Anatomical identification of extracellularly recorded cells in large-scale multielectrode recordings.

Abstract

This study combines for the first time two major approaches to understanding the function and structure of neural circuits: large-scale multielectrode recordings, and confocal imaging of labeled neurons. To achieve this end, we develop a novel approach to the central problem of anatomically identifying recorded cells, based on the electrical image: the spatiotemporal pattern of voltage deflections induced by spikes on a large-scale, high-density multielectrode array. Recordings were performed from identified ganglion cell types in the macaque retina. Anatomical images of cells in the same preparation were obtained using virally transfected fluorescent labeling or by immunolabeling after fixation. The electrical image was then used to locate recorded cell somas, axon initial segments, and axon trajectories, and these signatures were used to identify recorded cells. Comparison of anatomical and physiological measurements permitted visualization and physiological characterization of numerically dominant ganglion cell types with high efficiency in a single preparation.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1523/JNEUROSCI.3675-14.2015

Publication Info

Li, Peter H, Jeffrey L Gauthier, Max Schiff, Alexander Sher, Daniel Ahn, Greg D Field, Martin Greschner, Edward M Callaway, et al. (2015). Anatomical identification of extracellularly recorded cells in large-scale multielectrode recordings. J Neurosci, 35(11). pp. 4663–4675. 10.1523/JNEUROSCI.3675-14.2015 Retrieved from https://hdl.handle.net/10161/9723.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Schiff

Max Schiff

Assistant Professor of Psychiatry and Behavioral Sciences
Field

Greg D. Field

Adjunct Associate Professor of Neurobiology

My laboratory studies how the retina processes visual scenes and transmits this information to the brain.  We use multi-electrode arrays to record the activity of hundreds of retina neurons simultaneously in conjunction with transgenic mouse lines and chemogenetics to manipulate neural circuit function. We are interested in three major areas. First, we work to understand how neurons in the retina are functionally connected. Second we are studying how light-adaptation and circadian rhythms alter visual processing in the retina. Finally, we are working to understand the mechanisms of retinal degenerative conditions and we are investigating potential treatments in animal models.


Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.