Selecting the proper actions is essential for organism’s survival and reproduction in the ever-changing environment (Gallistel, 1980). Numerous studies have implicated that the basal ganglia, a series of interconnected subcortical nuclei including the striatum and substantia nigra, play a primary role in action selection (Graybiel, 1998; Hikosaka et al., 1998; Jin and Costa, 2015; Mink, 2003; Redgrave et al., 1999). Indeed, a wide range of neurological and psychiatric disorders associated with the dysfunctional basal ganglia circuitry, including Parkinson’s disease (Benecke et al., 1987), Huntington’s disease (Phillips et al., 1995), obsessive-compulsive disorder (Graybiel and Rauch, 2000), are characterized by major deficits in action selection and movement control. Anatomically, commands for motor control are processed by basal ganglia through two major pathways, termed direct and indirect pathway, originating from striatal D1- and D2-expressing spiny projection neurons (D1-/D2-SPNs), respectively (Albin et al., 1989; DeLong, 1990). These two pathways collectively modulate substantia nigra pars reticulata (SNr) activity and the basal ganglia output, thus influence behavioral decisions. There are currently two major types of thinking on how the basal ganglia pathways work. An early classic theory has suggested that the basal ganglia direct and indirect pathways oppose each other to facilitate and inhibit action, respectively (the ‘Go/No-go’ model) (Albin et al., 1989; DeLong, 1990; Kravitz et al., 2010). In contrast, a recent theory has proposed that direct pathway selects the desired action, while the indirect pathway inhibits other competing actions in order to highlight the targeted choice (the ‘Co-activation’ model) (Cui et al., 2013; Hikosaka et al., 2000; Mink, 1996).

The two theories have essentially agreed upon the function of direct pathway being the positive driving force for initiating or facilitating the desired actions. Yet, the ideas about the indirect pathway function are largely controversial as either impeding the desired action in the ‘Go/No-go’ model or inhibiting the competing actions in the ‘Co-activation’ model. While the precise neuroanatomy on how the D2-SPNs control SNr through indirect pathway has yet to be mapped out at single-cell level to differentiate the two hypotheses, either theory has found its supports from behavioral and physiological observations. For instance, it has been found that stimulation of striatal direct and indirect pathways can bidirectionally regulate locomotion (Durieux et al., 2012; Kravitz et al., 2010), consistent with the traditional ‘Go/No-go’ model. On the other hand, in vivo electrophysiological and imaging experiments revealed that the striatal direct and indirect pathways are both activated during action initiation (Barbera et al., 2016; Cui et al., 2013; Geddes et al., 2018; Isomura et al., 2013; Jin et al., 2014; Klaus and Plenz, 2016; Markowitz et al., 2018; Nonomura et al., 2018), as the ‘Co-activation’ model predicted. Furthermore, physiological and optogenetic studies concerning complex behavior such as learned action sequences have further complicated the issue, and unveiled various neuronal subpopulations in both pathways are activated during the initiation, termination, and switching of actions (Geddes et al., 2018; Jin and Costa, 2015; Jin et al., 2014; Tecuapetla et al., 2016). So far, how exactly the basal ganglia direct and indirect pathways work together to control action selection has been controversial and inconclusive, and the underlying circuit mechanism remains largely unclear (Calabresi et al., 2014).

Here, we trained mice to perform an operant action selection task where they were required to select one out of two actions to achieve reward, based on self-monitored time intervals (Howard et al., 2017). By employing in vivo neuronal recording, we found that the net output of two opponent SNr neuron populations is predictive of the behavioral choices. Through identifying striatal pathway-specific neuronal activity with optogenetic tagging, we found that there are neuronal populations in either the direct or indirect pathway that are activated during selecting one action and suppressed during another. Optogenetic inhibition, as well as selective ablation of direct pathway, impairs action selection, and optogenetic excitation of direct pathway enhances current choice, confirming a role of direct pathway in facilitating desired actions. Furthermore, optogenetic inhibition of indirect pathway improves action selection and excitation of indirect pathway impairs behavioral choices, as predicted by the ‘Go/No-go’ model. However, selective ablation of indirect pathway impairs action selection, opposite from the behavioral effect of optogenetic inhibition and at odds with the ‘Go/No-go’ model, but consistent with the prediction from the ‘Co-activation’ model. To resolve these contradictions, we propose a new center (direct)-surround (indirect)-context (indirect) ‘Triple-control’ functional model of basal ganglia pathways, in which there are two interacting indirect pathway subcircuits exerting opposite controls over the basal ganglia output. The new model can reproduce the neuronal and behavioral experimental results that cannot be simply explained by either the ‘Go/No-go’ or the ‘Co-activation’ model. Further systematic analyses from this new model suggested that the direct and indirect pathways modulate behavioral outputs in a linear and nonlinear manner, respectively. Notably, in the new ‘Triple-control’ model, the direct and indirect pathways can work together to dynamically control action selection and operate in a manner similar to ‘Go/No-go’ or ‘Co-activation’ model, depending on the activity level and the network state. These results revise our current understanding on how the basal ganglia control actions, and have important implications for a wide range of movement and psychiatric diseases where the dynamic balance between the two pathways is compromised (Albin et al., 1989; Benecke et al., 1987; Calabresi et al., 2014; DeLong, 1990; Graybiel and Rauch, 2000; Mink, 1996; Phillips et al., 1995).

Here, by using an internally driven 2–8 s action selection task in mice, we investigated the function of basal ganglia direct and indirect pathways in mediating dynamic action selection. We found that the neuronal activities in SNr, the major output of basal ganglia, directly reflect animals’ internal action selection process, other than simply time or value. It was also observed that the striatum, the main input of basal ganglia, shares the similar action selection-related neuronal dynamics with SNr and is needed for both learning and execution of proper action selection. Furthermore, the striatal direct and indirect pathways exhibit distinct neuronal activity and during manipulation, they have different functional effects on controlling action selection. Notably, the experimental observations on the physiology and function of direct and indirect pathways cannot be simply explained by either the traditional ‘Go/No-go’ model or the more recent ‘Co-activation’ model. We proposed a new ‘Triple-control’ functional model of basal ganglia, suggesting a critical role of dynamic interactions between different neuronal subpopulations within the indirect pathway for controlling basal ganglia output and behavior. In the model, a ‘center (direct pathway)-surround (indirect pathway)-context (indirect pathway)’ three layers of structure exerts dynamic control of action selection, depending on the input level and network state. This new model respects the realistic neuroanatomy, and can recapitulate and explain the essential in vivo electrophysiological and behavioral findings. It also provides a new perspective on understanding many behavioral phenomena involving in dopamine and basal ganglia circuitry in health and disease.

