Computational models of basal-ganglia pathway functions: focus on functional neuroanatomy

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.

Striatal projection neurons coexpressing dopamine D1 and D2 receptors modulate the motor function of D1- and D2-SPNs

The role of the striatum in motor control is commonly assumed to be mediated by the two striatal efferent pathways characterized by striatal projection neurons (SPNs) expressing dopamine (DA) D1 receptors or D2 receptors (D1-SPNs and D2-SPNs, respectively), without regard to SPNs coexpressing both receptors (D1/D2-SPNs). Here we developed an approach to target these hybrid SPNs in mice and demonstrate that, although these SPNs are less abundant, they have a major role in guiding the motor function of the other two populations. D1/D2-SPNs project exclusively to the external globus pallidus and have specific electrophysiological features with distinctive integration of DA signals. Gain- and loss-of-function experiments indicate that D1/D2-SPNs potentiate the prokinetic and antikinetic functions of D1-SPNs and D2-SPNs, respectively, and restrain the integrated motor response to psychostimulants. Overall, our findings demonstrate the essential role of this population of D1/D2-coexpressing neurons in orchestrating the fine-tuning of DA regulation in thalamo-cortico-striatal loops.

A Basal Ganglia model for understanding working memory functions in healthy and Parkinson's conditions

Working memory (WM) is considered as the scratchpad for reading, writing, and processing information necessary to perform cognitive tasks. The Basal Ganglia (BG) and Prefrontal Cortex are two important parts of the brain that are involved in WM functions, and both structures receive projections from dopaminergic nuclei. In this modelling study, we specifically focus on modelling the WM functions of the BG, the WM deficits in Parkinson's disease (PD) conditions, and the impact of dopamine deficiency on different kinds of WM functions. Though there are many experimental and modelling studies of WM properties, there is a paucity of models of the BG that provide insights into the contributions of the BG in WM functions. The proposed model of BG uses bistable flip-flop neurons to model striatal up-down neurons, a network of nonlinear oscillators to model the oscillations of the Indirect Pathway of BG and race-model for action selection. Five different WM tasks are used to demonstrate the generalisation ability of the proposed model. Experimental data from the four tasks are compared with model performance in both control and PD conditions. The model is extended to predict the response time of subjects and in the PD version of the model, the effect of dopaminergic medication on WM performance is also simulated. The proposed model of BG is a unified model that can explain the WM functions of the BG over a wide variety of tasks in both normal and PD conditions, and can be used to understand why specific WM functions are impaired whereas others remain intact in PD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-10056-y.

Model of a striatal circuit exploring biological mechanisms underlying decision-making during normal and disordered states

Decision-making requires continuous adaptation to internal and external contexts. Changes in decision-making are reliable transdiagnostic symptoms of neuropsychiatric disorders. We created a computational model demonstrating how the striosome compartment of the striatum constructs a mathematical space for decision-making computations depending on context, and how the matrix compartment defines action value depending on the space. The model explains multiple experimental results and unifies other theories like reward prediction error, roles of the direct versus indirect pathways, and roles of the striosome versus matrix, under one framework. We also found, through new analyses, that striosome and matrix neurons increase their synchrony during difficult tasks, caused by a necessary increase in dimensionality of the space. The model makes testable predictions about individual differences in disorder susceptibility, decision-making symptoms shared among neuropsychiatric disorders, and differences in neuropsychiatric disorder symptom presentation. The model reframes the role of the striosomal circuit in neuroeconomic and disorder-affected decision-making.

Highlights

Striosomes prioritize decision-related data used by matrix to set action values. Striosomes and matrix have different roles in the direct and indirect pathways. Abnormal information organization/valuation alters disorder presentation. Variance in data prioritization may explain individual differences in disorders.

eTOC

Beck et al. developed a computational model of how a striatal circuit functions during decision-making. The model unifies and extends theories about the direct versus indirect pathways. It further suggests how aberrant circuit function underlies decision-making phenomena observed in neuropsychiatric disorders.

Abnormalities in subcortical function and their treatment response in Wilson's disease

Extensive neuroimaging abnormalities in subcortical regions build the pathophysiological basis of Wilson's disease (WD). Yet, subcortical topographic organization fails to articulate, leaving a huge gap in understanding the neural mechanism of WD. Thus, how functional abnormalities of WD subcortical regions influence complex clinical symptoms and response to treatment remain unknown. Using resting-state functional MRI data from 232 participants (including 130 WD patients and 102 healthy controls), we applied a connectivity-based parcellation technique to develop a subcortical atlas for WD. The atlas was further used to investigate abnormalities in subcortical function (ASF) by exploring intrasubcortical functional connectivity (FC) and topographic organization of cortico-subcortical FC. We further used support vector machine (SVM) to integrate these functional abnormalities into the ASF score, which serves as a biomarker for characterizing individual subcortical dysfunction for WD. Finally, the baseline ASF score and one-year treatment data of the follow-up WD patients were used to assess treatment response. A group set of subcortical parcellations was evaluated, in which 26 bilateral regions well recapitulated the anatomical nuclei of the subcortical areas of WD. The results of cortico-subcortical FC and intrasubcortical FC reveal that dysfunction of the somatomotor networks-lenticular nucleus-thalamic pathways is involved in complex symptoms of WD. The ASF score was able to characterize disease progression and was significantly associated with treatment response of WD. Our findings provide a comprehensive elaboration of functional abnormalities of WD subcortical regions and reveal their association with clinical presentations, improving our understanding of the functional neural underpinnings in WD. Furthermore, abnormalities in subcortical function could serve as a potential biomarker for understanding the disease progression and evaluating treatment response of WD.

Rethinking Movement Disorders

At present, clinical practice and research in movement disorders (MDs) focus on the "normalization" of altered movements. In this review, rather than concentrating on problems and burdens people with MDs undoubtedly have, we highlight their hidden potentials. Starting with current definitions of Parkinson's disease (PD), dystonia, chorea, and tics, we outline that solely conceiving these phenomena as signs of dysfunction falls short of their complex nature comprising both problems and potentials. Such potentials can be traced and understood in light of well-established cognitive neuroscience frameworks, particularly ideomotor principles, and their influential modern derivatives. Using these frameworks, the wealth of data on altered perception-action integration in the different MDs can be explained and systematized using the mechanism-oriented concept of perception-action binding. According to this concept, MDs can be understood as phenomena requiring and fostering flexible modifications of perception-action associations. Consequently, although conceived as being caught in a (trough) state of deficits, given their high flexibility, people with MDs also have high potential to switch to (adaptive) peak activity that can be conceptualized as hidden potentials. Currently, clinical practice and research in MDs are concerned with deficits and thus the "deep and wide troughs," whereas "scattered narrow peaks" reflecting hidden potentials are neglected. To better delineate and utilize the latter to alleviate the burden of affected people, and destigmatize their conditions, we suggest some measures, including computational modeling combined with neurophysiological methods and tailored treatment. © 2024 International Parkinson and Movement Disorder Society.

