伏隔核建模:从单细胞到回路水平的计算模型。

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Journal of Computational Neuroscience Pub Date : 2021-02-01 Epub Date: 2020-11-09 DOI:10.1007/s10827-020-00769-y
Rahmi Elibol, Neslihan Serap Şengör
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引用次数: 0

摘要

伏隔核是基于奖励的学习和动机的认知处理所需的神经结构的一部分。了解其细胞动力学及其在基底神经节回路中的作用不仅对诊断成瘾和抑郁等行为障碍和精神问题很重要,而且对开发治疗方法也很重要。建立一个计算模型将扩大我们对伏隔核的理解。在这项工作中,我们的重点是建立一个伏隔核模型,这在计算神经科学中没有像背纹状体那样被考虑得那么多。我们将从单个细胞的行为建模开始,然后考虑突触电流的影响,建立伏隔核的整体模型。我们将通过显示模拟结果与经验数据的一致性来验证模型的有效性。此外,模拟结果揭示了皮质刺激和多巴胺能调节对中棘神经元活动的联合作用。这种效应与多巴胺受体的类型不同。
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Modeling nucleus accumbens : A Computational Model from Single Cell to Circuit Level.

Nucleus accumbens is part of the neural structures required for reward based learning and cognitive processing of motivation. Understanding its cellular dynamics and its role in basal ganglia circuits is important not only in diagnosing behavioral disorders and psychiatric problems as addiction and depression but also for developing therapeutic treatments for them. Building a computational model would expand our comprehension of nucleus accumbens. In this work, we are focusing on establishing a model of nucleus accumbens which has not been considered as much as dorsal striatum in computational neuroscience. We will begin by modeling the behavior of single cells and then build a holistic model of nucleus accumbens considering the effect of synaptic currents. We will verify the validity of the model by showing the consistency of simulation results with the empirical data. Furthermore, the simulation results reveal the joint effect of cortical stimulation and dopaminergic modulation on the activity of medium spiny neurons. This effect differentiates with the type of dopamine receptors.

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来源期刊
CiteScore
2.00
自引率
8.30%
发文量
32
审稿时长
3 months
期刊介绍: The Journal of Computational Neuroscience provides a forum for papers that fit the interface between computational and experimental work in the neurosciences. The Journal of Computational Neuroscience publishes full length original papers, rapid communications and review articles describing theoretical and experimental work relevant to computations in the brain and nervous system. Papers that combine theoretical and experimental work are especially encouraged. Primarily theoretical papers should deal with issues of obvious relevance to biological nervous systems. Experimental papers should have implications for the computational function of the nervous system, and may report results using any of a variety of approaches including anatomy, electrophysiology, biophysics, imaging, and molecular biology. Papers investigating the physiological mechanisms underlying pathologies of the nervous system, or papers that report novel technologies of interest to researchers in computational neuroscience, including advances in neural data analysis methods yielding insights into the function of the nervous system, are also welcomed (in this case, methodological papers should include an application of the new method, exemplifying the insights that it yields).It is anticipated that all levels of analysis from cognitive to cellular will be represented in the Journal of Computational Neuroscience.
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