Dynamic Excitatory and Inhibitory Gain Modulation Can Produce Flexible, Robust and Optimal Decision-making

PLoS Computational Biology

Volumn 9, Issue 6, 2013, Pages

  Niyogi, Ritwik K ^a   Wong Lin, KongFatt ^b  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF ULSTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVIORAL RESEARCH; DECISION MAKING; MAMMALS; NEURONS;

DECISIONS MAKINGS; EXCITATORY NEURONS; GAIN MODULATION; INHIBITORY NEURONS; OPTIMAL DECISION MAKING; PARIETAL CORTICES; PERCEPTUAL DECISION MAKING; ROBUST DECISIONS; SENSORY EVIDENCE; TEMPORAL INTEGRATION;

MODULATION;

ARTICLE; COGNITION; DECISION MAKING; EXCITATION AND STIMULATION; MOTION; MOTION DISCRIMINATION TASK; NERVE CELL; NEUROMODULATION; RESPONSE TIME; SIMULATION; STIMULUS RESPONSE; TASK PERFORMANCE;

ANIMALIA; PRIMATES;

EID: 84879544068     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003099     Document Type: Article

References (97)

1. Gold JI, Shadlen MN, (2007) The neural basis of decision making. Annu Rev Neurosci 30: 535-574.
2. Stanford TR, Shankar S, Massoglia DP, Costello MG, Salinas E, (2010) Perceptual decision making in less than 30 milliseconds. Nat Neurosci 13: 379-385.
3. Luce RD (1986) Response Times: Their Role in Inferring Elementary Mental Organization. New York (New York): Oxford Univ. Press. 577 p.
4. Andersen RA, Buneo CA, (2002) Intentional maps in posterior parietal cortex. Annu Rev Neurosci 25: 189-220.
5. Shadlen MN, Gold JI (2004) The neurophysiology of decision-making as a window on cognition. In: Gazzaniga MS, editor, The Cognitive Neurosciences, 3rd edition. MIT Press.
6. Cisek P, (2006) Integrated neural processes for defining potential actions and deciding between them: a computational model. J Neurosci 26: 9761-9770.
7. Doya K, (2008) Modulators of decision making. Nat Neurosci 11: 410-416.
8. Heekeren HP, Marrett S, Ungerleider LG, (2008) The neural systems that mediate human perceptual decision making. Nat Rev Neurosci 9: 467-479.
9. Andersen RA, Cui H, (2009) Intention, action planning, and decision making in parietal-frontal circuits. Neuron 63: 568-583.
10. Cisek P, Kalaska JF, (2010) Neural mechanisms for interacting with a world full of action choices. Annu Rev Neurosci 33: 269-298.
11. Doya K, Shadlen MN, (2012) Decision making. Curr Opin Neurobiol 22: 911-913.
12. Thura D, Beauregard-Racine J, Fradet CW, Cisek P, (2012) Decision making by urgency gating: theory and experimental support. J Neurophysiol 108: 2912-2930.
13. Reddi BA, Carpenter RHS, (2000) The influence of urgency on decision time. Nat Neurosci 3: 827-830.
14. Smith PL, Ratcliff R, Wolfgang BJ, (2004) Attention orienting and the time course of perceptual decisions: response time distributions with masked and unmasked displays. Vision Res 44: 1297-1320.
15. Ditterich J, (2006) Evidence for time-variant decision making. Eur J Neurosci 24: 3628-3641.
16. Ditterich J, (2006) Stochastic models of decisions about motion direction: behavior and physiology. Neural Netw 19: 981-1012.
17. Churchland AK, Kiani R, Shadlen MN, (2008) Decision-making with multiple alternatives. Nat Neurosci 11: 693-702.
18. Kiani R, Hanks TD, Shadlen MN, (2008) Bounded integration in parietal cortex underlies decisions even when viewing duration is dictated by the environment. J Neurosci 28: 3017-3029.
19. Smith PL, Ratcliff R, (2009) An integrated theory of attention and decision-making in visual signal detection. Psychol Rev 116: 283-317.
20. Cisek P, Puskas GA, El-Murr S, (2009) Decisions in changing conditions: the urgency-gating model. J Neurosci 29: 11560-11571.
21. Drugowitsch J, Moreno-Bote R, Churchland AK, Shadlen MN, Pouget A, (2012) The cost of accumulating evidence in perceptual decision making. J Neurosci 32: 3612-3628.
22. Treue S, Martinez-Trujillo JC, (1999) Feature-based attention influences motion processing gain in macaque visual cortex. Nature 399: 575-579.
