# Neural circuits for adaptively biasing decision making

> **NIH NIH R01** · UNIVERSITY OF COLORADO DENVER · 2024 · $332,868

## Abstract

PROJECT SUMMARY (ABSTRACT)
Our long-term goal is to elucidate the systems and circuits, within and across brain regions, responsible for
decision making. The objective of this proposal is to examine the neural circuit basis for how, in the face of
sensory uncertainty, perceptual decisions are adaptively biased to the most valuable option, as instructed by the
recent history of choices and their outcomes. We address this question by focusing on the superior colliculus
(SC), a key midbrain node in the network of brain regions responsible for selecting targets for movement (i.e.,
“spatial choice”), an important form of decision making amenable to circuit-level interrogation. The SC integrates
input from numerous brain regions, has extensive intrinsic circuitry capable of integrating priors with sensory
evidence as required by Bayesian frameworks, and outputs pre-motor orienting commands to downstream motor
nuclei. Given its role as a functional hub for spatial choice, as well as its known cell types and circuitry, the SC
is ideal for examining the neural circuit basis for adaptive decision making and how decisions are influenced by
priors. In particular, the SC receives a robust input – of unknown function – from the mesencephalic
pedunculopontine tegmental nucleus (PPTg), which we have shown represents recent spatial choices and
outcomes. In a set of experiments in behaving mice, we test the overarching hypothesis that the SC adaptively
biases spatial choice by integrating priors represented by PPTg input.
 We use a variant of an established spatial choice task for mice in which the dominant component of an
odor mixture presented at a central port cues whether reward is available at the left or right reward port, and in
which the left/right reward ratio changes across blocks of trials. On trials in which the odor mixture provides only
weak evidence about reward location, decision making can be optimized by biasing choices towards the port
yielding the larger reward. In Aim 1, we test the hypothesis that pre-motor SC output biases choice towards the
most valuable target, by recording and perturbing the activity of genetically defined pre-motor SC neurons during
the task. In Aim 2, we test the hypothesis that PPTg input transmits representations of priors to the SC that
instruct adaptive choice bias in pre-motor SC neurons. We examine whether SC neurons – particularly inhibitory
commissural neurons well positioned to mediating competition between left and right choices – represent choices
and outcomes of previous trials, as we have seen in the PPTg. We then determine whether representations of
priors and choice bias in the SC depend on PPTg input, by perturbing PPTg activity and recording SC activity
during the task.
 If successful, the overall impact of our proposal will be the elucidation of a key circuit mechanism for how
decisions are optimized by priors, a critical nervous system function. In addition, our proposal will enable future
research in...

## Key facts

- **NIH application ID:** 10913624
- **Project number:** 5R01NS129608-02
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** GIDON S FELSEN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $332,868
- **Award type:** 5
- **Project period:** 2023-09-01 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10913624

## Citation

> US National Institutes of Health, RePORTER application 10913624, Neural circuits for adaptively biasing decision making (5R01NS129608-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10913624. Licensed CC0.

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