Hold your horses: A dynamic computational role for the subthalamic nucleus in decision making

Subthalamic nucleus dynamics during executive functioning: Insights from local field potentials in Parkinson's disease

This study explores the involvement of the subthalamic nucleus (STN) in executive functions, particularly cognitive flexibility, in Parkinson's disease (PD) patients. Utilizing a computerized Wisconsin Card Sorting Task (WCST) and local field potential (LFP) recordings from implanted deep brain stimulation (DBS) electrodes, we investigated task-specific neural dynamics. Behavioural results demonstrated increased error rates and prolonged response times in trials requiring set-shifting and rule induction via cross-temporal information integration. Electrophysiological analyses revealed integration-specific LFP modulations, including enhanced theta-band activity linked to conflict monitoring and cognitive control during high-demand trials, and beta-band suppression associated with motor inhibition and task disengagement. These findings underscore the STN's integrative role in non-motor domains, supporting its function in cross-temporal information integration for cognitive control. The results also highlight the utility of the WCST for assessing multiple executive processes and the potential of LFP-based biomarkers to refine DBS programming. Despite the relatively small sample size, this study provides novel insights into the oscillatory dynamics of the STN, emphasizing its broader role in decision-making and executive control. Future research should expand the understanding of the STN's contributions across cognitive domains.

How the dynamic interplay of cortico-basal ganglia-thalamic pathways shapes the time course of deliberation and commitment

Although the cortico-basal ganglia-thalamic (CBGT) network is identified as a central circuit for decision-making, the dynamic interplay of multiple control pathways within this network in shaping decision trajectories remains poorly understood. Here we develop and apply a novel computational framework - CLAW (Circuit Logic Assessed via Walks) - for tracing the instantaneous flow of neural activity as it progresses through CBGT networks engaged in a virtual decision-making task. Our CLAW analysis reveals that the complex dynamics of network activity is functionally dissectible into two critical phases: deliberation and commitment. These two phases are governed by distinct contributions of underlying CBGT pathways, with indirect and pallidostriatal pathways influencing deliberation, while the direct pathway drives action commitment. We translate CBGT dynamics into the evolution of decision-related policies, based on three previously identified control ensembles (responsiveness, pliancy, and choice) that encapsulate the relationship between CBGT activity and the evidence accumulation process. Our results demonstrate two contrasting strategies for decision-making. Fast decisions, with direct pathway dominance, feature an early response in both boundary height and drift rate, leading to a rapid collapse of decision boundaries and a clear directional bias. In contrast, slow decisions, driven by indirect and pallidostriatal pathway dominance, involve delayed changes in both decision policy parameters, allowing for an extended period of deliberation before commitment to an action. These analyses provide important insights into how the CBGT circuitry can be tuned to adopt various decision strategies and how the decision-making process unfolds within each regime.

Subthalamic Activity Is Associated With Proactive Inhibition in Parkinson's Disease Patients

The subthalamic nucleus (STN) is a key element of the indirect pathway of the basal ganglia (BG) and an effective target for improving motor symptoms in Parkinson's disease (PD) using deep brain stimulation (DBS). While dopamine neuron loss in PD results in a net shift towards increased inhibitory output from the BG, the precise mechanisms by which STN contributes to diminished movement remain unclear due to the complexity and multiplicity of processes underlying response inhibition. We used a modified Go/NoGo task varying uncertainty about Go or NoGo responses to determine how changes in response inhibition are related to STN local field potentials measured in 19 PD patients operated for STN-DBS. When engaged in the task, low-frequency band (LFB, 2-7 Hz; including the theta band, 4-7 Hz) power was significantly increased by dopamine treatment. LFB power significantly increased when there was uncertainty about the requirement of executing or withholding a response compared to when a response was certain. Increases in LFB power in individual trials were also significantly associated with faster reaction times. By contrast, beta band (12-30 Hz) power exhibited an inverted profile: It was significantly decreased by dopamine treatment, increased by response certainty and associated with slower reaction times. Our results suggest that STN low-frequency activity during voluntary behaviour may complement and enhance information obtained from the beta band and should be considered as a possible biomarker for the regulation of inhibition in uncertain contexts.

CBGTPy: An extensible cortico-basal ganglia-thalamic framework for modeling biological decision making

Here we introduce CBGTPy, a virtual environment for designing and testing goal-directed agents with internal dynamics that are modeled on the cortico-basal-ganglia-thalamic (CBGT) pathways in the mammalian brain. CBGTPy enables researchers to investigate the internal dynamics of the CBGT system during a variety of tasks, allowing for the formation of testable predictions about animal behavior and neural activity. The framework has been designed around the principle of flexibility, such that many experimental parameters in a decision making paradigm can be easily defined and modified. Here we demonstrate the capabilities of CBGTPy across a range of single and multi-choice tasks, highlighting the ease of set up and the biologically realistic behavior that it produces. We show that CBGTPy is extensible enough to apply to a range of experimental protocols and to allow for the implementation of model extensions with minimal developmental effort.

Basal ganglia components have distinct computational roles in decision-making dynamics under conflict and uncertainty

The basal ganglia (BG) play a key role in decision-making, preventing impulsive actions in some contexts while facilitating fast adaptations in others. The specific contributions of different BG structures to this nuanced behavior remain unclear, particularly under varying situations of noisy and conflicting information that necessitate ongoing adjustments in the balance between speed and accuracy. Theoretical accounts suggest that dynamic regulation of the amount of evidence required to commit to a decision (a dynamic "decision boundary") may be necessary to meet these competing demands. Through the application of novel computational modeling tools in tandem with direct neural recordings from human BG areas, we find that neural dynamics in the theta band manifest as variations in a collapsing decision boundary as a function of conflict and uncertainty. We collected intracranial recordings from patients diagnosed with either Parkinson's disease (PD) (n = 14) or dystonia (n = 3) in the subthalamic nucleus (STN), globus pallidus internus (GPi), and globus pallidus externus (GPe) during their performance of a novel perceptual discrimination task in which we independently manipulated uncertainty and conflict. To formally characterize whether these task and neural components influenced decision dynamics, we leveraged modified diffusion decision models (DDMs). Behavioral choices and response time distributions were best characterized by a modified DDM in which the decision boundary collapsed over time, but where the onset and shape of this collapse varied with conflict. Moreover, theta dynamics in BG structures modulated the onset and shape of this collapse but differentially across task conditions. In STN, theta activity was related to a prolonged decision boundary (indexed by slower collapse and therefore more deliberate choices) during high conflict situations. Conversely, rapid declines in GPe theta during low conflict conditions were related to rapidly collapsing boundaries and expedited choices, with additional complementary decision bound adjustments during high uncertainty situations. Finally, GPi theta effects were uniform across conditions, with increases in theta associated with a prolongation of decision bound collapses. Together, these findings provide a nuanced understanding of how our brain thwarts impulsive actions while nonetheless enabling behavioral adaptation amidst noisy and conflicting information.

