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Published in: Journal of Computational Neuroscience 1/2011

01-02-2011

Local non-linear interactions in the visual cortex may reflect global decorrelation

Authors: Simo Vanni, Tom Rosenström

Published in: Journal of Computational Neuroscience | Issue 1/2011

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Abstract

The classical receptive field in the primary visual cortex have been successfully explained by sparse activation of relatively independent units, whose tuning properties reflect the statistical dependencies in the natural environment. Robust surround modulation, emerging from stimulation beyond the classical receptive field, has been associated with increase of lifetime sparseness in the V1, but the system-wide modulation of response strength have currently no theoretical explanation. We measured fMRI responses from human visual cortex and quantified the contextual modulation with a decorrelation coefficient (d), derived from a subtractive normalization model. All active cortical areas demonstrated local non-linear summation of responses, which were in line with hypothesis of global decorrelation of voxels responses. In addition, we found sensitivity to surrounding stimulus structure across the ventral stream, and large-scale sensitivity to the number of simultaneous objects. Response sparseness across voxel population increased consistently with larger stimuli. These data suggest that contextual modulation for a stimulus event reflect optimization of the code and perhaps increase in energy efficiency throughout the ventral stream hierarchy. Our model provides a novel prediction that average suppression of response amplitude for simultaneous stimuli across the cortical network is a monotonic function of similarity of response strengths in the network when the stimuli are presented alone.

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Appendix
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Literature
go back to reference Angelucci, A., & Bressloff, P. C. (2006). Contribution of feedforward, lateral and feedback connections to the classical receptive field center and extra-classical receptive field surround of primate V1 neurons. Progress in Brain Research, 154, 93–120.CrossRefPubMed Angelucci, A., & Bressloff, P. C. (2006). Contribution of feedforward, lateral and feedback connections to the classical receptive field center and extra-classical receptive field surround of primate V1 neurons. Progress in Brain Research, 154, 93–120.CrossRefPubMed
go back to reference Angelucci, A., Levitt, J. B., Walton, E. J., Hupé, J. M., Bullier, J., & Lund, J. S. (2002). Circuits for local and global signal integration in primary visual cortex. The Journal of Neuroscience, 22, 8633–8646.PubMed Angelucci, A., Levitt, J. B., Walton, E. J., Hupé, J. M., Bullier, J., & Lund, J. S. (2002). Circuits for local and global signal integration in primary visual cortex. The Journal of Neuroscience, 22, 8633–8646.PubMed
go back to reference Atick, J. J., & Redlich, A. N. (1990). Towards a theory of early visual processing. Neural Computation, 2, 308–320.CrossRef Atick, J. J., & Redlich, A. N. (1990). Towards a theory of early visual processing. Neural Computation, 2, 308–320.CrossRef
go back to reference Attwell, D., & Laughlin, S. B. (2001). An energy budget for signaling in the grey matter of the brain. Journal of Cerebral Blood Flow and Metabolism, 21, 1133–1145.PubMed Attwell, D., & Laughlin, S. B. (2001). An energy budget for signaling in the grey matter of the brain. Journal of Cerebral Blood Flow and Metabolism, 21, 1133–1145.PubMed
go back to reference Averbeck, B. B., Latham, P. E., & Pouget, A. (2006). Neural correlations, population coding and computation. Nature Reviews. Neuroscience, 7, 358–366.CrossRefPubMed Averbeck, B. B., Latham, P. E., & Pouget, A. (2006). Neural correlations, population coding and computation. Nature Reviews. Neuroscience, 7, 358–366.CrossRefPubMed
go back to reference Baddeley, R., Abbott, L. F., Booth, M. C., Sengpiel, F., Freeman, T., Wakeman, E. A., et al. (1997). Responses of neurons in primary and inferior temporal visual cortices to natural scenes. Proc Biol Sci, 264, 1775–1783.CrossRefPubMed Baddeley, R., Abbott, L. F., Booth, M. C., Sengpiel, F., Freeman, T., Wakeman, E. A., et al. (1997). Responses of neurons in primary and inferior temporal visual cortices to natural scenes. Proc Biol Sci, 264, 1775–1783.CrossRefPubMed
go back to reference Barlow, H. (1961). Possible principles underlying the transformation of sensory messages. In W. Rosenblith (Ed.), Sensory communication (pp. 217–234). Cambridge: MIT Press. Barlow, H. (1961). Possible principles underlying the transformation of sensory messages. In W. Rosenblith (Ed.), Sensory communication (pp. 217–234). Cambridge: MIT Press.
