Past events

Traditional models of memory dissociate memory from processes. Such tendency is rooted in the analogy between computers’ architecture and the brain, which dissociate the central processing units from the memory units. Based on such conceptualization, many empirical studies focus on simple delay periods in which memory has to be actively maintained but not processed and cases in which the integration between past and present information is undesirable. However, such models are not applicable to the majority of real life processes in which the past and present converge continuously in the processes of incoming information. Based on empirical data we outline a new framework for process-memory that resists the tendency to separate memory from process. We argue that cortical areas, ranging from early sensory areas to high order areas, has the capacity to accumulate information over time. Memory is intrinsic to each and any neural circuit, and is essential for its ability to process information. Furthermore, our data suggest that the process-memory timescale increases from early sensory areas to high order areas. Our hypothesis, that each brain area accumulates information over its preferred timescale, suggests that memories of the recent past are not stored in a few localized working memory buffers, but rather are distributed in an organized hierarchical topography throughout the nervous system. The “work of memory” is performed in virtually every neural circuit, and attentional systems modulate this ongoing processing in accordance with rule- or goal-related constraints.

Visual categorization is thought to occur in the human ventral temporal cortex (VTC), but how this categorization is achieved is still largely unknown. I will consider the computations and representations that are necessary for categorization, and examine how the microanatomical and macroanatomical layout of the VTC might optimize them to achieve rapid and flexible visual categorization. I will propose that efficient categorization is achieved by organizing representations in a nested spatial hierarchy in the VTC. This spatial hierarchy serves as a neural infrastructure for the representational hierarchy of visual information in the VTC and thereby enables flexible access to category information at several levels of abstraction.