Els for each and every topic that met our voxel selection criterion p .see Techniques are shown. All round, the tuning profiles revealed by the weights in each region seem to be broadly constant with tuning revealed by prior studies. We initially describe the weights in two comparably wellunderstood places (V and FFA), after which describe the weights for each and every model for 
all 3 sceneselective regions. In V, the weights for the MedChemExpress PIM-447 (dihydrochloride) Fourier power model (Figures A) show that photos containing high Fourier power have a tendency to elicit responses above the mean. This really is constant with numerous studies showing that V responses boost with growing image contrast (Albrecht and Hamilton, ; Gardner et al). The weights for the subjective distance model show that very distant scenes elicit responses beneath the imply in most V voxels. This is most likely since the most distant scenes (for instance the image of your ocean in Figure A) have low all round Fourier energy. The weights for the object category model show that the GSK1278863 site images with labels for fruit and vegetable, ready meals, and creepy animal all elicit responses above the imply. These are also most likely be associated to distinctive levels of Fourier energy. We analyze the correlations involving Fourier energy and particular object categories, too as other correlations among feature channels in unique models, in detail under. In FFA, the weights for the Fourier power model (Figures D) show that photos with higher frequency energy at tended to elicit BOLD responses above the mean, when high frequency power at vertical and horizontal (and) orientations elicit responses beneath the mean. Numerous prior research have rigorously argued that FFA responds to faces as an alternative to lowlevel image options (Kanwisher andFunctional Location LocalizersVisual regions in retinotopic visual cortex as well as functionally defined categoryselective visual regions have been identified in separate scan sessions applying conventional methods (Spiridon et al ; Hansen et al). Sceneselective places PPA, RSC, and OPA were all defined by a contrast of locations vs. objects. The Fusiform Face Area (FFA) was defined by a contrast of faces vs. objects. The boundaries of every region have been hand drawn on the cortical surface in the locations at which the t statistic for the contrast of locations vs. objects changed most swiftly.RESULTSTo investigate how organic scenes are represented in sceneselective locations within the human brain, we analyzed BOLD fMRI signals evoked by a large set of all-natural pictures (These information had been collected for two studies from our laboratory that were published previouslyNaselaris et al and Stansbury et al). We tested three particular hypotheses about scene representation inFrontiers in Computational Neuroscience Lescroart et al.Competing models of sceneselective areasFIGURE Voxelwise model weights for all models for all voxels in V and FFA. (A) Model weights for the Fourier power model for V. The image inside the decrease part of the panel shows the weight for every single voxel in V that met our choice criterion p see Solutions. Voxels are separated by subject (s), and also the relative size of every subject’s section indicates the relative number of voxels chosen in PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/16369121 V for that topic. marks indicate distinct ROIs in certain subjects with low signal quality (and thus couple of voxels selected for analysis). See Figure S for evaluation of signal across subjects. Every horizontal stripe via the image shows the weights for a various voxel. Voxels are sorted inside every single subject by normalized predic.Els for every subject that met our voxel selection criterion p .see Strategies are shown. Overall, the tuning profiles revealed by the weights in each region seem to be broadly consistent with tuning revealed by prior studies. We initial describe the weights in two comparably wellunderstood areas (V and FFA), after which describe the weights for each model for all 3 sceneselective regions. In V, the weights for the Fourier power model (Figures A) show that images containing higher Fourier power have a tendency to elicit responses above the imply. This can be consistent with several studies showing that V responses enhance with rising image contrast (Albrecht and Hamilton, ; Gardner et al). The weights for the subjective distance model show that very distant scenes elicit responses beneath the imply in most V voxels. This can be likely since one of the most distant scenes (including the image in the ocean in Figure A) have low overall Fourier energy. The weights for the object category model show that the pictures with labels for fruit and vegetable, ready meals, and creepy animal all elicit responses above the imply. They are also probably be related to distinct levels of Fourier power. We analyze the correlations involving Fourier energy and specific object categories, too as other correlations between function channels in different models, in detail beneath. In FFA, the weights for the Fourier energy model (Figures D) show that images with high frequency energy at tended to elicit BOLD responses above the imply, even though higher frequency power at vertical and horizontal (and) orientations elicit responses under the mean. A number of prior research have rigorously argued that FFA responds to faces as opposed to lowlevel image attributes (Kanwisher andFunctional Region LocalizersVisual places in retinotopic visual cortex too as functionally defined categoryselective visual places have been identified in separate scan sessions employing conventional procedures (Spiridon et al ; Hansen et al). Sceneselective places PPA, RSC, and OPA had been all defined by a contrast of areas vs. objects. The Fusiform Face Location (FFA) was defined by a contrast of faces vs. objects. The boundaries of each and every location were hand drawn around the cortical surface in the places at which the t statistic for the contrast of places vs. objects changed most swiftly.RESULTSTo investigate how natural scenes are represented in sceneselective locations within the human brain, we analyzed BOLD fMRI signals evoked by a large set of all-natural pictures (These data have been collected for two research from our laboratory that had been published previouslyNaselaris et al and Stansbury et al). We tested 3 precise hypotheses about scene representation inFrontiers in Computational Neuroscience Lescroart et al.Competing models of sceneselective areasFIGURE Voxelwise model weights for all models for all voxels in V and FFA. (A) Model weights for the Fourier energy model for V. The image in the reduced part of the panel shows the weight for each voxel in V that met our selection criterion p see Strategies. Voxels are separated by subject (s), along with the relative size of each subject’s section indicates the relative number of voxels selected in PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/16369121 V for that topic. marks indicate certain ROIs in specific subjects with low signal top quality (and hence few voxels selected for analysis). See Figure S for evaluation of signal across subjects. Each horizontal stripe by way of the image shows the weights for any distinctive voxel. Voxels are sorted inside each topic by 
normalized predic.