Title :
Analysis of visual theta rhythm-experimental and theoretical evidence of visual sniffing
Author :
Kozma, Robert ; Freeman, Walter J.
Author_Institution :
Div. of Comput. Sci., Memphis State Univ., TN, USA
Abstract :
The statistical properties of saccadic time intervals recorded in eye movements in human subjects were calculated. The probability density function of the inter-spike intervals exhibits a Poisson-type behavior with a maximum located at time lags around 600 ms. Such a value agrees well with the frequency of the theta rhythm observed in the visual cortex of mammals, in particular, rabbits. EEGs were recorded from 8×8 arrays of subdural electrodes at high density (6×6 mm) in rabbits trained to discriminate visual stimuli in a classical aversive paradigm. EEG patterns had the form of amplitude and phase modulation of this. The covariance between the spatial events revealed striking peaks in the theta range (2-7 Hz), even when the autospectrum of the EEG failed to show a prominent peak. Comparable sequences of spatial EEG patterns in the olfactory system occur at frequencies in the theta range, reflecting the driving by respiration. These multiple sets of observation suggest that the visual system may be driven by surges of sensory input that are occasioned by saccades. Further studies are indicated to analyze this relationship by cross correlating simultaneous recordings of saccades and scalp EEGs from the occipital leads
Keywords :
chemioception; electroencephalography; eye; probability; statistical analysis; EEGs; Poisson-type behavior; classical aversive paradigm; eye movements; human subjects; inter-spike intervals; mammals; olfactory system; probability density functio; rabbits; respiration; saccades; saccadic time intervals; scalp; spatial events; statistical properties; visual cortex; visual sniffing; visual stimuli; visual theta rhythm; Electrodes; Electroencephalography; Frequency; Humans; Olfactory; Phase modulation; Probability density function; Rabbits; Rhythm; Visual system;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939517