# Imaging decision-related neural cascades in the human brain

## TL;DR

This paper introduces a new method to observe brain activity during decision-making with high precision, revealing a complex sequence of neural events linked to decision confidence.

## Contribution

A novel encoding model combining EEG and fMRI data enables unprecedented spatiotemporal analysis of human brain dynamics during perceptual decisions.

## Key findings

- The method reveals a sequential reactivation of pre-response brain networks during perceptual decisions.
- The magnitude of this neural cascade correlates with decision confidence.
- Combining EEG and fMRI provides insights unattainable with either technique alone.

## Abstract

Perceptual decisions depend on coordinated patterns of neural activity cascading across the brain, running in time from stimulus to response and in space from primary sensory regions to the frontal lobe. Measuring this cascade and how it flows through the brain is key to developing an understanding of how our brains function. However observing, let alone understanding, this cascade, particularly in humans, is challenging. Here, we report a significant methodological advance allowing this observation in humans at unprecedented spatiotemporal resolution. We use a novel encoding model to link simultaneously measured electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) signals to infer the high-resolution spatiotemporal brain dynamics taking place during rapid visual perceptual decision-making. After demonstrating the methodology replicates past results, we show that it uncovers a previously unobserved sequential reactivation of a substantial fraction of the pre-response network whose magnitude correlates with decision confidence. Our results illustrate that a temporally coordinated and spatially distributed neural cascade underlies perceptual decision-making, with our methodology illuminating complex brain dynamics that would otherwise be unobservable using conventional fMRI or EEG separately. We expect this methodology to be useful in observing brain dynamics in a wide range of other mental processes.