Reward Reinforcement Creates Enduring Facilitation of Goal-directed Behavior

Stimulus-response habits benefit behavior by automatizing the selection of rewarding actions. However, this automaticity can come at the cost of reduced flexibility to adapt behavior when circumstances change. The goal-directed system is thought to counteract the habit system by providing the flexibility to pursue context-appropriate behaviors. The dichotomy between habitual action selection and flexible goal-directed behavior has recently been challenged by findings showing that rewards bias both action and goal selection. Here, we test whether reward reinforcement can give rise to habitual goal selection much as it gives rise to habitual action selection. We designed a rewarded, context-based perceptual discrimination task in which performance on one rule was reinforced. Using drift-diffusion models and psychometric analyses, we found that reward facilitates the initiation and execution of rules. Strikingly, we found that these biases persisted in a test phase in which rewards were no longer available. Although this facilitation is consistent with the habitual goal selection hypothesis, we did not find evidence that reward reinforcement reduced cognitive flexibility to implement alternative rules. Together, the findings suggest that reward creates a lasting impact on the selection and execution of goals but may not lead to the inflexibility characteristic of habits. Our findings demonstrate the role of the reward learning system in influencing how the goal-directed system selects and implements goals.

Subthalamic control of impulsive actions: insights from deep brain stimulation in Parkinson's disease

Control of actions allows adaptive, goal-directed behaviour. The basal ganglia, including the subthalamic nucleus, are thought to play a central role in dynamically controlling actions through recurrent negative feedback loops with the cerebral cortex. Here, we summarize recent translational studies that used deep brain stimulation to record neural activity from and apply electrical stimulation to the subthalamic nucleus in people with Parkinson's disease. These studies have elucidated spatial, spectral and temporal features of the neural mechanisms underlying the controlled delay of actions in cortico-subthalamic networks and demonstrated their causal effects on behaviour in distinct processing windows. While these mechanisms have been conceptualized as control signals for suppressing impulsive response tendencies in conflict tasks and as decision threshold adjustments in value-based and perceptual decisions, we propose a common framework linking decision-making, cognition and movement. Within this framework, subthalamic deep brain stimulation can lead to suboptimal choices by reducing the time that patients take for deliberation before committing to an action. However, clinical studies have consistently shown that the occurrence of impulse control disorders is reduced, not increased, after subthalamic deep brain stimulation surgery. This apparent contradiction can be reconciled when recognizing the multifaceted nature of impulsivity, its underlying mechanisms and modulation by treatment. While subthalamic deep brain stimulation renders patients susceptible to making decisions without proper forethought, this can be disentangled from effects related to dopamine comprising sensitivity to benefits versus costs, reward delay aversion and learning from outcomes. Alterations in these dopamine-mediated mechanisms are thought to underlie the development of impulse control disorders and can be relatively spared with reduced dopaminergic medication after subthalamic deep brain stimulation. Together, results from studies using deep brain stimulation as an experimental tool have improved our understanding of action control in the human brain and have important implications for treatment of patients with neurological disorders.

Subthalamic stimulation causally modulates human voluntary decision-making to stay or go

The voluntary nature of decision-making is fundamental to human behavior. The subthalamic nucleus is important in reactive decision-making, but its role in voluntary decision-making remains unclear. We recorded from deep brain stimulation subthalamic electrodes time-locked with acute stimulation using a Go/Nogo task to assess voluntary action and inaction. Beta oscillations during voluntary decision-making were temporally dissociated from motor function. Parkinson's patients showed an inaction bias with high beta and intermediate physiological states. Stimulation reversed the inaction bias highlighting its causal nature, and shifting physiology closer to reactive choices. Depression was associated with higher alpha during Voluntary-Nogo characterized by inaction or inertial status quo maintenance whereas apathy had higher beta-gamma during voluntary action or impaired effortful initiation of action. Our findings suggest the human subthalamic nucleus causally contributes to voluntary decision-making, possibly through threshold gating or toggling mechanisms, with stimulation shifting towards voluntary action and suggest biomarkers as potential clinical predictors.

Invasive neurophysiological recordings in human basal ganglia. What have we learned about non-motor behaviour?

Research into the function of deep brain structures has benefited greatly from microelectrode recordings in animals. This has helped to unravel physiological processes in the healthy and malfunctioning brain. Translation to the human is necessary for improving basic understanding of subcortical structures and their implications in diseases. The use of microelectrode recordings as a standard component of deep brain stimulation surgery offers the most viable route for studying the electrophysiology of single cells and local neuronal populations in important deep structures of the human brain. Most of the studies in the basal ganglia have targeted the motor loop and movement disorder pathophysiology. In recent years, however, research has diversified to include limbic and cognitive processes. This review aims to provide an overview of advances in neuroscience made using intraoperative and post-operative recordings with a focus on non-motor activity in the basal ganglia.

Subcortical Aphasia: An Update

PURPOSE OF REVIEW

This review aims to rediscuss the leading theories concerning the role of basal ganglia and the thalamus in the genesis of aphasic symptoms in the absence of gross anatomical lesions in cortical language areas as assessed by conventional neuroimaging studies.

RECENT FINDINGS

New concepts in language processing and modern neuroimaging techniques have enabled some progress in resolving the impasse between the current dominant theories: (a) direct and specific linguistic processing and (b) subcortical structures as processing relays in domain-general functions. Of particular interest are studies of connectivity based on functional magnetic resonance imaging (MRI) and tractography that highlight the impact of white matter pathway lesions on aphasia development and recovery. Connectivity studies have put into evidence the central role of the arcuate fasciculus (AF), inferior frontal occipital fasciculus (IFOF), and uncinate fasciculus (UF) in the genesis of aphasia. Regarding the thalamus, its involvement in lexical-semantic processing through modulation of the frontal cortex is becoming increasingly apparent.

Valence-dependent dopaminergic modulation during reversal learning in Parkinson's disease: A neurocomputational approach

Reinforcement learning, crucial for behavior in dynamic environments, is driven by rewards and punishments, modulated by dopamine (DA) changes. This study explores the dopaminergic system's influence on learning, particularly in Parkinson's disease (PD), where medication leads to impaired adaptability. Highlighting the role of tonic DA in signaling the valence of actions, this research investigates how DA affects response vigor and decision-making in PD. DA not only influences reward and punishment learning but also indicates the cognitive effort level and risk propensity in actions, which are essential for understanding and managing PD symptoms. In this work, we adapt our existing neurocomputational model of basal ganglia (BG) to simulate two reversal learning tasks proposed by Cools et al. We first optimized a Hebb rule for both probabilistic and deterministic reversal learning, conducted a sensitivity analysis (SA) on parameters related to DA effect, and compared performances between three groups: PD-ON, PD-OFF, and control subjects. In our deterministic task simulation, we explored switch error rates after unexpected task switches and found a U-shaped relationship between tonic DA levels and switch error frequency. Through SA, we classify these three groups. Then, assuming that the valence of the stimulus affects the tonic levels of DA, we were able to reproduce the results by Cools et al. As for the probabilistic task simulation, our results are in line with clinical data, showing similar trends with PD-ON, characterized by higher tonic DA levels that are correlated with increased difficulty in both acquisition and reversal tasks. Our study proposes a new hypothesis: valence, signaled by tonic DA levels, influences learning in PD, confirming the uncorrelation between phasic and tonic DA changes. This hypothesis challenges existing paradigms and opens new avenues for understanding cognitive processes in PD, particularly in reversal learning tasks.

