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Elife. 2019 Jan 28;8. pii: e42409. doi: 10.7554/eLife.42409.

Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons.

Insanally MN1,2,3,4,5, Carcea I1,2,3,4,5, Field RE1,2,3,4,5, Rodgers CC6,7, DePasquale B8, Rajan K9,10, DeWeese MR11,12, Albanna BF13, Froemke RC1,2,4,5,14.

Author information

1
Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, United States.
2
Neuroscience Institute, New York University School of Medicine, New York, United States.
3
Department of Otolaryngology, New York University School of Medicine, New York, United States.
4
Department of Neuroscience and Physiology, New York University School of Medicine, New York, United States.
5
Center for Neural Science, New York University, New York, United States.
6
Department of Neuroscience, Columbia University, New York, United States.
7
Kavli Institute of Brain Science, Columbia University, New York, United States.
8
Princeton Neuroscience Institute, Princeton University, Princeton, United States.
9
Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, United States.
10
Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, United States.
11
Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States.
12
Department of Physics, University of California, Berkeley, Berkeley, United States.
13
Department of Natural Sciences, Fordham University, New York, United States.
14
Howard Hughes Medical Institute, New York University School of Medicine, New York, United States.

Abstract

Neurons recorded in behaving animals often do not discernibly respond to sensory input and are not overtly task-modulated. These non-classically responsive neurons are difficult to interpret and are typically neglected from analysis, confounding attempts to connect neural activity to perception and behavior. Here, we describe a trial-by-trial, spike-timing-based algorithm to reveal the coding capacities of these neurons in auditory and frontal cortex of behaving rats. Classically responsive and non-classically responsive cells contained significant information about sensory stimuli and behavioral decisions. Stimulus category was more accurately represented in frontal cortex than auditory cortex, via ensembles of non-classically responsive cells coordinating the behavioral meaning of spike timings on correct but not error trials. This unbiased approach allows the contribution of all recorded neurons - particularly those without obvious task-related, trial-averaged firing rate modulation - to be assessed for behavioral relevance on single trials.

KEYWORDS:

behavior; computational biology; cortex; decoding; neuroscience; rat; systems biology

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