go back to reference Barlow, H. B. (1989). Unsupervised learning. Neural Computation, 1, 295–311.CrossRef Barlow, H. B. (1989). Unsupervised learning. Neural Computation, 1, 295–311.CrossRef
go back to reference Barlow, H., & Földiák, P. (1989). Adaptation and decorrelation in the cortex. In R. Durbin, C. Miall, & G. Mitchison (Eds.), The computing neuron (pp. 54–72). Boston: Addison-Wesley Longman Publishing Co., Inc. Barlow, H., & Földiák, P. (1989). Adaptation and decorrelation in the cortex. In R. Durbin, C. Miall, & G. Mitchison (Eds.), The computing neuron (pp. 54–72). Boston: Addison-Wesley Longman Publishing Co., Inc.
go back to reference Bishop, P. O., Coombs, J. S., & Henry, G. H. (1971). Interaction effects of visual contours on the discharge frequency of simple striate neurones. Journal de Physiologie, 219, 659–687. Bishop, P. O., Coombs, J. S., & Henry, G. H. (1971). Interaction effects of visual contours on the discharge frequency of simple striate neurones. Journal de Physiologie, 219, 659–687.
go back to reference Cavanaugh, J. R., Bair, W., & Movshon, J. A. (2002). Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons. Journal of Neurophysiology, 88, 2530–2546.CrossRefPubMed Cavanaugh, J. R., Bair, W., & Movshon, J. A. (2002). Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons. Journal of Neurophysiology, 88, 2530–2546.CrossRefPubMed
go back to reference Chen, Y., Geisler, W. S., & Seidemann, E. (2006). Optimal decoding of correlated neural population responses in the primate visual cortex. Nature Neuroscience, 9, 1412–1420.CrossRefPubMed Chen, Y., Geisler, W. S., & Seidemann, E. (2006). Optimal decoding of correlated neural population responses in the primate visual cortex. Nature Neuroscience, 9, 1412–1420.CrossRefPubMed
go back to reference Chisum, H. J., Mooser, F., & Fitzpatrick, D. (2003). Emergent properties of layer 2/3 neurons reflect the collinear arrangement of horizontal connections in tree shrew visual cortex. The Journal of Neuroscience, 23, 2947–2960.PubMed Chisum, H. J., Mooser, F., & Fitzpatrick, D. (2003). Emergent properties of layer 2/3 neurons reflect the collinear arrangement of horizontal connections in tree shrew visual cortex. The Journal of Neuroscience, 23, 2947–2960.PubMed
go back to reference Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage, 9, 179–194.CrossRefPubMed Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage, 9, 179–194.CrossRefPubMed
go back to reference Dan, Y., Atick, J. J., & Reid, R. C. (1996). Efficient coding of natural scenes in the lateral geniculate nucleus: experimental test of a computational theory. The Journal of Neuroscience, 16, 3351–3362.PubMed Dan, Y., Atick, J. J., & Reid, R. C. (1996). Efficient coding of natural scenes in the lateral geniculate nucleus: experimental test of a computational theory. The Journal of Neuroscience, 16, 3351–3362.PubMed
go back to reference DeAngelis, G. C., Freeman, R. D., & Ohzawa, I. (1994). Length and width tuning of neurons in the cat’s primary visual cortex. Journal of Neurophysiology, 71, 347–374.PubMed DeAngelis, G. C., Freeman, R. D., & Ohzawa, I. (1994). Length and width tuning of neurons in the cat’s primary visual cortex. Journal of Neurophysiology, 71, 347–374.PubMed
go back to reference Ecker, A. S., Berens, P., Keliris, G. A., Bethge, M., Logothetis, N. K., & Tolias, A. S. (2010). Decorrelated neuronal firing in cortical microcircuits. Science, 327, 584–587.CrossRefPubMed Ecker, A. S., Berens, P., Keliris, G. A., Bethge, M., Logothetis, N. K., & Tolias, A. S. (2010). Decorrelated neuronal firing in cortical microcircuits. Science, 327, 584–587.CrossRefPubMed
go back to reference Ejima, Y., & Takahashi, S. (1985). Apparent contrast of a sinusoidal grating in the simultaneous presence of peripheral gratings. Vision Research, 25, 1223–1232.CrossRefPubMed Ejima, Y., & Takahashi, S. (1985). Apparent contrast of a sinusoidal grating in the simultaneous presence of peripheral gratings. Vision Research, 25, 1223–1232.CrossRefPubMed
go back to reference Fairhall, A. L., Lewen, G. D., Bialek, W., & de Ruyter Van Steveninck, R. R. (2001). Efficiency and ambiguity in an adaptive neural code. Nature, 412, 787–792.CrossRefPubMed Fairhall, A. L., Lewen, G. D., Bialek, W., & de Ruyter Van Steveninck, R. R. (2001). Efficiency and ambiguity in an adaptive neural code. Nature, 412, 787–792.CrossRefPubMed
go back to reference Felleman, D. J., & Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex, 1, 1–47.CrossRefPubMed Felleman, D. J., & Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex, 1, 1–47.CrossRefPubMed
go back to reference Franco, L., Rolls, E. T., Aggelopoulos, N. C., & Jerez, J. M. (2007). Neuronal selectivity, population sparseness, and ergodicity in the inferior temporal visual cortex. Biological Cybernetics, 96, 547–560.CrossRefPubMed Franco, L., Rolls, E. T., Aggelopoulos, N. C., & Jerez, J. M. (2007). Neuronal selectivity, population sparseness, and ergodicity in the inferior temporal visual cortex. Biological Cybernetics, 96, 547–560.CrossRefPubMed
go back to reference Földiák, P. (2003). Sparse coding in the primate cortex. In M. A. Arbib (Ed.), The handbook of brain theory and neural networks (pp. 1064–1067). Cambridge: The MIT Press. Földiák, P. (2003). Sparse coding in the primate cortex. In M. A. Arbib (Ed.), The handbook of brain theory and neural networks (pp. 1064–1067). Cambridge: The MIT Press.
