# How the connectivity structure of neuronal networks influences responses to oscillatory stimuli

## TL;DR

This study explores how the structural connectivity of cortical neuronal networks influences their responses to oscillatory stimuli, revealing complex interactions and the challenge of inferring network motifs from response patterns.

## Contribution

It systematically analyzes the effects of network structure and stimulus parameters on oscillatory responses, highlighting the complexity of linking responses to specific anatomical motifs.

## Key findings

- Stimulating inhibitory neurons in upper layers reproduces gamma resonances.
- Network amplification and visibility of stimuli depend on specific motifs.
- Responses involve multiple interacting modes, complicating motif inference.

## Abstract

Propagation of oscillatory signals through the cortex and coherence is shaped by the connectivity structure of neuronal circuits. This study systematically investigates the network and stimulus properties that shape network responses. The results show how input to a cortical column model of the primary visual cortex excites dynamical modes determined by the laminar pattern. Stimulating the inhibitory neurons in the upper layer reproduces experimentally observed resonances at gamma frequency whose origin can be traced back to two anatomical sub-circuits. We develop this result systematically: Initially, we highlight the effect of stimulus amplitude and filter properties of the neurons on their response to oscillatory stimuli. Subsequently, we analyze the amplification of oscillatory stimuli by the effective network structure. We demonstrate that the amplification of stimuli, as well as their visibility in different populations, can be explained by specific network patterns. Inspired by experimental results we ask whether the anatomical origin of oscillations can be inferred by applying oscillatory stimuli. We find that different network motifs can generate similar responses to oscillatory input, showing that resonances in the network response cannot, straightforwardly, be assigned to the motifs they emerge from. Applying the analysis to a spiking model of a cortical column, we characterize how the dynamic mode structure, which is induced by the laminar connectivity, processes external input. In particular, we show that a stimulus applied to specific populations typically elicits responses of several interacting modes. The resulting network response is therefore composed of a multitude of contributions and can therefore neither be assigned to a single mode nor do the observed resonances necessarily coincide with the intrinsic resonances of the circuit.