Sight and Sound Converge to Form Modality-Invariant Representations in Temporoparietal Cortex

People can identify objects in the environment with remarkable accuracy, regardless of the sensory modality they use to perceive them. This suggests that information from different sensory channels converges somewhere in the brain to form modality-invariant representations, i.e., representations that reflect an object independently of the modality through which it has been apprehended. In this functional magnetic resonance imaging study of human subjects, we first identified brain areas that responded to both visual and auditory stimuli and then used crossmodal multivariate pattern analysis to evaluate the neural representations in these regions for content specificity (i.e., do different objects evoke different representations?) and modality invariance (i.e., do the sight and the sound of the same object evoke a similar representation?). While several areas became activated in response to both auditory and visual stimulation, only the neural patterns recorded in a region around the posterior part of the superior temporal sulcus displayed both content specificity and modality invariance. This region thus appears to play an important role in our ability to recognize objects in our surroundings through multiple sensory channels and to process them at a supramodal (i.e., conceptual) level.

[1]  Fraser W. Smith,et al.  Decoding natural sounds in early visual cortex , 2011 .

[2]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[3]  A. Amedi,et al.  Functional imaging of human crossmodal identification and object recognition , 2005, Experimental Brain Research.

[4]  M. Peelen,et al.  Supramodal Representations of Perceived Emotions in the Human Brain , 2010, The Journal of Neuroscience.

[5]  Michael S. Beauchamp,et al.  Statistical criteria in fMRI studies of multisensory integration , 2005, Neuroinformatics.

[6]  Emiliano Ricciardi,et al.  Beyond sensory images: Object-based representation in the human ventral pathway. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[8]  Hanna Damasio,et al.  Seeing touch is correlated with content-specific activity in primary somatosensory cortex. , 2011, Cerebral cortex.

[9]  Tom M. Mitchell,et al.  From the SelectedWorks of Marcel Adam Just 2011 Commonality of neural representations of words and pictures , 2016 .

[10]  D H Brainard,et al.  The Psychophysics Toolbox. , 1997, Spatial vision.

[11]  Chris I. Baker,et al.  Disentangling visual imagery and perception of real-world objects , 2012, NeuroImage.

[12]  Paul J. Laurienti,et al.  On the use of superadditivity as a metric for characterizing multisensory integration in functional neuroimaging studies , 2005, Experimental Brain Research.

[13]  Christoph Kayser,et al.  Spatial Organization of Multisensory Responses in Temporal Association Cortex , 2009, The Journal of Neuroscience.

[14]  A. Damasio,et al.  Convergence and divergence in a neural architecture for recognition and memory , 2009, Trends in Neurosciences.

[15]  Rainer Goebel,et al.  Information-based functional brain mapping. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Hanna Damasio,et al.  Predicting visual stimuli on the basis of activity in auditory cortices , 2010, Nature Neuroscience.

[17]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[18]  D. Pandya,et al.  Parietal, temporal, and occipita projections to cortex of the superior temporal sulcus in the rhesus monkey: A retrograde tracer study , 1994, The Journal of comparative neurology.

[19]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[20]  Thomas Serre,et al.  Reading the mind's eye: Decoding category information during mental imagery , 2010, NeuroImage.

[21]  L. Benevento,et al.  Auditory-visual interaction in single cells in the cortex of the superior temporal sulcus and the orbital frontal cortex of the macaque monkey , 1977, Experimental Neurology.

[22]  D. Pandya,et al.  Post‐rolandic cortical projections of the superior temporal sulcus in the rhesus monkey , 1991, The Journal of comparative neurology.

[23]  B. Argall,et al.  Unraveling multisensory integration: patchy organization within human STS multisensory cortex , 2004, Nature Neuroscience.

[24]  J. Driver,et al.  Multisensory Interplay Reveals Crossmodal Influences on ‘Sensory-Specific’ Brain Regions, Neural Responses, and Judgments , 2008, Neuron.

[25]  Robert J. Zatorre,et al.  Mental Concerts: Musical Imagery and Auditory Cortex , 2005, Neuron.

[26]  Keiji Tanaka,et al.  Polysensory properties of neurons in the anterior bank of the caudal superior temporal sulcus of the macaque monkey. , 1988, Journal of neurophysiology.

[27]  A. Damasio Time-locked multiregional retroactivation: A systems-level proposal for the neural substrates of recall and recognition , 1989, Cognition.

[28]  Hans-Jochen Heinze,et al.  Scanning silence: Mental imagery of complex sounds , 2005, NeuroImage.

[29]  J. Duncan,et al.  Top-Down Activation of Shape-Specific Population Codes in Visual Cortex during Mental Imagery , 2009, The Journal of Neuroscience.

[30]  Stefan Pollmann,et al.  PyMVPA: a Python Toolbox for Multivariate Pattern Analysis of fMRI Data , 2009, Neuroinformatics.

[31]  M. Naumer,et al.  Semantics and the multisensory brain: How meaning modulates processes of audio-visual integration , 2008, Brain Research.

[32]  D. J. Felleman,et al.  Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.

[33]  R. Desimone,et al.  Visual properties of neurons in a polysensory area in superior temporal sulcus of the macaque. , 1981, Journal of neurophysiology.

[34]  G. Calvert Crossmodal processing in the human brain: insights from functional neuroimaging studies. , 2001, Cerebral cortex.

[35]  D. Pandya,et al.  Afferent cortical connections and architectonics of the superior temporal sulcus and surrounding cortex in the rhesus monkey , 1978, Brain Research.

[36]  Stephen M. Smith,et al.  Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data , 2001, NeuroImage.

[37]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[38]  Francisco Pereira,et al.  Information mapping with pattern classifiers: A comparative study , 2011, NeuroImage.

[39]  D. Pandya,et al.  Efferent cortical connections of multimodal cortex of the superior temporal sulcus in the rhesus monkey , 1992, The Journal of comparative neurology.