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尖峰神经元的横向信息处理:意识的神经相关物的理论模型。

Lateral information processing by spiking neurons: a theoretical model of the neural correlate of consciousness.

机构信息

Wilhelm-Schickard-Institut für Informatik, Eberhard-Karls-Universität Tübingen, Germany.

出版信息

Comput Intell Neurosci. 2011;2011:247879. doi: 10.1155/2011/247879. Epub 2011 Oct 23.

Abstract

Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on "autopilot"). Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the "conscious pilot") suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious "auto-pilot" cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways "gap junctions" in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of synchrony, within which the contents of perception are represented and contained. This mobile zone can be viewed as a model of the neural correlate of consciousness in the brain.

摘要

认知脑功能,例如感觉感知、运动控制和学习,被理解为整合和点火神经元网络中轴突-树突化学突触的计算。认知脑功能可以有意识地或无意识地发生(在“自动驾驶”模式下)。意识认知的标志是 γ 同步 EEG,主要由树突-树突缝隙连接介导,在输入/整合层中的侧向连接。缝隙连接连接的神经元定义了更大神经网络中的一个子网络。一个理论模型(“意识飞行员”)表明,随着缝隙连接的打开和关闭,一个 γ 同步的子网或区域作为执行代理在大脑中移动,将无意识的“自动驾驶”认知转换为意识,并通过相干处理和集体整合增强计算。在这项研究中,我们在单层人工神经网络中实现了侧向“缝隙连接”,以执行图形/背景分离。通过缝隙连接连接的神经元集合形成可重新配置的电阻网格或子网区域。在该模型中,传出尖峰在时间上通过神经元的固定电阻网格进行积分,该固定电阻网格由通过缝隙连接连接的具有相似功能的神经元建立。这种空间平均,本质上是神经元输出的反馈信号,决定了神经元之间特定的缝隙连接是打开还是关闭。通过开放缝隙连接连接的神经元使其输出尖峰同步。我们已经在人工视网膜输入的单层神经网络上使用真实世界的图像对我们的缝隙连接定义的子网进行了测试。我们的系统能够执行图形/背景分离,其中连接的神经元的侧向子网代表感知到的对象。尽管我们仅展示了视觉刺激的结果,但我们的方法应该可以推广到其他模态。该系统展示了一个同步的移动子网区域,其中感知的内容被表示和包含。这个移动区域可以看作是大脑中意识神经相关物的模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bac9/3199212/bb42b30ffad9/CIN2011-247879.001.jpg

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