Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Distinct basal ganglia circuits controlling behaviors guided by flexible and stable values.

ABSTRACT: Choosing valuable objects is critical for survival, but their values may change flexibly or remain stable. Therefore, animals should be able to update the object values flexibly by recent experiences and retain them stably by long-term experiences. However, it is unclear how the brain encodes the two conflicting forms of values and controls behavior accordingly. We found that distinct circuits of the primate caudate nucleus control behavior selectively in the flexible and stable value conditions. Single caudate neurons encoded the values of visual objects in a regionally distinct manner: flexible value coding in the caudate head and stable value coding in the caudate tail. Monkeys adapted in both conditions by looking at objects with higher values. Importantly, inactivation of each caudate subregion disrupted the high-low value discrimination selectively in the flexible or stable context. This parallel complementary mechanism enables animals to choose valuable objects in both flexible and stable conditions.

SUBMITTER: Kim HF

PROVIDER: S-EPMC3782315 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Distinct basal ganglia circuits controlling behaviors guided by flexible and stable values.

Kim Hyoung F HF Hikosaka Okihide O

Neuron 20130815 5

Choosing valuable objects is critical for survival, but their values may change flexibly or remain stable. Therefore, animals should be able to update the object values flexibly by recent experiences and retain them stably by long-term experiences. However, it is unclear how the brain encodes the two conflicting forms of values and controls behavior accordingly. We found that distinct circuits of the primate caudate nucleus control behavior selectively in the flexible and stable value conditions ...[more]

PMID: 23954031

Similar Datasets

Basal ganglia circuits for reward value-guided behavior.

Project description:The basal ganglia are equipped with inhibitory and disinhibitory mechanisms that enable a subject to choose valuable objects and actions. Notably, a value can be determined flexibly by recent experience or stably by prolonged experience. Recent studies have revealed that the head and tail of the caudate nucleus selectively and differentially process flexible and stable values of visual objects. These signals are sent to the superior colliculus through different parts of the substantia nigra so that the animal looks preferentially at high-valued objects, but in different manners. Thus, relying on short-term value memories, the caudate head circuit allows the subject's gaze to move expectantly to recently valued objects. Relying on long-term value memories, the caudate tail circuit allows the subject's gaze to move automatically to previously valued objects. The basal ganglia also contain an equivalent parallel mechanism for action values. Such flexible-stable parallel mechanisms for object and action values create a highly adaptable system for decision making.

| S-EPMC4148825 | biostudies-literature

Basal ganglia circuits changes in Parkinson's disease patients.

Project description:Functional changes in basal ganglia circuitry are responsible for the major clinical features of Parkinson's disease (PD). Current models of basal ganglia circuitry can only partially explain the cardinal symptoms in PD. We used functional MRI to investigate the causal connectivity of basal ganglia networks from the substantia nigra pars compacta (SNc) in PD in the movement and resting state. In controls, SNc activity predicted increased activity in the supplementary motor area, the default mode network, and dorsolateral prefrontal cortex, but, in patients, activity predicted decreases in the same structures. The SNc had decreased connectivity with the striatum, globus pallidus, subthalamic nucleus, thalamus, supplementary motor area, dorsolateral prefrontal cortex, insula, default mode network, temporal lobe, cerebellum, and pons in patients compared to controls. Levodopa administration partially normalized the pattern of connectivity. Our findings show how the dopaminergic system exerts influences on widespread brain networks, including motor and cognitive networks. The pattern of basal ganglia network connectivity is abnormal in PD secondary to dopamine depletion, and is more deviant in more severe disease. Use of functional MRI with network analysis appears to be a useful method to demonstrate basal ganglia pathways in vivo in human subjects.

| S-EPMC4163196 | biostudies-literature

Neural representation of time in cortico-basal ganglia circuits.

Project description:Encoding time is universally required for learning and structuring motor and cognitive actions, but how the brain keeps track of time is still not understood. We searched for time representations in cortico-basal ganglia circuits by recording from thousands of neurons in the prefrontal cortex and striatum of macaque monkeys performing a routine visuomotor task. We found that a subset of neurons exhibited time-stamp encoding strikingly similar to that required by models of reinforcement-based learning: They responded with spike activity peaks that were distributed at different time delays after single task events. Moreover, the temporal evolution of the population activity allowed robust decoding of task time by perceptron models. We suggest that time information can emerge as a byproduct of event coding in cortico-basal ganglia circuits and can serve as a critical infrastructure for behavioral learning and performance.

| S-EPMC2776432 | biostudies-literature

Cell-Type-Specific Control of Brainstem Locomotor Circuits by Basal Ganglia.