Our current 2–8 s action selection task offers a unique opportunity to observe the animal’s internal switch from one choice to another and monitor the underlying neuronal dynamics correspondingly. We observed two major types of monotonically changing SNr neuronal dynamics during the internal choice switching, presumably one type associated with selecting one action and another with selecting the competing action, respectively. The classic view on SNr activity is that it tonically inhibits the downstream motor nuclei and releases action via disinhibition (Albin et al., 1989; DeLong, 1990; Hikosaka and Wurtz, 1983; Wurtz and Hikosaka, 1986). The increased response in SNr, however, could potentially inhibit the competing actions or the movements toward the opposing direction through projections to the contralateral brain regions like superior colliculus (Jiang et al., 2003). Here, we found that two subpopulations in SNr showed opposite monotonic firing change during the left-then-right choice, and notably, their neuronal dynamics switched when the animals performed the reversed version of task which requires a right-then-left choice. It thus suggests that these SNr neurons are indeed associated with different action options during choice behavior, and actively adjust their firing rates to facilitate respective action selection. Given the opposite neuronal dynamics and functionally antagonistic nature of Type 1 and Type 2 SNr neurons, we defined the net output of basal ganglia by the subtracting the neuronal activity between the two SNr subpopulations and correlated it with the behavioral choice. The subtraction between Type 1 and Type 2 SNr neurons is the net output of two competing choices and indicates animals’ choice in real time. Also, signals corresponding to left and right choices through direct/indirect pathways eventually converge to SNr (Albin et al., 1989; DeLong, 1990). The collateral inhibition within SNr (Brown et al., 2014; Mailly et al., 2003) gives rise to the direct competition between different SNr functional subgroups. Therefore, the subtraction between Type 1 and Type 2 SNr neurons represents the outcome of competition between choices. Indeed, we found that the basal ganglia net output exhibited a tight correlation with the psychometric curve of behavioral choice, and faithfully represented a neural basis for the dynamic action selection process.

As one of the major input nuclei of basal ganglia, striatum influences SNr activity through direct/indirect pathways and undisputedly, plays an essential role in action selection (Ding and Gold, 2012; Geddes et al., 2018; Jin et al., 2014; Lauwereyns et al., 2002; Tai et al., 2012). By genetic manipulation and pharmacological inactivation, we showed that striatum is indispensable for both learning action selection and the proper performance of learned behavioral choice. The recording of neuronal activity in dorsal-central striatum during action selection further revealed that striatal spiny projection neurons share the similar types of neuronal dynamics as SNr. Through optogenetic tagging in freely behaving mice, we further found that dorsal-central striatal SPNs in the direct and indirect pathways show distinct activity profile, with D1-SPNs representing a strong bias toward the preferred choice, while D2-SPNs encoding two choices equally.

Two prevailing models have been proposed to explain the functional distinction between D1- and D2-SPNs. The canonical model of the basal ganglia suggests that the D1- and D2-SPNs play antagonistic roles in controlling action as mediating ‘Go’ and ‘No-go’ signals, respectively (Albin et al., 1989; DeLong, 1990; Kravitz et al., 2010). A more recent model, however, implies that as D1-SPNs initiate an action, D2-SPNs co-activate with D1-SPNs to inhibit other competing actions (Cui et al., 2013; Hikosaka et al., 2000; Isomura et al., 2013; Jin et al., 2014; Mink, 1996). Essentially, these two models agree upon the functional role of D1-SPNs in releasing or facilitating the desired action, but contradict on the function of D2-SPNs on which targeted action of inhibiting. Here, our in vivo recording data indicate that both D1- and D2-SPNs share similar neuronal dynamics during action selection, and the neural activity alone is not sufficient to separate and determine whether ‘Go/No-go’ or ‘Co-activation’ model is supported (Cui et al., 2013; Isomura et al., 2013; Jin et al., 2014). To resolve the functional distinction of the direct vs. indirect pathway, we applied a series of cell-type-specific manipulations on striatal D1- and D2-SPNs during action selection behavior. First, we generated mutant mice in which NMDA receptors are deleted from either striatal D1- or D2-SPNs (Geddes et al., 2018; Jin et al., 2014). Both the D1-NR1 KO and D2-NR1 KO mice showed learning deficits and behavioral choice impairments when tested with probe trials, suggesting that both D1- and D2-SPNs are necessary for learning and performing action selection. Notably, while the D1-NR1 KO mice are mostly impaired in the choice associated with 8 s, a less-preferred option compared to 2 s, the D2-NR1 KO mice are compromised in both 2 s and 8 s choice. Additional experiments with cell-type-specific ablation further confirmed these results, consistent the distinct neuronal activity profile in these two pathways revealed during in vivo neuronal recording. While both the ‘Go/No-go’ and ‘Co-activation’ models predict the suppression of D1-SPNs activity leads to impaired action selection, supported by current KO and cell ablation data, the manipulation experiments on D2-SPNs favor the ‘Co-activation’ but not the ‘Go/No-go’ model which the latter suggests D2-SPNs ablation would improve rather than impair action selection.

