Contributions of the Basal Ganglia to Visual Perceptual Decisions

Literature Cited

1. Albin RL, van der Zee S, van Laar T, Sarter M, Lustig C et al. 2022. Cholinergic systems, attentional-motor integration, and cognitive control in Parkinson's disease. Prog. Brain Res. 269:345–71
   [Google Scholar]
2. Albin RL, Young AB, Penney JB. 1989. The functional anatomy of basal ganglia disorders. Trends Neurosci. 12:10366–75
   [Google Scholar]
3. Alexander GE, Crutcher MD. 1990. Functional architecture of basal ganglia circuits: neural substrates of parallel processing. Trends Neurosci. 13:7266–71
   [Google Scholar]
4. Alexander GE, DeLong MR, Strick PL. 1986. Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu. Rev. Neurosci. 9:357–81
   [Google Scholar]
5. Antzoulatos EG, Miller EK. 2011. Differences between neural activity in prefrontal cortex and striatum during learning of novel abstract categories. Neuron 71:2243–49
   [Google Scholar]
6. Apicella P. 2017. The role of the intrinsic cholinergic system of the striatum: What have we learned from TAN recordings in behaving animals?. Neuroscience 360:81–94
   [Google Scholar]
7. Arcizet F, Krauzlis RJ. 2018. Covert spatial selection in primate basal ganglia. PLOS Biol. 16:10e2005930
   [Google Scholar]
8. Bang D, Fleming SM. 2018. Distinct encoding of decision confidence in human medial prefrontal cortex. PNAS 115:236082–87
   [Google Scholar]
9. Barlow HB. 1956. Retinal noise and absolute threshold. J. Opt. Soc. Am. 46:8634–39
   [Google Scholar]
10. Basso MA, Liu P. 2007. Context-dependent effects of substantia nigra stimulation on eye movements. J. Neurophysiol. 97:64129–42
    [Google Scholar]
11. Basso MA, Wurtz RH. 2002. Neuronal activity in substantia nigra pars reticulata during target selection. J. Neurosci. 22:51883–94
    [Google Scholar]
12. Bergman H, Wichmann T, DeLong MR. 1990. Reversal of experimental parkinsonism by lesions of the subthalamic nucleus. Science 249:49751436–38
    [Google Scholar]
13. Berns GS, Sejnowski TJ 1995. How the basal ganglia make decisions. Neurobiology of Decision-Making AR Damasio, H Damasio, Y Christen 101–13. Berlin: Springer
    [Google Scholar]
14. Bitzer S, Park H, Blankenburg F, Kiebel SJ. 2014. Perceptual decision making: drift-diffusion model is equivalent to a Bayesian model. Front. Hum. Neurosci. 8:102
    [Google Scholar]
15. 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. 113:4700–65
    [Google Scholar]
16. Bogacz R, Gurney K. 2007. The basal ganglia and cortex implement optimal decision making between alternative actions. Neural Comput. 19:2442–77
    [Google Scholar]
17. Bogacz R, Larsen T. 2011. Integration of reinforcement learning and optimal decision-making theories of the basal ganglia. Neural Comput. 23:4817–51
    [Google Scholar]
18. Bogadhi AR, Bollimunta A, Leopold DA, Krauzlis RJ. 2018. Brain regions modulated during covert visual attention in the macaque. Sci. Rep. 8:15237
    [Google Scholar]
19. Bromberg-Martin ES, Matsumoto M, Hikosaka O. 2010. Dopamine in motivational control: rewarding, aversive, and alerting. Neuron 68:5815–34
    [Google Scholar]
20. Buerger AA, Gross CG, Rocha-Miranda CE. 1974. Effects of ventral putamen lesions on discrimination learning by monkeys. J. Comp. Physiol. Psychol. 86:3440–46
    [Google Scholar]
21. Buzzell GA, Roberts DM, Fedota JR, Thompson JC, Parasuraman R, McDonald CG. 2016. Uncertainty-dependent activity within the ventral striatum predicts task-related changes in response strategy. Cogn. Affect. Behav. Neurosci. 16:2219–33
    [Google Scholar]