Low-beta versus high-beta band cortico-subcortical coherence in movement inhibition and expectation

Beta band oscillations in the sensorimotor cortex and subcortical structures, such as the subthalamic nucleus (STN) and internal pallidum (GPi), are closely linked to motor control. Recent research suggests that low-beta (14.5-23.5 Hz) and high-beta (23.5-35 Hz) cortico-STN coherence arise through distinct networks, possibly reflecting indirect and hyperdirect pathways. In this study, we sought to probe whether low- and high-beta coherence also exhibit different functional roles in facilitating and inhibiting movement. Twenty patients with Parkinson's disease who had deep brain stimulation electrodes implanted in either STN or GPi performed a classical go/nogo task while undergoing simultaneous magnetoencephalography and local field potentials recordings. Subjects' expectations were manipulated by presenting go- and nogo-trials with varying probabilities. We identified a lateral source in the sensorimotor cortex for low-beta coherence, as well as a medial source near the supplementary motor area for high-beta coherence. Task-related coherence time courses for these two sources revealed that low-beta coherence was more strongly implicated than high-beta coherence in the performance of go-trials. Accordingly, average pre-stimulus low-beta but not high-beta coherence or spectral power correlated with overall reaction time across subjects. High-beta coherence during unexpected nogo-trials was higher compared to expected nogo-trials at a relatively long latency of 3 s after stimulus presentation. Neither low- nor high-beta coherence showed a significant correlation with patients' symptom severity at baseline assessment. While low-beta cortico-subcortical coherence appears to be related to motor output, the role of high-beta coherence requires further investigation.

Machine learning for the localization of Subthalamic Nucleus during deep brain stimulation surgery: a systematic review and Meta-analysis

INTRODUCTION

Delineating subthalamic nucleus (STN) boundaries using microelectrode recordings (MER) and trajectory history is a valuable resource for neurosurgeons, aiding in the accurate and efficient positioning of deep brain stimulation (DBS) electrodes within the STN. Here, we aimed to assess the application of artificial intelligence, specifically Hidden Markov Models (HMM), in the context of STN localization.

METHODS

A comprehensive search strategy was employed, encompassing electronic databases, including PubMed, EuroPMC, and MEDLINE. This search strategy entailed a combination of controlled vocabulary (e.g., MeSH terms) and free-text keywords pertaining to "artificial intelligence," "machine learning," "deep learning," and "deep brain stimulation." Inclusion criteria were applied to studies reporting the utilization of HMM for predicting outcomes in DBS, based on structured patient-level health data, and published in the English language.

RESULTS

This systematic review incorporated a total of 14 studies. Various machine learning compared wavelet feature to proposed features in diagnosing the STN, with the HMM yielding a diagnostic odds ratio (DOR) of 838.677 (95% CI: 203.309-3459.645). Similarly, the K-Nearest Neighbors (KNN) model produced parameter estimates, including a diagnostic odds ratio of 25.151 (95% CI: 12.270-51.555). Meanwhile, the support vector machine (SVM) model exhibited parameter estimates, with a DOR of 13.959 (95% CI: 10.436-18.671).

CONCLUSIONS

MER data demonstrates significant variability in neural activity, with studies employing a wide range of methodologies. Machine learning plays a crucial role in aiding STN diagnosis, though its accuracy varies across different approaches.

The subthalamic nucleus contributes causally to perceptual decision-making in monkeys

The subthalamic nucleus (STN) plays critical roles in the motor and cognitive function of the basal ganglia (BG), but the exact nature of these roles is not fully understood, especially in the context of decision-making based on uncertain evidence. Guided by theoretical predictions of specific STN contributions, we used single-unit recording and electrical microstimulation in the STN of healthy monkeys to assess its causal, computational roles in visual-saccadic decisions based on noisy evidence. The recordings identified subpopulations of STN neurons with distinct task-related activity patterns that related to different theoretically predicted functions. Microstimulation caused changes in behavioral choices and response times that reflected multiple contributions to an 'accumulate-to-bound'-like decision process, including modulation of decision bounds and evidence accumulation, and to non-perceptual processes. These results provide new insights into the multiple ways that the STN can support higher brain function.

Striatal indirect pathway mediates hesitation

Determining the best possible action in an uncertain situation is often challenging, and organisms frequently need extra time to deliberate. This pause in behavior in response to uncertainty - also known as hesitation - commonly occurs in many aspects of daily life, yet its neural circuits are poorly understood. Here we present the first experimental paradigm that reliably evokes hesitation in mice. Using cell-type specific electrophysiology and optogenetics, we show that indirect, but not direct, pathway spiny projection neurons specifically in the dorsomedial striatum mediate hesitation. These data indicate that the basal ganglia circuits controlling the pausing involved in cognitive processes like hesitation are distinct from those that control other types of behavioral inhibition, such as cue-induced stopping.

Concerning neuromodulation as treatment of neurological and neuropsychiatric disorder: Insights gained from selective targeting of the subthalamic nucleus, para-subthalamic nucleus and zona incerta in rodents

Neuromodulation such as deep brain stimulation (DBS) is advancing as a clinical intervention in several neurological and neuropsychiatric disorders, including Parkinson's disease, dystonia, tremor, and obsessive-compulsive disorder (OCD) for which DBS is already applied to alleviate severely afflicted individuals of symptoms. Tourette syndrome and drug addiction are two additional disorders for which DBS is in trial or proposed as treatment. However, some major remaining obstacles prevent this intervention from reaching its full therapeutic potential. Side-effects have been reported, and not all DBS-treated individuals are relieved of their symptoms. One major target area for DBS electrodes is the subthalamic nucleus (STN) which plays important roles in motor, affective and associative functions, with impact on for example movement, motivation, impulsivity, compulsivity, as well as both reward and aversion. The multifunctionality of the STN is complex. Decoding the anatomical-functional organization of the STN could enhance strategic targeting in human patients. The STN is located in close proximity to zona incerta (ZI) and the para-subthalamic nucleus (pSTN). Together, the STN, pSTN and ZI form a highly heterogeneous and clinically important brain area. Rodent-based experimental studies, including opto- and chemogenetics as well as viral-genetic tract tracings, provide unique insight into complex neuronal circuitries and their impact on behavior with high spatial and temporal precision. This research field has advanced tremendously over the past few years. Here, we provide an inclusive review of current literature in the pre-clinical research fields centered around STN, pSTN and ZI in laboratory mice and rats; the three highly heterogeneous and enigmatic structures brought together in the context of relevance for treatment strategies. Specific emphasis is placed on methods of manipulation and behavioral impact.

Neural indices of heritable impulsivity: Impact of the COMT Val158Met polymorphism on frontal beta power during early motor preparation

Studies of COMT Val158Met suggest that the neural circuitry subserving inhibitory control may be modulated by this functional polymorphism altering cortical dopamine availability, thus giving rise to heritable differences in behaviors. Using an anatomically-constrained magnetoencephalography method and stratifying the sample by COMT genotype, from a larger sample of 153 subjects, we examined the spatial and temporal dynamics of beta oscillations during motor execution and inhibition in 21 healthy Met158/Met158 (high dopamine) or 21 Val158/Val158 (low dopamine) genotype individuals during a Go/NoGo paradigm. While task performance was unaffected, Met158 homozygotes demonstrated an overall increase in beta power across regions essential for inhibitory control during early motor preparation (∼100 ms latency), suggestive of a global motor "pause" on behavior. This increase was especially evident on Go trials with slow response speed and was absent during inhibition failures. Such a pause could underlie the tendency of Met158 allele carriers to be more cautious and inhibited. In contrast, Val158 homozygotes exhibited a beta drop during early motor preparation, indicative of high response readiness. This decrease was associated with measures of behavioral disinhibition and consistent with greater extraversion and impulsivity observed in Val homozygotes. These results provide mechanistic insight into genetically-determined interindividual differences of inhibitory control with higher cortical dopamine associated with momentary response hesitation, and lower dopamine leading to motor impulsivity.

