A mathematical model of levodopa medication effect on basal ganglia in parkinson’s disease: An application to the alternate finger tapping task

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

Aberrant learning in Parkinson's disease: A neurocomputational study on bradykinesia

Parkinson's disease (PD) is a neurodegenerative disorder characterized by a progressive decline in motor functions, such as bradykinesia, caused by the pathological denervation of nigrostriatal dopaminergic neurons within the basal ganglia (BG). It is acknowledged that dopamine (DA) directly affects the modulatory role of BG towards the cortex. However, a growing body of literature is suggesting that DA-induced aberrant synaptic plasticity could play a role in the core symptoms of PD, thus recalling for a \u201creconceptualization\u201d of the pathophysiology. The aim of this work was to investigate DA-driven aberrant learning as a concurrent cause of bradykinesia, using a comprehensive, biologically inspired neurocomputational model of action selection in the BG. The model includes the three main pathways operating in the BG circuitry, that is the direct, indirect and hyperdirect pathways, and use a two-term Hebb rule to train synapses in the striatum, based on previous history of rewards and punishments. Levodopa pharmacodynamics is also incorporated. Through model simulations of the Alternate Finger Tapping motor task, we assessed the role of aberrant learning on bradykinesia. The results show that training under drug medication (levodopa) provides not only immediate but also delayed benefit lasting in time. Conversely, if performed in conditions of vanishing levodopa efficacy, training may result in dysfunctional corticostriatal synaptic plasticity, further worsening motor performances in PD subjects. This suggests that bradykinesia may result from the concurrent effects of low DA levels and dysfunctional plasticity and that training can be exploited in medicated subjects to improve levodopa treatment

A Biologically Inspired Computational Model of Basal Ganglia in Action Selection

The basal ganglia (BG) are a subcortical structure implicated in action selection. The aim of this work is to present a new cognitive neuroscience model of the BG, which aspires to represent a parsimonious balance between simplicity and completeness. The model includes the 3 main pathways operating in the BG circuitry, that is, the direct (Go), indirect (NoGo), and hyperdirect pathways. The main original aspects, compared with previous models, are the use of a two-term Hebb rule to train synapses in the striatum, based exclusively on neuronal activity changes caused by dopamine peaks or dips, and the role of the cholinergic interneurons (affected by dopamine themselves) during learning. Some examples are displayed, concerning a few paradigmatic cases: action selection in basal conditions, action selection in the presence of a strong conflict (where the role of the hyperdirect pathway emerges), synapse changes induced by phasic dopamine, and learning new actions based on a previous history of rewards and punishments. Finally, some simulations show model working in conditions of altered dopamine levels, to illustrate pathological cases (dopamine depletion in parkinsonian subjects or dopamine hypermedication). Due to its parsimonious approach, the model may represent a straightforward tool to analyze BG functionality in behavioral experiments

A neurocomputational model of dopamine dependent finger tapping task

One of the main disabling features of Parkinson's disease (PD) is bradykinesia. Usually, bradykinesia is clinically assessed through the performance of an extremely simple motor task: the finger tapping task. This motor test correlates with the extent of loss of dopaminergic neurons in the substantia nigra, which is responsible for the triggering of Parkinson's disease (PD) and for the subsequent lack of dopamine (DA) typical of the disease. Therefore, this simple task provides useful information on the state and on the progression of PD. The present study aims at quantifying the connection between DA levels and finger tapping performances by means of a biologically inspired neurocomputational model, which investigates in detail the neural circuitry altered in PD and links the observed output (the finger tapping performance) to the different DA levels included in the model

A computational model of Dopamine and Acetylcholine aberrant learning in Basal Ganglia

Basal Ganglia (BG) are implied in many motor and cognitive tasks, such as action selection, and have a central role in many pathologies, primarily Parkinson Disease. In the present work, we use a recently developed biologically inspired BG model to analyze how the dopamine (DA) level can affect the temporal response during action selection, and the capacity to learn new actions following rewards and punishments. The model incorporates the 3 main pathways (direct, indirect and hyperdirect) working in BG functioning. The behavior of 2 alternative networks (the first with normal DA levels, the second with reduced DA) is analyzed both in untrained conditions, and during training performed in different epochs. The results show that reduced DA causes delayed temporal responses in the untrained network, and difficult of learning during training, characterized by the necessity of much more epochs. The results provide interesting hints to understand the behavior of healthy and dopamine depleted subjects, such as parkinsonian patients

No difference in return to amateur sports after medial and lateral unicompartmental knee arthroplasty in patients younger than 65 years

