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Spatio-Temporal Fractal Dimension Analysis from Resting State EEG Signals in Parkinson's Disease
Juan Ruiz de Miras1,2, Chiara-Camilla Derchi2, Tiziana Atzori2
1Software Engineering Department, University of Granada, 18071 Granada, Spain.
Entropy (Basel, Switzerland)
|July 29, 2023
Summary
Four-dimensional fractal dimension (4DFD) analysis reveals distinct complexity patterns in electroencephalogram (EEG) signals of Parkinson's disease (PD) patients. This novel method shows potential for diagnosing PD by identifying unique brain dynamics.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Signal Processing
Background:
- Electroencephalogram (EEG) complexity analysis is crucial for understanding neurodegenerative disorders like Parkinson's disease (PD).
- Fractal dimension (FD) quantifies complexity but its application to PD EEG is underexplored.
- Existing methods lack detailed spatio-temporal characterization of brain dynamics in PD.
Purpose of the Study:
- To investigate the spatio-temporal characteristics of EEG signals in Parkinson's disease using four-dimensional fractal dimension (4DFD).
- To evaluate the diagnostic potential of 4DFD as a classifier for PD.
- To explore the relationship between brain dynamics and PD using advanced complexity measures.
Main Methods:
- Analysis of 42 resting-state EEG recordings from 27 PD patients and 15 healthy controls (HC).
- Source reconstruction of EEG to generate 3D cortical activation point clouds.
- Application of a sliding window (1-second) and box-counting algorithm to compute 4DFD.
Main Results:
- Significantly higher 4DFD values were observed in the PD group compared to HC (p < 0.001).
- 4DFD achieved an area under the curve (AUC) of 0.97 in receiver operating characteristic (ROC) analysis, indicating strong diagnostic performance.
- The findings highlight distinct spatio-temporal complexity differences in PD brain activity.
Conclusions:
- 4DFD is a sensitive measure for detecting alterations in brain dynamics associated with Parkinson's disease.
- This method shows promise as a non-invasive diagnostic tool for PD.
- Further research can explore 4DFD for disease progression monitoring and therapeutic response assessment.