CBGTPy: An extensible cortico-basal ganglia-thalamic framework for modeling biological decision making

Here we introduce CBGTPy, a virtual environment for designing and testing goal-directed agents with internal dynamics that are modeled on the cortico-basal-ganglia-thalamic (CBGT) pathways in the mammalian brain. CBGTPy enables researchers to investigate the internal dynamics of the CBGT system during a variety of tasks, allowing for the formation of testable predictions about animal behavior and neural activity. The framework has been designed around the principle of flexibility, such that many experimental parameters in a decision making paradigm can be easily defined and modified. Here we demonstrate the capabilities of CBGTPy across a range of single and multi-choice tasks, highlighting the ease of set up and the biologically realistic behavior that it produces. We show that CBGTPy is extensible enough to apply to a range of experimental protocols and to allow for the implementation of model extensions with minimal developmental effort.

Freezing of gait in Parkinson's disease is related to imbalanced stopping-related cortical activity

Freezing of gait, characterized by involuntary interruptions of walking, is a debilitating motor symptom of Parkinson's disease that restricts people's autonomy. Previous brain imaging studies investigating the mechanisms underlying freezing were restricted to scan people in supine positions and yielded conflicting theories regarding the role of the supplementary motor area and other cortical regions. We used functional near-infrared spectroscopy to investigate cortical haemodynamics related to freezing in freely moving people. We measured functional near-infrared spectroscopy activity over multiple motor-related cortical areas in 23 persons with Parkinson's disease who experienced daily freezing ('freezers') and 22 age-matched controls during freezing-provoking tasks including turning and doorway passing, voluntary stops and actual freezing. Crucially, we corrected the measured signals for confounds of walking. We first compared cortical activity between freezers and controls during freezing-provoking tasks without freezing (i.e. turning and doorway passing) and during stops. Secondly, within the freezers, we compared cortical activity between freezing, stopping and freezing-provoking tasks without freezing. First, we show that turning and doorway passing (without freezing) resemble cortical activity during stopping in both groups involving activation of the supplementary motor area and prefrontal cortex, areas known for their role in inhibiting actions. During these freezing-provoking tasks, the freezers displayed higher activity in the premotor areas than controls. Secondly, we show that, during actual freezing events, activity in the prefrontal cortex was lower than during voluntary stopping. The cortical relation between the freezing-provoking tasks (turning and doorway passing) and stopping may explain their susceptibility to trigger freezing by activating a stopping mechanism. Besides, the stopping-related activity of the supplementary motor area and prefrontal cortex seems to be out of balance in freezers. In this paper, we postulate that freezing results from a paroxysmal imbalance between the supplementary motor area and prefrontal cortex, thereby extending upon the current role of the supplementary motor area in freezing pathophysiology.

Pupil dilation reflects effortful action invigoration in overcoming aversive Pavlovian biases

"Pavlovian" or "motivational" biases describe the phenomenon that the valence of prospective outcomes modulates action invigoration: Reward prospect invigorates action, whereas punishment prospect suppresses it. The adaptive role of these biases in decision-making is still unclear. One idea is that they constitute a fast-and-frugal decision strategy in situations characterized by high arousal, e.g., in presence of a predator, which demand a quick response. In this pre-registered study (N = 35), we tested whether such a situation-induced via subliminally presented angry versus neutral faces-leads to increased reliance on Pavlovian biases. We measured trial-by-trial arousal by tracking pupil diameter while participants performed an orthogonalized Motivational Go/NoGo Task. Pavlovian biases were present in responses, reaction times, and even gaze, with lower gaze dispersion under aversive cues reflecting "freezing of gaze." The subliminally presented faces did not affect responses, reaction times, or pupil diameter, suggesting that the arousal manipulation was ineffective. However, pupil dilations reflected facets of bias suppression, specifically the physical (but not cognitive) effort needed to overcome aversive inhibition: Particularly strong and sustained dilations occurred when participants managed to perform Go responses to aversive cues. Conversely, no such dilations occurred when they managed to inhibit responses to Win cues. These results suggest that pupil diameter does not reflect response conflict per se nor the inhibition of prepotent responses, but specifically effortful action invigoration as needed to overcome aversive inhibition. We discuss our results in the context of the "value of work" theory of striatal dopamine.

The subthalamic nucleus contributes causally to perceptual decision-making in monkeys

The subthalamic nucleus (STN) plays critical roles in the motor and cognitive function of the basal ganglia (BG), but the exact nature of these roles is not fully understood, especially in the context of decision-making based on uncertain evidence. Guided by theoretical predictions of specific STN contributions, we used single-unit recording and electrical microstimulation in the STN of healthy monkeys to assess its causal, computational roles in visual-saccadic decisions based on noisy evidence. The recordings identified subpopulations of STN neurons with distinct task-related activity patterns that related to different theoretically predicted functions. Microstimulation caused changes in behavioral choices and response times that reflected multiple contributions to an "accumulate-to-bound"-like decision process, including modulation of decision bounds and evidence accumulation, and to non-perceptual processes. These results provide new insights into the multiple ways that the STN can support higher brain function.

Unraveling the enigmatic role of the subthalamic nucleus

Subpopulations of neurons in the subthalamic nucleus have distinct activity patterns that relate to the three hypotheses of the Drift Diffusion Model.

Early Rise and Persistent Inhibition of Electromyography during Failed Stopping

Reactively canceling movements is a vital feature of the motor system to ensure safety. This behavior can be studied in the laboratory using the stop-signal task. There remains ambiguity about whether a "point-of-no-return" exists, after which a response cannot be aborted. A separate question concerns whether motor system inhibition associated with attempted stopping persists when stopping is unsuccessful. We address these two questions using electromyography (EMG) in two stop-signal task experiments. Experiment 1 (n = 24) involved simple right and left index finger responses in separate task blocks. Experiment 2 (n = 28) involved a response choice between the right index and pinky fingers. To evaluate the approximate point of no return, we measured EMG in responding fingers during the 100 msec preceding the stop signal and observed significantly greater EMG amplitudes during failed than successful stopping in both experiments. Thus, EMG before the stop signal differentiated success, regardless of whether there was a response choice. To address whether motor inhibition persists after failed stopping, we assessed EMG peak-to-offset durations and slopes (i.e., rate of EMG decline) for go, failed stop, and successful stop (partial response) trials. EMG peak-to-offset was shorter and steeper for failed stopping compared to go and successful stop partial response trials, suggesting motor inhibition persists even when failing to stop. These findings indicate EMG is sensitive to a "transition zone" at which the relative likelihood of stop failure versus success inverts and also suggest peak-to-offset time of response-related EMG activity during failed stopping reflects stopping-related inhibition.