Project description:The basal ganglia (BG) are critical for adaptive motor control, but the circuit principles underlying their pathway-specific modulation of target regions are not well understood. Here, we dissect the mechanisms underlying BG direct and indirect pathway-mediated control of the mesencephalic locomotor region (MLR), a brainstem target of BG that is critical for locomotion. We optogenetically dissect the locomotor function of the three neurochemically distinct cell types within the MLR: glutamatergic, GABAergic, and cholinergic neurons. We find that the glutamatergic subpopulation encodes locomotor state and speed, is necessary and sufficient for locomotion, and is selectively innervated by BG. We further show activation and suppression, respectively, of MLR glutamatergic neurons by direct and indirect pathways, which is required for bidirectional control of locomotion by BG circuits. These findings provide a fundamental understanding of how BG can initiate or suppress a motor program through cell-type-specific regulation of neurons linked to specific actions.

| S-EPMC4733247 | biostudies-literature

Stable, flexible, common, and distinct behaviors support rule-based and information-integration category learning.

Project description:The ability to organize variable sensory signals into discrete categories is a fundamental process in human cognition thought to underlie many real-world learning problems. Decades of research suggests that two learning systems may support category learning and that categories with different distributional structures (rule-based, information-integration) optimally rely on different learning systems. However, it remains unclear how the same individual learns these different categories and whether the behaviors that support learning success are common or distinct across different categories. In two experiments, we investigate learning and develop a taxonomy of learning behaviors to investigate which behaviors are stable or flexible as the same individual learns rule-based and information-integration categories and which behaviors are common or distinct to learning success for these different types of categories. We found that some learning behaviors are stable in an individual across category learning tasks (learning success, strategy consistency), while others are flexibly task-modulated (learning speed, strategy, stability). Further, success in rule-based and information-integration category learning was supported by both common (faster learning speeds, higher working memory ability) and distinct factors (learning strategies, strategy consistency). Overall, these results demonstrate that even with highly similar categories and identical training tasks, individuals dynamically adjust some behaviors to fit the task and success in learning different kinds of categories is supported by both common and distinct factors. These results illustrate a need for theoretical perspectives of category learning to include nuances of behavior at the level of an individual learner.

| S-EPMC10183008 | biostudies-literature

A review of basal ganglia circuits and physiology: Application to deep brain stimulation.

Project description:INTRODUCTION:Drawing on the seminal work of DeLong, Albin, and Young, we have now entered an era of basal ganglia neuromodulation. Understanding, re-evaluating, and leveraging the lessons learned from neuromodulation will be crucial to facilitate an increased and improved application of neuromodulation in human disease. METHODS:We will focus on deep brain stimulation (DBS) - the most common form of basal ganglia neuromodulation - however, similar principles can apply to other neuromodulation modalities. We start with a brief review of DBS for Parkinson's disease, essential tremor, dystonia, and Tourette syndrome. We then review hallmark studies on basal ganglia circuits and electrophysiology resulting from decades of experience in neuromodulation. The organization and content of this paper follow Dr. Okun's Lecture from the 2018 Parkinsonism and Related Disorders World Congress. RESULTS:Information gained from neuromodulation has led to an expansion of the basal ganglia rate model, an enhanced understanding of nuclei dynamics, an emerging focus on pathological oscillations, a revision of the tripartite division of the basal ganglia, and a redirected focus toward individualized symptom-specific stimulation. Though there have been many limitations of the basal ganglia "box model," the construct provided the necessary foundation to advance the field. We now understand that information in the basal ganglia is encoded through complex neural responses that can be reliably measured and used to infer disease states for clinical translation. CONCLUSIONS:Our deepened understanding of basal ganglia physiology will drive new neuromodulation strategies such as adaptive DBS or cell-specific neuromodulation through the use of optogenetics.

| S-EPMC7020857 | biostudies-literature

Independent circuits in the basal ganglia for the evaluation and selection of actions.

Project description:The basal ganglia are critical for selecting actions and evaluating their outcome. Although the circuitry for selection is well understood, how these nuclei evaluate the outcome of actions is unknown. Here, we show in lamprey that a separate evaluation circuit, which regulates the habenula-projecting globus pallidus (GPh) neurons, exists within the basal ganglia. The GPh neurons are glutamatergic and can drive the activity of the lateral habenula, which, in turn, provides an indirect inhibitory influence on midbrain dopamine neurons. We show that GPh neurons receive inhibitory input from the striosomal compartment of the striatum. The striosomal input can reduce the excitatory drive to the lateral habenula and, consequently, decrease the inhibition onto the dopaminergic system. Dopaminergic neurons, in turn, provide feedback that inhibits the GPh. In addition, GPh neurons receive direct projections from the pallium (cortex in mammals), which can increase the GPh activity to drive the lateral habenula to increase the inhibition of the neuromodulatory systems. This circuitry, thus, differs markedly from the "direct" and "indirect" pathways that regulate the pallidal (e.g., globus pallidus) output nuclei involved in the control of motion. Our results show that a distinct reward-evaluation circuit exists within the basal ganglia, in parallel to the direct and indirect pathways, which select actions. Our results suggest that these circuits are part of the fundamental blueprint that all vertebrates use to select actions and evaluate their outcome.

| S-EPMC3780871 | biostudies-literature

Uncertainty-guided learning with scaled prediction errors in the basal ganglia.

