Center for Adaptive Systems, Boston University, 677 Beacon Street, Boston, MA 02215, USA; Graduate Program in Cognitive and Neural Systems, Departments of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering Boston University, 677 Beacon Street, Boston, MA 02215, USA.
Neural Netw. 2017 Mar;87:38-95. doi: 10.1016/j.neunet.2016.11.003. Epub 2016 Dec 6.
The hard problem of consciousness is the problem of explaining how we experience qualia or phenomenal experiences, such as seeing, hearing, and feeling, and knowing what they are. To solve this problem, a theory of consciousness needs to link brain to mind by modeling how emergent properties of several brain mechanisms interacting together embody detailed properties of individual conscious psychological experiences. This article summarizes evidence that Adaptive Resonance Theory, or ART, accomplishes this goal. ART is a cognitive and neural theory of how advanced brains autonomously learn to attend, recognize, and predict objects and events in a changing world. ART has predicted that "all conscious states are resonant states" as part of its specification of mechanistic links between processes of consciousness, learning, expectation, attention, resonance, and synchrony. It hereby provides functional and mechanistic explanations of data ranging from individual spikes and their synchronization to the dynamics of conscious perceptual, cognitive, and cognitive-emotional experiences. ART has reached sufficient maturity to begin classifying the brain resonances that support conscious experiences of seeing, hearing, feeling, and knowing. Psychological and neurobiological data in both normal individuals and clinical patients are clarified by this classification. This analysis also explains why not all resonances become conscious, and why not all brain dynamics are resonant. The global organization of the brain into computationally complementary cortical processing streams (complementary computing), and the organization of the cerebral cortex into characteristic layers of cells (laminar computing), figure prominently in these explanations of conscious and unconscious processes. Alternative models of consciousness are also discussed.
意识的难题是解释我们如何体验感受或现象经验,如看、听和感觉,以及知道它们是什么。为了解决这个问题,意识理论需要通过建模几个大脑机制相互作用的涌现属性如何体现个体意识心理体验的详细属性,将大脑与心灵联系起来。本文总结了证据,表明自适应共振理论(ART)实现了这一目标。ART 是一种关于高级大脑如何自主学习在不断变化的世界中注意、识别和预测物体和事件的认知和神经理论。ART 预测“所有意识状态都是共振状态”,作为其在意识、学习、期望、注意力、共振和同步过程之间的机制联系的规范的一部分。它由此提供了从单个尖峰及其同步到意识知觉、认知和认知情感体验的动力学的数据的功能和机制解释。ART 已经成熟到可以开始对支持视觉、听觉、感觉和认知体验的大脑共振进行分类。这种分类澄清了正常个体和临床患者的心理和神经生物学数据。这种分析还解释了为什么不是所有的共振都成为意识,为什么不是所有的大脑动力学都是共振的。大脑的全局组织成计算上互补的皮质处理流(互补计算),以及大脑皮层组织成具有特征细胞层(层状计算),在这些意识和无意识过程的解释中占据重要地位。还讨论了其他意识模型。