Prefrontal-subthalamic theta signaling mediates delayed responses during conflict processing

While medial frontal cortex (MFC) and subthalamic nucleus (STN) have been implicated in conflict monitoring and action inhibition, respectively, an integrated understanding of the spatiotemporal and spectral interaction of these nodes and how they interact with motor cortex (M1) to definitively modify motor behavior during conflict is lacking. We recorded neural signals intracranially across presupplementary motor area (preSMA), M1, STN, and globus pallidus internus (GPi), during a flanker task in 20 patients undergoing deep brain stimulation implantation surgery for Parkinson disease or dystonia. Conflict is associated with sequential and causal increases in local theta power from preSMA to STN to M1 with movement delays directly correlated with increased STN theta power, indicating preSMA is the MFC locus that monitors conflict and signals STN to implement a 'break.' Transmission of theta from STN-to-M1 subsequently results in a transient increase in M1-to-GPi beta flow immediately prior to movement, modulating the motor network to actuate the conflict-related action inhibition (i.e., delayed response). Action regulation during conflict relies on two distinct circuits, the conflict-related theta and movement-related beta networks, that are separated spatially, spectrally, and temporally, but which interact dynamically to mediate motor performance, highlighting complex parallel yet interacting networks regulating movement.

Reduced sleep quality defines a subtype of obsessive-compulsive disorder with lower Glx levels in the resting thalamus and worse response inhibition

BACKGROUND

The aim of this study was to investigate the differences between resting and active thalamic neurometabolite levels and inhibitory function in obsessive compulsive disorder (OCD) patients with poor sleep quality (PSQ was defined as Pittsburgh Sleep Quality Index >5 and sleep efficiency ≤85%) compared to OCD patients with good sleep quality (GSQ) and healthy controls (HCs), as well as the relationship of these indices to obsessive compulsive symptoms.

METHODS

Functional magnetic resonance spectroscopy (fMRS) was used to measure resting and active thalamic neurometabolite levels in 72 subjects (20 HCs and 38 OCD patients included in study analysis). Response inhibition function was measured by the Go-Nogo task before and during MRS recording. Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The symptoms of OCD, anxiety and depression were evaluated using relevant clinical scales.

RESULTS

OCD patients exhibited significantly reduced Glx/Cr levels in the resting thalamus. The levels of resting thalamic Glu/Cr and Glx/Cr in OCD patients with PSQ were significantly lowest. OCD patients had significantly lower correct rates on Go tasks, higher error rates on Nogo tasks, and longer error average response times (EART) to the Nogo task. OCD patients with PSQ demonstrated the highest Nogo task error rate and the longest EART to Nogo task. Furthermore, PSQI scores exhibited negative correlations with Glu/Cr and Glx/Cr in the resting thalamus.

CONCLUSION

OCD patients with PSQ demonstrated reduced levels of thalamic resting Glx and more pronounced response inhibitory function impairment. Aberrant neurometabolite levels in critical brain regions, coupled with heightened response inhibition function deficits, may be a neurobiological basis for the PSQ that OCD patients generally exhibit.

Adaptation of sequential action benefits from timing variability related to lateral basal ganglia circuitry

Streamlined action sequences must remain flexible should stable contingencies in the environment change. By combining analyses of behavioral structure with a circuit-specific manipulation in mice, we report on a relationship between action timing variability and successful adaptation that relates to post-synaptic targets of primary motor cortical (M1) projections to dorsolateral striatum (DLS). In a two-lever instrumental task, mice formed successful action sequences by, first, establishing action scaffolds and, second, smoothly extending action duration to adapt to increased task requirements. Interruption of DLS neurons in M1 projection territories altered this process, evoking higher-rate actions that were more stereotyped in their timing, reducing opportunities for success. Based on evidence from neuronal tracing experiments, we propose that DLS neurons in M1 projection territories supply action timing variability to facilitate adaptation, a function that may involve additional downstream subcortical processing relating to collateralization of descending motor pathways to multiple basal ganglia centers.

Corticospinal excitability reductions during action preparation and action stopping in humans: Different sides of the same inhibitory coin?

Motor functions and cognitive processes are closely associated with each other. In humans, this linkage is reflected in motor system state changes both when an action must be prepared and stopped. Single-pulse transcranial magnetic stimulation showed that both action preparation and action stopping are accompanied by a reduction of corticospinal excitability, referred to as preparatory and response inhibition, respectively. While previous efforts have been made to describe both phenomena extensively, an updated and comprehensive comparison of the two phenomena is lacking. To ameliorate such deficit, this review focuses on the role and interpretation of single-coil (single-pulse and paired-pulse) and dual-coil TMS outcome measures during action preparation and action stopping in humans. To that effect, it aims to identify commonalities and differences, detailing how TMS-based outcome measures are affected by states, traits, and psychopathologies in both processes. Eventually, findings will be compared, and open questions will be addressed to aid future research.

Double dissociation of dopamine and subthalamic nucleus stimulation on effortful cost/benefit decision making

Deep brain stimulation (DBS) and dopaminergic therapy (DA) are common interventions for Parkinson's disease (PD). Both treatments typically improve patient outcomes, and both can have adverse side effects on decision making (e.g., impulsivity).1,2 Nevertheless, they are thought to act via different mechanisms within basal ganglia circuits.3 Here, we developed and formally evaluated their dissociable predictions within a single cost/benefit effort-based decision-making task. In the same patients, we manipulated DA medication status and subthalamic nucleus (STN) DBS status within and across sessions. Using a series of descriptive and computational modeling analyses of participant choices and their dynamics, we confirm a double dissociation: DA medication asymmetrically altered participants' sensitivities to benefits vs. effort costs of alternative choices (boosting the sensitivity to benefits while simultaneously lowering sensitivity to costs); whereas STN DBS lowered the decision threshold of such choices. To our knowledge, this is the first study to show, using a common modeling framework, a dissociation of DA and DBS within the same participants. As such, this work offers a comprehensive account for how different mechanisms impact decision making, and how impulsive behavior (present in DA-treated patients with PD and DBS patients) may emerge from separate physiological mechanisms.

The onset of motor learning impairments in Parkinson's disease: a computational investigation

The basal ganglia (BG) is part of a basic feedback circuit regulating cortical function, such as voluntary movements control, via their influence on thalamocortical projections. BG disorders, namely Parkinson's disease (PD), characterized by the loss of neurons in the substantia nigra, involve the progressive loss of motor functions. At the present, PD is incurable. Converging evidences suggest the onset of PD-specific pathology prior to the appearance of classical motor signs. This latent phase of neurodegeneration in PD is of particular relevance in developing more effective therapies by intervening at the earliest stages of the disease. Therefore, a key challenge in PD research is to identify and validate markers for the preclinical and prodromal stages of the illness. We propose a mechanistic neurocomputational model of the BG at a mesoscopic scale to investigate the behavior of the simulated neural system after several degrees of lesion of the substantia nigra, with the aim of possibly evaluating which is the smallest lesion compromising motor learning. In other words, we developed a working framework for the analysis of theoretical early-stage PD. While simulations in healthy conditions confirm the key role of dopamine in learning, in pathological conditions the network predicts that there may exist abnormalities of the motor learning process, for physiological alterations in the BG, that do not yet involve the presence of symptoms typical of the clinical diagnosis.

