# Probing the neural computations underlying goal-directed decision-making in humans with single-neuron recordings

> **NIH NIH R01** · CALIFORNIA INSTITUTE OF TECHNOLOGY · 2024 · $423,307

## Abstract

Probing the neural computations underlying goal-directed decision-making in humans with single-neuron
recordings
MPIs: Dr. John P. O’Doherty and Dr. Ueli Rutishauser
PROJECT SUMMARY
Flexible goal-directed decision-making is a core aspect of higher-order adaptive biological intelligence. A number
of psychiatric disorders involve impairments in goal-directed decision-making, yet the current lack of even a basic
understanding of how goal-directed action selection is implemented at the neuronal level in humans hinders our
ability to pinpoint these neuropsychiatric dysfunctions. In particular, it is completely unknown how goals, and the
stimuli and actions that need to be selected from in order to pursue them, are represented at the level of single
neurons, nor how goals get selected from available possible goals.
 Here we will characterize the functional contribution of human ventromedial prefrontal (vmPFC), dorsal
anterior cingulate (dACC) and pre-supplementary motor area (pre-SMA) in these processes. We will first test the
longstanding proposal never tested at the neuronal level in humans that the value of stimuli is especially
represented by neurons in vmPFC, while the value of actions are more represented by neurons in dorsal cortical
areas such as the pre-SMA. We will then address how goals themselves are represented. In the real world,
animals including humans need to select a goal before any action is performed. Thus, there is a hierarchical
process of goal selection followed by action selection. We hypothesize that the vmPFC plays a specific role in
goal-valuation and selection, while neurons in dorsomedial areas including pre-SMA and dACC will play more of
a role in valuing and selecting the actions that implement the chosen goal. Most decision-making studies focus
either on action or stimulus selection, but don’t address how goals get selected in the first place. We will use
bespoke behavioral tasks to allow us to distinguish between these different goal and action-related computations
and analyze single neuron data simultaneously collected from these brain areas through the lens of
computational reinforcement-learning models. The significance of this proposal is that we will gain for the first
time, a comprehensive understanding of the functions of the human PFC in goal-directed decision-making at
cellular resolution while shedding light on the neural mechanisms of goal-representation and selection which
hitherto has been virtually unstudied. Consequently, the proposed project is highly significant in terms of the
potential impact that will be made toward understanding the distinct role of different human PFC subregions in
goal-directed decision-making.

## Key facts

- **NIH application ID:** 10910140
- **Project number:** 5R01MH133729-02
- **Recipient organization:** CALIFORNIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** JOHN P O'DOHERTY
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $423,307
- **Award type:** 5
- **Project period:** 2023-09-01 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10910140

## Citation

> US National Institutes of Health, RePORTER application 10910140, Probing the neural computations underlying goal-directed decision-making in humans with single-neuron recordings (5R01MH133729-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10910140. Licensed CC0.

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