Amplitude Adaptive Modulation of Neural Oscillations Over Long-Term Dynamic Conditions: A Computational Study.

Closed-loop deep brain stimulation (DBS) shows great potential for precise neuromodulation of various neurological disorders, particularly Parkinson's disease (PD). However, substantial challenges remain in clinical translation due to the complex programming procedure of closed-loop DBS parameters. In this study, we proposed an online optimized amplitude adaptive strategy based on the particle swarm optimization (PSO) and proportional-integral-differential (PID) controller for modulation of the beta oscillation in a PD mean field model over long-term dynamic conditions. The strategy aimed to calculate the stimulation amplitude adapting to the fluctuations caused by circadian rhythm, medication rhythm, and stochasticity in the basal ganglia-thalamus-cortical circuit. The PID gains were optimized online using PSO, based on modulation accuracy, mean stimulation amplitude, and stimulation variation. The results showed that the proposed strategy optimized the stimulation amplitude and achieved beta power modulation under the influence of circadian rhythm, medication rhythm, and stochasticity of beta oscillations. This work offers a novel approach for precise neuromodulation with the potential for clinical translation.

Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model.

Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target.Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin-Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions.Main results.This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson's disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling.Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.

Modeling Synaptic Integration of Bursty and ß Oscillatory Inputs in Ventromedial Motor Thalamic Neurons in Normal and Parkinsonian States.

The ventromedial motor thalamus (VM) is implicated in multiple motor functions and occupies a central position in the cortico-basal ganglia-thalamocortical loop. It integrates glutamatergic inputs from motor cortex (MC) and motor-related subcortical areas, and it is a major recipient of inhibition from basal ganglia. Previous in vitro experiments performed in mice showed that dopamine depletion enhances the excitability of thalamocortical (TC) neurons in VM due to reduced M-type potassium currents. To understand how these excitability changes impact synaptic integration in vivo, we constructed biophysically detailed mouse VM TC model neurons fit to normal and dopamine-depleted conditions, using the NEURON simulator. These models allowed us to assess the influence of excitability changes with dopamine depletion on the integration of synaptic inputs expected in vivo We found that VM neuron models in the dopamine-depleted state showed increased firing rates with the same synaptic inputs. Synchronous bursting in inhibitory input from the substantia nigra pars reticulata (SNR), as observed in parkinsonian conditions, evoked a postinhibitory firing rate increase with a longer duration in dopamine-depleted than control conditions, due to different M-type potassium channel densities. With ß oscillations in the inhibitory inputs from SNR and the excitatory inputs from cortex, we observed spike-phase locking in the activity of the models in normal and dopamine-depleted states, which relayed and amplified the oscillations of the inputs, suggesting that the increased ß oscillations observed in VM of parkinsonian animals are predominantly a consequence of changes in the presynaptic activity rather than changes in intrinsic properties.

Competing neural representations of choice shape evidence accumulation in humans.

Making adaptive choices in dynamic environments requires flexible decision policies. Previously, we showed how shifts in outcome contingency change the evidence accumulation process that determines decision policies. Using in silico experiments to generate predictions, here we show how the cortico-basal ganglia-thalamic (CBGT) circuits can feasibly implement shifts in decision policies. When action contingencies change, dopaminergic plasticity redirects the balance of power, both within and between action representations, to divert the flow of evidence from one option to another. When competition between action representations is highest, the rate of evidence accumulation is the lowest. This prediction was validated in in vivo experiments on human participants, using fMRI, which showed that (1) evoked hemodynamic responses can reliably predict trial-wise choices and (2) competition between action representations, measured using a classifier model, tracked with changes in the rate of evidence accumulation. These results paint a holistic picture of how CBGT circuits manage and adapt the evidence accumulation process in mammals.

Suppression of beta oscillations by delayed feedback in a cortex-basal ganglia-thalamus-pedunculopontine nucleus neural loop model.