Distinct Inhibitory-Control Processes Underlie Children's Judgments of Fairness

We examined how 5- to 8-year-olds (N = 51; Mage = 83 months; 27 female, 24 male; 69% White, 12% Black/African American, 8% Asian/Asian American, 6% Hispanic, 6% not reported) and adults (N = 18; Mage = 20.13 years; 11 female, 7 male) accepted or rejected different distributions of resources between themselves and others. We used a reach-tracking method to track finger movement in 3D space over time. This allowed us to dissociate two inhibitory processes. One involved pausing motor responses to detect conflict between observed information and how participants thought resources should be divided; the other involved resolving the conflict between the response and the alternative. Reasoning about disadvantageous inequities involved more of the first system, and this was stable across development. Reasoning about advantageous inequities involved more of the second system and showed more of a developmental progression. Generally, reach tracking offers an on-line measure of inhibitory control for the study of cognition.

Neural mechanisms for executive control of speed-accuracy trade-off

The medial frontal cortex (MFC) plays an important but disputed role in speed-accuracy trade-off (SAT). In samples of neural spiking in the supplementary eye field (SEF) in the MFC simultaneous with the visuomotor frontal eye field and superior colliculus in macaques performing a visual search with instructed SAT, during accuracy emphasis, most SEF neurons discharge less from before stimulus presentation until response generation. Discharge rates adjust immediately and simultaneously across structures upon SAT cue changes. SEF neurons signal choice errors with stronger and earlier activity during accuracy emphasis. Other neurons signal timing errors, covarying with adjusting response time. Spike correlations between neurons in the SEF and visuomotor areas did not appear, disappear, or change sign across SAT conditions or trial outcomes. These results clarify findings with noninvasive measures, complement previous neurophysiological findings, and endorse the role of the MFC as a critic for the actor instantiated in visuomotor structures.

Connecting the dots: harnessing dual-site transcranial magnetic stimulation to quantify the causal influence of medial frontal areas on the motor cortex

Dual-site transcranial magnetic stimulation has been widely employed to investigate the influence of cortical structures on the primary motor cortex. Here, we leveraged this technique to probe the causal influence of two key areas of the medial frontal cortex, namely the supplementary motor area and the medial orbitofrontal cortex, on primary motor cortex. We show that supplementary motor area stimulation facilitates primary motor cortex activity across short (6 and 8 ms) and long (12 ms) inter-stimulation intervals, putatively recruiting cortico-cortical and cortico-subcortico-cortical circuits, respectively. Crucially, magnetic resonance imaging revealed that this facilitatory effect depended on a key morphometric feature of supplementary motor area: individuals with larger supplementary motor area volumes exhibited more facilitation from supplementary motor area to primary motor cortex for both short and long inter-stimulation intervals. Notably, we also provide evidence that the facilitatory effect of supplementary motor area stimulation at short intervals is unlikely to arise from spinal interactions of volleys descending simultaneously from supplementary motor area and primary motor cortex. On the other hand, medial orbitofrontal cortex stimulation moderately suppressed primary motor cortex activity at both short and long intervals, irrespective of medial orbitofrontal cortex volume. These results suggest that dual-site transcranial magnetic stimulation is a fruitful approach to investigate the differential influence of supplementary motor area and medial orbitofrontal cortex on primary motor cortex activity, paving the way for the multimodal assessment of these fronto-motor circuits in health and disease.

Aberrations in temporal dynamics of cognitive processing induced by Parkinson's disease and Levodopa

The motor symptoms of Parkinson's disease (PD) have been shown to significantly improve by Levodopa. However, despite the widespread adoption of Levodopa as a standard pharmaceutical drug for the treatment of PD, cognitive impairments linked to PD do not show visible improvement with Levodopa treatment. Furthermore, the neuronal and network mechanisms behind the PD-induced cognitive impairments are not clearly understood. In this work, we aim to explain these cognitive impairments, as well as the ones exacerbated by Levodopa, through examining the differential dynamic patterns of the phase-amplitude coupling (PAC) during cognitive functions. EEG data recorded in an auditory oddball task performed by a cohort consisting of controls and a group of PD patients during both on and off periods of Levodopa treatment were analyzed to derive the temporal dynamics of the PAC across the brain. We observed distinguishing patterns in the PAC dynamics, as an indicator of information binding, which can explain the slower cognitive processing associated with PD in the form of a latency in the PAC peak time. Thus, considering the high-level connections between the hippocampus, the posterior and prefrontal cortices established through the dorsal and ventral striatum acting as a modulatory system, we posit that the primary issue with cognitive impairments of PD, as well as Levodopa's cognitive deficit side effects, can be attributed to the changes in temporal dynamics of dopamine release influencing the modulatory function of the striatum.

Cortical and subcortical contributions to non-motor inhibitory control: an fMRI study

Inhibition is a core executive cognitive function. However, the neural correlates of non-motor inhibitory control are not well understood. We investigated this question using functional Magnetic Resonance Imaging (fMRI) and a simple Count Go/NoGo task (n = 23), and further explored the causal relationships between activated brain regions. We found that the Count NoGo task activated a distinct pattern in the subcortical basal ganglia, including bilateral ventral anterior/lateral nucleus of thalamus (VA/VL), globus pallidus/putamen (GP/putamen), and subthalamic nucleus (STN). Stepwise regressions and mediation analyses revealed that activations in these region(s) were modulated differently by only 3 cortical regions i.e. the right inferior frontal gyrus/insula (rIFG/insula), along with left IFG/insula, and anterior cingulate cortex/supplementary motor area (ACC/SMA). The activations of bilateral VA/VL were modulated by both rSTN and rIFG/insula (with rGP/putamen as a mediator) independently, and the activation of rGP/putamen was modulated by ACC/SMA, with rIFG/insula as a mediator. Our findings provide the neural correlates of inhibitory control of counting and causal relationships between them, and strongly suggest that both indirect and hyperdirect pathways of the basal ganglia are involved in the Count NoGo condition.

Inferring cognitive state underlying conflict choices in verbal Stroop task using heterogeneous input discriminative-generative decoder model

Objective. The subthalamic nucleus (STN) of the basal ganglia interacts with the medial prefrontal cortex (mPFC) and shapes a control loop, specifically when the brain receives contradictory information from either different sensory systems or conflicting information from sensory inputs and prior knowledge that developed in the brain. Experimental studies demonstrated that significant increases in theta activities (2-8 Hz) in both the STN and mPFC as well as increased phase synchronization between mPFC and STN are prominent features of conflict processing. While these neural features reflect the importance of STN-mPFC circuitry in conflict processing, a low-dimensional representation of the mPFC-STN interaction referred to as a cognitive state, that links neural activities generated by these sub-regions to behavioral signals (e.g. the response time), remains to be identified.Approach. Here, we propose a new model, namely, the heterogeneous input discriminative-generative decoder (HI-DGD) model, to infer a cognitive state underlying decision-making based on neural activities (STN and mPFC) and behavioral signals (individuals' response time) recorded in ten Parkinson's disease (PD) patients while they performed a Stroop task. PD patients may have conflict processing which is quantitatively (may be qualitative in some) different from healthy populations.Main results. Using extensive synthetic and experimental data, we showed that the HI-DGD model can diffuse information from neural and behavioral data simultaneously and estimate cognitive states underlying conflict and non-conflict trials significantly better than traditional methods. Additionally, the HI-DGD model identified which neural features made significant contributions to conflict and non-conflict choices. Interestingly, the estimated features match well with those reported in experimental studies.Significance. Finally, we highlight the capability of the HI-DGD model in estimating a cognitive state from a single trial of observation, which makes it appropriate to be utilized in closed-loop neuromodulation systems.