go back to reference Gawne, T. J., & Richmond, B. J. (1993). How independent are the messages carried by adjacent inferior temporal cortical neurons? The Journal of Neuroscience, 13, 2758–2771.PubMed Gawne, T. J., & Richmond, B. J. (1993). How independent are the messages carried by adjacent inferior temporal cortical neurons? The Journal of Neuroscience, 13, 2758–2771.PubMed
go back to reference Geisler, W. S., Perry, J. S., Super, B. J., & Gallogly, D. P. (2001). Edge co-occurrence in natural images predicts contour grouping performance. Vision Research, 41, 711–724.CrossRefPubMed Geisler, W. S., Perry, J. S., Super, B. J., & Gallogly, D. P. (2001). Edge co-occurrence in natural images predicts contour grouping performance. Vision Research, 41, 711–724.CrossRefPubMed
go back to reference Goense, J. B., & Logothetis, N. K. (2008). Neurophysiology of the BOLD fMRI signal in awake monkeys. Current Biology, 18, 631–640.CrossRefPubMed Goense, J. B., & Logothetis, N. K. (2008). Neurophysiology of the BOLD fMRI signal in awake monkeys. Current Biology, 18, 631–640.CrossRefPubMed
go back to reference Grinvald, A., Lieke, E. E., Frostig, R. D., & Hildesheim, R. (1994). Cortical point-spread function and long-range lateral interactions revealed by real-time optical imaging of macaque monkey primary visual cortex. The Journal of Neuroscience, 14, 2545–2568.PubMed Grinvald, A., Lieke, E. E., Frostig, R. D., & Hildesheim, R. (1994). Cortical point-spread function and long-range lateral interactions revealed by real-time optical imaging of macaque monkey primary visual cortex. The Journal of Neuroscience, 14, 2545–2568.PubMed
go back to reference Guo, K., Robertson, R. G., Mahmoodi, S., & Young, M. P. (2005). Centre-surround interactions in response to natural scene stimulation in the primary visual cortex. The European Journal of Neuroscience, 21, 536–548.CrossRefPubMed Guo, K., Robertson, R. G., Mahmoodi, S., & Young, M. P. (2005). Centre-surround interactions in response to natural scene stimulation in the primary visual cortex. The European Journal of Neuroscience, 21, 536–548.CrossRefPubMed
go back to reference Harrison, L. M., Stephan, K. E., Rees, G., & Friston, K. J. (2007). Extra-classical receptive field effects measured in striate cortex with fMRI. Neuroimage, 34, 1199–1208.CrossRefPubMed Harrison, L. M., Stephan, K. E., Rees, G., & Friston, K. J. (2007). Extra-classical receptive field effects measured in striate cortex with fMRI. Neuroimage, 34, 1199–1208.CrossRefPubMed
go back to reference Haxby, J. V., Gobbini, M. I., Furey, M. L., Ishai, A., Schouten, J. L., & Pietrini, P. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293, 2425–2430.CrossRefPubMed Haxby, J. V., Gobbini, M. I., Furey, M. L., Ishai, A., Schouten, J. L., & Pietrini, P. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293, 2425–2430.CrossRefPubMed
go back to reference Heeger, D. J. (1992). Normalization of cell responses in cat striate cortex. Visual Neuroscience, 9, 181–197.CrossRefPubMed Heeger, D. J. (1992). Normalization of cell responses in cat striate cortex. Visual Neuroscience, 9, 181–197.CrossRefPubMed
go back to reference Hegdé, J., & Van Essen, D. C. (2000). Selectivity for complex shapes in primate visual area V2. Journal of Neuroscience, 20, RC61.PubMed Hegdé, J., & Van Essen, D. C. (2000). Selectivity for complex shapes in primate visual area V2. Journal of Neuroscience, 20, RC61.PubMed
go back to reference Henriksson, L., Hyvärinen, A., & Vanni, S. (2009). Representation of cross-frequency spatial phase relationships in human visual cortex. The Journal of Neuroscience, 29, 14342–14351.CrossRefPubMed Henriksson, L., Hyvärinen, A., & Vanni, S. (2009). Representation of cross-frequency spatial phase relationships in human visual cortex. The Journal of Neuroscience, 29, 14342–14351.CrossRefPubMed
go back to reference Hyvärinen, A., & Hoyer, P. O. (2001). A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images. Vision Research, 41, 2413–2423.CrossRefPubMed Hyvärinen, A., & Hoyer, P. O. (2001). A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images. Vision Research, 41, 2413–2423.CrossRefPubMed
go back to reference Hyvärinen, A., Hurri, J., & Hoyer, P. O. (2009). Natural image statistics: A Probabilistic approach to early computational vision. London: Springer. Hyvärinen, A., Hurri, J., & Hoyer, P. O. (2009). Natural image statistics: A Probabilistic approach to early computational vision. London: Springer.