Causality methods to study the functional connectivity in brain networks: the basal ganglia - thalamus causal interactions

This study uses methods recently developed to study the complex evolution of atmospheric phenomena which have some similarities with the dynamics of the human brain. In both cases, it is possible to record the activity of particular centers (geographic regions or brain nuclei) but not to make an experimental modification of their state. The study of "causality", which is necessary to understand the dynamics of these complex systems and to develop robust models that can predict their evolution, is hampered by the experimental restrictions imposed by the nature of both systems. The study was performed with data obtained in the thalamus and basal ganglia of awake humans executing different tasks. This work studies the linear, non-linear and more complex relationships of these thalamic centers with the cortex and main BG nuclei, using three complementary techniques: the partial correlation regression method, the Gaussian process regression/distance correlation and a model-free method based on nearest-neighbor that computes the conditional mutual information. These causality methods indicated that the basal ganglia present a different functional relationship with the anterior-ventral (motor), intralaminar and medio-dorsal thalamic centers, and that more than 60% of these thalamus-basal ganglia relationships present a non-linear dynamic (35 of the 57 relationships found). These functional interactions were observed for basal ganglia nuclei with direct structural connections with the thalamus (primary somatosensory and motor cortex, striatum, internal globus pallidum and substantia nigra pars reticulata), but also for basal ganglia without structural connections with the thalamus (external globus pallidum and subthalamic nucleus). The motor tasks induced rapid modifications of the thalamus-basal ganglia interactions. These findings provide new perspectives of the thalamus - BG interactions, many of which may be supported by indirect functional relationships and not by direct excitatory/inhibitory interactions.

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.

Temporally non-regular patterns of deep brain stimulation (DBS) enhance assessment of evoked potentials while maintaining motor symptom management in Parkinson's disease (PD)

BACKGROUND

Traditional deep brain stimulation (DBS) at fixed regular frequencies (>100 Hz) is effective in treating motor symptoms of Parkinson's disease (PD). Temporally non-regular patterns of DBS are a new parameter space that may help increase efficacy and efficiency.

OBJECTIVE

To compare the effects of temporally non-regular patterns of DBS to traditional regularly-spaced pulses.

METHODS

We simultaneously recorded local field potentials (LFP) and monitored motor symptoms (tremor and bradykinesia) in persons with PD during DBS in subthalamic nucleus (STN). We quantified both oscillatory activity and DBS local evoked potentials (DLEPs) from the LFP.

RESULTS

Temporally non-regular patterns were as effective as traditional pulse patterns in modulating motor symptoms, oscillatory activity, and DLEPs. Moreover, one of our novel patterns enabled recording of longer duration DLEPs during clinically effective stimulation.

CONCLUSIONS

Stimulation gaps of 50 ms can be used to increase efficiency and to enable regular assessment of long-duration DLEPs while maintaining effective symptom management. This may be a promising paradigm for closed-loop DBS with biomarker assessment during the gaps.

Evaluation of the efficacy and safety of MRI-guided focused ultrasound (MRgFUS) for focal hand dystonia: study protocol for an open-label non-randomised clinical trial

Introduction

MRI-guided focused ultrasound (MRgFUS) thalamotomy provides an exciting development in the field of minimally invasive stereotactic neurosurgery. Current treatment options for focal hand dystonia are limited, with potentially more effective invasive stereotactic interventions, such as deep brain stimulation or lesional therapies, rarely used. The advent of minimally invasive brain lesioning provides a potentially safe and effective treatment approach with a recent pilot study establishing MRgFUS Vo-complex thalamotomy as an effective treatment option for focal hand dystonia. In this study, we undertake an open-label clinical trial to further establish MRgFUS Vo-complex thalamotomy as an effective treatment for focal hand dystonia with greater attention paid to potential motor costs associated with this treatment. To elucidate pathophysiology of dystonia and treatment mechanisms, neurophysiological and MRI analysis will be performed longitudinally to explore the hypothesis that neuroplastic and structural changes that may underlie this treatment benefit.

Methods and analysis

A total of 10 participants will be recruited into this open-label clinical trial. All participants will undergo clinical, kinemetric, neurophysiological and radiological testing at baseline, followed by repeated measures at predesignated time points post MRgFUS Vo-complex thalamotomy. Further, to identify any underlying structural or neurophysiological abnormalities present in individuals with focal hand dystonia, 10 age and gender matched control participants will be recruited to undergo comparative investigation. These results will be compared with the intervention participants both at baseline and at 12 months to assess for normalisation of these abnormalities, if present.

Ethics and dissemination

This trial was reviewed and approved by the St Vincent's Health Network Sydney Human Research Ethics Committee (2022/ETH00778). Study results will be published in peer-reviewed journals and presented at both national and international conferences.

Trial registration number

CTRN12622000775718.

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.

Distinct cortico-striatal compartments drive competition between adaptive and automatized behavior

Cortical and basal ganglia circuits play a crucial role in the formation of goal-directed and habitual behaviors. In this study, we investigate the cortico-striatal circuitry involved in learning and the role of this circuitry in the emergence of inflexible behaviors such as those observed in addiction. Specifically, we develop a computational model of cortico-striatal interactions that performs concurrent goal-directed and habit learning. The model accomplishes this by distinguishing learning processes in the dorsomedial striatum (DMS) that rely on reward prediction error signals as distinct from the dorsolateral striatum (DLS) where learning is supported by salience signals. These striatal subregions each operate on unique cortical input: the DMS receives input from the prefrontal cortex (PFC) which represents outcomes, and the DLS receives input from the premotor cortex which determines action selection. Following an initial learning of a two-alternative forced choice task, we subjected the model to reversal learning, reward devaluation, and learning a punished outcome. Behavior driven by stimulus-response associations in the DLS resisted goal-directed learning of new reward feedback rules despite devaluation or punishment, indicating the expression of habit. We repeated these simulations after the impairment of executive control, which was implemented as poor outcome representation in the PFC. The degraded executive control reduced the efficacy of goal-directed learning, and stimulus-response associations in the DLS were even more resistant to the learning of new reward feedback rules. In summary, this model describes how circuits of the dorsal striatum are dynamically engaged to control behavior and how the impairment of executive control by the PFC enhances inflexible behavior.

The characteristics of glucose metabolism and functional connectivity in posterior default network during nondemented aging: relationship with executive function performance

BACKGROUND

Understanding the characteristics of intrinsic connectivity networks (ICNs) in terms of both glucose metabolism and functional connectivity (FC) is important for revealing cognitive aging and neurodegeneration, but the relationships between these two aspects during aging has not been well established in older adults.

OBJECTIVE

This study is to assess the relationship between age-related glucose metabolism and FC in key ICNs, and their direct or indirect effects on cognitive deficits in older adults.

METHODS

We estimated the individual-level standard uptake value ratio (SUVr) and FC of eleven ICNs in 59 cognitively unimpaired older adults, then analyzed the associations of SUVr and FC of each ICN and their relationships with cognitive performance.

RESULTS

The results showed both the SUVr and FC in the posterior default mode network (pDMN) had a significant decline with age, and the association between them was also significant. Moreover, both decline of metabolism and FC in the pDMN were significantly correlated with executive function decline. Finally, mediation analysis revealed the glucose metabolism mediated the FC decline with age and FC mediated the executive function deficits.

CONCLUSIONS

Our findings indicated that covariance between glucose metabolism and FC in the pDMN is one of the main routes that contributes to age-related executive function decline.

Prefrontal Cortex Activation and Stopping Performance Underlie the Beneficial Effects of Atomoxetine on Response Inhibition in Healthy Volunteers and Those With Cocaine Use Disorder

BACKGROUND

Impaired response inhibition in individuals with cocaine use disorder (CUD) is hypothesized to depend on deficient noradrenergic signaling in corticostriatal networks. Remediation of noradrenergic neurotransmission with selective norepinephrine reuptake inhibitors such as atomoxetine may therefore have clinical utility to improve response inhibitory control in CUD.

METHODS

We carried out a randomized, double-blind, placebo-controlled, crossover study with 26 participants with CUD and 28 control volunteers investigating the neural substrates of stop-signal inhibitory control. The effects of a single dose of atomoxetine (40 mg) were compared with placebo on stop-signal reaction time performance and functional network connectivity using dynamic causal modeling.

