# Volitional control of neural activity in the oculomotor system

> **NIH NIH R21** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2021 · $181,457

## Abstract

PROJECT SUMMARY
Sensorimotor transformations are mediated by premotor brain networks where individual neurons represent
sensory, cognitive, and movement-related information. In the superior colliculus (SC), a central hub for
producing visually-guided saccadic eye movements, many neurons emit a burst of action potentials both in
response to a visual stimulus and when generating an eye movement command. These so-called visuomotor
neurons project to the brainstem burst generator that produces the saccade. Thus, this downstream element is
challenged to differentiate between the incoming “visual” and “motor” bursts. Multiple mechanisms have been
proposed to account for movement generation. The “fixed threshold” hypothesis posits that a saccade is
produced once the firing rate of either an individual neuron or across a population crosses a threshold, which
only happens during the motor burst. Existing data, however, indicate that a simple thresholding mechanism is
likely not sufficient and requires consideration of other frameworks. The “optimal subspace” hypothesis uses a
dynamical systems approach to propose that a movement is generated when the population activity enters or
resides within a particular region of state space. This implies that the state space representations of SC visual
and motor bursts are dissociable. The “temporal stability” hypothesis states that a movement is generated
when bursting activity across a population of neurons preserves consistent temporal structure for a period of
time. Indeed, the stability of SC population activity is reduced during a visual response (“unstable” temporal
structure) and increased during an eye movement (“stable” temporal structure). We seek a framework that
reconciles these models. Our central hypothesis is that SC population activity is decoded as a movement
command when it both exhibits high temporal structure and resides within an optimal subspace. Our specific
aim is to employ a closed-loop brain-computer interface in which monkeys are trained to control an auditory
cursor by volitionally modulating the activity pattern across multiple SC neurons to lie within a visual or motor
subspace and to be temporally stable or unstable. We will first test the optimal subspace and temporal stability
frameworks individually before pitting the two against each other in a 2x2 design. Examining the trials in which
an eye movement is observed will reveal the patterns used by population activity to represent a movement
command. We predict that the animals will be able to modulate population activity along both visual-motor
subspace and stable-unstable dimensions, but that the likelihood of movement generation will be the highest
when the population activity is both stable and in the optimal subspace.

## Key facts

- **NIH application ID:** 10074569
- **Project number:** 5R21EY030667-02
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Neeraj J Gandhi
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $181,457
- **Award type:** 5
- **Project period:** 2020-01-01 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10074569

## Citation

> US National Institutes of Health, RePORTER application 10074569, Volitional control of neural activity in the oculomotor system (5R21EY030667-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10074569. Licensed CC0.

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