Cellular and circuit mechanisms maintain low spike co-variability and enhance population coding in somatosensory cortex

Frontiers in Computational Neuroscience

Volumn , Issue JANUARY 2012, 2012, Pages

  Ly, Cheng ^a   Middleton, Jason W ^a,b   Doiron, Brent D ^a  

^a UNIVERSITY OF PITTSBURGH   (United States)

^b UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

Author keywords

Fisher information; Layer 2 3 somatosensory cortex; Noise correlation; Whisker stimulation

Indexed keywords

CELL CULTURE; CELL PROLIFERATION; COMPUTATION THEORY; FISHER INFORMATION MATRIX; TIMING CIRCUITS; VELOCITY;

COMPUTATIONAL TECHNIQUE; FEEDFORWARD INHIBITION; FISHER INFORMATION; NOISE CORRELATION; POPULATION VARIABILITY; SOMATOSENSORY CORTEX; TRIAL-TO-TRIAL VARIABILITIES; WHISKER STIMULATION;

CELLS;

ANALYTIC METHOD; ANIMAL CELL; ANIMAL EXPERIMENT; ARTICLE; BRAIN CELL; CALCULATION; CELL POPULATION; CONTROLLED STUDY; FEMALE; LEAKY INTEGRATE AND FIRE MODEL; MEMBRANE POTENTIAL; NEOCORTEX; NERVE CELL STIMULATION; NONHUMAN; PYRAMIDAL NERVE CELL; RAT; SIMPLIFIED BINARY NEURON MODEL NETWORK; SIMULATION; SOMATOSENSORY CORTEX; SPIKING MODEL SIMULATION; STIMULUS RESPONSE;

EID: 85087246512     PISSN: 16625188     EISSN: None     Source Type: Journal    
DOI: 10.3389/fncom.2012.00007     Document Type: Article

References (82)