RESULTS

We found that atomoxetine speeded Go response times in both control participants and those with CUD. Improvements in stopping efficiency on atomoxetine were conditional on baseline (placebo) stopping performance and were directly associated with increased inferior frontal gyrus activation. Further, stopping performance, task-based brain activation, and effective connectivity were similar in the 2 groups. Dynamic causal modeling of effective connectivity of multiple prefrontal and basal ganglia regions replicated and extended previous models of network function underlying inhibitory control to CUD and control volunteers and showed subtle effects of atomoxetine on prefrontal-basal ganglia interactions.

CONCLUSIONS

These findings demonstrate that atomoxetine improves response inhibition in a baseline-dependent manner in control participants and in those with CUD. Our results emphasize inferior frontal cortex function as a future treatment target owing to its key role in improving response inhibition in CUD.

Missing pieces in decoding the brain oxytocin puzzle: Functional insights from mouse brain wiring diagrams

The hypothalamic neuropeptide, oxytocin (Oxt), has been the focus of research for decades due to its effects on body physiology, neural circuits, and various behaviors. Oxt elicits a multitude of actions mainly through its receptor, the Oxt receptor (OxtR). Despite past research to understand the central projections of Oxt neurons and OxtR- coupled signaling pathways in different brain areas, it remains unclear how this nonapeptide exhibits such pleiotropic effects while integrating external and internal information. Most reviews in the field either focus on neuroanatomy of the Oxt-OxtR system, or on the functional effects of Oxt in specific brain areas. Here, we provide a review by integrating brain wide connectivity of Oxt neurons and their downstream circuits with OxtR expression in mice. We categorize Oxt connected brain regions into three functional modules that regulate the internal state, somatic visceral, and cognitive response. Each module contains three neural circuits that process distinct behavioral effects. Broad innervations on functional circuits (e.g., basal ganglia for motor behavior) enable Oxt signaling to exert coordinated modulation in functionally inter-connected circuits. Moreover, Oxt acts as a neuromodulator of neuromodulations to broadly control the overall state of the brain. Lastly, we discuss the mismatch between Oxt projections and OxtR expression across various regions of the mouse brain. In summary, this review brings forth functional circuit-based analysis of Oxt connectivity across the whole brain in light of Oxt release and OxtR expression and provides a perspective guide to future studies.

Auricular Transcutaneous Vagus Nerve Stimulation Diminishes Alpha-Band-Related Inhibitory Gating Processes During Conflict Monitoring in Frontal Cortices

BACKGROUND

Pursuing goals is compromised when being confronted with interfering information. In such situations, conflict monitoring is important. Theoretical considerations on the neurobiology of response selection and control suggest that auricular transcutaneous vagus nerve stimulation (atVNS) should modulate conflict monitoring. However, the neurophysiological-functional neuroanatomical underpinnings are still not understood.

METHODS

AtVNS was applied in a randomized crossover study design (n = 45). During atVNS or sham stimulation, conflict monitoring was assessed using a Flanker task. EEG data were recorded and analyzed with focus on theta and alpha band activity. Beamforming was applied to examine functional neuroanatomical correlates of atVNS-induced EEG modulations. Moreover, temporal EEG signal decomposition was applied to examine different coding levels in alpha and theta band activity.

RESULTS

AtVNS compromised conflict monitoring processes when it was applied at the second appointment in the crossover study design. On a neurophysiological level, atVNS exerted specific effects because only alpha-band activity was modulated. Alpha-band activity was lower in middle and superior prefrontal regions during atVNS stimulation and thus lower when there was also a decline in task performance. The same direction of alpha-band modulations was evident in fractions of the alpha-band activity coding stimulus-related processes, stimulus-response translation processes, and motor response-related processes.

CONCLUSIONS

The combination of prior task experience and atVNS compromises conflict monitoring processes. This is likely due to reduction of the alpha-band-associated inhibitory gating process on interfering information in frontal cortices. Future research should pay considerable attention to boundary conditions affecting the direction of atVNS effects.

Model-based quantitative optimization of deep brain stimulation and prediction of parkinson's states

Although the exact etiology of Parkinson's disease (PD) is still unknown, there are a variety of treatments available to alleviate its symptoms according to the development stage of PD. Deep brain stimulation (DBS), the most common surgical treatment for advanced PD, accurately locates and implants stimulating electrodes at specific targets in the brain to deliver high-frequency electrical stimulation that alters the excitability of the corresponding nuclei. However, for different patients and stages of PD development, there exists a choice of the optimal DBS protocol. In this paper, we propose a quantitative method (multi-dimensional feature indexes) to determine the stimulation pattern, stimulation parameters, and target of DBS from the perspective of the network model. On the other hand, based on this method, the development of PD can be predicted so that timely treatment can be given to patients. Simulation results show that, first, different network states can be distinguished by extracting features of the firing activity of neuronal populations within the basal ganglia network system. Secondly, the optimal DBS treatment can be selected by comparing the feature indexes vectors of the pre- and post-state of the network after the action of different modes of DBS. Lastly, the evolution of the network state from normal to pathological is simulated. The critical point of network state transitions is determined. These results provide a quantitative and qualitative method for determining the optimal regimen for DBS for PD, which is helpful for clinical practice.

The metacontrol hypothesis as diagnostic framework of OCD and ADHD: A dimensional approach based on shared neurobiological vulnerability

Obsessive-compulsive disorder (OCD) and attention-deficit hyperactivity disorder (ADHD) are multi-faceted neuropsychiatric conditions that in many aspects appear to be each other's antipodes. We suggest a dimensional approach, according to which these partially opposing disorders fall onto a continuum that reflects variability regarding alterations of cortico-striato-thalamo-cortical (CSTC) circuits and of the processing of neural noise during cognition. By using theoretical accounts of human cognitive metacontrol, we develop a framework according to which OCD can be characterized by a chronic bias towards exaggerated cognitive persistence, equivalent to a high signal-to-noise ratio (SNR)-which facilitates perseverative behaviour but impairs mental flexibility. In contrast, ADHD is characterized by a chronic bias towards inflated cognitive flexibility, equivalent to a low SNR-which increases behavioural variability but impairs the focusing on one goal and on relevant information. We argue that, when pharmacology is not feasible, novel treatments of these disorders may involve methods to manipulate the signal-to-noise ratio via non-invasive brain stimulation techniques, in order to normalize the situational imbalance between cognitive persistence and cognitive flexibility.

Biophysical and Architectural Mechanisms of Subthalamic Theta under Response Conflict

The cortico-basal ganglia circuit is needed to suppress prepotent actions and to facilitate controlled behavior. Under conditions of response conflict, the frontal cortex and subthalamic nucleus (STN) exhibit increased spiking and theta band power, which are linked to adaptive regulation of behavioral output. The electrophysiological mechanisms underlying these neural signatures of impulse control remain poorly understood. To address this lacuna, we constructed a novel large-scale, biophysically principled model of the subthalamopallidal (STN-globus pallidus externus) network and examined the mechanisms that modulate theta power and spiking in response to cortical input. Simulations confirmed that theta power does not emerge from intrinsic network dynamics but is robustly elicited in response to cortical input as burst events representing action selection dynamics. Rhythmic burst events of multiple cortical populations, representing a state of conflict where cortical motor plans vacillate in the theta range, led to prolonged STN theta and increased spiking, consistent with empirical literature. Notably, theta band signaling required NMDA, but not AMPA, currents, which were in turn related to a triphasic STN response characterized by spiking, silence, and bursting periods. Finally, theta band resonance was also strongly modulated by architectural connectivity, with maximal theta arising when multiple cortical populations project to individual STN "conflict detector" units because of an NMDA-dependent supralinear response. Our results provide insights into the biophysical principles and architectural constraints that give rise to STN dynamics during response conflict, and how their disruption can lead to impulsivity and compulsivity.SIGNIFICANCE STATEMENT The subthalamic nucleus exhibits theta band power modulation related to cognitive control over motor actions during conditions of response conflict. However, the mechanisms of such dynamics are not understood. Here we developed a novel biophysically detailed and data-constrained large-scale model of the subthalamopallidal network, and examined the impacts of cellular and network architectural properties that give rise to theta dynamics. Our investigations implicate an important role for NMDA receptors and cortico-subthalamic nucleus topographical connectivities in theta power modulation.

