» Articles » PMID: 36003960

Selective Blockade of Rat Brain T-type Calcium Channels Provides Insights on Neurophysiological Basis of Arousal Dependent Resting State Functional Magnetic Resonance Imaging Signals

Overview
Journal Front Neurosci
Date 2022 Aug 25
PMID 36003960
Authors
Affiliations
Soon will be listed here.
Abstract

A number of studies point to slow (0.1-2 Hz) brain rhythms as the basis for the resting-state functional magnetic resonance imaging (rsfMRI) signal. Slow waves exist in the absence of stimulation, propagate across the cortex, and are strongly modulated by vigilance similar to large portions of the rsfMRI signal. However, it is not clear if slow rhythms serve as the basis of all neural activity reflected in rsfMRI signals, or just the vigilance-dependent components. The rsfMRI data exhibit quasi-periodic patterns (QPPs) that appear to increase in strength with decreasing vigilance and propagate across the brain similar to slow rhythms. These QPPs can complicate the estimation of functional connectivity (FC) rsfMRI, either by existing as unmodeled signal or by inducing additional wide-spread correlation between voxel-time courses of functionally connected brain regions. In this study, we examined the relationship between cortical slow rhythms and the rsfMRI signal, using a well-established pharmacological model of slow wave suppression. Suppression of cortical slow rhythms led to significant reduction in the amplitude of QPPs but increased rsfMRI measures of intrinsic FC in rats. The results suggest that cortical slow rhythms serve as the basis of only the vigilance-dependent components (e.g., QPPs) of rsfMRI signals. Further attenuation of these non-specific signals enhances delineation of brain functional networks.

Citing Articles

Variation in the distribution of large-scale spatiotemporal patterns of activity across brain states.

Meyer-Baese L, Anumba N, Bolt T, Daley L, LaGrow T, Zhang X Front Syst Neurosci. 2024; 18:1425491.

PMID: 39157289 PMC: 11327057. DOI: 10.3389/fnsys.2024.1425491.


Variation in the Distribution of Large-scale Spatiotemporal Patterns of Activity Across Brain States.

Meyer-Baese L, Anumba N, Bolt T, Daley L, LaGrow T, Zhang X bioRxiv. 2024; .

PMID: 38746246 PMC: 11092498. DOI: 10.1101/2024.04.26.591295.

References
1.
Yousefi B, Shin J, Schumacher E, Keilholz S . Quasi-periodic patterns of intrinsic brain activity in individuals and their relationship to global signal. Neuroimage. 2017; 167:297-308. PMC: 5845807. DOI: 10.1016/j.neuroimage.2017.11.043. View

2.
Papp E, Leergaard T, Calabrese E, Johnson G, Bjaalie J . Waxholm Space atlas of the Sprague Dawley rat brain. Neuroimage. 2014; 97:374-86. PMC: 4160085. DOI: 10.1016/j.neuroimage.2014.04.001. View

3.
Thompson G, Magnuson M, Merritt M, Schwarb H, Pan W, McKinley A . Short-time windows of correlation between large-scale functional brain networks predict vigilance intraindividually and interindividually. Hum Brain Mapp. 2012; 34(12):3280-98. PMC: 6870033. DOI: 10.1002/hbm.22140. View

4.
Lu H, Wang L, Rea W, Brynildsen J, Jaime S, Zuo Y . Low- but Not High-Frequency LFP Correlates with Spontaneous BOLD Fluctuations in Rat Whisker Barrel Cortex. Cereb Cortex. 2014; 26(2):683-694. PMC: 4712799. DOI: 10.1093/cercor/bhu248. View

5.
Sherman S . Tonic and burst firing: dual modes of thalamocortical relay. Trends Neurosci. 2001; 24(2):122-6. DOI: 10.1016/s0166-2236(00)01714-8. View