Dual coding hypotheses for neural information representation

Mathematical Biosciences

Volumn 207, Issue 2, 2007, Pages 312-321

  Masuda, Naoki ^a,b   Aihara, Kazuyuki ^b,c  

^a RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

^b JAPAN SCIENCE AND TECHNOLOGY AGENCY   (Japan)

^c INSTITUTE OF INDUSTRIAL SCIENCE   (Japan)

Author keywords

Firing rate; Neural code; Spike timing dependent plasticity; Synchrony

Indexed keywords

BRAIN; DATA PROCESSING; EMBEDDED SYSTEMS; ENCODING (SYMBOLS);

FIRING RATE; NEURAL CODE; SPIKE TIMING DEPENDENT PLASTICITY; SYNCHRONY;

NEURAL NETWORKS;

BRAIN; INFORMATION PROCESSING; NERVOUS SYSTEM; SYNCHRONY;

ARTICLE; BRAIN REGION; CODING; CORTICAL SYNCHRONIZATION; INFORMATION PROCESSING; NERVE POTENTIAL; NEUROSCIENCE; SPIKE WAVE;

ACTION POTENTIALS; ANIMALS; BRAIN; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; NERVOUS SYSTEM PHYSIOLOGY; NEURONAL PLASTICITY; NEURONS;

EID: 34248525915     PISSN: 00255564     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.mbs.2006.09.009     Document Type: Article

References (51)