23. Salinas E, Sejnowski TJ, (2001) Correlated neuronal activity and the flow of neural information. Nat Rev Neurosci 2: 539-550.
24. Salinas E, Sejnowski TJ, (2001) Gain modulation in the central nervous system: where behavior, neurophysiology, and computation meet. Neuroscientist 7: 430-440.
25. Reynolds JH, Chelazzi L, (2004) Attentional modulation of visual processing. Annu Rev Neurosci 27: 611-647.
26. Salinas E, (2004) Fast remapping of sensory stimuli onto motor actions on the basis of contextual modulation. J Neurosci 24: 1113-1118.
27. Gail A, Andersen RA, (2006) Neural dynamics in monkey parietal reach region reflect context- specific sensorimotor transformations. J Neurosci 26: 9376-9384.
28. Gottlieb J, (2007) From thought to action: the parietal cortex as a bridge between perception, action, and cognition. Neuron 53: 9-16.
29. Bisley JW, Goldberg ME, (2010) Attention, intention, and priority in the parietal lobe. Annu Rev Neurosci 33: 1-21.
30. Gottlieb J, Balan P, (2010) Attention as a decision in information space. Trends Cogn Sci 14: 240-248.
31. McAdams CJ, Maunsell JHR, (1999) Effects of attention on orientation-tuning functions of single neurons in macaque cortical area V4. J Neurosci 19: 431-441.
32. Servan-Schreiber GM, Printz H, Cohen JD, (1990) A network model of catecholamine effects: gain, signal-to-noise ratio, and behavior. Science 249: 892-895.
33. Salinas E, Abbott LF, (1996) A model of multiplicative neural responses in parietal cortex. Proc Natl Acad Sci USA 93: 11956-11961.
34. Abbott LF, Varela JA, Sen K, Nelson SB, (1997) Synaptic depression and cortical gain control. Science 275: 220-224.
35. Salinas E, Thier P, (2000) Gain modulation: a major computational principle of the central nervous system. Neuron 27: 15-21.
36. Salinas E, Sejnowski TJ, (2000) Impact of correlated synaptic input on output firing rate and variability in simple neuronal models. J Neurosci 20: 6193-6209.
37. Doiron B, Longtin A, Berman N, Maler L, (2001) Subtractive and divisive inhibition: effect of voltage-dependent inhibitory conductance and noise. Neural Comput 13: 227-248.
38. Chance FS, Abbott LF, Reyes AD, (2002) Gain modulation from background synaptic input. Neuron 35: 773-782.
39. Mitchell SJ, Silver RA, (2003) Shunting inhibition modulates neuronal gain during synaptic excitation. Neuron 38: 433-443.
40. Murphy BK, Miller KD, (2003) Multiplicative gain changes are induced by excitation or inhibition alone. Neuron 23: 10040-10051.
41. Prescott SA, Koninck YD, (2003) Gain control of firing rate by shunting inhibition: roles of synaptic noise and dendritic saturation. Proc Natl Acad Sci USA 100: 2076-2081.
42. Shu Y, Hasenstaub A, Badoual M, Bal T, McCormick DA, (2003) Barrages of synaptic activity control the gain and sensitivity of cortical neurons. J Neurosci 23: 10388-10401.
43. Tiesinga PH, Fellous JM, Salinas E, Jose JV, Sejnowski TJ, (2004) Inhibitory synchrony as a mechanism for attentional gain modulation. J Physiol Paris 98: 296-314.
44. Higgs MH, Slee SJ, Spain WJ, (2006) Diversity of gain modulation by noise in neocortical neurons: regulation by the slow afterhyperpolarization conductance. J Neurosci 26: 8787-8799.
45. Compte A, Wang XJ, (2006) Tuning curve shift by attention modulation in cortical neurons: a computational study of its mechanisms. Cereb Cortex 16: 761-778.
46. Brozovic M, Abbott LF, Andersen RA, (2008) Mechanism of gain modulation at single neuron and network levels. J Comput Neurosci 25: 158-168.
47. Ardid S, Wang XJ, Compte A, (2007) An integrated microcircuit model of attentional processing in the neocortex. J Neurosci 27: 8486-8496.
48. Arsiero M, Luscher HR, Lundstrom BN, Giugliano M, (2007) The impact of input fluctuations on the frequency-current relationships of layer 5 pyramidal neurons in the rat medial prefrontal cortex. J Neurosci 27: 3274-3284.
49. Reynolds JH, Heeger DJ, (2009) The normalization model of attention. Annu Rev Neurosci 61: 168-185.