Measuring utility with diffusion models

The drift diffusion model (DDM) is a prominent account of how people make decisions. Many of these decisions involve comparing two alternatives based on differences of perceived stimulus magnitudes, such as economic values. Here, we propose a consistent estimator for the parameters of a DDM in such cases. This estimator allows us to derive decision thresholds, drift rates, and subjective percepts (i.e., utilities in economic choice) directly from the experimental data. This eliminates the need to measure these values separately or to assume specific functional forms for them. Our method also allows one to predict drift rates for comparisons that did not occur in the dataset. We apply the method to two datasets, one comparing probabilities of earning a fixed reward and one comparing objects of variable reward value. Our analysis indicates that both datasets conform well to the DDM. We find that utilities are linear in probability and slightly convex in reward.

Apathy in Parkinson's Disease: Clinical Patterns and Neurobiological Basis

Apathy is commonly defined as a loss of motivation leading to a reduction in goal-directed behaviors. This multidimensional syndrome, which includes cognitive, emotional and behavioral components, is one of the most prevalent neuropsychiatric features of Parkinson's disease (PD). It has been established that the prevalence of apathy increases as PD progresses. However, the pathophysiology and anatomic substrate of this syndrome remain unclear. Apathy seems to be underpinned by impaired anatomical structures that link the prefrontal cortex with the limbic system. It can be encountered in the prodromal stage of the disease and in fluctuating PD patients receiving bilateral chronic subthalamic nucleus stimulation. In these stages, apathy may be considered as a disorder of motivation that embodies amotivational behavioral syndrome, is underpinned by combined dopaminergic and serotonergic denervation and is dopa-responsive. In contrast, in advanced PD patients, apathy may be considered as cognitive apathy that announces cognitive decline and PD dementia, is underpinned by diffuse neurotransmitter system dysfunction and Lewy pathology spreading and is no longer dopa-responsive. In this review, we discuss the clinical patterns of apathy and their treatment, the neurobiological basis of apathy, the potential role of the anatomical structures involved and the pathways in motivational and cognitive apathy.

Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.

Neural dynamics underlying self-control in the primate subthalamic nucleus

The subthalamic nucleus (STN) is hypothesized to play a central role in neural processes that regulate self-control. Still uncertain, however, is how that brain structure participates in the dynamically evolving estimation of value that underlies the ability to delay gratification and wait patiently for a gain. To address that gap in knowledge, we studied the spiking activity of neurons in the STN of monkeys during a task in which animals were required to remain motionless for varying periods of time in order to obtain food reward. At the single-neuron and population levels, we found a cost-benefit integration between the desirability of the expected reward and the imposed delay to reward delivery, with STN signals that dynamically combined both attributes of the reward to form a single integrated estimate of value. This neural encoding of subjective value evolved dynamically across the waiting period that intervened after instruction cue. Moreover, this encoding was distributed inhomogeneously along the antero-posterior axis of the STN such that the most dorso-posterior-placed neurons represented the temporal discounted value most strongly. These findings highlight the selective involvement of the dorso-posterior STN in the representation of temporally discounted rewards. The combination of rewards and time delays into an integrated representation is essential for self-control, the promotion of goal pursuit, and the willingness to bear the costs of time delays.

Exploration behavior after reversals is predicted by STN-GPe synaptic plasticity in a basal ganglia model

Humans can quickly adapt their behavior to changes in the environment. Classical reversal learning tasks mainly measure how well participants can disengage from a previously successful behavior but not how alternative responses are explored. Here, we propose a novel 5-choice reversal learning task with alternating position-reward contingencies to study exploration behavior after a reversal. We compare human exploratory saccade behavior with a prediction obtained from a neuro-computational model of the basal ganglia. A new synaptic plasticity rule for learning the connectivity between the subthalamic nucleus (STN) and external globus pallidus (GPe) results in exploration biases to previously rewarded positions. The model simulations and human data both show that during experimental experience exploration becomes limited to only those positions that have been rewarded in the past. Our study demonstrates how quite complex behavior may result from a simple sub-circuit within the basal ganglia pathways.

Error-related signaling in nucleus accumbens D2 receptor-expressing neurons guides inhibition-based choice behavior in mice

Learned associations between environmental cues and the outcomes they predict (cue-outcome associations) play a major role in behavioral control, guiding not only which responses we should perform, but also which we should inhibit, in order to achieve a specific goal. The encoding of such cue-outcome associations, as well as the performance of cue-guided choice behavior, is thought to involve dopamine D1 and D2 receptor-expressing medium spiny neurons (D1-/D2-MSNs) of the nucleus accumbens (NAc). Here, using a visual discrimination task in male mice, we assessed the role of NAc D1-/D2-MSNs in cue-guided inhibition of inappropriate responding. Cell-type specific neuronal silencing and in-vivo imaging revealed NAc D2-MSNs to contribute to inhibiting behavioral responses, with activation of NAc D2-MSNs following response errors playing an important role in optimizing future choice behavior. Our findings indicate that error-signaling by NAc D2-MSNs contributes to the ability to use environmental cues to inhibit inappropriate behavior.

The contribution of the basal ganglia and cerebellum to motor learning: A neuro-computational approach

Motor learning involves a widespread brain network including the basal ganglia, cerebellum, motor cortex, and brainstem. Despite its importance, little is known about how this network learns motor tasks and which role different parts of this network take. We designed a systems-level computational model of motor learning, including a cortex-basal ganglia motor loop and the cerebellum that both determine the response of central pattern generators in the brainstem. First, we demonstrate its ability to learn arm movements toward different motor goals. Second, we test the model in a motor adaptation task with cognitive control, where the model replicates human data. We conclude that the cortex-basal ganglia loop learns via a novelty-based motor prediction error to determine concrete actions given a desired outcome, and that the cerebellum minimizes the remaining aiming error.

Chaotic dynamics of the Hénon map and neuronal input-output: A comparison with neurophysiological data

In this study, the Hénon map was analyzed using quantifiers from information theory in order to compare its dynamics to experimental data from brain regions known to exhibit chaotic behavior. The goal was to investigate the potential of the Hénon map as a model for replicating chaotic brain dynamics in the treatment of Parkinson's and epilepsy patients. The dynamic properties of the Hénon map were compared with data from the subthalamic nucleus, the medial frontal cortex, and a q-DG model of neuronal input-output with easy numerical implementation to simulate the local behavior of a population. Using information theory tools, Shannon entropy, statistical complexity, and Fisher's information were analyzed, taking into account the causality of the time series. For this purpose, different windows over the time series were considered. The findings revealed that neither the Hénon map nor the q-DG model could perfectly replicate the dynamics of the brain regions studied. However, with careful consideration of the parameters, scales, and sampling used, they were able to model some characteristics of neural activity. According to these results, normal neural dynamics in the subthalamic nucleus region may present a more complex spectrum within the complexity-entropy causality plane that cannot be represented by chaotic models alone. The dynamic behavior observed in these systems using these tools is highly dependent on the studied temporal scale. As the size of the sample studied increases, the dynamics of the Hénon map become increasingly different from those of biological and artificial neural systems.

