Extra-classical receptive field effects measured in striate cortex with fMRI

The aim of this study was to measure the contextual influence of globally coherent motion on visual cortical responses using functional magnetic resonance imaging. Our motivation was to test a prediction from representational theories of perception (i.e. predictive coding) that primary visual responses should be suppressed by top-down influences during coherent motion. We used a sparse stimulus array such that each element could not fall within the same classical receptive field of primary visual cortex neurons (i.e. precluding lateral interactions within V1). This enabled us to attribute differences, in striate cortex responses, to extra-classical receptive field effects mediated by backward connections. In accord with theoretical predictions we were able to demonstrate suppression of striate cortex activations to coherent relative to incoherent motion. These results suggest that suppression of primary visual cortex responses to coherent motion reflect extra-classical effects mediated by backward connections.

[1]  O B Paulson,et al.  The activation pattern in normal humans during suppression, imagination and performance of saccadic eye movements. , 1997, Acta physiologica Scandinavica.

[2]  R. Shapley,et al.  Contrast's effect on spatial summation by macaque V1 neurons , 1999, Nature Neuroscience.

[3]  David J. Heeger,et al.  Pattern-motion responses in human visual cortex , 2002, Nature Neuroscience.

[4]  Joseph E LeDoux,et al.  The brain and cognitive sciences , 1978, Annals of neurology.

[5]  Katrin Amunts,et al.  Linking retinotopic fMRI mapping and anatomical probability maps of human occipital areas V1 and V2 , 2005, NeuroImage.

[6]  C. Blakemore,et al.  Characteristics of surround inhibition in cat area 17 , 1997, Experimental Brain Research.

[7]  B. Fischer,et al.  Visual field representations and locations of visual areas V1/2/3 in human visual cortex. , 2003, Journal of vision.

[8]  A. Leventhal,et al.  Signal timing across the macaque visual system. , 1998, Journal of neurophysiology.

[9]  Simon B. Eickhoff,et al.  A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data , 2005, NeuroImage.

[10]  D. Pandya,et al.  Intrinsic connections and architectonics of the superior temporal sulcus in the rhesus monkey , 1989, The Journal of comparative neurology.

[11]  J. Bullier,et al.  Reaching beyond the classical receptive field of V1 neurons: horizontal or feedback axons? , 2003, Journal of Physiology-Paris.

[12]  Karl J. Friston,et al.  Human Brain Function , 1997 .

[13]  J. Nelson,et al.  Orientation-selective inhibition from beyond the classic visual receptive field , 1978, Brain Research.

[14]  Alessandra Angelucci,et al.  Contribution of feedforward thalamic afferents and corticogeniculate feedback to the spatial summation area of macaque V1 and LGN , 2006, The Journal of comparative neurology.

[15]  A. Borst Seeing smells: imaging olfactory learning in bees , 1999, Nature Neuroscience.

[16]  D. Hubel,et al.  Uniformity of monkey striate cortex: A parallel relationship between field size, scatter, and magnification factor , 1974, The Journal of comparative neurology.

[17]  D. V. van Essen,et al.  The pattern of interhemispheric connections and its relationship to extrastriate visual areas in the macaque monkey , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[18]  G. Orban,et al.  Shape and Spatial Distribution of Receptive Fields and Antagonistic Motion Surrounds in the Middle Temporal Area (V5) of the Macaque , 1995, The European journal of neuroscience.

[19]  Karl J. Friston Learning and inference in the brain , 2003, Neural Networks.

[20]  G. Orban,et al.  Size and shape of receptive fields in the medial superior temporal area (MST) of the macaque , 1997, Neuroreport.

[21]  Tai Sing Lee,et al.  Hierarchical Bayesian inference in the visual cortex. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.

[22]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

[23]  Paul Sajda,et al.  Integration of form and motion within a generative model of visual cortex , 2004, Neural Networks.

[24]  C. Blakemore,et al.  Lateral inhibition between orientation detectors in the cat's visual cortex , 2004, Experimental Brain Research.