22. Caspari N, Janssens T, Mantini D, Vandenberghe R, Vanduffel W. 2015. Covert shifts of spatial attention in the macaque monkey. J. Neurosci. 35:207695–714
    [Google Scholar]
23. Cavanagh JF, Wiecki TV, Cohen MX, Figueroa CM, Samanta J et al. 2011. Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold. Nat. Neurosci. 14:111462–67
    [Google Scholar]
24. Cepeda C, Andre VM, Yamazaki I, Wu N, Kleiman-Weiner M, Levine MS. 2008. Differential electrophysiological properties of dopamine D1 and D2 receptor-containing striatal medium-sized spiny neurons. Eur. J. Neurosci. 27:3671–82
    [Google Scholar]
25. Chen MY, Jimura K, White CN, Maddox WT, Poldrack RA. 2015. Multiple brain networks contribute to the acquisition of bias in perceptual decision-making. Front. Neurosci 9:63
    [Google Scholar]
26. Coulthard EJ, Bogacz R, Javed S, Mooney LK, Murphy G et al. 2012. Distinct roles of dopamine and subthalamic nucleus in learning and probabilistic decision making. Brain 135:3721–34
    [Google Scholar]
27. Cowan WM, Powell TP. 1956. A study of thalamo-striate relations in the monkey. Brain 79:2364–90
    [Google Scholar]
28. de Lafuente V, Romo R. 2011. Dopamine neurons code subjective sensory experience and uncertainty of perceptual decisions. PNAS 108:4919767–71
    [Google Scholar]
29. DeLong MR. 1990. Primate models of movement disorders of basal ganglia origin. Trends Neurosci. 13:7281–85
    [Google Scholar]
30. Ding L. 2015. Distinct dynamics of ramping activity in the frontal cortex and caudate nucleus in monkeys. J. Neurophysiol. 114:31850–61
    [Google Scholar]
31. Ding L, Gold JI. 2010. Caudate encodes multiple computations for perceptual decisions. J. Neurosci. 30:4715747–59
    [Google Scholar]
32. Ding L, Gold JI. 2012a. Neural correlates of perceptual decision making before, during, and after decision commitment in monkey frontal eye field. Cereb. Cortex 22:51052–67
    [Google Scholar]
33. Ding L, Gold JI. 2012b. Separate, causal roles of the caudate in saccadic choice and execution in a perceptual decision task. Neuron 75:5865–74
    [Google Scholar]
34. Divac I, Rosvold HE, Szwarcbart MK. 1967. Behavioral effects of selective ablation of the caudate nucleus. J. Comp. Physiol. Psychol. 63:2184–90
    [Google Scholar]
35. Doi T, Fan Y, Gold JI, Ding L. 2020. The caudate nucleus contributes causally to decisions that balance reward and uncertain visual information. eLife 9:e56694
    [Google Scholar]
36. Downes JJ, Roberts AC, Sahakian BJ, Evenden JL, Morris RG, Robbins TW. 1989. Impaired extra-dimensional shift performance in medicated and unmedicated Parkinson's disease: evidence for a specific attentional dysfunction. Neuropsychologia 27:11–121329–43
    [Google Scholar]
37. Drugowitsch J, Moreno-Bote R, Churchland AK, Shadlen MN, Pouget A. 2012. The cost of accumulating evidence in perceptual decision making. J. Neurosci. 32:113612–28
    [Google Scholar]
38. Ell SW, Marchant NL, Ivry RB. 2006. Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks. Neuropsychologia 44:101737–51
    [Google Scholar]
39. Fan Y, Gold JI, Ding L. 2018. Ongoing, rational calibration of reward-driven perceptual biases. eLife 7:e36018
    [Google Scholar]
40. Fan Y, Gold JI, Ding L. 2020. Frontal eye field and caudate neurons make different contributions to reward-biased perceptual decisions. eLife 9:e60535
    [Google Scholar]
41. Ferrier D. 1873. Experimental researches in cerebral physiology and pathology. J. Anat. Physiol. 8:Pt 1152–55
    [Google Scholar]
