Literature DB >> 26404514

A General Approach for Quantifying Nonlinear Connectivity in the Nervous System Based on Phase Coupling.

Yuan Yang1, Teodoro Solis-Escalante1, Jun Yao2, Andreas Daffertshofer3, Alfred C Schouten1,4, Frans C T van der Helm1.   

Abstract

Interaction between distant neuronal populations is essential for communication within the nervous system and can occur as a highly nonlinear process. To better understand the functional role of neural interactions, it is important to quantify the nonlinear connectivity in the nervous system. We introduce a general approach to measure nonlinear connectivity through phase coupling: the multi-spectral phase coherence (MSPC). Using simulated data, we compare MSPC with existing phase coupling measures, namely n : m synchronization index and bi-phase locking value. MSPC provides a system description, including (i) the order of the nonlinearity, (ii) the direction of interaction, (iii) the time delay in the system, and both (iv) harmonic and (v) intermodulation coupling beyond the second order; which are only partly revealed by other methods. We apply MSPC to analyze data from a motor control experiment, where subjects performed isotonic wrist flexions while receiving movement perturbations. MSPC between the perturbation, EEG and EMG was calculated. Our results reveal directional nonlinear connectivity in the afferent and efferent pathways, as well as the time delay (43 ± 8 ms) between the perturbation and the brain response. In conclusion, MSPC is a novel approach capable to assess high-order nonlinear interaction and timing in the nervous system.

Keywords:  EEG; EMG; Phase coupling; motor control; nonlinear interaction; time delay

Mesh:

Year:  2015        PMID: 26404514     DOI: 10.1142/S0129065715500318

Source DB:  PubMed          Journal:  Int J Neural Syst        ISSN: 0129-0657            Impact factor:   5.866


  15 in total

1.  Quantifying Altered Neural Connectivity of the Stretch Reflex in Chronic Hemiparetic Stroke.

Authors:  Yuan Yang; Nirvik Sinha; Runfeng Tian; Netta Gurari; Justin M Drogos; Julius P A Dewald
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2020-04-07       Impact factor: 3.802

2.  Neurologically Motivated Coupling Functions in Models of Motor Coordination.

Authors:  Piotr Słowiński; Sohaib Al-Ramadhani; Krasimira Tsaneva-Atanasova
Journal:  SIAM J Appl Dyn Syst       Date:  2020-01-14       Impact factor: 2.316

3.  Quantifying the Nonlinear Interaction in the Nervous System Based on Phase-Locked Amplitude Relationship.

Authors:  Yuan Yang; Jun Yao; Julius P A Dewald; Frans C T van der Helm; Alfred C Schouten
Journal:  IEEE Trans Biomed Eng       Date:  2020-01-16       Impact factor: 4.538

Review 4.  Nonlinear System Identification of Neural Systems from Neurophysiological Signals.

Authors:  Fei He; Yuan Yang
Journal:  Neuroscience       Date:  2020-12-11       Impact factor: 3.590

5.  Multi-Phase Locking Value: A Generalized Method for Determining Instantaneous Multi-Frequency Phase Coupling.

Authors:  Bhavya Vasudeva; Runfeng Tian; Dee H Wu; Shirley A James; Hazem H Refai; Lei Ding; Fei He; Yuan Yang
Journal:  Biomed Signal Process Control       Date:  2022-01-07       Impact factor: 3.880

6.  Assessing Neural Connectivity and Associated Time Delays of Muscle Responses to Continuous Position Perturbations.

Authors:  Runfeng Tian; Julius P A Dewald; Nirvik Sinha; Yuan Yang
Journal:  Ann Biomed Eng       Date:  2020-07-23       Impact factor: 3.934

7.  Nonlinear Coupling between Cortical Oscillations and Muscle Activity during Isotonic Wrist Flexion.

Authors:  Yuan Yang; Teodoro Solis-Escalante; Mark van de Ruit; Frans C T van der Helm; Alfred C Schouten
Journal:  Front Comput Neurosci       Date:  2016-12-06       Impact factor: 2.380

8.  Slowly activating outward membrane currents generate input-output sub-harmonic cross frequency coupling in neurons.

Authors:  Nirvik Sinha; C J Heckman; Yuan Yang
Journal:  J Theor Biol       Date:  2020-10-03       Impact factor: 2.691

9.  Nonlinear Modeling of Cortical Responses to Mechanical Wrist Perturbations Using the NARMAX Method.

Authors:  Yuanlin Gu; Yuan Yang; Julius P A Dewald; Frans C T van der Helm; Alfred C Schouten; Hua-Liang Wei
Journal:  IEEE Trans Biomed Eng       Date:  2021-02-18       Impact factor: 4.538

10.  Cross-frequency and iso-frequency estimation of functional corticomuscular coupling after stroke.

Authors:  Ping Xie; Xiaohui Pang; Shengcui Cheng; Yuanyuan Zhang; Yinan Yang; Xiaoli Li; Xiaoling Chen
Journal:  Cogn Neurodyn       Date:  2020-09-16       Impact factor: 3.473

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