Pennartz Cyriel M A
Chair of Cognitive and Systems Neuroscience, Swammerdam Institute, Center for Neuroscience, Cognitive Science Center Amsterdam, Faculty of Science, Universiteit van Amsterdam, P.O. Box 94084, Kruislaan 320, 1090 GB, Amsterdam, The Netherlands.
Conscious Cogn. 2009 Sep;18(3):718-39. doi: 10.1016/j.concog.2009.03.003. Epub 2009 May 5.
A key question in studying consciousness is how neural operations in the brain can identify streams of sensory input as belonging to distinct modalities, which contributes to the representation of qualitatively different experiences. The basis for identification of modalities is proposed to be constituted by self-organized comparative operations across a network of unimodal and multimodal sensory areas. However, such network interactions alone cannot answer the question how sensory feature detectors collectively account for an integrated, yet phenomenally differentiated experiential content. This problem turns out to be different from, although related to, the binding problem. It is proposed that the neural correlate of an enriched, multimodal experience is constituted by the attractor state of a dynamic associative network. Within this network, unimodal and multimodal sensory maps continuously interact to influence each other's attractor state, so that a feature change in one modality results in a fast re-coding of feature information in another modality. In this scheme, feature detection is coded by firing-rate, whereas firing phase codes relational aspects.
研究意识的一个关键问题是,大脑中的神经活动如何将感觉输入流识别为属于不同的模态,这有助于对性质不同的体验进行表征。模态识别的基础被认为是由单模态和多模态感觉区域网络中的自组织比较操作构成的。然而,仅靠这种网络交互无法回答感觉特征探测器如何共同构成一个整合的、但在现象学上有差异的体验内容这一问题。事实证明,这个问题与捆绑问题不同,尽管与之相关。有人提出,丰富的多模态体验的神经关联是由动态联想网络的吸引子状态构成的。在这个网络中,单模态和多模态感觉图谱不断相互作用,影响彼此的吸引子状态,从而使一种模态中的特征变化导致另一种模态中特征信息的快速重新编码。在这个方案中,特征检测由放电率编码,而放电相位编码关系方面。