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Shin'ya Nishida, Kaoru Amano, Mark Edwards, David R. Badcock; Spatial frequency tuning of motion integration across space and orientation. Journal of Vision 2007;7(9):399. doi: https://doi.org/10.1167/7.9.399.
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© ARVO (1962-2015); The Authors (2016-present)
Motion sensors early in motion processing (e.g., V1) have small receptive fields and are selective for orientation. The sensor signals are integrated across space and orientation in later stages (e.g., MT/V5). The motion sensors are also tuned to spatial frequency. Using global motion stimuli comprised of drifting-carrier (static-envelope) Gabors (Nishida et al, 2006, Journal of Vision, 6(6), 1084a), we examined the role of spatial frequency (SF) when local 1D motion signals are simultaneously integrated across space and orientation. Signal Gabors (S) had carrier drift-velocities consistent with a given global-2D velocity, while the drift velocities of the noise Gabors (N) were inconsistent. First, we varied the carrier SF independently for S and N. The noise masking effects, estimated from the threshold S/N ratio required to identify global motion direction, showed broad low-pass tuning regardless of the SF of S. The results remained the same when we used random orientations, or changed orientation similarity between S and N. This broadband tuning is consistent with previous studies using global motion stimuli comprised of bandpass 2D dots. Second, we used two signal groups, S1 and S2 (no noise Gabors), with each group having a common SF and orientation. When S1 and S2 had similar SFs, they were perceived to move coherently in the global IOC direction for a wide range of S1–S2 density ratios. However, such stable integration was not observed when S1 and S2 had a 2-octave SF difference even if their orientation difference was small. These results are in contrast to the noise masking effect and to the results for standard plaid stimuli. In conclusion, motion integration across space and orientation is not simply broadband in SF, retaining selectively possibly for segmenting motion signals of separate objects based on SF differences.
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