Poster E94, Monday, March 26, 2:30-4:30 pm, Exhibit Hall C
Neural correlates of executed and imagined joystick directional movements: A functional near-infrared spectroscopy study
Matthew A. Mathison1, Donald C. Rojas1; 1Colorado State University
Motor-based brain computer interfaces (BCIs) attempt to restore and/or enhance motor functioning by measuring brain signals and converting them to computerized output. Given the high temporal resolution and low risk, the majority of extant BCI research has utilized electroencephalography (EEG) to measure these signals. Relative to EEG, functional near-infrared spectroscopy (fNIRS) offers greater resistance to noise and motion, higher spatial resolution, and simple setup but has lower temporal resolution. Few BCI studies have utilized fNIRS as the sole imaging method and none have combined a high-density optode array with a paradigm in which the imagery task closely mirrored the motor goal. The current task utilized a high-density array consisting of 46 sources and 32 detectors, forming 150 channels. Twenty-four participants were asked to complete a series of imagined and executed joystick deviations in one of four directions, indicated by an on-screen prompt. During each stimulus presentation, participants were asked to repeatedly move the joystick for sixteen seconds in the designated direction at a rate of one movement per second, in synchrony with an auditory tone. Results indicated significant differences in hemodynamic activity during executed conditions relative to imagined conditions. More specifically and of greater interest for BCI purposes, significant activation differences were observed in multiple brain regions (e.g. motor, premotor, and posterior parietal cortices) for each imagined movement direction compared to other imagined movements. These results lend support for the use of fNIRS in BCI. Future research could implement a machine learning algorithm to classify movement directions in real-time.
Topic Area: PERCEPTION & ACTION: Motor control