What do the basal ganglia do? A modeling perspective

Improved Mathematical Models of Parkinson's Disease with Hopf Bifurcation and Huntington's Disease with Chaos

Using delay differential equations to study mathematical models of Parkinson's disease and Huntington's disease is important to show how important it is for synchronization between basal ganglia loops to work together. We used the delay circuit RLC (resistor, inductor, capacitor) model to show how the direct pathway and the indirect pathway in the basal ganglia excite and inhibit the motor cortex, respectively. A term has been added to the mathematical model without time delay in the case of the hyperdirect pathway. It is proposed to add a non-linear term to adjust the synchronization. We studied Hopf bifurcation conditions for the proposed models. The desynchronization of response times between the direct pathway and the indirect pathway leads to different symptoms of Parkinson's disease. Tremor appears when the response time in the indirect pathway increases at rest. The simulation confirmed that tremor occurs and the motor cortex is in an inhibited state. The direct pathway can increase the time delay in the dopaminergic pathway, which significantly increases the activity of the motor cortex. The hyperdirect pathway regulates the activity of the motor cortex. The simulation showed bradykinesia occurs when we switch from one movement to another that is less exciting for the motor cortex. A decrease of GABA in the striatum or delayed excitation of the substantia nigra from the subthalamus may be a major cause of Parkinson's disease. An increase in the response time delay in one of the pathways results in the chaotic movement characteristic of Huntington's disease.

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

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

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.

The way we look at an image or a webpage can reveal personality traits

Personality is a central concept and a cross-domain explanatory factor in psychology to characterize and differentiate individuals. Surprisingly, among the many studies on oculomotor behavior, only a few have investigated how personality influences the exploration of a visual stimulus. Due to the limited number of existing studies, it is still uncertain if markers of personality in eye movements are always observable in eye movements across various exploration contexts. Here, introducing a novel concept of gaze-based signatures of personality, we used visual exploration metrics to detect personality signatures across various exploration contexts (visual search and free-viewing on images and webpages) in 91 participants. Personality data were collected as in the reference paper that validated the French version of the Big Five Inventory. Linear regression analyses demonstrated that while Extraversion and Openness to Experience did not correlate with any particular exploration metric, the other three traits-Conscientiousness, Agreeableness, and Neuroticism-correlated robustly with all exploration metrics in different visual exploration contexts. Our study provides evidence for the capture of the gaze-based signature of personality from very brief eye movement recordings.

Distinct dopaminergic spike-timing-dependent plasticity rules are suited to different functional roles

Various mathematical models have been formulated to describe the changes in synaptic strengths resulting from spike-timing-dependent plasticity (STDP). A subset of these models include a third factor, dopamine, which interacts with the timing of pre- and postsynaptic spiking to contribute to plasticity at specific synapses, notably those from cortex to striatum at the input layer of the basal ganglia. Theoretical work to analyze these plasticity models has largely focused on abstract issues, such as the conditions under which they may promote synchronization and the weight distributions induced by inputs with simple correlation structures, rather than on scenarios associated with specific tasks, and has generally not considered dopamine-dependent forms of STDP. In this paper, we analyze, mathematically and with simulations, three forms of dopamine-modulated STDP in three scenarios that are relevant to corticostriatal synapses. Two of the models considered comprise previously proposed STDP rules with modifications to incorporate dopamine, while the third is a corticostriatal dopamine-dependent STDP rule adapted from a similar one already in the literature. We test the ability of each of the three models to maintain its weights in the face of noise and to complete simple reward prediction and action selection tasks, studying the learned weight distributions and corresponding task performance in each setting. Interestingly, we find that each of the three plasticity rules is well suited to a subset of the scenarios studied but falls short in others. These results show that different tasks may require different forms of synaptic plasticity, yielding the prediction that the precise form of the STDP mechanism may vary across regions of the striatum, and other brain areas impacted by dopamine, that are involved in distinct computational functions.

Stochastic characterization of navigation strategies in an automated variant of the Barnes maze

Animals can use a repertoire of strategies to navigate in an environment, and it remains an intriguing question how these strategies are selected based on the nature and familiarity of environments. To investigate this question, we developed a fully automated variant of the Barnes maze, characterized by 24 vestibules distributed along the periphery of a circular arena, and monitored the trajectories of mice over 15 days as they learned to navigate towards a goal vestibule from a random start vestibule. We show that the patterns of vestibule visits can be reproduced by the combination of three stochastic processes reminiscent of random, serial, and spatial strategies. The processes randomly selected vestibules based on either uniform (random) or biased (serial and spatial) probability distributions. They closely matched experimental data across a range of statistical distributions characterizing the length, distribution, step size, direction, and stereotypy of vestibule sequences, revealing a shift from random to spatial and serial strategies over time, with a strategy switch occurring approximately every six vestibule visits. Our study provides a novel apparatus and analysis toolset for tracking the repertoire of navigation strategies and demonstrates that a set of stochastic processes can largely account for exploration patterns in the Barnes maze.

Influence of cognitive reserve on cognitive and motor function in α-synucleinopathies: A systematic review and multilevel meta-analysis

Cognitive reserve has shown promise as a justification for neuropathologically unexplainable clinical outcomes in Alzheimer's disease. Recent evidence suggests this effect may be replicated in conditions like Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. However, the relationships between cognitive reserve and different cognitive abilities, as well as motor outcomes, are still poorly understood in these conditions. Additionally, it is unclear whether the reported effects are confounded by medication. This review analysed studies investigating the relationship between cognitive reserve and clinical outcomes in these α-synucleinopathy cohorts, identified from MEDLINE, Scopus, psycINFO, CINAHL, and Web of Science. 85 records, containing 176 cognition and 31 motor function effect sizes, were pooled using multilevel meta-analysis. There was a significant, positive association between higher cognitive reserve and both better cognition and motor function. Cognition effect sizes differed by disease subtype, cognitive reserve measure, and outcome type; however, no moderators significantly impacted motor function. Review findings highlight the clinical implications of cognitive reserve and importance of engaging in reserve-building behaviours.

