Neuronal variability in orbitofrontal cortex during economic decisions

Journal of Neurophysiology

Volumn 114, Issue 3, 2015, Pages 1367-1381

  Conen, Katherine E ^a   Padoa Schioppa, Camillo ^a,b,c  

^a WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b WASHINGTON UNIVERSITY   (United States)

^c WASHINGTON UNIVERSITY IN ST LOUIS   (United States)

Author keywords

Neoroeconomics; Subjective value; Value based decision

Indexed keywords

ANIMAL EXPERIMENT; ARTICLE; CELLS BY BODY ANATOMY; COMPUTER SIMULATION; CONTROLLED STUDY; DECISION MAKING; ECONOMICS; FEMALE; FIRING RATE; MALE; MATHEMATICAL PARAMETERS; NERVE CELL; NONHUMAN; NULL CELL; ORBITAL CORTEX; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; RHESUS MONKEY; SIMULATION; ANIMAL; BIOLOGICAL MODEL; CLASSIFICATION; CYTOLOGY; ECONOMIC MODEL; PHYSIOLOGY; PREFRONTAL CORTEX; SIGNAL NOISE RATIO;

ANIMALS; DECISION MAKING; FEMALE; MACACA MULATTA; MALE; MODELS, ECONOMIC; MODELS, NEUROLOGICAL; NEURONS; PREFRONTAL CORTEX; SIGNAL-TO-NOISE RATIO;

EID: 84940676579     PISSN: 00223077     EISSN: 15221598     Source Type: Journal    
DOI: 10.1152/jn.00231.2015     Document Type: Article

References (60)

