Neurocomputational models of motor and cognitive deficits in Parkinson's disease

Mechanisms underlying corruption of working memory in Parkinson's disease

Working memory (WM) impairments are reported to occur in patients with Parkinson's disease (PD). However, the mechanisms are unclear. Here, we investigate several putative factors that might drive poor performance, by examining the precision of recall, the order in which items are recalled and whether memories are corrupted by random guessing (attentional lapses). We used two separate tasks that examined the quality of WM recall under different loads and retention periods, as well as a traditional digit span test. Firstly, on a simple measure of WM recall, where patients were asked to reproduce the orientation of a centrally presented arrow, overall recall was not significantly impaired. However, there was some evidence for increased guessing (attentional lapses). On a new analogue version of the Corsi-span task, where participants had to reproduce on a touchscreen the exact spatial pattern of presented stimuli in the order and locations in which they appeared, there was a reduction in the precision of spatial WM at higher loads. This deficit was due to misremembering item order. At the highest load, there was reduced recall precision, whereas increased guessing was only observed at intermediate set sizes. Finally, PD patients had impaired backward, but not forward, digit spans. Overall, these results reveal the task- and load-dependent nature of WM deficits in PD. On simple low-load tasks, attentional lapses predominate, whereas at higher loads, in the spatial domain, the corruption of mnemonic information-both order item and precision-emerge as the main driver of impairment.

Animal models of action control and cognitive dysfunction in Parkinson's disease

Parkinson's disease (PD) has historically been considered a motor disorder induced by a loss of dopaminergic neurons in the substantia nigra pars compacta. More recently, it has been recognized to have significant non-motor symptoms, most prominently cognitive symptoms associated with a dysexecutive syndrome. It is common in the literature to see motor and cognitive symptoms treated separately and, indeed, there has been a general call for specialized treatment of the latter, particularly in the more severe cases of PD with mild cognitive impairment and dementia. Animal studies have similarly been developed to model the motor or non-motor symptoms. Nevertheless, considerable research has established that segregating consideration of cognition from the precursors to motor movement, particularly movement associated with goal-directed action, is difficult if not impossible. Indeed, on some contemporary views cognition is embodied in action control, something that is particularly prevalent in theory and evidence relating to the integration of goal-directed and habitual control processes. The current paper addresses these issues within the literature detailing animal models of cognitive dysfunction in PD and their neural and neurochemical bases. Generally, studies using animal models of PD provide some of the clearest evidence for the integration of these action control processes at multiple levels of analysis and imply that consideration of this integrative process may have significant benefits for developing new approaches to the treatment of PD.

Cognitive control in Parkinson's disease

Cognitive control is the ability to act according to plan. Problems with cognitive control are a primary symptom and a major decrement of quality of life in Parkinson's disease (PD). Individuals with PD have problems with seemingly different controlled processes (e.g., task switching, impulsivity, gait disturbance, apathetic motivation). We review how these varied processes all rely upon disease-related alteration of common neural substrates, particularly due to dopaminergic imbalance. A comprehensive understanding of the neural systems underlying cognitive control will hopefully lead to more concise and reliable explanations of distributed deficits. However, high levels of clinical heterogeneity and medication-invariant control deficiencies suggest the need for increasingly detailed elaboration of the neural systems underlying control in PD.

The Supplementary Motor Complex in Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by both motor and nonmotor symptoms. Although the basal ganglia is traditionally the primary brain region implicated in this disease process, this limited view ignores the roles of the cortex and cerebellum that are networked with the basal ganglia to support motor and cognitive functions. In particular, recent research has highlighted dysfunction in the supplementary motor complex (SMC) in patients with PD. Using the PubMed and Google Scholar search engines, we identified research articles using keywords pertaining to the involvement of the SMC in action sequencing impairments, temporal processing disturbances, and gait impairment in patients with PD. A review of abstracts and full-text articles was used to identify relevant articles. In this review of 63 articles, we focus on the role of the SMC in PD, highlighting anatomical and functional data to create new perspectives in understanding clinical symptoms and, potentially, new therapeutic targets. The SMC has a nuanced role in the pathophysiology of PD, with both hypo- and hyperactivation associated with various symptoms. Further studies using more standardized patient populations and functional tasks are needed to more clearly elucidate the role of this region in the pathophysiology and treatment of PD.

Computational Psychiatry Needs Time and Context

Why has computational psychiatry yet to influence routine clinical practice? One reason may be that it has neglected context and temporal dynamics in the models of certain mental health problems. We develop three heuristics for estimating whether time and context are important to a mental health problem: Is it characterized by a core neurobiological mechanism? Does it follow a straightforward natural trajectory? And is intentional mental content peripheral to the problem? For many problems the answers are no, suggesting that modeling time and context is critical. We review computational psychiatry advances toward this end, including modeling state variation, using domain-specific stimuli, and interpreting differences in context. We discuss complementary network and complex systems approaches. Novel methods and unification with adjacent fields may inspire a new generation of computational psychiatry. Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Analogous computations in working memory input, output and motor gating: Electrophysiological and computational modeling evidence

Adaptive cognitive-control involves a hierarchical cortico-striatal gating system that supports selective updating, maintenance, and retrieval of useful cognitive and motor information. Here, we developed a task that independently manipulates selective gating operations into working-memory (input gating), from working-memory (output gating), and of responses (motor gating) and tested the neural dynamics and computational principles that support them. Increases in gating demands, captured by gate switches, were expressed by distinct EEG correlates at each gating level that evolved dynamically in partially overlapping time windows. Further, categorical representations of specific maintained items and of motor responses could be decoded from EEG when the corresponding gate was switching, thereby linking gating operations to prioritization. Finally, gate switching at all levels was related to increases in the motor decision threshold as quantified by the drift diffusion model. Together these results support the notion that cognitive gating operations scaffold on top of mechanisms involved in motor gating.

An integrative model of Parkinson's disease treatment including levodopa pharmacokinetics, dopamine kinetics, basal ganglia neurotransmission and motor action throughout disease progression

Levodopa is considered the gold standard treatment of Parkinson's disease. Although very effective in alleviating symptoms at their onset, its chronic use with the progressive neuronal denervation in the basal ganglia leads to a decrease in levodopa's effect duration and to the appearance of motor complications. This evolution challenges the establishment of optimal regimens to manage the symptoms as the disease progresses. Based on up-to-date pathophysiological and pharmacological knowledge, we developed an integrative model for Parkinson's disease to evaluate motor function in response to levodopa treatment as the disease progresses. We combined a pharmacokinetic model of levodopa to a model of dopamine's kinetics and a neurocomputational model of basal ganglia. The parameter values were either measured directly or estimated from human and animal data. The concentrations and behaviors predicted by our model were compared to available information and data. Using this model, we were able to predict levodopa plasma concentration, its related dopamine concentration in the brain and the response performance of a motor task for different stages of disease.