1. Abbott, L. and P. Dayan (1999a). The effect of correlated variability on the accuracy of a population code. Neural Computation 11, 91-101.
2. Abbott, L. and P. Dayan (1999b). The effect of correlated variability on the accuracy of a population code. Neural Computation 11(1), 91-101.
3. Arabzadeh, E., S. Panzeri, and M. Diamond (2004). Whisker vibration information carried by rat barrel cortex neurons. Journal of Neuroscience 24(26), 6011.
4. Arabzadeh, E., R. Petersen, and M. Diamond (2003). Encoding of whisker vibration by rat barrel cortex neurons: implications for texture discrimination. Journal of Neuroscience 23(27), 9146.
5. Averbeck, B., P. Latham, and A. Pouget (2006). Neural correlations, population coding and computation. Nature Reviews Neuroscience 7, 358-366.
6. Barreiro, A., E. Shea-Brown, and E. Thilo (2010). Time scales of spike-train correlation for neural oscillators with common drive. Physical Review E 81(1), 11916.
7. Beck, J.B.V.R., and A. Pouget (2011). Insights from a simple expression for linear fisher information in a recurrently connected population of spiking neurons. Neural Computation 23(6), 1484-1502.
8. Borgers, C. and N. Kopell (2003). Synchronization in networks of excitatory and inhibitory neurons with sparse, random connectivity. Neural Comput. 15(3), 509-538.
9. Britten, K., M. Shadlen, W. Newsome, and J. Movshon (1993). Responses of neurons in macaque mt to stochastic motion signals. Visual Neuroscience 10(06), 1157-1169.
10. Brunel, N. and D. Hansel (2006). How noise affects the synchronization properties of recurrent networks of inhibitory neurons. Neural Computation 18(5), 1066-1110.
11. Bruno, R. and D. Simons (2002). Feedforward mechanisms of excitatory and inhibitory cortical receptive fields. Journal of Neuroscience 22, 10966-10975.
12. Buzsaki, G. (2006). Rhythms of the Brain. Oxford University Press, USA.
13. Cafaro, J. and F. Rieke (2010). Noise correlations improve response fidelity and stimulus encoding. Nature 468(7326), 964-967.
14. Carandini, M. (2004). Amplification of trial-to-trial response variability by neurons in visual cortex. PLoS Biology 2, e264.
15. Cardin, J., M. Carlen, K. Meletis, U. Knoblich, F. Zhang, K. Deisseroth, L. Tsai, and C. Moore (2009). Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459, 663-667.
16. Carvell, G. and D. Simons (1990). Biometric analyses of vibrissal tactile discrimination in the rat. Journal of Neuroscience 10(8), 2638.
17. Cohen, M. and A. Kohn (2011). Measuring and interpreting neuronal correlations. Nature Neuroscience 14(1), 811-819.
18. Cohen, M. R. and J. H. Maunsell (2009, December). Attention improves performance primarily by reducing interneuronal correlations. Nature Neuroscience 12(12), 1594-1600.
19. de la Rocha, J., B. Doiron, E. Shea-Brown, K. Josic, and A. Reyes (2001). Correlation between neural spike trains increases with firing rate. Nature 448, 802-806.
20. Duda, R., P. Hart, D. Stork, et al. (2001). Pattern classification, Volume 2. New York: John Wiley.
21. Ecker, A., P. Berens, G. Keliris, M. Bethge, N. Logothetis, and A. Tolias (2010). Decorrelated neuronal firing in cortical microcircuits. Science 327, 584-581.
22. Faisal, A., L. Selen, and D. Wolpert (2008). Noise in the nervous system. Nature Reviews Neuroscience 9(4), 292.
23. Ferster, D. and K. Miller (2000). Neural mechanisms of orientation selectivity in the visual cortex. Annual Review of Neuroscience 23, 441-411.
24. Gawne, T., T. Kjaer, J. Hertz, and B. Richmond (1996). Adjacent visual cortical complex cells share about 20% of their stimulus-related information. Cerebral Cortex 6, 482-489.
25. Gentet, L., M. Avermann, F. Matyas, J. Staiger, and C. Petersen (2010). Membrane potential dynamics of GABAergic neurons in the barrel cortex of behaving mice. Neuron 65, 422-435.
26. Ginzburg, I. and H. Sompolinsky (1994). Theory of correlations in stochastic neural networks. Physical review E 50(4), 3111.
27. Greenberg, D., A. Houweling, and J. Kerr (2008). Population imaging of ongoing neuronal activity in the visual cortex of awake rats. Nature Neuroscience 11,149-151.
28. Guic-Robles, E., C. Valdivieso, and G. Guajardo (1989). Rats can learn a roughness discrimination using only their vibrissal system. Behavioural Brain Research 31(3), 285-289.
29. Gutnisky, D. and V. Dragoi (2008). Adaptive coding of visual information in neural populations. Nature 452, 220-224.