1. Thorpe S., Fize D., and Marlot C. Speed of processing in the human visual system. Nature 381 (1996) 520
2. Shadlen M.N., and Newsome W.T. The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. J. Neurosci. 18 (1998) 3870
3. Mar D.J., Chow C.C., Gerstner W., Adams R.W., and Collins J.J. Noise shaping in populations of coupled model neurons. Proc. Natl. Acad. Sci. USA 96 (1999) 10450
4. Cardoso de Oliveira S., Thiele A., and Hoffmann K.-P. Synchronization of neuronal activity during stimulus expectation in a direction discrimination task. J. Neurosci. 17 (1997) 9248
5. Riehle A., Grün S., Diesmann M., and Aertsen A. Spike synchronization and rate modulation differently involved in motor cortical function. Science 278 (1997) 1950
6. Steinmetz P.N., Roy A., Fitzgerald P.J., Hsiao S.S., Johnson K.O., and Niebur E. Attention modulates synchronized neuronal firing in primate somatosensory cortex. Nature 404 (2000) 187
7. Fries P., Reynolds J.H., Rorie A.E., and Desimone R. Modulation of oscillatory neuronal synchronization by selective visual attention. Science 291 (2001) 1560
8. Friedrich R.W., Habermann C.J., and Laurent G. Multiplexing using synchrony in the zebrafish olfactory bulb. Nat. Neurosci. 7 (2004) 862
9. Gray C.M., König P., Engel A.K., and Singer W. Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338 (1989) 334
10. Singer W., and Gray C.M. Visual feature integration and the temporal correlation hypothesis. Ann. Rev. Neurosci. 18 (1995) 555
11. Gray C.M. The temporal correlation hypothesis of visual feature integration: still alive and well. Neuron 24 (1999) 31
12. Vaadia E., Haalman L., Abeles M., Bergman H., Prut Y., Slovin H., and Aertsen A. Dynamics of neuronal interactions in monkey cortex in relation to behavioural events. Nature 373 (1995) 515
13. Roelfsema P.R., Lamme V.A.F., and Spekreijse H. Synchrony and covariation of firing rates in the primary visual cortex during contour grouping. Nat. Neurosci. 7 (2004) 982
14. Abeles M. Corticonics (1991), Cambridge University, Cambridge
15. Diesmann M., Gewaltig M.-O., and Aertsen A. Stable propagation of synchronous spiking in cortical neural networks. Nature 402 (1999) 529
16. Reyes A.D. Synchrony-dependent propagation of firing rate in iteratively constructed networks in vitro. Nat. Neurosci. 6 (2003) 593
17. Watanabe M., and Aihara K. Chaos in neural networks composed of coincidence detector neurons. Neural Netw. 10 (1997) 1353
18. Izhikevich E.M. Polychronization: computation with spikes. Neural. Comput. 18 (2006) 245
19. Bialek W., Rieke F., de Ruyter van Steveninck R.R., and Warland D. Reading a neural code. Science 252 (1991) 1854
20. Berry M.J., Warland D.K., and Meister M. The structure and precision of retinal spike trains. Proc. Natl. Acad. Sci. USA 94 (1997) 5411
21. Rieke F., Warland D., de Ruyter van Steveninck R., and Bialek W. Spikes (1997), The MIT, Cambridge
22. Sauer T. Reconstruction of dynamical systems from interspike intervals. Phys. Rev. Lett. 72 (1994) 3811
23. Suzuki H., Aihara K., Murakami J., and Shimozawa T. Analysis of neural spike trains with interspike interval reconstruction. Biol. Cybern. 82 (2000) 305
24. Aihara K., and Tokuda I. Possible neural coding with inter-event intervals of synchronous firing. Phys. Rev. E 66 (2002) 026212
25. Masuda N., and Aihara K. Spatio-temporal spike encoding of a continuous external signal. Neural Comput. 14 (2002) 1599
26. Krüger J., and Becker D. Recognizing the visual stimulus from neuronal discharges. Trends Neurosci. 14 (1991) 282
27. Sakurai Y. How do cell assemblies encode information in the brain?. Neurosci. Biobehav. Rev. 23 (1999) 785
28. Sompolinsky H., Golomb D., and Kleinfeld D. Global processing of visual stimuli in a neural network of coupled oscillators. Proc. Natl. Acad. Sci. USA 87 (1990) 7200
29. Huxter J., Burgess N., and O'Keefe J. Independent rate and temporal coding in hippocampal pyramidal cells. Nature 425 (2003) 828
30. Masuda N. Simultaneous rate-synchrony codes in populations of spiking neurons. Neural Comput. 18 (2006) 45
31. Masuda N., and Aihara K. Self-organizing dual coding based on spike-time-dependent plasticity. Neural Comput. 16 (2004) 627
32. Lu T., Liang L., and Wang X. Temporal and rate representations of time-varying signals in the auditory cortex of awake primates. Nat. Neurosci. 4 (2001) 1131
33. van Rossum M.C.W., Turrigiano G.G., and Nelson S.B. Fast propagation of firing rates through layered networks of noisy neurons. J. Neurosci. 22 (2002) 1956
34. Masuda N., and Aihara K. Bridging rate coding and temporal spike coding by effect of noise. Phys. Rev. Lett. 88 (2002) 248101
35. Masuda N., and Aihara K. Duality of rate coding and temporal spike coding in multilayered feedforward networks. Neural Comput. 15 (2003) 103
36. Tsuda I., Fujii H., Tadokoro S., Yasuoka T., and Yamaguti Y. Chaotic itinerancy as a mechanism of irregular changes between synchronization and desynchronization in a neural network. J. Integr. Neurosci. 3 (2004) 159
37. Y. Katori, N. Masuda, K. Aihara, Dynamic switching of neural codes in networks with gap junctions, Neural Netw. 19 (2006), in press.
38. Tsodyks M., Uziel A., and Markram H. Synchrony generation in recurrent networks with frequency-dependent synapses. J. Neurosci. 20 RC50 (2000) 1
39. Aviel Y., Mehring C., Abeles M., and Horn D. On embedding synfire chains in a balanced network. Neural Comput. 15 (2003) 1321
40. Mehring C., Hehl U., Kubo M., Diesmann M., and Aertsen A. Activity dynamics and propagation of synchronous spiking in locally connected random networks. Biol. Cybern. 88 (2003) 395
41. Vogels T.P., and Abbott L.F. Signal propagation and logic gating in networks of integrate-and-fire neurons. J. Neurosci. 25 (2005) 10786
42. Litvak V., Sompolinsky H., Segev I., and Abeles M. On the transmission of rate code in long feedforward networks with excitatory-inhibitory balance. J. Neurosci. 23 (2003) 3006
43. Stocks N.G. Suprathreshold stochastic resonance in multilevel threshold systems. Phys. Rev. Lett. 84 (2000) 2310
44. Hamaguchi K., and Aihara K. Quantitative information transfer through layers of spiking neurons connected by Mexican-hat-type connectigvity. Neurocomputing 58-60 (2004) 85
45. Hamaguchi K., Okada M., Yamana M., and Aihara K. Correlated firing in a feedforward network with Mexican-hat-type connectivity. Neural Comput. 17 (2005) 2034
46. Masuda N., and Aihara K. Dual coding and effects of global feedback in multilayered neural networks. Neurocomputing 58-60 (2004) 33
47. Kempter R., Gerstner W., and van Hemmen J.L. Hebbian learning and spiking neurons. Phys. Rev. E 59 (1999) 4498
48. Song S., and Abbott L.F. Cortical development and remapping through spike timing-dependent plasticity. Neuron 32 (2001) 339
49. Nadal J.-P., and Parga N. Nonlinear neurons in the low-noise limit: a factorial code maximizes information transfer. Network: Comput. Neural Syst. 5 (1994) 565
50. Bell A.J., and Sejnowski T.J. An information-maximization approach to blind separation and blind deconvolution. Neural Comput. 7 (1995) 1129
51. Toyoizumi T., Pfister J.-P., Aihara K., and Gerstner W. Generalized Bienenstock-Cooper-Munro rule for spiking neurons that maximizes information transmission. Proc. Natl. Acad. Sci. USA 102 (2005) 5239