Ocular-Following Responses (OFRs) to broadband visual stimuli of varying motion coherence.

Poster Presentation 53.416: Tuesday, May 21, 2024, 8:30 am – 12:30 pm, Pavilion
Session: Motion: Detection

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Boris M Sheliga1 (), Edmond J FitzGibbon1, Christian Quaia1, Richard J Krauzlis1; 1Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health

Manipulations of the strength of visual motion coherence have been widely used to study behavioral and neural mechanisms of visual motion processing. Here we asked how changing the strength of motion coherence in different spatial frequency (SF) bands of a broadband stimulus impacts Ocular-Following Responses (OFRs). We recorded horizontal OFRs in three human subjects using synthesized broadband stimuli: a sum of 1D vertical sine wave gratings (SWs) whose SF ranged from 0.0625 to 4 cpd in 0.05 log2(cpd) steps. Every 20 ms a proportion of SWs—from 25% to 100%—shifted in the same direction by ¼ of their respective wavelengths (motion) whereas the rest of SWs were assigned a random phase (flicker) or shifted by ½ of their respective wavelengths (counterphase) or remained stationary (stationary): 25-100% motion coherence. The magnitude of the OFRs decreased as the proportion of ‘not-in-motion’ SWs and/or their contrast increased. The effects were SF-dependent: for flicker and stationary SWs, SFs in the range of 0.3-0.6 cpd were the most disruptive; with counterphase SWs, low SFs were more effective. The data were quantitatively well described by a model which combined two factors: (1) an excitatory drive determined by a weighted sum of moving SF components scaled by (2) a SF-weighted contrast normalization term. All weight functions were SF-dependent. The model functions for motion and counterphase were inverted (log)cumulative Gaussians whose offset and sigma were the same; the amplitude was smaller for the counterphase function. The model functions for flicker and stationary SWs were (log)Gaussians whose offset and sigma were the same; the amplitude was smaller for stationary SWs. The differences in the model weight scaling are consistent with the known dependence of SF components' weights upon the stimulus temporal frequency (Quaia et al. 2017; Sheliga et al. 2020).

Acknowledgements: Supported by the Intramural Program of the National Eye Institute at the National Institutes of Health (NIH).