# Project B:  Neural basis of causal inference and sensory updating in trial-based tasks in monkeys

> **NIH NIH U19** · UNIVERSITY OF ROCHESTER · 2021 · $645,303

## Abstract

Project Summary
The world's complexity makes sensory information ambiguous. A set of signals sweeping across the retina, for
instance, might be generated by a moving object or by the animal's own motion. The brain resolves this
ambiguity by constructing an internal model of reality that associates patterns in sensory data with events in
the world, in a process called causal inference. To support adaptive action, the brain's estimates of all relevant
variables must be updated to remain consistent with physics under the current interpretation of the scene, as
well as with each other. This proposal focuses on perceptual interactions among object motion, self-motion,
and depth. This project will test the predictions of models from Project A for how causal inference should
update these related sensory variables. Based on previous work and preliminary data, the overall hypothesis is
that parietal (7a) and prefrontal (8av) areas signal whether or not an object moves in the world, and that these
signals flow through feedback projections to update sensory representations of object depth in area MT and
self-motion velocity in area MSTd. The goal of this project is to use traditional, trial-based tasks to determine
whether, and if so how, causal inferences are propagated back to sensory cortex to update representations of
task-relevant variables in monkeys. The goal of Aim 1 is to test whether causal inference modulates low-level
sensory representations of motion by examining neural correlates of optic flow parsing, a phenomenon in
which the perceived direction of an object's motion is strongly and predictably influenced by background optic
flow. Aim 2 will test directly if sensory representations of task variables are updated to maintain consistency
with beliefs about the world. Monkeys will judge whether an object moves in the world and also report its depth,
while neural populations in parietal area 7a, prefrontal area 8av, and sensory areas MT and MSTd are
recorded. The theoretical framework, supported by preliminary behavioral data, predicts that this causal
inference about object motion will induce specific patterns of bias in estimates of depth and self-motion
velocity, and that neural estimates of motion and depth in MT and MSTd will update to remain consistent with
behavior. To identify the neural circuitry necessary for causal inference and sensory updating, Aim 3 will
inactivate feedback pathways with muscimol or optogenetics while neural activity is recorded in sensory
representations, as animals perform the same task as in Aim 2. Aim 1 is expected to establish that causal
inference modulates early visual processing, and to identify the areas where these effects are implemented.
Aim 2 will provide the first cellular and neural population evidence of causal inference and sensory updating by
belief propagation. Aim 3 will establish a neural circuit that is necessary for mediating causal inference and for
updating sensory representations. Together,...

## Key facts

- **NIH application ID:** 10225404
- **Project number:** 5U19NS118246-02
- **Recipient organization:** UNIVERSITY OF ROCHESTER
- **Principal Investigator:** GREGORY C DEANGELIS
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $645,303
- **Award type:** 5
- **Project period:** 2020-08-01 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10225404

## Citation

> US National Institutes of Health, RePORTER application 10225404, Project B:  Neural basis of causal inference and sensory updating in trial-based tasks in monkeys (5U19NS118246-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10225404. Licensed CC0.

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