go back to reference Ichida, J. M., Schwabe, L., Bressloff, P. C., & Angelucci, A. (2007). Response facilitation from the “suppressive” receptive field surround of macaque V1 neurons. Journal of Neurophysiology, 98, 2168–2181.CrossRefPubMed Ichida, J. M., Schwabe, L., Bressloff, P. C., & Angelucci, A. (2007). Response facilitation from the “suppressive” receptive field surround of macaque V1 neurons. Journal of Neurophysiology, 98, 2168–2181.CrossRefPubMed
go back to reference Kapadia, M. K., Ito, M., Gilbert, C. D., & Westheimer, G. (1995). Improvement in visual sensitivity by changes in local context: parallel studies in human observers and in V1 of alert monkeys. Neuron, 15, 843–856.CrossRefPubMed Kapadia, M. K., Ito, M., Gilbert, C. D., & Westheimer, G. (1995). Improvement in visual sensitivity by changes in local context: parallel studies in human observers and in V1 of alert monkeys. Neuron, 15, 843–856.CrossRefPubMed
go back to reference Kastner, S., De Weerd, P., Desimone, R., & Ungerleider, L. G. (1998). Mechanisms of directed attention in the human extrastriate cortex as revealed by functional MRI. Science, 282, 108–111.CrossRefPubMed Kastner, S., De Weerd, P., Desimone, R., & Ungerleider, L. G. (1998). Mechanisms of directed attention in the human extrastriate cortex as revealed by functional MRI. Science, 282, 108–111.CrossRefPubMed
go back to reference Kastner, S., De Weerd, P., Pinsk, M. A., Elizondo, M. I., Desimone, R., & Ungerleider, L. G. (2001). Modulation of sensory suppression: implications for receptive field sizes in the human visual cortex. Journal of Neurophysiology, 86, 1398–1411.PubMed Kastner, S., De Weerd, P., Pinsk, M. A., Elizondo, M. I., Desimone, R., & Ungerleider, L. G. (2001). Modulation of sensory suppression: implications for receptive field sizes in the human visual cortex. Journal of Neurophysiology, 86, 1398–1411.PubMed
go back to reference Kay, K. N., Naselaris, T., Prenger, R. J., & Gallant, J. L. (2008). Identifying natural images from human brain activity. Nature, 452, 352–355.CrossRefPubMed Kay, K. N., Naselaris, T., Prenger, R. J., & Gallant, J. L. (2008). Identifying natural images from human brain activity. Nature, 452, 352–355.CrossRefPubMed
go back to reference Kinoshita, M., Gilbert, C. D., & Das, A. (2009). Optical imaging of contextual interactions in V1 of the behaving monkey. Journal of Neurophysiology, 102, 1930–1944.CrossRefPubMed Kinoshita, M., Gilbert, C. D., & Das, A. (2009). Optical imaging of contextual interactions in V1 of the behaving monkey. Journal of Neurophysiology, 102, 1930–1944.CrossRefPubMed
go back to reference Knierim, J. J., & Van Essen, D. C. (1992). Neuronal responses to static texture patters in area V1 of the alert macaque monkey. Journal of Neurophysiology, 67, 961–980.PubMed Knierim, J. J., & Van Essen, D. C. (1992). Neuronal responses to static texture patters in area V1 of the alert macaque monkey. Journal of Neurophysiology, 67, 961–980.PubMed
go back to reference Kouh, M., & Poggio, T. (2008). A canonical neural circuit for cortical nonlinear operations. Neural Computation, 20, 1427–1451.CrossRefPubMed Kouh, M., & Poggio, T. (2008). A canonical neural circuit for cortical nonlinear operations. Neural Computation, 20, 1427–1451.CrossRefPubMed
go back to reference Larsson, J., Landy, M. S., & Heeger, D. J. (2006). Orientation-selective adaptation to first- and second-order patterns in human visual cortex. Journal of Neurophysiology, 95, 862–881.CrossRefPubMed Larsson, J., Landy, M. S., & Heeger, D. J. (2006). Orientation-selective adaptation to first- and second-order patterns in human visual cortex. Journal of Neurophysiology, 95, 862–881.CrossRefPubMed
go back to reference Latham, P. E., & Nirenberg, S. (2005). Synergy, redundancy, and independence in population codes, revisited. The Journal of Neuroscience, 25, 5195–5206.CrossRefPubMed Latham, P. E., & Nirenberg, S. (2005). Synergy, redundancy, and independence in population codes, revisited. The Journal of Neuroscience, 25, 5195–5206.CrossRefPubMed
go back to reference Laughlin, S. B., & Sejnowski, T. J. (2003). Communication in neuronal networks. Science, 301, 1870–1874.CrossRefPubMed Laughlin, S. B., & Sejnowski, T. J. (2003). Communication in neuronal networks. Science, 301, 1870–1874.CrossRefPubMed