42. Filimon F, Philiastides MG, Nelson JD, Kloosterman NA, Heekeren HR. 2013. How embodied is perceptual decision making? Evidence for separate processing of perceptual and motor decisions. J. Neurosci. 33:52121–36
    [Google Scholar]
43. Fiorillo CD, Yun SR, Song MR. 2013. Diversity and homogeneity in responses of midbrain dopamine neurons. J. Neurosci. 33:114693–709
    [Google Scholar]
44. Flaherty AW, Graybiel AM. 1991. Corticostriatal transformations in the primate somatosensory system. Projections from physiologically mapped body-part representations. J. Neurophysiol. 66:41249–63
    [Google Scholar]
45. Fleming SM, Whiteley L, Hulme OJ, Sahani M, Dolan RJ. 2010. Effects of category-specific costs on neural systems for perceptual decision-making. J. Neurophysiol. 103:63238–47
    [Google Scholar]
46. Forstmann BU, Anwander A, Schafer A, Neumann J, Brown S et al. 2010a. Cortico-striatal connections predict control over speed and accuracy in perceptual decision making. PNAS 107:3615916–20
    [Google Scholar]
47. Forstmann BU, Brown S, Dutilh G, Neumann J, Wagenmakers E-J. 2010b. The neural substrate of prior information in perceptual decision making: a model-based analysis. Front. Hum. Neurosci. 4:40
    [Google Scholar]
48. Forstmann BU, Dutilh G, Brown S, Neumann J, von Cramon DY et al. 2008. Striatum and pre-SMA facilitate decision-making under time pressure. PNAS 105:4517538–42
    [Google Scholar]
49. Frank MJ, Samanta J, Moustafa AA, Sherman SJ. 2007. Hold your horses: impulsivity, deep brain stimulation, and medication in parkinsonism. Science 318:58541309–12
    [Google Scholar]
50. Gerfen CR. 1984. The neostriatal mosaic: compartmentalization of corticostriatal input and striatonigral output systems. Nature 311:5985461–64
    [Google Scholar]
51. Gerfen CR, Engber TM, Mahan LC, Susel Z, Chase TN et al. 1990. D1 and D2 dopamine receptor-regulated gene expression of striatonigral and striatopallidal neurons. Science 250:49861429–32
    [Google Scholar]
52. Gibson JJ. 1966. The Senses Considered as Perceptual Systems Boston: Houghton-Mifflin
53. Gold JI, Shadlen MN. 2002. Banburismus and the brain: decoding the relationship between sensory stimuli, decisions, and reward. Neuron 36:2299–308
    [Google Scholar]
54. Gold JI, Shadlen MN. 2007. The neural basis of decision making. Annu. Rev. Neurosci. 30:535–74
    [Google Scholar]
55. Graybiel AM, Aosaki T, Flaherty AW, Kimura M. 1994. The basal ganglia and adaptive motor control. Science 265:51801826–31
    [Google Scholar]
56. Green DM, Swets JA. 1966. Signal Detection Theory and Psychophysics New York: Wiley
57. Green N, Biele GP, Heekeren HR. 2012. Changes in neural connectivity underlie decision threshold modulation for reward maximization. J. Neurosci. 32:4314942–50
    [Google Scholar]
58. Green N, Bogacz R, Huebl J, Beyer AK, Kuhn AA, Heekeren HR. 2013. Reduction of influence of task difficulty on perceptual decision making by STN deep brain stimulation. Curr. Biol. 23:171681–84
    [Google Scholar]
59. Griffith T, Baker S-A, Lepora NF. 2021. The statistics of optimal decision making: exploring the relationship between signal detection theory and sequential analysis. J. Math. Psychol. 103:102544
    [Google Scholar]
60. Grinband J, Hirsch J, Ferrera VP. 2006. A neural representation of categorization uncertainty in the human brain. Neuron 49:5757–63
    [Google Scholar]
61. Guggenmos M, Wilbertz G, Hebart MN, Sterzer P. 2016. Mesolimbic confidence signals guide perceptual learning in the absence of external feedback. eLife 5:e13388
    [Google Scholar]
62. Haber SN. 2003. The primate basal ganglia: parallel and integrative networks. J. Chem. Neuroanat. 26:4317–30
