Spatial frequency processing in scene-selective cortical regions

Visual analysis begins with the parallel extraction of different attributes at different spatial frequencies. Low spatial frequencies (LSF) convey coarse information and are characterized by high luminance contrast, while high spatial frequencies (HSF) convey fine details and are characterized by low luminance contrast. In the present fMRI study, we examined how scene-selective regions-the parahippocampal place area (PPA), the retrosplenial cortex (RSC) and the occipital place area (OPA)-responded to spatial frequencies when contrast was either equalized or not equalized across spatial frequencies. Participants performed a categorization task on LSF, HSF and non-filtered scenes belonging to two different categories (indoors and outdoors). We either left contrast across scenes untouched, or equalized it using a root-mean-square contrast normalization. We found that when contrast remained unmodified, LSF and NF scenes elicited greater activation than HSF scenes in the PPA. However, when contrast was equalized across spatial frequencies, the PPA was selective to HFS. This suggests that PPA activity relies on an interaction between spatial frequency and contrast in scenes. In the RSC, LSF and NF elicited greater response than HSF scenes when contrast was not modified, while no effect of spatial frequencies appeared when contrast was equalized across filtered scenes, suggesting that the RSC is sensitive to high-contrast information. Finally, we observed selective activation of the OPA in response to HSF, irrespective of contrast manipulation. These results provide new insights into how scene-selective areas operate during scene processing.

[1]  Louise Kauffmann,et al.  The neural bases of spatial frequency processing during scene perception , 2014, Front. Integr. Neurosci..

[2]  Monica Baciu,et al.  Cerebral regions and hemispheric specialization for processing spatial frequencies during natural scene recognition. An event-related fMRI study , 2004, NeuroImage.

[3]  Roger B. H. Tootell,et al.  A Cardinal Orientation Bias in Scene-Selective Visual Cortex , 2012, The Journal of Neuroscience.

[4]  Tom Hartley,et al.  Patterns of response to visual scenes are linked to the low-level properties of the image , 2014, NeuroImage.

[5]  Chantal Kemner,et al.  Is the early modulation of brain activity by fearful facial expressions primarily mediated by coarse low spatial frequency information? , 2009, Journal of vision.

[6]  A. Mizuno,et al.  A change of the leading player in flow Visualization technique , 2006, J. Vis..

[7]  Soojin Park,et al.  Disentangling Scene Content from Spatial Boundary: Complementary Roles for the Parahippocampal Place Area and Lateral Occipital Complex in Representing Real-World Scenes , 2011, The Journal of Neuroscience.

[8]  M. Bar,et al.  Cortical Analysis of Visual Context , 2003, Neuron.

[9]  Russell A. Epstein,et al.  The Parahippocampal Place Area Recognition, Navigation, or Encoding? , 1999, Neuron.

[10]  D. Bub,et al.  Does face inversion change spatial frequency tuning? , 2010, Journal of experimental psychology. Human perception and performance.

[11]  Bart Farell,et al.  Coarse scales, fine scales, and their interactions in stereo vision. , 2004, Journal of vision.

[12]  D. G. Albrecht,et al.  Spatial frequency selectivity of cells in macaque visual cortex , 1982, Vision Research.

[13]  C. Malsburg,et al.  The role of complex cells in object recognition , 2002, Vision Research.

[14]  T. Hendler,et al.  A hierarchical axis of object processing stages in the human visual cortex. , 2001, Cerebral cortex.

[15]  Moshe Bar,et al.  Famous faces activate contextual associations in the parahippocampal cortex. , 2008, Cerebral cortex.

[16]  A. Ishai,et al.  Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex , 2001, Science.

[17]  Nathalie Guyader,et al.  Coarse-to-fine Categorization of Visual Scenes in Scene-selective Cortex , 2014, Journal of Cognitive Neuroscience.

[19]  Paul E. Downing,et al.  Viewpoint-Specific Scene Representations in Human Parahippocampal Cortex , 2003, Neuron.

