Frontiers in Synaptic Plasticity: Dendritic Spines, Circuitries and Behavior

Actin turnover in dendritic spines influences spine development, morphology, and plasticity, with functional consequences on learning and memory formation. In nonneuronal cells, protein kinase D (PKD) has an important role in stabilizing F-actin via multiple molecular pathways. Using in vitro models of neuronal plasticity, such as glycine-induced chemical long-term potentiation (LTP), known to evoke synaptic plasticity, or long-term depolarization block by KCl, leading to homeostatic morphological changes, we show that actin stabilization needed for the enlargement of dendritic spines is dependent on PKD activity. Consequently, impaired PKD functions attenuate activity-dependent changes in hippocampal dendritic spines, including LTP formation, cause morphological alterations in vivo, and have deleterious consequences on spatial memory formation. We thus provide compelling evidence that PKD controls synaptic plasticity and learning by regulating actin stability in dendritic spines.

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Biophysics of Biochemical Signaling in Dendritic Spines: Implications in Synaptic Plasticity

Biophysical Journal ◽

10.1016/j.bpj.2017.07.029 ◽

2017 ◽

Vol 113 (10) ◽

pp. 2152-2159 ◽

Cited By ~ 37

Author(s):

Ryohei Yasuda

Keyword(s):

Synaptic Plasticity ◽

Dendritic Spines

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Modification of Hippocampal Markers of Synaptic Plasticity by Memantine in Animal Models of Acute and Repeated Restraint Stress: Implications for Memory and Behavior

NeuroMolecular Medicine ◽

10.1007/s12017-015-8343-0 ◽

2015 ◽

Vol 17 (2) ◽

pp. 121-136 ◽

Cited By ~ 17

Author(s):

Shaimaa Nasr Amin ◽

Ahmed Amro El-Aidi ◽

Mohamed Mostafa Ali ◽

Yasser Mahmoud Attia ◽

Laila Ahmed Rashed

Keyword(s):

Synaptic Plasticity ◽

Animal Models ◽

Restraint Stress ◽

Repeated Restraint Stress ◽

And Behavior

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Plasticity: Cells, Circuits, Brains, and Behavior

The Computational Brain ◽

10.7551/mitpress/9780262533393.003.0005 ◽

2016 ◽

Author(s):

Patricia S. Churchland ◽

Terrence J. Sejnowski

Keyword(s):

Nervous System ◽

Synaptic Plasticity ◽

Classical Conditioning ◽

Neuronal Plasticity ◽

Neural Mechanism ◽

Synaptic Strength ◽

Physical Mechanisms ◽

And Behavior ◽

The Brain

This chapter examines the physical mechanisms in nervous systems in order to elucidate the structural bases and functional principles of synaptic plasticity. Neuroscientific research on plasticity can be divided into four main streams: the neural mechanism for relatively simple kinds of plasticity, such as classical conditioning or habituation; anatomical and physiological studies of temporal lobe structures, including the hippocampus and the amygdala; study of the development of the visual system; and the relation between the animal's genes and the development of its nervous system. The chapter first considers the role of the mammalian hippocampus in learning and memory before discussing Donald Hebb's views on synaptic plasticity. It then explores the mechanisms underlying neuronal plasticity and those that decrease synaptic strength, the relevance of time with respect to plasticity, and the occurrence of plasticity during the development of the nervous system. It also describes modules, modularity, and networks in the brain.

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Chemical LTD, but not LTP, induces transient accumulation of gelsolin in dendritic spines

Biological Chemistry ◽

10.1515/hsz-2019-0110 ◽

2019 ◽

Vol 400 (9) ◽

pp. 1129-1139 ◽

Cited By ~ 2

Author(s):

Iryna Hlushchenko ◽

Pirta Hotulainen

Keyword(s):

