# Behavior-dependent classification of neocortical cell types

> **NIH NIH R21** · YALE UNIVERSITY · 2021 · $209,375

## Abstract

PROJECT SUMMARY
 The classification of cell types in the cerebral cortex is a major goal in neuroscience, guided by the
expectation that elaborating a complete neuronal census will provide important insights into both healthy brain
function and the pathophysiology of disease. Traditional schemes for grouping cells have largely focused on
morphological, electrophysiological, and hodological features derived from ex vivo preparations. However, the
development of tools for labeling and recording neurons in vivo presents substantial opportunities to broaden
our knowledge of what constitutes a class of cells. Here, we propose that in vivo activity is an additional axis on
which to categorize neuronal types. Our overall goal is to develop a novel strategy for linking behaviorally
relevant activity with a traditional characterization of cellular properties. To that end, we focus on the role of
behavioral state in modulating the firing patterns of neurons in the mouse neocortex. Several recent studies
have demonstrated that locomotion is associated with significant but heterogeneous alteration in activity, with
different cells showing enhanced or suppressed output during periods of motor behavior. We will take advantage
of a novel green fluorescent protein, called CaMPARI2, enabling us to label cortical neurons that are active
during arousal by coupling light stimulation with real-time detection of locomotion. This approach is followed by
ex vivo analyses comparing locomotion-sensitive (photo-converted, red) and -insensitive (green) cells side by
side. In Aim 1, we characterize the regional and laminar differences in cells throughout the neocortex whose
activity is modulated by locomotion. In Aim 2, we examine the electrophysiological, morphological, and
transcriptional properties of these cells. Overall, these efforts to gain a complete picture of functional neuronal
diversity will be essential for understanding healthy brain function and for driving new interventions aimed at the
prevention and treatment of neuropsychiatric disorders.

## Key facts

- **NIH application ID:** 10059269
- **Project number:** 5R21MH121841-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Michael James Higley
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $209,375
- **Award type:** 5
- **Project period:** 2019-12-01 → 2021-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10059269

## Citation

> US National Institutes of Health, RePORTER application 10059269, Behavior-dependent classification of neocortical cell types (5R21MH121841-02). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10059269. Licensed CC0.

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