Abstract
Later visual areas become increasingly tolerant to variations in image properties such as object size, location, viewpoint, and so on. This phenomenon is often modeled by a cascade of repeated processing stages in which each stage involves pooling followed by a compressive nonlinearity. One result of this sequence is that stimulus-referred measurements show increasingly large receptive fields and stronger normalization. Here, we apply a similar approach to the temporal domain. Using fMRI and intracranial potentials (ECoG), we develop a population receptive field (pRF) model for temporal sequences of visual stimulation. The model consists of linear summation followed by a time-varying divisive normalization. The same model accurately accounts for both ECoG broadband time course and fMRI amplitudes. The model parameters reveal several regularites about temporal encoding in cortex. First, higher visual areas accumulate stimulus information over a longer time period than earlier areas, analogous to the hierarchically organized spatial receptive fields. Second, we found that all visual areas sum sub-linearly in time: e.g., the response to a long stimulus is less than the response to two successive brief stimuli. Third, the degree of compression increases in later visual areas, analogous to spatial vision. Finally, based on published data, we show that our model can account for the time course of single units in macaque V1 and multiunits in humans. This indicates that for space and time, cortex uses a similar processing strategy to achieve higher-level and increasingly invariant representations of the visual world.
Meeting abstract presented at VSS 2018