标题： 基于经验驱动的分块表示在分层视觉记忆模型中的形成 显示英文标题

标题： Experience-driven formation of parts-based representations in a model of layered visual memory

摘要： 越来越多的神经心理学和神经生理学证据表明，视觉皮层使用基于部分的表征来编码、存储和检索相关物体。 在这种机制下，物体被表示为一组空间分布的局部特征或部分，以典型的方式排列。 为了编码局部外观并表示组成部分之间的关系，必须通过先前对视觉对象的经验形成适当的记忆结构。 在这里，我们提出了一种模型，说明如何通过经验驱动的自组织过程建立支持高效存储和快速检索基于部分表征的分层记忆结构。 该过程基于双向突触可塑性和单元活动稳态调节的合作，两者都运行在具有赢家通吃特性的快速活动动力学之上，并受到振荡节律的调制。 这些神经机制为分布式单元及其突触连接之间的合作与竞争奠定了基础。 选择人脸识别作为测试任务，我们证明，在开放式、无监督的增量学习条件下，系统能够以基于部分的方式为个体面孔形成记忆痕迹。 在较低的记忆层，突触结构发展以表示局部面部特征及其相互关系，而不同人物的身份则在较高层次上明确捕获。 所得到的表示的一个附加特性是在回忆期间以及构成记忆痕迹的突触模式中的稀疏性。 显示英文摘要

摘要： Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces.