Plebe Alessio, Domenella Rosaria Grazia
Department of Cognitive Science, University of Messina, V Concezione 8, Messina, Italy.
Biosystems. 2006 Oct-Dec;86(1-3):63-74. doi: 10.1016/j.biosystems.2006.02.018. Epub 2006 Apr 7.
The most important ability of the human vision is object recognition, yet it is exactly the less understood aspect of the vision system. Computational models have been helpful in progressing towards an explanation of this obscure cognitive ability, and today it is possible to conceive more refined models, thanks to the new availability of neuroscientific data about the human visual cortex. This work proposes a model of the development of the object recognition capability, under a different perspective with respect to the most common approaches, with a precise theoretical epistemology. It is assumed that the main processing functions involved in recognition are not genetically determined and hardwired in the neural circuits, but are the result of interactions between epigenetic influences and the basic neural plasticity mechanisms. The model is organized in modules related with the main visual biological areas, and is implemented mainly using the LISSOM architecture, a recent self-organizing algorithm closely reflecting the essential behavior of cortical circuits.
人类视觉最重要的能力是物体识别,但这恰恰是视觉系统中人们了解较少的方面。计算模型有助于我们朝着解释这种模糊的认知能力迈进,如今,由于有了关于人类视觉皮层的神经科学新数据,我们能够构思出更精细的模型。这项工作从一个与最常见方法不同的角度,以精确的理论认识论,提出了一个物体识别能力发展的模型。我们假定,识别过程中涉及的主要处理功能并非由基因决定并硬连接在神经回路中,而是表观遗传影响与基本神经可塑性机制之间相互作用的结果。该模型按与主要视觉生物学区域相关的模块进行组织,主要使用LISSOM架构来实现,这是一种最近的自组织算法,紧密反映了皮层回路的基本行为。