50. Sutherland C, Doiron B, Longtin A, (2009) Feedback-induced gain control in stochastic spiking networks. Biol Cybern 100: 475-489.
51. Fernandez FR, White JA, (2010) Gain control in CA1 pyramidal cells using changes in somatic conductance. J Neurosci 30: 230-241.
52. Mitchell JF, Sundberg KS, Reynolds JH, (2007) Differential attention-dependent response modulation across cell classes in macaque visual area V4. Neuron 55: 131-141.
53. Ghose GM, Maunsell J, (2002) Attentional modulation in visual cortex depends on task timing. Nature 419: 616-620.
54. Standage D, You H, Wang DH, Dorris MC, (2011) Gain modulation by an urgency signal controls the speed-accuracy trade-off in a network model of a cortical decision circuit. Front Comput Neurosci 5: 7 doi: 10.3389/fncom.2011.00007.
55. Wong KF, Wang XJ, (2006) A recurrent network mechanism of time integration in perceptual decisions. J Neurosci 26: 1314-1328.
56. Wong KF, Huk AC, Shadlen MN, Wang XJ, (2007) Neural circuit dynamics underlying accumulation of time-varying evidence during perceptual decision-making. Front Comput Neurosci 1: 6 doi: 10.3389/neuro.10/006.2007.
57. Roitman JD, Shadlen MN, (2002) Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. J Neurosci 22: 9475-9489.
58. Niyogi RK, Wong-Lin KF (2010). Time-varying gain modulation on neural circuit dynamics and performance in perceptual decisions. Abstract No. 246, Computational and Systems Neuroscience (CoSyNe) 2010, Salt Lake City, UT, USA. Published in Frontiers in Neuroscience doi: 10.3389/conf.fnins.2010.03.00132. (online).
59. Wang X, (2002) Probabilistic decision making by slow reverberation in cortical circuits. Neuron 36: 955-968.
60. Abbott LF, Chance FS, (2005) Drivers and modulators from push-pull and balanced synaptic input. Prog Brain Res 149: 147-155.
61. Amit D, Brunel N, (1997) Dynamics of a recurrent network of spiking neurons before and following learning. Network-Computation in Neural Systems 8: 373-404.
62. Amit DJ, Brunel N, (1997) Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. Cereb Cortex (New York, NY: 1991) 7: 237-52.
63. Britten KH, Shadlen MN, Newsome WT, Movshon JA, (1993) Response of neurons in macaque MT to stochastic motion signals. Vis Neurosci 10: 1157-1169.
64. Andersen RA, Mountcastle VB, (1983) The influence of the angle of gaze upon the excitability of the light-sensitive neurons of the posterior parietal cortex. J Neurosci 3: 532-548.
65. Broderick T, Wong-Lin KF, Holmes P, (2010) Closed-form approximations of first-passage distributions for a stochastic decision making model. Applied Mathematics Research eXpress 2009 No 2: 123-141.
66. Herrington TM, Assad JA, (2010) Temporal sequence of attentional modulation in the lateral intraparietal area and middle temporal area during rapid covert shifts of attention. J Neurosci 30: 3287-3296.
67. Ratcliff R, Cherian A, Seagraves M, (2003) A comparison of macaque behavior and superior colliculus neuronal activity to predictions from models of two-choice decisions. J Neurophysiol 90: 1392-1407.
68. Ratcliff R, Rouder R, (1998) Modeling response times for two-choice decisions. Psychol Sci 9: 347-356.
69. Liu F, Wang XJ, (2008) A common cortical circuit mechanism for perceptual categorical discrimination and veridical judgment. PLoS Comput Biol 4 (12):: e1000253 doi:10.1371/journal.pcbi.1000253.
70. Furman M, Wang XJ, (2008) Similarity effect and optimal control of multiple-choice decision making. Neuron 60: 1153-1168.
71. Albantakis L, Deco G, (2009) The encoding of alternatives in multiple-choice decision making. Proc Natl Acad Sci USA 23: 10308-10313.
72. Eckhoff P, Wong-Lin KF, Holmes P, (2011) Dimension reduction and dynamics of a spiking neural network model for decision making under neuromodulation. SIAM J Appl Dyn Syst 10: 148-188.
73. Huk AC, Shadlen MN, (2005) A neural integrator underlying perceptual decision-making in macaque parietal cortex. J Neurosci 25: 10420-10436.
