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Interaction between Long-Term Potentiation and Depression in CA1 Synapses: Temporal Constrains, Functional Compartmentalization and Protein Synthesis

Overview of attention for article published in PLOS ONE, January 2012
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Title
Interaction between Long-Term Potentiation and Depression in CA1 Synapses: Temporal Constrains, Functional Compartmentalization and Protein Synthesis
Published in
PLOS ONE, January 2012
DOI 10.1371/journal.pone.0029865
Pubmed ID
Authors

Alice Pavlowsky, Juan Marcos Alarcon

Abstract

Information arriving at a neuron via anatomically defined pathways undergoes spatial and temporal encoding. A proposed mechanism by which temporally and spatially segregated information is encoded at the cellular level is based on the interactive properties of synapses located within and across functional dendritic compartments. We examined cooperative and interfering interactions between long-term synaptic potentiation (LTP) and depression (LTD), two forms of synaptic plasticity thought to be key in the encoding of information in the brain. Two approaches were used in CA1 pyramidal neurons of the mouse hippocampus: (1) induction of LTP and LTD in two separate synaptic pathways within the same apical dendritic compartment and across the basal and apical dendritic compartments; (2) induction of LTP and LTD separated by various time intervals (0-90 min). Expression of LTP/LTD interactions was spatially and temporally regulated. While they were largely restricted within the same dendritic compartment (compartmentalized), the nature of the interaction (cooperation or interference) depended on the time interval between inductions. New protein synthesis was found to regulate the expression of the LTP/LTD interference. We speculate that mechanisms for compartmentalization and protein synthesis confer the spatial and temporal modulation by which neurons encode multiplex information in plastic synapses.

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Geographical breakdown

Country Count As %
United Kingdom 2 4%
France 1 2%
Portugal 1 2%
Canada 1 2%
Belgium 1 2%
Japan 1 2%
Greece 1 2%
United States 1 2%
Unknown 40 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 35%
Researcher 9 18%
Student > Master 7 14%
Student > Bachelor 2 4%
Other 2 4%
Other 7 14%
Unknown 5 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 41%
Neuroscience 6 12%
Psychology 5 10%
Medicine and Dentistry 5 10%
Computer Science 2 4%
Other 5 10%
Unknown 6 12%