[20]  Poggio Gf Spatial properties of neurons in striate cortex of unanesthetized macaque monkey. , 1972 .

[21]  J R Lishman,et al.  Temporal Integration of Spatially Filtered Visual Images , 1992, Perception.

[22]  Antonio Torralba,et al.  Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.

[23]  Antonio Torralba,et al.  Statistics of natural image categories , 2003, Network.

[24]  Michel Dojat,et al.  Retinotopic and Lateralized Processing of Spatial Frequencies in Human Visual Cortex during Scene Categorization , 2013, Journal of Cognitive Neuroscience.

[25]  Soojin Park,et al.  Different roles of the parahippocampal place area (PPA) and retrosplenial cortex (RSC) in panoramic scene perception , 2009, NeuroImage.

[26]  Russell A. Epstein The cortical basis of visual scene processing , 2005 .

[27]  Paul Schrater,et al.  BOLD fMRI and psychophysical measurements of contrast response to broadband images , 2004, Vision Research.

[28]  Li Fei-Fei,et al.  Differential Connectivity Within the Parahippocampal Place Area , 2013 .

[29]  Nancy Kanwisher,et al.  A cortical representation of the local visual environment , 1998, Nature.

[30]  Meredith Wadman Privacy bill under fire from researchers , 1998, Nature.

[31]  Nathalie Guyader,et al.  Rapid scene categorization: Role of spatial frequency order, accumulation mode and luminance contrast , 2015, Vision Research.

[32]  Christoph M. Michel,et al.  The Neural Substrates and Timing of Top–Down Processes during Coarse-to-Fine Categorization of Visual Scenes: A Combined fMRI and ERP Study , 2010, Journal of Cognitive Neuroscience.

[33]  Russell A. Epstein,et al.  Abstract Representations of Location and Facing Direction in the Human Brain , 2013, The Journal of Neuroscience.

[34]  A. Oliva,et al.  From Blobs to Boundary Edges: Evidence for Time- and Spatial-Scale-Dependent Scene Recognition , 1994 .

[35]  J. Hegdé Time course of visual perception: Coarse-to-fine processing and beyond , 2008, Progress in Neurobiology.

[36]  J. Rieger,et al.  BOLD responses in human V1 to local structure in natural scenes: Implications for theories of visual coding. , 2013, Journal of vision.

[37]  D. Tolhurst,et al.  Amplitude spectra of natural images , 1992 .

[38]  C. Enroth-Cugell,et al.  Chapter 9 Visual adaptation and retinal gain controls , 1984 .

[39]  R. L. Valois,et al.  The orientation and direction selectivity of cells in macaque visual cortex , 1982, Vision Research.

[40]  Nathalie Guyader,et al.  The coarse-to-fine hypothesis revisited: Evidence from neuro-computational modeling , 2005, Brain and Cognition.

[41]  M. Bar,et al.  Scenes Unseen: The Parahippocampal Cortex Intrinsically Subserves Contextual Associations, Not Scenes or Places Per Se , 2008, The Journal of Neuroscience.

[42]  Russell A. Epstein,et al.  Differential parahippocampal and retrosplenial involvement in three types of visual scene recognition. , 2006, Cerebral cortex.

[43]  Fei-Fei Li,et al.  Differential connectivity within the Parahippocampal Place Area , 2013, NeuroImage.

[44]  Tom Hartley,et al.  Selectivity for low-level features of objects in the human ventral stream , 2010, NeuroImage.

[45]  Katsumi Aoki,et al.  Recent development of flow visualization , 2004, J. Vis..

[46]  Geoffrey M Boynton Contrast Gain in the Brain , 2005, Neuron.

[47]  J. Bullier Integrated model of visual processing , 2001, Brain Research Reviews.

[48]  Rainer Goebel,et al.  From Coarse to Fine? Spatial and Temporal Dynamics of Cortical Face Processing , 2010, Cerebral cortex.

[49]  Arthur P. Ginsburg,et al.  Spatial filtering and visual form perception. , 1986 .