Early life stress influences basal ganglia dopamine receptors and novel object recognition of adolescent and adult rats

Environmental stimuli in early life are recognized to affect brain development and behavior. Mother-pup interaction constitutes a determinant stimulus during this critical period. It is known that the dopaminergic system undergoes significant reorganization during adolescence and that dopamine receptors are involved in recognition memory. Based on the above, we examined the effects of brief and prolonged maternal separation during the neonatal period (15 or 180 min daily) on basal ganglia dopamine receptors and on the behavior in the novel object recognition task of adolescent and adult male rats. Using the NOR task, we observed that the discrimination index (DI) was decreased in rats with brief maternal separations independent of age. Using receptor autoradiography, we observed that brief maternal separation induced decreases in D1, D2 and D4 receptor binding levels in adult basal ganglia nuclei, while prolonged maternal separation induced increases in D1 receptor binding levels in caudate - putamen (CPu) of adolescent rats. With immunoblotting experiments, we found decreases in D1 and increases in D2 total protein levels in CPu of adult rats with prolonged maternal separations. Α positive correlation was observed between DI and D1 binding levels in CPu, internal globus pallidus and substantia nigra, and D2 binding levels in nucleus accumbens core in adult rats, using the Pearson correlation coefficient. Our results indicate that the long-lasting effects of neonatal mother-offspring separation on dopamine receptors depend on the duration of maternal separation and age and that this early life experience impairs recognition memory in adolescent and adult rats. Furthermore, the present results suggest that modulation of striatal dopamine receptors might underlie the reduced recognition memory of adult rats with brief neonatal maternal separations.

Increased Basal Ganglia Modulatory Effective Connectivity Observed in Resting-State fMRI in Individuals With Parkinson's Disease

Alterations to interactions between networked brain regions underlie cognitive impairment in many neurodegenerative diseases, providing an important physiological link between brain structure and cognitive function. Previous attempts to characterize the effects of Parkinson's disease (PD) on network functioning using resting-state functional magnetic resonance imaging (rs-fMRI), however, have yielded inconsistent and contradictory results. Potential problems with prior work arise in the specifics of how the area targeted by the diseases (the basal ganglia) interacts with other brain regions. Specifically, current computational models point to the fact that the basal ganglia contributions should be captured with modulatory (i.e., second-order) rather than direct (i.e., first-order) functional connectivity measures. Following this hypothesis, a principled but manageable large-scale brain architecture, the Common Model of Cognition, was used to identify differences in basal ganglia connectivity in PD by analyzing resting-state fMRI data from 111 participants (70 patients with PD; 41 healthy controls) using Dynamic Causal Modeling (DCM). Specifically, the functional connectivity of the basal ganglia was modeled as two second-level, modulatory connections that control projections from sensory cortices to the prefrontal cortex, and from the hippocampus and medial temporal lobe to the prefrontal cortex. We then examined group differences between patients with PD and healthy controls in estimated modulatory effective connectivity in these connections. The Modulatory variant of the Common Model of Cognition outperformed the Direct model across all subjects. It was also found that these second-level modulatory connections had higher estimates of effective connectivity in the PD group compared to the control group, and that differences in effective connectivity were observed for all direct connections between the PD and control groups.We make the case that accounting for modulatory effective connectivity better captures the effects of PD on network functioning and influences the interpretation of the directionality of the between-group results. Limitations include that the PD group was scanned on dopaminergic medication, results were derived from a reasonable but small number of individuals and the ratio of PD to healthy control participants was relatively unbalanced. Future research will examine if the observed effect holds for individuals with PD scanned off their typical dopaminergic medications.

Coarse-Grained Neural Network Model of the Basal Ganglia to Simulate Reinforcement Learning Tasks

Computational models of the basal ganglia (BG) provide a mechanistic account of different phenomena observed during reinforcement learning tasks performed by healthy individuals, as well as by patients with various nervous or mental disorders. The aim of the present work was to develop a BG model that could represent a good compromise between simplicity and completeness. Based on more complex (fine-grained neural network, FGNN) models, we developed a new (coarse-grained neural network, CGNN) model by replacing layers of neurons with single nodes that represent the collective behavior of a given layer while preserving the fundamental anatomical structures of BG. We then compared the functionality of both the FGNN and CGNN models with respect to several reinforcement learning tasks that are based on BG circuitry, such as the Probabilistic Selection Task, Probabilistic Reversal Learning Task and Instructed Probabilistic Selection Task. We showed that CGNN still has a functionality that mirrors the behavior of the most often used reinforcement learning tasks in human studies. The simplification of the CGNN model reduces its flexibility but improves the readability of the signal flow in comparison to more detailed FGNN models and, thus, can help to a greater extent in the translation between clinical neuroscience and computational modeling.

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

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

Sustained attention induces altered effective connectivity of the ascending thalamo-cortical relay in obsessive-compulsive disorder

Abnormal function of the thalamo-cortical relay is considered a hallmark of obsessive-compulsive disorder (OCD) and aberrant network interactions may underpin many of the clinical and cognitive symptoms that characterize the disorder. Several statistical approaches have been applied to in vivo fMRI data to support the general loss of thalamo-cortical connectivity in OCD. However, (a) few studies have assessed the contextual constraints under which abnormal network interactions arise or (b) have used methods of effective connectivity to understand abnormal network interactions. Effective connectivity is a particularly valuable method as it describes the putative causal influences that brain regions exert over each other, as opposed to the largely statistical consistencies captured in functional connectivity techniques. Here, using dynamic causal modeling (DCM), we evaluated how attention demand induced inter-group differences (HC ≠ OCD) in effective connectivity within a motivated thalamo-cortical network. Of interest was whether these effects were observed on the ascending thalamo-cortical relay, essential for the sensory innervation of the cortex. fMRI time series data from sixty-two participants (OCD, 30; HC, 32) collected using an established sustained attention task were submitted to a space of 162 competing models. Across the space, models distinguished between competing hypotheses of thalamo-cortical interactions. Bayesian model selection (BMS) identified marginally differing likely generative model architectures in OCD and HC groups. Bayesian model averaging (BMA), was used to weight connectivity parameter estimates across all models, with each parameter weighted by each model's posterior probability, thus providing more stable estimates of effective connectivity. Inferential statistical analyses of estimated parameters revealed two principal results: (1) Significantly reduced intrinsic connectivity of the V1 → SPC pathway in OCD, suggested connective weakness in the early constituents of the dorsal visual pathway; (2) More pertinent with the discovery possibilities afforded by DCM, sustained attention in OCD patients induced significantly reduced contextual modulation of the ascending relay from the thalamus to the prefrontal cortex. These results form an important complement to our understanding of the contextual bases of thalamo-cortical network deficits in OCD, emphasizing vulnerability of the ascending relay.

Bihemispheric developmental alterations in basal ganglia volumes following unilateral perinatal stroke

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Basal ganglia segmentation appears reliable in children with perinatal stroke.

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Alterations from perinatal stroke to basal ganglia development may be bihemispheric.

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Stroke type may dictate nucleus-specific differences in basal ganglia development.

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Putamen volume is associated with motor function in children with perinatal stroke.

