Complementary contributions of basolateral amygdala and orbitofrontal cortex to value learning under uncertainty

eLife

Volumn 6, Issue , 2017, Pages

  Stolyarova, Alexandra ^a   Izquierdo, Alicia ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL EXPERIMENT; BASOLATERAL AMYGDALA; FACILITATION; LEARNING; NONHUMAN; ORBITAL CORTEX; REWARD; UNCERTAINTY; ANIMAL; DECISION MAKING; PATHOLOGY; PHYSIOLOGY; PREFRONTAL CORTEX; RAT;

ANIMALS; BASOLATERAL NUCLEAR COMPLEX; DECISION MAKING; LEARNING; PREFRONTAL CORTEX; RATS; UNCERTAINTY;

EID: 85027099681     PISSN: None     EISSN: 2050084X     Source Type: Journal    
DOI: 10.7554/eLife.27483     Document Type: Article

References (98)

1. Bakhurin KI, Goudar V, Shobe JL, Claar LD, Buonomano DV, Masmanidis SC. 2017. Differential encoding of Time by Prefrontal and Striatal Network Dynamics. The Journal of Neuroscience 37: 854–870. doi: 10.1523/JNEUROSCI.1789-16.2016, PMID: 28123021
2. Bari A, Robbins TW. 2013. Inhibition and impulsivity: behavioral and neural basis of response control. Progress in Neurobiology 108: 44–79. doi: 10.1016/j.pneurobio.2013.06.005, PMID: 23856628
3. Behrens TE, Woolrich MW, Walton ME, Rushworth MF. 2007. Learning the value of information in an uncertain world. Nature Neuroscience 10: 1214–1221. doi: 10.1038/nn1954, PMID: 17676057
4. Chan SC, Niv Y, Norman KA. 2016. A Probability distribution over latent causes, in the Orbitofrontal Cortex. The Journal of Neuroscience 36: 7817–7828. doi: 10.1523/JNEUROSCI.0659-16.2016, PMID: 27466328
5. Chang SE, McDannald MA, Wheeler DS, Holland PC. 2012. The effects of basolateral amygdala lesions on unblocking. Behavioral Neuroscience 126: 279–289. doi: 10.1037/a0027576, PMID: 22448857
6. Chen J, Yu S, Fu Y, Li X. 2014. Synaptic proteins and receptors defects in autism spectrum disorders. Frontiers in Cellular Neuroscience 8: 276. doi: 10.3389/fncel.2014.00276, PMID: 25309321
7. Chhatwal JP, Myers KM, Ressler KJ, Davis M. 2005. Regulation of gephyrin and GABAA receptor binding within the amygdala after fear acquisition and extinction. Journal of Neuroscience 25: 502–506. doi: 10.1523/JNEUROSCI.3301-04.2005, PMID: 15647495
8. Chu HY, Ito W, Li J, Morozov A. 2012. Target-specific suppression of GABA release from parvalbumin interneurons in the basolateral amygdala by dopamine. Journal of Neuroscience 32: 14815–14820. doi: 10.1523/JNEUROSCI.2997-12.2012, PMID: 23077066
9. Cikara M, Gershman SJ. 2016. Medial prefrontal cortex updates its Status. Neuron 92: 937–939. doi: 10.1016/j. neuron.2016.11.040, PMID: 27930908
10. Conen KE, Padoa-Schioppa C. 2015. Neuronal variability in orbitofrontal cortex during economic decisions. Journal of Neurophysiology 114: 1367–1381. doi: 10.1152/jn.00231.2015, PMID: 26084903
11. Courville AC, Daw ND, Touretzky DS. 2006. Bayesian theories of conditioning in a changing world. Trends in Cognitive Sciences 10: 294–300. doi: 10.1016/j.tics.2006.05.004, PMID: 16793323
12. Dalley JW, Cardinal RN, Robbins TW. 2004. Prefrontal executive and cognitive functions in rodents: neural and neurochemical substrates. Neuroscience & Biobehavioral Reviews 28: 771–784. doi: 10.1016/j.neubiorev.2004.09.006, PMID: 15555683
13. Dalton GL, Wang NY, Phillips AG, Floresco SB. 2016. Multifaceted contributions by different regions of the Orbitofrontal and medial prefrontal cortex to Probabilistic reversal Learning. Journal of Neuroscience 36: 1996-2006. doi: 10.1523/JNEUROSCI.3366-15.2016, PMID: 26865622