1. Abbott LF, Dayan P. The effect of correlated variability on the accuracy of a population code. Neural Comput 11: 91–101, 1999
2. Ahn S, Fessler JA. Globally convergent image reconstruction for emission tomography using relaxed ordered subsets algorithms. IEEE Trans Med Imaging 22: 613–626, 2003
3. Averbeck BB, Lee D. Neural noise and movement-related codes in the macaque supplementary motor area. J Neurosci 23: 7630–7641, 2003
4. Bair W, Koch C. Temporal precision of spike trains in extrastriate cortex of the behaving macaque monkey. Neural Comput 8: 1185–1202, 1996
5. Britten KH, Newsome WT, Saunders RC. Effects of inferotemporal cortex lesions on form-from-motion discrimination in monkeys. Exp Brain Res 88: 292–302, 1992
6. Britten KH, Newsome WT, Shadlen MN, Celebrini S, Movshon JA. A relationship between behavioral choice and the visual responses of neurons in macaque MT. Vis Neurosci 13: 87–100, 1996
7. Camille N, Griffiths CA, Vo K, Fellows LK, Kable JW. Ventromedial frontal lobe damage disrupts value maximization in humans. J Neurosci 31: 7527–7532, 2011
8. Carnevale F, de Lafuente V, Romo R, Parga N. Internal signal correlates neural populations and biases perceptual decision reports. Proc Natl Acad Sci USA 109: 18938–18943, 2012
9. Churchland MM, Yu BM, Cunningham JP, Sugrue LP, Cohen MR, Corrado GS, Newsome WT, Clark AM, Hosseini P, Scott BB, Bradley DC, Smith MA, Kohn A, Movshon JA, Armstrong KM, Moore T, Chang SW, Snyder LH, Lisberger SG, Priebe NJ, Finn IM, Ferster D, Ryu SI, Santhanam G, Sahani M, Shenoy KV. Stimulus onset quenches neural variability: a widespread cortical phenomenon. Nat Neurosci 13: 369–378, 2010
10. Cohen MR, Kohn A. Measuring and interpreting neuronal correlations. Nat Neurosci 14: 811–819, 2011
11. Cohen MR, Maunsell JH. Attention improves performance primarily by reducing interneuronal correlations. Nat Neurosci 12: 1594–1600, 2009
12. Cohen MR, Newsome WT. Context-dependent changes in functional circuitry in visual area MT. Neuron 60: 162–173, 2008
13. Cohen MR, Newsome WT. Estimates of the contribution of single neurons to perception depend on timescale and noise correlation. J Neurosci 29: 6635–6648, 2009
14. Constantinidis C, Goldman-Rakic PS. Correlated discharges among putative pyramidal neurons and interneurons in the primate prefrontal cortex. J Neurophysiol 88: 3487–3497, 2002
15. de la Rocha J, Doiron B, Shea-Brown E, Josic= K, Reyes A. Correlation between neural spike trains increases with firing rate. Nature 448: 802–806, 2007
16. Dean AF. The variability of discharge of simple cells in the cat striate cortex Exp Brain Res 44: 437–440, 1981
17. Ecker AS, Berens P, Cotton RJ, Subramaniyan M, Denfield GH, Cadwell CR, Smirnakis SM, Bethge M, Tolias AS. State dependence of noise correlations in macaque primary visual cortex. Neuron 82: 235–248, 2014
18. Ecker AS, Berens P, Keliris GA, Bethge M, Logothetis NK, Tolias AS Decorrelated neuronal firing in cortical microcircuits. Science 327: 584– 587, 2010
19. Ecker AS, Berens P, Tolias AS, Bethge M. The effect of noise correlations in populations of diversely tuned neurons. J Neurosci 31: 14272–14283, 2011
20. Erickson CA, Jagadeesh B, Desimone R. Clustering of perirhinal neurons with similar properties following visual experience in adult monkeys. Nat Neurosci 3: 1143–1148, 2000
21. Gallagher M, McMahan RW, Schoenbaum G. Orbitofrontal cortex and representation of incentive value in associative learning. J Neurosci 19: 6610–6614, 1999
22. Gawne TJ, Kjaer TW, Hertz JA, Richmond BJ. Adjacent visual cortical complex cells share about 20% of their stimulus-related information. Cereb Cortex 6: 482–489, 1996
23. Gawne TJ, Richmond BJ. How independent are the messages carried by adjacent inferior temporal cortical neurons? J Neurosci 13: 2758–2771, 1993
24. Glaister P. Least squares revisited. Math Gaz 85: 104–107, 2001
25. Gremel CM, Costa RM. Orbitofrontal and striatal circuits dynamically encode the shift between goal-directed and habitual actions. Nat Commun 4: 2264, 2013
26. Gutnisky DA, Dragoi V. Adaptive coding of visual information in neural populations. Nature 452: 220–224, 2008
27. Haefner RM, Gerwinn S, Macke JH, Bethge M. Inferring decoding strategies from choice probabilities in the presence of correlated variability. Nat Neurosci 16: 235–242, 2013
28. Hardin J, Garcia SR, Golan DA. Method for generating realistic correlation matrices. Ann Appl Stat 7: 1733–1762, 2013
