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It is commonly conceived that the cortical areas of the hippocampal region are functionally divided into the perirhinal cortex (PRC) and the lateral entorhinal cortex (LEC), which selectively process object information; and the medial entorhinal cortex (MEC), which selectively processes spatial information. Contrary to this notion, in rats performing a task that demands both object and spatial information processing, single neurons in PRC, LEC, and MEC, including those in both superficial and deep cortical areas and in grid, border, and head direction cells of MEC, have a highly similar range of selectivity to object and spatial dimensions of the task. By contrast, representational similarity analysis of population activity reveals a key distinction in the organization of information in these areas, such thatPRCand LEC populations prioritize object over location information, whereas MEC populations prioritize location over object information. These findings bring to the hippocampal system a growing emphasis on population analyses as a powerful tool for characterizing neural representations supporting cognition and memory. [ABSTRACT FROM AUTHOR]

The behavioral and neural mechanisms of orienting behavior have interested experimental psychologists for the last several decades. For example, in the framework of associative learning, examining the brain substrates of orienting behavior has yielded significant insight into the neural basis of attentional function and learning. The present study describes a procedure by which the orienting response to a visual stimulus (rearing on the hind legs) can be monitored automatically, and it validates the procedure by comparing data generated by the automated procedure with data generated by the typical observational procedure. The automated procedure provides an inexpensive means of obtaining immediate, online assessment of rearing behavior during a conditioning session, reduces the possibility of experimenter bias, and significantly reduces the time required to evaluate observational data. [ABSTRACT FROM AUTHOR]