Next, we directly introduced transient bidirectional manipulations to D1- and D2-SPNs activity by optogenetics while mice performing the task. Our findings revealed that activation or inhibition of D1-SPNs increased and decreased the correct rate of choice respectively, suggesting a facilitating role of direct pathway in action selection, which again fits well with the ‘Go/No-go’ as well as the ‘Co-activation’ model. In contrast, optogenetic activation of D2-SPNs decreased the correct rate of choice, while inhibition of D2-SPNs promoted the correct choice. When stimulating D2-SPNs, animals are still able to press the lever and make a selection shortly after lever extension, therefore, the behavioral effect triggered by D2 stimulation is not simply due to a general effect of decreased locomotion, but the altered action selection process. These results were supportive to the ‘Go/No-go’ model but contradicted to the prediction of ‘Co-activation’ theory, which the latter predicts that activation of D2-SPNs inhibits competing actions to facilitate desired choice, whereas inhibition of D2-SPNs releases competing actions and compromises the ongoing choice.

In summary, neither ‘Go/No-go’ nor ‘Co-activation’ models could fully explain the experimental results we found, particularly for experiments on D2-SPNs in the indirect pathway. Through computer simulation, we further demonstrated that a simple additive combination of ‘Go/No-go’ nor ‘Co-activation’ models by linear addition cannot reproduce all the experimental observations. To resolve these theoretical difficulties, we proposed a new center-surround-context ‘Triple-control’ model of basal ganglia pathways for action selection. Specifically, two subpopulations of D2-SPNs in the indirect pathway function as ‘Co-activation’ and ‘Go/No-go’ modules respectively, and an activity-dependent inhibition from ‘Co-activation’ to ‘Go/No-go’ module mediates the dynamic switch between the dominant module depending on the inputs and network state. Due to the dominant ‘Co-activation’ module in the default state, excessive inhibition of D2-SPNs or ablating the entire indirect pathway eliminates the promotive contribution and impairs action selection in the ‘Triple-control’ model, consistent with the experimental observations. In contrast, transient increase of D2-SPNs firing activity during optogenetic stimulation introduces shift toward the ‘Go/No-go’ dominance from the ‘Co-activation’ module via firing rate-dependent short-term depression of the inhibitory synapses between them, which amplifies the ‘No-go’ signal and compromises action selection as experimentally found. In contrast, transient decrease of D2-SPNs firing activity during optogenetic inhibition results in disinhibition of ‘Go/No-go’ module from inhibitory control of ‘Co-activation’ module, with an attenuated ‘No-go’ signal which leads to better performance in choice. These results from our new ‘Triple-control’ model thus suggest that the basal ganglia circuitry could be much more dynamic than previously thought, and it could employ a complex mechanism of functional module reconfiguration for context- or state-dependent flexible control. More importantly, our model further proposed that while direct pathway regulates action selection in a linear manner, the indirect pathway modulates action selection in a nonlinear inverted-U-shaped way depending on the inputs and the network state (Figure 7). Indeed, experimental results have suggested that the amplitude of activities of D2 pathway is pivotal to the behavioral outcome (Meng et al., 2018), consistent with our proposed ‘nonlinear’ control of D2 pathway over action selection. These results of various functional assemblies defied previous basal ganglia models in which either direct or indirect pathway has been treated as one uniform population and assigned with a single function in controlling action.

In the ‘Triple-control’ model, we posited the collateral connections among striatal D2-SPNs and its short-term plasticity could serve as an operational mechanism for the dominant module switching. However, besides these well-known striatal local connections as one of the simplest possible mechanisms, other anatomical circuits within basal ganglia circuitry could potentially fulfill this functional role alone or additionally as well. For example, striatal D2-SPNs project to external global pallidus (GPe) through striatopallidal pathway, and meanwhile they receive arkypallidal projections from GPe to both the striatal SPNs and interneurons (Abdi et al., 2015; Fujiyama et al., 2016; Mallet et al., 2016). It is thus also possible that the dynamic interaction between ‘Co-activation’ and ‘Go/No-go’ modules is mediated through di-synaptic or tri-synaptic modulation with GPe and/or striatal interneurons involved. Furthermore, in theory this dynamic interaction between ‘Co-activation’ and ‘Go/No-go’ modules can also occur outside striatum in the downstream nuclei including GPe and SNr, given their specific neuronal subpopulations receiving inputs from corresponding striatal D2-SPNs subgroups and proper collateral connections within the nuclei (Atherton et al., 2013; Cazorla et al., 2014; Fujiyama et al., 2011; Lee et al., 2020; Wu et al., 2000). Considering the crucial role of dopamine in basal ganglia circuitry, the new ‘Triple-control’ model can also reproduce our previous experiments results on the effect of nigrostriatal dopamine on action selection (Howard et al., 2017). Importantly, it unveils that there is an inverted-U-shaped relationship between dopamine concentration change and action selection (Cools and D’Esposito, 2011). The model simulation suggests that while moderate dopamine increase improves decision making, too much dopamine changes, either increase or decrease, dramatically impair the choice behavior. These results might be able to explain some of behavioral observations involving in obscure decision making under the influence of addictive substances.

Our findings also have important implications in many neurological and psychiatric diseases. It was known that the loss of dopamine leads to hyperactivity of D2-SPNs and disruption of local D2-SPNs collaterals in Parkinson’s disease (Taverna et al., 2008; Wei and Wang, 2016). These alterations will not only break the balance of direct vs. indirect pathway, but also disrupt the multiple dynamic controls from the indirect pathway. The action selection will thus be largely problematic, even with L-DOPA treatment, which might restore the dopamine partially but not necessarily the altered basal ganglia circuitry and its circuit dynamics (Bastide et al., 2015). The current ‘Triple-control’ model also provides some mechanistic insights into the inhibitory control deficits observed schizophrenia (Taverna et al., 2008; Wei and Wang, 2016). For instance, an increase in the density and occupancy of the striatal D2 receptors (D2R) has been frequently reported in schizophrenia patients (Abi-Dargham et al., 2000; Howes and Kapur, 2009; Laruelle et al., 1997; Wong et al., 1986). Many antipsychotic medications primarily aim to block the D2R (la Fougère et al., 2005; Lally and MacCabe, 2015; Yokoi et al., 2002), but the drug dose is the key to the treatment and severer adverse effects are associated with overdose of D2R antagonism (Levine and Ruha, 2012). In addition, prolonged exposure to antipsychotics often causes extrapyramidal symptoms, including Parkinsonian symptoms and tardive dyskinesia (Jarskog et al., 2007; Seeman, 2002). The dose-dependent effects when modulating D2R were also found in cognitive functions such as serial discrimination, in which relatively low and high dose of D2R agonist in striatum impairs the performance in the discrimination task, while the intermediate dose of D2R agonist produces significant improvement (Cools and D’Esposito, 2011; Goldman-Rakic et al., 2000; Horst et al., 2019; Mattay et al., 2003). These observations thus further underscore the dynamic interplays and complexity of basal ganglia pathways in action control, as demonstrated in current study and the new ‘Triple-control’ functional model.

