Dynamic functional connectivity and gene expression correlates in temporal lobe epilepsy: insights from hidden markov...

Area of Science:

• Neuroscience
• Epilepsy Research
• Computational Psychiatry

Background:

• Temporal lobe epilepsy (TLE) is characterized by abnormal dynamic functional connectivity.
• The precise temporal brain activity changes and underlying molecular mechanisms in TLE remain largely unknown.

Purpose of the Study:

• To investigate dynamic brain activity patterns in TLE patients using Hidden Markov Model (HMM) analysis.
• To explore the temporal dynamics of brain activity in TLE patients with cognitive impairment (TLE-CI).
• To examine gene expression profiles linked to dynamic brain states in TLE.

Main Methods:

• Resting-state functional MRI (rs-fMRI) data from 84 TLE patients and 35 healthy controls (HCs).
• Hidden Markov Model (HMM) analysis to identify brain states and their temporal dynamics.
• Analysis of gene expression data using the Allen Human Brain Atlas (AHBA).

Main Results:

• Five distinct HMM states were identified.
• TLE and TLE-CI patients showed significant differences in state occupancy, duration, and transition rates compared to HCs.
• Dynamic brain states were associated with the default mode network (DMN), subcortical network (SCN), and cerebellum network (CN).
• 1580 genes, primarily involved in neuronal signaling and synaptic function, were significantly associated with dynamic brain states in TLE.

Conclusions:

• HMM analysis reveals distinct dynamic neural activity patterns in TLE.
• These findings deepen the understanding of the neurobiological basis of TLE and TLE-CI.
• A significant link exists between dynamic neural configurations and gene expression in TLE.