# Leveraging multisensory decisions to understand brain wide decision circuits

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2021 · $378,300

## Abstract

The goal!of the proposed research is to uncover the brain wide circuits and local computations
that together allow animals to combine multiple, diverse sources of information to guide
decision-making. Specifically, these experiments will investigate how mammals integrate
sensory signals over time and across sensory modalities. The main hypothesis is that in
addition to sense-specific circuits, auditory and visual decisions rely on common, core decision
circuits for decision-related computations, such as evidence accumulation and action selection.
Within these structures, targeted connectivity between excitatory and inhibitory neurons
supports persistent activity and competition for action selection. The proposed method to test
this hypothesis is to measure and manipulate neural activity in mice trained to make perceptual
decisions about auditory and visual stimuli. Three approaches, taken together, form the core of
the proposal to evaluate this hypothesis and provide a new view of decision-making circuits.
First, the degree to which auditory and visual decisions activate overlapping or largely separate
neural structures will be evaluated based on wide field imaging of cortex-wide activity during
decision-making. Cortex-wide activity will be measured in transgenic mice that express calcium
indicators in cortical excitatory neurons. Classifiers and decision-making models we will used to
link activity in a given brain structure to decision-making computations. This approach will
uncover candidate areas that are active during auditory, visual or multisensory decisions.
Next, optogenetic suppression of these candidate areas will be used to evaluate their causal
role in decision-making. A model-based comparison of behavior on suppression and control
trials will evaluate the effects of disruption on decision-related computations such as event
discrimination, evidence accumulation, and action planning.
Finally, areas that are identified as causal for specific decision computations will be investigated
more closely to understand how these computations are implemented by single neurons. 2-
photon microscopy will be used to image populations of single neurons. The experimental
subjects will be transgenic mice in which inhibitory neurons emit red fluorescent light that is
independent of the green fluorescence that is used as an estimate of neural activity. These two
separate signals make it possible to distinguish excitatory from inhibitory neurons and evaluate
their respective roles in decision-making. Single-trial classifiers will be used to evaluate the
ability of excitatory and inhibitory populations to predict the animal’s choice. The outcome of this
experiment will be used to distinguish candidate models of decision-making.

## Key facts

- **NIH application ID:** 10150855
- **Project number:** 5R01EY022979-10
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** ANNE KATHRYN CHURCHLAND
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $378,300
- **Award type:** 5
- **Project period:** 2013-03-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10150855

## Citation

> US National Institutes of Health, RePORTER application 10150855, Leveraging multisensory decisions to understand brain wide decision circuits (5R01EY022979-10). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10150855. Licensed CC0.

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