29. Jeanne JM, Sharpee TO, Gentner TQ. Associative learning enhances population coding by inverting interneuronal correlation patterns. Neuron 78: 352–363, 2013
30. Kable JW, Glimcher PW. The neurobiology of decision: consensus and controversy. Neuron 63: 733–745, 2009
31. Kohn A, Smith MA. Stimulus dependence of neuronal correlation in primary visual cortex of the macaque. J Neurosci 25: 3661–3673, 2005
32. Lee D, Port NL, Kruse W, Georgopoulos AP. Variability and correlated noise in the discharge of neurons in motor and parietal areas of the primate cortex. J Neurosci 18: 1161–1170, 1998
33. Liu S, Gu Y, DeAngelis GC, Angelaki DE. Choice-related activity and correlated noise in subcortical vestibular neurons. Nat Neurosci 16: 89–97, 2013
34. Mitchell JF, Sundberg KA, Reynolds JH. Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4. Neuron 63: 879–888, 2009
35. Miura K, Mainen ZF, Uchida N. Odor representations in olfactory cortex: distributed rate coding and decorrelated population activity. Neuron 74: 1087–1098, 2012
36. Moreno-Bote R, Beck J, Kanitscheider I, Pitkow X, Latham P, Pouget A Information-limiting correlations. Nat Neurosci 17: 1410–1417, 2014
37. Nienborg H, Cohen MR, Cumming BG. Decision-related activity in sensory neurons: correlations among neurons and with behavior. Annu Rev Neurosci 35: 463–483, 2012
38. Nienborg H, Cumming BG. Decision-related activity in sensory neurons may depend on the columnar architecture of cerebral cortex. J Neurosci 34: 3579–3585, 2014
39. Nienborg H, Cumming BG. Decision-related activity in sensory neurons reflects more than a neuron’s causal effect. Nature 459: 89–92, 2009
40. Nienborg H, Cumming BG. Macaque V2 neurons, but not V1 neurons, show choice-related activity. J Neurosci 26: 9567–9578, 2006
41. Ongur D, Price JL. The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and humans. Cereb Cortex 10: 206–219, 2000
42. Padoa-Schioppa C. Neurobiology of economic choice: a good-based model Annu Rev Neurosci 34: 333–359, 2011
43. Padoa-Schioppa C. Neuronal origins of choice variability in economic decisions Neuron 80: 1322–1336, 2013
44. Padoa-Schioppa C, Assad JA. Neurons in orbitofrontal cortex encode economic value. Nature 441: 223–226, 2006
45. Padoa-Schioppa C, Assad JA. The representation of economic value in the orbitofrontal cortex is invariant for changes of menu. Nat Neurosci 11: 95–102, 2008
46. Poort J, Roelfsema PR. Noise correlations have little influence on the coding of selective attention in area V1. Cereb Cortex 19: 543–553, 2009
47. Rangel A, Hare T. Neural computations associated with goal-directed choice Curr Opin Neurobiol 20: 262–270, 2010
48. Romo R, Hernandez A, Zainos A, Lemus L, Brody CD. Neuronal correlates of decision-making in secondary somatosensory cortex. Nat Neurosci 5: 1217–1225, 2002
49. Romo R, Hernandez A, Zainos A, Salinas E. Correlated neuronal discharges that increase coding efficiency during perceptual discrimination. Neuron 38: 649–657, 2003
50. Rosenbaum RJ, Trousdale J, Josic= K. Pooling and correlated neural activity Front Comput Neurosci 4: 9, 2010
51. Rudebeck PH, Saunders RC, Prescott AT, Chau LS, Murray EA. Prefrontal mechanisms of behavioral flexibility, emotion regulation and value updating. Nat Neurosci 16: 1140–1145, 2013
52. Rushworth MF, Kolling N, Sallet J, Mars RB. Valuation and decisionmaking in frontal cortex: one or many serial or parallel systems? Curr Opin Neurobiol 22: 946–955, 2012
53. Shadlen MN, Britten KH, Newsome WT, Movshon JA. A computational analysis of the relationship between neuronal and behavioral responses to visual motion. J Neurosci 16: 1486–1510, 1996
54. Shadlen MN, Newsome WT. The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. J Neurosci 18: 3870–3896, 1998
55. Smith MA, Kohn A. Spatial and temporal scales of neuronal correlation in primary visual cortex. J Neurosci 28: 12591–12603, 2008
56. Smith MA, Sommer MA. Spatial and temporal scales of neuronal correlation in visual area V4. J Neurosci 33: 5422–5432, 2013
57. Vogels R, Spileers W, Orban GA. The response variability of striate cortical neurons in the behaving monkey. Exp Brain Res 77: 432–436, 1989
58. Wallis JD. Cross-species studies of orbitofrontal cortex and value-based decision-making. Nat Neurosci 15: 13–19, 2011
59. Xanthopoulos P, Pardalos P, Trafalis T. Linear discriminant analysis. In: Robust Data Mining. New York: Springer, 2013, p. 27–33
60. Zohary E, Shadlen MN, Newsome WT. Correlated neuronal discharge rate and its implications for psychophysical performance. Nature 370: 140–143, 1994