14. Dayan P, Kakade S, Montague PR. 2000. Learning and selective attention. Nature Neuroscience 3 Suppl: 1218-1223. doi: 10.1038/81504, PMID: 11127841
15. Diederen KM, Schultz W. 2015. Scaling prediction errors to reward variability benefits error-driven learning in humans. Journal of Neurophysiology 114: 1628–1640. doi: 10.1152/jn.00483.2015, PMID: 26180123
16. Dolan RJ. 2007. The human amygdala and orbital prefrontal cortex in behavioural regulation. Philosophical Transactions of the Royal Society B: Biological Sciences 362: 787–799. doi: 10.1098/rstb.2007.2088, PMID: 17403643
17. Elliott R, Deakin B. 2005. Role of the orbitofrontal cortex in reinforcement processing and inhibitory control: evidence from functional magnetic resonance imaging studies in healthy human subjects. International Review of Neurobiology 65: 89–116. doi: 10.1016/S0074-7742 (04) 65004-5, PMID: 16140054
18. Elliott R, Dolan RJ, Frith CD. 2000. Dissociable functions in the medial and lateral orbitofrontal cortex: evidence from human neuroimaging studies. Cerebral Cortex 10: 308–317. doi: 10.1093/cercor/10.3.308, PMID: 10731225
19. Emery NJ. 2006. Cognitive ornithology: the evolution of avian intelligence. Philosophical Transactions of the Royal Society B: Biological Sciences 361: 23–43. doi: 10.1098/rstb.2005.1736, PMID: 16553307
20. Esber GR, Holland PC. 2014. The basolateral amygdala is necessary for negative prediction errors to enhance cue salience, but not to produce conditioned inhibition. European Journal of Neuroscience 40: 3328–3337. doi: 10.1111/ejn.12695, PMID: 25135841
21. Faraut MC, Procyk E, Wilson CR. 2016. Learning to learn about uncertain feedback. Learning & Memory 23: 90-98. doi: 10.1101/lm.039768.115, PMID: 26787780
22. Fellows LK, Farah MJ. 2003. Ventromedial frontal cortex mediates affective shifting in humans: evidence from a reversal learning paradigm. Brain 126: 1830–1837. doi: 10.1093/brain/awg180, PMID: 12821528
23. Fellows LK, Farah MJ. 2007. The role of ventromedial prefrontal cortex in decision making: judgment under uncertainty or judgment per se? Cerebral Cortex 17: 2669–2674. doi: 10.1093/cercor/bhl176, PMID: 17259643
24. Freeman KB, Green L, Myerson J, Woolverton WL. 2009. Delay discounting of saccharin in rhesus monkeys. Behavioural Processes 82: 214–218. doi: 10.1016/j.beproc.2009.06.002, PMID: 19540317
25. Gallistel CR, Mark TA, King AP, Latham PE. 2001. The rat approximates an ideal detector of changes in rates of reward: implications for the law of effect. Journal of Experimental Psychology: Animal Behavior Processes 27: 354–372. doi: 10.1037/0097-7403.27.4.354, PMID: 11676086
26. Gershman SJ, Niv Y. 2010. Learning latent structure: carving nature at its joints. Current Opinion in Neurobiology 20: 251–256. doi: 10.1016/j.conb.2010.02.008, PMID: 20227271
27. Ghods-Sharifi S, St Onge JR, Floresco SB. 2009. Fundamental contribution by the basolateral amygdala to different forms of decision making. Journal of Neuroscience 29: 5251–5259. doi: 10.1523/JNEUROSCI.0315-09.2009, PMID: 19386921
28. Green L, Myerson J, Oliveira L, Chang SE. 2013. Delay discounting of monetary rewards over a wide range of amounts. Journal of the Experimental Analysis of Behavior 100: 269–281. doi: 10.1002/jeab.45, PMID: 24037826
