Cross-Frequency Coupling and Intelligent Neuromodulation

Author:

Yeh Chien-Hung1,Zhang Chuting1,Shi Wenbin1,Lo Men-Tzung2,Tinkhauser Gerd3,Oswal Ashwini4

Affiliation:

1. School of Information and Electronics, Beijing Institute of Technology, Beijing, China.

2. Department of Biomedical Sciences and Engineering, National Central University, Taoyuan, Taiwan.

3. Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.

4. MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.

Abstract

Cross-frequency coupling (CFC) reflects (nonlinear) interactions between signals of different frequencies. Evidence from both patient and healthy participant studies suggests that CFC plays an essential role in neuronal computation, interregional interaction, and disease pathophysiology. The present review discusses methodological advances and challenges in the computation of CFC with particular emphasis on potential solutions to spurious coupling, inferring intrinsic rhythms in a targeted frequency band, and causal interferences. We specifically focus on the literature exploring CFC in the context of cognition/memory tasks, sleep, and neurological disorders, such as Alzheimer's disease, epilepsy, and Parkinson's disease. Furthermore, we highlight the implication of CFC in the context and for the optimization of invasive and noninvasive neuromodulation and rehabilitation. Mainly, CFC could support advancing the understanding of the neurophysiology of cognition and motor control, serve as a biomarker for disease symptoms, and leverage the optimization of therapeutic interventions, e.g., closed-loop brain stimulation. Despite the evident advantages of CFC as an investigative and translational tool in neuroscience, further methodological improvements are required to facilitate practical and correct use in cyborg and bionic systems in the field.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Applied Mathematics,General Mathematics

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