Decoding spike trains instant by instant using order statistics and the mixture-of-poissons model

Journal of Neuroscience

Volumn 23, Issue 6, 2003, Pages 2394-2406

  Wiener, Matthew C ^a,b   Richmond, Barry J ^a  

^a NATIONAL INSTITUTE OF MENTAL HEALTH   (United States)

^b MERCK RESEARCH LABORATORIES   (United States)

Author keywords

Coding; Information; Modeling; Statistics; Timing; Visual cortex

Indexed keywords

ARTICLE; DATA ANALYSIS; INFORMATION PROCESSING; MODEL; MONKEY; POISSON DISTRIBUTION; PRIORITY JOURNAL; SPIKE WAVE; STATISTICAL ANALYSIS; STATISTICAL MODEL; STIMULUS RESPONSE; STOCHASTIC MODEL; VISUAL CORTEX;

EID: 0037444559     PISSN: 02706474     EISSN: None     Source Type: Journal    
DOI: 10.1523/jneurosci.23-06-02394.2003     Document Type: Article

References (37)

1. Arnold BC, Balakrishnan N, Nagaraja HN (1992) A first course in order statistics. New York: Wiley.
2. Baddeley R, Abbott LF, Booth MCA, Sengpiel F, Freeman T, Wakeman EA, Rolls ET (1997) Responses of neurons in primary and inferior temporal visual cortices to natural scenes. Proc R Soc Lond B Biol Sci 264:1775-1783.
3. Baker SN, Lemon RN (2000) Precise spatiotemporal repeating patterns in monkey primary and supplementary motor areas occur at chance levels. J Neurophysiol 84:1770-1780.
4. Barbieri R, Quirk MC, Frank LM, Wilson MA, Brown EN (2001) Construction and analysis of non-Poisson stimulus-response models of neural spiking activity. J Neurosci Methods 105:25-37.
5. Brown EN, Frank LM, Tang D, Quirk MC, Wilson MA (1998) A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cells. J Neurosci 18:7411-7425.
6. Brown EN, Barbieri R, Ventura V, Kass RE, Frank LM (2002) The time-rescaling theorem and its application to neural spike train data analysis. Neural Comput 14:325-346.
7. Cover TM, Thomas JA (1991) Elements of information theory. New York: Wiley.
8. Craven P, Wahba G (1979) Smoothing noisy data with spline functions. Numerische Mathematik 31:377-403.
9. Gabbiani F, Koch C (1996) Coding of time-varying signals in spike trains of integrate-and-fire neurons with random threshold. Neural Comput 8:44-66.
10. Gershon ED, Wiener MC, Latham PE, Richmond BJ (1998) Coding strategies in monkey V1 and inferior temporal cortices. J Neurophysiol 79:1135-1144.
11. Golomb D, Hertz J, Panzeri S, Treves A, Richmond BJ (1997) How well can we estimate the information carried in neuronal responses from limited samples? Neural Comput 9:649-665.
12. Greschner M, Bongard M, Rujan P, Ammermuller J (2002) Retinal ganglion cell synchronization by fixational eye movements improves feature estimation. Nat Neurosci 5:341-347.
13. Huang X, Paradiso MA (2000) Stimulus structure and expectation reflected in the delayed responses of macaque V1 neurons. Soc Neurosci Abstr 26:559.
14. Ihaka R, Gentleman R (1996) R: a language for data analysis and graphics. J Comput Graphical Stat 5:299-314.
15. Kass RE, Ventura V (2001) A spike-train probability model. Neural Comput 13:1713-1720.
16. Kjaer TW, Gawne TJ, Hertz JA, Richmond BJ (1997) Insensitivity of V1 complex cells to small shifts in the retinal image of complex patterns. J Neurophysiol 78:3187-3197.
17. Lansky P, Vaillant J (2000) Stochastic model of the overdispersion in the place cell discharge. Biosystems 58:27-32.
18. Lansky P, Fenton AA, Vaillant J (2001) The overdispersion in activity of place cells, Neurocomputing 38:1393-1399.
19. Loader C (1999) Local regression and likelihood. New York: Springer.
20. Manwani A, Steinmetz PN, Koch C (2001) The impact of spike timing variability on the signal-encoding performance of neural spiking models. Neural Comput 14:347-367.
21. Nirenberg S, Carcieri SM, Jacobs AL, Latham PE (2001) Retinal ganglion cells act largely as independent encoders. Nature 411:698-701.
22. Oram MW, Wiener MC, Lestienne R, Richmond BJ (1999) The stochastic nature of precisely timed spike patterns in visual system neuronal responses. J Neurophysiol 81:3021-3033.
23. Oram MW, Hatsopoulos NG, Richmond BI, Donoghue JP (2001) Synchrony in motor cortical neurons provides direction information that is redundant with the information from coarse temporal response measures. J Neurophysiol 86:1700-1716.
24. Panzeri S, Treves A (1996) Analytical estimates of limited sampling biases in different information measures. Network 7:87-107.
25. Reich DS, Mechler F, Victor JD (2001) Formal and attribute-specific information in primary visual cortex. J Neurophysiol 85:305-318.
26. Reinagel P, Reid RC (2000) Temporal coding of visual information in the thalamus. J Neurosci 20:5392-5400.
27. Rieke F, Warland D, de Ruyter van Steveninck RR, Bialek W (1997) Spikes: a Bradford book. Cambridge, MA: MIT.
28. Schwartz AB, Moran DW (2000) Arm trajectory and representation of movement processing in motor cortical activity. Eur J Neurosci 12:1851-1856.
29. Serruya MD, Hatsopoulos NG, Paninski L, Fellows MR, Donoghue JP (2002) Brain-machine interface: instant neural control of a movement signal. Nature 416:141-142.
30. Shannon CE, Weaver W (1949) The mathematical theory of communication. Urbana, IL: University of Illinois.
31. Sobotka S, Ringo JL (1997) Saccadic eye movements, even in darkness, generate event-related potentials recorded in medial sputum and medial temporal cortex. Brain Res 756:168-173.
32. Sobotka S, Nowicka A, Ringo JL (1997) Activity linked to externally cued saccades in single units recorded from hippocampal, parahippocampal, and inferotemporal areas of macaques. J Neurophysiol 78:2156-2163.
33. Strong SP, Koberle R, van Steveninck RDR, Bialek W (1998) Entropy and information in neural spike trains. Phys Rev Lett 80:197-200.
34. Wessberg J, Stambaugh CR, Kralik JD, Beck PD, Laubach M, Chapin JK, Kim J, Biggs SJ, Srinivisan MA, Nicolelis MAL (2000) Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature 408:361-365.
35. Wiener MC, Richmond BJ (1998) Using response models to study coding strategies in monkey visual cortex. Biosystems 48:279-286.
36. Wiener MC, Richmond BJ (1999) Using response models to estimate channel capacity for neuronal classification of stationary visual stimuli using temporal coding. J Neurophysiol 82:2861-2875.
37. Wiener MC, Oram MW, Liu Z, Richmond BJ (2001) Consistency of encoding in monkey visual cortex. J Neurosci 21:8210-8221.