ePrints

Hetereogeneity in Neuronal Intrinsic Properties: A Possible Mechanism for Hub-Like Properties of the Rat Anterior Cingulate Cortex during Network Activity

Lookup NU author(s): Natalie Adams, Professor Miles Whittington, Dr Fiona LeBeau

Downloads

• Published version [.pdf]

Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

© 2017 Adams et al. The anterior cingulate cortex (ACC) is vital for a range of brain functions requiring cognitive control and has highly divergent inputs and outputs, thus manifesting as a hub in connectomic analyses. Studies show diverse functional interactions within the ACC are associated with network oscillations in the β (20-30 Hz) and γ (30-80 Hz) frequency range. Oscillations permit dynamic routing of information within cortex, a function that depends on bandpass filter-like behavior to selectively respond to specific inputs. However, a putative hub region such as ACC needs to be able to combine inputs from multiple sources rather than select a single input at the expense of others. To address this potential functional dichotomy, we modeled local ACC network dynamics in the rat in vitro. Modal peak oscillation frequencies in the β and γ frequency band corresponded to GABAAergic synaptic kinetics as seen in other regions; however, the intrinsic properties of ACC principal neurons were highly diverse. Computational modeling predicted that this neuronal response diversity broadened the bandwidth for filtering rhythmic inputs and supported combination-rather than selectionof different frequencies within the canonical γ and β electroencephalograph bands. These findings suggest that oscillating neuronal populations can support either response selection (routing) or combination, depending on the interplay between the kinetics of synaptic inhibition and the degree of heterogeneity of principal cell intrinsic conductances.

Publication metadata

Author(s): Adams NE, Sherfey JS, Kopell NJ, Whittington MA, LeBeau FEN

Publication type: Article

Publication status: Published

Journal: eNeuro

Year: 2017

Volume: 4

Issue: 1

Online publication date: 07/02/2017

Acceptance date: 14/01/2017

Date deposited: 07/11/2017

ISSN (print): 2373-2822

Publisher: Society for Neuroscience

URL: https://doi.org/10.1523/ENEURO.0313-16.2017

DOI: 10.1523/ENEURO.0313-16.2017

PubMed id: 28275720

Altmetrics

Share