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整合信息理论与现象绑定问题:动态框架中的挑战与解决方案

Integrated Information Theory and the Phenomenal Binding Problem: Challenges and Solutions in a Dynamic Framework.

作者信息

Percy Chris, Gómez-Emilsson Andrés

机构信息

College of Arts, Humanities and Education, University of Derby, Derby DE22 1GB, UK.

Qualia Research Institute, San Francisco, CA 95066, USA.

出版信息

Entropy (Basel). 2025 Mar 25;27(4):338. doi: 10.3390/e27040338.

Abstract

Theories of consciousness grounded in neuroscience must explain the phenomenal binding problem, e.g., how micro-units of information are combined to create the macro-scale conscious experience common to human phenomenology. An example is how single 'pixels' of a visual scene are experienced as a single holistic image in the 'mind's eye', rather than as individual, separate, and massively parallel experiences, corresponding perhaps to individual neuron activations, neural ensembles, or foveal saccades, any of which could conceivably deliver identical functionality from an information processing point of view. There are multiple contested candidate solutions to the phenomenal binding problem. This paper explores how the metaphysical infrastructure of Integrated Information Theory (IIT) v4.0 can provide a distinctive solution. The solution-that particular entities aggregable from multiple units ('complexes') define existence-might work in a static picture, but introduces issues in a dynamic system. We ask what happens to our phenomenal self as the main complex moves around a biological neural network. Our account of conscious entities developing through time leads to an apparent dilemma for IIT theorists between non-local entity transitions and contiguous selves: the 'dynamic entity evolution problem'. As well as specifying the dilemma, we describe three ways IIT might dissolve the dilemma before it gains traction. Clarifying IIT's position on the phenomenal binding problem, potentially underpinned with novel empirical or theoretical research, helps researchers understand IIT and assess its plausibility. We see our paper as contributing to IIT's current research emphasis on the shift from static to dynamic analysis.

摘要

基于神经科学的意识理论必须解释现象约束问题,例如,信息的微观单元是如何组合起来,以创造出人类现象学中常见的宏观层面的意识体验。一个例子是,视觉场景中的单个“像素”是如何在“脑海”中被体验为一个整体图像,而不是作为个体、分离且大量并行的体验,这些体验可能分别对应于单个神经元激活、神经集合或中央凹扫视,从信息处理的角度来看,其中任何一种都可能实现相同的功能。对于现象约束问题,有多种存在争议的候选解决方案。本文探讨了整合信息理论(IIT)v4.0的形而上学基础结构如何能提供一种独特的解决方案。这种解决方案——即从多个单元聚合而成的特定实体(“复合体”)定义存在——在静态图景中可能行得通,但在动态系统中会引发问题。我们要问,当主要复合体在生物神经网络中移动时,我们的现象自我会发生什么。我们对有意识实体随时间发展的描述,给IIT理论家带来了一个明显的两难困境,即在非局部实体转变和连续自我之间:“动态实体进化问题”。除了明确这个两难困境,我们还描述了IIT在这个两难困境变得棘手之前可能化解它的三种方式。阐明IIT在现象约束问题上的立场,可能有新的实证或理论研究作为支撑,这有助于研究人员理解IIT并评估其合理性。我们认为我们的论文有助于IIT目前从静态分析转向动态分析的研究重点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7059/12026057/f39bf764bbc3/entropy-27-00338-g001.jpg

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