# Millisecond resolution statistics of cortical populations

> **NIH NIH R00** · UNIVERSITY OF COLORADO DENVER · 2020 · $249,000

## Abstract

Project Summary/Abstract
The mammalian brain builds and transforms representations of the outside world through the concerted
activity of populations of neurons, but the extent to which spike times or spike counts are coordinated
within these ensembles beyond pairs is not clear. Models of neural encoding predict variable
frequencies of spike pattern occurrence, and models of decoding delineate requirements for spike time
precision within the population response. While considerable effort has been made toward the
development and refinement of the theoretical basis of such neural coding schemes, and predictions
have been tested against single cell and pairwise data, there has been relatively little experimental data
beyond pairs able to differentiate between competing hypotheses of population coding. The proposed
career development plan aims to marry large-scale electrophysiology in primary visual cortex with
analysis of specific predictions derived from computational and theoretical neuroscience work for spike
time coordination beyond pairwise interactions. The candidate has a deep background in in vivo
experimental techniques and proposes to receive training in the high-dimensional computational
techniques and to use experimental data collected to validate specific theoretical predictions. This
training will establish the skills necessary for a successful independent research career studying the
mechanisms of information representation and transfer in visual cortex, bridging the gap between
experimental and computational neuroscience. The candidate will carry out the mentored phase under
the guidance of Dr. Clay Reid, a world expert in multiple aspects of mammalian central visual
processing including anatomy, physiology, and computation. Additional advising from Dr. Eric Shea-
Brown and Dr. Christof Koch will provide guidance in the theoretical and applied mathematical
approaches required to implement and assess advanced models of neural encoding and decoding. The
training will utilize the strengths of the Allen Institute for Brain Science in collecting large-scale data and
the didactic opportunities at the University of Washington. In the independent phase the candidate will
use the newly acquired analytical and modeling skills in combination with his previous training in
optogenetic techniques to better constrain population measurements. This work will help establish a
unique independent research program to elucidate the mechanisms underlying cortical representation.

## Key facts

- **NIH application ID:** 10006552
- **Project number:** 5R00EY028612-04
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** Daniel James Denman
- **Activity code:** R00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $249,000
- **Award type:** 5
- **Project period:** 2019-09-30 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10006552

## Citation

> US National Institutes of Health, RePORTER application 10006552, Millisecond resolution statistics of cortical populations (5R00EY028612-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10006552. Licensed CC0.

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