Rich-club organization of whole-brain spatio-temporal multilayer functional connectivity networks

Objective

In this work, we propose a novel method for constructing whole-brain spatio-temporal multilayer functional connectivity networks (FCNs) and four innovative rich-club metrics.

Methods

Spatio-temporal multilayer FCNs achieve a high-order representation of the spatio-temporal dynamic characteristics of brain networks by combining the sliding time window method with graph theory and hypergraph theory. The four proposed rich-club scales are based on the dynamic changes in rich-club node identity, providing a parameterized description of the topological dynamic characteristics of brain networks from both temporal and spatial perspectives. The proposed method was validated in three independent differential analysis experiments: male-female gender difference analysis, analysis of abnormality in patients with autism spectrum disorders (ASD), and individual difference analysis.

Results

The proposed method yielded results consistent with previous relevant studies and revealed some innovative findings. For instance, the dynamic topological characteristics of specific white matter regions effectively reflected individual differences. The increased abnormality in internal functional connectivity within the basal ganglia may be a contributing factor to the occurrence of repetitive or restrictive behaviors in ASD patients.

Conclusion

The proposed methodology provides an efficacious approach for constructing whole-brain spatio-temporal multilayer FCNs and conducting analysis of their dynamic topological structures. The dynamic topological characteristics of spatio-temporal multilayer FCNs may offer new insights into physiological variations and pathological abnormalities in neuroscience.

Cognitive Control Architecture for the Practical Realization of UAV Collision Avoidance

A highly intelligent system often draws lessons from the unique abilities of humans. Current humanlike models, however, mainly focus on biological behavior, and the brain functions of humans are often overlooked. By drawing inspiration from brain science, this article shows how aspects of brain processing such as sensing, preprocessing, cognition, obstacle learning, behavior, strategy learning, pre-action, and action can be melded together in a coherent manner with cognitive control architecture. This work is based on the notion that the anti-collision response is activated in sequence, which starts from obstacle sensing to action. In the process of collision avoidance, cognition and learning modules continuously control the UAV's repertoire. Furthermore, simulated and experimental results show that the proposed architecture is effective and feasible.

Fifty Years of Handedness Research: A Neurological and Methodological Update

Handedness, a complex human aspect that reflects the functional lateralization of the hemispheres, also interacts with the immune system. This study aimed to expand the knowledge of the lateralization of hand, foot, and eye activities in patients with immune-mediated (IM) or other (noIM) neurological diseases and to clarify the properties of the Edinburgh Handedness Inventory (EHI) in an Italian population. Three hundred thirty-four patients with IM or noIM diseases affecting the brain or spine and peripheral nervous system were interviewed about stressful events preceding the disease, subjective handedness, and familiarity for left-handedness or ambidexterity. The patients and 40 healthy subjects underwent EHI examination. In the whole group of participants, 24 items of the EHI were classified into five factors (Hand Transitive, Hand Refined, Hand Median, Foot, Eye), demonstrating good reliability and validity. Chronological age had a significant influence on hand and foot EHI factors and the laterality quotient (LQ), particularly on writing and painting. In the patient groups, EHI factors and the LQ were also predicted by age of disease onset, duration of disease, and family history of left-handedness or ambidexterity. No differences were found between patients and healthy subjects, but pencil use scored significantly lower in patients with IM diseases than in those with noIM brain diseases. These results demonstrate that the lateralization of hand and foot activities is not a fixed human aspect, but that it can change throughout life, especially for abstract and symbolic activities. Chronic neurological diseases can cause changes in handedness. This may explain why, unlike systemic immunological diseases, IM neurological diseases are not closely associated with left-handedness. In these patients, the long version of the EHI is appropriate for determining the lateralization of body activities to contextualize the neurological picture; therefore, these findings extend the Italian normative data sets.

Longitudinal microstructural changes in 18 amygdala nuclei resonate with cortical circuits and phenomics

The amygdala nuclei modulate distributed neural circuits that most likely evolved to respond to environmental threats and opportunities. So far, the specific role of unique amygdala nuclei in the context processing of salient environmental cues lacks adequate characterization across neural systems and over time. Here, we present amygdala nuclei morphometry and behavioral findings from longitudinal population data (>1400 subjects, age range 40-69 years, sampled 2-3 years apart): the UK Biobank offers exceptionally rich phenotyping along with brain morphology scans. This allows us to quantify how 18 microanatomical amygdala subregions undergo plastic changes in tandem with coupled neural systems and delineating their associated phenome-wide profiles. In the context of population change, the basal, lateral, accessory basal, and paralaminar nuclei change in lockstep with the prefrontal cortex, a region that subserves planning and decision-making. The central, medial and cortical nuclei are structurally coupled with the insular and anterior-cingulate nodes of the salience network, in addition to the MT/V5, basal ganglia, and putamen, areas proposed to represent internal bodily states and mediate attention to environmental cues. The central nucleus and anterior amygdaloid area are longitudinally tied with the inferior parietal lobule, known for a role in bodily awareness and social attention. These population-level amygdala-brain plasticity regimes in turn are linked with unique collections of phenotypes, ranging from social status and employment to sleep habits and risk taking. The obtained structural plasticity findings motivate hypotheses about the specific functions of distinct amygdala nuclei in humans.

Contributions of the left and right thalami to language: A meta-analytic approach

BACKGROUND

Despite a pervasive cortico-centric view in cognitive neuroscience, subcortical structures including the thalamus have been shown to be increasingly involved in higher cognitive functions. Previous structural and functional imaging studies demonstrated cortico-thalamo-cortical loops which may support various cognitive functions including language. However, large-scale functional connectivity of the thalamus during language tasks has not been examined before.

METHODS

The present study employed meta-analytic connectivity modeling to identify language-related coactivation patterns of the left and right thalami. The left and right thalami were used as regions of interest to search the BrainMap functional database for neuroimaging experiments with healthy participants reporting language-related activations in each region of interest. Activation likelihood estimation analyses were then carried out on the foci extracted from the identified studies to estimate functional convergence for each thalamus. A functional decoding analysis based on the same database was conducted to characterize thalamic contributions to different language functions.