Excessive neural synchronization of neural populations in the beta (ß) frequency range (12-35 Hz) is intimately related to the symptoms of hypokinesia in Parkinson's disease (PD). Studies have shown that delayed feedback stimulation strategies can interrupt excessive neural synchronization and effectively alleviate symptoms associated with PD dyskinesia. Work on optimizing delayed feedback algorithms continues to progress, yet it remains challenging to further improve the inhibitory effect with reduced energy expenditure. Therefore, we first established a neural mass model of the cortex-basal ganglia-thalamus-pedunculopontine nucleus (CBGTh-PPN) closed-loop system, which can reflect the internal properties of cortical and basal ganglia neurons and their intrinsic connections with thalamic and pedunculopontine nucleus neurons. Second, the inhibitory effects of three delayed feedback schemes based on the external globus pallidum (GPe) on ß oscillations were investigated separately and compared with those based on the subthalamic nucleus (STN) only. Our results show that all four delayed feedback schemes achieve effective suppression of pathological ß oscillations when using the linear delayed feedback algorithm. The comparison revealed that the three GPe-based delayed feedback stimulation strategies were able to have a greater range of oscillation suppression with reduced energy consumption, thus improving control performance effectively, suggesting that they may be more effective for the relief of Parkinson's motor symptoms in practical applications.

Activation of Cerebellum, Basal Ganglia and Thalamus During Observation and Execution of Mouth, hand, and foot Actions.

Humans and monkey studies showed that specific sectors of cerebellum and basal ganglia activate not only during execution but also during observation of hand actions. However, it is unknown whether, and how, these structures are engaged during the observation of actions performed by effectors different from the hand. To address this issue, in the present fMRI study, healthy human participants were required to execute or to observe grasping acts performed with different effectors, namely mouth, hand, and foot. As control, participants executed and observed simple movements performed with the same effectors. The results show that: (1) execution of goal-directed actions elicited somatotopically organized activations not only in the cerebral cortex but also in the cerebellum, basal ganglia, and thalamus; (2) action observation evoked cortical, cerebellar and subcortical activations, lacking a clear somatotopic organization; (3) in the territories displaying shared activations between execution and observation, a rough somatotopy could be revealed in both cortical, cerebellar and subcortical structures. The present study confirms previous findings that action observation, beyond the cerebral cortex, also activates specific sectors of cerebellum and subcortical structures and it shows, for the first time, that these latter are engaged not only during hand actions observation but also during the observation of mouth and foot actions. We suggest that each of the activated structures processes specific aspects of the observed action, such as performing internal simulation (cerebellum) or recruiting/inhibiting the overt execution of the observed action (basal ganglia and sensory-motor thalamus).

Cerebellar Contributions to the Basal Ganglia Influence Motor Coordination, Reward Processing, and Movement Vigor.

Both the cerebellum and the basal ganglia are known for their roles in motor control and motivated behavior. These two systems have been classically considered as independent structures that coordinate their contributions to behavior via separate cortico-thalamic loops. However, recent evidence demonstrates the presence of a rich set of direct connections between these two regions. Although there is strong evidence for connections in both directions, for brevity we limit our discussion to the better-characterized connections from the cerebellum to the basal ganglia. We review two sets of such connections: disynaptic projections through the thalamus and direct monosynaptic projections to the midbrain dopaminergic nuclei, the VTA and the SNc. In each case, we review the evidence for these pathways from anatomic tracing and physiological recordings, and discuss their potential functional roles. We present evidence that the disynaptic pathway through the thalamus is involved in motor coordination, and that its dysfunction contributes to motor deficits, such as dystonia. We then discuss how cerebellar projections to the VTA and SNc influence dopamine release in the respective targets of these nuclei: the NAc and the dorsal striatum. We argue that the cerebellar projections to the VTA may play a role in reward-based learning and therefore contribute to addictive behavior, whereas the projection to the SNc may contribute to movement vigor. Finally, we speculate how these projections may explain many of the observations that indicate a role for the cerebellum in mental disorders, such as schizophrenia.

Dynamic reorganization of the cortico-basal ganglia-thalamo-cortical network during task learning.

Adaptive behavior is coordinated by neuronal networks that are distributed across multiple brain regions such as in the cortico-basal ganglia-thalamo-cortical (CBGTC) network. Here, we ask how cross-regional interactions within such mesoscale circuits reorganize when an animal learns a new task. We apply multi-fiber photometry to chronically record simultaneous activity in 12 or 48 brain regions of mice trained in a tactile discrimination task. With improving task performance, most regions shift their peak activity from the time of reward-related action to the reward-predicting stimulus. By estimating cross-regional interactions using transfer entropy, we reveal that functional networks encompassing basal ganglia, thalamus, neocortex, and hippocampus grow and stabilize upon learning, especially at stimulus presentation time. The internal globus pallidus, ventromedial thalamus, and several regions in the frontal cortex emerge as salient hub regions. Our results highlight the learning-related dynamic reorganization that brain networks undergo when task-appropriate mesoscale network dynamics are established for goal-oriented behavior.

Dynamic control of visually guided locomotion through corticosubthalamic projections.

Goal-directed locomotion requires control signals that propagate from higher order areas to regulate spinal mechanisms. The corticosubthalamic hyperdirect pathway offers a short route for cortical information to reach locomotor centers in the brainstem. We developed a task in which head-fixed mice run to a visual landmark and then stop and wait to collect the reward and examined the role of secondary motor cortex (M2) projections to the subthalamic nucleus (STN) in controlling locomotion. Our behavioral modeling, calcium imaging, and optogenetics manipulation results suggest that the M2-STN pathway can be recruited during visually guided locomotion to rapidly and precisely control the pedunculopontine nucleus (PPN) of the mesencephalic locomotor region through the basal ganglia. By capturing the physiological dynamics through a feedback control model and analyzing neuronal signals in M2, PPN, and STN, we find that the corticosubthalamic projections potentially control PPN activity by differentiating an M2 error signal to ensure fast input-output dynamics.

Exploring phase-amplitude coupling from primary motor cortex-basal ganglia-thalamus network model.

The purpose of this study is to develop a primary motor cortex (M1)-basal ganglia-thalamus model capable of reproducing the physiological phenomenon of exaggerated phase-amplitude coupling (PAC) in Parkinson's disease and exploring the potential sources of PAC anomalies in M1. The subthalamic nucleus (STN) phase-STN amplitude coupling, STN phase-M1 amplitude coupling, and M1 phase-M1 amplitude coupling are reproduced, where the phase frequencies are distributed in the beta band and the amplitude frequencies are distributed in the broad gamma band. We mainly study the impacts of thalamus →M1 connections and STN↔M1 bidirectional synaptic connections. Abnormal beta oscillations generated within the basal ganglia are found to be transmitted to M1 through the STN or thalamus and could be one of the potential sources of PAC-related beta oscillations in M1, thereby interfering with high-frequency signals in the motor cortex. Furthermore, the weakening of M1→STN leads to a shift of the oscillations of the STN from the high beta band to the low beta band, which is more consistent with pathological experiments, thus supporting the experimental results that the hyper-direct path from M1 to STN drives the beta oscillations of STN. Finally, the suppression effect of STN deep brain stimulation on PAC is investigated. As the stimulation frequency increases, the PAC modulation index within different regions gradually decreases, in general agreement with the trend of synchronization level and beta oscillation energy, indirectly indicating that PAC can be used as a feedback indicator of parkinsonian state.

Identifying control ensembles for information processing within the cortico-basal ganglia-thalamic circuit.

In situations featuring uncertainty about action-reward contingencies, mammals can flexibly adopt strategies for decision-making that are tuned in response to environmental changes. Although the cortico-basal ganglia thalamic (CBGT) network has been identified as contributing to the decision-making process, it features a complex synaptic architecture, comprised of multiple feed-forward, reciprocal, and feedback pathways, that complicate efforts to elucidate the roles of specific CBGT populations in the process by which evidence is accumulated and influences behavior. In this paper we apply a strategic sampling approach, based on Latin hypercube sampling, to explore how variations in CBGT network properties, including subpopulation firing rates and synaptic weights, map to variability of parameters in a normative drift diffusion model (DDM), representing algorithmic aspects of information processing during decision-making. Through the application of canonical correlation analysis, we find that this relationship can be characterized in terms of three low-dimensional control ensembles within the CBGT network that impact specific qualities of the emergent decision policy: responsiveness (a measure of how quickly evidence evaluation gets underway, associated with overall activity in corticothalamic and direct pathways), pliancy (a measure of the standard of evidence needed to commit to a decision, associated largely with overall activity in components of the indirect pathway of the basal ganglia), and choice (a measure of commitment toward one available option, associated with differences in direct and indirect pathways across action channels). These analyses provide mechanistic predictions about the roles of specific CBGT network elements in tuning the way that information is accumulated and translated into decision-related behavior.

Virtual deep brain stimulation: Multiscale co-simulation of a spiking basal ganglia model and a whole-brain mean-field model with The Virtual Brain.

Deep brain stimulation (DBS) has been successfully applied in various neurodegenerative diseases as an effective symptomatic treatment. However, its mechanisms of action within the brain network are still poorly understood. Many virtual DBS models analyze a subnetwork around the basal ganglia and its dynamics as a spiking network with their details validated by experimental data. However, connectomic evidence shows widespread effects of DBS affecting many different cortical and subcortical areas. From a clinical perspective, various effects of DBS besides the motoric impact have been demonstrated. The neuroinformatics platform The Virtual Brain (TVB) offers a modeling framework allowing us to virtually perform stimulation, including DBS, and forecast the outcome from a dynamic systems perspective prior to invasive surgery with DBS lead placement. For an accurate prediction of the effects of DBS, we implement a detailed spiking model of the basal ganglia, which we combine with TVB via our previously developed co-simulation environment. This multiscale co-simulation approach builds on the extensive previous literature of spiking models of the basal ganglia while simultaneously offering a whole-brain perspective on widespread effects of the stimulation going beyond the motor circuit. In the first demonstration of our model, we show that virtual DBS can move the firing rates of a Parkinson's disease patient's thalamus - basal ganglia network towards the healthy regime while, at the same time, altering the activity in distributed cortical regions with a pronounced effect in frontal regions. Thus, we provide proof of concept for virtual DBS in a co-simulation environment with TVB. The developed modeling approach has the potential to optimize DBS lead placement and configuration and forecast the success of DBS treatment for individual patients.

Contribution of the sensorimotor beta oscillations and the cortico-basal ganglia-thalamic circuitry during value-based decision making: A simultaneous EEG-fMRI investigation.

In decision neuroscience, the motor system has primarily been considered to be involved in executing choice actions. However, a competing perspective suggests its engagement in the evaluation of options, traditionally considered to be performed by the brain's valuation system. Here, we investigate the role of the motor system in value-based decision making by determining the neural circuitries associated with the sensorimotor beta oscillations previously identified to encode decision options. In a simultaneous EEG-fMRI study, participants evaluated reward and risk associated with a forthcoming action. A significant sensorimotor beta desynchronization was identified prior to and independent of response. The level of beta desynchronization showed evidence of encoding the reward levels. This beta desynchronization covaried, on a trial-by-trial level, with BOLD activity in the cortico-basal ganglia-thalamic circuitry. In contrast, there was only a weak covariation within the valuation network, despite significant modulation of its BOLD activity by reward levels. These results suggest that the way in which decision variables are processed differs in the valuation network and in the cortico-basal ganglia-thalamic circuitry. We propose that sensorimotor beta oscillations indicate incentive motivational drive towards a choice action computed from the decision variables even prior to making a response, and it arises from the cortico-basal ganglia-thalamic circuitry.

Processing of information from the parafascicular nucleus of the thalamus through the basal ganglia.

Accumulating evidence implicates the parafascicular nucleus of the thalamus (Pf) in basal ganglia (BG)-related functions and pathologies. Despite Pf connectivity with all BG components, most attention is focused on the thalamostriatal system and an integrated view of thalamic information processing in this network is still lacking. Here, we addressed this question by recording the responses elicited by Pf activation in single neurons of the substantia nigra pars reticulata (SNr), the main BG output structure in rodents, in anesthetized mice. We performed optogenetic activation of Pf neurons innervating the striatum, the subthalamic nucleus (STN), or the SNr using virally mediated transcellular delivery of Cre from injection in either target in Rosa26-LoxP-stop-ChR2-EYFP mice to drive channelrhodopsin expression. Photoactivation of Pf neurons connecting the striatum evoked an inhibition often followed by an excitation, likely resulting from the activation of the trans-striatal direct and indirect pathways, respectively. Photoactivation of Pf neurons connecting the SNr or the STN triggered one or two early excitations, suggesting partial functional overlap of trans-subthalamic and direct thalamonigral projections. Excitations were followed in about half of the cases by an inhibition that might reflect recruitment of intranigral inhibitory loops. Finally, global Pf stimulation, electrical or optogenetic, elicited similar complex responses comprising up to four components: one or two short-latency excitations, an inhibition, and a late excitation. These data provide evidence for functional connections between the Pf and different BG components and for convergence of the information processed through these pathways in single SNr neurons, stressing their importance in regulating BG outflow.

Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit.

Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson's disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple "reversible lesion" effect to augment network communication. Specifically, we examined the modulation of beta band (14-30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson's. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease.

Effects of thalamic and basal ganglia deep brain stimulation on language-related functions - Conceptual and clinical considerations.

Deep Brain Stimulation (DBS) is a therapy for various neurological movement disorders. It acts predominantly on motor symptoms, but may unfold a number of mostly subtle cognitive effects. In this regard, reports on particular language-related DBS sequels are comparably frequent, but difficult to overlook, given the heterogeneity of targeted structures in the brain, treated diseases, assessment methods and results reported. Accordingly, available knowledge was organized with respect to important aspects, such as the main DBS loci and surgical versus neuromodulatory therapy actions. Current views of biolinguistic underpinnings of the reviewed data, their clinical relevance and potential implications are discussed.

Enhanced habit formation in Tourette patients explained by shortcut modulation in a hierarchical cortico-basal ganglia model.

Devaluation protocols reveal that Tourette patients show an increased propensity to habitual behaviors as they continue to respond to devalued outcomes in a cognitive stimulus-response-outcome association task. We use a neuro-computational model of hierarchically organized cortico-basal ganglia-thalamo-cortical loops to shed more light on habit formation and its alteration in Tourette patients. In our model, habitual behavior emerges from cortico-thalamic shortcut connections, where enhanced habit formation can be linked to faster plasticity in the shortcut or to a stronger feedback from the shortcut to the basal ganglia. We explore two major hypotheses of Tourette pathophysiology-local striatal disinhibition and increased dopaminergic modulation of striatal medium spiny neurons-as causes for altered shortcut activation. Both model changes altered shortcut functioning and resulted in higher rates of responses towards devalued outcomes, similar to what is observed in Tourette patients. We recommend future experimental neuroscientific studies to locate shortcuts between cortico-basal ganglia-thalamo-cortical loops in the human brain and study their potential role in health and disease.

Challenges for future theories of Parkinson pathophysiology.

Current theories on the basal ganglia-thalamic-cortical circuitry address the phenomena of hypokinesia and hyperkinesia. In this Perspective, we question whether the current models can address the orchestration of the motor units which is the common final pathway of the motor system. We conclude that the current theories do not to address this orchestration in health and disease. One alternative approach worthy of consideration is nonmonotonic nonlinear dynamics that contrast with a fundamentally linear or monotonic nonlinear approach that are presumed by current theories of basal ganglia-thalamic-cortical system. The purpose here is to make the case that current theories do presuppose a linear or monotonic nonlinear perspective which will be demonstrated as failing to adequately explicate the complex orchestration of motor unit activities in normal movement and in movement disorders. The notion of nonlinear dynamics is not new to neurophysiology; however, it is argued that it is new to the concepts of the physiology and pathophysiology of the basal ganglia-thalamic-cortical system. Providing a wholesale reconceptualization of the basal ganglia-thalamic-cortical system is beyond the scope of this effort. Rather, the contribution of the essay is convincing that there is a need to reconceptualize theories as nonlinear dynamical systems and there are metaphors and analogies from nonlinear science that can be productive in the reconsideration.

