scholarly journals Rapid and Sustained Homeostatic Control of Presynaptic Exocytosis at a Central Synapse

2019 ◽  
Author(s):  
Igor Delvendahl ◽  
Katarzyna Kita ◽  
Martin Müller
Keyword(s):  
Time Scales ◽  
Neural Circuit ◽  
Mossy Fiber ◽  
Pool Size ◽  
Homeostatic Plasticity ◽  
Experimental Conditions ◽  
Central Synapse ◽  
Circuit Function ◽  
Vesicle Pool ◽  
Activity Dependent

AbstractAnimal behavior is remarkably robust despite constant changes in neural activity. Homeostatic plasticity stabilizes central nervous system (CNS) function on time scales of hours to days. If and how CNS function is stabilized on more rapid time scales remains unknown. Here we discovered that mossy fiber synapses in the mouse cerebellum homeostatically control synaptic efficacy within minutes after pharmacological glutamate receptor impairment. This rapid form of homeostatic plasticity is expressed presynaptically. We show that modulations of readily-releasable vesicle pool size and release probability normalize synaptic strength in a hierarchical fashion upon acute pharmacological and prolonged genetic receptor perturbation. Presynaptic membrane capacitance measurements directly demonstrate regulation of vesicle pool size upon receptor impairment. Moreover, presynaptic voltage-clamp analysis revealed increased calcium-current density under specific experimental conditions. Thus, homeostatic modulation of presynaptic exocytosis through specific mechanisms stabilizes synaptic transmission in a CNS circuit on time scales ranging from minutes to months. Rapid presynaptic homeostatic plasticity may ensure stable neural circuit function in light of rapid activity-dependent plasticity.

scholarly journals Rapid and sustained homeostatic control of presynaptic exocytosis at a central synapse

2019 ◽  
Vol 116 (47) ◽  
pp. 23783-23789 ◽  
Author(s):  
Igor Delvendahl ◽  
Katarzyna Kita ◽  
Martin Müller
Keyword(s):  
Time Scales ◽  
Neural Circuit ◽  
Mossy Fiber ◽  
Pool Size ◽  
Homeostatic Plasticity ◽  
Experimental Conditions ◽  
Central Synapse ◽  
Circuit Function ◽  
Vesicle Pool ◽  
Activity Dependent

Animal behavior is remarkably robust despite constant changes in neural activity. Homeostatic plasticity stabilizes central nervous system (CNS) function on time scales of hours to days. If and how CNS function is stabilized on more rapid time scales remains unknown. Here, we discovered that mossy fiber synapses in the mouse cerebellum homeostatically control synaptic efficacy within minutes after pharmacological glutamate receptor impairment. This rapid form of homeostatic plasticity is expressed presynaptically. We show that modulations of readily releasable vesicle pool size and release probability normalize synaptic strength in a hierarchical fashion upon acute pharmacological and prolonged genetic receptor perturbation. Presynaptic membrane capacitance measurements directly demonstrate regulation of vesicle pool size upon receptor impairment. Moreover, presynaptic voltage-clamp analysis revealed increased Ca2+-current density under specific experimental conditions. Thus, homeostatic modulation of presynaptic exocytosis through specific mechanisms stabilizes synaptic transmission in a CNS circuit on time scales ranging from minutes to months. Rapid presynaptic homeostatic plasticity may ensure stable neural circuit function in light of rapid activity-dependent plasticity.

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 Compensatory variability in network parameters enhances memory performance in the Drosophila mushroom body

2021 ◽  
Author(s):  
Nada Y. Abdelrahman ◽  
Eleni Vasilaki ◽  
Andrew C. Lin
Keyword(s):  
Mushroom Body ◽  
Neural Circuit ◽  
Memory Performance ◽  
Activity Levels ◽  
Compensatory Mechanisms ◽  
Network Parameters ◽  
Kenyon Cells ◽  
Average Activity ◽  
Circuit Function ◽  
Activity Dependent

AbstractNeural circuits use homeostatic compensation to achieve consistent behaviour despite variability in underlying intrinsic and network parameters. However, it remains unclear how compensation regulates variability across a population of the same type of neurons within an individual, and what computational benefits might result from such compensation. We address these questions in the Drosophila mushroom body, the fly’s olfactory memory center. In a computational model, we show that memory performance is degraded when the mushroom body’s principal neurons, Kenyon cells (KCs), vary realistically in key parameters governing their excitability, because the resulting inter-KC variability in average activity levels makes odor representations less separable. However, memory performance is rescued while maintaining realistic variability if parameters compensate for each other to equalize KC average activity. Such compensation can be achieved through both activity-dependent and activity-independent mechanisms. Finally, we show that correlations predicted by our model’s compensatory mechanisms appear in the Drosophila hemibrain connectome. These findings reveal compensatory variability in the mushroom body and describe its computational benefits for associative memory.Significance statementHow does variability between neurons affect neural circuit function? How might neurons behave similarly despite having different underlying features? We addressed these questions in neurons called Kenyon cells, which store olfactory memories in flies. Kenyon cells differ among themselves in key features that affect how active they are, and in a model of the fly’s memory circuit, adding this inter-neuronal variability made the model fly worse at learning the values of multiple odors. However, memory performance was rescued if compensation between the variable underlying features allowed Kenyon cells to be equally active on average, and we found the hypothesized compensatory variability in real Kenyon cells’ anatomy. This work reveals the existence and computational benefits of compensatory variability in neural networks.

