The initial torsional Ocular Following Response (tOFR) in humans: A response to the total motion energy in the stimulus?

Abstract

We recorded the initial torsional Ocular Following Responses (tOFRs) elicited at short latency by visual images that occupied the frontal plane and rotated about the lines of sight. Using 1-D radial gratings, the local spatio-temporal characteristics of these tOFRs closely resembled those we previously reported for the hOFRs to horizontal motion with 1-D vertical gratings. When the 1-D radial grating was subdivided into a number of concentric annuli, each with the same radial thickness, tOFRs were less than predicted from the sum of the responses to the individual annuli: spatial normalization. However, the normalization was much weaker than that which we previously reported for the hOFRs. Further, when the number, thickness and contrast of these concentric annuli were varied systematically, the latency and magnitude of the tOFRs were well described by single monotonic functions when plotted against the product of the Total Area of the Annuli and the Square of their Michelson Contrast (“A*C 2”), consistent with the hypothesis that the onset and magnitude of the initial tOFR are determined by the Total Motion Energy in the stimulus. When our previously published hOFR data were plotted against A*C 2, a single monotonic function sufficed to describe the latency but not the magnitude.

Coordinated Control of Three-Dimensional Components of Smooth Pursuit to Rotating and Translating Textures

“…Average torsional velocity gain in our study was 0.013 in experiment 1 and 0.01 in experiment 2. These values are slightly lower than those reported in the literature, 8,55,56 likely due to the smaller size of stimuli used in our study (48-128 diameter) and the fact that torsional velocity gain scales with stimulus size (Fig. 4C).…”

“…[56][57][58] Hence, one could argue that observers' texture pursuit in our study might be a superposition of classical (horizontal/2D) point pursuit and rotational OKN/OFR. While such an account can explain effects of stimulus size and speed, 56 it would predict an additive mechanism, creating symmetric effects of rotational direction (natural versus unnatural rotation) on torsional speed, because CW and CCW rotation produce effects of equal magnitude on torsional OKN. 8 However, results in Figure 3A show that the addition of stimulus rotation does not simply add to or subtract from baseline torsion by a fixed magnitude.…”

“…[7][8][9][10]55,56 Even though most of these studies used large rotating textures, horizontal and rotational OFRs can also be elicited by smaller stimuli. [56][57][58] Hence, one could argue that observers' texture pursuit in our study might be a superposition of classical (horizontal/2D) point pursuit and rotational OKN/OFR. While such an account can explain effects of stimulus size and speed, 56 it would predict an additive mechanism, creating symmetric effects of rotational direction (natural versus unnatural rotation) on torsional speed, because CW and CCW rotation produce effects of equal magnitude on torsional OKN.…”

“…59 Our finding shows departure from Listing's law that depends on such stimulus motion, consistent with the view that pursuit serves to stabilize a relatively small moving target close to the fovea. It is important to note that torsional velocity gain is usually very low, less than 0.1 8,55,56 ; that is, the eye rotates at less than 10% of the rotational target speed. Average torsional velocity gain in our study was 0.013 in experiment 1 and 0.01 in experiment 2.…”

Retinal visual processing constrains human ocular following response

“…Figure 5H shows how the parameter A varies with contrast, when all the other parameters were held fixed. These dependencies were very well fit by a power function using the following expression (Sheliga, Fitzgibbon & Miles, 2009): $$K\ast {\mathrm{C}}^{-n}+A_0$$ where K is a scaling coefficient, C is the stimulus contrast, n is an exponent, A 0 is an asymptote ( r 2 were 0.999 for all three subjects). Fits are shown by continuous lines in Figure 5H, and the best-fit coefficients can be found in Table S3 of the Supplementary Material.…”