Introduction

Perinatal stroke affects millions of children and results in lifelong disability. Two forms prevail: arterial ischemic stroke (AIS), and periventricular venous infarction (PVI). With such focal damage early in life, neural structures may reorganize during development to determine clinical function, particularly in the contralesional hemisphere. Such processes are increasingly understood in the motor system, however, the role of the basal ganglia, a group of subcortical nuclei that are critical to movement, behaviour, and learning, remain relatively unexplored. Perinatal strokes that directly damage the basal ganglia have been associated with worse motor outcomes, but how developmental plasticity affects bilateral basal ganglia structure is unknown. We hypothesized that children with perinatal stroke have alterations in bilateral basal ganglia volumes, the degree of which correlates with clinical motor function.

Methods

Children with AIS or PVI, and controls, aged 6–19 years, were recruited from a population-based cohort. MRIs were acquired on a 3 T GE MR750w scanner. High-resolution T1-weighted images (166 slices, 1 mm isotropic voxels) underwent manual segmentations of bilateral caudate and putamen. Extracted volumes were corrected for total intracranial volume. A structure volume ratio quantified hemispheric asymmetry of caudate and putamen (non-dominant/dominant hemisphere structure volume) with ratios closer to 1 reflecting a greater degree of symmetry between structures. Participants were additionally dichotomized by volume ratios into two groups, those with values above the group mean (0.8) and those below. Motor function was assessed using the Assisting Hand Assessment (AHA) and the Box and Blocks test in affected (BBTA) and unaffected (BBTU) hands. Group differences in volumes were explored using Kruskal-Wallis tests, and interhemispheric differences using Wilcoxon. Partial Spearman correlations explored associations between volumes and motor function (factoring out age, and whole-brain white matter volume, a proxy for lesion extent).

Results

In the dominant (non-lesioned) hemisphere, volumes were larger in AIS compared to PVI for both the caudate (p < 0.05) and putamen (p < 0.01) but comparable between stroke groups and controls. Non-dominant (lesioned) hemisphere volumes were larger for controls than AIS for the putamen (p < 0.05), and for the caudate in PVI (p = 0.001). Interhemispheric differences showed greater dominant hemisphere volumes for the putamen in controls (p < 0.01), for both the caudate (p < 0.01) and putamen (p < 0.001) in AIS, and for the caudate (p = 0.01) in PVI. Motor scores did not differ between AIS and PVI thus groups were combined to increase statistical power. Better motor scores were associated with larger non-dominant putamen volumes (BBTA: r = 0.40, p = 0.011), and larger putamen volume ratios (BBTA: r = 0.52, p < 0.001, AHA: r = 0.43, p < 0.01). For those with relatively symmetrical putamen volume ratios (ratio > group mean of 0.8), age was positively correlated with BBTA (r = 0.54, p < 0.01) and BBTU (r = 0.69, p < 0.001). For those with more asymmetrical putamen volume ratios, associations with motor function and age were not seen (BBTA: r = 0.21, p = 0.40, BBTU: r = 0.37, p = 0.13).

Conclusion

Specific perinatal stroke lesions affect different elements of basal ganglia development. PVI primarily affected the caudate, while AIS primarily affected the putamen. Putamen volumes in the lesioned hemisphere are associated with clinical motor function. The basal ganglia should be included in evolving models of developmental plasticity after perinatal stroke.

Optimal attention tuning in a neuro-computational model of the visual cortex-basal ganglia-prefrontal cortex loop

Visual attention is widely considered a vital factor in the perception and analysis of a visual scene. Several studies explored the effects and mechanisms of top-down attention, but the mechanisms that determine the attentional signal are less explored. By developing a neuro-computational model of visual attention including the visual cortex-basal ganglia loop, we demonstrate how attentional alignment can evolve based on dopaminergic reward during a visual search task. Unlike most previous modeling studies of feature-based attention, we do not implement a manually predefined attention template. Dopamine-modulated covariance learning enable the basal ganglia to learn rewarded associations between the visual input and the attentional gain represented in the PFC of the model. Hence, the model shows human-like performance on a visual search task by optimally tuning the attention signal. In particular, similar as in humans, this reward-based tuning in the model leads to an attentional template that is not centered on the target feature, but a relevant feature deviating away from the target due to the presence of highly similar distractors. Further analyses of the model shows, attention is mainly guided by the signal-to-noise ratio between target and distractors.

Basal ganglia-orbitofrontal circuits are associated with prospective memory deficits in Wilson's disease

Degenerative changes in the basal ganglia (BG) are thought to contribute to neurological symptoms in Wilson's disease (WD). However, very little is known about whether and how the BG have an influence on prospective memory (PM) by interacting with the cerebral cortex. Here, we employed structural magnetic resonance imaging to systematically examine the effect of volume atrophy of BG on cortical thickness and to evaluate the relationships between cortical thickness of regions associated with BG atrophy and PM performance in WD. Cortical thickness atrophy in the left temporal pole and medial frontal gyrus are not related to degenerative changes in BG. Cortical thickness in the left superior frontal gyrus and right orbitofrontal gyrus (ORB) have stronger correlations with volume atrophy of the left accumbens, pallidum, and putamen in WD when compared with healthy controls. Furthermore, the cortical thickness of the right ORB is not only significantly correlated with PM performance but can also distinguish the severity of PM impairment in WD. Additionally, the middle cingulate cortex was related to volume atrophy of the accumbens, and its cortical thickness has a significant positive correlation with event-based PM. Together, these findings highlight that BG-orbitofrontal circuits may serve as neural biomarkers of PM and provide implications for the neural mechanisms underlying cognitive impairment in WD.

Neuro4PD: An Initial Neurorobotics Model of Parkinson's Disease

In this work, we present the first steps toward the creation of a new neurorobotics model of Parkinson's Disease (PD) that embeds, for the first time in a real robot, a well-established computational model of PD. PD mostly affects the modulation of movement in humans. The number of people suffering from this neurodegenerative disease is set to double in the next 15 years and there is still no cure. With the new model we were capable to further explore the dynamics of the disease using a humanoid robot. Results show that the embedded model under both conditions, healthy and parkinsonian, was capable of performing a simple behavioural task with different levels of motor disturbance. We believe that this neurorobotics model is a stepping stone to the development of more sophisticated models that could eventually test and inform new PD therapies and help to reduce and replace animals in research.

The causal interaction in human basal ganglia

The experimental study of the human brain has important restrictions, particularly in the case of basal ganglia, subcortical centers whose activity can be recorded with fMRI methods but cannot be directly modified. Similar restrictions occur in other complex systems such as those studied by Earth system science. The present work studied the cause/effect relationships between human basal ganglia with recently introduced methods to study climate dynamics. Data showed an exhaustive (identifying basal ganglia interactions regardless of their linear, non-linear or complex nature) and selective (avoiding spurious relationships) view of basal ganglia activity, showing a fast functional reconfiguration of their main centers during the execution of voluntary motor tasks. The methodology used here offers a novel view of the human basal ganglia which expands the perspective provided by the classical basal ganglia model and may help to understand BG activity under normal and pathological conditions.

A spiking model of basal ganglia dynamics in stopping behavior supported by arkypallidal neurons

The common view that stopping action plans by the basal ganglia is achieved mainly by the subthalamic nucleus alone due to its direct excitatory projection onto the output nuclei of the basal ganglia has been challenged by recent findings. The proposed "pause-then-cancel" model suggests that the subthalamic nucleus provides a rapid stimulus-unspecific "pause" signal, followed by a stop-cue-specific "cancel" signal from striatum-projecting arkypallidal neurons. To determine more precisely the relative contribution of the different basal ganglia nuclei in stopping, we simulated a stop-signal task with a spiking neuron model of the basal ganglia, considering recently discovered connections from the arkypallidal neurons, and cortex-projecting GPe neurons. For the arkypallidal and prototypical GPe neurons, we obtained neuron model parameters by fitting their neuronal responses to published experimental data. Our model replicates findings of stop-signal tasks at neuronal and behavioral levels. We provide evidence for the existence of a stop-related cortical input to the arkypallidal and cortex-projecting GPe neurons such that the stop responses of the subthalamic nucleus, the arkypallidal neurons, and the cortex-projecting GPe neurons complement each other to achieve functional stopping behavior. Particularly, the cortex-projecting GPe neurons may complement the stopping within the basal ganglia caused by the arkypallidal and STN neurons by diminishing cortical go-related processes. Furthermore, we predict effects of lesions on stopping performance and propose that arkypallidal neurons mainly participate in stopping by inhibiting striatal neurons of the indirect rather than the direct pathway.