Project description:To accurately predict rewards associated with states or actions, the variability of observations has to be taken into account. In particular, when the observations are noisy, the individual rewards should have less influence on tracking of average reward, and the estimate of the mean reward should be updated to a smaller extent after each observation. However, it is not known how the magnitude of the observation noise might be tracked and used to control prediction updates in the brain reward system. Here, we introduce a new model that uses simple, tractable learning rules that track the mean and standard deviation of reward, and leverages prediction errors scaled by uncertainty as the central feedback signal. We show that the new model has an advantage over conventional reinforcement learning models in a value tracking task, and approaches a theoretic limit of performance provided by the Kalman filter. Further, we propose a possible biological implementation of the model in the basal ganglia circuit. In the proposed network, dopaminergic neurons encode reward prediction errors scaled by standard deviation of rewards. We show that such scaling may arise if the striatal neurons learn the standard deviation of rewards and modulate the activity of dopaminergic neurons. The model is consistent with experimental findings concerning dopamine prediction error scaling relative to reward magnitude, and with many features of striatal plasticity. Our results span across the levels of implementation, algorithm, and computation, and might have important implications for understanding the dopaminergic prediction error signal and its relation to adaptive and effective learning.

| S-EPMC9182698 | biostudies-literature

Cannabinoids differentially modulate cortical information transmission through the sensorimotor or medial prefrontal basal ganglia circuits.

Project description:Background and purposeIn the sensorimotor (SM) and medial prefrontal (mPF) basal ganglia (BG) circuits, the cortical information is transferred to the substantia nigra pars reticulata (SNr) through the hyperdirect trans-subthalamic pathway and through the direct and indirect trans-striatal pathways. The cannabinoid CB1 receptor, which is highly expressed in both BG circuits, may participate in the regulation of motor and motivational behaviours. Here, we investigated the modulation of cortico-nigral information transmission through the BG circuits by cannabinoids.Experimental approachWe used single-unit recordings of SNr neurons along with simultaneous electrical stimulation of motor or mPF cortex in anaesthetized rats.Key resultsCortical stimulation elicited a triphasic response in the SNr neurons from both SM and mPF-BG circuits, which consisted of an early excitation (hyperdirect transmission pathway), an inhibition (direct transmission pathway), and a late excitation (indirect transmission pathway). In the SM circuit, after Δ9 -tetrahydrocannabinol or WIN 55,212-2 administration, the inhibition and the late excitation were decreased or completely lost, whereas the early excitation response remained unaltered. However, cannabinoid administration dramatically decreased all the responses in the mPF circuit. The CB1 receptor antagonist AM251 (2 mg·kg-1 , i.v.) did not modify the triphasic response, but blocked the effects induced by cannabinoid agonists.Conclusions and implicationsCB1 receptor activation modulates the SM information transmission through the trans-striatal pathways and profoundly decreases the cortico-BG transmission through the mPF circuit. These results may be relevant for elucidating the involvement of the cannabinoid system in motor performance and in decision making or goal-directed behaviour.

| S-EPMC6451076 | biostudies-literature

Medial thalamus in the territory of oculomotor basal ganglia represents stable object value.

Project description:Many visual objects are attached with values which were created by our long rewarding history. Such stable object values attract gaze. We previously found that the output pathway of basal ganglia from caudal-dorsal-lateral portion of substantia nigra pars reticulata (cdlSNr) to superior colliculus (SC) carries robust stable value signal to execute the automatic choice of valuable objects. An important question here is whether stable value signal in basal ganglia can influence on other inner processing such as perception, attention, emotion, or arousal than motor execution. The key brain circuit is another output path of basal ganglia: the pathway from SNr to temporal and frontal lobes through thalamus. To examine the existence of stable value signal in this pathway, we explored thalamus in a wide range. We found that many neurons in the medial thalamus represented stable value. Histological examination showed that the recorded sites of those neurons included ventral anterior nucleus, pars magnocellularis (VAmc) which is the main target of nigrothalamic projection. Consistent with the SNr GABArgic projection, the latency of value signal in the medial thalamus was later than cdlSNr, and the sign of value coding in the medial thalamus was opposite to cdlSNr. As is the case with cdlSNr neurons, the medial thalamus neurons showed no sensitivity to frequently updated value (flexible value). These results suggest that the pathway from cdlSNr to the medial thalamus influences on various aspects of cognitive processing by propagating stable value signal to the wide cortical area.

| S-EPMC6426671 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data