Encoding temporal regularities and information copying in hippocampal circuits

Roberts, Terri P, Kern, Felix B, Fernando, Chrisantha, Szathmary, Eors, Husbands, Phil, Philippides, Andrew O and Staras, Kevin (2019) Encoding temporal regularities and information copying in hippocampal circuits. Scientific Reports, 9. a19036. ISSN 2045-2322

[img] PDF (published OA journal paper) - Published Version
Available under License Creative Commons Attribution.

Download (5MB)


Discriminating, extracting and encoding temporal regularities is a critical requirement in the brain, relevant to sensory-motor processing and learning. However, the cellular mechanisms responsible remain enigmatic; for example, whether such abilities require specific, elaborately organized neural networks or arise from more fundamental, inherent properties of neurons. Here, using multi-electrode array technology, and focusing on interval learning, we demonstrate that sparse reconstituted rat hippocampal neural circuits are intrinsically capable of encoding and storing sub-second-order time intervals for over an hour timescale, represented in changes in the spatial-temporal architecture of firing relationships among populations of neurons. This learning is accompanied by increases in mutual information and transfer entropy, formal measures related to information storage and flow. Moreover, temporal relationships derived from previously trained circuits can act as templates for copying intervals into untrained networks, suggesting the possibility of circuit-to-circuit information transfer. Our findings illustrate that dynamic encoding and stable copying of temporal relationships are fundamental properties of simple in vitro networks, with general significance for understanding elemental principles of information processing, storage and replication.

Item Type: Article
Keywords: Hippocampus, temporal encoding, information copying, transfer entropy, mutual information, cross-correlation, multi-electrode array
Schools and Departments: School of Engineering and Informatics > Informatics
School of Life Sciences > Neuroscience
Research Centres and Groups: Centre for Computational Neuroscience and Robotics
Sussex Neuroscience
Subjects: Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
Q Science > QP Physiology > QP0351 Neurophysiology and neuropsychology > QP0361 Nervous system
Q Science > QP Physiology > QP0351 Neurophysiology and neuropsychology > QP0361 Nervous system > QP0364.5 Neural transmission
Depositing User: Phil Husbands
Date Deposited: 16 Dec 2019 09:10
Last Modified: 16 Dec 2019 09:15
URI: http://sro.sussex.ac.uk/id/eprint/88795

View download statistics for this item

📧 Request an update
Project NameSussex Project NumberFunderFunder Ref
INSIGHT-II Darwinian NeurodynamicsG1087EUROPEAN UNION308943
Ultrastructure-function properties of recycling vesicle pools in native central synapsesG1150BBSRC-BIOTECHNOLOGY & BIOLOGICAL SCIENCES RESEARCH COUNCILBB/K019015/1
Functional synaptic vesicle pool remodelling as a basis for plasticity and control of complex behaviourG2521BBSRC-BIOTECHNOLOGY & BIOLOGICAL SCIENCES RESEARCH COUNCILBB/S00310X/1