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Unsupervised Feature Learning Improves Prediction of Human Brain Activity in Response to Natural Images

Figure 3

Preferred parameter maps of the SC model.

The phase, location, orientation and spatial frequency preference of the simple and complex cells were quantified as the corresponding parameters of Gabor wavelets that were fit to their receptive fields. Each pixel in a parameter map shows the corresponding preferred parameter of a simple or complex cell. The adjacent simple and complex cells had similar location, orientation and spatial frequency preference but different phase preference.

Figure 3

doi: https://doi.org/10.1371/journal.pcbi.1003724.g003