RESULTS

The results revealed bilateral frontotemporal and bilateral subcortical (basal ganglia) coactivation patterns for both the left and right thalami, and also right cerebellar coactivations for the left thalamus, during language processing. In light of previous empirical studies and theoretical frameworks, the present connectivity and functional decoding findings suggest that cortico-subcortical-cerebellar-cortical loops modulate and fine-tune information transfer within the bilateral frontotemporal cortices during language processing, especially during production and semantic operations, but also other language (e.g., syntax, phonology) and cognitive operations (e.g., attention, cognitive control).

CONCLUSION

The current findings show that the language-relevant network extends beyond the classical left perisylvian cortices and spans bilateral cortical, bilateral subcortical (bilateral thalamus, bilateral basal ganglia) and right cerebellar regions.

Electrocardiographic approach strategies in patients with Parkinson disease treated with deep brain stimulation

Deep brain stimulation (DBS) is an interdisciplinary and reversible therapy that uses high-frequency electrical stimulation to correct aberrant neural pathways in motor and cognitive neurological disorders. However, the high frequency of the waves used in DBS can interfere with electrical recording devices (e.g., electrocardiogram, electroencephalogram, cardiac monitor), creating artifacts that hinder their interpretation. The compatibility of DBS with these devices varies and depends on factors such as the underlying disease and the configuration of the neurostimulator. In emergencies where obtaining an electrocardiogram is crucial, the need for more consensus on reducing electrical artifacts in patients with DBS becomes a significant challenge. Various strategies have been proposed to attenuate the artifact generated by DBS, such as changing the DBS configuration from monopolar to bipolar, temporarily deactivating DBS during electrocardiographic recording, applying frequency filters both lower and higher than those used by DBS, and using non-standard leads. However, the inexperience of medical personnel, variability in DBS models, or the lack of a controller at the time of approach limit the application of these strategies. Current evidence on their reproducibility and efficacy is limited. Due to the growing elderly population and the rising utilization of DBS, it is imperative to create electrocardiographic methods that are easily accessible and reproducible for general physicians and emergency services.

Healthy and pathological pallidal regulation of thalamic burst versus tonic mode firing: a computational simulation

The mechanisms by which the basal ganglia influence the pallidal-receiving thalamus remain to be adequately defined. Our prior in vivo recordings in fully alert normal and dystonic rats revealed that normally fast tonic discharging entopeduncular [EP, rodent equivalent of the globus pallidus internus (GPi)] neurons are pathologically slow, highly irregular, and bursty under dystonic conditions. This, in turn, induces pallidal-receiving thalamic movement-related neurons to change from a healthy burst predominant to a pathological tonic-predominant resting firing mode. This study aims to understand the pallidal influence on thalamic firing modes using computational simulations. We inputted various combinations of healthy and pathological (dystonic) in vivo neuronal recordings to the Rubin and Terman's computational model of low threshold spiking pallidothalamic neurons. The input sets consist of representative tonic, burst, irregular tonic and irregular burst inputs collected from EP/GPi in our animal lab. Initial test combinations of EP/ GPi input to the model were identical to the neuronal population distributions observed in vivo. The thalamic neuron model outputted similar firing rate and mode as observed in corresponding in-vivo thalamus. Further influence of each individual patterns was also delineated. By simulating the firing properties of encountered neurons, the basal ganglia output is suggested to critically act as firing mode selector for thalamic motor relay neurons. By selecting and determining the timing and extent of opening of thalamic T-type calcium channels via GABAergic hyperpolarizing input, GPi neurons are in position to precisely orchestrate thalamocortical burst motor signaling.

Omega 3 fatty acid improves sexual and erectile function in BPF-treated rats by upregulating NO/cGMP signaling and steroidogenic enzymes activities

Bisphenol F (BPF) is an environmental pollutant that has been implicated in sexual dysfunction. Omega 3 fatty acid (O3FA), on the other hand, is an antioxidant with the ability to improve fertility indices. However, no study has explored the possible ameliorative effect of O3FA on BPF-induced sexual dysfunction. Thus, the effect of BPF and/or O3FA on male sexual performance was investigated. Male Wistar rats were randomized into 6 groups, corn oil-treated, O3FA low and high dose (100 and 300 mg/kg), BPF-treated, BPF + O3FA low and BPF + O3FA high dose. BPF significantly impaired male sexual competence, evidenced by a reduction in motivation to mate, prolonged mount, intromission and ejaculation latency, and post-ejaculatory index. Furthermore, a reduction in mount, intromission, and ejaculation frequency were observed. Also, BPF caused a decrease in gonadotropin releasing hormone, follicle stimulating hormone, luteinizing hormone, testosterone, nitric oxide (NO) cyclic guanosine monophosphate (cGMP), 3beta-hydroxysteroid dehydrogenase (3β-HSD), 17beta-hydroxysteroid dehydrogenase (17β-HSD), dopamine, and acetylcholine esterase. Furthermore, it was accompanied by a significant increase in prolactin and estrogen and poor pregnancy outcomes. These observed BPF-led alterations were abolished by O3FA administration. This study showed that O3FA ameliorates BPF-induced sexual dysfunction by upregulating NO/cGMP signaling and steroidogenic enzymes activities.

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

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

BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation

Spiking neural networks (SNNs) serve as a promising computational framework for integrating insights from the brain into artificial intelligence (AI). Existing software infrastructures based on SNNs exclusively support brain simulation or brain-inspired AI, but not both simultaneously. To decode the nature of biological intelligence and create AI, we present the brain-inspired cognitive intelligence engine (BrainCog). This SNN-based platform provides essential infrastructure support for developing brain-inspired AI and brain simulation. BrainCog integrates different biological neurons, encoding strategies, learning rules, brain areas, and hardware-software co-design as essential components. Leveraging these user-friendly components, BrainCog incorporates various cognitive functions, including perception and learning, decision-making, knowledge representation and reasoning, motor control, social cognition, and brain structure and function simulations across multiple scales. BORN is an AI engine developed by BrainCog, showcasing seamless integration of BrainCog's components and cognitive functions to build advanced AI models and applications.