Electrophysiological Correlates of Different Proactive Controls during Response Competition and Inhibition Tasks

The present study aims to investigate the behavioral outcomes and the antecedent brain dynamics during the preparation of tasks in which the discrimination is either about the choice (choice response task; CRT) or the action (Go/No-go), and in a task not requiring discrimination (simple response task; SRT). Using event-related potentials (ERPs), the mean amplitude over prefrontal, central, and parietal-occipital sites was analyzed in 20 young healthy participants in a time frame before stimulus presentation to assess cognitive, motor, and visual readiness, respectively. Behaviorally, participants were faster and more accurate in the SRT than in the CRT and the Go/No-go. At the electrophysiological level, the proactive cognitive and motor ERP components were larger in the CRT and the Go/No-go than the SRT, but the largest amplitude emerged in the Go/No-go. Further, the amplitude over parieto-occipital leads was enhanced in the SRT. The strongest intensity of the frontal negative expectancy wave over prefrontal leads in the Go/No-go task could be attributed to the largest uncertainty about the target presentation and subsequent motor response selection and execution. The enhanced sensory readiness in the SRT can be related to either an increased visual readiness associated with task requirements or a reduced overlap with proactive processing on the scalp.

Evolving characterization of the human hyperdirect pathway

The hyperdirect pathway (HDP) represents the main glutamatergic input to the subthalamic nucleus (STN), through which the motor and prefrontal cerebral cortex can modulate basal ganglia activity. Further, direct activation of the motor HDP is thought to be an important component of therapeutic deep brain stimulation (DBS), mediating the disruption of pathological oscillations. Alternatively, unintended recruitment of the prefrontal HDP may partly explain some cognitive side effects of DBS therapy. Previous work describing the HDP has focused on non-human primate (NHP) histological pathway tracings, diffusion-weighted MRI analysis of human white matter, and electrophysiology studies involving paired cortical recordings with DBS. However, none of these approaches alone yields a complete understanding of the complexities of the HDP. As such, we propose that generative modeling methods hold promise to bridge anatomy and physiology results, from both NHPs and humans, into a more detailed representation of the human HDP. Nonetheless, numerous features of the HDP remain to be experimentally described before model-based methods can simulate corticosubthalamic activity with a high degree of scientific detail. Therefore, the goals of this review are to examine the experimental evidence for HDP projections from across the primate neocortex and discuss new data which are required to improve the utility of anatomical and biophysical models of the human corticosubthalamic system.

Subthalamic oscillatory activity during normal and impaired speech

OBJECTIVE

We studied the relationship between oscillatory activity in the subthalamic nucleus (STN) and speech production in order to better understand the functional role of the STN.

METHODS

We simultaneously recorded subthalamic local field potentials and audio recordings from 5 patients with Parkinson's disease while they performed verbal fluency tasks. We then analyzed the oscillatory signals present in the subthalamic nucleus during these tasks.

RESULTS

We report that normal speech leads to a suppression of subthalamic alpha and beta power. Contrarily, a patient with motor blocks during speech initiation showed a low beta power increase. We also report an increase in error rates in the phonemic non-alternating verbal fluency task during deep brain stimulation (DBS).

CONCLUSIONS

We confirm previous findings that intact speech leads to desynchronization in the beta range in the STN. The speech related narrowband beta power increase in a patient with speech problems suggests that exaggerated synchronization in this frequency band is associated with motor blocks during speech initiation. The increased number of errors in verbal fluency tasks during DBS might be caused by an impairment of the response inhibition network caused by stimulation of the STN.

SIGNIFICANCE

We suggest that the inability to attenuate beta activity during motor processes is associated with motor freezing across motor behaviours such as speech and gait, as previously shown for freezing of gait.

Basal ganglia network dynamics and function: Role of direct, indirect and hyper-direct pathways in action selection

Basal ganglia (BG) are a widely recognized neural basis for action selection, but its decision-making mechanism is still a difficult problem for researchers. Therefore, we constructed a spiking neural network inspired by the BG anatomical data. Simulation experiments were based on the principle of dis-inhibition and our functional hypothesis within the BG: the direct pathway, the indirect pathway, and the hyper-direct pathway of the BG jointly implement the initiation execution and termination of motor programs. Firstly, we studied the dynamic process of action selection with the network, which contained intra-group competition and inter-group competition. Secondly, we focused on the effects of the stimulus intensity and the proportion of excitation and inhibition on the GPi/SNr. The results suggested that inhibition and excitation shape action selection. They also explained why the firing rate of GPi/SNr did not continue to increase in the action-selection experiment. Finally, we discussed the experimental results with the functional hypothesis. Uniquely, this paper summarized the decision-making neural mechanism of action selection based on the direct pathway, the indirect pathway, and the hyper-direct pathway within BG.

No effect of subthalamic deep brain stimulation on metacognition in Parkinson's disease

Deep brain stimulation of the subthalamic nucleus (STN-DBS) is a powerful treatment in Parkinson's disease (PD), which provides a positive effect on motor symptoms although the way it operates on high cognitive processes such as metacognition remains unclear. To address this issue, we recorded electroencephalogram (EEG) of PD patients treated with STN-DBS that performed a reversal learning (RL) paradigm endowed with metacognitive self-assessment. We considered two stimulation conditions, namely DBS-ON (stimulation on) and DBS-OFF (stimulation off), and focused our EEG-analysis on the frontal brain region due to its involvement on high cognitive processes. We found a trend towards a significant difference in RL ability between stimulation conditions. STN-DBS showed no effect on metacognition, although a significant association between accuracy and decision confidence level held for DBS OFF, but not in the case of DBS ON. In summary, our study revealed no significant effect of STN-DBS on RL or metacognition.

Computational analysis of speed-accuracy tradeoff

Speed-accuracy tradeoff (SAT) in the decision making of humans and animals is a well-documented phenomenon, but its underlying neuronal mechanism remains unclear. Modeling approaches have conceptualized SAT through the threshold hypothesis as adjustments to the decision threshold. However, the leading neurophysiological view is the gain modulation hypothesis. This hypothesis postulates that the SAT mechanism is implemented through changes in the dynamics of the choice circuit, which increase the baseline firing rate and the speed of neuronal integration. In this paper, I investigated alternative computational mechanisms of SAT and showed that the threshold hypothesis was qualitatively consistent with the behavioral data, but the gain modulation hypothesis was not. In order to reconcile the threshold hypothesis with the neurophysiological evidence, I considered the interference of alpha oscillations with the decision process and showed that alpha oscillations could increase the discriminatory power of the decision system, although they slowed down the decision process. This suggests that the magnitude of alpha waves suppression during the event related desynchronization (ERD) of alpha oscillations depends on a SAT condition and the amplitude of alpha oscillations is lower in the speed condition. I also showed that the lower amplitude of alpha oscillations resulted in an increase in the baseline firing rate and the speed of neuronal intergration. Thus, the interference of the event related desynchronization of alpha oscillations with a SAT condition explains why an increase in the baseline firing rate and the speed of neuronal integration accompany the speed condition.