Receptive Field Inference with Localized Priors

doi:10.1371/journal.pcbi.1002219

Receptive Field Inference with Localized Priors

Figure 5

Comparison of error rates on simulated data.

Responses of a pixel Gabor filter (shown in Fig. 4 A) were simulated using white noise stimuli (left) or “naturalistic” 1/F Gaussian stimuli (right). (A): Filter error using white noise stimuli, for varying amounts of training data (See Methods). (B) Average filter error under each method. (C–D) Analogous to A–B, but for 1/F stimuli. For both kinds of stimuli, ALDsf achieved error rates almost 2 times smaller than ASD, the next best method. By examining horizontal slices through panels (A) and (C), it is apparent that traditional methods (ML and ridge regression) required four times more data on white noise stimuli, and twenty to thirty times more data on 1/F stimuli, to achieve the same error rate as ALDsf.

doi: https://doi.org/10.1371/journal.pcbi.1002219.g005