ArticleComputational intelligence and neuroscience2015
A Biologically Inspired Computational Model of Basal Ganglia in Action Selection.
Article in Computational intelligence and neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- A Mechanistic Understanding of the Different Factors Affecting Adaptation and Flexibility During Probabilistic Reversal Learning: A Neurocomputational Study on Patients with Parkinson's Disease and Control Subjects.Annals of biomedical engineering · 2026Article
- A TAN-dopamine interaction mechanism based computational model of basal ganglia in action selection.Cognitive neurodynamics · 2024Article
- Feasibility of dopamine as a vector-valued feedback signal in the basal ganglia.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- A model of working memory for encoding multiple items and ordered sequences exploiting the theta-gamma code.Cognitive neurodynamics · 2023Article
- Evolving characterization of the human hyperdirect pathway.Brain structure & function · 2023Review
- Phasic Dopamine Changes and Hebbian Mechanisms during Probabilistic Reversal Learning in Striatal Circuits: A Computational Study.International journal of molecular sciences · 2022Article
- Coarse-Grained Neural Network Model of the Basal Ganglia to Simulate Reinforcement Learning Tasks.Brain sciences · 2022Article
- A mechanistic model of ADHD as resulting from dopamine phasic/tonic imbalance during reinforcement learning.Frontiers in computational neuroscience · 2022Article
- An integrative model of Parkinson's disease treatment including levodopa pharmacokinetics, dopamine kinetics, basal ganglia neurotransmission and motor action throughout disease progression.Journal of pharmacokinetics and pharmacodynamics · 2021Article
- Response Systems, Antagonistic Responses, and the Behavioral Repertoire.Frontiers in behavioral neuroscience · 2021Article
- Mathematical modeling and parameter estimation of levodopa motor response in patients with parkinson disease.PloS one · 2020Article
- A Brain-Inspired Decision-Making Spiking Neural Network and Its Application in Unmanned Aerial Vehicle.Frontiers in neurorobotics · 2018Article
- Effects of Levodopa on Postural Strategies in Parkinson's disease.Gait & posture · 2016Article
- A Mathematical Model of Levodopa Medication Effect on Basal Ganglia in Parkinson's Disease: An Application to the Alternate Finger Tapping Task.Frontiers in human neuroscience · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.