# Computational modeling reveals biological mechanisms underlying the whisker flick EEG

## TL;DR

This paper uses computational models to explore how whisker flicks in rodents generate specific brainwave patterns, shedding light on neural mechanisms involved.

## Contribution

The study predicts which neural populations contribute to specific EEG components during whisker flick stimulation using computational modeling.

## Key findings

- The initial positive EEG deflection is predicted to be driven by direct thalamic inputs to cortical pyramidal cells.
- The negative EEG deflection involves a complex mix of thalamic and cortical connectivity.
- Modifications in circuit connectivity significantly affect EEG signals without altering firing rates.

## Abstract

Whisker flick stimulation is a commonly used protocol to investigate somatosensory processing in rodents. Neural activity evoked by whisker flicks produces a characteristic electroencephalography (EEG) waveform known as a somatosensory evoked potential. In this paper, we use computational modeling to make predictions about the neural populations that contribute to this signal, either through their own membrane currents or the membrane currents they elicit in downstream populations. While the model cannot fully explain the mechanisms of somatosensory evoked potential (SEP) generation, we predict that the initial positive deflection of the EEG waveform is driven largely by direct thalamic inputs to layer 2/3 and layer 5 pyramidal cells, while the negative deflection is driven by a more complex mix of sources, including thalamic and recurrent cortical connectivity. Small changes to the local connectivity of the circuit can have an important impact on the recorded EEG, without substantially affecting firing rates, suggesting that EEG may be useful in constraining in silico neural models.

•The BBP’s somatosensory cortex model replicates key features of in vivo whisker flick EEG•We predict neural populations’ contributions to different components of the EEG•Changes to circuit connectivity have large impacts on EEG without changing firing rates

The BBP’s somatosensory cortex model replicates key features of in vivo whisker flick EEG

We predict neural populations’ contributions to different components of the EEG

Changes to circuit connectivity have large impacts on EEG without changing firing rates

Systems neuroscience; Sensory neuroscience; Signal processing; Modeling signal processing system; Computer simulation