Information theory in neuroscience

Journal of Computational Neuroscience

Volumn 30, Issue 1, 2011, Pages 1-5

  Dimitrov, Alexander G ^a   Lazar, Aurel A ^b   Victor, Jonathan D ^c  

^a WASHINGTON STATE UNIVERSITY   (United States)

^b Columbia University ^*  (United States)

^c WEILL CORNELL MEDICAL COLLEGE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

NEUROLOGY;

BRAIN FUNCTION; BRAIN REGION; INFORMATION PROCESSING; INFORMATION SCIENCE; MAGNETOENCEPHALOGRAPHY; MATHEMATICAL COMPUTING; MOTOR PERFORMANCE; NERVE CELL NETWORK; NERVE CONDUCTION; NEUROANATOMY; NEUROSCIENCE; PRIORITY JOURNAL; PROCESS DEVELOPMENT; PUBLICATION; REVIEW; SYSTEMS BIOLOGY;

EID: 79151486126     PISSN: 09295313     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10827-011-0314-3     Document Type: Review

References (76)

1. M Abeles Y Lass 1975 Transmission of information by the axon: II. The channel capacity Biological Cybernetics 19 121 125 1:STN:280: DyaE28%2FhvFamsA%3D%3D 10.1007/BF00337250 1174580
2. Amblard, P.-O.; & Michel, O. (2011). On directed information theory and granger causality graphs. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0231-x.
3. JJ Atick AN Redlich 1990 Towards a theory of early visual processing Neural Computation 2 308 320 10.1162/neco.1990.2.3.308
4. F Attneave 1954 Some information aspects of visual perception Psychological Review 61 183 193 1:STN:280:DyaG2c%2Foslalug%3D%3D 10.1037/h0054663 13167245
5. Barlow, H. B. (1961). Possible princilples underlying the transformation of sensory messages. In W. A. Rosenblith (Ed.), Sensory communications. MIT Press, Cambridge, MA.
6. AG Carlton 1969 On the bias of information estimates Psychological Bulletin 71 108 109 10.1037/h0026857
7. R de Ruyter van Steveninck W Bialek 1988 Real-time performance of a movement-sensitive neuron in the blowfly visual system: Coding and information transfer in short spike sequences Proceedings of the Royal Society Series B, Biological Sciences 234 379 414 10.1098/rspb.1988.0055
8. Dimitrov, A. G.; Cummins, G. I.; Baker, A.; & Aldworth, Z. N. (2011). Characterizing the fine structure of a neural sensory code through information distortion. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0261- 4.
9. AG Dimitrov JP Miller 2001 Neural coding and decoding: Communication channels and quantization Network: Computation in Neural Systems 12 441 472 1:STN:280:DC%2BD38%2FjsVCltg%3D%3D (Pubitemid 33625157)
10. JP Eagles RL Purple 1974 Afferent fibers with multiple encoding sites Brain Research 77 2 187 193 1:STN:280:DyaE2c3psl2qsA%3D%3D 10.1016/0006-8993(74) 90783-5 4850455
11. R Eckhorn OJ Grüsser J Kröller K Pellnitz B Pöpel 1976 Efficiency of different neuronal codes: Information transfer calculations for three different neuronal systems Biological Cybernetics 22 49 60 1:STN:280:DyaE287js1Grtw%3D%3D 10.1007/BF00340232 175859
12. R Eckhorn B Pöpel 1974 Rigorous and extended application of information theory to the afferent visual system of the cat. I. Basic conceptsfferent visual system of the cat. I. Basic concepts Biological Cybernetics 16 191 200 1:STN:280:DyaE2M7ntlaqsg%3D%3D
13. R Eckhorn B Pöpel 1981 Responses of cat retinal ganglion cells to the random motion of a spot stimulus Vision Research 21 4 435 443 1:STN:280:DyaL3M3nslSmsg%3D%3D 10.1016/0042-6989(81)90090-0 7269323 (Pubitemid 11139927)
14. R Eckhorn H Querfurth 1985 Information transmission by isolated frog muscle spindle Biological Cybernetics 52 165 176 1:STN:280:DyaL2M3otVKitg%3D%3D 2992613 (Pubitemid 15007507)
15. MS Fuller WJ Williams 1983 A continuous information theoretic approach to the analysis of cutaneous receptor neurons Biological Cybernetics 47 13 16 1:STN:280:DyaL3s3lslCgtA%3D%3D 6871281 (Pubitemid 13027638)
16. Gersho, A.; & Gray, R. M. (1991). Vector Quantization and Signal Compression. Series in Engineering and Computer Science. Kluwer International.
