Purchase this article with an account.
Laurent Caplette, Bruno Wicker, Frédéric Gosselin; Top-down modulation of spatial frequency extraction. Journal of Vision 2016;16(12):1173. doi: 10.1167/16.12.1173.
Download citation file:
© 2017 Association for Research in Vision and Ophthalmology.
According to prominent models of object recognition, the early extraction of low spatial frequencies (SF) modulates in a top-down fashion the later extraction of high SFs. In the present study, we investigated the precise time course of SF extraction during object recognition in 49 healthy adults. On each trial, a short video (333 ms), in which the SFs of an object were randomly sampled across time, was presented. An object name followed and subjects had to indicate if it matched the object. We then performed multiple linear regressions between SF x time sampling planes and accuracy. We observed a continuous extraction of low SFs (1-21.5 cycles per image, cpi) with an extraction of higher SFs (up to 36 cpi) afterwards (t > 4.00, p < .05). This means that some information was extracted at specific moments regardless of what was seen before (i.e., ballistically). Next, we performed the regressions after having weighted trials according to the quantity of low SFs (1-20 cpi) shown in the first 167 ms. We observed that high SFs (up to 35 cpi), but also lower SFs (as low as 3 cpi), led to more accurate responses when they were preceded by low SFs (t > 3.78, p < .05). These results indicate that SF extraction is modulated by the earlier extraction of low SFs (i.e., adaptively). To disentangle adaptive and ballistic aspects of visual processing, we analyzed the modulation of SFs in every frame by low SFs in every preceding frame. Information around 150-242 ms was exclusively modulated by low SFs around 80-96 ms (t > 3.96, p < .05). Altogether, these results suggest a top-down modulation of SF extraction, but not limited to high SFs, and occurring at specific moments.
Meeting abstract presented at VSS 2016
This PDF is available to Subscribers Only