# Population Neural Activity Mediating Sensory Perception Across Modalities

> **NIH NIH R01** · STANFORD UNIVERSITY · 2020 · $1,004,773

## Abstract

Project Summary:
Natural sensory inputs are typically complex, and often combine multiple modalities. Human speech, for
example, combines auditory signals with visual cues, such as facial expressions, that inform the interpretation
of the spoken words. As individual sensory pathways only provide a partial representation of the sensory
information available, selecting the context-appropriate behavioral response to a multimodal stimulus often
requires integrating information across modalities. How do neural circuits perform this fundamental
computation?
Our current understanding of sensory processing is predominantly built upon studies that have focused on
single sensory modalities, working into the brain beginning from sensory receptors. As a result, we have a
deep understanding of peripheral circuit computations in many different experimental contexts. However,
working inward, cell-type by cell-type, has left our understanding of the circuits and computational principles
that link sensation to action incomplete. Moreover, experimental strategies that focus exclusively on single
sensory modalities cannot, by design, lead to insights into how the unified percepts that guide behavior can be
assembled from information emerging in separate sensory processing streams. Here we leverage whole-brain
imaging and advanced computational approaches to establish the fruit fly Drosophila as a model system for
uncovering fundamental principles underpinning multisensory integration.
This proposal has three goals. First, we will optimize whole-brain imaging in this experimental system, and use
this technology to comprehensively characterize population dynamics underpinning the sensations of vision,
mechanosensation and taste. Second, we will systematically quantify circuit interactions between these
sensory modalities and across-animal variability, testing computational models of statistical inference, and
identifying the algorithmic bases of multimodal integration. Third, we will link population dynamics to the
response properties of single cell-types, providing a powerful path to characterizing circuit and synaptic
mechanisms. Taken together, by developing and applying improved methods for large-scale monitoring of
neural activity, combined with computational modeling and quantitative analysis, this project will greatly expand
our understanding of sensory processing mechanisms across the brain.

## Key facts

- **NIH application ID:** 9999691
- **Project number:** 5R01NS110060-03
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Thomas Robert Clandinin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,004,773
- **Award type:** 5
- **Project period:** 2018-09-30 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9999691

## Citation

> US National Institutes of Health, RePORTER application 9999691, Population Neural Activity Mediating Sensory Perception Across Modalities (5R01NS110060-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9999691. Licensed CC0.

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