17. Gillespie, J. B.; & Houghton, C. (2011). A metric space approach to the information channel capacity of spike trains. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0286-8.
18. C Granger 1969 Investigating causal relations by econometric models and cross-spectral methods Econometrica 37 3 424 438 10.2307/1912791
19. R Harvey 1978 Patterns of output firing generated by a many-input neuronal model for different model parameters and patterns of synaptic drive Brain Research 150 2 259 276 1:STN:280:DyaE1c3js1Kjtw%3D%3D 10.1016/0006- 8993(78)90279-2 678971 (Pubitemid 8374920)
20. M Kennel J Shlens H Abarbanel EJ Chichilnisky 2005 Estimating entropy rates with bayesian confidence intervals Neural Computation 17 1531 1576 10.1162/0899766053723050 15901407 (Pubitemid 40669911)
21. Kim, A. J.; Lazar, A. A.; & Slutskiy, Y. B. (2011). System identification of drosophila olfactory sensory neurons. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0265-0.
22. TW Kjaer JA Hertz BJ Richmond 1994 Decoding cortical neuronal signals: Network models, information estimation and spatial tuning Journal of Computational Neuroscience 1 1-2 109 139 1:STN:280:DyaK28zosVensg%3D%3D 10.1007/BF00962721 8792228
23. Y Lass M Abeles 1975 Transmission of information by the axon: I. Noise and memory in the myelinated nerve fiber of the frog Biological Cybernetics 19 61 67 1:STN:280:DyaE28%2Fmt1Krtw%3D%3D 10.1007/BF00364102 172162
24. AA Lazar 2004 Time encoding with an integrate-and-fire neuron with a refractory period Neurocomputing 58-60 53 58 10.1016/j.neucom.2004.01.022 (Pubitemid 38684257)
25. AA Lazar 2010 Population encoding with Hodgkin-Huxley neurons IEEE Transactions on Information Theory, Special Issue on Molecular Biology and Neuroscience 56 2 821 837
26. AA Lazar EA Pnevmatikakis 2008 Faithful representation of stimuli with a population of integrate-and-fire neurons Neural Computation 20 11 2715 2744 10.1162/neco.2008.06-07-559 18533815
27. AA Lazar EA Pnevmatikakis Y Zhou 2010 Encoding natural scenes with neural circuits with random thresholds Vision Research, Special Issue on Mathematical Models of Visual Coding 50 22 2200 2212
28. R Lestienne BL Strehler 1987 Time structure and stimulus dependence of precisely replicating patterns present in monkey cortical neuronal spike trains Brain Research 437 2 214 238 1:STN:280:DyaL1c7jsFeitg%3D%3D 10.1016/0006- 8993(87)91638-6 3435837 (Pubitemid 18016210)
29. R Lestienne B Strehler 1988 Differences between monkey visual cortex cells in triplet and ghost doublet informational symbols relationships Biological Cybernetics 59 337 352 1:STN:280:DyaL1M%2Fmt1Gkug%3D%3D 10.1007/BF00332924 3196778
30. Lewi, J.; Schneider, D.; Woolley, S.; & Paninski, L. (2011). Automating the design of informative sequences of sensory stimuli. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0248-1.
31. Lizier, J.; Heinzle, J.; Horstmann, A.; Haynes, J.-D.; & Prokopenko, M. (2011). Multivariate information-theoretic measures reveal directed information structure and task relevant changes in fMRI connectivity. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0271-2.
32. CK Machens 2002 Adaptive sampling by information maximization Physical Review Letters 88 22 228104(4) 10.1103/PhysRevLett.88.228104
33. DM MacKay WS McCulloch 1952 The limiting information capacity of a neuronal link Bulletin of Mathematical Biophysics 14 127 135 10.1007/BF02477711
34. Massey, J. (1990). Causality, feedback and directed information. In Proc. Intl. Symp. Information Theory Applications (ISITA-90) (pp. 303-305).
35. Massey, J.; & Massey, P. (2005). Conservation of mutual and directed information. In Proc. Intl. Symp. Information Theory (ISIT 2005) (pp. 157-158). (Pubitemid 44508181)
36. McCulloch, W. S. (1952). An upper bound on the informational capacity of a synapse. In Proceedings of the 1952 ACM national meeting, Pittsburgh, Pensilvania.
