Graduation Year
12-1992
Document Type
Thesis
Degree
Master of Science
Degree Name
Master of Science (M.S.)
Department
Biology
Degree Granting Department
Biology
Major Professor
Steward Swihart, Ph.D.
Committee Member
Gary Arendash, Ph.D.
Committee Member
Frank Friedl, Ph.D.
Committee Member
Paschal Strong, Ph.D.
Abstract
Electrical potentials were recorded from scalp of normal male subjects while they were viewing continuously moving sinusoidal gratings. Responses from the occipital cortex were amplified, digitized, stored and then transformed from the time domain to the frequency domain using a microcomputer based Fast Fourier Transform algorithm. High frequency components (Beta Activity) of the resulting power spectrum were analyzed for evidence on neural generators (electrical sources) in the striate cortex driven presumably by transient-cells (Y-cells or Magnocellular) responding to the continuously moving grating. Several stimulus parameters were examined: angular velocity, spatial frequency, direction (orientation), color, and intensity. A16 Hz component of the power spectrum associated with motion detection manifested at the cortical level was identified, Motion Evoked Potentials (MEPs). Statistical analyses revealed that responses were dependent on the angular velocity of the stimulus, the airection of motion, and the particular color of the stimulus, but not on spatial frequency or stimulus intensity.
Three physiological explanations of the results are discussed: (1) cortico-thalamo-cortical reverberatory circuits, (2) intrathalamic or intracortical reverberatory circuits, and (3) after discharges of local neurons. It was concluded that an intracortical reverberatory circuit is the most likely neuronal generator of the Motion Evoked Response and that the amplitude of the response is dependent on angular velocity.
Scholar Commons Citation
Painter, Howard E., "Human Motion Detection Evaluated Through an Evoked Cortical Potential Frequency Spectrum" (2023). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/10014