part by complex systems
theory, which emphasizes the role of positive feedback in generating and amplifying small differences, creating
outcomes that seem stochastic. To address this hypothesis, we will leverage our recent finding that different
dopamine neurons calculate reward prediction error across different dimensions of the environment.
Specifically, we will use dopamine neuron recordings to infer the time-varying features of the environment that
each animal uses to predict reward, and then build reinforcement learning models of each individual based on
these features. Ultimately, this testable framework aims to explain both normal variation across individuals, as
well as the ubiquitous contribution of dopamine in mediating a disparate range of neuropsychiatric diseases.

## Key facts

- **NIH application ID:** 10911260
- **Project number:** 5DP1MH136573-02
- **Recipient organization:** PRINCETON UNIVERSITY
- **Principal Investigator:** Ilana Witten
- **Activity code:** DP1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,148,000
- **Award type:** 5
- **Project period:** 2023-08-21 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10911260

## Citation

> US National Institutes of Health, RePORTER application 10911260, Individual differences through self-reinforcement of suboptimal strategies (5DP1MH136573-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10911260. Licensed CC0.

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