Intrinsic dynamic shapes responses to external stimulation in the human brain

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Current computational models of brain activity struggle to differentiate immediate sensory responses from intrinsic neural dynamics.
• Understanding the interplay between external stimuli and the brain's internal network activity is crucial for accurate modeling.

Purpose of the Study:

• To develop and apply a novel computational model that disentangles immediate sensory responses from intrinsic brain dynamics.
• To investigate how the brain's intrinsic recurrent activity influences neural responses to external stimuli.

Main Methods:

• Application of a vector-autoregressive model with external input (VARX) to intracranial recordings in humans.
• Integration of concepts from functional connectivity and encoding models.
• Analysis of neural responses to various sensory stimuli, including scene cuts, eye movements, and sounds.

Main Results:

• The VARX model successfully separated extrinsic stimulus effects from intrinsic recurrent brain dynamics.
• Intrinsic brain dynamics were found to enhance and prolong neural responses to sensory stimuli.
• Failure to account for intrinsic dynamics led to the identification of spurious recurrent connections.
• Recurrent connectivity decreased during movie watching compared to rest.
• External stimuli can reduce intrinsic neural noise, and sensory areas exhibit predominantly outward connections, while higher-order areas show mostly incoming connections.

Conclusions:

• The intrinsic dynamics of the brain play a dominant role in responding to external audiovisual stimuli.
• The brain's intrinsic activity, observed even during rest, significantly shapes its response to sensory input.
• Accurate computational models must account for both extrinsic stimuli and intrinsic neural network properties.