A non-linear deterministic model of action selection in the basal ganglia to simulate motor fluctuations in Parkinson's disease

Motor fluctuations and dyskinesias are severe complications of Parkinson's disease (PD), especially evident at its advanced stage, under long-term levodopa therapy. Despite their strong clinical prevalence, the neural origin of these motor symptoms is still a subject of intense debate. In this work, a non-linear deterministic neurocomputational model of the basal ganglia (BG), inspired by biology, is used to provide more insights into possible neural mechanisms at the basis of motor complications in PD. In particular, the model is used to simulate the finger tapping task. The model describes the main neural pathways involved in the BG to select actions [the direct or Go, the indirect or NoGo, and the hyperdirect pathways via the action of the sub-thalamic nucleus (STN)]. A sensitivity analysis is performed on some crucial model parameters (the dopamine level, the strength of the STN mechanism, and the strength of competition among different actions in the motor cortex) at different levels of synapses, reflecting major or minor motor training. Depending on model parameters, results show that the model can reproduce a variety of clinically relevant motor patterns, including normokinesia, bradykinesia, several attempts before movement, freezing, repetition, and also irregular fluctuations. Motor symptoms are, especially, evident at low or high dopamine levels, with excessive strength of the STN and with weak competition among alternative actions. Moreover, these symptoms worsen if the synapses are subject to insufficient learning. The model may help improve the comprehension of motor complications in PD and, ultimately, may contribute to the treatment design.

Mathematical modeling and parameter estimation of levodopa motor response in patients with parkinson disease

Parkinson disease (PD) is characterized by a clear beneficial motor response to levodopa (LD) treatment. However, with disease progression and longer LD exposure, drug-related motor fluctuations usually occur. Recognition of the individual relationship between LD concentration and its effect may be difficult, due to the complexity and variability of the mechanisms involved. This work proposes an innovative procedure for the automatic estimation of LD pharmacokinetics and pharmacodynamics parameters, by a biologically-inspired mathematical model. An original issue, compared with previous similar studies, is that the model comprises not only a compartmental description of LD pharmacokinetics in plasma and its effect on the striatal neurons, but also a neurocomputational model of basal ganglia action selection. Parameter estimation was achieved on 26 patients (13 with stable and 13 with fluctuating LD response) to mimic plasma LD concentration and alternate finger tapping frequency along four hours after LD administration, automatically minimizing a cost function of the difference between simulated and clinical data points. Results show that individual data can be satisfactorily simulated in all patients and that significant differences exist in the estimated parameters between the two groups. Specifically, the drug removal rate from the effect compartment, and the Hill coefficient of the concentration-effect relationship were significantly higher in the fluctuating than in the stable group. The model, with individualized parameters, may be used to reach a deeper comprehension of the PD mechanisms, mimic the effect of medication, and, based on the predicted neural responses, plan the correct management and design innovative therapeutic procedures.

Driven by Pain, Not Gain: Computational Approaches to Aversion-Related Decision Making in Psychiatry

Although it is well known that "losses loom larger than gains," computational approaches to aversion-related decision making (ARDM) for psychiatric disorders is an underdeveloped area. Computational models of ARDM have been implemented primarily as state-dependent reinforcement learning models with bias parameters to quantify Pavlovian associations, and differential learning rates to quantify instrumental updating have been shown to depend on context, involve complex cost calculations, and include the consideration of counterfactual outcomes. Little is known about how individual differences influence these models relevant to anxiety-related conditions or addiction-related dysfunction. It is argued that model parameters reflecting 1) Pavlovian biases in the context of reinforcement learning or 2) hyperprecise prior beliefs in the context of active inference play an important role in the emergence of dysfunctional avoidance behaviors. The neural implementation of ARDM includes brain areas that are important for valuation (ventromedial prefrontal cortex) and positive reinforcement-related prediction errors (ventral striatum), but also aversive processing (insular cortex and cerebellum). Computational models of ARDM will help to establish a quantitative explanatory account of the development of anxiety disorders and addiction, but such models also face several challenges, including limited evidence for stability of individual differences, relatively low reliability of tasks, and disorder heterogeneity. Thus, it will be necessary to develop robust, reliable, and model-based experimental probes; recruit larger sample sizes; and use single case experimental designs for better pragmatic and explanatory biological models of psychiatric disorders.

Cannabidiol and Cannabinoid Compounds as Potential Strategies for Treating Parkinson's Disease and L-DOPA-Induced Dyskinesia

Parkinson's disease (PD) and L-DOPA-induced dyskinesia (LID) are motor disorders with significant impact on the patient's quality of life. Unfortunately, pharmacological treatments that improve these disorders without causing severe side effects are not yet available. Delay in initiating L-DOPA is no longer recommended as LID development is a function of disease duration rather than cumulative L-DOPA exposure. Manipulation of the endocannabinoid system could be a promising therapy to control PD and LID symptoms. In this way, phytocannabinoids and synthetic cannabinoids, such as cannabidiol (CBD), the principal non-psychotomimetic constituent of the Cannabis sativa plant, have received considerable attention in the last decade. In this review, we present clinical and preclinical evidence suggesting CBD and other cannabinoids have therapeutic effects in PD and LID. Here, we discuss CBD pharmacology, as well as its neuroprotective effects and those of other cannabinoids. Finally, we discuss the modulation of several pro- or anti-inflammatory factors as possible mechanisms responsible for the therapeutic/neuroprotective potential of Cannabis-derived/cannabinoid synthetic compounds in motor disorders.

Dopamine affects short-term memory corruption over time in Parkinson's disease

Cognitive deficits are a recognised component of Parkinson's disease (PD). However, particularly within the domain of short-term memory, it is unclear whether these impairments are masked, or caused, by patients' dopaminergic medication. The effect of medication on pure maintenance in PD patients has rarely been explored, with most assessments examining maintenance intercalated between other executive tasks. Moreover, few studies have utilised methods that can measure the quality of mental representations, which can enable the decomposition of recall errors into their underlying neurocognitive components. Here, we fill this gap by examining pure maintenance in PD patients in high and low dopaminergic states. Participants had to encode the orientation of two stimuli and reproduce these orientations after a short (2 s) or long (8 s) delay. In addition, we also examined the performance of healthy, age-matched older adults to contextualise these effects and determine whether PD represents an exacerbation of the normal ageing process. Patients showed improved recall OFF compared to ON their dopaminergic medication, but only for long-duration trials. Moreover, PD patients OFF their medication actually performed at a level superior to age-matched controls, indicative of a paradoxical enhancement of memory in the low dopaminergic state. The application of a probabilistic model of response selection suggested that PD patients made fewer misbinding errors in the low, compared with high, dopaminergic state for longer-delay trials. Thus, unexpectedly, the mechanisms that prevent memoranda from being corrupted by misbinding over time appear to be enhanced in PD patients OFF dopaminergic medication. Possible explanations for this paradoxical effect are discussed.

