Sasi Swapna, Sen Bhattacharya Basabdatta
Computer Science and Information Systems, Birla Institute of Technology and Science (BITS) Pilani, Sancoale, India.
Front Med Technol. 2022 Apr 5;4:856412. doi: 10.3389/fmedt.2022.856412. eCollection 2022.
We have studied brain connectivity using a biologically inspired model of the visual pathway consisting of the lateral geniculate nucleus (LGN) of the thalamus, and layers 4 and 6 of the primary visual cortex. The connectivity parameters in the model are informed by the existing anatomical parameters from mammals and rodents. In the base state, the LGN and layer 6 populations in the model oscillate with dominant alpha frequency, while the layer 4 oscillates in the theta band. By changing intra-cortical hyperparameters, specifically inhibition from layer 6 to layer 4, we demonstrate a transition to alpha mode for all the populations. Furthermore, by increasing the feedforward connectivities in the thalamo-cortico-thalamic loop, we could transition into the beta band for all the populations. On looking closely, we observed that the origin of this beta band is in the layer 6 (infragranular layers); lesioning the thalamic feedback from layer 6 removed the beta from the LGN and the layer 4. This agrees with existing physiological studies where it is shown that beta rhythm is generated in the infragranular layers. Lastly, we present a case study to demonstrate a neurological condition in the model. By changing connectivities in the network, we could simulate the condition of significant ( < 0.001) decrease in beta band power and a simultaneous increase in the theta band power, similar to that observed in Schizophrenia patients. Overall, we have shown that the connectivity changes in a simple visual thalamocortical model can simulate state changes in the brain corresponding to both health and disease conditions.
我们使用一种受生物启发的视觉通路模型研究了大脑连通性，该模型由丘脑的外侧膝状体核（LGN）以及初级视觉皮层的第4层和第6层组成。模型中的连通性参数依据来自哺乳动物和啮齿动物的现有解剖学参数确定。在基础状态下，模型中的LGN和第6层群体以占主导的α频率振荡，而第4层在θ波段振荡。通过改变皮层内超参数，特别是从第6层到第4层的抑制作用，我们证明了所有群体都转变为α模式。此外，通过增加丘脑 - 皮层 - 丘脑回路中的前馈连通性，我们可以使所有群体转变为β波段。仔细观察发现，这个β波段的起源在第6层（颗粒下层）；破坏来自第6层的丘脑反馈会使LGN和第4层中的β消失。这与现有的生理学研究一致，该研究表明β节律在颗粒下层产生。最后，我们展示了一个案例研究以证明模型中的一种神经疾病状态。通过改变网络中的连通性，我们可以模拟出β波段功率显著（<0.001）下降以及θ波段功率同时增加的状态，这与在精神分裂症患者中观察到的情况相似。总体而言，我们已经表明，一个简单的视觉丘脑皮层模型中的连通性变化可以模拟大脑中与健康和疾病状态相对应的状态变化。