Data and code are available at Dryad: https://doi.org/10.5061/dryad.gxd2547s1.

1. 1. Li H
   2. Jin X

   (2023) Dryad Digital Repository

   Experimental data.

   https://doi.org/10.5061/dryad.gxd2547s1

1. 1. Abdi A
   2. Mallet N
   3. Mohamed FY
   4. Sharott A
   5. Dodson PD
   6. Nakamura KC
   7. Suri S
   8. Avery SV
   9. Larvin JT
   10. Garas FN
   11. Garas SN
   12. Vinciati F
   13. Morin S
   14. Bezard E
   15. Baufreton J
   16. Magill PJ

   (2015) Prototypic and arkypallidal neurons in the dopamine-intact external globus pallidus

   The Journal of Neuroscience 35:6667–6688.

   https://doi.org/10.1523/JNEUROSCI.4662-14.2015

   • PubMed
   • Google Scholar
2. 1. Abi-Dargham A
   2. Rodenhiser J
   3. Printz D
   4. Zea-Ponce Y
   5. Gil R
   6. Kegeles LS
   7. Weiss R
   8. Cooper TB
   9. Mann JJ
   10. Van Heertum RL
   11. Gorman JM
   12. Laruelle M

   (2000) Increased baseline occupancy of D2 receptors by dopamine in schizophrenia

   PNAS 97:8104–8109.

   https://doi.org/10.1073/pnas.97.14.8104

   • PubMed
   • Google Scholar
3. 1. Albin RL
   2. Young AB
   3. Penney JB

   (1989) The functional anatomy of basal ganglia disorders

   Trends in Neurosciences 12:366–375.

   https://doi.org/10.1016/0166-2236(89)90074-x

   • PubMed
   • Google Scholar
4. 1. Aoki S
   2. Smith JB
   3. Li H
   4. Yan X
   5. Igarashi M
   6. Coulon P
   7. Wickens JR
   8. Ruigrok TJ
   9. Jin X

   (2019) An open cortico-basal ganglia loop allows limbic control over motor output via the nigrothalamic pathway

   eLife 8:e49995.

   https://doi.org/10.7554/eLife.49995

   • PubMed
   • Google Scholar
5. 1. Atherton JF
   2. Menard A
   3. Urbain N
   4. Bevan MD

   (2013) Short-term depression of external globus pallidus-subthalamic nucleus synaptic transmission and implications for patterning subthalamic activity

   The Journal of Neuroscience 33:7130–7144.

   https://doi.org/10.1523/JNEUROSCI.3576-12.2013

   • PubMed
   • Google Scholar
6. 1. Azim E
   2. Jiang J
   3. Alstermark B
   4. Jessell TM

   (2014) Skilled reaching relies on a V2a propriospinal internal copy circuit

   Nature 508:357–363.

   https://doi.org/10.1038/nature13021

   • PubMed
   • Google Scholar
7. 1. Barbera G
   2. Liang B
   3. Zhang L
   4. Gerfen CR
   5. Culurciello E
   6. Chen R
   7. Li Y
   8. Lin DT

   (2016) Spatially compact neural clusters in the dorsal striatum encode locomotion relevant information

   Neuron 92:202–213.

   https://doi.org/10.1016/j.neuron.2016.08.037

   • PubMed
   • Google Scholar
8. 1. Bastide MF
   2. Meissner WG
   3. Picconi B
   4. Fasano S
   5. Fernagut P-O
   6. Feyder M
   7. Francardo V
   8. Alcacer C
   9. Ding Y
   10. Brambilla R
   11. Fisone G
   12. Jon Stoessl A
   13. Bourdenx M
   14. Engeln M
   15. Navailles S
   16. De Deurwaerdère P
   17. Ko WKD
   18. Simola N
   19. Morelli M
   20. Groc L
   21. Rodriguez M-C
   22. Gurevich EV
   23. Quik M
   24. Morari M
   25. Mellone M
   26. Gardoni F
   27. Tronci E
   28. Guehl D
   29. Tison F
   30. Crossman AR
   31. Kang UJ
   32. Steece-Collier K
   33. Fox S
   34. Carta M
   35. Angela Cenci M
   36. Bézard E

   (2015) Pathophysiology of L-dopa-induced motor and non-motor complications in Parkinson’s disease

   Progress in Neurobiology 132:96–168.

   https://doi.org/10.1016/j.pneurobio.2015.07.002

   • PubMed
   • Google Scholar
9. 1. Benecke R
   2. Rothwell JC
   3. Dick JP
   4. Day BL
   5. Marsden CD

   (1987) Disturbance of sequential movements in patients with Parkinson’s disease

   Brain 110:361–379.

   https://doi.org/10.1093/brain/110.2.361

   • PubMed
   • Google Scholar
10. 1. Brown J
    2. Pan WX
    3. Dudman JT

    (2014) The inhibitory microcircuit of the substantia nigra provides feedback gain control of the basal ganglia output

    eLife 3:e02397.

    https://doi.org/10.7554/eLife.02397

    • PubMed
    • Google Scholar
11. 1. Brunton BW
    2. Botvinick MM
    3. Brody CD

    (2013) Rats and humans can optimally accumulate evidence for decision-making

    Science 340:95–98.

