Inverse mapping the neuronal substrates of face categorizations.

Face perception is a complex process involving a network of brain structures, dynamically processing information to enable judgments about a face to be made (e.g., familiarity, identity, and expression). Here we introduce an analysis methodology that makes it possible to directly study this information processing in the brain from spatially and temporally resolved magnetoencephalographic signals. We apply our methodology to the study of 2 face categorization tasks, gender and expressiveness, and track the processing of 3 key visual features that underlie behavioral performance, over time and throughout the cortex. We find information processing correlates beginning from 90 ms following stimulus onset, where features are processed in isolation in occipital extrastriate regions. Over time, processing of successively more features and feature combinations takes place in occipitotemporal regions, with maximal information processing of visual information coinciding with the well-established face-selective M170 component at 170 ms. Later still, around 250-400 ms, cortical activity responds significantly more to task-specific features and their complex combinations. These results indicate a complex process of visual information processing during face perception with face parts processed in isolation at very early stages, and task-specific processing of combinations of features taking place within 300 ms. Crucially, our approach specifically establishes which information in the visual stimulus the brain signal is responding to and how this varies with time, cortical location, and task demands to establish a more precise tracking of information processing mechanisms in the cortex during face perception.

[1]  Philippe G Schyns,et al.  Perceptual moments of conscious visual experience inferred from oscillatory brain activity. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Lucy S. Petro,et al.  Dynamics of Visual Information Integration in the Brain for Categorizing Facial Expressions , 2007, Current Biology.

[3]  Miguel P Eckstein,et al.  Classification images: a tool to analyze visual strategies. , 2002, Journal of vision.

[4]  N. Kanwisher,et al.  The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception , 1997, The Journal of Neuroscience.

[5]  R. Hari,et al.  Face recognition and cortical responses show similar sensitivity to noise spatial frequency. , 2005, Cerebral cortex.

[6]  R. Henson,et al.  Electrophysiological and haemodynamic correlates of face perception, recognition and priming. , 2003, Cerebral cortex.

[7]  M. Tarr,et al.  The Fusiform Face Area is Part of a Network that Processes Faces at the Individual Level , 2000, Journal of Cognitive Neuroscience.

[8]  Karl J. Friston,et al.  Population-level inferences for distributed MEG source localization under multiple constraints: Application to face-evoked fields , 2007, NeuroImage.

[9]  Richard M. Leahy,et al.  Electromagnetic brain mapping , 2001, IEEE Signal Process. Mag..

[10]  T. Allison,et al.  Electrophysiological studies of human face perception. I: Potentials generated in occipitotemporal cortex by face and non-face stimuli. , 1999, Cerebral cortex.

[11]  J. Haxby,et al.  The distributed human neural system for face perception , 2000, Trends in Cognitive Sciences.

[12]  P. Schyns,et al.  Receptive Fields for Flexible Face Categorizations , 2004, Psychological science.

[13]  Frédéric Gosselin,et al.  A Principled Method for Determining the Functionality of ERP Components. , 2003 .

[14]  N. Kanwisher,et al.  Stages of processing in face perception: an MEG study , 2002, Nature Neuroscience.

[15]  J. Vrba,et al.  Linearly constrained minimum variance beamformers, synthetic aperture magnetometry, and MUSIC in MEG applications , 2000, Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154).

[16]  Pia Rotshtein,et al.  Distinct and Convergent Visual Processing of High and Low Spatial Frequency Information in Faces , 2007 .

[17]  Marie L. Smith,et al.  From a face to its category via a few information processing states in the brain , 2007, NeuroImage.

[18]  Gabriel Curio,et al.  MEG/EEG sources of the 170-ms response to faces are co-localized in the fusiform gyrus , 2007, NeuroImage.

[19]  P. Schyns,et al.  A principled method for determining the functionality of brain responses , 2003, Neuroreport.

[20]  P. Fries A mechanism for cognitive dynamics: neuronal communication through neuronal coherence , 2005, Trends in Cognitive Sciences.

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

[22]  Frédéric Gosselin,et al.  Bubbles: a technique to reveal the use of information in recognition tasks , 2001, Vision Research.

[23]  E. Halgren,et al.  Cognitive response profile of the human fusiform face area as determined by MEG. , 2000, Cerebral cortex.

[24]  J. Martinerie,et al.  The brainweb: Phase synchronization and large-scale integration , 2001, Nature Reviews Neuroscience.

[25]  Garrison W. Cottrell,et al.  Transmitting and decoding facial expressions of emotion , 2004 .

[26]  P. Schyns,et al.  Show Me the Features! Understanding Recognition From the Use of Visual Information , 2002, Psychological science.

[27]  T. Allison,et al.  Electrophysiological Studies of Face Perception in Humans , 1996, Journal of Cognitive Neuroscience.

[28]  Topi Tanskanen,et al.  Face recognition and cortical responses: Effect of stimulus duration , 2007, NeuroImage.

[29]  T. Allison,et al.  Electrophysiological studies of human face perception. II: Response properties of face-specific potentials generated in occipitotemporal cortex. , 1999, Cerebral cortex.

[30]  Sean M. Polyn,et al.  Beyond mind-reading: multi-voxel pattern analysis of fMRI data , 2006, Trends in Cognitive Sciences.

[31]  Garrison W. Cottrell,et al.  Transmitting and Decoding Facial Expressions , 2005, Psychological science.

[32]  Margot J. Taylor,et al.  Inversion and contrast-reversal effects on face processing assessed by MEG , 2006, Brain Research.

[33]  Conny F. Schmidt,et al.  Face perception is mediated by a distributed cortical network , 2005, Brain Research Bulletin.

[34]  WITHDRAWN: Face perception is mediated by a distributed cortical network , 2005 .

[35]  T. Yoshimoto,et al.  Recent Advances in Biomagnetism , 2007 .

[36]  J. Fermaglich Electric Fields of the Brain: The Neurophysics of EEG , 1982 .

[37]  N. Kanwisher,et al.  The selectivity of the occipitotemporal M170 for faces , 2000, Neuroreport.

[38]  Philippe G Schyns,et al.  Accurate statistical tests for smooth classification images. , 2005, Journal of vision.

[39]  M. Seghier,et al.  A network of occipito-temporal face-sensitive areas besides the right middle fusiform gyrus is necessary for normal face processing. , 2003, Brain : a journal of neurology.

[40]  Frédéric Gosselin,et al.  Information processing algorithms in the brain , 2009, Trends in Cognitive Sciences.

[41]  R. Oostenveld,et al.  Nonparametric statistical testing of EEG- and MEG-data , 2007, Journal of Neuroscience Methods.

[42]  Hisao Nishijo,et al.  Generators of Visual Evoked Potentials for Faces and Eyes in the Human Brain as Determined by Dipole Localization , 2004, Brain Topography.

[43]  Bruno Rossion,et al.  Early lateralization and orientation tuning for face, word, and object processing in the visual cortex , 2003, NeuroImage.

[44]  C. Granger Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[45]  W. Drongelen,et al.  Localization of brain electrical activity via linearly constrained minimum variance spatial filtering , 1997, IEEE Transactions on Biomedical Engineering.

[46]  M. Giese,et al.  Flexible Coding for Categorical Decisions in the Human Brain , 2007, The Journal of Neuroscience.