29. Hart EE, Izquierdo A. 2017. Basolateral amygdala supports the maintenance of value and effortful choice of a preferred option. European Journal of Neuroscience 45: 388–397. doi: 10.1111/ejn.13497, PMID: 27977047
30. Haruno M, Kimura M, Frith CD. 2014. Activity in the nucleus accumbens and amygdala underlies individual differences in prosocial and individualistic economic choices. Journal of Cognitive Neuroscience 26: 1861–1870. doi: 10.1162/jocn_a_00589, PMID: 24564471
31. Hoshino O. 2014. Balanced crossmodal excitation and inhibition essential for maximizing multisensory gain. Neural Computation 26: 1362–1385. doi: 10.1162/NECO_a_00606, PMID: 24708367
32. Hsu M, Bhatt M, Adolphs R, Tranel D, Camerer CF. 2005. Neural systems responding to degrees of uncertainty in human decision-making. Science 310: 1680–1683. doi: 10.1126/science.1115327, PMID: 16339445
33. Hwang J, Kim S, Lee D. 2009. Temporal discounting and inter-temporal choice in rhesus monkeys. Frontiers in Behavioral Neuroscience 3: 9. doi: 10.3389/neuro.08.009.2009, PMID: 19562091
34. Imhof LA, Fudenberg D, Nowak MA. 2007. Tit-for-tat or win-stay, lose-shift? Journal of Theoretical Biology 247: 574–580. doi: 10.1016/j.jtbi.2007.03.027, PMID: 17481667
35. Izquierdo A, Brigman JL, Radke AK, Rudebeck PH, Holmes A. 2017. The neural basis of reversal learning: An updated perspective. Neuroscience 345: 12–26. doi: 10.1016/j.neuroscience.2016.03.021, PMID: 26979052
36. Izquierdo A, Murray EA. 2010. Functional interaction of medial mediodorsal thalamic nucleus but not nucleus accumbens with amygdala and orbital prefrontal cortex is essential for adaptive response selection after reinforcer devaluation. Journal of Neuroscience 30: 661–669. doi: 10.1523/JNEUROSCI.3795-09.2010, PMID: 20071531
37. Izquierdo A, Suda RK, Murray EA. 2004. Bilateral orbital prefrontal cortex lesions in rhesus monkeys disrupt choices guided by both reward value and reward contingency. Journal of Neuroscience 24: 7540–7548. doi: 10.1523/JNEUROSCI.1921-04.2004, PMID: 15329401
38. Khamassi M, Lallée S, Enel P, Procyk E, Dominey PF. 2011. Robot cognitive control with a neurophysiologically inspired reinforcement learning model. Frontiers in Neurorobotics 5: 1. doi: 10.3389/fnbot.2011.00001, PMID: 21808619
39. Lee D, Seo H, Jung MW. 2012. Neural basis of reinforcement learning and decision making. Annual Review of Neuroscience 35: 287–308. doi: 10.1146/annurev-neuro-062111-150512, PMID: 22462543
40. Li J, Schiller D, Schoenbaum G, Phelps EA, Daw ND. 2011. Differential roles of human striatum and amygdala in associative learning. Nature Neuroscience 14: 1250–1252. doi: 10.1038/nn.2904, PMID: 21909088
41. Li Y, Vanni-Mercier G, Isnard J, Mauguière F, Dreher JC. 2016. The neural dynamics of reward value and risk coding in the human orbitofrontal cortex. Brain 139: 1295–1309. doi: 10.1093/brain/awv409, PMID: 26811252
42. Liguz-Lecznar M, Lehner M, Kaliszewska A, Zakrzewska R, Sobolewska A, Kossut M. 2015. Altered glutamate/GABA equilibrium in aged mice cortex influences cortical plasticity. Brain Structure and Function 220: 1681-1693. doi: 10.1007/s00429-014-0752-6, PMID: 24659256
