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Reconciling the object and spatial processing views of the perirhinal cortex through task‐relevant unitization
Author(s) -
Fiorilli Julien,
Bos Jeroen J.,
Grande Xenia,
Lim Judith,
Düzel Emrah,
Pennartz Cyriel M. A.
Publication year - 2021
Publication title -
hippocampus
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.767
H-Index - 155
eISSN - 1098-1063
pISSN - 1050-9631
DOI - 10.1002/hipo.23304
Subject(s) - perirhinal cortex , psychology , temporal lobe , neuroscience , cognitive neuroscience of visual object recognition , sensory system , computer science , cognitive psychology , object (grammar) , recognition memory , cognition , artificial intelligence , epilepsy
The perirhinal cortex is situated on the border between sensory association cortex and the hippocampal formation. It serves an important function as a transition area between the sensory neocortex and the medial temporal lobe. While the perirhinal cortex has traditionally been associated with object coding and the “what” pathway of the temporal lobe, current evidence suggests a broader function of the perirhinal cortex in solving feature ambiguity and processing complex stimuli. Besides fulfilling functions in object coding, recent neurophysiological findings in freely moving rodents indicate that the perirhinal cortex also contributes to spatial and contextual processing beyond individual sensory modalities. Here, we address how these two opposing views on perirhinal cortex—the object‐centered and spatial‐contextual processing hypotheses—may be reconciled. The perirhinal cortex is consistently recruited when different features can be merged perceptually or conceptually into a single entity. Features that are unitized in these entities include object information from multiple sensory domains, reward associations, semantic features and spatial/contextual associations. We propose that the same perirhinal network circuits can be flexibly deployed for multiple cognitive functions, such that the perirhinal cortex performs similar unitization operations on different types of information, depending on behavioral demands and ranging from the object‐related domain to spatial, contextual and semantic information.

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