37. Merolla, P. A.; & Boahen, K. (2006). Dynamic computation in a recurrent network of heterogeneous silicon neurons. In IEEE International Symposium on Circuits and Systems (pp. 4539-4542). IEEE Press. (Pubitemid 47132565)
38. O Milenkovic G Alterovitz G Battail TP Coleman J Hagenauer SP Meyn, et al. 2010 Introduction to the special issue on information theory in molecular biology and neuroscience IEEE Transactions on Information Theory 56 2 649 652 10.1109/TIT.2009.2036971
39. Miller, G. A. (1955). Note on the bias of information estimates. In Information Theory in Psychology: Problems and Methods (Vol. II-B, pp. 95-100). Free Press.
40. I Nemenman W Bialek R de Ruyter van Steveninck 2004 Entropy and information in neural spike trains: Progress on the sampling problem Physical Review Letters 69 056111
41. Neymotin, S. A.; Jacobs, K. M.; Fenton, A. A.; & Lytton, W. W. (2011). Synaptic information transfer in computer models of neocortical columns. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0253-4.
42. S Nirenberg JD Victor 2007 Analyzing the activity of large populations of neurons-How tractable is the problem? Current Opinion in Neurobiology 17 397 400 1:CAS:528:DC%2BD2sXhtFGrsL%2FP 10.1016/j.conb.2007.07.002 17709240 (Pubitemid 47531946)
43. K Norwich 1977 On the information received by sensory receptors Bulletin of Mathematical Biology 39 453 461 1:STN:280:DyaE2s3it1Omsg%3D%3D 880410 (Pubitemid 8136526)
44. IE Ohiorhenuan F Mechler KP Purpura AM Schmidt JD Victor 2010 Sparse coding and high-order correlations in fine-scale cortical networks Nature 466 617 621 1:CAS:528:DC%2BC3cXotlWku7c%3D 10.1038/nature09178 20601940
45. Ohiorhenuan, I. E.; & Victor, J. D. (2011). Information geometric measure of 3-neuron firing patterns characterizes scale-dependence in cortical networks. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0257-0.
46. LM Optican BJ Richmond 1987 Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. III. Information theoretic analysis Journal of Neurophysiology 57 163 178
47. L Paninski 2003 Estimation of entropy and mutual information Neural Computation 15 1191 1253 10.1162/089976603321780272 (Pubitemid 37049793)
48. L Paninski 2005 Asymptotic theory of information-theoretic experimental design Neural Computation 17 1480 1507 10.1162/0899766053723032 15901405 (Pubitemid 40678197)
49. DJM Poussart 1971 Membrane current noise in lobster axon under voltage clamp Biophysical Journal 11 2 211 234 1:CAS:528:DyaE3MXhtV2hurk%3D 10.1016/S0006-3495(71)86209-4 5542614
50. Quinn, C. J.; Coleman, T. P.; Kiyavash, N.; & Hatsopoulos, N. G. (2011). Estimating the directed information to infer causal relationships in ensemble neural spike train recordings. Journal of Computational Neuroscience.. doi: 10.1007/s10827-010-0247-2.
51. A Rapoport WJ Horvath 1960 The theoretical channel capacity of a single neuron as determined by various coding systems Information and Control 3 4 335 350 10.1016/S0019-9958(60)90917-7
52. I Samengo 2002 Information loss in an optimal maximum likelihood decoding Neural Computation 14 771 779 10.1162/089976602317318947 11936960
53. E Schneidman MJ Berry II R Segev W Bialek 2006 Weak pairwise correlations imply strongly correlated network states in a neural population Nature 440 1007 1012 1:CAS:528:DC%2BD28Xjs1agtL8%3D 10.1038/nature04701 16625187
54. T Schreiber 2000 Measuring information transfer Physical Review Letters 85 2 461 464 1:CAS:528:DC%2BD3cXks1ersL4%3D 10.1103/PhysRevLett.85.461 10991308
55. CE Shannon 1948 A mathematical theory of communication Bell System Technical Journal 27 623 656
56. CE Shannon 1956 The bandwagon IRE Transactions in Information Theory 2 1 3 10.1109/TIT.1956.1056774
57. Shannon, C. E.; & McCarthy, J. (Eds.) (1956). Automata studies. In Annals of mathematics studies (Vol. 34). Princeton University Press.
