An Analysis of the Transitions Between Down and Up States of the Cortical Slow Oscillation Under Urethane Anaesthesia
Overview
Authors
Affiliations
We study the dynamics of the transition between the low- and high-firing states of the cortical slow oscillation by using intracellular recordings of the membrane potential from cortical neurons of rats. We investigate the evidence for a bistability in assemblies of cortical neurons playing a major role in the maintenance of this oscillation. We show that the trajectory of a typical transition takes an approximately exponential form, equivalent to the response of a resistor-capacitor circuit to a step-change in input. The time constant for the transition is negatively correlated with the membrane potential of the low-firing state, and values are broadly equivalent to neural time constants measured elsewhere. Overall, the results do not strongly support the hypothesis of a bistability in cortical neurons; rather, they suggest the cortical manifestation of the oscillation is a result of a step-change in input to the cortical neurons. Since there is evidence from previous work that a phase transition exists, we speculate that the step-change may be a result of a bistability within other brain areas, such as the thalamus, or a bistability among only a small subset of cortical neurons, or as a result of more complicated brain dynamics.
Consciousness is supported by near-critical slow cortical electrodynamics.
Toker D, Pappas I, Lendner J, Frohlich J, Mateos D, Muthukumaraswamy S Proc Natl Acad Sci U S A. 2022; 119(7).
PMID: 35145021 PMC: 8851554. DOI: 10.1073/pnas.2024455119.
Maksimov A, Diesmann M, van Albada S Front Comput Neurosci. 2018; 12:44.
PMID: 30042668 PMC: 6048296. DOI: 10.3389/fncom.2018.00044.
Sykes M, Matheson N, Brownjohn P, Tang A, Rodger J, Shemmell J Front Neural Circuits. 2016; 10:80.
PMID: 27766073 PMC: 5052269. DOI: 10.3389/fncir.2016.00080.
Characterization of K-complexes and slow wave activity in a neural mass model.
Weigenand A, Schellenberger Costa M, Ngo H, Claussen J, Martinetz T PLoS Comput Biol. 2014; 10(11):e1003923.
PMID: 25392991 PMC: 4230734. DOI: 10.1371/journal.pcbi.1003923.
A probabilistic framework for a physiological representation of dynamically evolving sleep state.
Dadok V, Kirsch H, Sleigh J, Lopour B, Szeri A J Comput Neurosci. 2013; 37(1):105-24.
PMID: 24363031 DOI: 10.1007/s10827-013-0489-x.