Oscillatory Activity in the Cortex, Motor Thalamus and Nucleus Reticularis Thalami in Acute TTX and Chronic 6-OHDA Dopamine-Depleted Animals

The motor thalamus (MTh) and the nucleus reticularis thalami (NRT) have been largely neglected in Parkinson's disease (PD) research, despite their key role as interface between basal ganglia (BG) and cortex (Cx). In the present study, we investigated the oscillatory activity within the Cx, MTh, and NRT, in normal and different dopamine (DA)-deficient states. We performed our experiments in both acute and chronic DA-denervated rats by injecting into the medial forebrain bundle (MFB) tetrodotoxin (TTX) or 6-hydroxydopamine (6-OHDA), respectively. Interestingly, almost all the electroencephalogram (EEG) frequency bands changed in acute and/or chronic DA depletion, suggesting alteration of all oscillatory activities and not of a specific band. Overall, δ (2-4 Hz) and θ (4-8 Hz) band decreased in NRT and Cx in acute and chronic state, whilst, α (8-13 Hz) band decreased in acute and chronic states in the MTh and NRT but not in the Cx. The β (13-40 Hz) and γ (60-90 Hz) bands were enhanced in the Cx. In the NRT the β bands decreased, except for high-β (Hβ, 25-30 Hz) that increased in acute state. In the MTh, Lβ and Hβ decreased in acute DA depletion state and γ decreased in both TTX and 6-OHDA-treated animals. These results confirm that abnormal cortical β band are present in the established DA deficiency and it might be considered a hallmark of PD. The abnormal oscillatory activity in frequency interval of other bands, in particular the dampening of low frequencies in thalamic stations, in both states of DA depletion might also underlie PD motor and non-motor symptoms. Our data highlighted the effects of acute depletion of DA and the strict interplay in the oscillatory activity between the MTh and NRT in both acute and chronic stage of DA depletion. Moreover, our findings emphasize early alterations in the NRT, a crucial station for thalamic information processing.

Fractionating the Neurocognitive Mechanisms Underlying Working Memory: Independent Effects of Dopamine and Parkinson's Disease

Deficits in working memory (WM) in Parkinson’s disease (PD) are often considered to be secondary to dopaminergic depletion. However, the neurocognitive mechanisms by which dopamine causes these deficits remain highly contested, and PD is now also known to be associated with nondopaminergic pathology. Here, we examined how PD and dopaminergic medication modulate three components of WM: maintenance over time, updating contents with new information and making memories distracter-resistant. Compared with controls, patients were disproportionately impaired when retaining information for longer durations. By applying a probabilistic model, we were able to reveal that the source of this error was selectively due to precision of memory representations degrading over time. By contrast, replenishing dopamine levels in PD improved executive control over both the ability to ignore and update, but did not affect maintenance of information across time. This was due to a decrease in guess responses, consistent with the view that dopamine serves to prevent WM representations being corrupted by irrelevant information, but has no impact on information decay. Cumulatively, these results reveal a dissociation in the neural mechanisms underlying poor WM: whereas dopamine reduces interference, nondopaminergic systems in PD appear to modulate processes that prevent information decaying more quickly over time.

To Do or Not to Do: Dopamine, Affordability and the Economics of Opportunity

Five years ago, we introduced the thrift hypothesis of dopamine (DA), suggesting that the primary role of DA in adaptive behavior is regulating behavioral energy expenditure to match the prevailing economic conditions of the environment. Here we elaborate that hypothesis with several new ideas. First, we introduce the concept of affordability, suggesting that costs must necessarily be evaluated with respect to the availability of resources to the organism, which computes a value not only for the potential reward opportunity, but also the value of resources expended. Placing both costs and benefits within the context of the larger economy in which the animal is functioning requires consideration of the different timescales against which to compute resource availability, or average reward rate. Appropriate windows of computation for tracking resources requires corresponding neural substrates that operate on these different timescales. In discussing temporal patterns of DA signaling, we focus on a neglected form of DA plasticity and adaptation, changes in the physical substrate of the DA system itself, such as up- and down-regulation of receptors or release probability. We argue that changes in the DA substrate itself fundamentally alter its computational function, which we propose mediates adaptations to longer temporal horizons and economic conditions. In developing our hypothesis, we focus on DA D2 receptors (D2R), arguing that D2R implements a form of “cost control” in response to the environmental economy, serving as the “brain’s comptroller”. We propose that the balance between the direct and indirect pathway, regulated by relative expression of D1 and D2 DA receptors, implements affordability. Finally, as we review data, we discuss limitations in current approaches that impede fully investigating the proposed hypothesis and highlight alternative, more semi-naturalistic strategies more conducive to neuroeconomic investigations on the role of DA in adaptive behavior.

Interrelations between cognitive dysfunction and motor symptoms of Parkinson's disease: behavioral and neural studies

Parkinson's disease (PD) is characterized by a range of motor symptoms. Besides the cardinal symptoms (tremor, bradykinesia/akinesia, and rigidity), PD patients also show other motor deficits, including gait disturbance, speech deficits, and impaired handwriting. However, along with these key motor symptoms, PD patients also experience cognitive deficits in attention, executive function, working memory, and learning. Recent evidence suggests that these motor and cognitive deficits of PD are not completely dissociable, as aspects of cognitive dysfunction can impact motor performance in PD. In this article, we provide a review of behavioral and neural studies on the associations between motor symptoms and cognitive deficits in PD, specifically akinesia/bradykinesia, tremor, gait, handwriting, precision grip, and speech production. This review paves the way for providing a framework for understanding how treatment of cognitive dysfunction, for example cognitive rehabilitation programs, may in turn influence the motor symptoms of PD.