58. J Shlens DG Field JL Gauthier M Greschner A Sher AM Litke, et al. 2009 The structure of large-scale synchronized firing in primate retina Journal of Neuroscience 29 5022 5031 1:CAS:528:DC%2BD1MXltFShsbs%3D 10.1523/JNEUROSCI.5187- 08.2009 19369571
59. J Shlens DG Field LJ Gauthier MI Grivich D Petrusca A Sher, et al. 2006 The structure of multi-neuron firing patterns in primate retina Journal of Neuroscience 26 8254 8266 1:CAS:528:DC%2BD28Xos1Kjtbc%3D 10.1523/JNEUROSCI.1282- 06.2006 16899720 (Pubitemid 44309839)
60. L Stark J Negrete-Martinze G Yankelevich G Theodoridis 1969 Experiments on information coding in nerve impulse trains Mathematical Biosciences 4 3-4 451 485 10.1016/0025-5564(69)90024-8
61. RB Stein 1967 The information capacity of nerve cells using a frequency code Biophysical Journal 7 6 797 826 1:STN:280:DC%2BD1M7jsFGrtg%3D%3D 10.1016/S0006-3495(67)86623-2 19210999
62. RB Stein AS French AV Holden 1972 The frequency response, coherence, and information capacity of two neuronal models Biophysical Journal 12 3 295 322 1:STN:280:DyaE387ltlWlug%3D%3D 10.1016/S0006-3495(72)86087-9 5016114
63. SP Strong R Koberle R de Ruyter van Steveninck W Bialek 1998 Entropy and information in neural spike trains Physical Review Letters 80 1 197 200 1:CAS:528:DyaK1cXislOjsQ%3D%3D 10.1103/PhysRevLett.80.197 (Pubitemid 128621483)
64. DJ Surmeier RJ Weinberg 1985 The relationship between cross-correlation measures and underlying synaptic events Brain Research 331 1 180 184 1:STN:280:DyaL2M7ns1Skuw%3D%3D 10.1016/0006-8993(85)90732-2 2985197 (Pubitemid 15115379)
65. RC Taylor 1975 Integration in the crayfish antennal neuropile: Topographic representation and multiple-channel coding of mechanoreceptive submodalities Developmental Neurobiology 6 5 475 499 1:STN:280: DyaE28%2Fis1KhsA%3D%3D
66. Tishby, N.; Pereira, F.; & Bialek, W. (1999). The information bottleneck method. In Proceedings of The 37th annual Allerton conference on communication, control and computing. University of Illinios.
67. A Treves S Panzeri 1995 The upward bias in measures of information derived from limited data samples Neural Computation 7 399 440 10.1162/neco.1995.7.2.399
68. M Tsukada T Aihara G Hauske 1984 Redundancy reducing processes in single neurons Biological Cybernetics 50 157 165 1:STN:280:DyaL2c3otFWhug%3D%3D 10.1007/BF00340023 6087932 (Pubitemid 14051974)
69. E Tzanakou R Michalak E Harth 1979 The alopex process: Visual receptive fields by response feedback Biological Cybernetics 35 161-174 161 174 1:STN:280:DyaL3c%2FovVCmtQ%3D%3D 10.1007/BF00337061 518937 (Pubitemid 10175678)
70. Vanni, S.; & Rosenström, T. (2011). Local non-linear interactions in the visual cortex may reflect global decorrelation. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0239-2.
71. Vicente, R.; Wibral, M.; Lindner, M.; & Pipa, G. (2011). Transfer entropy-A model-free measure of effective connectivity for the neurosciences. Journal of Computational Neuroscience. doi: 10.1007/s10827-010-0262-3.
72. JD Victor 2002 Binless strategies for estimation of information from neural data Physical Review E 66 051903 10.1103/PhysRevE.66.051903 (Pubitemid 40618506)
73. JD Victor PM Johanessma 1986 Maximum-entropy approximations of stochastic nonlinear transductions: An extension of the wiener theory Biological Cybernetics 54 289 300 1:STN:280:DyaL283ps1yntA%3D%3D 10.1007/BF00318425 3741900
74. L Walloe 1970 On the transmission of information through sensory neurons Biophysical Journal 10 8 745 763 1:STN:280:DyaE3M%2FisFWmtQ%3D%3D 10.1016/S0006-3495(70)86333-0 5475732
75. G Werner VB Mountcastle 1965 Neural activity in mechanoreceptive cutaneous afferents: Stimulus-response relations, weber functions, and information transmission Journal of Neurophysiolgy 28 359 397 1:STN:280:DyaF2M%2FoslKgtg%3D%3D
76. Winograd, S.; & Cowan, J. D. (1963). Reliable computation in the presence of noise. The MIT Press.