Ulysse Klatzmann, Sean Froudist-Walsh, Daniel P Bliss, Panagiota Theodoni, Jorge Mejías, Meiqi Niu, Lucija Rapan, Nicola Palomero-Gallagher, Claire Sergent, Stanislas Dehaene, Xiao-Jing Wang
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引用次数: 0
Abstract
Conscious access is suggested to involve "ignition," an all-or-none activation across cortical areas. To elucidate this phenomenon, we carry out computer simulations of a detection task using a mesoscale connectome-based model for the multiregional macaque cortex. The model uncovers a dynamic bifurcation mechanism that gives rise to ignition in a network of associative regions. A hierarchical N-methyl-D-aspartate (NMDA)/α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor gradient plays a critical role: fast AMPA receptors drive feedforward signal propagation, while slow NMDA receptors in feedback pathways shape and sustain the ignited network. Intriguingly, the model suggests higher NMDA-to-AMPA receptor ratios in sensory areas compared to association areas, a prediction supported by in vitro autoradiography data. Furthermore, the model accounts for diverse behavioral and physiological phenomena linked to consciousness. This work sheds light on how receptor gradients along the cortical hierarchy enable distributed cognitive functions and provides a biologically constrained computational framework for investigating the neurophysiological basis of conscious access.
有意识的接触被认为涉及到“点火”,一种横跨皮质区域的全或无激活。为了阐明这一现象,我们使用基于中尺度连接体的多区域猕猴皮层模型进行了检测任务的计算机模拟。该模型揭示了一种动态分岔机制,该机制在关联区域网络中引起点火。一个分层的n -甲基- d -天冬氨酸(NMDA)/α-氨基-3-羟基-5-甲基-4-异氧唑丙酸(AMPA)受体梯度起着关键作用:快速的AMPA受体驱动前馈信号传播,而缓慢的NMDA受体在反馈通路中形成并维持点燃的网络。有趣的是,该模型表明,与关联区相比,感觉区nmda与ampa受体的比例更高,这一预测得到了体外放射自显影数据的支持。此外,该模型还解释了与意识相关的各种行为和生理现象。这项工作揭示了沿着皮质层次的受体梯度如何实现分布式认知功能,并为研究意识访问的神经生理学基础提供了生物学约束的计算框架。
期刊介绍:
Cell Reports publishes high-quality research across the life sciences and focuses on new biological insight as its primary criterion for publication. The journal offers three primary article types: Reports, which are shorter single-point articles, research articles, which are longer and provide deeper mechanistic insights, and resources, which highlight significant technical advances or major informational datasets that contribute to biological advances. Reviews covering recent literature in emerging and active fields are also accepted.
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