Mapping the subcortical connectivity of the human default mode network.

The default mode network (DMN) mediates self-awareness and introspection, core components of human consciousness. Therapies to restore consciousness in patients with severe brain injuries have historically targeted subcortical sites in the brainstem, thalamus, hypothalamus, basal forebrain, and basal ganglia, with the goal of reactivating cortical DMN nodes. However, the subcortical connectivity of the DMN has not been fully mapped, and optimal subcortical targets for therapeutic neuromodulation of consciousness have not been identified. In this work, we created a comprehensive map of DMN subcortical connectivity by combining high-resolution functional and structural datasets with advanced signal processing methods. We analyzed 7 Tesla resting-state functional MRI (rs-fMRI) data from 168 healthy volunteers acquired in the Human Connectome Project. The rs-fMRI blood-oxygen-level-dependent (BOLD) data were temporally synchronized across subjects using the BrainSync algorithm. Cortical and subcortical DMN nodes were jointly analyzed and identified at the group level by applying a novel Nadam-Accelerated SCAlable and Robust (NASCAR) tensor decomposition method to the synchronized dataset. The subcortical connectivity map was then overlaid on a 7 Tesla 100 µm ex vivo MRI dataset for neuroanatomic analysis using automated segmentation of nuclei within the brainstem, thalamus, hypothalamus, basal forebrain, and basal ganglia. We further compared the NASCAR subcortical connectivity map with its counterpart generated from canonical seed-based correlation analyses. The NASCAR method revealed that BOLD signal in the central lateral nucleus of the thalamus and ventral tegmental area of the midbrain is strongly correlated with that of the DMN. In an exploratory analysis, additional subcortical sites in the median and dorsal raphe, lateral hypothalamus, and caudate nuclei were correlated with the cortical DMN. We also found that the putamen and globus pallidus are negatively correlated (i.e., anti-correlated) with the DMN, providing rs-fMRI evidence for the mesocircuit hypothesis of human consciousness, whereby a striatopallidal feedback system modulates anterior forebrain function via disinhibition of the central thalamus. Seed-based analyses yielded similar subcortical DMN connectivity, but the NASCAR result showed stronger contrast and better spatial alignment with dopamine immunostaining data. The DMN subcortical connectivity map identified here advances understanding of the subcortical regions that contribute to human consciousness and can be used to inform the selection of therapeutic targets in clinical trials for patients with disorders of consciousness.

A cortico-basal ganglia-thalamo-cortical channel underlying short-term memory.

Persistent activity underlying short-term memory encodes sensory information or instructs specific future movement and, consequently, has a crucial role in cognition. Despite extensive study, how the same set of neurons respond differentially to form selective persistent activity remains unknown. Here, we report that the cortico-basal ganglia-thalamo-cortical (CBTC) circuit supports the formation of selective persistent activity in mice. Optogenetic activation or inactivation of the basal ganglia output nucleus substantia nigra pars reticulata (SNr)-to-thalamus pathway biased future licking choice, without affecting licking execution. This perturbation differentially affected persistent activity in the frontal cortex and selectively modulated neural trajectory that encodes one choice but not the other. Recording showed that SNr neurons had selective persistent activity distributed across SNr, but with a hotspot in the mediolateral region. Optogenetic inactivation of the frontal cortex also differentially affected persistent activity in the SNr. Together, these results reveal a CBTC channel functioning to produce selective persistent activity underlying short-term memory.