74. Bogacz R, Wagenmakers EJ, Forstmann BU, Nieuwenhuis S, (2009) The neural basis of the speed-accuracy tradeoff. Trends Neurosci 33: 10-16.
75. Simen P, Cohen JD, Holmes P, (2006) Rapid decision threshold modulation by reward rate in a neural network. Neural Netw 19: 1013-1026.
76. Balci F, Simen P, Niyogi R, Saxe A, Hughes JA, et al. (2011) Acquisition of decision making criteria: reward rate ultimately beats accuracy. Atten Percept Psychophys 73: 640-657.
77. Lo CC, Wang XJ, (2006) Cortico-basal ganglia circuit mechanism for a decision threshold in reaction time tasks. Nat Neurosci 9: 956-963.
78. Frank MJ, (2006) Hold your horses: a dynamic computational role for the subthalamic nucleus in decision making. Neural Netw 19: 1120-1136.
79. Marti D, Deco G, Mattia M, Gigante G, Giudice PD, (2008) A fluctuation-driven mechanisms for slow decision processes in reverberant networks. PLoS ONE 3 (7):: e2534 doi:10.1371/journal.pone.0002534.
80. Shadlen MN, Newsome WT, (2001) Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J Neurophysiol 86: 1916-1936.
81. Bogacz R, Brown E, Moehlis J, Holmes P, Cohen JD, (2006) The physics of optimal decision making: A formal analysis of models of performance in two-alternative forced choice tasks. Psychol Rev 113: 700-765.
82. Deneve S (2009) Bayesian decision making in two-alternative forced choices. In: Handbook of reward and decision making, Dreher JC, Tremblay L, Eds. New York (New York): Academic Press. 500p.
83. Bollimunta A, Ditterich J, (2011) Local computation of decision-relevant sensory evidence in parietal cortex. Cereb Cortex 22: 903-917.
84. Eckhoff P, Wong-Lin KF, Holmes P, (2009) Optimality and robustness of a biophysical decision-making model under norepinephrine modulation. J Neurosci 29: 4301-4311.
85. Wong-Lin KF (2009). Are redundant neurons redundant in categorical decision making? a ro-bustness study of a network model. Abstract No. 194.12, Society for Neuroscience meeting 2009, Washington D.C., USA.
86. Meister MLR, Hennig JA, Huk AC, (2013) Signal multiplexing and single-neuron computations in lateral intraparietal area during decision-making. J Neurosci 33: 2254-67.
87. Wang XJ, (1999) Synaptic basis of cortical persistent activity: the importance of NMDA receptors to working memory. J Neurosci 19: 9587-9603.
88. Gutkin BS, Laing CR, Colby CL, Chow CC, Ermentrout GB, (2001) Turning on and off with excitation: the role of spike-timing asynchrony and synchrony in sustained neural activity. J Comput Neurosci 11: 121-134.
89. Grossberg S, Pilly P, (2008) Temporal dynamics of decision-making during motion perception in the visual cortex. Vision Res 48: 1345-1373.
90. Machens CK, Romo R, Brody CD, (2005) Flexible control of mutual inhibition: a neural model of two-interval discrimination. Science 18: 1121-1124.
91. Niyogi RK, (2009) Dynamical effects of non-linearities and time-varying gain modulation in neurally plausible network models of perceptual decision-making. Dickinson College Mathematics honors thesis.
92. Brown E, Gao J, Holmes P, Bogacz MG, Cohen JD, (2005) Simple neural networks that optimize decisions. Int J Bifurcation and Chaos 15: 803-826.
93. Feng S, Holmes P, Rorie A, Newsome WT, (2009) Can monkeys choose optimally when faced with noisy stimuli and unequal rewards? PLoS Comput Biol 5 (2):: e1000284 doi:10.1371/journal.pcbi.1000284.
94. Uhlenbeck GE, Ornstein LS, (1930) On the theory of Brownian motion. Phys Rev 36: 823-841.
95. Higham DJ, (2001) An algorithmic introduction to numerical simulation of stochastic differential equations. SIAM Rev 43: 525-546.
96. Strogatz SH (2001) Nonlinear dynamics and chaos: with applications to physics, biology, chemistry and engineering. Perseus Books Group, Cambridge MA.
97. Ermentrout B (2002) Simulating, analyzing, and animating dynamical systems: a guide to XPPAUT for researchers and students (software, environments, tools). Philadelphia, PA: Society for Industrial and Applied Mathematics.