nips nips2013 nips2013-205 nips2013-205-reference knowledge-graph by maker-knowledge-mining
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Author: Aurel A. Lazar, Yevgeniy Slutskiy
Abstract: We investigate a spiking neuron model of multisensory integration. Multiple stimuli from different sensory modalities are encoded by a single neural circuit comprised of a multisensory bank of receptive fields in cascade with a population of biophysical spike generators. We demonstrate that stimuli of different dimensions can be faithfully multiplexed and encoded in the spike domain and derive tractable algorithms for decoding each stimulus from the common pool of spikes. We also show that the identification of multisensory processing in a single neuron is dual to the recovery of stimuli encoded with a population of multisensory neurons, and prove that only a projection of the circuit onto input stimuli can be identified. We provide an example of multisensory integration using natural audio and video and discuss the performance of the proposed decoding and identification algorithms. 1
[1] Barry E. Stein and Terrence R. Stanford. Multisensory integration: Current issues from the perspective of a single neuron. Nature Reviews Neuroscience, 9:255–266, April 2008.
[2] Christoph Kayser, Christopher I. Petkov, and Nikos K. Logothetis. Multisensory interactions in primate auditory cortex: fmri and electrophysiology. Hearing Research, 258:80–88, March 2009.
[3] Stephen J. Huston and Vivek Jayaraman. Studying sensorimotor integration in insects. Current Opinion in Neurobiology, 21:527–534, June 2011.
[4] Barry E. Stein and M. Alex Meredith. The merging of the senses. The MIT Press, 1993.
[5] David A. Bulkin and Jennifer M. Groh. Seeing sounds: Visual and auditory interactions in the brain. Current Opinion in Neurobiology, 16:415–419, July 2006.
[6] Jon Driver and Toemme Noesselt. Multisensory interplay reveals crossmodal influences on ’sensoryspecific’ brain regions, natural responses, and judgments. Neuron, 57:11–23, January 2008.
[7] Christoph Kayser, Nikos K. Logothetis, and Stefano Panzeri. Visual enhancement of the information representation in auditory cortex. Current Biology, pages 19–24, January 2010.
[8] Asif A. Ghazanfar and Charles E. Schroeder. Is neocortex essentially multisensory? Trends in Cognitive Sciences, 10:278–285, June 2006.
[9] Paul J. Laurienti, Thomas J. Perrault, Terrence R. Stanford, Mark T. Wallace, and Barry E. Stein. On the use of superadditivity as a metric for characterizing multisensory integration in functional neuroimaging studies. Experimental Brain Research, 166:289–297, 2005.
[10] Konrad P. K¨ rding and Joshua B. Tenenbaum. Causal inference in sensorimotor integration. Advances in o Neural Information Processing Systems 19, 2007.
[11] Ulrik R. Beierholm, Konrad P. K¨ rding, Ladan Shams, and Wei Ji Ma. Comparing bayesian models for o multisensory cue combination without mandatory integration. Advances in Neural Information Processing Systems 20, 2008.
[12] Daniel C. Kadunce, J. William Vaughan, Mark T. Wallace, and Barry E. Stein. The influence of visual and auditory receptive field organization on multisensory integration in the superior colliculus. Experimental Brain Research, 2001.
[13] Wei Ji Ma and Alexandre Pouget. Linking neurons to behavior in multisensory perception: A computational review. Brain Research, 1242:4–12, 2008.
[14] Mark A. Frye. Multisensory systems integration for high-performance motor control in flies. Current Opinion in Neurobiology, 20:347–352, 2010.
[15] Aurel A. Lazar and Yevgeniy B. Slutskiy. Channel Identification Machines. Computational Intelligence and Neuroscience, 2012.
[16] Aurel A. Lazar. Time encoding with an integrate-and-fire neuron with a refractory period. Neurocomputing, 58-60:53–58, June 2004.
[17] Aurel A. Lazar. Population encoding with Hodgkin-Huxley neurons. IEEE Transactions on Information Theory, 56(2), February 2010.
[18] Aurel A. Lazar and Laszlo T. T´ th. Perfect recovery and sensitivity analysis of time encoded bandlimited o signals. IEEE Transactions on Circuits and Systems-I: Regular Papers, 51(10):2060–2073, 2004.
[19] Aurel A. Lazar and Eftychios A. Pnevmatikakis. Faithful representation of stimuli with a population of integrate-and-fire neurons. Neural Computation, 20(11):2715–2744, November 2008.
[20] Aurel A. Lazar and Yevgeniy B. Slutskiy. Functional identification of spike-processing neural circuits. Neural Computation, in press, 2013.
[21] Anmo J. Kim and Aurel A. Lazar. Recovery of stimuli encoded with a Hodgkin-Huxley neuron using conditional PRCs. In N.W. Schultheiss, A.A. Prinz, and R.J. Butera, editors, Phase Response Curves in Neuroscience. Springer, 2011.
[22] Alain Berlinet and Christine Thomas-Agnan. Reproducing Kernel Hilbert Spaces in Probability and Statistics. Kluwer Academic Publishers, 2004.
[23] Aurel A. Lazar, Eftychios A. Pnevmatikakis, and Yiyin Zhou. Encoding natural scenes with neural circuits with random thresholds. Vision Research, 2010. Special Issue on Mathematical Models of Visual Coding.
[24] Aurel A. Lazar and Eftychios A. Pnevmatikakis. Reconstruction of sensory stimuli encoded with integrate-and-fire neurons with random thresholds. EURASIP Journal on Advances in Signal Processing, 2009, 2009.
[25] Yevgeniy B. Slutskiy. Identification of Dendritic Processing in Spiking Neural Circuits. PhD thesis, Columbia University, 2013. 9