The Roles of Phasic and Tonic Dopamine in Tic Learning and Expression

Tourette syndrome (TS) prominently involves dopaminergic disturbances, but the precise nature of those disturbances has remained elusive. A substantial body of empirical work and recent computational models have characterized the specific roles of phasic and tonic dopamine (DA) in action learning and selection, respectively. Using insights from this work and models, we suggest that TS involves increases in both phasic and tonic DA, which produce increased propensities for tic learning and expression, respectively. We review the evidence from reinforcement-learning and habit-learning studies in TS, which supports the idea that TS involves increased phasic DA responses; we also review the evidence that tics engage the habit-learning circuitry. On the basis of these findings, we suggest that tics are exaggerated, maladaptive, and persistent motor habits reinforced by aberrant, increased phasic DA responses. Increased tonic DA amplifies the tendency to execute learned tics and also provides a fertile ground of motor hyperactivity for tic learning. We review evidence suggesting that antipsychotics may counter both the increased propensity for tic expression, by increasing excitability in the indirect pathway, and the increased propensity for tic learning, by shifting plasticity in the indirect pathway toward long-term potentiation (and possibly also through more complex mechanisms). Finally, we review evidence suggesting that low doses of DA agonists that effectively treat TS decrease both phasic and tonic DA, thereby also reducing the propensity for both tic learning and tic expression, respectively.

Chronic Nicotine Mitigates Aberrant Inhibitory Motor Learning Induced by Motor Experience under Dopamine Deficiency

Although dopamine receptor antagonism has long been associated with impairments in motor performance, more recent studies have shown that dopamine D2 receptor (D2R) antagonism, paired with a motor task, not only impairs motor performance concomitant with the pharmacodynamics of the drug, but also impairs future motor performance once antagonism has been relieved. We have termed this phenomenon "aberrant motor learning" and have suggested that it may contribute to motor symptoms in movement disorders such as Parkinson's disease (PD). Here, we show that chronic nicotine (cNIC), but not acute nicotine, treatment mitigates the acquisition of D2R-antagonist-induced aberrant motor learning in mice. Although cNIC mitigates D2R-mediated aberrant motor learning, cNIC has no effect on D1R-mediated motor learning. β2-containing nicotinic receptors in dopamine neurons likely mediate the protective effect of cNIC against aberrant motor learning, because selective deletion of β2 nicotinic subunits in dopamine neurons reduced D2R-mediated aberrant motor learning. Finally, both cNIC treatment and β2 subunit deletion blunted postsynaptic responses to D2R antagonism. These results suggest that a chronic decrease in function or a downregulation of β2-containing nicotinic receptors protects the striatal network against aberrant plasticity and aberrant motor learning induced by motor experience under dopamine deficiency.

SIGNIFICANCE STATEMENT

Increasingly, aberrant plasticity and aberrant learning are recognized as contributing to the development and progression of movement disorders. Here, we show that chronic nicotine (cNIC) treatment or specific deletion of β2 nicotinic receptor subunits in dopamine neurons mitigates aberrant motor learning induced by dopamine D2 receptor (D2R) blockade in mice. Moreover, both manipulations also reduced striatal dopamine release and blunt postsynaptic responses to D2R antagonists. These results suggest that chronic downregulation of function and/or receptor expression of β2-containing nicotinic receptors alters presynaptic and postsynaptic striatal signaling to protect against aberrant motor learning. Moreover, these results suggest that cNIC treatment may alleviate motor symptoms and/or delay the deterioration of motor function in movement disorders by blocking aberrant motor learning.

Cognitive states influence dopamine-driven aberrant learning in Parkinson's disease

Individual differences in dopaminergic tone underlie tendencies to learn from reward versus punishment. These effects are well documented in Parkinson's patients, who vacillate between low and high tonic dopaminergic states as a function of medication. Yet very few studies have investigated the influence of higher-level cognitive states known to affect downstream dopaminergic learning in Parkinson's patients. A dopamine-dependent cognitive influence over learning would provide a candidate mechanism for declining cognitive integrity and motivation in Parkinson's patients. In this report we tested the influence of two high-level cognitive states (cost of conflict and value of volition) that have recently been shown to cause predictable learning biases in healthy young adults as a function of dopamine receptor subtype and dopaminergic challenge. It was hypothesized that Parkinson's patients OFF medication would have an enhanced cost of conflict and a decreased value of volition, and that these effects would be remediated or reversed ON medication. Participants included N = 28 Parkinson's disease patients who were each tested ON and OFF dopaminergic medication and 28 age- and sex-matched controls. The expected cost of conflict effect was observed in Parkinson's patients OFF versus ON medication, but only in those that were more recently diagnosed (<5 years). We found an unexpected effect in the value of volition task: medication compromised the ability to learn from difficult a-volitional (instructed) choices. This novel finding was also enhanced in recently diagnosed patients. The difference in learning biases ON versus OFF medication between these two tasks was strongly correlated, bolstering the idea that they tapped into a common underlying imbalance in dopaminergic tone that is particularly variable in earlier stage Parkinsonism. The finding that these decision biases are specific to earlier but not later stage disease may offer a chance for future studies to quantify phenotypic expressions of idiosyncratic disease progression.

Chemogenetic stimulation of striatal projection neurons modulates responses to Parkinson's disease therapy

Parkinson's disease (PD) patients experience loss of normal motor function (hypokinesia), but can develop uncontrollable movements known as dyskinesia upon treatment with L-DOPA. Poverty or excess of movement in PD has been attributed to overactivity of striatal projection neurons forming either the indirect (iSPNs) or the direct (dSPNs) pathway, respectively. Here, we investigated the two pathways' contribution to different motor features using SPN type-specific chemogenetic stimulation in rodent models of PD (PD mice) and L-DOPA-induced dyskinesia (LID mice). Using the activatory Gq-coupled human M3 muscarinic receptor (hM3Dq), we found that chemogenetic stimulation of dSPNs mimicked, while stimulation of iSPNs abolished the therapeutic action of L-DOPA in PD mice. In LID mice, hM3Dq stimulation of dSPNs exacerbated dyskinetic responses to L-DOPA, while stimulation of iSPNs inhibited these responses. In the absence of L-DOPA, only chemogenetic stimulation of dSPNs mediated through the Gs-coupled modified rat muscarinic M3 receptor (rM3Ds) induced appreciable dyskinesia in PD mice. Combining D2 receptor agonist treatment with rM3Ds-dSPN stimulation reproduced all symptoms of LID. These results demonstrate that dSPNs and iSPNs oppositely modulate both therapeutic and dyskinetic responses to dopamine replacement therapy in PD. We also show that chemogenetic stimulation of different signaling pathways in dSPNs leads to markedly different motor outcomes. Our findings have important implications for the design of effective antiparkinsonian and antidyskinetic drug therapies.

