Construction of Direction Selectivity through Local Energy Computations in Primary Visual Cortex

PLoS ONE

Volumn 8, Issue 3, 2013, Pages

  Lochmann, Timm ^a,c   Blanche, Timothy J ^b   Butts, Daniel A ^a  

^a University of Maryland   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL EXPERIMENT; ARTICLE; ARTIFICIAL NEURAL NETWORK; BRAIN DEPTH RECORDING; CAT; CELL INTERACTION; CELL TYPE; COMPLEX CELL; DIRECTION SELECTIVITY; LOCAL ENERGY COMPUTATION; MACACA; MALE; NERVE CELL STIMULATION; NONBIOLOGICAL MODEL; NONHUMAN; RECEPTIVE FIELD; SIMPLE CELL; SOMATOSENSORY SYSTEM; SPATIAL SUMMATION; SPATIOTEMPORAL ANALYSIS; SPIKE TRIGGERED COVARIANCE ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL MODEL; STIMULUS RESPONSE; STRIATE CORTEX; VISUAL STIMULATION; VISUAL THRESHOLD;

ANIMALS; MACACA; MALE; MODELS, NEUROLOGICAL; NEURONS; PHOTIC STIMULATION; REACTION TIME; SPACE PERCEPTION; VISUAL CORTEX;

EID: 84875015638     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0058666     Document Type: Article

References (68)

