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2015 ; 9
(ä): 138
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Models of Metaplasticity: A Review of Concepts
#MMPMID26617512
Yger P
; Gilson M
Front Comput Neurosci
2015[]; 9
(ä): 138
PMID26617512
show ga
Part of hippocampal and cortical plasticity is characterized by synaptic
modifications that depend on the joint activity of the pre- and post-synaptic
neurons. To which extent those changes are determined by the exact timing and the
average firing rates is still a matter of debate; this may vary from brain area
to brain area, as well as across neuron types. However, it has been robustly
observed both in vitro and in vivo that plasticity itself slowly adapts as a
function of the dynamical context, a phenomena commonly referred to as
metaplasticity. An alternative concept considers the regulation of groups of
synapses with an objective at the neuronal level, for example, maintaining a
given average firing rate. In that case, the change in the strength of a
particular synapse of the group (e.g., due to Hebbian learning) affects others'
strengths, which has been coined as heterosynaptic plasticity. Classically,
Hebbian synaptic plasticity is paired in neuron network models with such
mechanisms in order to stabilize the activity and/or the weight structure. Here,
we present an oriented review that brings together various concepts from
heterosynaptic plasticity to metaplasticity, and show how they interact with
Hebbian-type learning. We focus on approaches that are nowadays used to
incorporate those mechanisms to state-of-the-art models of spiking plasticity
inspired by experimental observations in the hippocampus and cortex. Making the
point that metaplasticity is an ubiquitous mechanism acting on top of classical
Hebbian learning and promoting the stability of neural function over multiple
timescales, we stress the need for incorporating it as a key element in the
framework of plasticity models. Bridging theoretical and experimental results
suggests a more functional role for metaplasticity mechanisms than simply
stabilizing neural activity.
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