go back to reference Levitt, J. B., & Lund, J. S. (1997). Contrast dependence of contextual effects in primate visual cortex. Nature, 387, 73–76.CrossRefPubMed Levitt, J. B., & Lund, J. S. (1997). Contrast dependence of contextual effects in primate visual cortex. Nature, 387, 73–76.CrossRefPubMed
go back to reference Levy, W. B., & Baxter, R. A. (1996). Energy efficient neural codes. Neural Computation, 8, 531–543.CrossRefPubMed Levy, W. B., & Baxter, R. A. (1996). Energy efficient neural codes. Neural Computation, 8, 531–543.CrossRefPubMed
go back to reference Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature, 412, 150–157.CrossRefPubMed Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature, 412, 150–157.CrossRefPubMed
go back to reference Maffei, L., & Fiorentini, A. (1976). The unresponsive regions of visual cortical receptive fields. Vision Research, 16, 1131–1139.CrossRefPubMed Maffei, L., & Fiorentini, A. (1976). The unresponsive regions of visual cortical receptive fields. Vision Research, 16, 1131–1139.CrossRefPubMed
go back to reference Miller, E. K., Gochin, P. M., & Gross, C. G. (1993). Suppression of visual responses of neurons in inferior temporal cortex of the awake macaque by addition of a second stimulus. Brain Research, 616, 25–29.CrossRefPubMed Miller, E. K., Gochin, P. M., & Gross, C. G. (1993). Suppression of visual responses of neurons in inferior temporal cortex of the awake macaque by addition of a second stimulus. Brain Research, 616, 25–29.CrossRefPubMed
go back to reference Missal, M., Vogels, R., Li, C. Y., & Orban, G. A. (1999). Shape interactions in macaque inferior temporal neurons. Journal of Neurophysiology, 82, 131–142.PubMed Missal, M., Vogels, R., Li, C. Y., & Orban, G. A. (1999). Shape interactions in macaque inferior temporal neurons. Journal of Neurophysiology, 82, 131–142.PubMed
go back to reference Murayama, Y., Bießmann, F., Meinecke, F. C., Muller, K. R., Augath, M., Oeltermann, A., et al. (2010). Relationship between neural and hemodynamic signals during spontaneous activity studied with temporal kernel CCA Magn Reson Imaging. http://dx.doi.org/10.1016/j.mri.2009.12.016 Murayama, Y., Bießmann, F., Meinecke, F. C., Muller, K. R., Augath, M., Oeltermann, A., et al. (2010). Relationship between neural and hemodynamic signals during spontaneous activity studied with temporal kernel CCA Magn Reson Imaging. http://​dx.​doi.​org/​10.​1016/​j.​mri.​2009.​12.​016
go back to reference Nurminen, L., Kilpeläinen, M., Laurinen, P., & Vanni, S. (2009). Area summation in human visual system: psychophysics, fMRI, and modeling. Journal of Neurophysiology, 102, 2900–2909.CrossRefPubMed Nurminen, L., Kilpeläinen, M., Laurinen, P., & Vanni, S. (2009). Area summation in human visual system: psychophysics, fMRI, and modeling. Journal of Neurophysiology, 102, 2900–2909.CrossRefPubMed
go back to reference Olshausen, B. A., & Field, D. J. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381, 607–609.CrossRefPubMed Olshausen, B. A., & Field, D. J. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381, 607–609.CrossRefPubMed
go back to reference Olshausen, B. A., & Field, D. J. (2004). Sparse coding of sensory inputs. Current Opinion in Neurobiology, 14, 481–487.CrossRefPubMed Olshausen, B. A., & Field, D. J. (2004). Sparse coding of sensory inputs. Current Opinion in Neurobiology, 14, 481–487.CrossRefPubMed
go back to reference Ozeki, H., Finn, I. M., Schaffer, E. S., Miller, K. D., & Ferster, D. (2009). Inhibitory stabilization of the cortical network underlies visual surround suppression. Neuron, 62, 578–592.CrossRefPubMed Ozeki, H., Finn, I. M., Schaffer, E. S., Miller, K. D., & Ferster, D. (2009). Inhibitory stabilization of the cortical network underlies visual surround suppression. Neuron, 62, 578–592.CrossRefPubMed
go back to reference Pihlaja, M., Henriksson, L., James, A. C., & Vanni, S. (2008). Quantitative multifocal fMRI shows active suppression in human V1. Human Brain Mapping, 29, 1001–1014.CrossRefPubMed Pihlaja, M., Henriksson, L., James, A. C., & Vanni, S. (2008). Quantitative multifocal fMRI shows active suppression in human V1. Human Brain Mapping, 29, 1001–1014.CrossRefPubMed