[25]  Peter Dayan,et al.  Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems , 2001 .

[26]  W. Newsome,et al.  Motion selectivity in macaque visual cortex. II. Spatiotemporal range of directional interactions in MT and V1. , 1986, Journal of neurophysiology.

[27]  R. S. J. Frackowiak,et al.  Activity in human areas V1/V2, V3 and V5 during the perception of coherent and incoherent motion , 1996, NeuroImage.

[28]  R. Wurtz,et al.  Responses of MT and MST neurons to one and two moving objects in the receptive field. , 1997, Journal of neurophysiology.

[29]  M. Mesulam,et al.  From sensation to cognition. , 1998, Brain : a journal of neurology.

[30]  G. V. Van Hoesen,et al.  Neural connections of the posteromedial cortex in the macaque , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[31]  J. B. Levitt,et al.  Circuits for Local and Global Signal Integration in Primary Visual Cortex , 2002, The Journal of Neuroscience.

[32]  Lawrence C. Sincich,et al.  Bypassing V1: a direct geniculate input to area MT , 2004, Nature Neuroscience.

[33]  Yair Weiss Bayesian motion estimation and segmentation , 1998 .

[34]  E. Adelson,et al.  Phenomenal coherence of moving visual patterns , 1982, Nature.

[35]  S. Zeki A vision of the brain , 1993 .

[36]  S. Zeki,et al.  The consequences of inactivating areas V1 and V5 on visual motion perception. , 1995, Brain : a journal of neurology.

[37]  Rainer Goebel,et al.  Activity patterns in human motion sensitive areas depend on the interpretation of global motion , 2001, NeuroImage.

[38]  A. T. Smith,et al.  Estimating receptive field size from fMRI data in human striate and extrastriate visual cortex. , 2001, Cerebral cortex.

[39]  Michael I. Jordan Learning in Graphical Models , 1999, NATO ASI Series.

[40]  F. Aboitiz,et al.  Brain connections: interhemispheric fiber systems and anatomical brain asymmetries in humans. , 1992, Biological research.

[41]  Karl J. Friston,et al.  A direct quantitative relationship between the functional properties of human and macaque V5 , 2000, Nature Neuroscience.

[42]  G. Orban,et al.  Response latencies of visual cells in macaque areas V1, V2 and V5 , 1989, Brain Research.

[43]  O. Braddick,et al.  Brain Areas Sensitive to Coherent Visual Motion , 2001, Perception.

[44]  J. Bullier,et al.  The role of feedback connections in shaping the responses of visual cortical neurons. , 2001, Progress in brain research.

[45]  J. Ashburner,et al.  Multimodal Image Coregistration and Partitioning—A Unified Framework , 1997, NeuroImage.

[46]  K. Amunts,et al.  Human V5/MT+: comparison of functional and cytoarchitectonic data , 2005, Anatomy and Embryology.

[47]  T. Poggio,et al.  Predicting the visual world: silence is golden , 1999, Nature Neuroscience.

[48]  Karl J. Friston,et al.  A heuristic for the degrees of freedom of statistics based on multiple variance parameters , 2003, NeuroImage.

[49]  Karl J. Friston,et al.  A theory of cortical responses , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[50]  Tai Sing Lee,et al.  Contextual Influences in Visual Processing , 2008 .

[51]  Rainer Goebel,et al.  Activity patterns in human motion-sensitive areas depend on the interpretation of global motion , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[52]  J. Bullier,et al.  Feedforward and feedback connections between areas V1 and V2 of the monkey have similar rapid conduction velocities. , 2001, Journal of neurophysiology.

[53]  A. Cowey,et al.  Blindsight in man and monkey. , 1997, Brain : a journal of neurology.

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

[55]  J. B. Levitt,et al.  The spatial extent over which neurons in macaque striate cortex pool visual signals , 2002, Visual Neuroscience.

[56]  Paul Schrater,et al.  Shape perception reduces activity in human primary visual cortex , 2002, Proceedings of the National Academy of Sciences of the United States of America.