A neuronal network model linking subjective reports and objective physiological data during conscious perception

TLDR

Visual perception is linked to sustained V1 activity, widespread cortical activation, gamma oscillations, and P300 waveforms. The study proposes a neuronal network model to explain how physiological signals align with conscious perceptual reports. The model posits that access awareness arises when processed visual stimuli enter a global brain state that connects distant regions, including prefrontal cortex, and it is applied to simulate the attentional blink paradigm. The model reproduces attentional blink features and predicts a nonlinear, all‑or‑none transition to conscious perception, which was confirmed behaviorally in humans.

Abstract

The subjective experience of perceiving visual stimuli is accompanied by objective neuronal activity patterns such as sustained activity in primary visual area (V1), amplification of perceptual processing, correlation across distant regions, joint parietal, frontal, and cingulate activation, γ-band oscillations, and P300 waveform. We describe a neuronal network model that aims at explaining how those physiological parameters may cohere with conscious reports. The model proposes that the step of conscious perception, referred to as access awareness, is related to the entry of processed visual stimuli into a global brain state that links distant areas including the prefrontal cortex through reciprocal connections, and thus makes perceptual information reportable by multiple means. We use the model to simulate a classical psychological paradigm: the attentional blink. In addition to reproducing the main objective and subjective features of this paradigm, the model predicts an unique property of nonlinear transition from nonconscious processing to subjective perception. This all-or-none dynamics of conscious perception was verified behaviorally in human subjects.