A deep network-based model of hippocampal memory functions under normal and Alzheimer's disease conditions

We present a deep network-based model of the associative memory functions of the hippocampus. The proposed network architecture has two key modules: (1) an autoencoder module which represents the forward and backward projections of the cortico-hippocampal projections and (2) a module that computes familiarity of the stimulus and implements hill-climbing over the familiarity which represents the dynamics of the loops within the hippocampus. The proposed network is used in two simulation studies. In the first part of the study, the network is used to simulate image pattern completion by autoassociation under normal conditions. In the second part of the study, the proposed network is extended to a heteroassociative memory and is used to simulate picture naming task in normal and Alzheimer's disease (AD) conditions. The network is trained on pictures and names of digits from 0 to 9. The encoder layer of the network is partly damaged to simulate AD conditions. As in case of AD patients, under moderate damage condition, the network recalls superordinate words ("odd" instead of "nine"). Under severe damage conditions, the network shows a null response ("I don't know"). Neurobiological plausibility of the model is extensively discussed.

A generalized reinforcement learning based deep neural network agent model for diverse cognitive constructs

Human cognition is characterized by a wide range of capabilities including goal-oriented selective attention, distractor suppression, decision making, response inhibition, and working memory. Much research has focused on studying these individual components of cognition in isolation, whereas in several translational applications for cognitive impairment, multiple cognitive functions are altered in a given individual. Hence it is important to study multiple cognitive abilities in the same subject or, in computational terms, model them using a single model. To this end, we propose a unified, reinforcement learning-based agent model comprising of systems for representation, memory, value computation and exploration. We successfully modeled the aforementioned cognitive tasks and show how individual performance can be mapped to model meta-parameters. This model has the potential to serve as a proxy for cognitively impaired conditions, and can be used as a clinical testbench on which therapeutic interventions can be simulated first before delivering to human subjects.

Pallidal neuromodulation of the explore/exploit trade-off in decision-making

Every decision that we make involves a conflict between exploiting our current knowledge of an action's value or exploring alternative courses of action that might lead to a better, or worse outcome. The sub-cortical nuclei that make up the basal ganglia have been proposed as a neural circuit that may contribute to resolving this explore-exploit 'dilemma'. To test this hypothesis, we examined the effects of neuromodulating the basal ganglia's output nucleus, the globus pallidus interna, in patients who had undergone deep brain stimulation (DBS) for isolated dystonia. Neuromodulation enhanced the number of exploratory choices to the lower value option in a two-armed bandit probabilistic reversal-learning task. Enhanced exploration was explained by a reduction in the rate of evidence accumulation (drift rate) in a reinforcement learning drift diffusion model. We estimated the functional connectivity profile between the stimulating DBS electrode and the rest of the brain using a normative functional connectome derived from heathy controls. Variation in the extent of neuromodulation induced exploration between patients was associated with functional connectivity from the stimulation electrode site to a distributed brain functional network. We conclude that the basal ganglia's output nucleus, the globus pallidus interna, can adaptively modify decision choice when faced with the dilemma to explore or exploit.

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

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

Effect of bisphenol F on sexual performance and quality of offspring in Male Wistar rats

This study investigated the effect of BPF on male sexual performance and the quality of the offspring. Eighty (80) Male Wistar rats (n = 10 per group) were randomised into normal saline-treated control and control recovery, BPF varied doses (low, medium, and high), and BPF varied doses recovery (low, medium, and high) groups. The study was terminated after 28 days of BPF oral administration. The animals were sacrificed after 24 h from the last dose, while those in the recovery groups were allowed to recover for another 28 days before being sacrificed. BPF administration was found to impair sexual performance, as shown by a significant decrease in frequencies (mount, intromission, and ejaculation frequencies) and an increase in latencies (mount, intromission, and ejaculation latencies). This was accompanied by a significant decrease in plasma LH, FSH, testosterone, dopamine, acetylcholinesterase, nitric oxide, and penile cyclic guanosine monophosphate (cGMP) level. The level of plasma oestrogen and prolactin were significantly increased following BPF administration. BPF also reduced the sperm count, morphology, viability, and motility. Furthermore, BPF reduced fertility success and index, litter size, litter weight, and offspring survival rate. These toxic effects of BPF were dose-dependent and were not reversed by withdrawal following 28 days of recovery. This study concluded that BPF disrupts sexual competence and offspring quality by suppressing the hypothalamic-pituitary-gonadal axis and mediating oestrogen-induced hyperprolactinemia. These events were associated with reduced fertility index and success, poor semen quality, and reduced offspring survival rate. The observed toxic effects of BPF were dose-dependent and not reversed by cessation of BPF exposure.

Activation, but not inhibition, of the indirect pathway disrupts choice rejection in a freely moving, multiple-choice foraging task

The dorsomedial striatum (DMS) plays a key role in action selection, but less is known about how direct and indirect pathway spiny projection neurons (dSPNs and iSPNs, respectively) contribute to choice rejection in freely moving animals. Here, we use pathway-specific chemogenetic manipulation during a serial choice foraging task to test the role of dSPNs and iSPNs in learned choice rejection. We find that chemogenetic activation, but not inhibition, of iSPNs disrupts rejection of nonrewarded choices, contrary to predictions of a simple "select/suppress" heuristic. Our findings suggest that iSPNs' role in stopping and freezing does not extend in a simple fashion to choice rejection in an ethological, freely moving context. These data may provide insights critical for the successful design of interventions for addiction or other conditions in which it is desirable to strengthen choice rejection.