go back to reference Polat, U., & Sagi, D. (1993). Lateral interactions between spatial channels: suppression and facilitation revealed by lateral masking experiments. Vision Research, 33, 993–999.CrossRefPubMed Polat, U., & Sagi, D. (1993). Lateral interactions between spatial channels: suppression and facilitation revealed by lateral masking experiments. Vision Research, 33, 993–999.CrossRefPubMed
go back to reference Polat, U., Mizobe, K., Pettet, M. W., Kasamatsu, T., & Norcia, A. M. (1998). Collinear stimuli regulate visual responses depending on cell’s contrast threshold. Nature, 391, 580–584.CrossRefPubMed Polat, U., Mizobe, K., Pettet, M. W., Kasamatsu, T., & Norcia, A. M. (1998). Collinear stimuli regulate visual responses depending on cell’s contrast threshold. Nature, 391, 580–584.CrossRefPubMed
go back to reference Rao, R. P., & Ballard, D. H. (1999). Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience, 2, 79–87.CrossRefPubMed Rao, R. P., & Ballard, D. H. (1999). Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience, 2, 79–87.CrossRefPubMed
go back to reference Renart, A., de la Rocha, J., Bartho, P., Hollender, L., Parga, N., Reyes, A., et al. (2010). The asynchronous state in cortical circuits. Science, 327, 587–590.CrossRefPubMed Renart, A., de la Rocha, J., Bartho, P., Hollender, L., Parga, N., Reyes, A., et al. (2010). The asynchronous state in cortical circuits. Science, 327, 587–590.CrossRefPubMed
go back to reference Sayres, R., & Grill-Spector, K. (2008). Relating retinotopic and object-selective responses in human lateral occipital cortex. Journal of Neurophysiology, 100, 249–267.CrossRefPubMed Sayres, R., & Grill-Spector, K. (2008). Relating retinotopic and object-selective responses in human lateral occipital cortex. Journal of Neurophysiology, 100, 249–267.CrossRefPubMed
go back to reference Sceniak, M. P., Ringach, D. L., Hawken, M. J., & Shapley, R. (1999). Contrast’s effect on spatial summation by macaque V1 neurons. Nature Neuroscience, 2, 733–739.CrossRefPubMed Sceniak, M. P., Ringach, D. L., Hawken, M. J., & Shapley, R. (1999). Contrast’s effect on spatial summation by macaque V1 neurons. Nature Neuroscience, 2, 733–739.CrossRefPubMed
go back to reference Sceniak, M. P., Hawken, M. J., & Shapley, R. (2001). Visual spatial characterization of macaque V1 neurons. Journal of Neurophysiology, 85, 1873–1887.PubMed Sceniak, M. P., Hawken, M. J., & Shapley, R. (2001). Visual spatial characterization of macaque V1 neurons. Journal of Neurophysiology, 85, 1873–1887.PubMed
go back to reference Schwabe, L., & Obermayer, K. (2005). Adaptivity of tuning functions in a generic recurrent network model of a cortical hypercolumn. The Journal of Neuroscience, 25, 3323–3332.CrossRefPubMed Schwabe, L., & Obermayer, K. (2005). Adaptivity of tuning functions in a generic recurrent network model of a cortical hypercolumn. The Journal of Neuroscience, 25, 3323–3332.CrossRefPubMed
go back to reference Schwabe, L., Obermayer, K., Angelucci, A., & Bressloff, P. C. (2006). The role of feedback in shaping the extra-classical receptive field of cortical neurons: a recurrent network model. The Journal of Neuroscience, 26, 9117–9129.CrossRefPubMed Schwabe, L., Obermayer, K., Angelucci, A., & Bressloff, P. C. (2006). The role of feedback in shaping the extra-classical receptive field of cortical neurons: a recurrent network model. The Journal of Neuroscience, 26, 9117–9129.CrossRefPubMed
go back to reference Schwabe, L., Ichida, J. M., Shushruth, S., Mangapathy, P., & Angelucci, A. (2010). Contrast-dependence of surround suppression in Macaque V1: Experimental testing of a recurrent network model. Neuroimage. http://dx.doi.org/10.1016/j.neuroimage.2010.01.032 Schwabe, L., Ichida, J. M., Shushruth, S., Mangapathy, P., & Angelucci, A. (2010). Contrast-dependence of surround suppression in Macaque V1: Experimental testing of a recurrent network model. Neuroimage. http://​dx.​doi.​org/​10.​1016/​j.​neuroimage.​2010.​01.​032