Parkinson's disease as a system-level disorder

Traditionally, the basal ganglia have been considered the main brain region implicated in Parkinson’s disease. This single area perspective gives a restricted clinical picture and limits therapeutic approaches because it ignores the influence of altered interactions between the basal ganglia and other cerebral components on Parkinsonian symptoms. In particular, the basal ganglia work closely in concert with cortex and cerebellum to support motor and cognitive functions. This article proposes a theoretical framework for understanding Parkinson’s disease as caused by the dysfunction of the entire basal ganglia–cortex–cerebellum system rather than by the basal ganglia in isolation. In particular, building on recent evidence, we propose that the three key symptoms of tremor, freezing, and impairments in action sequencing may be explained by considering partially overlapping neural circuits including basal ganglia, cortical and cerebellar areas. Studying the involvement of this system in Parkinson’s disease is a crucial step for devising innovative therapeutic approaches targeting it rather than only the basal ganglia. Possible future therapies based on this different view of the disease are discussed.

Dopamine and temporal attention: An attentional blink study in Parkinson's disease patients on and off medication

The current study aimed to shed more light on the role of dopamine in temporal attention. To this end, we pharmacologically manipulated dopamine levels in a large sample of Parkinson's disease patients (n=63) while they performed an attentional blink (AB) task in which they had to identify two targets (T1 and T2) presented in close temporal proximity among distractors. We specifically examined 1) differences in the magnitude of the AB between unmedicated Parkinson patients, who have depleted levels of striatal dopamine, and healthy controls, and 2) effects of two dopaminergic medications (l-DOPA and dopamine agonists) on the AB in the Parkinson patients at the group level and as a function of individual baseline performance. In line with the notion that relatively low levels of striatal dopamine may impair target detection in general, Parkinson patients OFF medications displayed overall poor target perception compared to healthy controls. Moreover, as predicted, effects of dopaminergic medication on AB performance critically depended on individual baseline AB size, although this effect was only observed for l-DOPA. l-DOPA generally decreased the size of the AB in patients with a large baseline AB (i.e., OFF medications), while l-DOPA generally increased the AB in patients with a small baseline AB. These findings may support a role for dopamine in the AB and temporal attention, more generally and corroborate the notion that there is an optimum dopamine level for cognitive function. They also emphasize the need for more studies that examine the separate effects of DA agonists and l-DOPA on cognitive functioning.

A Mathematical Model of Levodopa Medication Effect on Basal Ganglia in Parkinson's Disease: An Application to the Alternate Finger Tapping Task

Malfunctions in the neural circuitry of the basal ganglia (BG), induced by alterations in the dopaminergic system, are responsible for an array of motor disorders and milder cognitive issues in Parkinson's disease (PD). Recently Baston and Ursino (2015a) presented a new neuroscience mathematical model aimed at exploring the role of basal ganglia in action selection. The model is biologically inspired and reproduces the main BG structures and pathways, modeling explicitly both the dopaminergic and the cholinergic system. The present work aims at interfacing this neurocomputational model with a compartmental model of levodopa, to propose a general model of medicated Parkinson's disease. Levodopa effect on the striatum was simulated with a two-compartment model of pharmacokinetics in plasma joined with a motor effect compartment. The latter is characterized by the levodopa removal rate and by a sigmoidal relationship (Hill law) between concentration and effect. The main parameters of this relationship are saturation, steepness, and the half-maximum concentration. The effect of levodopa is then summed to a term representing the endogenous dopamine effect, and is used as an external input for the neurocomputation model; this allows both the temporal aspects of medication and the individual patient characteristics to be simulated. The frequency of alternate tapping is then used as the outcome of the whole model, to simulate effective clinical scores. Pharmacokinetic-pharmacodynamic modeling was preliminary performed on data of six patients with Parkinson's disease (both "stable" and "wearing-off" responders) after levodopa standardized oral dosing over 4 h. Results show that the model is able to reproduce the temporal profiles of levodopa in plasma and the finger tapping frequency in all patients, discriminating between different patterns of levodopa motor response. The more influential parameters are the Hill coefficient, related with the slope of the effect sigmoidal relationship, the drug concentration at half-maximum effect, and the drug removal rate from the effect compartment. The model can be of value to gain a deeper understanding on the pharmacokinetics and pharmacodynamics of the medication, and on the way dopamine is exploited in the neural circuitry of the basal ganglia in patients at different stages of the disease progression.

The Striatum and Subthalamic Nucleus as Independent and Collaborative Structures in Motor Control

The striatum and the subthalamic nucleus (STN) are two separate input structures into the basal ganglia (BG). Accordingly, research to date has primarily focused on the distinct roles of these structures in motor control and cognition, often through investigation of Parkinson’s disease (PD). Both structures are divided into sensorimotor, associative, and limbic subdivisions based on cortical connectivity. The more recent discovery of the STN as an input structure into the BG drives comparison of these two structures and their respective roles in cognition and motor control. This review compares the role of the striatum and STN in motor response inhibition and execution, competing motor programs, feedback based learning, and response planning. Through comparison, it is found that the striatum and STN have highly independent roles in motor control but also collaborate in order to execute desired actions. There is also the possibility that inhibition or activation of one of these structures indirectly contributes to the function of other connected anatomical structures. Both structures contribute to selective motor response inhibition, which forms the basis of many tasks, but the STN additionally contributes to global inhibition through the hyperdirect pathway. Research is warranted on the functional connectivity of the network for inhibition involving the rIFG, preSMA, striatum, and STN.

A computational analysis of flanker interference in depression

BACKGROUND

Depression is characterized by poor executive function, but - counterintuitively - in some studies, it has been associated with highly accurate performance on certain cognitively demanding tasks. The psychological mechanisms responsible for this paradoxical finding are unclear. To address this issue, we applied a drift diffusion model (DDM) to flanker task data from depressed and healthy adults participating in the multi-site Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) study.

METHOD

One hundred unmedicated, depressed adults and 40 healthy controls completed a flanker task. We investigated the effect of flanker interference on accuracy and response time, and used the DDM to examine group differences in three cognitive processes: prepotent response bias (tendency to respond to the distracting flankers), response inhibition (necessary to resist prepotency), and executive control (required for execution of correct response on incongruent trials).

RESULTS

Consistent with prior reports, depressed participants responded more slowly and accurately than controls on incongruent trials. The DDM indicated that although executive control was sluggish in depressed participants, this was more than offset by decreased prepotent response bias. Among the depressed participants, anhedonia was negatively correlated with a parameter indexing the speed of executive control (r = -0.28, p = 0.007).