    https://doi.org/10.1126/science.1233912

    • PubMed
    • Google Scholar
12. 1. Burke DA
    2. Rotstein HG
    3. Alvarez VA

    (2017) Striatal local circuitry: a new framework for lateral inhibition

    Neuron 96:267–284.

    https://doi.org/10.1016/j.neuron.2017.09.019

    • PubMed
    • Google Scholar
13. 1. Calabresi P
    2. Picconi B
    3. Tozzi A
    4. Ghiglieri V
    5. Di Filippo M

    (2014) Direct and indirect pathways of basal ganglia: a critical reappraisal

    Nature Neuroscience 17:1022–1030.

    https://doi.org/10.1038/nn.3743

    • PubMed
    • Google Scholar
14. 1. Cazorla M
    2. de Carvalho FD
    3. Chohan MO
    4. Shegda M
    5. Chuhma N
    6. Rayport S
    7. Ahmari SE
    8. Moore H
    9. Kellendonk C

    (2014) Dopamine D2 receptors regulate the anatomical and functional balance of basal ganglia circuitry

    Neuron 81:153–164.

    https://doi.org/10.1016/j.neuron.2013.10.041

    • PubMed
    • Google Scholar
15. 1. Cools R
    2. D’Esposito M

    (2011) Inverted-U-shaped dopamine actions on human working memory and cognitive control

    Biological Psychiatry 69:113–125.

    https://doi.org/10.1016/j.biopsych.2011.03.028

    • PubMed
    • Google Scholar
16. 1. Cui G
    2. Jun SB
    3. Jin X
    4. Pham MD
    5. Vogel SS
    6. Lovinger DM
    7. Costa RM

    (2013) Concurrent activation of striatal direct and indirect pathways during action initiation

    Nature 494:238–242.

    https://doi.org/10.1038/nature11846

    • PubMed
    • Google Scholar
17. 1. DeLong MR

    (1990) Primate models of movement disorders of basal ganglia origin

    Trends in Neurosciences 13:281–285.

    https://doi.org/10.1016/0166-2236(90)90110-v

    • PubMed
    • Google Scholar
18. Book

    1. Deniau JM
    2. Maurice N
    3. Charpier S

    (2007)

    Gaba and the Basal Ganglia - from Molecules to Systems

    Elsevier.

    • Google Scholar
19. 1. Ding L
    2. Gold JI

    (2012) Separate, causal roles of the caudate in saccadic choice and execution in a perceptual decision task

    Neuron 75:865–874.

    https://doi.org/10.1016/j.neuron.2012.07.021

    • PubMed
    • Google Scholar
20. 1. Durieux PF
    2. Schiffmann SN
    3. de Kerchove d’Exaerde A

    (2012) Differential regulation of motor control and response to dopaminergic drugs by D1R and D2R neurons in distinct dorsal striatum subregions

    The EMBO Journal 31:640–653.

    https://doi.org/10.1038/emboj.2011.400

    • Google Scholar
21. 1. Fujiyama F
    2. Sohn J
    3. Nakano T
    4. Furuta T
    5. Nakamura KC
    6. Matsuda W
    7. Kaneko T

    (2011) Exclusive and common targets of neostriatofugal projections of rat striosome neurons: a single neuron-tracing study using a viral vector

    European Journal of Neuroscience 33:668–677.

    https://doi.org/10.1111/j.1460-9568.2010.07564.x

    • Google Scholar
22. 1. Fujiyama F
    2. Nakano T
    3. Matsuda W
    4. Furuta T
    5. Udagawa J
    6. Kaneko T

    (2016) A single-neuron tracing study of arkypallidal and prototypic neurons in healthy rats

    Brain Structure and Function 221:4733–4740.

    https://doi.org/10.1007/s00429-015-1152-2

    • Google Scholar
23. Book

    1. Gallistel CR

    (1980)

    The Organization of Action: A New Synthesis

    Routledge.

    • Google Scholar
24. 1. Geddes CE
    2. Li H
    3. Jin X

    (2018) Optogenetic editing reveals the hierarchical organization of learned action sequences

    Cell 174:32–43.

    https://doi.org/10.1016/j.cell.2018.06.012

    • PubMed
    • Google Scholar
25. 1. Goldman-Rakic PS
    2. Muly EC
    3. Williams GV

    (2000) D(1) receptors in prefrontal cells and circuits

    Brain Research. Brain Research Reviews 31:295–301.

    https://doi.org/10.1016/s0165-0173(99)00045-4

    • PubMed
    • Google Scholar
26. 1. Gong S
    2. Doughty M
    3. Harbaugh CR
    4. Cummins A
    5. Hatten ME
    6. Heintz N
    7. Gerfen CR

    (2007) Targeting Cre recombinase to specific neuron populations with bacterial artificial chromosome constructs

    The Journal of Neuroscience 27:9817–9823.

    https://doi.org/10.1523/JNEUROSCI.2707-07.2007

    • PubMed
    • Google Scholar
27. 1. Gradinaru V
    2. Zhang F
    3. Ramakrishnan C
    4. Mattis J
    5. Prakash R
    6. Diester I
    7. Goshen I
    8. Thompson KR
    9. Deisseroth K

    (2010) Molecular and cellular approaches for diversifying and extending optogenetics

    Cell 141:154–165.

    https://doi.org/10.1016/j.cell.2010.02.037

    • PubMed
    • Google Scholar
28. 1. Graybiel AM

    (1998) The basal ganglia and chunking of action repertoires

    Neurobiology of Learning and Memory 70:119–136.

    https://doi.org/10.1006/nlme.1998.3843

    • PubMed
    • Google Scholar
29. 1. Graybiel AM
    2. Rauch SL

    (2000) Toward a neurobiology of obsessive-compulsive disorder

    Neuron 28:343–347.

    https://doi.org/10.1016/s0896-6273(00)00113-6

    • PubMed
    • Google Scholar
30. 1. Gustafson N
    2. Gireesh-Dharmaraj E
    3. Czubayko U
    4. Blackwell KT
    5. Plenz D