A new era for executive function research: On the transition from centralized to distributed executive functioning

"Executive functions" (EFs) is an umbrella term for higher cognitive control functions such as working memory, inhibition, and cognitive flexibility. One of the most challenging problems in this field of research has been to explain how the wide range of cognitive processes subsumed as EFs are controlled without an all-powerful but ill-defined central executive in the brain. Efforts to localize control mechanisms in circumscribed brain regions have not led to a breakthrough in understanding how the brain controls and regulates itself. We propose to re-conceptualize EFs as emergent consequences of highly distributed brain processes that communicate with a pool of highly connected hub regions, thus precluding the need for a central executive. We further discuss how graph-theory driven analysis of brain networks offers a unique lens on this problem by providing a reference frame to study brain connectivity in EFs in a holistic way and helps to refine our understanding of the mechanisms underlying EFs by providing new, testable hypotheses and resolves empirical and theoretical inconsistencies in the EF literature.

Neural Mechanisms of Human Decision-Making

We present a theory and neural network model of the neural mechanisms underlying human decision-making. We propose a detailed model of the interaction between brain regions, under a proposer-predictor-actor-critic​ ​framework. This theory is based on detailed animal data and theories of action-selection. Those theories are adapted to serial operation to bridge levels of analysis and explain human decision-making. Task-relevant areas of cortex propose a candidate plan using fast, model-free, parallel neural computations. Other areas of cortex and medial temporal lobe can then predict​ likely outcomes of that plan in this situation. This optional prediction- (or model-) based computation can produce better accuracy and generalization, at the expense of speed. Next, linked regions of basal ganglia act​ to accept or reject the proposed plan based on its reward history in similar contexts. If that plan is rejected, the process repeats to consider a new option. The reward-prediction system acts as a critic​ to determine the value of the outcome relative to expectations and produce dopamine as a training signal for cortex and basal ganglia. By operating sequentially and hierarchically, the same mechanisms previously proposed for animal action-selection could explain the most complex human plans and decisions. We discuss explanations of model-based decisions, habitization, and risky behavior based on the computational model.

Cortico-basal ganglia circuits underlying dysfunctional control of motor behaviors in neuropsychiatric disorders

Neuropsychiatric disorders often manifest with abnormal control of motor behavior. Common symptoms include restricted and repetitive patterns of behavior (RRBs). Cortico-basal ganglia circuits have been implicated in the etiology of RBBs. However, there is a vast range of behaviors encompassed in RRBs, from simple explosive motor tics to rather complex ritualized compulsions. In this review, we highlight how recent findings about the function of specific basal ganglia circuits can begin to shed light into defined motor symptoms associated with neuropsychiatric disorders. We discuss recent studies using genetic animal models that advocate that different aspects of motor repetition in neurodevelopmental disorders, like obsessive-compulsive disorder and autism spectrum disorder, emerge from particular dysregulations in distinct cortico-basal ganglia circuits.

Sedative drugs modulate the neuronal activity in the subthalamic nucleus of parkinsonian patients

Microelectrode recording (MER) is often used to identify electrode location which is critical for the success of deep brain stimulation (DBS) treatment of Parkinson’s disease. The usage of anesthesia and its’ impact on MER quality and electrode placement is controversial. We recorded neuronal activity at a single depth inside the Subthalamic Nucleus (STN) before, during, and after remifentanil infusion. The root mean square (RMS) of the 250–6000 Hz band-passed signal was used to evaluate the regional spiking activity, the power spectrum to evaluate the oscillatory activity and the coherence to evaluate synchrony between two microelectrodes. We compare those to new frequency domain (spectral) analysis of previously obtained data during propofol sedation. Results showed Remifentanil decreased the normalized RMS by 9% (P < 0.001), a smaller decrease compared to propofol. Regarding the beta range oscillatory activity, remifentanil depressed oscillations (drop from 25 to 5% of oscillatory electrodes), while propofol did not (increase from 33.3 to 41.7% of oscillatory electrodes). In the cases of simultaneously recorded oscillatory electrodes, propofol did not change the synchronization while remifentanil depressed it. In conclusion, remifentanil interferes with the identification of the dorsolateral oscillatory region, whereas propofol interferes with RMS identification of the STN borders. Thus, both have undesired effect during the MER procedure.

Trial registration: NCT00355927 and NCT00588926.

Optimal Control Perspective on Parkinson's Disease: Increased Delay Between State Estimator and Controller Produces Tremor

Parkinson's disease produces tremor in a large subset of patients despite generally inhibiting movement. The pathophysiology of parkinsonian tremor is unclear, leading to uncertainty in how and why treatments reduce tremor with varying effectiveness. Models for parkinsonian tremor attempt to explain the underlying principles of tremor generation in the central nervous system, often focusing on neural activity of specific substructures. In contrast, control system approaches to modeling the human motor system provide qualitative results that help inform conclusions from clinical studies. This article uses an optimal control approach to investigate the hypothesis that an increased delay in the central nervous system-unaccounted by delay compensation mechanisms-produces parkinsonian tremor. This hypothesis is motivated by the excessive inhibition projected from the basal ganglia to the thalamus in Parkinson's disease. The thalamus relays signals from the cerebellum to the primary motor cortex: previous mapping of optimal control components indicates this prospective delay exists between the estimator (cerebellum) and controller (primary motor cortex). Simulations demonstrate realistic tremor in a neuromuscular model of the wrist. In addition, changes to effort sensitivity in the optimal controller may account for some clinical features of parkinsonian tremor, including the characteristics of re-emergent tremor and the time-varying amplitude and frequency of tremor. Contextualization of the optimal control model with physiological models and clinical observations provides insight into the potential role of the basal ganglia and cerebello-thalamo-cortical circuit and how treatments like dopaminergic medications and deep brain stimulation reduce tremor.

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.

Habit learning in hierarchical cortex-basal ganglia loops

How do the multiple cortico-basal ganglia-thalamo-cortical loops interact? Are they parallel and fully independent or controlled by an arbitrator, or are they hierarchically organized? We introduce here a set of four key concepts, integrated and evaluated by means of a neuro-computational model, that bring together current ideas regarding cortex-basal ganglia interactions in the context of habit learning. According to key concept 1, each loop learns to select an intermediate objective at a different abstraction level, moving from goals in the ventral striatum to motor in the putamen. Key concept 2 proposes that the cortex integrates the basal ganglia selection with environmental information regarding the achieved objective. Key concept 3 claims shortcuts between loops, and key concept 4 predicts that loops compute their own prediction error signal for learning. Computational benefits of the key concepts are demonstrated. Contrasting with former concepts of habit learning, the loops collaborate to select goal-directed actions while training slower shortcuts develops habitual responses.

