scholarly journals Hebbian plasticity requires compensatory processes on multiple timescales

2017 ◽  
Vol 372 (1715) ◽  
pp. 20160259 ◽  
Author(s):  
Friedemann Zenke ◽  
Wulfram Gerstner
Keyword(s):  
Synaptic Plasticity ◽  
Experimental Research ◽  
Neural Circuits ◽  
Homeostatic Plasticity ◽  
Fine Tuning ◽  
Control Mechanisms ◽  
Network Stability ◽  
Multiple Timescales ◽  
Hebbian Plasticity ◽  
Compensatory Process

We review a body of theoretical and experimental research on Hebbian and homeostatic plasticity, starting from a puzzling observation: while homeostasis of synapses found in experiments is a slow compensatory process, most mathematical models of synaptic plasticity use rapid compensatory processes (RCPs). Even worse, with the slow homeostatic plasticity reported in experiments, simulations of existing plasticity models cannot maintain network stability unless further control mechanisms are implemented. To solve this paradox, we suggest that in addition to slow forms of homeostatic plasticity there are RCPs which stabilize synaptic plasticity on short timescales. These rapid processes may include heterosynaptic depression triggered by episodes of high postsynaptic firing rate. While slower forms of homeostatic plasticity are not sufficient to stabilize Hebbian plasticity, they are important for fine-tuning neural circuits. Taken together we suggest that learning and memory rely on an intricate interplay of diverse plasticity mechanisms on different timescales which jointly ensure stability and plasticity of neural circuits. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.

scholarly journals MicroRNAs and synaptic plasticity—a mutual relationship

2014 ◽  
Vol 369 (1652) ◽  
pp. 20130515 ◽  
Author(s):  
Ayla Aksoy-Aksel ◽  
Federico Zampa ◽  
Gerhard Schratt
Keyword(s):  
Synaptic Plasticity ◽  
Cognitive Abilities ◽  
Neural Circuits ◽  
Cell Activity ◽  
Regulatory Function ◽  
Mammalian Brain ◽  
Regulation Of Transcription ◽  
Control Mechanisms ◽  
Mutual Relationship ◽  
Loss Of Function

MicroRNAs (miRNAs) are rapidly emerging as central regulators of gene expression in the postnatal mammalian brain. Initial studies mostly focused on the function of specific miRNAs during the development of neuronal connectivity in culture, using classical gain- and loss-of-function approaches. More recently, first examples have documented important roles of miRNAs in plastic processes in intact neural circuits in the rodent brain related to higher cognitive abilities and neuropsychiatric disease. At the same time, evidence is accumulating that miRNA function itself is subjected to sophisticated control mechanisms engaged by the activity of neural circuits. In this review, we attempt to pay tribute to this mutual relationship between miRNAs and synaptic plasticity. In particular, in the first part, we summarize how neuronal activity influences each step in the lifetime of miRNAs, including the regulation of transcription, maturation, gene regulatory function and turnover in mammals. In the second part, we discuss recent examples of miRNA function in synaptic plasticity in rodent models and their implications for higher cognitive function and neurological disorders, with a special emphasis on epilepsy as a disorder of abnormal nerve cell activity.

scholarly journals Synapse-Specific Homeostatic Mechanisms in the Hippocampus

2009 ◽  
Vol 101 (2) ◽  
pp. 503-506 ◽  
Author(s):  
Katherine E. Deeg
Keyword(s):  
Neural Circuits ◽  
Epileptic Seizures ◽  
Homeostatic Plasticity ◽  
Excitatory Synapses ◽  
Network Stability ◽  
Homeostatic Synaptic Plasticity ◽  
New Type ◽  
Hippocampal Network ◽  
Synaptic Gain ◽  
Different Populations

Homeostatic synaptic plasticity allows neural circuits to function stably despite fluctuations to their inputs. Previous work has shown that excitatory synaptic strength increases globally when neuronal inputs are chronically silenced. A recent paper by Kim and Tsien describes a new type of synapse-specific homeostatic plasticity in which input silencing causes simultaneous strengthening and weakening of different populations of excitatory synapses within a hippocampal network. These seemingly antagonistic homeostatic adaptations maintain synaptic gain and preserve overall network stability by limiting harmful reverberatory bursting, which may underlie epileptic seizures.