    (2006) A comparative voltage and current-clamp analysis of feedback and feedforward synaptic transmission in the striatal microcircuit in vitro

    Journal of Neurophysiology 95:737–752.

    https://doi.org/10.1152/jn.00802.2005

    • PubMed
    • Google Scholar
31. 1. Hikosaka O
    2. Wurtz RH

    (1983) Visual and oculomotor functions of monkey substantia nigra pars reticulata IV Relation of substantia nigra to superior colliculus

    Journal of Neurophysiology 49:1285–1301.

    https://doi.org/10.1152/jn.1983.49.5.1285

    • PubMed
    • Google Scholar
32. 1. Hikosaka O
    2. Miyashita K
    3. Miyachi S
    4. Sakai K
    5. Lu X

    (1998) Differential roles of the frontal cortex, basal ganglia, and cerebellum in visuomotor sequence learning

    Neurobiology of Learning and Memory 70:137–149.

    https://doi.org/10.1006/nlme.1998.3844

    • PubMed
    • Google Scholar
33. 1. Hikosaka O
    2. Takikawa Y
    3. Kawagoe R

    (2000) Role of the basal ganglia in the control of purposive saccadic eye movements

    Physiological Reviews 80:953–978.

    https://doi.org/10.1152/physrev.2000.80.3.953

    • PubMed
    • Google Scholar
34. 1. Hikosaka O

    (2007) GABAergic output of the basal ganglia

    Progress in Brain Research 160:209–226.

    https://doi.org/10.1016/S0079-6123(06)60012-5

    • PubMed
    • Google Scholar
35. 1. Horst NK
    2. Jupp B
    3. Roberts AC
    4. Robbins TW

    (2019) D2 receptors and cognitive flexibility in marmosets: tri-phasic dose-response effects of intra-striatal quinpirole on serial reversal performance

    Neuropsychopharmacology 44:564–571.

    https://doi.org/10.1038/s41386-018-0272-9

    • PubMed
    • Google Scholar
36. 1. Howard CD
    2. Li H
    3. Geddes CE
    4. Jin X

    (2017) Dynamic nigrostriatal dopamine biases action selection

    Neuron 93:1436–1450.

    https://doi.org/10.1016/j.neuron.2017.02.029

    • PubMed
    • Google Scholar
37. 1. Howes OD
    2. Kapur S

    (2009) The dopamine hypothesis of schizophrenia: version III--the final common pathway

    Schizophrenia Bulletin 35:549–562.

    https://doi.org/10.1093/schbul/sbp006

    • PubMed
    • Google Scholar
38. 1. Isomura Y
    2. Takekawa T
    3. Harukuni R
    4. Handa T
    5. Aizawa H
    6. Takada M
    7. Fukai T

    (2013) Reward-modulated motor information in identified striatum neurons

    The Journal of Neuroscience 33:10209–10220.

    https://doi.org/10.1523/JNEUROSCI.0381-13.2013

    • PubMed
    • Google Scholar
39. 1. Jarskog LF
    2. Miyamoto S
    3. Lieberman JA

    (2007) Schizophrenia: new pathological insights and therapies

    Annual Review of Medicine 58:49–61.

    https://doi.org/10.1146/annurev.med.58.060904.084114

    • PubMed
    • Google Scholar
40. 1. Jiang H
    2. Stein BE
    3. McHaffie JG

    (2003) Opposing basal ganglia processes shape midbrain visuomotor activity bilaterally

    Nature 423:982–986.

    https://doi.org/10.1038/nature01698

    • PubMed
    • Google Scholar
41. 1. Jin X
    2. Costa RM

    (2010) Start/stop signals emerge in nigrostriatal circuits during sequence learning

    Nature 466:457–462.

    https://doi.org/10.1038/nature09263

    • PubMed
    • Google Scholar
42. 1. Jin X
    2. Tecuapetla F
    3. Costa RM

    (2014) Basal ganglia subcircuits distinctively encode the parsing and concatenation of action sequences

    Nature Neuroscience 17:423–430.

    https://doi.org/10.1038/nn.3632

    • PubMed
    • Google Scholar
43. 1. Jin X
    2. Costa RM

    (2015) Shaping action sequences in basal ganglia circuits

    Current Opinion in Neurobiology 33:188–196.

    https://doi.org/10.1016/j.conb.2015.06.011

    • PubMed
    • Google Scholar
44. 1. Klaus A
    2. Plenz D

    (2016) A low-correlation resting state of the striatum during cortical avalanches and its role in movement suppression

    PLOS Biology 14:e1002582.

    https://doi.org/10.1371/journal.pbio.1002582

    • PubMed
    • Google Scholar
45. 1. Kravitz AV
    2. Freeze BS
    3. Parker PRL
    4. Kay K
    5. Thwin MT
    6. Deisseroth K
    7. Kreitzer AC

    (2010) Regulation of parkinsonian motor behaviours by optogenetic control of basal ganglia circuitry

    Nature 466:622–626.

    https://doi.org/10.1038/nature09159

    • PubMed
    • Google Scholar
46. 1. la Fougère C
    2. Meisenzahl E
    3. Schmitt G
    4. Stauss J
    5. Frodl T
    6. Tatsch K
    7. Hahn K
    8. Möller H-J
    9. Dresel S

    (2005)

    D2 receptor occupancy during high- and low-dose therapy with the atypical antipsychotic amisulpride: a 123I-iodobenzamide SPECT study

    Journal of Nuclear Medicine 46:1028–1033.