New players in basal ganglia dysfunction in Parkinson's disease

The classical model of the basal ganglia (BG) circuit has been recently revised with the identification of other structures that play an increasing relevant role especially in the pathophysiology of Parkinson's disease (PD). Numerous studies have supported the spreading of the alpha-synuclein pathology to several areas beyond the BG and likely even before their involvement. With the aim of better understanding PD pathophysiology and finding new targets for treatment, the spinal cord, the pedunculopontine nucleus, the substantia nigra pars reticulata, the retina, the superior colliculus, the cerebellum, the nucleus parabrachialis and the Meynert's nucleus have been investigated both in animal and human studies. In this chapter, we describe the main anatomical and functional connections between the above structures and the BG, the relationship between their pathology and PD features, and the rational of applying neuromodulation treatment to improve motor and non-motor symptoms in PD. Some of these new players in the BG circuits might also have a potential intriguing role as early biomarkers of PD.

The dynamic of basal ganglia activity with a multiple covariance method: influences of Parkinson's disease

The closed-loop cortico-subcortical pathways of basal ganglia have been extensively used to describe the physiology of these centres and to justify the functional disorders of basal ganglia diseases. This approach justifies some experimental and clinical data but not others, and furthermore, it does not include a number of subcortical circuits that may produce a more complex basal ganglia dynamic than that expected for closed-loop linear networks. This work studied the functional connectivity of the main regions of the basal ganglia motor circuit with magnetic resonance imaging and a new method (functional profile method), which can analyse the multiple covariant activity of human basal ganglia. The functional profile method identified the most frequent covariant functional status (profiles) of the basal ganglia motor circuit, ordering them according to their relative frequency and identifying the most frequent successions between profiles (profile transitions). The functional profile method classified profiles as input profiles that accept the information coming from other networks, output profiles involved in the output of processed information to other networks and highly interconnected internal profiles that accept transitions from input profiles and send transitions to output profiles. Profile transitions showed a previously unobserved functional dynamic of human basal ganglia, suggesting that the basal ganglia motor circuit may work as a dynamic multiple covariance network. The number of internal profiles and internal transitions showed a striking decrease in patients with Parkinson’s disease, a fact not observed for input and output profiles. This suggests that basal ganglia of patients with Parkinson’s disease respond to requirements coming from other neuronal networks, but because the internal processing of information is drastically weakened, its response will be insufficient and perhaps also self-defeating. These marked effects were found in patients with few motor disorders, suggesting that the functional profile method may be an early procedure to detect the first stages of the Parkinson’s disease when the motor disorders are not very evident. The multiple covariance activity found presents a complementary point of view to the cortico-subcortical closed-loop model of basal ganglia. The functional profile method may be easily applied to other brain networks, and it may provide additional explanations for the clinical manifestations of other basal ganglia disorders.

Effects of the antidepressant medication duloxetine on brain metabolites in persistent depressive disorder: A randomized, controlled trial

Background

To assess whether patients with Persistent Depressive Disorder (PDD) have abnormal levels of N-acetyl-aspartate (NAA) and whether those levels normalize following treatment with the antidepressant medication duloxetine. Furthermore, we conducted post hoc analyses of other important brain metabolites to understand better the cellular and physiological determinants for changes in NAA levels.

Methods

We acquired proton (1H) magnetic resonance spectroscopic imaging (MRSI) data on a 3 Tesla (3T), GE Magnetic Resonance Imaging (MRI) scanner in 41 patients (39.9±10.4 years, 22 males) with PDD at two time points: before the start and at the end of a 10-week, placebo-controlled, double-blind, randomized controlled trial (RCT) of the antidepressant medication duloxetine. Patients were randomized such that 21 patients received the active medication and 20 patients received placebo during the 10 week period of the trial. In addition, we acquire 1H MRSI data once in 29 healthy controls (37.7±11.2 years, 17 males).

Findings

Patients had significantly higher baseline concentrations of NAA across white matter (WM) pathways and subcortical gray matter, and in direct proportion to the severity of depressive symptoms. NAA concentrations declined in duloxetine-treated patients over the duration of the trial in the direction toward healthy values, whereas concentrations increased in placebo-treated patients, deviating even further away from healthy values. Changes in NAA concentration did not mediate medication effects on reducing symptom severity, however; instead, changes in symptom severity partially mediated the effects of medication on NAA concentration, especially in the caudate and putamen.

Interpretation

These findings, taken together, suggest that PDD is not a direct consequence of elevated NAA concentrations, but that a more fundamental pathophysiological process likely causes PDD and determines the severity of its symptoms. The findings also suggest that although duloxetine normalized NAA concentrations in patients, it did so by modulating the severity of depressive symptoms. Medication presumably reduced depressive symptoms through other, as yet unidentified, brain processes.

Trial registration

ClinicalTrials.gov NCT00360724.

Altered amplitude of low-frequency fluctuation in basal ganglia correlates to pulmonary ventilation function in COPD patients: A resting-state fMRI study

INTRODUCTION

Patients under chronic obstructive pulmonary disease (COPD) has been reported to be associated with a higher prevalence of cognitive impairment (CI). However, it is still largely unknown whether the aberrant resting-state spontaneous neuronal activity pattern reflected by the amplitude of low-frequency fluctuation (ALFF) analysis will be associated with the CI in COPD patients.

MATERIALS

A total of 28 COPD patients and 26 healthy controls were enrolled in this study. Of all the subjects, structural and functional MRI data, spirometry tests performance and neuropsychological assessments of different cognitive domains were collected. Voxel-based two-sample t tests were used to detect brain regions showing differences in the ALFF value between COPD patients and healthy controls. An additional fMRI runs with supplementary oxygen delivery were employed to explore the impact of elevated partial pressure of oxygen (PaO₂ ) or moderate hyperoxia on ALFF in COPD patients and healthy controls respectively.

RESULTS

More extensive white matter lesion was detected in COPD patients. COPD patients exhibit decreased ALFF value in bilateral basal ganglia areas and right thalamus, and aberrant ALFF value is correlated with PaO₂ and pulmonary ventilation function (FEV1%pred). COPD patients performed worse in the Digit Span Test (reverse), Digit Symbol Substitution Test, Trail-making test (A and B) than controls. After supplementary oxygen inhalation, the ALFF value of basal ganglia and right thalamus significantly increased in the controls, but not in the COPD patients.

CONCLUSIONS

COPD patients mainly exhibit impaired executive function but not long-term memory in cognitive function assessment. Aberrant ALFF alteration in the deep brain may be directly related to lower PaO₂ in COPD patients.

The homotopic connectivity of the functional brain: a meta-analytic approach

Homotopic connectivity (HC) is the connectivity between mirror areas of the brain hemispheres. It can exhibit a marked and functionally relevant spatial variability, and can be perturbed by several pathological conditions. The voxel-mirrored homotopic connectivity (VMHC) is a technique devised to enquire this pattern of brain organization, based on resting state functional connectivity. Since functional connectivity can be revealed also in a meta-analytical fashion using co-activations, here we propose to calculate the meta-analytic homotopic connectivity (MHC) as the meta-analytic counterpart of the VMHC. The comparison between the two techniques reveals their general similarity, but also highlights regional differences associated with how HC varies from task to rest. Two main differences were found from rest to task: (i) regions known to be characterized by global hubness are more similar than regions displaying local hubness; and (ii) medial areas are characterized by a higher degree of homotopic connectivity, while lateral areas appear to decrease their degree of homotopic connectivity during task performance. These findings show that MHC can be an insightful tool to study how the hemispheres functionally interact during task and rest conditions.

