Spatiotemporal response properties of optic-flow processing neurons

Neuron

Volumn 67, Issue 4, 2010, Pages 629-642

  Weber, Franz ^a,c   Machens, Christian K ^b   Borst, Alexander ^a  

^a MAX PLANCK INSTITUTE OF NEUROBIOLOGY   (Germany)

^b ECOLE NORMALE SUPÉRIEURE   (France)

^c UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL CELL; ARTICLE; BIOPHYSICS; CELL DENSITY; CELL MOTION; CONTROLLED STUDY; DENDRITIC CELL; FLY; NERVE CELL; NERVE CELL EXCITABILITY; NERVE CELL MEMBRANE CONDUCTANCE; NERVE CELL NETWORK; NERVE CELL STIMULATION; NEUROMODULATION; NONHUMAN; OPTIC FLOW PROCESSING; PRESYNAPTIC NERVE; PRIORITY JOURNAL; RECEPTIVE FIELD; SYNAPTIC TRANSMISSION; VISUAL STIMULATION; ACTION POTENTIAL; ALGORITHM; ANIMAL; BIOLOGICAL MODEL; DENDRITE; DIPTERA; EVALUATION STUDY; MICROELECTRODE; MOTION; MOVEMENT PERCEPTION; NONLINEAR SYSTEM; PHOTOSTIMULATION; PHYSIOLOGY; STATISTICAL MODEL; TIME;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; DENDRITES; DIPTERA; LINEAR MODELS; MICROELECTRODES; MODELS, NEUROLOGICAL; MOTION; MOTION PERCEPTION; NEURONS; NONLINEAR DYNAMICS; PHOTIC STIMULATION; TIME FACTORS;

EID: 77955930961     PISSN: 08966273     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuron.2010.07.017     Document Type: Article

References (56)

