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一种用于动作选择的受生物启发的基底神经节计算模型。

A Biologically Inspired Computational Model of Basal Ganglia in Action Selection.

作者信息

Baston Chiara, Ursino Mauro

机构信息

Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy.

出版信息

Comput Intell Neurosci. 2015;2015:187417. doi: 10.1155/2015/187417. Epub 2015 Nov 10.

DOI:10.1155/2015/187417
PMID:26640481
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4657096/
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.

摘要

基底神经节(BG)是一种与动作选择有关的皮质下结构。这项工作的目的是提出一种新的基底神经节认知神经科学模型,该模型力求在简单性和完整性之间实现简约的平衡。该模型包括基底神经节回路中运作的3条主要通路,即直接(Go)通路、间接(NoGo)通路和超直接通路。与先前模型相比,主要的创新点在于使用双项赫布规则来训练纹状体中的突触,该规则完全基于多巴胺峰值或谷值引起的神经元活动变化,以及胆碱能中间神经元(其自身受多巴胺影响)在学习过程中的作用。展示了一些关于几个典型案例的示例:基础条件下的动作选择、存在强烈冲突时的动作选择(此时超直接通路的作用显现)、相位多巴胺诱导的突触变化,以及基于先前奖惩历史学习新动作。最后,一些模拟展示了模型在多巴胺水平改变的条件下的运作情况,以说明病理案例(帕金森病患者的多巴胺耗竭或多巴胺用药过量)。由于其简约的方法,该模型可能是行为实验中分析基底神经节功能的一种直接工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79d1/4657096/a2ca265f5a9c/CIN2015-187417.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79d1/4657096/2bc08665b733/CIN2015-187417.001.jpg
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本文引用的文献

1
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2
The subthalamic nucleus, oscillations, and conflict.底丘脑核、振荡与冲突。
Mov Disord. 2015 Mar;30(3):328-38. doi: 10.1002/mds.26072. Epub 2015 Feb 17.
3
Direct and indirect pathways of basal ganglia: a critical reappraisal.基底神经节的直接和间接通路:批判性再评价。
一种利用θ-γ编码对多个项目和有序序列进行编码的工作记忆模型。
Cogn Neurodyn. 2023 Apr;17(2):489-521. doi: 10.1007/s11571-022-09836-9. Epub 2022 Jul 16.
4
Evolving characterization of the human hyperdirect pathway.人类超直接通路的不断演变的特征描述。
Brain Struct Funct. 2023 Mar;228(2):353-365. doi: 10.1007/s00429-023-02610-5. Epub 2023 Jan 28.
5
A mechanistic model of ADHD as resulting from dopamine phasic/tonic imbalance during reinforcement learning.一种将注意力缺陷多动障碍(ADHD)归因于强化学习过程中多巴胺相位/张力失衡的机制模型。
Front Comput Neurosci. 2022 Jul 18;16:849323. doi: 10.3389/fncom.2022.849323. eCollection 2022.
6
Phasic Dopamine Changes and Hebbian Mechanisms during Probabilistic Reversal Learning in Striatal Circuits: A Computational Study.纹状体回路中概率反转学习期间的相位多巴胺变化和赫布机制:一项计算研究。
Int J Mol Sci. 2022 Mar 22;23(7):3452. doi: 10.3390/ijms23073452.
7
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Brain Sci. 2022 Feb 14;12(2):262. doi: 10.3390/brainsci12020262.
8
Response Systems, Antagonistic Responses, and the Behavioral Repertoire.反应系统、拮抗反应与行为 repertoire
Front Behav Neurosci. 2022 Jan 13;15:778420. doi: 10.3389/fnbeh.2021.778420. eCollection 2021.
9
Mathematical modeling and parameter estimation of levodopa motor response in patients with parkinson disease.帕金森病患者左旋多巴运动反应的数学建模和参数估计。
PLoS One. 2020 Mar 3;15(3):e0229729. doi: 10.1371/journal.pone.0229729. eCollection 2020.
10
A Brain-Inspired Decision-Making Spiking Neural Network and Its Application in Unmanned Aerial Vehicle.一种受脑启发的决策脉冲神经网络及其在无人机中的应用。
Front Neurorobot. 2018 Sep 11;12:56. doi: 10.3389/fnbot.2018.00056. eCollection 2018.
Nat Neurosci. 2014 Aug;17(8):1022-30. doi: 10.1038/nn.3743. Epub 2014 Jul 28.
4
Multiphasic modulation of cholinergic interneurons by nigrostriatal afferents.黑质纹状体传入对胆碱能中间神经元的多相调制。
J Neurosci. 2014 Jun 18;34(25):8557-69. doi: 10.1523/JNEUROSCI.0589-14.2014.
5
Inhibition, executive function, and freezing of gait.抑制、执行功能与步态冻结。
J Parkinsons Dis. 2014;4(1):111-22. doi: 10.3233/JPD-130221.
6
Computational models of basal-ganglia pathway functions: focus on functional neuroanatomy.基底神经节通路功能的计算模型:聚焦于功能神经解剖学。
Front Syst Neurosci. 2013 Dec 30;7:122. doi: 10.3389/fnsys.2013.00122.
7
Exploring the cognitive and motor functions of the basal ganglia: an integrative review of computational cognitive neuroscience models.探索基底神经节的认知和运动功能:计算认知神经科学模型的综合综述。
Front Comput Neurosci. 2013 Dec 6;7:174. doi: 10.3389/fncom.2013.00174.
8
Dysfunctional and compensatory synaptic plasticity in Parkinson's disease.帕金森病中的功能障碍和代偿性突触可塑性。
Eur J Neurosci. 2014 Feb;39(4):688-702. doi: 10.1111/ejn.12434. Epub 2013 Dec 9.
9
A computational model of inhibitory control in frontal cortex and basal ganglia.前额皮质和基底神经节抑制控制的计算模型。
Psychol Rev. 2013 Apr;120(2):329-55. doi: 10.1037/a0031542.
10
A spiking neuron model of the cortico-basal ganglia circuits for goal-directed and habitual action learning.用于目标导向和习惯动作学习的皮质基底神经节电路的尖峰神经元模型。
Neural Netw. 2013 May;41:212-24. doi: 10.1016/j.neunet.2012.11.009. Epub 2012 Dec 5.