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Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Published on: October 30, 2018

Analysis for brain activities during operations using measured EEG.

Yoshio Kaji¹, Masatake Akutagawa, Fumio Shichijo

¹Faculty of Engineering, Tokushima Bunri University, 1314-1 Shido, Sanuki-shi, Kagawa 769-2193 Japan.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

|February 7, 2007

Summary

This study introduces moving average type neural networks (MANN) for electroencephalogram (EEG) analysis. MANN effectively monitors brain condition changes during surgery by analyzing EEG data, confirming its clinical usefulness.

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Cortical Source Analysis of High-Density EEG Recordings in Children

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Published on: June 30, 2014

Area of Science:

Neuroscience
Medical Engineering
Artificial Intelligence

Background:

Electroencephalogram (EEG) analysis is a standard method for monitoring brain activity.
Cerebral blood flow monitoring is crucial during surgeries involving arterial occlusion to prevent complications.
Existing methods for EEG analysis may require enhancement for real-time surgical monitoring.

Purpose of the Study:

To develop integrated software for comprehensive EEG analysis.
To propose and evaluate the Moving Average type Neural Network (MANN) for EEG analysis.
To assess the capability of MANN in detecting changes in brain condition during critical surgical procedures.

Main Methods:

EEG data was segmented into overlapping 30-second periods.
A Moving Average type Neural Network (MANN) was trained to predict EEG signals using previous samples.
Connection weights from trained MANNs were compared using inner product to assess brain condition changes.

Main Results:

The Moving Average type Neural Network (MANN) demonstrated effectiveness in analyzing EEG data.
The study confirmed the clinical utility of MANN analysis for monitoring brain conditions.
Deviation Ratio (DR) analysis, in conjunction with MANN, showed significant results in evaluating brain state changes.

Conclusions:

The proposed MANN method is a viable tool for analyzing EEG signals.
This approach offers a promising method for real-time brain condition monitoring during surgery.
The integration of MANN and DR analysis provides a robust system for assessing neurological status.