1. Van Essen DC, Anderson CH, Felleman DJ, (1992) Information processing in the primate visual system: an integrated systems perspective. Science 255: 419-423.
2. Ringach DL, Shapley RM, Hawken MJ, (2002) Orientation selectivity in macaque V1: diversity and laminar dependence. J Neurosci 22: 5639-5651.
3. Jia H, Rochefort NL, Chen X, Konnerth A, (2010) Dendritic organization of sensory input to cortical neurons in vivo. Nature 464: 1307-1312.
4. Rust NC, Stocker AA, (2010) Ambiguity and invariance: two fundamental challenges for visual processing. Curr Opin Neurobiol 20: 382-388.
5. Movshon JA, Newsome WT, (1996) Visual response properties of striate cortical neurons projecting to area MT in macaque monkeys. J Neurosci 16: 7733-7741.
6. Priebe NJ, Cassanello CR, Lisberger SG, (2003) The neural representation of speed in macaque area MT/V5. J Neurosci 23: 5650-5661.
7. Hubel DH, Wiesel TN, (1968) Receptive fields and functional architecture of monkey striate cortex. J Physiol 195: 215-243.
8. Adelson EH, Bergen JR, (1985) Spatiotemporal energy models for the perception of motion. J Opt Soc Am A 2: 284-299.
9. Carandini M, Demb JB, Mante V, Tolhurst DJ, Dan Y, et al. (2005) Do we know what the early visual system does? J Neurosci 25: 10577-10597.
10. Emerson RC, Bergen JR, Adelson EH, (1992) Directionally selective complex cells and the computation of motion energy in cat visual cortex. Vision Res 32: 203-218.
11. Peterson MR, Li B, Freeman RD, (2004) The derivation of direction selectivity in the striate cortex. J Neurosci 24: 3583-3591.
12. Jagadeesh B, Wheat HS, Kontsevich LL, Tyler CW, Ferster D, (1997) Direction selectivity of synaptic potentials in simple cells of the cat visual cortex. J Neurophysiol 78: 2772-2789.
13. Saul AB, Carras PL, Humphrey AL, (2005) Temporal properties of inputs to direction-selective neurons in monkey V1. J Neurophysiol 94: 282-294.
14. Touryan J, Lau B, Dan Y, (2002) Isolation of relevant visual features from random stimuli for cortical complex cells. J Neurosci 22: 10811-10818.
15. Rust NC, Schwartz O, Movshon JA, Simoncelli EP, (2005) Spatiotemporal elements of macaque V1 receptive fields. Neuron 46: 945-956.
16. Ahrens MB, Paninski L, Sahani M, (2008) Inferring input nonlinearities in neural encoding models. Network 19: 35-67.
17. Butts DA, Weng C, Jin J, Alonso J-M, Paninski L, (2011) Temporal precision in the visual pathway through the interplay of excitation and stimulus-driven suppression. J Neurosci 31: 11313-11327.
18. Ringach DL, (2002) Spatial structure and symmetry of simple-cell receptive fields in macaque primary visual cortex. J Neurophysiol 88: 455-463.
19. Reid RC, Victor JD, Shapley RM, (1997) The use of m-sequences in the analysis of visual neurons: linear receptive field properties. Vis Neurosci 14: 1015-1027.
20. DeAngelis GC, Ohzawa I, Freeman RD, (1993) Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. I. General characteristics and postnatal development. J Neurophysiol 69: 1091-1117.
21. Blanche TJ, Spacek M, Hetke JF, Swindale NV, (2005) Polytrodes: high-density silicon electrode arrays for large-scale multiunit recording. J Neurophysiol 93: 2987-3000.
22. Kayser C, Salazar RF, Konig P, (2003) Responses to natural scenes in cat V1. J Neurophysiol 90: 1910-1920.
23. Steveninck RDR V, Bialek W, (1988) Real-time performance of a movement-sensitive neuron in the blowfly visual system: Coding and information transfer in short spike sequences. Proc Royal Soc Lond B 234: 379-414.
24. Schwartz O, Pillow JW, Rust NC, Simoncelli EP, (2006) Spike-triggered neural characterization. J Vis 6: 484-507.
25. Pillow JW, Simoncelli EP, (2006) Dimensionality reduction in neural models: an information-theoretic generalization of spike-triggered average and covariance analysis. J Vis 6: 414-428.
26. Saleem AB, Krapp HG, Schultz SR, (2008) Receptive field characterization by spike-triggered independent component analysis. J Vis 8: 1-16.
27. Theunissen FE, David S V, Singh NC, Hsu A, Vinje WE, et al. (2001) Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli. Network 12: 289-316.
28. Touryan J, Felsen G, Dan Y, (2005) Spatial structure of complex cell receptive fields measured with natural images. Neuron 45: 781-791.
29. Park M, Pillow JW, (2011) Receptive field inference with localized priors. PLoS Comput Biol 7: e1002219.
30. Chichilnisky EJ, (2001) A simple white noise analysis of neuronal light responses. Network 12: 199-213.
31. Paninski L, (2004) Maximum likelihood estimation of cascade point-process neural encoding models. Network 15: 243-262.
32. Hastie T, Tibshirani R, (1986) Generalized additive models. Statistical Science 1: 297-310.
33. Gerwinn S, Macke J, Seeger M, Bethge M, (2008) Bayesian inference for spiking neuron models with a sparsity prior. NIPS 20 20: 1-8.
34. Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning: Data mining, inference, and prediction, second edition. Springer.