scholarly journals The dialectic of Hebb and homeostasis

2017 ◽  
Vol 372 (1715) ◽  
pp. 20160258 ◽  
Author(s):  
Gina G. Turrigiano
Keyword(s):  
Recent Progress ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Homeostatic Plasticity ◽  
Homeostatic Control ◽  
Spatial And Temporal Scales ◽  
Network Function ◽  
Hebbian Plasticity ◽  
Circuit Function ◽  
Hebbian Mechanisms

It has become widely accepted that homeostatic and Hebbian plasticity mechanisms work hand in glove to refine neural circuit function. Nonetheless, our understanding of how these fundamentally distinct forms of plasticity compliment (and under some circumstances interfere with) each other remains rudimentary. Here, I describe some of the recent progress of the field, as well as some of the deep puzzles that remain. These include unravelling the spatial and temporal scales of different homeostatic and Hebbian mechanisms, determining which aspects of network function are under homeostatic control, and understanding when and how homeostatic and Hebbian mechanisms must be segregated within neural circuits to prevent interference. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.

scholarly journals Wherefore Art Thou, Homeo(stasis)? Functional Diversity in Homeostatic Synaptic Plasticity

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Bridget N. Queenan ◽  
Kea Joo Lee ◽  
Daniel T. S. Pak
Keyword(s):  
Synaptic Plasticity ◽  
Homeostatic Plasticity ◽  
Network Activity ◽  
Control Mechanisms ◽  
Adaptive Responses ◽  
Neuronal Function ◽  
Homeostatic Synaptic Plasticity ◽  
Regulatory Principle ◽  
Functional Classes ◽  
Homeostatic Mechanisms

Homeostatic plasticity has emerged as a fundamental regulatory principle that strives to maintain neuronal activity within optimal ranges by altering diverse aspects of neuronal function. Adaptation to network activity is often viewed as an essential negative feedback restraint that prevents runaway excitation or inhibition. However, the precise importance of these homeostatic functions is often theoretical rather than empirically derived. Moreover, a remarkable multiplicity of homeostatic adaptations has been observed. To clarify these issues, it may prove useful to ask: why do homeostatic mechanisms exist, what advantages do these adaptive responses confer on a given cell population, and why are there so many seemingly divergent effects? Here, we approach these questions by applying the principles of control theory to homeostatic synaptic plasticity of mammalian neurons and suggest that the varied responses observed may represent distinct functional classes of control mechanisms directed toward disparate physiological goals.

scholarly journals Homeostatic structural plasticity leads to the formation of memory engrams through synaptic rewiring in recurrent networks

2020 ◽  
Author(s):  
Júlia V. Gallinaro ◽  
Nebojša Gašparović ◽  
Stefan Rotter
Keyword(s):  
Neural Networks ◽  
Synaptic Plasticity ◽  
Diffusion Process ◽  
Structural Plasticity ◽  
Memory Formation ◽  
Homeostatic Plasticity ◽  
Spiking Neural Networks ◽  
Recurrent Networks ◽  
Hebbian Plasticity ◽  
Stimulation Of

AbstractBrain networks store new memories using functional and structural synaptic plasticity. Memory formation is generally attributed to Hebbian plasticity, while homeostatic plasticity is thought to have an ancillary role in stabilizing network dynamics. Here we report that homeostatic plasticity alone can also lead to the formation of stable memories. We analyze this phenomenon using a new theory of network remodeling, combined with numerical simulations of recurrent spiking neural networks that exhibit structural plasticity based on firing rate homeostasis. These networks are able to store repeatedly presented patterns and recall them upon the presentation of incomplete cues. Storing is fast, governed by the homeostatic drift. In contrast, forgetting is slow, driven by a diffusion process. Joint stimulation of neurons induces the growth of associative connections between them, leading to the formation of memory engrams. In conclusion, homeostatic structural plasticity induces a specific type of “silent memories”, different from conventional attractor states.

scholarly journals Homeostatic Synaptic Plasticity: Balanced by COX2-PGE2 System to a New Setpoint

2013 ◽  
Vol 1 (2) ◽  
pp. 20-23
Author(s):  
Fuzhou Wang
Keyword(s):  
Nervous System ◽  
Synaptic Plasticity ◽  
Prostaglandin E2 ◽  
Neural Activity ◽  
Neural Circuits ◽  
Critical Role ◽  
Homeostatic Plasticity ◽  
Homeostatic Synaptic Plasticity ◽  
Cox 2