[50]  Y. Gutfreund,et al.  Saliency mapping in the optic tectum and its relationship to habituation , 2014, Front. Integr. Neurosci..

[51]  M. Bar,et al.  The parahippocampal cortex mediates spatial and nonspatial associations. , 2007, Cerebral cortex.

[52]  H. Hughes,et al.  Global Precedence, Spatial Frequency Channels, and the Statistics of Natural Images , 1996, Journal of Cognitive Neuroscience.

[53]  M. Bar A Cortical Mechanism for Triggering Top-Down Facilitation in Visual Object Recognition , 2003, Journal of Cognitive Neuroscience.

[54]  P. Bex,et al.  Spatial frequency, phase, and the contrast of natural images. , 2002, Journal of the Optical Society of America. A, Optics, image science, and vision.

[55]  Emily J. Ward,et al.  How reliable are visual context effects in the parahippocampal place area? , 2010, Cerebral cortex.

[56]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[57]  Leslie G. Ungerleider,et al.  Scene-Selective Cortical Regions in Human and Nonhuman Primates , 2011, The Journal of Neuroscience.

[58]  D. Heeger,et al.  Linear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1 , 1996, The Journal of Neuroscience.

[59]  Masayuki Kamba,et al.  Building-specific categorical processing in the retrosplenial cortex , 2008, Brain Research.

[60]  Dirk B. Walther,et al.  Natural Scene Categories Revealed in Distributed Patterns of Activity in the Human Brain , 2009, The Journal of Neuroscience.

[61]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .

[62]  Andrea De Cesarei,et al.  Global and local vision in natural scene identification , 2011, Psychonomic bulletin & review.

[63]  Daniel D. Dilks,et al.  The Occipital Place Area Is Causally and Selectively Involved in Scene Perception , 2013, The Journal of Neuroscience.

[64]  Erin M. Harley,et al.  Why is it easier to identify someone close than far away? , 2005, Psychonomic bulletin & review.

[65]  A. Oliva,et al.  Coarse Blobs or Fine Edges? Evidence That Information Diagnosticity Changes the Perception of Complex Visual Stimuli , 1997, Cognitive Psychology.

[66]  S. Solomon,et al.  Contrast sensitivity in natural scenes depends on edge as well as spatial frequency structure. , 2009, Journal of vision.

[67]  M. Torrens Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268 , 1990 .

[68]  Yuanzhen Li,et al.  Measuring visual clutter. , 2007, Journal of vision.

[69]  Natalia Y. Bilenko,et al.  The “Parahippocampal Place Area” Responds Preferentially to High Spatial Frequencies in Humans and Monkeys , 2011, PLoS biology.

[70]  Nathalie Guyader,et al.  Image phase or amplitude? Rapid scene categorization is an amplitude-based process. , 2004, Comptes rendus biologies.

[71]  Ravi S. Menon,et al.  Effect of luminance contrast on BOLD fMRI response in human primary visual areas. , 1998, Journal of neurophysiology.

[72]  Eleanor A. Maguire,et al.  Retrosplenial Cortex Codes for Permanent Landmarks , 2012, PloS one.

[73]  M. Bar Visual objects in context , 2004, Nature Reviews Neuroscience.

[74]  Sheng Li,et al.  The neural signature of spatial frequency-based information integration in scene perception , 2013, Experimental Brain Research.

[75]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[76]  M. Bar The proactive brain: using analogies and associations to generate predictions , 2007, Trends in Cognitive Sciences.

[77]  Russell A. Epstein Parahippocampal and retrosplenial contributions to human spatial navigation , 2008, Trends in Cognitive Sciences.

[78]  Antonio Schettino,et al.  Brain dynamics of upstream perceptual processes leading to visual object recognition: A high density ERP topographic mapping study , 2011, NeuroImage.

[79]  Russell A. Epstein,et al.  Visual scene processing in familiar and unfamiliar environments. , 2007, Journal of neurophysiology.