1. Aertsen A.M., Johannesma P.I. The spectro-temporal receptive field. A functional characteristic of auditory neurons. Biol. Cybern. 1981, 42:133-143.
2. Ahrens M.B., Linden J.F., Sahani M. Nonlinearities and contextual influences in auditory cortical responses modeled with multilinear spectrotemporal methods. J. Neurosci. 2008, 28:1929-1942.
3. Baccus S.A., Meister M. Fast and slow contrast adaptation in retinal circuitry. Neuron 2002, 36:909-919.
4. Bernander O., Koch C., Douglas R.J. Amplification and linearization of distal synaptic input to cortical pyramidal cells. J. Neurophysiol. 1994, 72:2743-2753.
5. Bialek W., Rieke F., de Ruyter van Steveninck R.R., Warland D. Reading a neural code. Science 1991, 252:1854-1857.
6. Bishop C.M. Pattern Recognition and Machine Learning 2008, Springer, Berlin.
7. Borst A. Computation of olfactory signals in Drosophila melanogaster. J. Comp. Physiol. [A] 1983, 152:373-383.
8. Borst A. Noise, not stimulus entropy, determines neural information rate. J. Comput. Neurosci. 2003, 14:23-31.
9. Borst A., Haag J. The intrinsic electrophysiological characteristics of fly lobula plate tangential cells: I. Passive membrane properties. J. Comput. Neurosci. 1996, 3:313-336.
10. Borst A., Theunissen F.E. Information theory and neural coding. Nat. Neurosci. 1999, 2:947-957.
11. Borst A., Egelhaaf M., Haag J. Mechanisms of dendritic integration underlying gain control in fly motion-sensitive interneurons. J. Comput. Neurosci. 1995, 2:5-18.
12. Borst A., Flanagin V.L., Sompolinsky H. Adaptation without parameter change: Dynamic gain control in motion detection. Proc. Natl. Acad. Sci. USA 2005, 102:6172-6176.
13. Borst A., Haag J., Reiff D.F. Fly motion vision. Annu. Rev. Neurosci. 2010, 33:49-70.
14. Britten K.H. Mechanisms of self-motion perception. Annu. Rev. Neurosci. 2008, 31:389-410.
15. Carandini M., Heeger D.J. Summation and division by neurons in primate visual cortex. Science 1994, 264:1333-1336.
16. Chance F.S., Abbott L.F., Reyes A.D. Gain modulation from background synaptic input. Neuron 2002, 35:773-782.
17. Christianson G.B., Sahani M., Linden J.F. The consequences of response nonlinearities for interpretation of spectrotemporal receptive fields. J. Neurosci. 2008, 28:446-455.
18. David S.V., Vinje W.E., Gallant J.L. Natural stimulus statistics alter the receptive field structure of v1 neurons. J. Neurosci. 2004, 24:6991-7006.
19. Dayan P., Abbott L.F. Theoretical Neuroscience 2001, MIT Press, Cambridge, MA.
20. DeAngelis G.C., Ohzawa I., Freeman R.D. Receptive-field dynamics in the central visual pathways. Trends Neurosci. 1995, 18:451-458.
21. Duffy C.J., Wurtz R.H. Sensitivity of MST neurons to optic flow stimuli. I. A continuum of response selectivity to large-field stimuli. J. Neurophysiol. 1991, 65:1329-1345.
22. Duffy C.J., Wurtz R.H. Multiple temporal components of optic flow responses in MST neurons. Exp. Brain Res. 1997, 114:472-482.
23. Egelhaaf M., Borst A., Reichardt W. Computational structure of a biological motion-detection system as revealed by local detector analysis in the fly's nervous system. J. Opt. Soc. Am. A 1989, 6:1070-1087.
24. Fairhall A.L., Lewen G.D., Bialek W., de Ruyter Van Steveninck R.R. Efficiency and ambiguity in an adaptive neural code. Nature 2001, 412:787-792.
25. Felsen G., Touryan J., Han F., Dan Y. Cortical sensitivity to visual features in natural scenes. PLoS Biol. 2005, 3:e342.
26. Franz M.O., Krapp H.G. Wide-field, motion-sensitive neurons and matched filters for optic flow fields. Biol. Cybern. 2000, 83:185-197.
27. Grewe J., Matos N., Egelhaaf M., Warzecha A.-K. Implications of functionally different synaptic inputs for neuronal gain and computational properties of fly visual interneurons. J. Neurophysiol. 2006, 96:1838-1847.
28. Haag J., Borst A. Reciprocal inhibitory connections within a neural network for rotational optic-flow processing. Front. Neurosci. 2007, 1:111-121.
29. Hausen K. The lobula-complex of the fly: structure, function and significance in visual behavior. Photoreception and Vision in Invertebrates 1984, 523-559. Plenum Press, New York.
30. Holt G.R., Koch C. Shunting inhibition does not have a divisive effect on firing rates. Neural Comput. 1997, 9:1001-1013.
31. Koch C., Bernander O., Douglas R.J. Do neurons have a voltage or a current threshold for action potential initiation?. J. Comput. Neurosci. 1995, 2:63-82.
32. Krapp H.G., Hengstenberg R. Estimation of self-motion by optic flow processing in single visual interneurons. Nature 1996, 384:463-466.
33. Krapp H.G., Hengstenberg R., Egelhaaf M. Binocular contributions to optic flow processing in the fly visual system. J. Neurophysiol. 2001, 85:724-734.
34. Lesica N.A., Jin J., Weng C., Yeh C.I., Butts D.A., Stanley G.B., Alonso J.M. Adaptation to stimulus contrast and correlations during natural visual stimulation. Neuron 2007, 55:479-491.
35. Lindemann J.P., Kern R., van Hateren J.H., Ritter H., Egelhaaf M. On the computations analyzing natural optic flow: quantitative model analysis of the blowfly motion vision pathway. J. Neurosci. 2005, 25:6435-6448.
36. Linden J.F., Liu R.C., Sahani M., Schreiner C.E., Merzenich M.M. Spectrotemporal structure of receptive fields in areas AI and AAF of mouse auditory cortex. J. Neurophysiol. 2003, 90:2660-2675.
37. Machens C.K., Wehr M.S., Zador A.M. Linearity of cortical receptive fields measured with natural sounds. J. Neurosci. 2004, 24:1089-1100.
38. Maimon G., Straw A.D., Dickinson M.H. Active flight increases the gain of visual motion processing in Drosophila. Nat. Neurosci. 2010, 13:393-399.
39. Marmarelis P.Z., Marmarelis V.Z. Analysis of Physiological Systems: The White-Noise Approach 1978, Plenum Press, New York.
40. Olsen S.R., Bhandawat V., Wilson R.I. Divisive normalization in olfactory population codes. Neuron 2010, 66:287-299.
41. Paolini M., Distler C., Bremmer F., Lappe M., Hoffmann K.P. Responses to continuously changing optic flow in area MST. J. Neurophysiol. 2000, 84:730-743.
42. Pouille F., Marin-Burgin A., Adesnik H., Atallah B.V., Scanziani M. Input normalization by global feedforward inhibition expands cortical dynamic range. Nat. Neurosci. 2009, 12:1577-1585.
43. Reichardt W. Autocorrelation, a principle for the evaluation of sensory information by the central nervous system. Sensory Communication 1961, 303-317. MIT Press and John Wiley and Sons, New York, London.
44. Ringach D.L., Sapiro G., Shapley R. A subspace reverse-correlation technique for the study of visual neurons. Vision Res. 1997, 37:2455-2464.
45. Rust N.C., Mante V., Simoncelli E.P., Movshon J.A. How MT cells analyze the motion of visual patterns. Nat. Neurosci. 2006, 9:1421-1431.
46. Sahani M., Linden J.F. How linear are auditory cortical responses?. Advances in Neural Information Processing Systems 2003, 125-132. MIT Press, Cambridge, MA.
47. Schwartz O., Simoncelli E.P. Natural signal statistics and sensory gain control. Nat. Neurosci. 2001, 4:819-825.
48. Shapley R.M., Victor J.D. The effect of contrast on the transfer properties of cat retinal ganglion cells. J. Physiol. 1978, 285:275-298.
49. Sharpee T.O., Sugihara H., Kurgansky A.V., Rebrik S.P., Stryker M.P., Miller K.D. Adaptive filtering enhances information transmission in visual cortex. Nature 2006, 439:936-942.
50. Single S., Borst A. Dendritic integration and its role in computing image velocity. Science 1998, 281:1848-1850.
51. Single S., Haag J., Borst A. Dendritic computation of direction selectivity and gain control in visual interneurons. J. Neurosci. 1997, 17:6023-6030.
52. Theunissen F.E., David S.V., Singh N.C., Hsu A., Vinje W.E., Gallant J.L. Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli. Network 2001, 12:289-316.
53. Wark B., Lundstrom B.N., Fairhall A. Sensory adaptation. Curr. Opin. Neurobiol. 2007, 17:423-429.
54. Wertz A., Haag J., Borst A. Local and global motion preferences in descending neurons of the fly. J. Comp. Physiol. A Neuroethol. Sens. Neural. Behav. Physiol. 2009, 195:1107-1120.
55. Wu M.C.-K., David S.V., Gallant J.L. Complete functional characterization of sensory neurons by system identification. Annu. Rev. Neurosci. 2006, 29:477-505.
56. Wylie D.R., Bischof W.F., Frost B.J. Common reference frame for neural coding of translational and rotational optic flow. Nature 1998, 392:278-282.