30. Hansel, D. and C. van Vreeswijk (2002). How noise contributes to contrast invariance of orientation tuning in cat visual cortex. Journal of Neuroscience 22, 5118-5128.
31. Heiss, J., Y. Katz, E. Ganmor, and I. Lampl (2008). Shift in the balance between excitation and inhibition during sensory adaptation of s1 neurons. Journal of Neuroscience 28(49), 13320.
32. Higley, M. and D. Contreras (2006). Balanced excitation and inhibition determine spike timing during frequency adaptation. Journal ofNeuroscience 26(2), 448.
33. Jadhav, S., J. Wolfe, and D. Feldman (2009). Sparse temporal coding of elementary tactile features during active whisker sensation. Nature Neuroscience 12(6), 192-800.
34. Josić, K., E. Shea-Brown, B. Doiron, and J. De La Rocha (2009). Stimulus-dependent correlations and population codes. Neural Computation 21(10), 2774-2804.
35. Kay, S. (1993). Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory. Upper Saddle River, NJ: Prentice Hall.
36. Kerr, J., C. de Kock, D. Greenberg, R. Bruno, B. Sakmann, and F. Helmchen (2007). Spatial organization of neuronal population responses in layer 2/3 of rat barrel cortex. Journal of Neuroscience 27(48), 13316.
37. Khatri, V., R. Bruno, and D. Simons (2009). Stimulus-specific and stimulus-nonspecific firing synchrony and its modulation by sensory adaptation in the whisker-to-barrel pathway. Journal of Neurophysiology 101(5), 2328.
38. Kohn, A. and M. Smith (2005). Stimulus dependence of neuronal correlation in primary visual cortex of the macaque. Journal of Neuroscience 25, 3661-3673.
39. Kohn, A., A. Zandvakili, and M. Smith (2009). Correlations and brain states: from electrophysiology to functional imaging. Current Opinion in Neurobiology 19(4), 434-438.
40. Latham, P. and S. Nirenberg (2005). Synergy, redundancy, and independence in population codes, revisited. Journal of Neuroscience 25(21), 5195.
41. Litwin-Kumar, A., A.-M. M. Oswald, N. N. Urban, and B. Doiron (2011). Balanced synaptic input shapes the correlation between neural spike trains. PLoS Comput Biol 7(12), e1002305.
42. Marella, S. and G. Ermentrout (2008). Class-II neurons display a higher degree of stochastic synchronization than class-I neurons. Physical Review E 77(4), 41918.
43. Markram, H., M. Toledo-Rodriguez, Y. Wang, A. Gupta, G. Silberberg, and C. Wu (2004). Interneurons of the neocortical inhibitory system. Nature Reviews Neuroscience 5(10), 793-807.
44. Middleton, J. W., C. Omar, B. Doiron, and D. Simons (2012). Neural correlation is stimulus-modulated by feedforward inhibitory circuitry. Journal of Neuroscience 32(2), 506-518.
45. Miller, K., D. Pinto, and D. Simons (2001). Processing in layer 4 of the neocortical circuit: new insights from visual and somatosensory cortex. Current Opinion in Neurobiology 11, 488-497.
46. Mitchell, J. F., K. A. Sundberg, and J. H. Reynolds (2009). Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4. Neuron 63(6), 879-888.
47. Moreno, R., J. de La Rocha, A. Renart, and N. Parga (2002). Response of spiking neurons to correlated inputs. Physical Review Letters 89(28), 288101.
48. Moreno-Bote, R. and A. Pouget (2011). Correlations: why size does not necessarily matter. To appear.
49. Okun, M. and I. Lampl (2008). Instantaneous correlation of excitation and inhibition during ongoing and sensory- evoked activities. Nature Neuroscience 11, 535-537.
50. Oram, M. (2011). Visual stimulation decorrelates neuronal activity. Journal of Neurophysiology 95, 942-957.
51. Petersen, R., S. Panzeri, and M. Diamond (2001). Population coding of stimulus location in rat somatosensory cortex. Neuron 32(3), 503-514.
52. Pinto, D., J. Brumberg, and D. Simons (2000). Circuit dynamics and coding strategies in rodent somatosensory cortex. Journal of Neurophysiology 83, 1158-1166.
53. Pinto, D., J. Brumberg, D. Simons, G. Ermentrout, and R. Traub (1996). A quantitative population model of whisker barrels: re-examining the Wilson-Cowan equations. Journal ofComputational Neuroscience 3, 241-264.
54. Poulet, J. and C. Petersen (2008). Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice. Nature 454, 881-885.
55. Priebe, N. and D. Ferster (2008). Inhibition, spike threshold, and stimulus selectivity in primary visual cortex. Neuron 57, 482-491.
56. Renart, A., J. de la Rocha, P. Bartho, L. Hollender, N. Parga, A. Reyes, and K. Harris (2010). The asynchronous state in cortical circuits. Science 327, 581-590.
