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Big-Loop Recurrence within the Hippocampal System Supports Integration of Information across Episodes

Koster, Raphael; Chadwick, Martin J.; Chen, Yi; Berron, David LU ; Banino, Andrea; Düzel, Emrah; Hassabis, Demis and Kumaran, Dharshan (2018) In Neuron 99(6). p.6-1354
Abstract

Recent evidence challenges the widely held view that the hippocampus is specialized for episodic memory, by demonstrating that it also underpins the integration of information across experiences. Contemporary computational theories propose that these two contrasting functions can be accomplished by big-loop recurrence, whereby the output of the system is recirculated back into the hippocampus. We use ultra-high-resolution fMRI to provide support for this hypothesis, by showing that retrieved information is presented as a new input on the superficial entorhinal cortex—driven by functional connectivity between the deep and superficial entorhinal layers. Further, the magnitude of this laminar connectivity correlated with inferential... (More)

Recent evidence challenges the widely held view that the hippocampus is specialized for episodic memory, by demonstrating that it also underpins the integration of information across experiences. Contemporary computational theories propose that these two contrasting functions can be accomplished by big-loop recurrence, whereby the output of the system is recirculated back into the hippocampus. We use ultra-high-resolution fMRI to provide support for this hypothesis, by showing that retrieved information is presented as a new input on the superficial entorhinal cortex—driven by functional connectivity between the deep and superficial entorhinal layers. Further, the magnitude of this laminar connectivity correlated with inferential performance, demonstrating its importance for behavior. Our findings offer a novel perspective on information processing within the hippocampus and support a unifying framework in which the hippocampus captures higher-order structure across experiences, by creating a dynamic memory space from separate episodic codes for individual experiences. The hippocampus is central for storing distinct episodes, while also supporting integration across related episodes. Using ultra-high-resolution fMRI, Koster et al. provide evidence for a core computational principle (big-loop recurrence) that can account for these apparently conflicting hippocampal roles.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
7 Tesla, fMRI, hippocampus, MVPA, paired-associate inference task
in
Neuron
volume
99
issue
6
pages
6 - 1354
publisher
Cell Press
external identifiers
  • scopus:85052954488
ISSN
0896-6273
DOI
10.1016/j.neuron.2018.08.009
language
English
LU publication?
yes
id
57d44f1e-7d69-4b25-b073-f882e13929b4
date added to LUP
2018-10-11 07:35:54
date last changed
2019-09-17 04:40:41
@article{57d44f1e-7d69-4b25-b073-f882e13929b4,
  abstract     = {<p>Recent evidence challenges the widely held view that the hippocampus is specialized for episodic memory, by demonstrating that it also underpins the integration of information across experiences. Contemporary computational theories propose that these two contrasting functions can be accomplished by big-loop recurrence, whereby the output of the system is recirculated back into the hippocampus. We use ultra-high-resolution fMRI to provide support for this hypothesis, by showing that retrieved information is presented as a new input on the superficial entorhinal cortex—driven by functional connectivity between the deep and superficial entorhinal layers. Further, the magnitude of this laminar connectivity correlated with inferential performance, demonstrating its importance for behavior. Our findings offer a novel perspective on information processing within the hippocampus and support a unifying framework in which the hippocampus captures higher-order structure across experiences, by creating a dynamic memory space from separate episodic codes for individual experiences. The hippocampus is central for storing distinct episodes, while also supporting integration across related episodes. Using ultra-high-resolution fMRI, Koster et al. provide evidence for a core computational principle (big-loop recurrence) that can account for these apparently conflicting hippocampal roles.</p>},
  author       = {Koster, Raphael and Chadwick, Martin J. and Chen, Yi and Berron, David and Banino, Andrea and Düzel, Emrah and Hassabis, Demis and Kumaran, Dharshan},
  issn         = {0896-6273},
  keyword      = {7 Tesla,fMRI,hippocampus,MVPA,paired-associate inference task},
  language     = {eng},
  month        = {09},
  number       = {6},
  pages        = {6--1354},
  publisher    = {Cell Press},
  series       = {Neuron},
  title        = {Big-Loop Recurrence within the Hippocampal System Supports Integration of Information across Episodes},
  url          = {http://dx.doi.org/10.1016/j.neuron.2018.08.009},
  volume       = {99},
  year         = {2018},
}