43. Lionel AC, Vaags AK, Sato D, Gazzellone MJ, Mitchell EB, Chen HY, Costain G, Walker S, Egger G, Thiruvahindrapuram B, Merico D, Prasad A, Anagnostou E, Fombonne E, Zwaigenbaum L, Roberts W, Szatmari P, Fernandez BA, Georgieva L, Brzustowicz LM, et al. 2013. Rare exonic deletions implicate the synaptic organizer gephyrin (GPHN) in risk for autism, schizophrenia and seizures. Human Molecular Genetics 22: 2055-2066. doi: 10.1093/hmg/ddt056, PMID: 23393157
44. Lopatina N, Sadacca BF, McDannald MA, Styer CV, Peterson JF, Cheer JF, Schoenbaum G. 2017. Ensembles in medial and lateral orbitofrontal cortex construct cognitive maps emphasizing different features of the behavioral landscape. Behavioral Neuroscience 131: 201–212. doi: 10.1037/bne0000195, PMID: 28541078
45. Marquardt K, Sigdel R, Brigman JL. 2017. Touch-screen visual reversal learning is mediated by value encoding and signal propagation in the orbitofrontal cortex. Neurobiology of Learning and Memory 139: 179–188. doi: 10.1016/j.nlm.2017.01.006, PMID: 28111339
46. Mazur JE, Biondi DR. 2009. Delay-amount tradeoffs in choices by pigeons and rats: hyperbolic versus exponential discounting. Journal of the Experimental Analysis of Behavior 91: 197–211. doi: 10.1901/jeab.2009.91-197, PMID: 19794834
47. McDannald MA, Lucantonio F, Burke KA, Niv Y, Schoenbaum G. 2011. Ventral striatum and orbitofrontal cortex are both required for model-based, but not model-free, reinforcement learning. Journal of Neuroscience 31: 2700–2705. doi: 10.1523/JNEUROSCI.5499-10.2011, PMID: 21325538
48. McDannald MA, Saddoris MP, Gallagher M, Holland PC. 2005. Lesions of orbitofrontal cortex impair rats’ differential outcome expectancy learning but not conditioned stimulus-potentiated feeding. Journal of Neuroscience 25: 4626–4632. doi: 10.1523/JNEUROSCI.5301-04.2005, PMID: 15872110
49. Merlo E, Ratano P, Ilioi EC, Robbins MA, Everitt BJ, Milton AL. 2015. Amygdala dopamine receptors are required for the destabilization of a reconsolidating appetitive memory (1, 2). eNeuro 2: ENEURO.0024-14.2015. doi: 10.1523/ENEURO.0024-14.2015, PMID: 26464966
50. Mitchell SH, Wilson VB, Karalunas SL. 2015. Comparing hyperbolic, delay-amount sensitivity and present-bias models of delay discounting. Behavioural Processes 114: 52–62. doi: 10.1016/j.beproc.2015.03.006, PMID: 25796454
51. Morris LS, Kundu P, Dowell N, Mechelmans DJ, Favre P, Irvine MA, Robbins TW, Daw N, Bullmore ET, Harrison NA, Voon V. 2016. Fronto-striatal organization: defining functional and microstructural substrates of behavioural flexibility. Cortex 74: 118–133. doi: 10.1016/j.cortex.2015.11.004, PMID: 26673945
52. Motanis H, Maroun M, Barkai E. 2014. Learning-induced bidirectional plasticity of intrinsic neuronal excitability reflects the valence of the outcome. Cerebral Cortex 24: 1075–1087. doi: 10.1093/cercor/bhs394, PMID: 23236201
53. Murray EA, Izquierdo A. 2007. Orbitofrontal cortex and amygdala contributions to affect and action in primates. Annals of the New York Academy of Sciences 1121: 273–296. doi: 10.1196/annals.1401.021, PMID: 17846154
54. Nassar MR, Wilson RC, Heasly B, Gold JI. 2010. An approximately bayesian delta-rule model explains the dynamics of belief updating in a changing environment. Journal of Neuroscience 30: 12366–12378. doi: 10.1523/JNEUROSCI.0822-10.2010, PMID: 20844132
