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新皮层中感知与意识的神经计算机制。

Neurocomputational mechanisms underlying perception and sentience in the neocortex.

作者信息

Johnson Andrew S, Winlow William

机构信息

Dipartimento di Biologia, Università degli Studi di Napoli Federico II, Napoli, Italy.

Institute of Ageing and Chronic Diseases, University of Liverpool, Liverpool, United Kingdom.

出版信息

Front Comput Neurosci. 2024 Mar 5;18:1335739. doi: 10.3389/fncom.2024.1335739. eCollection 2024.

Abstract

The basis for computation in the brain is the quantum threshold of "soliton," which accompanies the ion changes of the action potential, and the refractory membrane at convergences. Here, we provide a logical explanation from the action potential to a neuronal model of the coding and computation of the retina. We also explain how the visual cortex operates through quantum-phase processing. In the small-world network, parallel frequencies collide into definable patterns of distinct objects. Elsewhere, we have shown how many sensory cells are meanly sampled from a single neuron and that convergences of neurons are common. We also demonstrate, using the threshold and refractory period of a quantum-phase pulse, that action potentials diffract across a neural network due to the annulment of parallel collisions in the phase ternary computation (PTC). Thus, PTC applied to neuron convergences results in a collective mean sampled frequency and is the only mathematical solution within the constraints of the brain neural networks (BNN). In the retina and other sensory areas, we discuss how this information is initially coded and then understood in terms of network abstracts within the lateral geniculate nucleus (LGN) and visual cortex. First, by defining neural patterning within a neural network, and then in terms of contextual networks, we demonstrate that the output of frequencies from the visual cortex contains information amounting to abstract representations of objects in increasing detail. We show that nerve tracts from the LGN provide time synchronization to the neocortex (defined as the location of the combination of connections of the visual cortex, motor cortex, auditory cortex, etc.). The full image is therefore combined in the neocortex with other sensory modalities so that it receives information about the object from the eye and all the abstracts that make up the object. Spatial patterns in the visual cortex are formed from individual patterns illuminating the retina, and memory is encoded by reverberatory loops of computational action potentials (CAPs). We demonstrate that a similar process of PTC may take place in the cochlea and associated ganglia, as well as ascending information from the spinal cord, and that this function should be considered universal where convergences of neurons occur.

摘要

大脑中的计算基础是“孤子”的量子阈值,它伴随着动作电位的离子变化以及汇聚处的不应性膜。在此,我们从动作电位到视网膜编码与计算的神经元模型提供了一种逻辑解释。我们还解释了视觉皮层如何通过量子相位处理进行运作。在小世界网络中,并行频率碰撞形成可定义的不同物体模式。在其他地方,我们已经展示了从单个神经元平均采样了多少感觉细胞以及神经元汇聚是常见的。我们还利用量子相位脉冲的阈值和不应期证明,由于相位三元计算(PTC)中并行碰撞的消除,动作电位在神经网络中发生衍射。因此,应用于神经元汇聚的PTC会产生一个集体平均采样频率,并且是大脑神经网络(BNN)约束范围内的唯一数学解。在视网膜和其他感觉区域,我们讨论了这些信息最初是如何编码的,然后如何根据外侧膝状体核(LGN)和视觉皮层内的网络摘要来理解。首先,通过定义神经网络内的神经模式,然后根据上下文网络,我们证明视觉皮层频率输出包含的信息量相当于物体越来越详细的抽象表示。我们表明,来自LGN的神经束为新皮层(定义为视觉皮层、运动皮层、听觉皮层等连接组合的位置)提供时间同步。因此,完整图像在新皮层中与其他感觉模态相结合,以便它从眼睛接收有关物体的信息以及构成物体的所有摘要。视觉皮层中的空间模式由照亮视网膜的个体模式形成,记忆由计算动作电位(CAP)的回响回路编码。我们证明,类似的PTC过程可能发生在耳蜗和相关神经节以及来自脊髓的上行信息中,并且在神经元发生汇聚的地方,这种功能应被视为普遍存在的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a92/10948548/cb0e1a0db476/fncom-18-1335739-g0001.jpg

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