Analysis of Multineuron Activity Using the Kernel Method

Masaki Nomura; Yoshio Sakurai; Toshio Aoyagi

doi:10.20965/jrm.2007.p0364

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JRM Vol.19 No.4 pp. 364-368

doi: 10.20965/jrm.2007.p0364

(2007)

Paper:

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Analysis of Multineuron Activity Using the Kernel Method

Masaki Nomura^, Yoshio Sakurai^,**, and Toshio Aoyagi^*,***

^*CREST, Japan Science and Technology Corporation, Kawaguchi, Saitama 332-0012, Japan

^**Department of Psychology, Graduate School of Letters, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan

^***Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan

Received:

January 11, 2007

Accepted:

April 20, 2007

Published:

August 20, 2007

Keywords:

hippocampus, multineuron activity, kernel method

Abstract

We recorded multineuron spike time-series data from rat hippocampus region CA1 during a conditional discrimination task. We separated out individual single-neuron activity from multineuron activity data and prepared spike count data and calculated a kernel matrix using a Spikernel function, then applied k-means clustering and principal component analysis (PCA). Comparing spike count data to an appropriate time, we divided data into clusters and found the correspondence between the obtained cluster and rat activity. We discuss information expression in nervous-system activity expected from the kernel function.

Cite this article as:

M. Nomura, Y. Sakurai, and T. Aoyagi, “Analysis of Multineuron Activity Using the Kernel Method,” J. Robot. Mechatron., Vol.19 No.4, pp. 364-368, 2007.

Data files:

References

[1] M. A. L. Nicolelis, “Actions from thoughts,” Nature, Vol.409, pp. 403-407, 2001.
[2] Y. Kamitani and F. Tong, “Decoding the visual and subjective contents of the human brain,” Nature Neurosci., Vol.8, No.5, pp. 679-685, 2005.
[3] Y. Sakurai, “Brain-machine interface to detect real dynamics of neuronal assemblies in the working brain,” Complex Medical Engineering, J. L. Wu, K. Ito, S. Tobimatsu, T. Nishida, and H. Fukuyama (Eds.), Springer, Tokyo, 2006 (in press).
[4] Y. Koike, H. Hirose, Y. Sakurai, and T. Iijima, “Prediction of arm trajectory from a small number of neuron activities in the primary motor cortex,” Neurosci. Res., Vol.56, pp. 146-153, 2006.
[5] B. Scholkopf and A. J. Smola, “Learning With Kernels: Support Vector Machines, Regularization, Optimization and Beyond,” Adaptive Computation and Machine Learning, MIT Press, 2001.
[6] J. Shawe-Taylor and N. Cristianini, “Kernel Methods for Pattern Analysis,” Cambridge University Press, 2004.
[7] L. Shpigelman, Y. Singer, R. Paz, and E. Vaadia, “Spikernels: Predicting Arm Movements by Embedding Population Spike Rate Patterns in Inner-Product Spaces,” Neural Comput., Vol.17, pp. 671-690, 2005.
[8] Y. Sakurai, “Hippocampal cells have behavioral correlates during the performance of an auditory working memory task in the rat,” Behav. Neurosci., Vol.104, pp. 253-263, 1990.
[9] Y. Sakurai, “Involvement of auditory cortical and hippocampal neurons in auditory working memory and reference memory in the rat,” J. Neurosci., Vol.14, pp. 2606-2623, 1994.
[10] Y. Sakurai, “Coding of temporal information by hippocampal individual cells and cell assemblies in the rat,” Neuroscience, Vol.115, pp. 1153-1163, 2002.
[11] S. Takahashi, Y. Anzai, and Y. Sakurai, “Automatic sorting for multi-neuronal activity recorded with tetrodes in the presence of overlapping spikes,” J. Neurophysiol., Vol.89, pp. 2245-2258, 2003.
[12] J. J. Hopfield, “Neural networks and physical systems with emergent collective computational abilities,” Proc. Natl. Acad. Sci. USA, Vol.79, pp. 2554-2558, 1982.
[13] T. Aoyagi and M. Nomura, “Oscillator Neural Networks Retrieving Sparsely Coded Phase Patterns,” Phys. Rev. Lett., Vol.83, No.5, pp. 1062-1065, 1999.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] M. A. L. Nicolelis, “Actions from thoughts,” Nature, Vol.409, pp. 403-407, 2001.

[2] [2] Y. Kamitani and F. Tong, “Decoding the visual and subjective contents of the human brain,” Nature Neurosci., Vol.8, No.5, pp. 679-685, 2005.

[3] [3] Y. Sakurai, “Brain-machine interface to detect real dynamics of neuronal assemblies in the working brain,” Complex Medical Engineering, J. L. Wu, K. Ito, S. Tobimatsu, T. Nishida, and H. Fukuyama (Eds.), Springer, Tokyo, 2006 (in press).

[4] [4] Y. Koike, H. Hirose, Y. Sakurai, and T. Iijima, “Prediction of arm trajectory from a small number of neuron activities in the primary motor cortex,” Neurosci. Res., Vol.56, pp. 146-153, 2006.

[5] [5] B. Scholkopf and A. J. Smola, “Learning With Kernels: Support Vector Machines, Regularization, Optimization and Beyond,” Adaptive Computation and Machine Learning, MIT Press, 2001.

[6] [6] J. Shawe-Taylor and N. Cristianini, “Kernel Methods for Pattern Analysis,” Cambridge University Press, 2004.

[7] [7] L. Shpigelman, Y. Singer, R. Paz, and E. Vaadia, “Spikernels: Predicting Arm Movements by Embedding Population Spike Rate Patterns in Inner-Product Spaces,” Neural Comput., Vol.17, pp. 671-690, 2005.

[8] [8] Y. Sakurai, “Hippocampal cells have behavioral correlates during the performance of an auditory working memory task in the rat,” Behav. Neurosci., Vol.104, pp. 253-263, 1990.

[9] [9] Y. Sakurai, “Involvement of auditory cortical and hippocampal neurons in auditory working memory and reference memory in the rat,” J. Neurosci., Vol.14, pp. 2606-2623, 1994.

[10] [10] Y. Sakurai, “Coding of temporal information by hippocampal individual cells and cell assemblies in the rat,” Neuroscience, Vol.115, pp. 1153-1163, 2002.

[11] [11] S. Takahashi, Y. Anzai, and Y. Sakurai, “Automatic sorting for multi-neuronal activity recorded with tetrodes in the presence of overlapping spikes,” J. Neurophysiol., Vol.89, pp. 2245-2258, 2003.

[12] [12] J. J. Hopfield, “Neural networks and physical systems with emergent collective computational abilities,” Proc. Natl. Acad. Sci. USA, Vol.79, pp. 2554-2558, 1982.

[13] [13] T. Aoyagi and M. Nomura, “Oscillator Neural Networks Retrieving Sparsely Coded Phase Patterns,” Phys. Rev. Lett., Vol.83, No.5, pp. 1062-1065, 1999.

Analysis of Multineuron Activity Using the Kernel Method

Masaki Nomura*, Yoshio Sakurai*,**, and Toshio Aoyagi*,***

Masaki Nomura^, Yoshio Sakurai^,**, and Toshio Aoyagi^*,***