55. Niv Y, Daniel R, Geana A, Gershman SJ, Leong YC, Radulescu A, Wilson RC. 2015. Reinforcement learning in multidimensional environments relies on attention mechanisms. Journal of Neuroscience 35: 8145–8157. doi: 10.1523/JNEUROSCI.2978-14.2015, PMID: 26019331
56. Ostrander S, Cazares VA, Kim C, Cheung S, Gonzalez I, Izquierdo A. 2011. Orbitofrontal cortex and basolateral amygdala lesions result in suboptimal and dissociable reward choices on cue-guided effort in rats. Behavioral Neuroscience 125: 350–359. doi: 10.1037/a0023574, PMID: 21639604
57. Padoa-Schioppa C, Schoenbaum G. 2015. Dialogue on economic choice, learning theory, and neuronal representations. Current Opinion in Behavioral Sciences 5: 16–23. doi: 10.1016/j.cobeha.2015.06.004, PMID: 26613099
58. Padoa-Schioppa C. 2007. Orbitofrontal cortex and the computation of economic value. Annals of the New York Academy of Sciences 1121: 232–253. doi: 10.1196/annals.1401.011, PMID: 17698992
59. Padoa-Schioppa C. 2009. Range-adapting representation of economic value in the orbitofrontal cortex. Journal of Neuroscience 29: 14004–14014. doi: 10.1523/JNEUROSCI.3751-09.2009, PMID: 19890010
60. Paton JJ, Belova MA, Morrison SE, Salzman CD. 2006. The primate amygdala represents the positive and negative value of visual stimuli during learning. Nature 439: 865–870. doi: 10.1038/nature04490, PMID: 16482160
61. Paxinos G, Watson C. 1997. The Rat Brainin Stereotaxic Coordinates. Cambridge: Academic Press.
62. Payzan-LeNestour E, Bossaerts P. 2011. Risk, unexpected uncertainty, and estimation uncertainty: bayesian learning in unstable settings. PLoS Computational Biology 7: e1001048. doi: 10.1371/journal.pcbi.1001048, PMID: 21283774
63. Pearce JM, Hall G. 1980. A model for pavlovian learning: variations in the effectiveness of conditioned but not of unconditioned stimuli. Psychological Review 87: 532–552. doi: 10.1037/0033-295X.87.6.532, PMID: 7443916
64. Pearson JM, Platt ML. 2013. Change detection, multiple controllers, and dynamic environments: insights from the brain. Journal of the Experimental Analysis of Behavior 99: 74–84. doi: 10.1002/jeab.5, PMID: 23344989
65. Potts R. 2004. Paleoenvironmental basis of cognitive evolution in great apes. American Journal of Primatology 62: 209–228. doi: 10.1002/ajp.20016, PMID: 15027093
66. Preuschoff K, Bossaerts P. 2007. Adding prediction risk to the theory of reward learning. Annals of the New York Academy of Sciences 1104: 135–146. doi: 10.1196/annals.1390.005, PMID: 17344526
67. Rachlin H, Raineri A, Cross D. 1991. Subjective probability and delay. Journal of the Experimental Analysis of Behavior 55: 233–244. doi: 10.1901/jeab.1991.55-233, PMID: 2037827
68. Ramirez DR, Savage LM. 2007. Differential involvement of the basolateral amygdala, orbitofrontal cortex, and nucleus accumbens core in the acquisition and use of reward expectancies. Behavioral Neuroscience 121: 896-906. doi: 10.1037/0735-7044.121.5.896, PMID: 17907822
69. Riceberg JS, Shapiro ML. 2012. Reward stability determines the contribution of orbitofrontal cortex to adaptive behavior. Journal of Neuroscience 32: 16402–16409. doi: 10.1523/JNEUROSCI.0776-12.2012, PMID: 23152622
70. Riceberg JS, Shapiro ML. 2017. Orbitofrontal Cortex signals expected outcomes with predictive codes when stable contingencies promote the integration of reward history. The Journal of Neuroscience 37: 2010–2021. doi: 10.1523/JNEUROSCI.2951-16.2016, PMID: 28115481