35. Priebe NJ, Ferster D, (2005) Direction selectivity of excitation and inhibition in simple cells of the cat primary visual cortex. Neuron 45: 133-145.
36. Jones JP, Palmer LA, (1987) The two-dimensional spatial structure of simple receptive fields in cat striate cortex. J Neurophysiol 58: 1187-1211.
37. Szulborski RG, Palmer LA, (1990) The two-dimensional spatial structure of nonlinear subunits in the receptive fields of complex cells. Vis Res 30: 249-254.
38. Bialek W, Van Steveninck RR de R (2005) Features and dimensions: Motion estimation in fly vision. http://arxiv.org/abs/q-bio/0505003.
39. Van Santen JP, Sperling G, (1985) Elaborated Reichardt detectors. J Opt Soc Am A 2: 300-321.
40. Hassenstein B, Reichardt W, (1956) Systemtheoretische Analyse der Zeit, Reihenfolgen, und Vorzeichenauswertung bei der Bewegungsperzepion des Rüsselkäfers Chlorophanus. Z. Naturforsch. Zeitschrift für Naturforschung 11b: 513-524.
41. Livingstone MS, (1998) Mechanisms of direction selectivity in macaque V1. Neuron 20: 509-526.
42. Finn IM, Priebe NJ, Ferster D, (2007) The emergence of contrast-invariant orientation tuning in simple cells of cat visual cortex. Neuron 54: 137-152.
43. Li Y, Van Hooser SD, Mazurek M, White LE, Fitzpatrick D, (2008) Experience with moving visual stimuli drives the early development of cortical direction selectivity. Nature 456: 952-956.
44. Cleland BG, Levick WR, (1974) Properties of rarely encountered types of ganglion cells in the cat's retina and an overall classification. J Neurophysiol 240: 457-492.
45. De Monasterio FM, Gouras P, (1975) Functional properties of ganglion cells of the rhesus monkey retina. J Neurophysiol 251: 167-195.
46. Euler T, Detwiler PB, Denk W, (2002) Directionally selective calcium signals in dendrites of starburst amacrine cells. Nature 418: 845-852.
47. Borst A, Haag J, Reiff DF, (2010) Fly motion vision. Ann Rev Neurosci 33: 49-70.
48. Chance FS, Nelson SB, Abbott LF, (1999) Complex cells as cortically amplified simple cells. Nat Neurosci 2: 277-282.
49. Wielaard J, Sajda P, (2006) Circuitry and the classification of simple and complex cells in V1. J Neurophysiol 96: 2739-2749.
50. Lauritzen TZ, Miller KD, (2003) Different roles for simple-cell and complex-cell inhibition in V1. J Neurosci 23: 10201-10213.
51. Alonso J-M, Martinez LM, (1998) Functional connectivity between simple cells and complex cells in cat striate cortex. Nat Neurosci 1: 395-403.
52. Martinez LM, Alonso J-M, (2003) Complex receptive fields in primary visual cortex. Neuroscientist 9: 317-331.
53. Mechler F, Ringach DL, (2002) On the classification of simple and complex cells. Vis Res 42: 1017-1033.
54. Reid RC, Alonso J-M, (1995) Specificity of monosynaptic connections from thalamus to visual cortex. Nature 378: 281-284.
55. Ko H, Hofer SB, Pichler B, Buchanan KA, Sjöström PJ, et al. (2011) Functional specificity of local synaptic connections in neocortical networks. Nature 473: 87-91.
56. Pillow JW, Shlens J, Paninski L, Sher A, Litke AM, et al. (2008) Spatio-temporal correlations and visual signalling in a complete neuronal population. Nature 454: 995-999.
57. Mante V, Carandini M, (2005) Mapping of stimulus energy in primary visual cortex. J Neurophysiol 94: 788-798.
58. Simoncelli EP, Heeger DJ, (1998) A model of neuronal responses in visual area MT. Vis Res 38: 743-761.
59. Nishimoto S, Gallant JL, (2011) A three-dimensional spatiotemporal receptive field model explains responses of area MT neurons to naturalistic movies. J Neurosci 31: 14551-14564.
60. Heess N, Bair W, (2010) Direction opponency, not quadrature, is key to the 1/4 cycle preference for apparent motion in the motion energy model. J Neurosci 30: 11300-11304.
61. Park I, Pillow J (2011) Bayesian spike-triggered covariance. NIPS 24. MIT Press. pp.1-9.
62. Vintch B, Movshon A, Simoncelli E (2012) Efficient and direct estimation of a neural subunit model for sensory coding. NIPS 25.
63. Fitzgerald JD, Rowekamp RJ, Sincich LC, Sharpee TO, (2011) Second order dimensionality reduction using minimum and maximum mutual information models. PLoS Comput Biol 7: e1002249.
64. Rad KR, Paninski L, (2010) Efficient, adaptive estimation of two-dimensional firing rate surfaces via Gaussian process methods. Network 21: 142-168.
65. Lau B, Stanley GB, Dan Y, (2002) Computational subunits of visual cortical neurons revealed by artificial neural networks. Proc Natl Acad Sci USA 99: 8974-8979.
66. Hornik K, Stinchcombe M, White H, (1989) Multilayer feedforward networks are universal approximators. Neural Networks 2: 359-366.
67. Freeman J, Field GD, LI PH, Greschner M, Jepson LH, et al. (2012) Characterizing the nonlinear subunits of primate retinal ganglion cells. Annual Meeting. Society for Neuroscience. p. 631.02.
68. McFarland J, Cui Y, Butts DA (2012) Describing sensory processing using a general nonlinear model structured to reflect rectified synaptic inputs. Annual Meeting. Society for Neuroscience. p. 631.07.