57. Ritt, J., M. Andermann, and C. Moore (2008). Embodied information processing: Vibrissa mechanics and texture features shape micromotions in actively sensing rats. Neuron 57, 599-613.
58. Romo, R., A. Hernandez, A. Zainos, and E. Salinas (2003). Correlated neuronal discharges that increase coding efficiency during perceptual discrimination. Neuron 38, 649-651.
59. Rosenbaum, R. and K. Josic (2011). Mechanisms that modulate the transfer of spiking correlations. Neural Computation, 1-45.
60. Rothschild, G., I. Nelken, and A. Mizrahi (2010). Functional organization and population dynamics in the mouse primary auditory cortex. Nature Neuroscience 13(3), 353-360.
61. Salinas, E. and T. J. Sejnowski (2000, August). Impact of correlated synaptic input on output firing rate and variability in simple neuronal models. Journal of Neuroscience 20(16), 6193-6209.
62. Series, P., P. Latham, and A. Pouget (2004). Tuning curve sharpening for orientation selectivity: coding efficiency and the impact of correlations. Nature Neuroscience 7, 1129-1135.
63. Shadlen, M. N. and W. T. Newsome (1998). The Variable Discharge of Cortical Neurons: Implications for Connectivity, Computation, and Information Coding. Journal Neuroscience 18, 3810-3896.
64. Shamir, M. and H. Sompolinsky (2004). Nonlinear population codes. Neural Computation 16(6), 1105-1136.
65. Shea-Brown, E., K. Josic, J. de La Rocha, and B. Doiron (2008). Correlation and synchrony transfer in integrate- and-fire neurons: basic properties and consequences for coding. Physical Review Letters 100, 108102.
66. Simons, D. (1918). Response properties of vibrissa units in rat si somatosensory neocortex. Journal ofNeuro- physiology 41(3), 198.
67. Smith, M. and A. Kohn (2008). Spatial and Temporal Scales of Neuronal Correlation in Primary Visual Cortex. Journal of Neuroscience 28, 12591-12603.
68. Softky, W. and C. Koch (1993). The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. Journal of Neuroscience 13, 334-350.
69. Sompolinsky, H., H. Yoon, K. Kang, and M. Shamir (2001). Population coding in neuronal systems with correlated noise. Physical Review E 64(5), 051904.
70. Swadlow, H. (2003). Fast-spike interneurons and feedforward inhibition in awake sensory neocortex. Cerebral Cortex 13, 25-32.
71. Tchumatchenko, T., A. Malyshev, T. Geisel, M. Volgushev, and F. Wolf (2010). Correlations and synchrony in threshold neuron models. Physical Review Letters 104(5), 58102.
72. Tiesinga, P., J. Fellous, E. Salinas, J. Jose, and T. Sejnowski (2004). Inhibitory synchrony as a mechanism for attentional gain modulation. Journal Physiology-Paris 98(4-6), 296-314.
73. van Vreeswijk, C., L. Abbott, and G. Ermentrout (1994). When inhibition not excitation synchronizes neural firing. Journal of Computational Neuroscience 1, 313-321.
74. Wang, Q., R. Webber, and G. Stanley (2010). Thalamic synchrony and the adaptive gating of information flow to cortex. Nature Neuroscience 13, 1534-1541.
75. Wang, X. and G. Buzsaki (1996). Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. Journal of Neuroscience 16, 6402-6413.
76. Wehr, M. and A. Zador (2003). Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex. Nature 426, 442-446.
77. Whittington, M., R. Traub, N. Kopell, B. Ermentrout, and E. Buhl (2000). Inhibition-based rhythms: experimental and mathematical observations on network dynamics. International Journal of Psychophysiology 38, 315-336.
78. Wilent, W. and D. Contreras (2005). Dynamics of excitation and inhibition underlying stimulus selectivity in rat somatosensory cortex. Nature Neuroscience 8, 1364-1370.
79. Wolfe, J., D. Hill, S. Pahlavan, P. Drew, D. Kleinfeld, and D. Feldman (2008). Texture coding in the rat whisker system: slip-stick versus differential resonance. PLoSBiology 6(8), e215.
80. Yu, J. and D. Ferster (2010). Membrane potential synchrony in primary visual cortex during sensory stimulation. Neuron 68, 1187-1201.
81. Zhu, Y., R. Stornetta, and J. Zhu (2004). Chandelier cells control excessive cortical excitation: characteristics of whisker-evoked synaptic responses of layer 2/3 nonpyramidal and pyramidal neurons. The Journal of Neuroscience 24, 5101-5108.
82. Zohary, E., M. Shadlen, and W. Newsome (1994). Correlated neuronal discharge rate and its implications for psychophysical performance. Nature 370, 140-143.