Inferring synaptic excitation/inhibition balance from field potentials

Abstract

Neural circuits sit in a dynamic balance between excitation (E) and inhibition (I). Fluctuations in E:I balance have been shown to influence neural computation, working memory, and information flow, while more drastic shifts and aberrant E:I patterns are implicated in numerous neurological and psychiatric disorders. Current methods for measuring E:I dynamics require invasive procedures that are difficult to perform in behaving animals, and nearly impossible in humans. This has limited the ability to examine the full impact that E:I shifts have in cognition and disease. In this study, we develop a computational model to show that E:I changes can be estimated from the power law exponent (slope) of the electrophysiological power spectrum. Predictions from the model are validated in published data from two species (rats and macaques). We find that reducing E:I ratio via the administration of general anesthetic in macaques results in steeper power spectra, tracking conscious state over time. This causal result is supported by inference from known anatomical E:I changes across the depth of rat hippocampus, as well as oscillatory theta-modulated dynamic shifts in E:I. Our results provide evidence that E:I ratio may be inferred from electrophysiological recordings at many spatial scales, ranging from the local field potential to surface electrocorticography. This simple method for estimating E:I ratio-one that can be applied retrospectively to existing data-removes a major hurdle in understanding a currently difficult to measure, yet fundamental, aspect of neural computation.

Differential contributions of subthalamic beta rhythms and neural noise to Parkinson motor symptoms

“…These findings emphasize its physiological origins, and are in line with previous works: arecent study demonstrated that ECoG and EEG electrophysiological neural noise correlates with age and cognitive impairments [21], and it has been associated with an increase in baseline neural spiking activity [28]. It has been hypothesized that increases in the neural noise are a consequence of pathological decoupling between population spiking activity and low-frequency oscillatory neural field [18], and is associated with an imbalance between synaptic excitation and inhibition [29]. Further research is needed to define how background neural activity and oscillatory components interact in PD and how it can affect neural communication in the basal-ganglia-thalamocortical network.…”

Changes in EEG multiscale entropy and power‐law frequency scaling during the human sleep cycle

“…A computational model that incorporated the differential time constants of glutamatergic (AMPA) and GABAergic synaptic currents found that a reduction in the E:I ratio led to more negatively sloped PSDs, while an increased ratio was associated with slope flattening (Gao et al, 2017; but see Lombardi et al, 2017). Corroborating evidence comes from the observation that the PSD becomes more negatively sloped in electrocorticographic (ECoG) recordings of rhesus monkeys undergoing propofol-induced sedation (Gao et al, 2017).…”

Electrophysiological Frequency Band Ratio Measures Conflate Periodic and Aperiodic Neural Activity

“…If a considerable proportion of the variance of band ratios measures is due to aperiodic 661 properties, and not well described or interpreted as band specific changes, then it becomes an 662 open question to ask what the physiological interpretation should be, and therefore how these 663 findings should be interpreted. One hypothesis is that the aperiodic properties of neural time series 664 may relate the relative balance of excitatory and inhibitory activity(Gao et al, 2017). Though further 665 work is required to explore this hypothesis and how it relates to measurements done with band 666 ratios, this does suggest a potential link between what has been measured in band ratios, as a 667 correlate of various cognitive markers and disease states, and potential interpretations related to 668 excitation and inhibition.…”