Neural mass modelling of brain stimulation to Alleviate Schizophrenia biomarkers in brain rhythms

IF 7 2区 医学 Q1 BIOLOGY
Swapna Sasi , Basabdatta Sen Bhattacharya , Vanteemar S. Sreeraj , Ganesan Venkatasubramanian
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Abstract

We present a neural mass model (NMM) of the brain thalamo-cortico-thalamic (TCT) network to understand the effectiveness of non-invasive treatment with transcranial Direct Current Stimulation (tDCS) in reversing the anomalous electroencephalogram (EEG) oscillations in Schizophrenia. Our TCT NMM consists of twelve neural populations representing the thalamus and cortex modules of the visual pathway connected in a closed loop; the synaptic pathways are modelled with a 3-state kinetic framework allowing the inclusion of the slow excitatory N-methyl-D-aspartate-receptors (NMDAR). Indeed, a popular hypothesis in Schizophrenia is the hypofunction of the Glutamatergic neurotransmitter receptors, NMDAR, associated with the inhibitory Gamma-amino-butyric-acid (GABA-)ergic populations in the cortex, leading to anomalous brain oscillations. Experimental studies simulate the EEG conditions in Schizophrenia by administering sub-anesthetic dosage of Ketamine, which blocks NMDAR channels at the Magnesium binding sites. We could simulate the Ketamine-induced NMDAR channel blocking by varying the Magnesium concentration in the 3-state synaptic models of appropriate pathways. Our results show Ketamine-induced increased excitatory behaviour in the model output; the changes in the γ and σ band oscillations conform to experimental studies. A model to factor in the neuroplasticity effects of applying tDCS (after (Riedinger and Hutt, 2022)) is interfaced with the TCT NMM. Informed by experimental literature, the simulated extrinsic current induced by tDCS is set to affect the plasticity in selected pathways. With appropriate parameterisation, we could simulate the reversal of the Ketamine-induced altered EEG oscillations. Overall, our in silico study emphasises the potential of NMM in predicting protocols for tDCS towards effective personalised treatment of Schizophrenia.
脑刺激减轻脑节律中精神分裂症生物标志物的神经质量模型
我们提出了脑丘脑-皮质-丘脑(TCT)网络的神经团块模型(NMM),以了解经颅直流电刺激(tDCS)非侵入性治疗在逆转精神分裂症异常脑电图(EEG)振荡方面的有效性。我们的TCT NMM由十二个神经群组成,这些神经群代表视觉通路的丘脑和皮层模块,它们以闭环连接;突触通路用三态动力学框架建模,允许包含慢兴奋性n -甲基- d -天冬氨酸受体(NMDAR)。事实上,精神分裂症中一个流行的假说是谷氨酸能神经递质受体(NMDAR)功能低下,与皮层中抑制性γ -氨基丁酸(GABA-)能群相关,导致异常的大脑振荡。实验研究通过给予亚麻醉剂量的氯胺酮来模拟精神分裂症患者的脑电图状况,氯胺酮可以阻断镁结合位点的NMDAR通道。我们可以通过改变相应通路的三态突触模型中的镁浓度来模拟氯胺酮诱导的NMDAR通道阻断。我们的研究结果表明,氯胺酮诱导模型输出的兴奋行为增加;γ和σ波段振荡的变化符合实验研究。将应用tDCS的神经可塑性效应纳入模型(在(Riedinger and Hutt, 2022)之后)与TCT NMM相结合。根据实验文献,设置tDCS诱导的模拟外源电流,影响所选通路的可塑性。通过适当的参数化,我们可以模拟氯胺酮引起的脑电图振荡改变的逆转。总的来说,我们的计算机研究强调了NMM在预测tDCS对精神分裂症有效个性化治疗方案方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers in biology and medicine
Computers in biology and medicine 工程技术-工程:生物医学
CiteScore
11.70
自引率
10.40%
发文量
1086
审稿时长
74 days
期刊介绍: Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.
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