Using the Change Manager Model for the Hippocampal System to Predict Connectivity and Neurophysiological Parameters in the Perirhinal Cortex.
Comput Intell Neurosci
; 2016: 8625875, 2016.
Article
in En
| MEDLINE
| ID: mdl-26819594
Theoretical arguments demonstrate that practical considerations, including the needs to limit physiological resources and to learn without interference with prior learning, severely constrain the anatomical architecture of the brain. These arguments identify the hippocampal system as the change manager for the cortex, with the role of selecting the most appropriate locations for cortical receptive field changes at each point in time and driving those changes. This role results in the hippocampal system recording the identities of groups of cortical receptive fields that changed at the same time. These types of records can also be used to reactivate the receptive fields active during individual unique past events, providing mechanisms for episodic memory retrieval. Our theoretical arguments identify the perirhinal cortex as one important focal point both for driving changes and for recording and retrieving episodic memories. The retrieval of episodic memories must not drive unnecessary receptive field changes, and this consideration places strong constraints on neuron properties and connectivity within and between the perirhinal cortex and regular cortex. Hence the model predicts a number of such properties and connectivity. Experimental test of these falsifiable predictions would clarify how change is managed in the cortex and how episodic memories are retrieved.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Temporal Lobe
/
Hippocampus
/
Models, Neurological
/
Neural Pathways
/
Neurophysiology
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Animals
/
Humans
Language:
En
Journal:
Comput Intell Neurosci
Journal subject:
INFORMATICA MEDICA
/
NEUROLOGIA
Year:
2016
Document type:
Article
Affiliation country:
Australia
Country of publication:
United States