The organization of the basal ganglia functional connectivity network is non-linear in Parkinson's disease

The motor symptoms in Parkinson's disease (PD) have been linked to changes in the excitatory/inhibitory interactions of centers involved in the cortical-subcortical closed-loop circuits which connect basal ganglia (BG) and the brain cortex. This approach may explain some motor symptoms of PD but not others, which has driven the study of BG from new perspectives. Besides their cortical-subcortical linear circuits, BG have a number of subcortical circuits which directly or indirectly connect each BG with all the others. This suggests that BG may work as a complex network whose output is the result of massive functional interactions between all of their nuclei (decentralized network; DCN), more than the result of the linear excitatory/inhibitory interactions of the cortical-subcortical closed-loops. The aim of this work was to study BG as a DCN, and to test whether the DCN behavior of BG changes in PD. BG activity was recorded with MRI methods and their complex interactions were studied with a procedure based on multiple correspondence analysis, a data-driven multifactorial method which can work with non-linear multiple interactions. The functional connectivity of twenty parkinsonian patients and eighteen age-matched controls were studied during resting and when they were performing sequential hand movements. Seven functional configurations were identified in the control subjects during resting, and some of these interactions changed with motor activity. Five of the seven interactions found in control subjects changed in Parkinson's disease. The BG response to the motor task was also different in PD patients and controls. These data show the basal ganglia as a decentralized network where each region can perform multiple functions and each function is performed by multiple regions. This framework of BG interactions may provide new explanations concerning motor symptoms of PD which are not explained by current BG models.

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The classical basal ganglia model is based on linear excitatory/inhibitory interactions.

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The classical model only explains part of the motor disorders of Parkinson's disease.

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fcMRI images were studied with Multiple Correspondence Analysis (MCA).

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MCA showed multiple non-linear interactions between basal ganglia.

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Parkinson's disease induced marked changes of non-linear basal ganglia interactions.

Methamphetamine Users Show No Behavioral Deficits in Response Selection After Protracted Abstinence

Introduction: Chronic recreational methamphetamine use causes dopaminergic neurotoxicity, which has been linked to impairments in executive functioning. Within this functional domain, response selection and the resolution of associated conflicts have repeatedly been demonstrated to be strongly modulated by dopamine. Yet, it has never been investigated whether chronic methamphetamine use leads to general impairments in response selection (i.e., irrespective of consumption-associated behavior) after substance use is discontinued. Materials and Methods: We tested n = 24 abstinent methamphetamine users (on average 2.7 years of abstinence) and n = 24 individually matched controls in a cross-sectional design with a flanker task. Results: Compared to healthy controls, former methamphetamine consumers had significantly slower reaction times, but did not show differences in the size of the flanker or Gratton effect, or post-error slowing. Complementary Bayesian analyses further substantiated this lack of effects despite prior consumption for an average of 7.2 years. Discussion: The ability to select a correct response from a subset of conflicting alternatives, as well as the selective attention required for this seem to be largely preserved in case of prolonged abstinence. Likewise, the ability to take previous contextual information into account during response selection and to process errors seem to be largely preserved as well. Complementing previously published finding of worse inhibition/interference control in abstinent consumers, our results suggest that not all executive domains are (equally) impaired by methamphetamine, possibly because different cognitive processes require different levels of dopamine activity.

Association of Affected Neurocircuitry With Deficit of Response Inhibition and Delayed Gratification in Attention Deficit Hyperactivity Disorder: A Narrative Review

The neural networks that constitute corticostriatothalamocortical circuits between prefrontal cortex and subcortical structure provide a heuristic framework for bridging gaps between neurocircuitry and executive dysfunction in attention deficit hyperactivity disorder (ADHD). “Cool” and “Hot” executive functional theory and the models of dual pathway are supposed to be applied within the neuropsychology of ADHD. The theoretical model elaborated response inhibition and delayed gratification in ADHD. We aimed to review and summarize the literature about the circuits on ADHD and ADHD-related comorbidities, as well as the effects of neurocircuitry on the executive dysfunction in ADHD.

Roles for globus pallidus externa revealed in a computational model of action selection in the basal ganglia

The basal ganglia are considered vital to action selection - a hypothesis supported by several biologically plausible computational models. Of the several subnuclei of the basal ganglia, the globus pallidus externa (GPe) has been thought of largely as a relay nucleus, and its intrinsic connectivity has not been incorporated in significant detail, in any model thus far. Here, we incorporate newly revealed subgroups of neurons within the GPe into an existing computational model of the basal ganglia, and investigate their role in action selection. Three main results ensued. First, using previously used metrics for selection, the new extended connectivity improved the action selection performance of the model. Second, low frequency theta oscillations were observed in the subpopulation of the GPe (the TA or 'arkypallidal' neurons) which project exclusively to the striatum. These oscillations were suppressed by increased dopamine activity - revealing a possible link with symptoms of Parkinson's disease. Third, a new phenomenon was observed in which the usual monotonic relationship between input to the basal ganglia and its output within an action 'channel' was, under some circumstances, reversed. Thus, at high levels of input, further increase of this input to the channel could cause an increase of the corresponding output rather than the more usually observed decrease. Moreover, this phenomenon was associated with the prevention of multiple channel selection, thereby assisting in optimal action selection. Examination of the mechanistic origin of our results showed the so-called 'prototypical' GPe neurons to be the principal subpopulation influencing action selection. They control the striatum via the arkypallidal neurons and are also able to regulate the output nuclei directly. Taken together, our results highlight the role of the GPe as a major control hub of the basal ganglia, and provide a mechanistic account for its control function.

On the Role of Cortex-Basal Ganglia Interactions for Category Learning: A Neurocomputational Approach

In addition to the prefrontal cortex (PFC), the basal ganglia (BG) have been increasingly often reported to play a fundamental role in category learning, but the circuit mechanisms mediating their interaction remain to be explored. We developed a novel neurocomputational model of category learning that particularly addresses the BG-PFC interplay. We propose that the BG bias PFC activity by removing the inhibition of cortico-thalamo-cortical loop and thereby provide a teaching signal to guide the acquisition of category representations in the corticocortical associations to the PFC. Our model replicates key behavioral and physiological data of macaque monkey learning a prototype distortion task from Antzoulatos and Miller (2011) Our simulations allowed us to gain a deeper insight into the observed drop of category selectivity in striatal neurons seen in the experimental data and in the model. The simulation results and a new analysis of the experimental data based on the model's predictions show that the drop in category selectivity of the striatum emerges as the variability of responses in the striatum rises when confronting the BG with an increasingly larger number of stimuli to be classified. The neurocomputational model therefore provides new testable insights of systems-level brain circuits involved in category learning that may also be generalized to better understand other cortico-BG-cortical loops.SIGNIFICANCE STATEMENT Inspired by the idea that basal ganglia (BG) teach the prefrontal cortex (PFC) to acquire category representations, we developed a novel neurocomputational model and tested it on a task that was recently applied in monkey experiments. As an advantage over previous models of category learning, our model allows to compare simulation data with single-cell recordings in PFC and BG. We not only derived model predictions, but already verified a prediction to explain the observed drop in striatal category selectivity. When testing our model with a simple, real-world face categorization task, we observed that the fast striatal learning with a performance of 85% correct responses can teach the slower PFC learning to push the model performance up to almost 100%.

The Accessory Olfactory System: Innately Specialized or Microcosm of Mammalian Circuitry?

In mammals, the accessory olfactory system is a distinct circuit that has received attention for its role in detecting and responding to pheromones. While the neuroscientific investigation of this system is comparatively new, recent advances and its compact size have made it an attractive model for developing an end-to-end understanding of such questions as regulation of essential behaviors, plasticity, and individual recognition. Recent discoveries have indicated a need to reevaluate our conception of this system, suggesting that ( a) physical principles—rather than biological necessity—play an underappreciated role in its raison d'être and that ( b) the anatomy of downstream projections is not dominated by unique specializations but instead consists of an abbreviated cortical/basal ganglia motif reminiscent of other sensorimotor systems. These observations suggest that the accessory olfactory system distinguishes itself primarily by the physicochemical properties of its ligands, but its architecture is otherwise a microcosm of mammalian neurocircuitry.