Neural Phenomenon in Musicality: The Interpretation of Dual-Processing Modes in Melodic Perception

The confluence of creativity in music performance finds itself in performance practices and cultural motifs, the communication of the human body along with the instrument it interacts with, and individual performers' perceptual, motor, and cognitive abilities that contribute to varied musical interpretations of the same piece or melodic line. The musical and artistic execution of a player, as well as the product of this phenomena can become determinant causes in a creative mental state. With advances in neurocognitive measures, the state of one's artistic intuition and execution has been a growing interest in understanding the creative thought process of human behavior, particularly in improvising artists. This article discusses the implementation on the concurrence of spontaneous (Type-1) and controlled (Type-2) processing modes that may be apparent in the perception of non-improvising artists on how melodic lines are perceived in music performance. Elucidating the cortical-subcortical activity in the dual-process model may extend to non-improvising musicians explored in the paradigm of neural correlates. These interactions may open new possibilities for expanding the repertoire of executive functions, creativity, and the coordinated activity of cortical-subcortical regions that regulate the free flow of artistic ideas and expressive spontaneity in future neuromusical research.

Reaching and Grasping Movements in Parkinson's Disease: A Review

Parkinson's disease (PD) is known to affect the brain motor circuits involving the basal ganglia (BG) and to induce, among other signs, general slowness and paucity of movements. In upper limb movements, PD patients show a systematic prolongation of movement duration while maintaining a sufficient level of endpoint accuracy. PD appears to cause impairments not only in movement execution, but also in movement initiation and planning, as revealed by abnormal preparatory activity of motor-related brain areas. Grasping movement is affected as well, particularly in the coordination of the hand aperture with the transport phase. In the last fifty years, numerous behavioral studies attempted to clarify the mechanisms underlying these anomalies, speculating on the plausible role that the BG-thalamo-cortical circuitry may play in normal and pathological motor control. Still, many questions remain open, especially concerning the management of the speed-accuracy tradeoff and the online feedback control. In this review, we summarize the literature results on reaching and grasping in parkinsonian patients. We analyze the relevant hypotheses on the origins of dysfunction, by focusing on the motor control aspects involved in the different movement phases and the corresponding role played by the BG. We conclude with an insight into the innovative stimulation techniques and computational models recently proposed, which might be helpful in further clarifying the mechanisms through which PD affects reaching and grasping movements.

A novel rat robot controlled by electrical stimulation of the nigrostriatal pathway

OBJECTIVE

Artificial manipulation of animal movement could offer interesting advantages and potential applications using the animal's inherited superior sensation and mobility. Although several behavior control models have been introduced, they generally epitomize virtual reward-based training models. In this model, rats are trained multiple times so they can recall the relationship between cues and rewards. It is well known that activation of one side of the nigrostriatal pathway (NSP) in the rat induces immediate turning toward the contralateral side. However, this NSP stimulation-induced directional movement has not been used for the purpose of animal-robot navigation. In this study, the authors aimed to electrically stimulate the NSP of conscious rats to build a command-prompt rat robot.

METHODS

Repetitive NSP stimulation at 1-second intervals was applied via implanted electrodes to induce immediate contraversive turning movements in 7 rats in open field tests in the absence of any sensory cues or rewards. The rats were manipulated to navigate from the start arm to a target zone in either the left or right arm of a T-maze. A leftward trial was followed by a rightward trial, and each rat completed a total of 10 trials. In the control group, 7 rats were tested in the same way without NSP stimulation. The time taken to navigate the maze was compared between experimental and control groups.

RESULTS

All rats in the experimental group successfully reached the target area for all 70 trials in a short period of time with a short interstimulus interval (< 0.7 seconds), but only 41% of rats in the control group reached the target area and required a longer period of time to do so. The experimental group made correct directional turning movements at the intersection zone of the T-maze, taking significantly less time than the control group. No significant difference in navigation duration for the forward movements on the start and goal arms was observed between the two groups. However, the experimental group showed quick and accurate movement at the intersection zone, which made the difference in the success rate and elapsed time of tasks.

CONCLUSIONS

The results of this study clearly indicate that a rat-robot model based on NSP stimulation can be a practical alternative to previously reported models controlled by virtual sensory cues and rewards.

RGS14 Regulation of Post-Synaptic Signaling and Spine Plasticity in Brain

The regulator of G-protein signaling 14 (RGS14) is a multifunctional signaling protein that regulates post synaptic plasticity in neurons. RGS14 is expressed in the brain regions essential for learning, memory, emotion, and stimulus-induced behaviors, including the basal ganglia, limbic system, and cortex. Behaviorally, RGS14 regulates spatial and object memory, female-specific responses to cued fear conditioning, and environmental- and psychostimulant-induced locomotion. At the cellular level, RGS14 acts as a scaffolding protein that integrates G protein, Ras/ERK, and calcium/calmodulin signaling pathways essential for spine plasticity and cell signaling, allowing RGS14 to naturally suppress long-term potentiation (LTP) and structural plasticity in hippocampal area CA2 pyramidal cells. Recent proteomics findings indicate that RGS14 also engages the actomyosin system in the brain, perhaps to impact spine morphogenesis. Of note, RGS14 is also a nucleocytoplasmic shuttling protein, where its role in the nucleus remains uncertain. Balanced nuclear import/export and dendritic spine localization are likely essential for RGS14 neuronal functions as a regulator of synaptic plasticity. Supporting this idea, human genetic variants disrupting RGS14 localization also disrupt RGS14’s effects on plasticity. This review will focus on the known and unexplored roles of RGS14 in cell signaling, physiology, disease and behavior.

Adaptive SNN for Anthropomorphic Finger Control

Anthropomorphic hands that mimic the smoothness of human hand motions should be controlled by artificial units of high biological plausibility. Adaptability is among the characteristics of such control units, which provides the anthropomorphic hand with the ability to learn motions. This paper presents a simple structure of an adaptive spiking neural network implemented in analogue hardware that can be trained using Hebbian learning mechanisms to rotate the metacarpophalangeal joint of a robotic finger towards targeted angle intervals. Being bioinspired, the spiking neural network drives actuators made of shape memory alloy and receives feedback from neuromorphic sensors that convert the joint rotation angle and compression force into the spiking frequency. The adaptive SNN activates independent neural paths that correspond to angle intervals and learns in which of these intervals the rotation the finger rotation is stopped by an external force. Learning occurs when angle-specific neural paths are stimulated concurrently with the supraliminar stimulus that activates all the neurons that inhibit the SNN output stopping the finger. The results showed that after learning, the finger stopped in the angle interval in which the angle-specific neural path was active, without the activation of the supraliminar stimulus. The proposed concept can be used to implement control units for anthropomorphic robots that are able to learn motions unsupervised, based on principles of high biological plausibility.

