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The White Matter Functional Abnormalities in Patients with Transient Ischemic Attack: A Reinforcement Learning
Huibin Ma1,2, Zhou Xie1, Lina Huang3
1School of Information and Electronics Technology, Jiamusi University, Jiamusi, China.
Neural Plasticity
|October 27, 2022
Summary
Transient ischemic attack (TIA) is linked to stroke risk. This study found abnormal white matter (WM) activity in TIA patients using resting-state fMRI, showing potential for WM function as a diagnostic marker.
Area of Science:
- Neuroscience
- Radiology
- Medical Imaging
Background:
- Transient ischemic attack (TIA) is a significant risk factor for stroke.
- Previous research focused on gray matter (GM) alterations in TIA patients.
- Functional abnormalities in white matter (WM) in TIA patients remain understudied.
Purpose of the Study:
- To investigate functional abnormalities in the low-frequency range of WM in TIA patients.
- To explore if altered WM function can serve as a diagnostic indicator for TIA.
- To apply resting-state metrics and reinforcement learning for TIA classification.
Main Methods:
- Utilized resting-state functional magnetic resonance imaging (rs-fMRI) on 48 TIA patients and 41 healthy controls (HCs).
- Compared low-frequency fluctuations in WM using amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF).
- Employed a Q-learning algorithm, a reinforcement learning method, with ALFF and fALFF values as diagnostic features.
Main Results:
- TIA patients exhibited decreased ALFF in specific WM regions (e.g., right cingulate gyrus, left superior corona radiata).
- Reduced fALFF was observed in TIA patients in areas including the right cerebral peduncle and middle cerebellar peduncle.
- The Q-learning model achieved 82.02% accuracy, 85.42% sensitivity, 78.05% specificity, and an AUC of 0.87.
Conclusions:
- Abnormal low-frequency WM functional alterations are present in TIA patients.
- WM functional neural activity shows potential as a neuromarker for TIA classification.
- Findings provide new insights into TIA pathophysiology from a WM functional perspective.