CONCLUSIONS

Executive control was delayed in depression but this was counterbalanced by reduced prepotent response bias, demonstrating how participants with executive function deficits can nevertheless perform accurately in a cognitive control task. Drawing on data from neural network simulations, we speculate that these results may reflect tonically reduced striatal dopamine in depression.

The algorithmic anatomy of model-based evaluation

Despite many debates in the first half of the twentieth century, it is now largely a truism that humans and other animals build models of their environments and use them for prediction and control. However, model-based (MB) reasoning presents severe computational challenges. Alternative, computationally simpler, model-free (MF) schemes have been suggested in the reinforcement learning literature, and have afforded influential accounts of behavioural and neural data. Here, we study the realization of MB calculations, and the ways that this might be woven together with MF values and evaluation methods. There are as yet mostly only hints in the literature as to the resulting tapestry, so we offer more preview than review.

Zooming in on the small: the plasticity of striatal dendritic spines in L-DOPA-induced dyskinesia

The spiny dendrites of striatal projection neurons integrate synaptic inputs of different origins to regulate movement. It has long been known that these dendrites lose spines and display atrophic features in Parkinson's disease (PD), but the significance of these morphological changes has remained unknown. Some recent studies reveal a remarkable structural plasticity of striatal spines in parkinsonian rodents treated with L-3,4-dihydroxyphenylalanine (L-DOPA), and they demonstrate an association between this plasticity and the development of dyskinesia. These studies used different approaches and animal models, which possibly explains why they emphasize different plastic changes as being most closely linked to dyskinesia (such as a growth of new spines in neurons of the indirect pathway, or a loss of spines in neurons of the direct pathway, or the appearance of spines with aberrant synaptic features). Clearly, further investigations are required to reconcile these intriguing findings and integrate them in a coherent pathophysiological model. Nevertheless, these studies may mark the beginning of a new era for dyskinesia research. In addition to addressing neurochemical and molecular events that trigger involuntary movements, there is a need to better understand the long-lasting structural reorganization of cells and circuits that maintain the brain in a "dyskinesia-prone" state. This may lead to the identification of new efficacious approaches to prevent the complications of dopaminergic therapies in PD.

Methamphetamine-induced neurotoxicity disrupts pharmacologically evoked dopamine transients in the dorsomedial and dorsolateral striatum

Phasic dopamine (DA) signaling, during which burst firing by DA neurons generates short-lived elevations in extracellular DA in terminal fields called DA transients, is implicated in reinforcement learning. Disrupted phasic DA signaling is proposed to link DA depletions and cognitive-behavioral impairment in methamphetamine (METH)-induced neurotoxicity. Here, we further investigated this disruption by assessing effects of METH pretreatment on DA transients elicited by a drug cocktail of raclopride, a D2 DA receptor antagonist, and nomifensine, an inhibitor of the dopamine transporter (DAT). One advantage of this approach is that pharmacological activation provides a large, high-quality data set of transients elicited by endogenous burst firing of DA neurons for analysis of regional differences and neurotoxicity. These pharmacologically evoked DA transients were measured in the dorsomedial (DM) and dorsolateral (DL) striatum of urethane-anesthetized rats by fast-scan cyclic voltammetry. Electrically evoked DA levels were also recorded to quantify DA release and uptake, and DAT binding was determined by means of autoradiography to index DA denervation. Pharmacologically evoked DA transients in intact animals exhibited a greater amplitude and frequency and shorter duration in the DM compared to the DL striatum, despite similar pre- and post-drug assessments of DA release and uptake in both sub-regions as determined from the electrically evoked DA signals. METH pretreatment reduced transient activity. The most prominent effect of METH pretreatment on transients across striatal sub-region was decreased amplitude, which mirrored decreased DAT binding and was accompanied by decreased DA release. Overall, these results identify marked intrastriatal differences in the activity of DA transients that appear independent of presynaptic mechanisms for DA release and uptake and further support disrupted phasic DA signaling mediated by decreased DA release in rats with METH-induced neurotoxicity.

Cyclic AMP and afferent activity govern bidirectional synaptic plasticity in striatopallidal neurons

Recent experimental evidence suggests that the low dopamine conditions in Parkinson's disease (PD) cause motor impairment through aberrant motor learning. Those data, along with computational models, suggest that this aberrant learning results from maladaptive corticostriatal plasticity and learned motor inhibition. Dopaminergic modulation of both corticostriatal long-term depression (LTD) and long-term potentiation (LTP) is proposed to be critical for these processes; however, the regulatory mechanisms underlying bidirectional corticostriatal plasticity are not fully understood. Previously, we demonstrated a key role for cAMP signaling in corticostriatal LTD. In this study, mouse brain slices were used to perform a parametric experiment that tested the impact of varying both intracellular cAMP levels and the strength of excitatory inputs on corticostriatal plasticity. Using slice electrophysiology in the dorsolateral striatum, we demonstrate that both LTP and LTD can be sequentially induced in the same D2-expressing neuron and that LTP was strongest with high intracellular cAMP and LFS, whereas LTD required low intracellular cAMP and high-frequency stimulation. Our results provide a molecular and cellular basis for regulating bidirectional corticostriatal synaptic plasticity and may help to identify novel therapeutic targets for blocking or reversing the aberrant synaptic plasticity that likely contributes to motor deficits in PD.

Motivational tuning of fronto-subthalamic connectivity facilitates control of action impulses

It is critical for survival to quickly respond to environmental stimuli with the most appropriate action. This task becomes most challenging when response tendencies induced by relevant and irrelevant stimulus features are in conflict, and have to be resolved in real time. Inputs from the pre-supplementary motor area (pre-SMA) and inferior frontal gyrus (IFG) to the subthalamic nucleus (STN) are thought to support this function, but the connectivity and causality of these regions in calibrating motor control has not been delineated. In this study, we combined off-line noninvasive brain stimulation and functional magnetic resonance imaging, while young healthy human participants performed a modified version of the Simon task. We show that impairing pre-SMA function by noninvasive brain stimulation improved control over impulsive response tendencies, but only when participants were explicitly rewarded for fast and accurate responses. These effects were mediated by enhanced activation and connectivity of the IFG-STN pathway. These results provide causal evidence for a pivotal role of the IFG-STN pathway during action control. Additionally, they suggest a parallel rather than hierarchical organization of the pre-SMA-STN and IFG-STN pathways, since interruption of pre-SMA function can enhance IFG-STN connectivity and improve control over inappropriate responses.

