Searching for Cross-Diagnostic Convergence: Neural Mechanisms Governing Excitation and Inhibition Balance in Schizophrenia and Autism Spectrum Disorders

Abstract

Recent theoretical accounts have proposed excitation and inhibition (E/I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. We highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with electroencephalography, magnetoencephalography, proton magnetic resonance spectroscopy, and functional magnetic resonance imaging, including effects observed both during task and at rest. Throughout this review, we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human noninvasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions.

Keywords: Autism; Computational modeling; E/I balance; Mechanism; Neuroimaging; Review; Schizophrenia.

Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1. Considering the Complexity of E/I Imbalance Effects on the Cortical Microcircuit Level in the Context of Shared versus Distinct Neurobiology in Schizophrenia and Autism Spectrum Disorder

1A. Several genes associated with GABAergic and glutamatergic functioning have been implicated across both ASD and SCZ. 1B. The expression of such genes, and the time course at which their expression might go awry, can differ across development. Developmental differences in gene expression affecting E/I balance could contribute to variations in both neural circuitry alterations and ultimate clinical phenotypes. Different colors conceptually highlight distinct time courses and time-dependent patterns of gene expression that may relate to disturbances in each disorder. 1C. Alterations, such as deletions or duplications, of genes altered in SCZ and/or ASD can result in microcircuit dysfunction, characterized by imbalance in E/I neurotransmission, as a result of changes at E->E, E->I, or I->E synapses. 1D. Adapted from(163). The nature of E/I disruption can take any of several different forms (left panel), which in turn would contribute to variable baseline and task-evoked abnormalities in excitatory and inhibitory neural functions. 1E. Based on the complex interactions between the processes depicted in panels 1A–1D, differential neuropathology may emerge from many of the same underlying alterations and may be characterized by regional variability in the degree to which E/I balance is disturbed(101), thereby differentially impacting neural computation at the system level(175). Surface models adapted from Glasser et al.(176).

Figure 2. Neuroimaging Paradigms Tapping into E/I Balance in Sensory and Associative Circuits

2A. Visual Evoked Potential (VEP) paradigm, in which EEG is recorded over occipital cortex to contrast-reversing checkerboard stimuli. This paradigm results in a canonical waveform, wherein successive peaks reflect glutamatergic and GABAergic activity. It has been used in both SCZ and ASD. 2B. Adapted from Seymour et al.(123). Surround suppression stimuli, wherein activation elicited by a grating-filled annulus is suppressed due to lateral inhibition in the context of parallel (top right panel) but not perpendicular (bottom right panel) surround. Seymour and colleagues(123) showed that patients with SCZ exhibit reduced surround suppression effects (left panel). This type of paradigm is also being used in studies of individuals with ASD.

Figure 3. Computational and Pharmacological Studies Informing E/I Imbalance Cross-diagnostically

Figure adapted from(177). 3A. Computational modeling of microcircuit E/I balance predicts neural activity that is disrupted when E/I ratio is elevated (i.e. disinhibition induced via reduction of feedback inhibition shown with red arrow). This computational manipulation generates predictions relevant for E/I balance both at rest and during task states(100, 135, 178). 3B. Pharmacological models, such as NMDAR antagonism via ketamine, known to disrupt E/I balance can be used to test computational models to determine whether well understood in vivo disruptions result in predicted alterations in neural activity. 3C. Findings from patients with SCZ or ASD can then be compared to results generated by computational and pharmacological models to gain a better understanding of the underlying mechanisms driving the disease state. This iterative ‘computational psychiatric’ framework can help deepen insight into the links between circuit mechanism, neural system deficits, and symptoms across diagnoses(179).