The setpoint of neural activity plays a critical role in maintaining the complex neural circuits into stable activities. Homeostatic synaptic plasticity is a major component of the setpoint theory that dynamically adjusts synaptic strengths. Cyclooxy-genase 2 (COX 2) is rapidly upregulated in inflammatory episodes after nervous injury and its product prostaglandin E2 (PGE2) exerts contrast functions in the nervous system by working on the homeostatic plasticity. New data revealed that COX2-PGE2 system takes an essential part in balancing excitation and inhibition of the synaptic activities at a new setpoint that finally is maintained by the homeostatic synaptic plasticity.

scholarly journals The temporal paradox of Hebbian learning and homeostatic plasticity

2017 ◽  
Author(s):  
Friedemann Zenke ◽  
Wulfram Gerstner ◽  
Surya Ganguli
Keyword(s):  
Learning And Memory ◽  
Neuronal Activity ◽  
Neural Circuits ◽  
Hebbian Learning ◽  
Homeostatic Plasticity ◽  
Hebbian Plasticity ◽  
Slow Evolution ◽  
The Brain

AbstractHebbian plasticity, a synaptic mechanism which detects and amplifies co-activity between neurons, is considered a key ingredient underlying learning and memory in the brain. However, Hebbian plasticity alone is unstable, leading to runaway neuronal activity, and therefore requires stabilization by additional compensatory processes. Traditionally, a diversity of homeostatic plasticity phenomena found in neural circuits are thought to play this role. However, recent modelling work suggests that the slow evolution of homeostatic plasticity, as observed in experiments, is insufficient to prevent instabilities originating from Hebbian plasticity. To remedy this situation, we suggest that homeostatic plasticity is complemented by additional rapid compensatory processes, which rapidly stabilize neuronal activity on short timescales.

scholarly journals Functional consequences of pre- and postsynaptic expression of synaptic plasticity

2017 ◽  
Vol 372 (1715) ◽  
pp. 20160153 ◽  
Author(s):  
Rui Ponte Costa ◽  
Beatriz E. P. Mizusaki ◽  
P. Jesper Sjöström ◽  
Mark C. W. van Rossum
Keyword(s):  
Synaptic Plasticity ◽  
Research Effort ◽  
Receptive Fields ◽  
Spike Timing ◽  
Homeostatic Plasticity ◽  
Response Latencies ◽  
Open Questions ◽  
Hebbian Plasticity ◽  
Functional Consequences ◽  
Specific Locus

Growing experimental evidence shows that both homeostatic and Hebbian synaptic plasticity can be expressed presynaptically as well as postsynaptically. In this review, we start by discussing this evidence and methods used to determine expression loci. Next, we discuss the functional consequences of this diversity in pre- and postsynaptic expression of both homeostatic and Hebbian synaptic plasticity. In particular, we explore the functional consequences of a biologically tuned model of pre- and postsynaptically expressed spike-timing-dependent plasticity complemented with postsynaptic homeostatic control. The pre- and postsynaptic expression in this model predicts (i) more reliable receptive fields and sensory perception, (ii) rapid recovery of forgotten information (memory savings), and (iii) reduced response latencies, compared with a model with postsynaptic expression only. Finally, we discuss open questions that will require a considerable research effort to better elucidate how the specific locus of expression of homeostatic and Hebbian plasticity alters synaptic and network computations. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.

scholarly journals How neural circuits achieve and use stable dynamics

2019 ◽  
Author(s):  
Leo Kozachkov ◽  
Mikael Lundqvist ◽  
Jean-Jacques Slotine ◽  
Earl K. Miller
Keyword(s):  
Neural Networks ◽  
Synaptic Plasticity ◽  
Recurrent Neural Networks ◽  
Neural Circuits ◽  
Stable State ◽  
Distributed Networks ◽  
Time Varying ◽  
Multiple Sources ◽  
Hebbian Plasticity ◽  
The Brain

1AbstractThe brain consists of many interconnected networks with time-varying activity. There are multiple sources of noise and variation yet activity has to eventually converge to a stable state for its computations to make sense. We approached this from a control-theory perspective by applying contraction analysis to recurrent neural networks. This allowed us to find mechanisms for achieving stability in multiple connected networks with biologically realistic dynamics, including synaptic plasticity and time-varying inputs. These mechanisms included anti-Hebbian plasticity, synaptic sparsity and excitatory-inhibitory balance. We leveraged these findings to construct networks that could perform functionally relevant computations in the presence of noise and disturbance. Our work provides a blueprint for how to construct stable plastic and distributed networks.

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