go back to reference Schwartz, O., Sejnowski, T. J., & Dayan, P. (2006). Soft mixer assignment in a hierarchical generative model of natural scene statistics. Neural Computation, 18, 2680–2718.CrossRefPubMed Schwartz, O., Sejnowski, T. J., & Dayan, P. (2006). Soft mixer assignment in a hierarchical generative model of natural scene statistics. Neural Computation, 18, 2680–2718.CrossRefPubMed
go back to reference Schwartz, O., Sejnowski, T. J., & Dayan, P. (2009). Perceptual organization in the tilt illusion. Journal of Vision, 9(19), 1–20.PubMed Schwartz, O., Sejnowski, T. J., & Dayan, P. (2009). Perceptual organization in the tilt illusion. Journal of Vision, 9(19), 1–20.PubMed
go back to reference Seghier, M., Dojat, M., Delon-Martin, C., Rubin, C., Warnking, J., Segebarth, C., et al. (2000). Moving illusory contours activate primary visual cortex: an fMRI study. Cerebral Cortex, 10, 663–670.CrossRefPubMed Seghier, M., Dojat, M., Delon-Martin, C., Rubin, C., Warnking, J., Segebarth, C., et al. (2000). Moving illusory contours activate primary visual cortex: an fMRI study. Cerebral Cortex, 10, 663–670.CrossRefPubMed
go back to reference Shadlen, M. N., & Newsome, W. T. (1994). Noise, neural codes and cortical organization. Current Opinion in Neurobiology, 4, 569–579.CrossRefPubMed Shadlen, M. N., & Newsome, W. T. (1994). Noise, neural codes and cortical organization. Current Opinion in Neurobiology, 4, 569–579.CrossRefPubMed
go back to reference Shannon, C. E. (1948). A Mathematical theory of communication. The Bell System Technical Journal, 27, 379–423. Shannon, C. E. (1948). A Mathematical theory of communication. The Bell System Technical Journal, 27, 379–423.
go back to reference Sharpee, T. O., & Victor, J. D. (2009). Contextual modulation of V1 receptive fields depends on their spatial symmetry. Journal of Computational Neuroscience, 26, 203–218.CrossRefPubMed Sharpee, T. O., & Victor, J. D. (2009). Contextual modulation of V1 receptive fields depends on their spatial symmetry. Journal of Computational Neuroscience, 26, 203–218.CrossRefPubMed
go back to reference Shmuel, A., Chaimow, D., Raddatz, G., Ugurbil, K., & Yacoub, E. (2010). Mechanisms underlying decoding at 7 T: Ocular dominance columns, broad structures, and macroscopic blood vessels in V1 convey information on the stimulated eye. Neuroimage, 49, 1943–1948.CrossRef Shmuel, A., Chaimow, D., Raddatz, G., Ugurbil, K., & Yacoub, E. (2010). Mechanisms underlying decoding at 7 T: Ocular dominance columns, broad structures, and macroscopic blood vessels in V1 convey information on the stimulated eye. Neuroimage, 49, 1943–1948.CrossRef
go back to reference Shulman, R. G., Hyder, F., & Rothman, D. L. (2001). Cerebral energetics and the glycogen shunt: neurochemical basis of functional imaging. Proceedings of the National Academy of Sciences of the United States of America, 98, 6417–6422.CrossRefPubMed Shulman, R. G., Hyder, F., & Rothman, D. L. (2001). Cerebral energetics and the glycogen shunt: neurochemical basis of functional imaging. Proceedings of the National Academy of Sciences of the United States of America, 98, 6417–6422.CrossRefPubMed
go back to reference Simoncelli, E. P., & Olshausen, B. A. (2001). Natural image statistics and neural representation. Annual Review of Neuroscience, 24, 1193–1216.CrossRefPubMed Simoncelli, E. P., & Olshausen, B. A. (2001). Natural image statistics and neural representation. Annual Review of Neuroscience, 24, 1193–1216.CrossRefPubMed
go back to reference Spratling, M. W. (2010). Predictive coding as a model of response properties in cortical area v1. The Journal of Neuroscience, 30, 3531–3543.CrossRefPubMed Spratling, M. W. (2010). Predictive coding as a model of response properties in cortical area v1. The Journal of Neuroscience, 30, 3531–3543.CrossRefPubMed
go back to reference Sundberg, K. A., Mitchell, J. F., & Reynolds, J. H. (2009). Spatial attention modulates center-surround interactions in macaque visual area v4. Neuron, 61, 952–963.CrossRefPubMed Sundberg, K. A., Mitchell, J. F., & Reynolds, J. H. (2009). Spatial attention modulates center-surround interactions in macaque visual area v4. Neuron, 61, 952–963.CrossRefPubMed
