A computational model elucidating mechanisms and variability in theta burst stimulation responses.

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Journal of Computational Neuroscience Pub Date : 2024-08-01 Epub Date: 2024-08-09 DOI:10.1007/s10827-024-00875-1
Mohammadreza Vasheghani Farahani, Seyed Peyman Shariatpanahi, Bahram Goliaei
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Abstract

Theta burst stimulation (TBS) is a form of repetitive transcranial magnetic stimulation (rTMS) with unknown underlying mechanisms and highly variable responses across subjects. To investigate these issues, we developed a simple computational model. Our model consisted of two neurons linked by an excitatory synapse that incorporates two mechanisms: short-term plasticity (STP) and spike-timing-dependent plasticity (STDP). We applied a variable-amplitude current through I-clamp with a TBS time pattern to the pre- and post-synaptic neurons, simulating synaptic plasticity. We analyzed the results and provided an explanation for the effects of TBS, as well as the variability of responses to it. Our findings suggest that the interplay of STP and STDP mechanisms determines the direction of plasticity, which selectively affects synapses in extended neurons and underlies functional effects. Our model describes how the timing, number, and intensity of pulses delivered to neurons during rTMS contribute to induced plasticity. This not only successfully explains the different effects of intermittent TBS (iTBS) and continuous TBS (cTBS), but also predicts the results of other protocols such as 10 Hz rTMS. We propose that the variability in responses to TBS can be attributed to the variable span of neuronal thresholds across individuals and sessions. Our model suggests a biologically plausible mechanism for the diverse responses to TBS protocols and aligns with experimental data on iTBS and cTBS outcomes. This model could potentially aid in improving TBS and rTMS protocols and customizing treatments for patients, brain areas, and brain disorders.

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阐明θ猝发刺激反应机制和可变性的计算模型。
Theta 脉冲串刺激(TBS)是一种重复经颅磁刺激(rTMS),其潜在机制不明,不同受试者的反应差异很大。为了研究这些问题,我们开发了一个简单的计算模型。我们的模型由两个神经元组成,两个神经元通过兴奋性突触相连,突触包含两种机制:短期可塑性(STP)和尖峰计时可塑性(STDP)。我们通过具有 TBS 时间模式的 I 型钳向突触前后神经元施加可变振幅电流,模拟突触可塑性。我们对结果进行了分析,并解释了 TBS 的影响以及对其反应的可变性。我们的研究结果表明,STP 和 STDP 机制的相互作用决定了可塑性的方向,可选择性地影响扩展神经元的突触,并成为功能效应的基础。我们的模型描述了经颅磁刺激过程中传递给神经元的脉冲的时间、数量和强度是如何促成可塑性的。这不仅成功解释了间歇性经颅磁刺激(iTBS)和连续性经颅磁刺激(cTBS)的不同效果,还预测了其他方案(如 10 赫兹经颅磁刺激)的结果。我们提出,对 TBS 反应的可变性可归因于不同个体和疗程中神经元阈值的可变跨度。我们的模型为 TBS 方案的不同反应提出了一种生物学上合理的机制,并与 iTBS 和 cTBS 结果的实验数据相一致。该模型可能有助于改进 TBS 和经颅磁刺激方案,并为患者、脑区和脑部疾病定制治疗方案。
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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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