Human anterior thalamic stimulation evoked cortical potentials align with intrinsic functional connectivity

Area of Science:

• Neuroscience
• Systems Neuroscience
• Human Brain Imaging

Background:

• Understanding human thalamocortical networks is crucial for explaining complex behaviors due to the thalamus's role in cortico-subcortical communication.
• Functional magnetic resonance imaging (fMRI) has enabled mapping of resting-state functional connectivity (RSFC), but the electrophysiological basis of these networks remains unclear.

Purpose of the Study:

• To investigate the electrophysiological basis of human thalamocortical network architecture.
• To determine if anterior nucleus of the thalamus (ANT) stimulation evokes cortical potentials that align with intrinsic functional connectivity patterns.

Main Methods:

• Utilized stereoelectroencephalography (SEEG) in 10 epilepsy patients with electrodes in cortical regions and the anterior nucleus of the thalamus (ANT).
• Delivered single-pulse electrical stimulation to the ANT and recorded evoked cortical potentials.
• Compared SEEG-derived evoked potentials with normative resting-state functional connectivity (RSFC) data from a large cohort (n=1000).

Main Results:

• Demonstrated spatial convergence between ANT stimulation-evoked cortical potentials and normative RSFC.
• Identified strong ANT connectivity with higher-order association cortices beyond the Papez circuit, including the precuneus, angular gyrus, dorsal lateral prefrontal cortex, and anterior insula.
• Found that the spatial distribution and magnitude of evoked cortical responses precisely matched the pattern and strength of normative RSFC.

Conclusions:

• Provided the first electrophysiological evidence that electrical activity evoked by ANT stimulation propagates along intrinsic thalamocortical brain networks.
• Confirmed that intrinsic brain networks dictate the flow of electrical activity in the human thalamocortical system.
• Highlighted the utility of combining SEEG with normative connectomics for elucidating brain network dynamics.