Characteristics of Multimodal Brain Connectomics in Patients With Schizophrenia and the Unaffected First-Degree Relatives

OBJECTIVE

Increasing pieces of evidence suggest that abnormal brain connectivity plays an important role in the pathophysiology of schizophrenia. As an essential strategy in psychiatric neuroscience, the research of brain connectivity-based neuroimaging biomarkers has gained increasing attention. Most of previous studies focused on a single modality of the brain connectomics. Multimodal evidence will not only depict the full profile of the brain abnormalities of patients but also contribute to our understanding of the neurobiological mechanisms of this disease.

METHODS

In the current study, 99 schizophrenia patients, 69 sex- and education-matched healthy controls, and 42 unaffected first-degree relatives of patients were recruited and scanned. The brain was parcellated into 246 regions and multimodal network analyses were used to construct brain connectivity networks for each participant.

RESULTS

Using the brain connectomics from three modalities as the features, the multi-kernel support vector machine method yielded high discrimination accuracies for schizophrenia patients (94.86%) and for the first-degree relatives (95.33%) from healthy controls. Using an independent sample (49 patients and 122 healthy controls), we tested the model and achieved a classification accuracy of 64.57%. The convergent pattern within the basal ganglia and thalamus-cortex circuit exhibited high discriminative power during classification. Furthermore, substantial overlaps of the brain connectivity abnormality between patients and the unaffected first-degree relatives were observed compared to healthy controls.

CONCLUSION

The current findings demonstrate that decreased functional communications between the basal ganglia, thalamus, and the prefrontal cortex could serve as biomarkers and endophenotypes for schizophrenia.

A global framework for a systemic view of brain modeling

The brain is a complex system, due to the heterogeneity of its structure, the diversity of the functions in which it participates and to its reciprocal relationships with the body and the environment. A systemic description of the brain is presented here, as a contribution to developing a brain theory and as a general framework where specific models in computational neuroscience can be integrated and associated with global information flows and cognitive functions. In an enactive view, this framework integrates the fundamental organization of the brain in sensorimotor loops with the internal and the external worlds, answering four fundamental questions (what, why, where and how). Our survival-oriented definition of behavior gives a prominent role to pavlovian and instrumental conditioning, augmented during phylogeny by the specific contribution of other kinds of learning, related to semantic memory in the posterior cortex, episodic memory in the hippocampus and working memory in the frontal cortex. This framework highlights that responses can be prepared in different ways, from pavlovian reflexes and habitual behavior to deliberations for goal-directed planning and reasoning, and explains that these different kinds of responses coexist, collaborate and compete for the control of behavior. It also lays emphasis on the fact that cognition can be described as a dynamical system of interacting memories, some acting to provide information to others, to replace them when they are not efficient enough, or to help for their improvement. Describing the brain as an architecture of learning systems has also strong implications in Machine Learning. Our biologically informed view of pavlovian and instrumental conditioning can be very precious to revisit classical Reinforcement Learning and provide a basis to ensure really autonomous learning.

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.

Differences in behavior between surface and cave Astyanax mexicanus may be mediated by changes in catecholamine signaling

Astyanax mexicanus is a teleost fish that is in the process of allopatric speciation. Ancestral Astyanax are found in surface rivers and derived blind forms are found in cave systems. Adaptation to life in nutrient poor caves without predation includes the evolution of enhanced food seeking behaviors and loss of defensive responses. These behavioral adaptations may be mediated by changes in catecholaminergic control systems in the brain. We examined the distribution of tyrosine hydroxylase, a conserved precursor for the synthesis of the catecholamines dopamine and noradrenaline, in the brains of surface and cave Astyanax using immunohistochemistry. We found differences in tyrosine hydroxylase staining in regions that are associated with nonvisual sensory perception, motor control, endocrine release, and attention. These differences included significant increases in the diameters of tyrosine hydroxylase immunoreactive soma in cave Astyanax in the olfactory bulb, basal telencephalon, preoptic nuclei, ventral thalamus, posterior tuberculum, and locus coeruleus. These increases in modulation by dopamine and noradrenaline likely indicate changes in behavioral control that underlie adaptations to the cave environment.

Basal ganglia role in learning rewarded actions and executing previously learned choices: Healthy and diseased states

The basal ganglia (BG) is a collection of nuclei located deep beneath the cerebral cortex that is involved in learning and selection of rewarded actions. Here, we analyzed BG mechanisms that enable these functions. We implemented a rate model of a BG-thalamo-cortical loop and simulated its performance in a standard action selection task. We have shown that potentiation of corticostriatal synapses enables learning of a rewarded option. However, these synapses became redundant later as direct connections between prefrontal and premotor cortices (PFC-PMC) were potentiated by Hebbian learning. After we switched the reward to the previously unrewarded option (reversal), the BG was again responsible for switching to the new option. Due to the potentiated direct cortical connections, the system was biased to the previously rewarded choice, and establishing the new choice required a greater number of trials. Guided by physiological research, we then modified our model to reproduce pathological states of mild Parkinson's and Huntington's diseases. We found that in the Parkinsonian state PMC activity levels become extremely variable, which is caused by oscillations arising in the BG-thalamo-cortical loop. The model reproduced severe impairment of learning and predicted that this is caused by these oscillations as well as a reduced reward prediction signal. In the Huntington state, the potentiation of the PFC-PMC connections produced better learning, but altered BG output disrupted expression of the rewarded choices. This resulted in random switching between rewarded and unrewarded choices resembling an exploratory phase that never ended. Along with other computational studies, our results further reconcile the apparent contradiction between the critical involvement of the BG in execution of previously learned actions and yet no impairment of these actions after BG output is ablated by lesions or deep brain stimulation. We predict that the cortico-BG-thalamo-cortical loop conforms to previously learned choice in healthy conditions, but impedes those choices in disease states.

