# Can we infer excitation-inhibition balance from the spectrum of population activity?

## TL;DR

The paper shows that changes in brain activity patterns may not reliably indicate shifts in excitation-inhibition balance.

## Contribution

The study demonstrates that spectral slope is not a robust indicator of excitation-inhibition balance in neural networks.

## Key findings

- Spectral slope does not predict the ratio of excitatory and inhibitory synaptic conductance.
- Changes in spectral slope align with synaptic weight changes only in limited simulation scenarios.
- Interpreting spectral slope as EI balance is cautioned for a wide range of network parameters.

## Abstract

Networks in the brain operate in an excitation-inhibition (EI) balanced state. Altered EI balance underlies aberrant dynamics and impaired information processing. Given its importance, it is crucial to establish non-invasive measures of the EI balance. Previous studies have suggested that relative EI balance can be inferred from the spectrum of the population signals such as Local Field Potentials (LFP), Electroencephalogram (EEG) and Magnetoencephalography (MEG). This idea exploits the fact that in most cases excitatory and inhibitory synapses have quite different time constants. However, it is not clear to what extent spectral slope of population activity is related to the network parameters that define the EI balance e.g. excitatory and inhibitory conductance. To address this question we simulated two different types of recurrent networks and measured spectral slope for a wide range of parameters. Our results show that the slope of the spectrum cannot predict the ratio of excitatory and inhibitory synaptic conductance. Only in a small set of simulations a change in the spectral slope was consistent with the corresponding change in the synaptic weights or inputs to the network. Thus, our results show that we should be careful in interpreting the change in the slope of the population activity spectrum.

Here the authors show that a change in the slope of the population activity spectrum, an emerging biomarker of brain state and health, should not be interpreted as a change in the balance of excitation and inhibition in a network for a wide range of parameters.