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Cortical Excitation:Inhibition Imbalance Causes Abnormal Brain Network Dynamics as Observed in Neurodevelopmental Disorders


Markicevic, Marija; Fulcher, Ben D; Lewis, Christopher; Helmchen, Fritjof; Rudin, Markus; Zerbi, Valerio; Wenderoth, Nicole (2020). Cortical Excitation:Inhibition Imbalance Causes Abnormal Brain Network Dynamics as Observed in Neurodevelopmental Disorders. Cerebral Cortex, 30(9):4922-4937.

Abstract

Abnormal brain development manifests itself at different spatial scales. However, whether abnormalities at the cellular level can be diagnosed from network activity measured with functional magnetic resonance imaging (fMRI) is largely unknown, yet of high clinical relevance. Here a putative mechanism reported in neurodevelopmental disorders, that is, excitation-to-inhibition ratio (E:I), was chemogenetically increased within cortical microcircuits of the mouse brain and measured via fMRI. Increased E:I caused a significant "reduction" of long-range connectivity, irrespective of whether excitatory neurons were facilitated or inhibitory Parvalbumin (PV) interneurons were suppressed. Training a classifier on fMRI signals, we were able to accurately classify cortical areas exhibiting increased E:I. This classifier was validated in an independent cohort of Fmr1y/- knockout mice, a model for autism with well-documented loss of parvalbumin neurons and chronic alterations of E:I. Our findings demonstrate a promising novel approach towards inferring microcircuit abnormalities from macroscopic fMRI measurements.

Abstract

Abnormal brain development manifests itself at different spatial scales. However, whether abnormalities at the cellular level can be diagnosed from network activity measured with functional magnetic resonance imaging (fMRI) is largely unknown, yet of high clinical relevance. Here a putative mechanism reported in neurodevelopmental disorders, that is, excitation-to-inhibition ratio (E:I), was chemogenetically increased within cortical microcircuits of the mouse brain and measured via fMRI. Increased E:I caused a significant "reduction" of long-range connectivity, irrespective of whether excitatory neurons were facilitated or inhibitory Parvalbumin (PV) interneurons were suppressed. Training a classifier on fMRI signals, we were able to accurately classify cortical areas exhibiting increased E:I. This classifier was validated in an independent cohort of Fmr1y/- knockout mice, a model for autism with well-documented loss of parvalbumin neurons and chronic alterations of E:I. Our findings demonstrate a promising novel approach towards inferring microcircuit abnormalities from macroscopic fMRI measurements.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Neuroscience Center Zurich
04 Faculty of Medicine > Brain Research Institute
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Scopus Subject Areas:Life Sciences > Cognitive Neuroscience
Life Sciences > Cellular and Molecular Neuroscience
Language:English
Date:30 July 2020
Deposited On:21 Jan 2021 14:24
Last Modified:01 Feb 2021 16:27
Publisher:Oxford University Press
ISSN:1047-3211
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/cercor/bhaa084
PubMed ID:32313923

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