    [Google Scholar]
63. Hanks TD, Ditterich J, Shadlen MN. 2006. Microstimulation of macaque area LIP affects decision-making in a motion discrimination task. Nat. Neurosci. 9:5682–89
    [Google Scholar]
64. Hanks TD, Kopec CD, Brunton BW, Duan CA, Erlich JC, Brody CD. 2015. Distinct relationships of parietal and prefrontal cortices to evidence accumulation. Nature 520:7546220–23
    [Google Scholar]
65. Hanks TD, Mazurek ME, Kiani R, Hopp E, Shadlen MN. 2011. Elapsed decision time affects the weighting of prior probability in a perceptual decision task. J. Neurosci. 31:176339–52
    [Google Scholar]
66. Hebart MN, Schriever Y, Donner TH, Haynes J-D. 2016. The relationship between perceptual decision variables and confidence in the human brain. Cereb. Cortex 26:1118–30
    [Google Scholar]
67. Heitz RP. 2014. The speed-accuracy tradeoff: history, physiology, methodology, and behavior. Front. Neurosci. 8:150
    [Google Scholar]
68. Herz DM, Tan H, Brittain JS, Fischer P, Cheeran B et al. 2017. Distinct mechanisms mediate speed-accuracy adjustments in cortico-subthalamic networks. eLife 6:e21481
    [Google Scholar]
69. Herz DM, Zavala BA, Bogacz R, Brown P. 2016. Neural correlates of decision thresholds in the human subthalamic nucleus. Curr. Biol. 26:7916–20
    [Google Scholar]
70. Hikosaka O, Sakamoto M, Usui S. 1989. Functional properties of monkey caudate neurons. II. Visual and auditory responses. J. Neurophysiol. 61:4799–813
    [Google Scholar]
71. Hsiao PY, Lo CC. 2013. A plastic corticostriatal circuit model of adaptation in perceptual decision making. Front. Comput. Neurosci. 7:178
    [Google Scholar]
72. Huang Y, Rao RP. 2013. Reward optimization in the primate brain: a probabilistic model of decision making under uncertainty. PLOS ONE 8:1e53344
    [Google Scholar]
73. Isoda M, Hikosaka O. 2008. Role for subthalamic nucleus neurons in switching from automatic to controlled eye movement. J. Neurosci. 28:287209–18
    [Google Scholar]
74. Ito M, Doya K. 2011. Multiple representations and algorithms for reinforcement learning in the cortico-basal ganglia circuit. Curr. Opin. Neurobiol. 21:368–73
    [Google Scholar]
75. Jantz JJ, Watanabe M, Levy R, Munoz DP. 2017. Evidence for a task-dependent switch in subthalamo-nigral basal ganglia signaling. Nat. Commun. 8:1039
    [Google Scholar]
76. Kable JW, Glimcher PW. 2009. The neurobiology of decision: consensus and controversy. Neuron 63:6733–45
    [Google Scholar]
77. Kawagoe R, Takikawa Y, Hikosaka O. 1998. Expectation of reward modulates cognitive signals in the basal ganglia. Nat. Neurosci. 1:5411–16
    [Google Scholar]
78. Khalvati K, Kiani R, Rao RPN. 2021. Bayesian inference with incomplete knowledge explains perceptual confidence and its deviations from accuracy. Nat. Commun. 12:5704
    [Google Scholar]
79. Krauzlis RJ, Bollimunta A, Arcizet F, Wang L. 2014. Attention as an effect not a cause. Trends Cogn. Sci. 18:9457–64
    [Google Scholar]
80. Lak A, Nomoto K, Keramati M, Sakagami M, Kepecs A. 2017. Midbrain dopamine neurons signal belief in choice accuracy during a perceptual decision. Curr. Biol. 27:6821–32
    [Google Scholar]
81. Lak A, Okun M, Moss MM, Gurnani H, Farrell K et al. 2020. Dopaminergic and prefrontal basis of learning from sensory confidence and reward value. Neuron 105:4700–11.e6
    [Google Scholar]
82. Lo CC, Wang XJ. 2006. Cortico-basal ganglia circuit mechanism for a decision threshold in reaction time tasks. Nat. Neurosci. 9:7956–63
    [Google Scholar]
