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Updated: Sep 15, 2025

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A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
Published on: November 13, 2016
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Mapping human thalamocortical connectivity with electrical stimulation and recording.
Dian Lyu1, James Robert Stiger1, Zoe Lusk1
1Laboratory of Behavioral and Cognitive Neuroscience, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Nature Neuroscience
|July 15, 2025
Summary
This study maps brain connectivity using electrical stimulation, revealing distinct patterns for information transmission. A new waveform linked to thalamic stimulation, delayed-onset theta oscillations, was identified in cortical regions.
Area of Science:
- Neuroscience
- Electrophysiology
- Brain Connectivity
Background:
- The brain's functional architecture relies on electrophysiological interactions between cortical and subcortical structures.
- Understanding these causal connections is crucial for deciphering brain function.
Purpose of the Study:
- To create an atlas of electrophysiological causal connections across numerous human brain sites.
- To identify distinct spectral signatures and connectivity patterns associated with information transmission.
Main Methods:
- Utilized repeated single-pulse electrical stimulations and intracranial electrode recordings in 27 human participants.
- Mapped connectivity across 4,864 brain sites, including cortical regions and thalamic nuclei.
Main Results:
- Identified distinct spectral signatures corresponding to perturbations in specific brain areas.
- Observed highly organized yet distinct patterns of causal connectivity, suggesting separate information transmission modes.
- Discovered a novel waveform, delayed-onset theta oscillations, linked to thalamic stimulation in cortical areas.
Conclusions:
- The findings provide a detailed map of the human brain's functional architecture.
- The identified connectivity patterns and novel waveform offer insights into brain information processing.
- This data can inform the development of biologically-inspired computational models.