    • PubMed
    • Google Scholar
47. 1. Lally J
    2. MacCabe JH

    (2015) Antipsychotic medication in schizophrenia: a review

    British Medical Bulletin 114:169–179.

    https://doi.org/10.1093/bmb/ldv017

    • PubMed
    • Google Scholar
48. 1. Laruelle M
    2. D’Souza CD
    3. Baldwin RM
    4. Abi-Dargham A
    5. Kanes SJ
    6. Fingado CL
    7. Seibyl JP
    8. Zoghbi SS
    9. Bowers MB
    10. Jatlow P
    11. Charney DS
    12. Innis RB

    (1997) Imaging D2 receptor occupancy by endogenous dopamine in humans

    Neuropsychopharmacology 17:162–174.

    https://doi.org/10.1016/S0893-133X(97)00043-2

    • PubMed
    • Google Scholar
49. 1. Lauwereyns J
    2. Watanabe K
    3. Coe B
    4. Hikosaka O

    (2002) A neural correlate of response bias in monkey caudate nucleus

    Nature 418:413–417.

    https://doi.org/10.1038/nature00892

    • PubMed
    • Google Scholar
50. 1. Lee Y
    2. Han N-E
    3. Kim W
    4. Kim JG
    5. Lee IB
    6. Choi SJ
    7. Chun H
    8. Seo M
    9. Lee CJ
    10. Koh H-Y
    11. Kim J-H
    12. Baik J-H
    13. Bear MF
    14. Choi S-Y
    15. Yoon B-J

    (2020) Dynamic changes in the bridging collaterals of the basal ganglia circuitry control stress-related behaviors in mice

    Molecules and Cells 43:360–372.

    https://doi.org/10.14348/molcells.2019.0279

    • PubMed
    • Google Scholar
51. 1. Levine M
    2. Ruha AM

    (2012) Overdose of atypical antipsychotics: clinical presentation, mechanisms of toxicity and management

    CNS Drugs 26:601–611.

    https://doi.org/10.2165/11631640-000000000-00000

    • PubMed
    • Google Scholar
52. 1. Lima SQ
    2. Hromádka T
    3. Znamenskiy P
    4. Zador AM

    (2009) PINP: a new method of tagging neuronal populations for identification during in vivo electrophysiological recording

    PLOS ONE 4:e6099.

    https://doi.org/10.1371/journal.pone.0006099

    • PubMed
    • Google Scholar
53. 1. Lo CC
    2. Wang XJ

    (2006) Cortico-basal ganglia circuit mechanism for a decision threshold in reaction time tasks

    Nature Neuroscience 9:956–963.

    https://doi.org/10.1038/nn1722

    • PubMed
    • Google Scholar
54. 1. Madisen L
    2. Mao T
    3. Koch H
    4. Zhuo J
    5. Berenyi A
    6. Fujisawa S
    7. Hsu YWA
    8. Garcia AJ
    9. Gu X
    10. Zanella S
    11. Kidney J
    12. Gu H
    13. Mao Y
    14. Hooks BM
    15. Boyden ES
    16. Buzsáki G
    17. Ramirez JM
    18. Jones AR
    19. Svoboda K
    20. Han X
    21. Turner EE
    22. Zeng H

    (2012) A toolbox of Cre-dependent optogenetic transgenic mice for light-induced activation and silencing

    Nature Neuroscience 15:793–802.

    https://doi.org/10.1038/nn.3078

    • PubMed
    • Google Scholar
55. 1. Mailly P
    2. Charpier S
    3. Menetrey A
    4. Deniau JM

    (2003) Three-dimensional organization of the recurrent axon collateral network of the substantia nigra pars reticulata neurons in the rat

    The Journal of Neuroscience 23:5247–5257.

    https://doi.org/10.1523/JNEUROSCI.23-12-05247.2003

    • PubMed
    • Google Scholar
56. 1. Mallet N
    2. Schmidt R
    3. Leventhal D
    4. Chen F
    5. Amer N
    6. Boraud T
    7. Berke JD

    (2016) Arkypallidal cells send a stop signal to striatum

    Neuron 89:308–316.

    https://doi.org/10.1016/j.neuron.2015.12.017

    • PubMed
    • Google Scholar
57. 1. Markowitz JE
    2. Gillis WF
    3. Beron CC
    4. Neufeld SQ
    5. Robertson K
    6. Bhagat ND
    7. Peterson RE
    8. Peterson E
    9. Hyun M
    10. Linderman SW
    11. Sabatini BL
    12. Datta SR

    (2018) The striatum organizes 3d behavior via moment-to-moment action selection

    Cell 174:44–58.

    https://doi.org/10.1016/j.cell.2018.04.019

    • PubMed
    • Google Scholar
58. 1. Mattay VS
    2. Goldberg TE
    3. Fera F
    4. Hariri AR
    5. Tessitore A
    6. Egan MF
    7. Kolachana B
    8. Callicott JH
    9. Weinberger DR

    (2003) Catechol O-methyltransferase val158-met genotype and individual variation in the brain response to amphetamine

    PNAS 100:6186–6191.

    https://doi.org/10.1073/pnas.0931309100

    • PubMed
    • Google Scholar
59. 1. Meng C
    2. Zhou J
    3. Papaneri A
    4. Peddada T
    5. Xu K
    6. Cui G

    (2018) Spectrally resolved fiber photometry for multi-component analysis of brain circuits

    Neuron 98:707–717.

    https://doi.org/10.1016/j.neuron.2018.04.012

    • PubMed
    • Google Scholar
60. 1. Mink JW

    (1996) The basal ganglia: focused selection and inhibition of competing motor programs

    Progress in Neurobiology 50:381–425.

    https://doi.org/10.1016/s0301-0082(96)00042-1

    • PubMed
    • Google Scholar
61. 1. Mink JW

    (2003) The Basal Ganglia and involuntary movements: impaired inhibition of competing motor patterns

    Archives of Neurology 60:1365–1368.

    https://doi.org/10.1001/archneur.60.10.1365

    • PubMed
    • Google Scholar
62. 1. Nonomura S
    2. Nishizawa K
    3. Sakai Y
    4. Kawaguchi Y
    5. Kato S
    6. Uchigashima M
    7. Watanabe M
    8. Yamanaka K
    9. Enomoto K
    10. Chiken S
    11. Sano H
    12. Soma S
    13. Yoshida J
    14. Samejima K
    15. Ogawa M
    16. Kobayashi K
    17. Nambu A
    18. Isomura Y
    19. Kimura M

    (2018) Monitoring and updating of action selection for goal-directed behavior through the striatal direct and indirect pathways

    Neuron 99:1302–1314.

    https://doi.org/10.1016/j.neuron.2018.08.002

    • PubMed
    • Google Scholar
63. 1. Phillips JG
    2. Chiu E
    3. Bradshaw JL
    4. Iansek R

    (1995) Impaired movement sequencing in patients with Huntington’s disease: A kinematic analysis

    Neuropsychologia 33:365–369.

    https://doi.org/10.1016/0028-3932(94)00114-5

    • Google Scholar
64. 1. Redgrave P
    2. Prescott TJ
    3. Gurney K

    (1999) The basal ganglia: a vertebrate solution to the selection problem?