go back to reference Tajima, S., Watanabe, M., Imai, C., Ueno, K., Asamizuya, T., Sun, P., et al. (2010). Opposing effects of contextual surround in human early visual cortex revealed by functional magnetic resonance imaging with continuously modulated visual stimuli. The Journal of Neuroscience, 30, 3264–3270.CrossRefPubMed Tajima, S., Watanabe, M., Imai, C., Ueno, K., Asamizuya, T., Sun, P., et al. (2010). Opposing effects of contextual surround in human early visual cortex revealed by functional magnetic resonance imaging with continuously modulated visual stimuli. The Journal of Neuroscience, 30, 3264–3270.CrossRefPubMed
go back to reference Tsodyks, M. V., Skaggs, W. E., Sejnowski, T. J., & McNaughton, B. L. (1997). Paradoxical effects of external modulation of inhibitory interneurons. The Journal of Neuroscience, 17, 4382–4388.PubMed Tsodyks, M. V., Skaggs, W. E., Sejnowski, T. J., & McNaughton, B. L. (1997). Paradoxical effects of external modulation of inhibitory interneurons. The Journal of Neuroscience, 17, 4382–4388.PubMed
go back to reference Vanni, S., Dojat, M., Warnking, J., Delon-Martin, C., Segebarth, C., & Bullier, J. (2004). Timing of interactions across the visual field in the human cortex. Neuroimage, 21, 818–828.CrossRefPubMed Vanni, S., Dojat, M., Warnking, J., Delon-Martin, C., Segebarth, C., & Bullier, J. (2004). Timing of interactions across the visual field in the human cortex. Neuroimage, 21, 818–828.CrossRefPubMed
go back to reference Williams, A. L., Singh, K. D., & Smith, A. T. (2003). Surround modulation measured with functional MRI in the human visual cortex. Journal of Neurophysiology, 89, 525–533.CrossRefPubMed Williams, A. L., Singh, K. D., & Smith, A. T. (2003). Surround modulation measured with functional MRI in the human visual cortex. Journal of Neurophysiology, 89, 525–533.CrossRefPubMed
go back to reference Willmore, B., & Tolhurst, D. J. (2001). Characterizing the sparseness of neural codes. Network, 12, 255–270.PubMed Willmore, B., & Tolhurst, D. J. (2001). Characterizing the sparseness of neural codes. Network, 12, 255–270.PubMed
go back to reference Vinje, W. E., & Gallant, J. L. (2000). Sparse coding and decorrelation in primary visual cortex during natural vision. Science, 287, 1273–1276.CrossRefPubMed Vinje, W. E., & Gallant, J. L. (2000). Sparse coding and decorrelation in primary visual cortex during natural vision. Science, 287, 1273–1276.CrossRefPubMed
go back to reference Vinje, W. E., & Gallant, J. L. (2002). Natural stimulation of the nonclassical receptive field increases information transmission efficiency in V1. The Journal of Neuroscience, 22, 2904–2915.PubMed Vinje, W. E., & Gallant, J. L. (2002). Natural stimulation of the nonclassical receptive field increases information transmission efficiency in V1. The Journal of Neuroscience, 22, 2904–2915.PubMed
go back to reference Xing, J., & Heeger, D. J. (2001). Measurement and modeling of center-surround suppression and enhancement. Vision Research, 41, 571–583.CrossRefPubMed Xing, J., & Heeger, D. J. (2001). Measurement and modeling of center-surround suppression and enhancement. Vision Research, 41, 571–583.CrossRefPubMed
go back to reference Zenger-Landolt, B., & Heeger, D. J. (2003). Response suppression in v1 agrees with psychophysics of surround masking. The Journal of Neuroscience, 23, 6884–6893.PubMed Zenger-Landolt, B., & Heeger, D. J. (2003). Response suppression in v1 agrees with psychophysics of surround masking. The Journal of Neuroscience, 23, 6884–6893.PubMed
go back to reference Zoccolan, D., Cox, D. D., & DiCarlo, J. J. (2005). Multiple object response normalization in monkey inferotemporal cortex. The Journal of Neuroscience, 25, 8150–8164.CrossRefPubMed Zoccolan, D., Cox, D. D., & DiCarlo, J. J. (2005). Multiple object response normalization in monkey inferotemporal cortex. The Journal of Neuroscience, 25, 8150–8164.CrossRefPubMed
Metadata
Title
Local non-linear interactions in the visual cortex may reflect global decorrelation
Authors
Simo Vanni
Tom Rosenström
Publication date
01-02-2011
Publisher
Springer US
Published in
Journal of Computational Neuroscience / Issue 1/2011
Print ISSN: 0929-5313
Electronic ISSN: 1573-6873
DOI
https://doi.org/10.1007/s10827-010-0239-2

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