83. Maddox WT, Aparicio P, Marchant NL, Ivry RB. 2005. Rule-based category learning is impaired in patients with Parkinson's disease but not in patients with cerebellar disorders. J. Cogn. Neurosci. 17:5707–23
    [Google Scholar]
84. Mansfield EL, Karayanidis F, Jamadar S, Heathcote A, Forstmann BU. 2011. Adjustments of response threshold during task switching: a model-based functional magnetic resonance imaging study. J. Neurosci. 31:4114688–92
    [Google Scholar]
85. Merchant H, Zainos A, Hernandez A, Salinas E, Romo R. 1997. Functional properties of primate putamen neurons during the categorization of tactile stimuli. J. Neurophysiol. 77:31132–54
    [Google Scholar]
86. Mink JW. 1996. The basal ganglia: focused selection and inhibition of competing motor programs. Prog. Neurobiol. 50:4381–425
    [Google Scholar]
87. Moss M, Zatka-Haas P, Harris K, Carandini M, Lak A. 2021. Dopamine axons in dorsal striatum encode contralateral visual stimuli and choices. J. Neurosci. 41:347197–205
    [Google Scholar]
88. Muhammad R, Wallis JD, Miller EK. 2006. A comparison of abstract rules in the prefrontal cortex, premotor cortex, inferior temporal cortex, and striatum. J. Cogn. Neurosci. 18:6974–89
    [Google Scholar]
89. Mulder MJ, Wagenmakers EJ, Ratcliff R, Boekel W, Forstmann BU. 2012. Bias in the brain: a diffusion model analysis of prior probability and potential payoff. J. Neurosci. 32:72335–43
    [Google Scholar]
90. Nagano-Saito A, Cisek P, Perna AS, Shirdel FZ, Benkelfat C et al. 2012. From anticipation to action, the role of dopamine in perceptual decision making: an fMRI-tyrosine depletion study. J. Neurophysiol. 108:2501–12
    [Google Scholar]
91. Nakamura K, Ding L. 2017. Parsing heterogeneous striatal activity. Front. Neuroanat. 11:43
    [Google Scholar]
92. Nomoto K, Schultz W, Watanabe T, Sakagami M. 2010. Temporally extended dopamine responses to perceptually demanding reward-predictive stimuli. J. Neurosci. 30:3210692–702
    [Google Scholar]
93. Nomura EM, Reber PJ. 2008. A review of medial temporal lobe and caudate contributions to visual category learning. Neurosci. Biobehav. Rev. 32:2279–91
    [Google Scholar]
94. Oorschot DE 2010. Cell types in the different nuclei of the basal ganglia. Handbook of Behavioral Neuroscience, Vol. 20 H Steiner, KY Tseng 63–74. Amsterdam: Elsevier
    [Google Scholar]
95. Parent A, Hazrati LN. 1993. Anatomical aspects of information processing in primate basal ganglia. Trends Neurosci. 16:3111–16
    [Google Scholar]
96. Parent A, Mackey A, De Bellefeuille L. 1983. The subcortical afferents to caudate nucleus and putamen in primate: a fluorescence retrograde double labeling study. Neuroscience 10:41137–50
    [Google Scholar]
97. Pasupathy A, Miller EK. 2005. Different time courses of learning-related activity in the prefrontal cortex and striatum. Nature 433:7028873–76
    [Google Scholar]
98. Perugini A, Ditterich J, Basso MA. 2016. Patients with Parkinson's disease show impaired use of priors in conditions of sensory uncertainty. Curr. Biol. 26:141902–10
    [Google Scholar]
99. Preuschhof C, Schubert T, Villringer A, Heekeren HR. 2010. Prior information biases stimulus representations during vibrotactile decision making. J. Cogn. Neurosci. 22:5875–87
    [Google Scholar]
100. Rao RP. 2010. Decision making under uncertainty: a neural model based on partially observable Markov decision processes. Front. Comput. Neurosci. 4:146
     [Google Scholar]
101. Rao V, DeAngelis GC, Snyder LH. 2012. Neural correlates of prior expectations of motion in the lateral intraparietal and middle temporal areas. J. Neurosci. 32:2910063–74
