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Analysis of the neural mechanism of spectra decrease in MCI by a thalamo-cortical coupled neural mass model
Dong Cui1, Han Li1, Pengxiang Liu1
1Hebei Key Laboratory of Information Transmission and Signal Processing, School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, People's Republic of China.
Journal of Neural Engineering
|December 20, 2022
Summary
Mild cognitive impairment (MCI) is associated with decreased brain activity, potentially due to reduced cortical synaptic connectivity. This study proposes a new neural mass model to investigate this EEG spectra decrease mechanism in MCI patients.
Area of Science:
- Computational neuroscience
- Neuroimaging
- Cognitive neurology
Background:
- Mild cognitive impairment (MCI) is characterized by a decrease in electroencephalogram (EEG) spectral power.
- The underlying neurophysiological mechanisms of this spectral decrease in MCI remain incompletely understood.
- Advanced computational models are needed to investigate brain activity alterations in neurological conditions.
Purpose of the Study:
- To develop and utilize a novel thalamo-cortical coupled neural mass model (TCC-NMM) for simulating intracerebral electrophysiological activities.
- To investigate the neurophysiological mechanisms responsible for the observed spectra decrease in EEG signals of MCI patients.
- To identify specific neural parameters correlated with cognitive function in MCI.
Main Methods:
- Proposed a thalamo-cortical coupled neural mass model (TCC-NMM) to simulate electrophysiological activity.
- Employed the unscented Kalman filter (UKF) algorithm for reverse parameter identification within the TCC-NMM.
- Combined TCC-NMM simulations with UKF analysis of real EEG data from MCI patients and healthy controls, using t-tests and Pearson correlation.
Main Results:
- Simulation indicated that decreased cortical synaptic connectivity constants (C1) lead to spectral power reduction in the TCC-NMM.
- EEG analysis revealed significantly lower C1 values in MCI patients compared to controls in frontal and occipital regions.
- Identified C1 parameters positively correlated with Montreal Cognitive Assessment (MoCA) scores in both MCI and control groups.
Conclusions:
- The study suggests that reduced cortical synaptic connectivity, specifically from pyramidal cells to excitatory interneurons (eIN), is a potential mechanism underlying EEG spectral power decrease in MCI.
- The developed TCC-NMM provides a valuable tool for understanding brain dynamics in neurological disorders.
- Findings highlight the link between synaptic connectivity deficits and cognitive decline in MCI.