Time representation in reinforcement learning models of the basal ganglia

Reinforcement learning (RL) models have been influential in understanding many aspects of basal ganglia function, from reward prediction to action selection. Time plays an important role in these models, but there is still no theoretical consensus about what kind of time representation is used by the basal ganglia. We review several theoretical accounts and their supporting evidence. We then discuss the relationship between RL models and the timing mechanisms that have been attributed to the basal ganglia. We hypothesize that a single computational system may underlie both RL and interval timing—the perception of duration in the range of seconds to hours. This hypothesis, which extends earlier models by incorporating a time-sensitive action selection mechanism, may have important implications for understanding disorders like Parkinson's disease in which both decision making and timing are impaired.

Perspectives for computational modeling of cell replacement for neurological disorders

Mathematical modeling of anatomically-constrained neural networks has provided significant insights regarding the response of networks to neurological disorders or injury. A logical extension of these models is to incorporate treatment regimens to investigate network responses to intervention. The addition of nascent neurons from stem cell precursors into damaged or diseased tissue has been used as a successful therapeutic tool in recent decades. Interestingly, models have been developed to examine the incorporation of new neurons into intact adult structures, particularly the dentate granule neurons of the hippocampus. These studies suggest that the unique properties of maturing neurons, can impact circuit behavior in unanticipated ways. In this perspective, we review the current status of models used to examine damaged CNS structures with particular focus on cortical damage due to stroke. Secondly, we suggest that computational modeling of cell replacement therapies can be made feasible by implementing approaches taken by current models of adult neurogenesis. The development of these models is critical for generating hypotheses regarding transplant therapies and improving outcomes by tailoring transplants to desired effects.

Dopamine overdose hypothesis: evidence and clinical implications

About a half a century has passed since dopamine was identified as a neurotransmitter, and it has been several decades since it was established that people with Parkinson's disease receive motor symptom relief from oral levodopa. Despite the evidence that levodopa can reduce motor symptoms, there has been a developing body of literature that dopaminergic therapy can improve cognitive functions in some patients but make them worse in others. Over the past two decades, several laboratories have shown that dopaminergic medications can impair the action of intact neural structures and impair the behaviors associated with these structures. In this review, we consider the evidence that has accumulated in the areas of reversal learning, motor sequence learning, and other cognitive tasks. The purported inverted-U shaped relationship between dopamine levels and performance is complex and includes many contributory factors. The regional striatal topography of nigrostriatal denervation is a critical factor, as supported by multimodal neuroimaging studies. A patient's individual genotype will determine the relative baseline position on this inverted-U curve. Dopaminergic pharmacotherapy and individual gene polymorphisms can affect the mesolimbic and prefrontal cortical dopaminergic functions in a comparable, inverted-U dose-response relationship. Depending on these factors, a patient can respond positively or negatively to levodopa when performing reversal learning and motor sequence learning tasks. These tasks may continue to be relevant as our society moves to increased technological demands of a digital world that requires newly learned motor sequences and adaptive behaviors to manage daily life activities.

Abnormal patterns of theta frequency oscillations during the temporal evolution of freezing of gait in Parkinson's disease

OBJECTIVE

We sought to characterize the electrophysiological signature of Freezing of gait in Parkinson's disease.

METHODS

We examined 24 patients with idiopathic Parkinson's disease and significant freezing of gait as they performed a series of timed up-and-go tasks in their 'off' state while electroencephalographic data was collected from four scalp leads. Fast Fourier Transformation was utilized to explore the power spectral density between periods of normal walking and periods of freezing, as well as during the transition between the two states. In addition, Cross Spectrum and Cross Frequency analyses were used to explore the role of impaired temporal and spatial connectivity.

RESULTS

When compared to walking, episodes of freezing were associated with a significant increase in theta band power within the central and frontal leads. The transition from normal walking to freezing of gait was also associated with increased theta frequency coupling between the central and frontal leads, along with an increase in cross-frequency coupling in the central lead.

CONCLUSIONS

Episodes of freezing of gait in Parkinson's disease are associated with abnormal oscillatory activity in the brain.

SIGNIFICANCE

These results provide novel insights into the pattern of spatiotemporal dynamics underlying freezing of gait and may provide a potential means for therapeutic prediction and alleviation of freezing episodes in susceptible patients.

The role of frontostriatal impairment in freezing of gait in Parkinson's disease

Freezing of gait (FOG) is a disabling symptom of advanced Parkinson's disease (PD) that leads to an increased risk of falls and nursing home placement. Interestingly, multiple lines of evidence suggest that the manifestation of FOG is related to specific deficits in cognition, such as set shifting and the ability to process conflict-related signals. These findings are consistent with the specific patterns of abnormal cortical processing seen during functional neuroimaging experiments of FOG, implicating increased neural activation within cortical structures underlying cognition, such as the Cognitive Control Network. In addition, these studies show that freezing episodes are associated with abnormalities in the BOLD response within key structures of the basal ganglia, such as the striatum and the subthalamic nucleus. In this article, we discuss the implications of these findings on current models of freezing behavior and propose an updated model of basal ganglia impairment during FOG episodes that integrates the neural substrates of freezing from the cortex and the basal ganglia to the cognitive dysfunctions inherent in the condition.

The Enemy within: Propagation of Aberrant Corticostriatal Learning to Cortical Function in Parkinson's Disease

Motor dysfunction in Parkinson’s disease is believed to arise primarily from pathophysiology in the dorsal striatum and its related corticostriatal and thalamostriatal circuits during progressive dopamine denervation. One function of these circuits is to provide a filter that selectively facilitates or inhibits cortical activity to optimize cortical processing, making motor responses rapid and efficient. Corticostriatal synaptic plasticity mediates the learning that underlies this performance-optimizing filter. Under dopamine denervation, corticostriatal plasticity is altered, resulting in aberrant learning that induces inappropriate basal ganglia filtering that impedes rather than optimizes cortical processing. Human imaging suggests that increased cortical activity may compensate for striatal dysfunction in PD patients. In this Perspective article, we consider how aberrant learning at corticostriatal synapses may impair cortical processing and learning and undermine potential cortical compensatory mechanisms. Blocking or remediating aberrant corticostriatal plasticity may protect cortical function and support cortical compensatory mechanisms mitigating the functional decline associated with progressive dopamine denervation.