71. Roesch MR, Calu DJ, Esber GR, Schoenbaum G. 2010. Neural correlates of variations in event processing during learning in basolateral amygdala. Journal of Neuroscience 30: 2464–2471. doi: 10.1523/JNEUROSCI.5781-09.2010, PMID: 20164330
72. Rössert C, Moore LE, Straka H, Glasauer S. 2011. Cellular and network contributions to vestibular signal processing: impact of ion conductances, synaptic inhibition, and noise. Journal of Neuroscience 31: 8359–8372. doi: 10.1523/JNEUROSCI.6161-10.2011, PMID: 21653841
73. Rudebeck PH, Murray EA. 2014. The orbitofrontal oracle: cortical mechanisms for the prediction and evaluation of specific behavioral outcomes. Neuron 84: 1143–1156. doi: 10.1016/j.neuron.2014.10.049, PMID: 25521376
74. Salinas JA, Parent MB, McGaugh JL. 1996. Ibotenic acid lesions of the amygdala basolateral complex or central nucleus differentially effect the response to reductions in reward. Brain Research 742: 283–293. doi: 10.1016/S0006-8993 (96) 01030-X, PMID: 9117406
75. Salzman CD, Paton JJ, Belova MA, Morrison SE. 2007. Flexible neural representations of value in the primate brain. Annals of the New York Academy of Sciences 1121: 336–354. doi: 10.1196/annals.1401.034, PMID: 17872400
76. Savage LM, Koch AD, Ramirez DR. 2007. Basolateral amygdala inactivation by muscimol, but not ERK/MAPK inhibition, impairs the use of reward expectancies during working memory. European Journal of Neuroscience 26: 3645–3651. doi: 10.1111/j.1460-9568.2007.05959.x, PMID: 18052977
77. Schoenbaum G, Roesch MR, Stalnaker TA, Takahashi YK. 2011a. Orbitofrontal Cortex and Outcome Expectancies: Optimizing Behavior and Sensory Perception. In: Gottfried J. A (Ed). Neurobiology of Sensation and Reward. Boca Raton: CRC Press/Taylor & Francis.
78. Schoenbaum G, Takahashi Y, Liu TL, McDannald MA. 2011b. Does the orbitofrontal cortex signal value? Annals of the New York Academy of Sciences 1239: 87–99. doi: 10.1111/j.1749-6632.2011.06210.x, PMID: 22145878
79. Schuck NW, Cai MB, Wilson RC, Niv Y. 2016. Human Orbitofrontal Cortex represents a cognitive map of State Space. Neuron 91: 1402–1412. doi: 10.1016/j.neuron.2016.08.019, PMID: 27657452
80. Soares C, Lee KF, Nassrallah W, Béıque JC. 2013. Differential subcellular targeting of glutamate receptor subtypes during homeostatic synaptic plasticity. Journal of Neuroscience 33: 13547–13559. doi: 10.1523/JNEUROSCI.1873-13.2013, PMID: 23946413
81. Stalnaker TA, Cooch NK, Schoenbaum G. 2015. What the orbitofrontal cortex does not do. Nature Neuroscience 18: 620–627. doi: 10.1038/nn.3982, PMID: 25919962
82. Steppan SJ, Storz BL, Hoffmann RS. 2004. Nuclear DNA phylogeny of the squirrels (Mammalia: rodentia) and the evolution of arboreality from c-myc and RAG1. Molecular Phylogenetics and Evolution 30: 703–719. doi: 10.1016/S1055-7903 (03) 00204-5, PMID: 15012949
83. Stopper CM, Green EB, Floresco SB. 2014. Selective involvement by the medial orbitofrontal cortex in biasing risky, but not impulsive, choice. Cerebral Cortex 24: 154–162. doi: 10.1093/cercor/bhs297, PMID: 23042736
84. Sugrue LP, Corrado GS, Newsome WT. 2005. Choosing the greater of two goods: neural currencies for valuation and decision making. Nature Reviews Neuroscience 6: 363–375. doi: 10.1038/nrn1666, PMID: 15832198