     [Google Scholar]
102. Ratcliff R. 1978. Theory of memory retrieval. Psychol. Rev. 85:259–108
     [Google Scholar]
103. Ratcliff R, Frank MJ. 2012. Reinforcement-based decision making in corticostriatal circuits: mutual constraints by neurocomputational and diffusion models. Neural Comput. 24:51186–229
     [Google Scholar]
104. Ratcliff R, Smith PL, Brown SD, McKoon G. 2016. Diffusion decision model: current issues and history. Trends Cogn. Sci. 20:4260–81
     [Google Scholar]
105. Redgrave P, Prescott TJ, Gurney K. 1999. The basal ganglia: a vertebrate solution to the selection problem?. Neuroscience 89:41009–23
     [Google Scholar]
106. Roitman JD, Shadlen MN. 2002. Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. J. Neurosci. 22:219475–89
     [Google Scholar]
107. Samejima K, Doya K. 2007. Multiple representations of belief states and action values in corticobasal ganglia loops. Ann. N. Y. Acad. Sci. 1104:213–28
     [Google Scholar]
108. Scheibe C, Ullsperger M, Sommer W, Heekeren HR. 2010. Effects of parametrical and trial-to-trial variation in prior probability processing revealed by simultaneous electroencephalogram/functional magnetic resonance imaging. J. Neurosci. 30:4916709–17
     [Google Scholar]
109. Schmidt R, Leventhal DK, Mallet N, Chen F, Berke JD 2013. Canceling actions involves a race between basal ganglia pathways. Nat. Neurosci. 16:81118–24
     [Google Scholar]
110. Schor JS, Gonzalez Montalvo I, Spratt PWE, Brakaj RJ, Stansil JA et al. 2022. Therapeutic deep brain stimulation disrupts movement-related subthalamic nucleus activity in parkinsonian mice. eLife 11:e75253
     [Google Scholar]
111. Schultz W. 1998. Predictive reward signal of dopamine neurons. J. Neurophysiol. 80:11–27
     [Google Scholar]
112. Schultz W. 2019. Recent advances in understanding the role of phasic dopamine activity. F1000Research 8:1680
     [Google Scholar]
113. Seger CA, Cincotta CM. 2005. The roles of the caudate nucleus in human classification learning. J. Neurosci. 25:112941–51
     [Google Scholar]
114. Selemon LD, Goldman-Rakic PS. 1985. Longitudinal topography and interdigitation of corticostriatal projections in the rhesus monkey. J. Neurosci. 5:776–94
     [Google Scholar]
115. Seo M, Lee E, Averbeck BB 2012. Action selection and action value in frontal-striatal circuits. Neuron 74:5947–60
     [Google Scholar]
116. Sharpe MH. 1990. Distractibility in early Parkinson's disease. Cortex 26:2239–46
     [Google Scholar]
117. Shin S, Sommer MA. 2010. Activity of neurons in monkey globus pallidus during oculomotor behavior compared with that in substantia nigra pars reticulata. J. Neurophysiol. 103:41874–87
     [Google Scholar]
118. Simen P, Contreras D, Buck C, Hu P, Holmes P, Cohen JD. 2009. Reward rate optimization in two-alternative decision making: empirical tests of theoretical predictions. J. Exp. Psychol. Hum. Percept. Perform. 35:61865–97
     [Google Scholar]
119. Sprague JM. 1966. Interaction of cortex and superior colliculus in mediation of visually guided behavior in the cat. Science 153:37431544–47
     [Google Scholar]
120. Stone M. 1960. Models for choice-reaction time. Psychometrika 25:3251–60
     [Google Scholar]
121. Summerfield C, Koechlin E. 2008. A neural representation of prior information during perceptual inference. Neuron 59:2336–47
     [Google Scholar]
122. Summerfield C, Koechlin E. 2010. Economic value biases uncertain perceptual choices in the parietal and prefrontal cortices. Front. Hum. Neurosci. 4:208
     [Google Scholar]