The role of the striatum in visuomotor integration during handwriting: an fMRI study

This study investigates the role of the dorsal/sensorimotor striatum in visuomotor integration (i.e., the transformation of internal visual information about letter shapes into motor output) during handwriting. Twenty healthy participants underwent fMRI scanning with tasks consisting of self-paced handwriting of alphabetically ordered single letters and simple dots, with both tasks performed without visual feedback. Functional connectivity (FC) from these two tasks was compared to demonstrate the difference between coordinated activity arising during handwriting and the activity during a simpler motor condition. Our study focused upon the writing-specific cortico-striatal network of preselected regions of interest consisting of the visual word form area (VWFA), anterior intraparietal sulcus/superior parietal lobule, striatum, premotor cortex/Exner's area, and primary and supplementary motor regions. We observed systematically increased task-induced cortico-striatal and cortico-cortical FC. This increased synchronization of neural activity between the VWFA, i.e., the visual cortical area containing information about letter shapes, and the frontoparietal motor regions is mediated by the striatum. These findings suggest the involvement of the striatum in integrating stored letter-shape information with motor planning and execution during handwriting.

Associations between brain structural networks and neurological soft signs in healthy adults

Neurological soft signs (NSS), as minor neurological deficits, have been identified in several psychiatric disorders, especially in schizophrenia. However, it's unclear how the neuropathological processes of the disease affect NSS related brain morphological changes and whether it is confounded by the use of medication. As NSS also exist in healthy people, the potential confounding effects of psychopathology or medication will be excluded if NSS are investigated in healthy people. Therefore, we applied a novel multivariate approach, source-based morphometry (SBM), to study structural networks in relation to NSS in healthy adults based on structural magnetic resonance imaging (MRI) data. The Heidelberg Scale was applied to evaluate NSS. Using SBM, we constructed structural networks and investigated their associations with NSS in healthy adults. Six grey matter (GM) structural networks were identified. Sensory integration subscores were associated with the cerebellar component and the cortico-basal ganglia-thalamic component. Motor coordination subscores and total NSS scores were associated with the sensorimotor component. The present findings indicated that structural network abnormalities in cerebellar, subcortical and cortical sensorimotor areas contribute to NSS performance in healthy adults.

Bipolar oscillations between positive and negative mood states in a computational model of Basal Ganglia

Bipolar disorder is characterized by mood swings-oscillations between manic and depressive states. The swings (oscillations) mark the length of an episode in a patient's mood cycle (period), and can vary from hours to years. The proposed modeling study uses decision making framework to investigate the role of basal ganglia network in generating bipolar oscillations. In this model, the basal ganglia system performs a two-arm bandit task in which one of the arms (action responses) leads to a positive outcome, while the other leads to a negative outcome. We explore the dynamics of key reward and risk related parameters in the system while the model agent receives various outcomes. Particularly, we study the system using a model that represents the fast dynamics of decision making, and a module to capture the slow dynamics that describe the variation of some meta-parameters of fast dynamics over long time scales. The model is cast at three levels of abstraction: (1) a two-dimensional dynamical system model, that is a simple two variable model capable of showing bistability for rewarding and punitive outcomes; (2) a phenomenological basal ganglia model, to extend the implications from the reduced model to a cortico-basal ganglia setup; (3) a detailed network model of basal ganglia, that incorporates detailed cellular level models for a more realistic understanding. In healthy conditions, the model chooses positive action and avoids negative one, whereas under bipolar conditions, the model exhibits slow oscillations in its choice of positive or negative outcomes, reminiscent of bipolar oscillations. Phase-plane analyses on the simple reduced dynamical system with two variables reveal the essential parameters that generate pathological 'bipolar-like' oscillations. Phenomenological and network models of the basal ganglia extend that logic, and interpret bipolar oscillations in terms of the activity of dopaminergic and serotonergic projections on the cortico-basal ganglia network dynamics. The network's dysfunction, specifically in terms of reward and risk sensitivity, is shown to be responsible for the pathological bipolar oscillations. The study proposes a computational model that explores the effects of impaired serotonergic neuromodulation on the dynamics of the cortico basal ganglia network, and relates this impairment to abstract mood states (manic and depressive episodes) and oscillations of bipolar disorder.

A theory of consciousness: computation, algorithm, and neurobiological realization

The most enigmatic aspect of consciousness is the fact that it is felt, as a subjective sensation. The theory proposed here aims to explain this particular aspect. The theory encompasses both the computation that is presumably involved and the way in which that computation may be realized in the brain's neurobiology. It is assumed that the brain makes an internal estimate of an individual's own evolutionary fitness, which can be shown to produce a special, distinct form of causation. Communicating components of the fitness estimate (either for external or for internal use) requires inverting them. Such inversion can be performed by the thalamocortical feedback loop in the mammalian brain, if that loop is operating in a switched, dual-stage mode. A first (nonconscious) stage produces forward estimates, whereas the second (conscious) stage inverts those estimates. It is argued that inversion produces another special, distinct form of causation, which is spatially localized and is plausibly sensed as the feeling of consciousness.

How Long Is Too Long: An Individual Time-Window for Motor Planning

Human motor response time (RT) is determined by the matureness of the preceding neural motor planning process. In the current study, we characterize the temporal boundaries required for the motor planning process, and its impact on the overall motor RT. In particular, we contrasted short and long planning times by measuring the resulting differences in motor RTs, in an attempt to find whether an optimal planning time for minimal RT exists. Using a "Timed Response" paradigm, we presented participants with varying planning intervals prior to a requested motor response and studied their effect on the timing of initiation of the following movement. We found that, as expected, reaction time shortens as more planning time is provided, yet only until reaching a minimal RT, after which additional planning time increases the motor RT, thus creating a U-shaped behavioral function. Furthermore, since the minimal RT was found to be an individual characteristic, we suggest that there is an individual time window for motor planning.