85. Tyagarajan SK, Ghosh H, Yévenes GE, Nikonenko I, Ebeling C, Schwerdel C, Sidler C, Zeilhofer HU, Gerrits B, Muller D, Fritschy JM. 2011. Regulation of GABAergic synapse formation and plasticity by GSK3beta-dependent phosphorylation of gephyrin. PNAS 108: 379–384. doi: 10.1073/pnas.1011824108, PMID: 21173228
86. van Duuren E, van der Plasse G, Lankelma J, Joosten RN, Feenstra MG, Pennartz CM. 2009. Single-cell and population coding of expected reward probability in the orbitofrontal cortex of the rat. Journal of Neuroscience 29: 8965–8976. doi: 10.1523/JNEUROSCI.0005-09.2009, PMID: 19605634
87. Walton ME, Behrens TE, Buckley MJ, Rudebeck PH, Rushworth MF. 2010. Separable learning systems in the macaque brain and the role of orbitofrontal cortex in contingent learning. Neuron 65: 927–939. doi: 10.1016/j. neuron.2010.02.027, PMID: 20346766
88. Walton ME, Behrens TE, Noonan MP, Rushworth MF. 2011. Giving credit where credit is due: orbitofrontal cortex and valuation in an uncertain world. Annals of the New York Academy of Sciences 1239: 14–24. doi: 10.1111/j.1749-6632.2011.06257.x, PMID: 22145871
89. Wassum KM, Izquierdo A. 2015. The basolateral amygdala in reward learning and addiction. Neuroscience & Biobehavioral Reviews 57: 271–283. doi: 10.1016/j.neubiorev.2015.08.017, PMID: 26341938
90. Wilson RC, Takahashi YK, Schoenbaum G, Niv Y. 2014. Orbitofrontal cortex as a cognitive map of task space. Neuron 81: 267–279. doi: 10.1016/j.neuron.2013.11.005, PMID: 24462094
91. Winstanley CA, Clark L. 2016a. Translational models of Gambling-Related Decision-Making. Current Topics in Behavioral Neurosciences 28: 93–120. doi: 10.1007/7854_2015_5014, PMID: 27418069
92. Winstanley CA, Floresco SB. 2016b. Deciphering decision making: variation in Animal models of effort-and Uncertainty-Based choice reveals distinct neural circuitries underlying Core Cognitive Processes. Journal of Neuroscience 36: 12069–12079. doi: 10.1523/JNEUROSCI.1713-16.2016, PMID: 27903717
93. Winstanley CA. 2007. The orbitofrontal cortex, impulsivity, and addiction: probing orbitofrontal dysfunction at the neural, neurochemical, and molecular level. Annals of the New York Academy of Sciences 1121: 639–655. doi: 10.1196/annals.1401.024, PMID: 17846162
94. Wolff SB, Gründemann J, Tovote P, Krabbe S, Jacobson GA, Müller C, Herry C, Ehrlich I, Friedrich RW, Letzkus JJ, Lüthi A. 2014. Amygdala interneuron subtypes control fear learning through disinhibition. Nature 509: 453-458. doi: 10.1038/nature13258, PMID: 24814341
95. Worthy DA, Hawthorne MJ, Otto AR. 2013. Heterogeneity of strategy use in the Iowa gambling task: a comparison of win-stay/lose-shift and reinforcement learning models. Psychonomic Bulletin & Review 20: 364-371. doi: 10.3758/s13423-012-0324-9, PMID: 23065763
96. Yates JR, Batten SR, Bardo MT, Beckmann JS. 2015. Role of ionotropic glutamate receptors in delay and probability discounting in the rat. Psychopharmacology 232: 1187–1196. doi: 10.1007/s00213-014-3747-3, PMID: 25270726
97. Yu AJ, Dayan P. 2005. Uncertainty, neuromodulation, and attention. Neuron 46: 681–692. doi: 10.1016/j.neuron. 2005.04.026, PMID: 15944135
98. Zeeb FD, Winstanley CA. 2011. Lesions of the basolateral amygdala and orbitofrontal cortex differentially affect acquisition and performance of a rodent gambling task. Journal of Neuroscience 31: 2197–2204. doi: 10.1523/ JNEUROSCI.5597-10.2011, PMID: 21307256