# Multisensory Integration in Action: a Multineuronal and Feedback-Control Approach

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $336,456

## Abstract

Project Summary: Multisensory processing is vital for daily activities such as walking and manipulating
objects, yet much remains unknown about the neural mechanisms by which sensory information is integrated
in the central nervous system to influence motor control. We address this knowledge gap by analyzing
behavioral and multi-neuronal multi-area recordings in the cerebral cortex of Rhesus monkeys trained to
perform a prolonged motor control task (the critical stability task (CST)) that cannot be performed without
continuous sensory feedback (visual and/or tactile). Rhesus monkeys will perform the CST using hand
movements or a brain-computer interface (BCI) to control a cursor, while we manipulate sensory feedback.
Neural activity will be recorded from primary visual (V1), somatosensory (S1) and motor cortices (M1). Our
motivating hypothesis is that cortical processing is highly flexible, and can be rapidly reconfigured based on the
immediate sensory and motor context. Several specific predictions flow from this perspective. First, we predict
that primary motor cortex (M1) will exhibit a strong sensory response during a motor task that requires ongoing
sensory feedback. Second, we hypothesize that V1 neurons adopt tactile responses, and S1 adopts visual
responses, when both are relevant for ongoing motor control. Third, we expect that altering the signal quality of
one sensory modality will shift their relative contribution to neural responses, consistent with Bayesian
estimation. Animals will perform the CST using BCI control as a more dramatic test of cortical flexibility. During
BCI control, sensory responses should be reduced in M1, since the BCI decoder cannot distinguish sensory
responses from motor commands, which would diminish the quality of control. If multisensory integration is
reduced in M1 under BCI control, then it must occur elsewhere. We hypothesize that there will be an enhanced
cross-modal sensory representation in the primary sensory cortices under BCI control, in comparison to hand
control. We approach these questions through a collaboration that combines expertise in sensorimotor
neurophysiology with expertise in computational modeling of multisensory integration. The findings of this
research will improve the understanding of the neural mechanisms of multimodal sensory integration during
continuous motor tasks, and will have clinical implications for BCIs and advanced prostheses design.

## Key facts

- **NIH application ID:** 9844419
- **Project number:** 5R01HD090125-04
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Aaron Paul Batista
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $336,456
- **Award type:** 5
- **Project period:** 2017-02-01 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9844419

## Citation

> US National Institutes of Health, RePORTER application 9844419, Multisensory Integration in Action: a Multineuronal and Feedback-Control Approach (5R01HD090125-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9844419. Licensed CC0.

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