scholarly journals Optimal synaptic dynamics for memory maintenance in the presence of noise

2020 ◽  
Author(s):  
Dhruva V Raman ◽  
Timothy O’Leary
Keyword(s):  
Neural Circuit ◽  
Behavioural Change ◽  
Experimental Measurements ◽  
Synaptic Connections ◽  
Biological Noise ◽  
Brain Areas ◽  
Dependent Component ◽  
Synaptic Dynamics ◽  
Circuit Function ◽  
Activity Dependent

ABSTRACTSynaptic connections in many brain areas have been found to fluctuate significantly, with substantial turnover and remodelling occurring over hours to days. Remarkably, this flux in connectivity persists in the absence of overt learning or behavioural change. What proportion of these ongoing fluctuations can be attributed to systematic plasticity processes that maintain memories and neural circuit function? We show under general conditions that the optimal magnitude of systematic plasticity is typically less than the magnitude of perturbations due to internal biological noise. Thus, for any given amount of unavoidable noise, 50% or more of total synaptic turnover should be effectively random for optimal memory maintenance. Our analysis does not depend on specific neural circuit architectures or plasticity mechanisms and predicts previously unexplained experimental measurements of the activity-dependent component of ongoing plasticity.

Myelin Plasticity and Nervous System Function

2018 ◽  
Vol 41 (1) ◽  
pp. 61-76 ◽  
Author(s):  
Michelle Monje
Keyword(s):  
Nervous System ◽  
Neural Circuit ◽  
Neurological Function ◽  
Nervous System Activity ◽  
Second Mode ◽  
Nervous System Function ◽  
Plastic Changes ◽  
Circuit Function ◽  
Activity Dependent ◽  
Development Proceeds

Structural plasticity in the myelinated infrastructure of the nervous system has come to light. Although an innate program of myelin development proceeds independent of nervous system activity, a second mode of myelination exists in which activity-dependent, plastic changes in myelin-forming cells influence myelin structure and neurological function. These complementary and possibly temporally overlapping activity-independent and activity-dependent modes of myelination crystallize in a model of experience-modulated myelin development and plasticity with broad implications for neurological function. In this article, I consider the contributions of myelin to neural circuit function, the dynamic influences of experience on myelin microstructure, and the role that plasticity of myelin may play in cognition.

scholarly journals Analytical investigation of self-organized criticality in neural networks

2013 ◽  
Vol 10 (78) ◽  
pp. 20120558 ◽  
Author(s):  
Felix Droste ◽  
Anne-Ly Do ◽  
Thilo Gross
Keyword(s):  
Neural Networks ◽  
Stochastic Dynamics ◽  
Analytical Investigation ◽  
Homeostatic Plasticity ◽  
Dynamical Phase Transition ◽  
Discrete State ◽  
Dynamical Phase ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Activity Dependent

Dynamical criticality has been shown to enhance information processing in dynamical systems, and there is evidence for self-organized criticality in neural networks. A plausible mechanism for such self-organization is activity-dependent synaptic plasticity. Here, we model neurons as discrete-state nodes on an adaptive network following stochastic dynamics. At a threshold connectivity, this system undergoes a dynamical phase transition at which persistent activity sets in. In a low-dimensional representation of the macroscopic dynamics, this corresponds to a transcritical bifurcation. We show analytically that adding activity-dependent rewiring rules, inspired by homeostatic plasticity, leads to the emergence of an attractive steady state at criticality and present numerical evidence for the system's evolution to such a state.

scholarly journals Neural circuit function redundancy in brain disorders

2021 ◽  
Vol 70 ◽  
pp. 74-80
Author(s):  
Beatriz E.P. Mizusaki ◽  
Cian O'Donnell
Keyword(s):  
Neural Circuit ◽  
Brain Disorders ◽  
Circuit Function

scholarly journals The intellectual disability gene Kirrel3 regulates target-specific mossy fiber synapse development in the hippocampus

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
E Anne Martin ◽  
Shruti Muralidhar ◽  
Zhirong Wang ◽  
Diégo Cordero Cervantes ◽  
Raunak Basu ◽  
...  
Keyword(s):  
Synapse Formation ◽  
Mossy Fiber ◽  
Neuron Activity ◽  
Target Cells ◽  
Synaptic Changes ◽  
Mossy Fiber Synapse ◽  
Ca3 Neurons ◽  
Circuit Function ◽  
Feed Forward Inhibition

Synaptic target specificity, whereby neurons make distinct types of synapses with different target cells, is critical for brain function, yet the mechanisms driving it are poorly understood. In this study, we demonstrate Kirrel3 regulates target-specific synapse formation at hippocampal mossy fiber (MF) synapses, which connect dentate granule (DG) neurons to both CA3 and GABAergic neurons. Here, we show Kirrel3 is required for formation of MF filopodia; the structures that give rise to DG-GABA synapses and that regulate feed-forward inhibition of CA3 neurons. Consequently, loss of Kirrel3 robustly increases CA3 neuron activity in developing mice. Alterations in the Kirrel3 gene are repeatedly associated with intellectual disabilities, but the role of Kirrel3 at synapses remained largely unknown. Our findings demonstrate that subtle synaptic changes during development impact circuit function and provide the first insight toward understanding the cellular basis of Kirrel3-dependent neurodevelopmental disorders.

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