Purpose: The aim of this study was to assess the return to amateur sports of patients under 65 years, following medial unicompartmental knee arthroplasty (mUKA) versus lateral unicompartmental knee arthroplasty (lUKA). It was hypothesized that patients younger than 65 years who underwent lateral or medial unicondylar knee replacement will result in similar rates to amateur sports, at a minimum follow-up of 2 years. Method: Patients who underwent medial or lateral UKA participated in a 2-year follow-up program, where they were clinically evaluated for their return to amateur sports, using the University of California, Los Angeles (UCLA) activity scale and the High-Activity Arthroplasty Score (HAAS). Furthermore, subgroup analyses by gender and age were performed. Power analysis was performed to ensure sample size considering that lUKA is implanted ten times less frequently than its medial counterpart. Results: There were 85 patients who completed the entire minimum 2-year follow-up of which 73 belonged to the mUKA group and 12 to the lUKA group. No preoperative differences were found between the groups regarding the gender, the affected side, age, and mean follow-up. Both groups showed statistically significant improvement (p < 0.05) in their return to amateur sports in all parameters (UCLA and HAAS). No differences among the two groups were found at T 0 and T 1 (n.s.) . All subgroups showed a statistically significant improvement (p < 0.05) with respect to the preoperative value, except for UCLA for lUKA with less than 60 years and HAAS for males in the lUKA group (n.s.). No differences were found among subgroups both at T o and T 1 (n.s.). Conclusion: Both mUKA and lUKA procedures enabled all young and active patients a certain return to amateur sports 2 years after surgery, regardless of age and gender. UKA, medial or lateral, should always be considered for the treatment of isolated osteoarthritis in young and active patients with high functional demands. Level of evidence: Cohort Study, Level of Evidence III. Registration: Researchregistry6221 – Research Registry www.researchregistry.com

Low STING expression in a transplantable KrasG12D/P53ko lung cancer model contributes to SiglecF+ neutrophil and CD103+Treg accumulation in tumors

Lung cancer is the leading cause of mortality by cancer worldwide. Non-small cell lung cancer is the most common type of lung cancer and mutations in the KRAS gene are frequently found in this pathology. While immune checkpoint inhibitors are providing new hope for lung cancer care, only a subset of patients show durable benefit from these new therapies designed to drive an efficient anti-tumor immune response. Hence, it is crucial to better understand the mechanisms through which the tumor immune microenvironment is established in lung tumors. Using bioinformatics, we observed that high expression of the STimulator of INterferon Gene (STING) associates with a longer overall survival specifically in KRAS mutant cancer patients. In lung cancer cell lines, STING expression is linked to interferon response and epithelial-to-mesenchymal transition. Because STING activation in immune cells of the tumor microenvironment using specific agonists is an emerging strategy to trigger an anti-tumor immune response, we took advantage of two transplantable models of Kras driven lung cancer, expressing high or low levels of STING, to investigate the function of STING directly in cancer cells in vivo. We observed that high-STING expression and constitutive STING signaling were critical for transplanted tumor formation rather than playing a major role in tumor immunogenicity. Besides, low-STING expression in cancer cells is associated with an immunosuppressive tumor microenvironment characterized by the accumulation of tumor promoting SiglecF+ neutrophils and CD103+ regulatory T cells. In that model, knocking out STING increased the early response to anti-PD1 treatment. We conclude that low-STING expression in cancer cells might confer them an independence from pro-inflammatory signals and a greater immunosuppressive capability and aggressiveness

The baroreflex contribution to spontaneous heart rhythm assessed with a mathematical model in rats

In Spontaneously Hypertensive (SHR) and Wistar–Kyoto (WKY) normotensive rats, we quantified the extent to which spontaneous fluctuations of heart period (HP) may be determined from arterial pressure based on linear baroreflex properties.We analyzed time series (30-s length) of low-frequency (b0.8 Hz) fluctuations of HP and mean arterial pressure obtained during quiet wakefulness, rapid-eye-movement sleep (REMS) and non-rapid-eye-movement sleep (NREMS) as well as a control set of surrogate isospectral data with random phase. HP was modeled as the summed output of two parallel linear transfer functions with arterial pressure as input. The mean square difference between modeled and recorded HP was minimized by varying model parameters. The percentage of time series, in which such difference was lower than half the measured HP variance was significantly lower in REMS (6±1%, SHR; 5±1%, WKY) than either in quiet wakefulness (25±2%, SHR; 35±3%, WKY) or NREMS (33±3%, SHR; 27±3%, WKY), and in quiet wakefulness, it was significantly lower in SHR than inWKY. In surrogate data, these percentages were significantly lower than in recorded data during quiet wakefulness and NREMS, but not during REMS. The extent to which linear baroreflex properties explain spontaneous heart rhythm thus depends on the interaction between the behavioral state and the hypertensive disease, and in REMS, may be accounted for by chance couplings between HP and arterial pressure