123. Summerfield C, Tsetsos K. 2012. Building bridges between perceptual and economic decision-making: neural and computational mechanisms. Front. Neurosci. 6:70
     [Google Scholar]
124. Takahashi YK, Batchelor HM, Liu B, Khanna A, Morales M, Schoenbaum G. 2017. Dopamine neurons respond to errors in the prediction of sensory features of expected rewards. Neuron 95:61395–405.e3
     [Google Scholar]
125. Thura D, Beauregard-Racine J, Fradet CW, Cisek P. 2012. Decision making by urgency gating: theory and experimental support. J. Neurophysiol. 108:112912–30
     [Google Scholar]
126. Thura D, Cisek P. 2014. Deliberation and commitment in the premotor and primary motor cortex during dynamic decision making. Neuron 81:61401–16
     [Google Scholar]
127. Thura D, Cisek P. 2017. The basal ganglia do not select reach targets but control the urgency of commitment. Neuron 95:51160–70.e5
     [Google Scholar]
128. Tsutsui-Kimura I, Matsumoto H, Akiti K, Yamada MM, Uchida N, Watabe-Uchida M. 2020. Distinct temporal difference error signals in dopamine axons in three regions of the striatum in a decision-making task. eLife 9:e62390
     [Google Scholar]
129. Wald A 1947. Sequential Analysis New York: Wiley
130. Wallace SF, Rosenquist AC, Sprague JM. 1989. Recovery from cortical blindness mediated by destruction of nontectotectal fibers in the commissure of the superior colliculus in the cat. J. Comp. Neurol. 284:3429–50
     [Google Scholar]
131. Wallace SF, Rosenquist AC, Sprague JM. 1990. Ibotenic acid lesions of the lateral substantia nigra restore visual orientation behavior in the hemianopic cat. J. Comp. Neurol. 296:2222–52
     [Google Scholar]
132. Wang AY, Miura K, Uchida N. 2013. The dorsomedial striatum encodes net expected return, critical for energizing performance vigor. Nat. Neurosci. 16:5639–47
     [Google Scholar]
133. Wang L, Krauzlis RJ. 2020. Involvement of striatal direct pathway in visual spatial attention in mice. Curr. Biol. 30:234739–44.e5
     [Google Scholar]
134. Wang L, Rangarajan KV, Gerfen CR, Krauzlis RJ. 2018. Activation of striatal neurons causes a perceptual decision bias during visual change detection in mice. Neuron 97:61369–81.e5
     [Google Scholar]
135. Wei W, Rubin JE, Wang XJ. 2015. Role of the indirect pathway of the basal ganglia in perceptual decision making. J. Neurosci. 35:94052–64
     [Google Scholar]
136. Wilson CJ. 2013. Active decorrelation in the basal ganglia. Neuroscience 250:467–82
     [Google Scholar]
137. Wilson SAK. 1914. An experimental research into the anatomy and physiology of the corpus striatum. Brain 36:427–92
     [Google Scholar]
138. Winkel J, Hawkins GE, Ivry RB, Brown SD, Cools R, Forstmann BU. 2016. Focal striatum lesions impair cautiousness in humans. Cortex 85:37–45
     [Google Scholar]
139. Yanike M, Ferrera VP. 2014. Interpretive monitoring in the caudate nucleus. eLife 3:e03727
     [Google Scholar]
140. Yartsev MM, Hanks TD, Yoon AM, Brody CD. 2018. Causal contribution and dynamical encoding in the striatum during evidence accumulation. eLife 7:e34929
     [Google Scholar]
141. Yeterian EH, Pandya DN. 1995. Corticostriatal connections of extrastriate visual areas in rhesus monkeys. J. Comp. Neurol. 352:3436–57
     [Google Scholar]
142. Zavala BA, Tan H, Little S, Ashkan K, Hariz M et al. 2014. Midline frontal cortex low-frequency activity drives subthalamic nucleus oscillations during conflict. J. Neurosci. 34:217322–33
     [Google Scholar]
143. Znamenskiy P, Zador AM. 2013. Corticostriatal neurons in auditory cortex drive decisions during auditory discrimination. Nature 497:7450482–85
     [Google Scholar]