PET imaging on neurofunctional changes after optogenetic stimulation in a rat model of panic disorder

Panic disorder (PD) is an acute paroxysmal anxiety disorder with poorly understood pathophysiology. The dorsal periaqueductal gray (dPAG) is involved in the genesis of PD. However, the downstream neurofunctional changes of the dPAG during panic attacks have yet to be evaluated in vivo. In this study, optogenetic stimulation to the dPAG was performed to induce panic-like behaviors, and in vivo positron emission tomography (PET) imaging with ¹⁸F-flurodeoxyglucose (¹⁸F-FDG) was conducted to evaluate neurofunctional changes before and after the optogenetic stimulation. Compared with the baseline, post-optogenetic stimulation PET imaging demonstrated that the glucose metabolism significantly increased (P < 0.001) in dPAG, the cuneiform nucleus, the cerebellar lobule, the cingulate cortex, the alveus of the hippocampus, the primary visual cortex, the septohypothalamic nucleus, and the retrosplenial granular cortex but significantly decreased (P < 0.001) in the basal ganglia, the frontal cortex, the forceps minor corpus callosum, the primary somatosensory cortex, the primary motor cortex, the secondary visual cortex, and the dorsal lateral geniculate nucleus. Taken together, these data indicated that in vivo PET imaging can successfully detect downstream neurofunctional changes involved in the panic attacks after optogenetic stimulation to the dPAG.

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.

Motor dysfunction as research domain across bipolar, obsessive-compulsive and neurodevelopmental disorders

Although genuine motor abnormalities (GMA) are frequently found in schizophrenia, they are also considered as an intrinsic feature of bipolar, obsessive-compulsive, and neurodevelopmental disorders with early onset such as autism, ADHD, and Tourette syndrome. Such transnosological observations strongly suggest a common neural pathophysiology. This systematic review highlights the evidence on GMA and their neuroanatomical substrates in bipolar, obsessive-compulsive, and neurodevelopmental disorders. The data lends support for a common pattern contributing to GMA expression in these diseases that seems to be related to cerebello-thalamo-cortical, fronto-parietal, and cortico-subcortical motor circuit dysfunction. The identified studies provide first evidence for a motor network dysfunction as a correlate of early neurodevelopmental deviance prior to clinical symptom expression. There are also first hints for a developmental risk factor model of these mental disorders. An in-depth analysis of motor networks and related patho-(physiological) mechanisms will not only help promoting Research Domain Criteria (RDoC) Motor System construct, but also facilitate the development of novel psychopharmacological models, as well as the identification of neurobiologically plausible target sites for non-invasive brain stimulation.

Theta Neurofeedback Effects on Motor Memory Consolidation and Performance Accuracy: An Apparent Paradox?

Previous studies have shown that theta neurofeedback enhances motor memory consolidation on an easy-to-learn finger-tapping task. However, the simplicity of the finger-tapping task precludes evaluating the putative effects of elevated theta on performance accuracy. Mastering a motor sequence is classically assumed to entail faster performance with fewer errors. The speed-accuracy tradeoff (SAT) principle states that as action speed increases, motor performance accuracy decreases. The current study investigated whether theta neurofeedback could improve both performance speed and performance accuracy, or would only enhance performance speed at the cost of reduced accuracy. A more complex task was used to study the effects of parietal elevated theta on 45 healthy volunteers The findings confirmed previous results on the effects of theta neurofeedback on memory consolidation. In contrast to the two control groups, in the theta-neurofeedback group the speed-accuracy tradeoff was reversed. The speed-accuracy tradeoff patterns only stabilized after a night's sleep implying enhancement in terms of both speed and accuracy.

Interactions of spatial strategies producing generalization gradient and blocking: A computational approach

We present a computational model of spatial navigation comprising different learning mechanisms in mammals, i.e., associative, cognitive mapping and parallel systems. This model is able to reproduce a large number of experimental results in different variants of the Morris water maze task, including standard associative phenomena (spatial generalization gradient and blocking), as well as navigation based on cognitive mapping. Furthermore, we show that competitive and cooperative patterns between different navigation strategies in the model allow to explain previous apparently contradictory results supporting either associative or cognitive mechanisms for spatial learning. The key computational mechanism to reconcile experimental results showing different influences of distal and proximal cues on the behavior, different learning times, and different abilities of individuals to alternatively perform spatial and response strategies, relies in the dynamic coordination of navigation strategies, whose performance is evaluated online with a common currency through a modular approach. We provide a set of concrete experimental predictions to further test the computational model. Overall, this computational work sheds new light on inter-individual differences in navigation learning, and provides a formal and mechanistic approach to test various theories of spatial cognition in mammals.

A system-level mathematical model of Basal Ganglia motor-circuit for kinematic planning of arm movements

In this paper, a novel system-level mathematical model of the Basal Ganglia (BG) for kinematic planning, is proposed. An arm composed of several segments presents a geometric redundancy. Thus, selecting one trajectory among an infinite number of possible ones requires overcoming redundancy, according to some kinds of optimization. Solving this optimization is assumed to be the function of BG in planning. In the proposed model, first, a mathematical solution of kinematic planning is proposed for movements of a redundant arm in a plane, based on minimizing energy consumption. Next, the function of each part in the model is interpreted as a possible role of a nucleus of BG. Since the kinematic variables are considered as vectors, the proposed model is presented based on the vector calculus. This vector model predicts different neuronal populations in BG which is in accordance with some recent experimental studies. According to the proposed model, the function of the direct pathway is to calculate the necessary rotation of each joint, and the function of the indirect pathway is to control each joint rotation considering the movement of the other joints. In the proposed model, the local feedback loop between Subthalamic Nucleus and Globus Pallidus externus is interpreted as a local memory to store the previous amounts of movements of the other joints, which are utilized by the indirect pathway. In this model, activities of dopaminergic neurons would encode, at short-term, the error between the desired and actual positions of the end-effector. The short-term modulating effect of dopamine on Striatum is also modeled as cross product. The model is simulated to generate the commands of a redundant manipulator. The performance of the model is studied for different reaching movements between 8 points in a plane. Finally, some symptoms of Parkinson's disease such as bradykinesia and akinesia are simulated by modifying the model parameters, inspired by the dopamine depletion.