Asymmetric transfer of perceptual learning of luminance- and contrast-modulated motion

Abstract

Perceptual learning was used as a tool for studying motion perception. The pattern of transfer of learning of luminance- (LM) and contrast-modulated (CM) motion is diagnostic of how their respective processing pathways are integrated. Twenty observers practiced fine direction discrimination with either additive (LM) or multiplicative (CM) mixtures of a dynamic noise carrier and a radially isotropic texture modulator. The temporal frequency was 10 Hz, speed was 10 deg/s, and duration was 400 ms, with feedback. Group 1 pre-tested CM for 2 blocks, trained LM for 16 blocks, and post-tested CM for 6 blocks during 6 sessions on separate days. In Group 2, the LM and CM roles were reversed. The d' improved almost twofold in both groups. There seemed to be full transfer from CM to LM but no significant transfer from LM to CM. The pattern of post-switch improvement was asymmetric as well-no further learning during the LM post-test versus rapid relearning during the CM post-test. These strong asymmetries suggest a dual-pathway architecture with Fourier channels sensitive only to LM signals and non-Fourier channels sensitive to both LM and CM. We hypothesize that the channels tuned for the same motion direction but different carriers are integrated using a MAX operation.

Dissociation of first- and second-order motion systems by perceptual learning

“…None of the three previous experiments investigating transfer of learning between Fourier and non-Fourier motion tasks (Chen et al, 2009; Petrov & Hayes, 2010; Zanker, 1999) yielded the clean double dissociation observed in the present study. On the contrary, the finding common to all three of these studies was that skill acquired through training in non-Fourier motion tasks transfers effectively to LD motion tasks; however, skill acquired through training in LD motion tasks fails to transfer to non-Fourier tasks.…”

“…A similar result was obtained by Petrov and Hayes (2010). Their LD stimuli consisted of dynamic white noise combined additively with isotropically, band-pass filtered noise fields translating rigidly so as to produce 10-Hz temporal modulation at the center spatial frequency of the filtered noise.…”

“…Furthermore, training in the 8-Hz CD motion task improved performance in both the CD and LD motion tasks across all six temporal frequencies. As was observed by Petrov and Hayes (2010), this suggests that the third-order motion system (Lu & Sperling, 1995), which cuts off around 4 Hz, probably plays a negligible role with these stimuli.…”

A robust perception based method for iris tracking

“…It means that the evolution of luminance and contrast over time in a fixed location cannot be neglected. In particular, it is possible to define a first order motion stimulus, that is related to the spatio-temporal variation of the luminance, and a second order motion stimulus which is related to the motion of a contrast modulated texture [36,23,19,29]. Also in this case the two stimuli are almost independent and the global visual stimulus is the sum of the two different spatio-temporal stimuli.…”

“…One of the most interesting neurological results is that human eyes are attracted by very few points (regions) of the observed scene [18,27,30]. In addition, human eye reacts to a moving stimulus which can be modeled as a combination of luminance modulated (first order motion) and contrast modulated (second order motion) sinusoidal stimulus [36,23,19,29]. With regard to face processing, eyes belong to these attentional points [21] and iris represents its prominent and highly contrasted component; moreover iris is a moving and textured eye component.…”