Abstract
The basal ganglia have been increasingly recognized as an important structure involved in decision making. Neurons in the basal ganglia were found to reflect the evidence accumulation process during decision making. However, it is not well understood how the direct and indirect pathways of the basal ganglia work together for decision making. Here, we create a recurrent neural network model that is composed of the direct and indirect pathways and test it with the classic random dot motion discrimination task. The direct pathway drives the outputs, which are modulated through a gating mechanism controlled by the indirect pathway. We train the network to learn the task and find that the network reproduces the accuracy and reaction time patterns of previous animal studies. Units in the model exhibit ramping activities that reflect evidence accumulation. Finally, we simulate manipulations of the direct and indirect pathways and find that the manipulations of the direct pathway mainly affect the choice while the manipulations of the indirect pathway affect the model’s reaction time. These results suggest a potential circuitry mechanism of the basal ganglia’s role in decision making with predictions that can be tested experimentally in the future.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Albin RL, Young AB, Penney JB (1989) The functional anatomy of basal ganglia disorders. Trends Neurosci 12:366–375. https://doi.org/10.1016/0166-2236(89)90074-X
Balasubramani PP, Chakravarthy VS (2020) Bipolar oscillations between positive and negative mood states in a computational model of Basal Ganglia. Cogn Neurodyn 14:181–202. https://doi.org/10.1007/s11571-019-09564-7
Bergman H, Wichmann T, Karmon B, DeLong MR (1994) The primate subthalamic nucleus. II. Neuronal activity in the MPTP model of parkinsonism. J Neurophysiol 72:507–520. https://doi.org/10.1152/jn.1994.72.2.507
Bogacz R, Gurney K (2007) The basal ganglia and cortex implement optimal decision making between alternative actions. Neural Comput 19:442–477
Brown J, Pan WX, Dudman JT (2014) The inhibitory microcircuit of the substantia nigra provides feedback gain control of the basal ganglia output. Elife. https://doi.org/10.7554/eLife.02397
Cui G, Jun SB, Jin X, Pham MD, Vogel SS, Lovinger DM, Costa RM (2013) Concurrent activation of striatal direct and indirect pathways during action initiation. Nature 494:238–242. https://doi.org/10.1038/nature11846
DeLong MR (1983) The neurophysiologic basis of abnormal movements in basal ganglia disorders. Neurobehav Toxicol Teratol 5:611–616
DeLong MR (1990) Primate models of movement disorders of basal ganglia origin. Trends Neurosci. https://doi.org/10.1016/0166-2236(90)90110-V
Ding L, Gold JI (2010) Caudate encodes multiple computations for perceptual decisions. J Neurosci 30:15747–15759
Ding L, Gold JI (2012) Separate, causal roles of the caudate in saccadic choice and execution in a perceptual decision task. Neuron 75:865–874
Frank MJ, Claus ED (2006) Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal. Psychol Rev 113:300–326
Frank MJ, Loughry B, O’Reilly RC (2001) Interactions between frontal cortex and basal ganglia in working memory: a computational model. Cogn Affect Behav Neurosci 1:137–160
Gerfen CR, Surmeier DJ (2011) Modulation of striatal projection systems by dopamine. Annu Rev Neurosci 34:441–466. https://doi.org/10.1146/annurev-neuro-061010-113641
Gerfen CR, Engber TM, Mahan LC, Susel Z, Chase TN, Monsma FJ, Sibley DR (1990) D1 and D2 dopamine receptor-regulated gene expression of striatonigral and striatopallidal neurons. Science 250:1429–1432. https://doi.org/10.1126/science.2147780
Greff K, Srivastava RK, Koutník J (2016) LSTM: a search space odyssey. IEEE Trans 28:1–11