    Neuroscience 89:1009–1023.

    https://doi.org/10.1016/s0306-4522(98)00319-4

    • PubMed
    • Google Scholar
65. 1. Schmidt R
    2. Berke JD

    (2017) A Pause-then-Cancel model of stopping: evidence from basal ganglia neurophysiology

    Philosophical Transactions of the Royal Society B 372:20160202.

    https://doi.org/10.1098/rstb.2016.0202

    • Google Scholar
66. 1. Seeman P

    (2002)

    Atypical antipsychotics: mechanism of action

    Canadian Journal of Psychiatry. Revue Canadienne de Psychiatrie 47:27–38.

    • PubMed
    • Google Scholar
67. Book

    1. Sheskin DJ

    (2003) Handbook of Parametric and Nonparametric Statistical Procedures

    Chapman and Hall/CRC.

    https://doi.org/10.1201/9781420036268

    • Google Scholar
68. 1. Smith Y
    2. Bevan MD
    3. Shink E
    4. Bolam JP

    (1998) Microcircuitry of the direct and indirect pathways of the basal ganglia

    Neuroscience 86:353–387.

    https://doi.org/10.1016/s0306-4522(98)00004-9

    • PubMed
    • Google Scholar
69. 1. Tai LH
    2. Lee AM
    3. Benavidez N
    4. Bonci A
    5. Wilbrecht L

    (2012) Transient stimulation of distinct subpopulations of striatal neurons mimics changes in action value

    Nature Neuroscience 15:1281–1289.

    https://doi.org/10.1038/nn.3188

    • PubMed
    • Google Scholar
70. 1. Taverna S
    2. Ilijic E
    3. Surmeier DJ

    (2008) Recurrent collateral connections of striatal medium spiny neurons are disrupted in models of Parkinson’s disease

    The Journal of Neuroscience 28:5504–5512.

    https://doi.org/10.1523/JNEUROSCI.5493-07.2008

    • PubMed
    • Google Scholar
71. 1. Tecuapetla F
    2. Carrillo-Reid L
    3. Bargas J
    4. Galarraga E

    (2007) Dopaminergic modulation of short-term synaptic plasticity at striatal inhibitory synapses

    PNAS 104:10258–10263.

    https://doi.org/10.1073/pnas.0703813104

    • Google Scholar
72. 1. Tecuapetla F
    2. Jin X
    3. Lima SQ
    4. Costa RM

    (2016) Complementary contributions of striatal projection pathways to action initiation and execution

    Cell 166:703–715.

    https://doi.org/10.1016/j.cell.2016.06.032

    • PubMed
    • Google Scholar
73. 1. Wang XJ

    (2002) Probabilistic decision making by slow reverberation in cortical circuits

    Neuron 36:955–968.

    https://doi.org/10.1016/s0896-6273(02)01092-9

    • PubMed
    • Google Scholar
74. 1. Wei W
    2. Wang XJ

    (2016) Inhibitory control in the cortico-basal ganglia-thalamocortical loop: complex regulation and interplay with memory and decision processes

    Neuron 92:1093–1105.

    https://doi.org/10.1016/j.neuron.2016.10.031

    • PubMed
    • Google Scholar
75. 1. Wong DF
    2. Wagner HN Jr
    3. Tune LE
    4. Dannals RF
    5. Pearlson GD
    6. Links JM
    7. Tamminga CA
    8. Broussolle EP
    9. Ravert HT
    10. Wilson AA
    11. Toung JK
    12. Malat J
    13. Williams JA
    14. O’Tuama LA
    15. Snyder SH
    16. Kuhar MJ
    17. Gjedde A

    (1986) Positron emission tomography reveals elevated D2 dopamine receptors in drug-naive schizophrenics

    Science 234:1558–1563.

    https://doi.org/10.1126/science.2878495

    • PubMed
    • Google Scholar
76. 1. Wu Y
    2. Richard S
    3. Parent A

    (2000) The organization of the striatal output system: a single-cell juxtacellular labeling study in the rat

    Neuroscience Research 38:49–62.

    https://doi.org/10.1016/s0168-0102(00)00140-1

    • PubMed
    • Google Scholar
77. 1. Wurtz RH
    2. Hikosaka O

    (1986) Role of the basal ganglia in the initiation of saccadic eye movements

    Progress in Brain Research 64:175–190.

    https://doi.org/10.1016/S0079-6123(08)63412-3

    • PubMed
    • Google Scholar
78. 1. Yokoi F
    2. Gründer G
    3. Biziere K
    4. Stephane M
    5. Dogan AS
    6. Dannals RF
    7. Ravert H
    8. Suri A
    9. Bramer S
    10. Wong DF

    (2002) Dopamine D2 and D3 receptor occupancy in normal humans treated with the antipsychotic drug aripiprazole (OPC 14597): a study using positron emission tomography and [11C]raclopride

    Neuropsychopharmacology 27:248–259.

    https://doi.org/10.1016/S0893-133X(02)00304-4

    • PubMed
    • Google Scholar

Author details

1. Hao Li

   Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6312-4276

2. Xin Jin

   1. Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, United States
   2. Center for Motor Control and Disease, Key Laboratory of Brain Functional Genomics, East China Normal University, Shanghai, China
   3. NYU–ECNU Institute of Brain and Cognitive Science, New York University Shanghai, Shanghai, China

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   xjin@bio.ecnu.edu.cn

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1106-4013

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