Measurement of excitation-inhibition ratio in autism spectrum disorder using critical brain dynamics

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Bruining , H , Hardstone , R , Juarez-Martinez , E L , Sprengers , J , Avramiea , A-E , Simpraga , S , Houtman , S J , Poil , S-S , Dallares , E , Palva , S , Oranje , B , Matias Palva , J , Mansvelder , H D & Linkenkaer-Hansen , K 2020 , ' Measurement of excitation-inhibition ratio in autism spectrum disorder using critical brain dynamics ' , Scientific Reports , vol. 10 , no. 1 , 9195 . https://doi.org/10.1038/s41598-020-65500-4

Title: Measurement of excitation-inhibition ratio in autism spectrum disorder using critical brain dynamics
Author: Bruining, Hilgo; Hardstone, Richard; Juarez-Martinez, Erika L.; Sprengers, Jan; Avramiea, Arthur-Ervin; Simpraga, Sonja; Houtman, Simon J.; Poil, Simon-Shlomo; Dallares, Eva; Palva, Satu; Oranje, Bob; Matias Palva, J.; Mansvelder, Huibert D.; Linkenkaer-Hansen, Klaus
Contributor: University of Helsinki, Neuroscience Center
University of Helsinki, Matias Palva / Principal Investigator
Date: 2020-06-08
Language: eng
Number of pages: 15
Belongs to series: Scientific Reports
ISSN: 2045-2322
URI: http://hdl.handle.net/10138/316217
Abstract: Balance between excitation (E) and inhibition (I) is a key principle for neuronal network organization and information processing. Consistent with this notion, excitation-inhibition imbalances are considered a pathophysiological mechanism in many brain disorders including autism spectrum disorder (ASD). However, methods to measure E/I ratios in human brain networks are lacking. Here, we present a method to quantify a functional E/I ratio (fE/I) from neuronal oscillations, and validate it in healthy subjects and children with ASD. We define structural E/I ratio in an in silico neuronal network, investigate how it relates to power and long-range temporal correlations (LRTC) of the network's activity, and use these relationships to design the fE/I algorithm. Application of this algorithm to the EEGs of healthy adults showed that fE/I is balanced at the population level and is decreased through GABAergic enforcement. In children with ASD, we observed larger fE/I variability and stronger LRTC compared to typically developing children (TDC). Interestingly, visual grading for EEG abnormalities that are thought to reflect E/I imbalances revealed elevated fE/I and LRTC in ASD children with normal EEG compared to TDC or ASD with abnormal EEG. We speculate that our approach will help understand physiological heterogeneity also in other brain disorders.
Subject: 3112 Neurosciences
RANGE TEMPORAL CORRELATIONS
NEURONAL AVALANCHES
EXCITATION/INHIBITION BALANCE
EPILEPTIFORM ABNORMALITIES
FUNCTIONAL CONNECTIVITY
GAMMA FREQUENCY
RESTING GABA
STATE
NETWORKS
OSCILLATIONS
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