Haber SN, Fudge JL, McFarland NR (2000) Striatonigrostriatal pathways in primates form an ascending spiral from the shell to the dorsolateral striatum. J Neurosci 20:2369–2382. https://doi.org/10.1523/jneurosci.20-06-02369.2000
Hu B, Guo Y, Zou X, Dong J, Pan L, Yu M, Yang Z, Zhou C, Cheng Z, Tang W, Sun H (2018) Controlling mechanism of absence seizures by deep brain stimulus applied on subthalamic nucleus. Cogn Neurodyn 12:103–119. https://doi.org/10.1007/s11571-017-9457-x
Hu B, Wang D, Xia Z, Yang A, Zhang J, Shi Q, Dai H (2020) Regulation and control roles of the basal ganglia in the development of absence epileptiform activities. Cogn Neurodyn 14:137–154. https://doi.org/10.1007/s11571-019-09559-4
Hutchison WD, Allan RJ, Opitz H, Levy R, Dostrovsky JO, Lang AE, Lozano AM (1998) Neurophysiological identification of the subthalamic nucleus in surgery for Parkinson’s disease. Ann Neurol 44:622–628. https://doi.org/10.1002/ana.410440407
Isomura Y, Takekawa T, Harukuni R, Handa T, Aizawa H, Takada M, Fukai T (2013) Reward-modulated motor information in identified striatum neurons. J Neurosci 33:10209–10220. https://doi.org/10.1523/JNEUROSCI.0381-13.2013
Kingma DP, Ba J (2014) Adam: a method for stochastic optimization
Knowlton BJ, Mangels JA, Squire LR (1996) A neostriatal habit learning system in humans. Science 273:1399–1402. https://doi.org/10.1126/science.273.5280.1399
Lawrence AD, Sahakian BJ, Robbins TW (1998) Cognitive functions and corticostriatal circuits: insights from Huntington’s disease. Trends Cogn Sci. https://doi.org/10.1016/S1364-6613(98)01231-5
Lo CC, Wang XJ (2006) Cortico-basal ganglia circuit mechanism for a decision threshold in reaction time tasks. Nat Neurosci 9:956–963. https://doi.org/10.1038/nn1722
Mink JW (1996) The basal ganglia: focused selection and inhibition of competing motor programs. Prog Neurobiol 50:381–425. https://doi.org/10.1016/S0301-0082(96)00042-1
Pasupathy A, Miller EK (2005) Different time courses of learning-related activity in the prefrontal cortex and striatum. Nature 433:873–876. https://doi.org/10.1038/nature03287
Reiner A, Albin RL, Anderson KD, D’Amato CJ, Penney JB, Young AB (1988) Differential loss of striatal projection neurons in Huntington disease. Proc Natl Acad Sci USA 85:5733–5737. https://doi.org/10.1073/pnas.85.15.5733
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
Schultz W, Dayan P, Montague PR (1997) Neural substrate of prediction. Science 275:1593–1599
Thura D, Cisek P (2017) The basal ganglia do not select reach targets but control the urgency of commitment. Neuron 95:1160–1170.e5. https://doi.org/10.1016/j.neuron.2017.07.039
Wickens JR, Reynolds JNJ, Hyland BI (2003) Neural mechanisms of reward-related motor learning. Curr Opin Neurobiol. https://doi.org/10.1016/j.conb.2003.10.013
Yartsev MM, Hanks TD, Yoon AM, Brody CD (2018) Causal contribution and dynamical encoding in the striatum during evidence accumulation. Elife 7:1–24. https://doi.org/10.7554/eLife.34929
Zhang Z, Cheng H, Lin Z, Yang T (2019) A sequence learning model for decision making in the brain. bioRxiv. https://doi.org/10.1101/555862
Acknowledgements
We thank Zhewei Zhang for his help in the study. The authors declare no competing financial or nonfinancial interests.
Funding
This work was supported by Shanghai Municipal Science and Technology Major Project (Grant No. 2018SHZDZX05) and by Strategic Priority Research Program of Chinese Academy of Science, Grant No. XDB32070100.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Chen, X., Yang, T. A neural network model of basal ganglia’s decision-making circuitry. Cogn Neurodyn 15, 17–26 (2021). https://doi.org/10.1007/s11571-020-09609-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11571-020-09609-2