Dejittered spike-conditioned stimulus waveforms yield improved estimates of neuronal feature selectivity and spike-timing precision of sensory interneurons

Journal of Neuroscience

Volumn 25, Issue 22, 2005, Pages 5323-5332

  Aldworth, Zane N ^a   Miller, John P ^a   Gedeon, Tomás ^a   Cummins, Graham I ^a   Dimitrov, Alexander G ^a  

^a MONTANA STATE UNIVERSITY   (United States)

Author keywords

Information theory; Interneuron; Mechanosensory; Receptive field; Response; Temporal coding

Indexed keywords

ACCURACY; ACTION POTENTIAL; ALGORITHM; ARTICLE; CALCULATION; FEMALE; INSECT; INTERNEURON; LATENT PERIOD; NONHUMAN; PRIORITY JOURNAL; RECEPTIVE FIELD; SENSORY NERVE CELL; SPIKE; STIMULUS; TECHNIQUE; WAVEFORM;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; FEMALE; GANGLIA, INVERTEBRATE; GRYLLIDAE; INFORMATION THEORY; INTERNEURONS; NEURONS, AFFERENT; PHYSICAL STIMULATION; REACTION TIME;

EID: 20044370450     PISSN: 02706474     EISSN: None     Source Type: Journal    
DOI: 10.1523/JNEUROSCI.0359-05.2005     Document Type: Article

References (33)

1. Bacon JP, Murphey RK (1984) Receptive fields of cricket (Acheta domesticus) are determined by their dendritic structure. J Physiol (Lond) 352:601-613.
2. Berry MJ, Warland DK, Meister M (1997) The structure and precision of retinal spike trains. Proc Natl Acad Sci USA 94:5411-5416.
3. Borst A, Theunissen FE (1999) Information theory and neural coding. Nat Neurosci 2:947-957.
4. Bryant HL, Segundo JP (1976) Spike initiation by transmembrane current: a white-noise analysis. J Physiol (Lond) 260:279-314.
5. Bryant HL, Marcos AR, Segundo JP (1973) Correlations of neuronal spike discharges produced by monosynaptic connections and by common inputs. J Neurophysiol 36:205-225.
6. Buracas GT, Zador AM, DeWeese MR, Albright TD (1998) Efficient discrimination of temporal patterns by motion-sensitive neurons in primate visual cortex. Neuron 20:959-969.
7. Chichilnisky EJ, Kalmar R (2003) Temporal resolution of ensemble visual motion signals in primate retina. J Neurosci 23:6681-6689.
8. Dimitrov AG, Miller JP, Gedeon T, Aldworth Z, Parker AE (2003) Analysis of neural coding using quantization with an information-based distortion measure. Network 14:151-176.
9. Duda RO, Hart PE, Stork DG (2000) Pattern classification, Chap 10, Ed 2. New York: Wiley.
10. Gnatzy W, Heusslein R (1986) Digger wasp against crickets. I. Receptors involved in the antipredator strategies of the prey. Naturwissenschaften 73:212-215.
11. Hsu A, Borst A, Theunissen FE (2004) Quantifying variability in neural responses and its application for the validation of model predictions. Network 15:91-109.
12. Jacobs GA, Murphey RK (1987) Segmental origins of the cricket giant interneuron system. J Comp Neurol 265:145-157.
13. Kämper G, Kleindienst H-U (1990) Oscillation of cricket sensory hairs in a low-frequency sound field. J Comp Physiol [A] 167:193-200.
14. Keat J, Reinagel P, Reid RC, Meister M (2001) Predicting every spike: a model for the responses of visual neurons. Neuron 30:803-817.
15. Kennel M, Shlens J, Abarbanel HDI, Chichilnisky EJ (2005) Estimating entropy rates with Bayesian confidence intervals. Neural Comp, in press.
16. Liu RC, Tzonev S, Rebrik S, Miller KD (2001) Variability and information in a neural code of the cat lateral geniculate nucleus. J Neurophysiol 86:2789-2806.
17. Mainen ZF, Sejnowski TJ (1995) Reliability of spike timing in neocortical neurons. Science 268:1503-1506.
18. Maršálek P, Koch C, Maunsell J (1997) On the relationship between synaptic input and spike output jitter in individual neurons. Proc Natl Acad Sci USA 94:735-740.
19. Miller JP, Theunissen FE, Jacobs GA (1991) Representation of sensory information in the cricket cereal sensory system. I. Response properties of the primary interneurons. J Neurophysiol 66:1680-1689.
20. O'Shea M, Adams ME (1981) Pentapetide (proctolin) associated with an identified neuron. Science 213:576-569.
21. Palka J, Levine R, Schubiger M (1977) The cercus-to-giant interneuron system of crickets. I. Some aspects of the sensory cells. J Comp Physiol 119:267-283.
22. Paninski L (2003) Estimation of entropy and mutual information. Neural Comput 15:1191-1253.
23. Reich DS, Victor JD, Knight BW, Ozaki T, Kaplan E (1997) Response variability and timing precision of neuronal spike trains in vivo. J Neurophysiol 77:2836-2841.
24. Reinagel P, Reid RC (2000) Temporal coding of visual information in the thalamus. J Neurosci 20:5392-5400.
25. Rieke F, Warland D, de Ruyter van Steveninck R, Bialek W (1997) Spikes: exploring the neural code, Chap 2. Boston: MIT.
26. Roddey JC, Girish B, Miller JP (2000) Assessing the performance of neural encoding models in the presence of noise. J Comput Neurosci 8:95-112.
27. Strong SP, Koberle R, de Ruyter van Steveninck RR, Bialek W (1998) Entropy and information in neural spike trains. Phys Rev Lett 80:197-200.
28. Theunissen F, Miller JP (1995) Temporal encoding in nervous systems: a rigorous definition. J Comput Neurosci 2:149-162.
29. Theunissen FE, Roddey JC, Stufflebeam S, Clague H, Miller JP (1996) Information theoretical analysis of dynamical encoding by four identified primary sensory interneurons in the cricket cereal system. J Neurophysiol 75:1345-1364.
30. Theunissen FE, David SV, Singh NC, Hsu A, Vinje WE, Gallant JL (2001) Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli. Network 12:289-316.
31. Uzzell VJ, Chichilnisky EJ (2004) Precision of spike trains in primate retinal ganglion cells. J Neurophysiol 92:780-789.
32. Victor JD, Purpura KP (1996) Nature and precision of temporal coding in visual cortex: a metric-space analysis. J Neurophysiol 76:1310-1326.
33. Zoccolan D, Pinato G, Torre V (2002) Highly variable spike trains underlie reproducible sensorimotor responses in the medicinal leech. J Neurosci 22:10790-10800.