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Vol.3 , No. 6, Publication Date: Oct. 17, 2017, Page: 54-63
 and deoxy-hemoglobin (deoxy-Hb), using functional near-infrared spectroscopy (fNIRS). To demonstrate the validity of the proposed method, we analyze hemodynamic data recorded from human subjects performing an orthogonal movement task. Our results show that phase space plots can quantify the dynamic time-varying relationships between the two variables based on the trajectory of the loci of data points in the phase space plots. In particular, the location of the phase space plots in different quadrants provides a specific coupling relationship between the two hemodynamic variables. The orientation of the loci of points characterizes further the relationship between these two variables, which can be directly or inversely proportional. The locus of the trajectory along a straight line or an elliptical path can reveal the phase relationship between the two variables. Thus, using phase space analysis on these two simultaneously recorded hemodynamic variables can uniquely identify the movement direction encoded by the motor cortex.&picture=http://www.aascit.org/aascit/decorators/img/journal/893.jpg)
| [1] | Nicoladie Tam, Department of Biological Sciences, University of North Texas, Denton, USA. |
| [2] | Luca Pollonini, Departments of Engineering Technology, University of Houston, Houston, USA. |
| [3] | George Zouridakis, Departments of Engineering Technology, University of Houston, Houston, USA; Biomedical Engineering, University of Houston, Houston, USA; Electrical & Computer Engineering, University of Houston, Houston, USA. |
In this study, we propose the use of phase space plot analysis to characterize coupling relationships between two simultaneously recorded hemodynamic variables, i.e., oxy-hemoglobin (oxy-Hb) and deoxy-hemoglobin (deoxy-Hb), using functional near-infrared spectroscopy (fNIRS). To demonstrate the validity of the proposed method, we analyze hemodynamic data recorded from human subjects performing an orthogonal movement task. Our results show that phase space plots can quantify the dynamic time-varying relationships between the two variables based on the trajectory of the loci of data points in the phase space plots. In particular, the location of the phase space plots in different quadrants provides a specific coupling relationship between the two hemodynamic variables. The orientation of the loci of points characterizes further the relationship between these two variables, which can be directly or inversely proportional. The locus of the trajectory along a straight line or an elliptical path can reveal the phase relationship between the two variables. Thus, using phase space analysis on these two simultaneously recorded hemodynamic variables can uniquely identify the movement direction encoded by the motor cortex.
Keywords
Optical Imaging, Near Infrared Spectroscopy, Phase Space Plot, Phase Space Analysis, Movement Decoding, Brain Hemodynamics
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