Amphetamine elicits opposing actions on readily releasable and reserve pools for dopamine

Amphetamine, a highly addictive drug with therapeutic efficacy, exerts paradoxical effects on the fundamental communication modes employed by dopamine neurons in modulating behavior. While amphetamine elevates tonic dopamine signaling by depleting vesicular stores and driving non-exocytotic release through reverse transport, this psychostimulant also activates phasic dopamine signaling by up-regulating vesicular dopamine release. We hypothesized that these seemingly incongruent effects arise from amphetamine depleting the reserve pool and enhancing the readily releasable pool. This novel hypothesis was tested using in vivo voltammetry and stimulus trains of varying duration to access different vesicular stores. We show that amphetamine actions are stimulus dependent in the dorsal striatum. Specifically, amphetamine up-regulated vesicular dopamine release elicited by a short-duration train, which interrogates the readily releasable pool, but depleted release elicited by a long-duration train, which interrogates the reserve pool. These opposing actions of vesicular dopamine release were associated with concurrent increases in tonic and phasic dopamine responses. A link between vesicular depletion and tonic signaling was supported by results obtained for amphetamine in the ventral striatum and cocaine in both striatal sub-regions, which demonstrated augmented vesicular release and phasic signals only. We submit that amphetamine differentially targeting dopamine stores reconciles the paradoxical activation of tonic and phasic dopamine signaling. Overall, these results further highlight the unique and region-distinct cellular mechanisms of amphetamine and may have important implications for its addictive and therapeutic properties.

Methamphetamine-induced neurotoxicity disrupts naturally occurring phasic dopamine signaling

Methamphetamine (METH) is a highly addictive drug that is also neurotoxic to central dopamine (DA) systems. Although striatal DA depletions induced by METH are associated with behavioral and cognitive impairments, the link between these phenomena remains poorly understood. Previous work in both METH-pretreated animals and the 6-hydroxydopamine model of Parkinson's disease suggests that a disruption of phasic DA signaling, which is important for learning and goal-directed behavior, may be such a link. However, previous studies used electrical stimulation to elicit phasic-like DA responses and were also performed under anesthesia, which alters DA neuron activity and presynaptic function. Here we investigated the consequences of METH-induced DA terminal loss on both electrically evoked phasic-like DA signals and so-called 'spontaneous' phasic DA transients measured by voltammetry in awake rats. Not ostensibly attributable to discrete stimuli, these subsecond DA changes may play a role in enhancing reward-cue associations. METH pretreatment reduced tissue DA content in the dorsomedial striatum and nucleus accumbens by ~55%. Analysis of phasic-like DA responses elicited by reinforcing stimulation revealed that METH pretreatment decreased their amplitude and underlying mechanisms for release and uptake to a similar degree as DA content in both striatal subregions. Most importantly, characteristics of DA transients were altered by METH-induced DA terminal loss, with amplitude and frequency decreased and duration increased. These results demonstrate for the first time that denervation of DA neurons alters naturally occurring DA transients and are consistent with diminished phasic DA signaling as a plausible mechanism linking METH-induced striatal DA depletions and cognitive deficits.

Phasic-like stimulation of the medial forebrain bundle augments striatal gene expression despite methamphetamine-induced partial dopamine denervation

Methamphetamine-induced partial dopamine depletions are associated with impaired basal ganglia function, including decreased preprotachykinin mRNA expression and impaired transcriptional activation of activity-regulated, cytoskeleton-associated (Arc) gene in striatum. Recent work implicates deficits in phasic dopamine signaling as a potential mechanism linking methamphetamine-induced dopamine loss to impaired basal ganglia function. This study thus sought to establish a causal link between phasic dopamine transmission and altered basal ganglia function by determining whether the deficits in striatal neuron gene expression could be restored by increasing phasic dopamine release. Three weeks after pretreatment with saline or a neurotoxic regimen of methamphetamine, rats underwent phasic- or tonic-like stimulation of ascending dopamine neurons. Striatal gene expression was examined using in situ hybridization histochemistry. Phasic-like, but not tonic-like, stimulation induced immediate-early genes Arc and zif268 in both groups, despite the partial striatal dopamine denervation in methamphetamine-pretreated rats, with the Arc expression occurring in presumed striatonigral efferent neurons. Phasic-like stimulation also restored preprotachykinin mRNA expression. These results suggest that disruption of phasic dopamine signaling likely underlies methamphetamine-induced impairments in basal ganglia function, and that restoring phasic dopamine signaling may be a viable approach to manage long-term consequences of methamphetamine-induced dopamine loss on basal ganglia functions.

Exploring the cortical and subcortical functional magnetic resonance imaging changes associated with freezing in Parkinson's disease

Freezing of gait is a devastating symptom of advanced Parkinson's disease yet the neural correlates of this phenomenon remain poorly understood. In this study, severity of freezing of gait was assessed in 18 patients with Parkinson's disease on a series of timed 'up and go' tasks, in which all patients suffered from episodes of clinical freezing of gait. The same patients also underwent functional magnetic resonance imaging with a virtual reality gait paradigm, performance on which has recently been shown to correlate with actual episodes of freezing of gait. Statistical parametric maps were created that compared the blood oxygen level-dependent response associated with paroxysmal motor arrests (freezing) to periods of normal motor output. The results of a random effects analysis revealed that these events were associated with a decreased blood oxygen level-dependent response in sensorimotor regions and an increased response within frontoparietal cortical regions. These signal changes were inversely correlated with the severity of clinical freezing of gait. Motor arrests were also associated with decreased blood oxygen level-dependent signal bilaterally in the head of caudate nucleus, the thalamus and the globus pallidus internus. Utilizing a mixed event-related/block design, we found that the decreased blood oxygen level-dependent response in the globus pallidus and the subthalamic nucleus persisted even after controlling for the effects of cognitive load, a finding which supports the notion that paroxysmal increases in basal ganglia outflow are associated with the freezing phenomenon. This method also revealed a decrease in the blood oxygen level-dependent response within the mesencephalic locomotor region during motor arrests, the magnitude of which was positively correlated with the severity of clinical freezing of gait. These results provide novel insights into the pathophysiology underlying freezing of gait and lend support to models of freezing of gait that implicate dysfunction across coordinated neural networks.

Failure to filter: anxious individuals show inefficient gating of threat from working memory

Dispositional anxiety is a well-established risk factor for the development of psychiatric disorders along the internalizing spectrum, including anxiety and depression. Importantly, many of the maladaptive behaviors characteristic of anxiety, such as anticipatory apprehension, occur when threat is absent. This raises the possibility that anxious individuals are less efficient at gating threat's access to working memory, a limited capacity workspace where information is actively retained, manipulated, and used to flexibly guide goal-directed behavior when it is no longer present in the external environment. Using a well-validated neurophysiological index of working memory storage, we demonstrate that threat-related distracters were difficult to filter on average and that this difficulty was exaggerated among anxious individuals. These results indicate that dispositionally anxious individuals allocate excessive working memory storage to threat, even when it is irrelevant to the task at hand. More broadly, these results provide a novel framework for understanding the maladaptive thoughts and actions characteristic of internalizing disorders.