Work

Modeling relationships between rhythmic processes and neuronal spike timing

Year: 2022

Type: article

Abstract: Statistical models that incorporate neural spiking history and relationships to the phase of ongoing oscillations in the local field potential robustly capture and predict neuronal engagement in rhythmic processes. These models constitute a powerful tool to systematically test explicit hypotheses regarding the specific rhythmic currents that constrain neural spiking activity over time and during different behaviors.

Source: Journal of Neurophysiology

DOI: 10.1152/jn.00423.2021

Authors: Pamela D. Rivière, Gabriel Schamberg, Todd P. Coleman, Lara M. Rangel

Institutions: Massachusetts Institute of Technology, University of California System

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: hybrid

Funders: National Science Foundation, University of California, San Diego, National Institute of Mental Health, Kavli Institute for Brain and Mind, University of California, San Diego