Synaptic Plasticity ◽

Dendritic Spines ◽

Hippocampal Neurons ◽

Long Term Potentiation ◽

Excitatory Synapses ◽

Signal Molecule ◽

Brain Functions ◽

Dendritic Shaft ◽

Term Potentiation

Abstract Synaptic plasticity underlies central brain functions, such as learning. Ca2+ signaling is involved in both strengthening and weakening of synapses, but it is still unclear how one signal molecule can induce two opposite outcomes. By identifying molecules, which can distinguish between signaling leading to weakening or strengthening, we can improve our understanding of how synaptic plasticity is regulated. Here, we tested gelsolin’s response to the induction of chemical long-term potentiation (cLTP) or long-term depression (cLTD) in cultured rat hippocampal neurons. We show that gelsolin relocates from the dendritic shaft to dendritic spines upon cLTD induction while it did not show any relocalization upon cLTP induction. Dendritic spines are small actin-rich protrusions on dendrites, where LTD/LTP-responsive excitatory synapses are located. We propose that the LTD-induced modest – but relatively long-lasting – elevation of Ca2+ concentration increases the affinity of gelsolin to F-actin. As F-actin is enriched in dendritic spines, it is probable that increased affinity to F-actin induces the relocalization of gelsolin.

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Secretory vesicle-related gene CAPS2 knock-out mice exhibit the reduced number of hippocampal GABAergic interneuron and the impairments in synaptic plasticity and behavior

Neuroscience Research ◽

10.1016/j.neures.2009.09.737 ◽

2009 ◽

Vol 65 ◽

pp. S146

Author(s):

Yo Shinoda ◽

Emi Kinameri ◽

Asako Furuya ◽

Tetsushi Sadakata ◽

Teiichi Furuichi

Keyword(s):

Synaptic Plasticity ◽

Secretory Vesicle ◽

Gabaergic Interneuron ◽

Related Gene ◽

Knock Out ◽

Knock Out Mice ◽

And Behavior

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Metabolic constraints on synaptic learning and memory

Journal of Neurophysiology ◽

10.1152/jn.00092.2019 ◽

2019 ◽

Vol 122 (4) ◽

pp. 1473-1490 ◽

Cited By ~ 2

Author(s):

Jan Karbowski

Keyword(s):

Synaptic Plasticity ◽

Metabolic Rate ◽

Protein Phosphorylation ◽

Learning And Memory ◽

Dendritic Spines ◽

Energy Cost ◽

Memory Trace ◽

Metabolic Energy ◽

Cascade Models ◽

New Learning

Dendritic spines, the carriers of long-term memory, occupy a small fraction of cortical space, and yet they are the major consumers of brain metabolic energy. What fraction of this energy goes for synaptic plasticity, correlated with learning and memory? It is estimated here based on neurophysiological and proteomic data for rat brain that, depending on the level of protein phosphorylation, the energy cost of synaptic plasticity constitutes a small fraction of the energy used for fast excitatory synaptic transmission, typically 4.0–11.2%. Next, this study analyzes a metabolic cost of new learning and its memory trace in relation to the cost of prior memories, using a class of cascade models of synaptic plasticity. It is argued that these models must contain bidirectional cyclic motifs, related to protein phosphorylation, to be compatible with basic thermodynamic principles. For most investigated parameters longer memories generally require proportionally more energy to store. The exceptions are the parameters controlling the speed of molecular transitions (e.g., ATP-driven phosphorylation rate), for which memory lifetime per invested energy can increase progressively for longer memories. Furthermore, in general, a memory trace decouples dynamically from a corresponding synaptic metabolic rate such that the energy expended on new learning and its memory trace constitutes in most cases only a small fraction of the baseline energy associated with prior memories. Taken together, these empirical and theoretical results suggest a metabolic efficiency of synaptically stored information. NEW & NOTEWORTHY Learning and memory involve a sequence of molecular events in dendritic spines called synaptic plasticity. These events are physical in nature and require energy, which has to be supplied by ATP molecules. However, our knowledge of the energetics of these processes is very poor. This study estimates the empirical energy cost of synaptic plasticity and considers theoretically a metabolic rate of learning and its memory trace in a class of cascade models of synaptic plasticity.

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