scholarly journals A model of rapid homeostatic plasticity accounts for hidden, long-lasting changes in a neuronal circuit after exposure to high potassium.

2021 ◽  
Author(s):  
Mara C.P. Rue ◽  
Leandro M Alonso ◽  
Eve Marder
Keyword(s):  
Computational Models ◽  
Neural Circuits ◽  
Model Neuron ◽  
Normal Activity ◽  
Homeostatic Plasticity ◽  
Neuronal Circuit ◽  
High Potassium ◽  
After Hours ◽  
Activity Dependent ◽  
Target Activity

Neural circuits must both function reliably and flexibly adapt to changes in their environment. We studied how both biological neurons and computational models respond to high potassium concentrations. Pyloric neurons of the crab stomatogastric ganglion (STG) initially become quiescent, then recover spiking activity in high potassium saline. The neurons retain this adaptation and recover more rapidly in subsequent high potassium applications, even after hours in control saline. We constructed a novel activity-dependent computational model that qualitatively captures these results. In this model, regulation of conductances is gated on and off depending on how far the neuron is from its target activity. This allows the model neuron to retain a trace of past perturbations even after it returns to its target activity in control conditions. Thus, perturbation, followed by recovery of normal activity, can hide cryptic changes in neuronal properties that are only revealed by subsequent perturbations.

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 A neuronal circuit for vector computation builds an allocentric traveling-direction signal in the Drosophila fan-shaped body

2020 ◽  
Author(s):  
Cheng Lyu ◽  
L.F. Abbott ◽  
Gaby Maimon
Keyword(s):  
Computational Models ◽  
Neuronal Population ◽  
The Body ◽  
Central Complex ◽  
Two Dimensional ◽  
Neuronal Circuit ◽  
Head Direction ◽  
Neural Signals ◽  
Shaped Body ◽  
External Cues

AbstractMany behavioral tasks require the manipulation of mathematical vectors, but, outside of computational models1–8, it is not known how brains perform vector operations. Here we show how the Drosophila central complex, a region implicated in goal-directed navigation8–14, performs vector arithmetic. First, we describe neural signals in the fan-shaped body that explicitly track a fly’s allocentric traveling direction, that is, the traveling direction in reference to external cues. Past work has identified neurons in Drosophila12,15–17 and mammals18,19 that track allocentric heading (e.g., head-direction cells), but these new signals illuminate how the sense of space is properly updated when traveling and heading angles differ. We then characterize a neuronal circuit that rotates, scales, and adds four vectors related to the fly’s egocentric traveling direction–– the traveling angle referenced to the body axis––to compute the allocentric traveling direction. Each two-dimensional vector is explicitly represented by a sinusoidal activity pattern across a distinct neuronal population, with the sinusoid’s amplitude representing the vector’s length and its phase representing the vector’s angle. The principles of this circuit, which performs an egocentric-to-allocentric coordinate transformation, may generalize to other brains and to domains beyond navigation where vector operations or reference-frame transformations are required.

scholarly journals GABAB receptor deficiency causes failure of neuronal homeostasis in hippocampal networks

2015 ◽  
Vol 112 (25) ◽  
pp. E3291-E3299 ◽  
Author(s):  
Irena Vertkin ◽  
Boaz Styr ◽  
Edden Slomowitz ◽  
Nir Ofir ◽  
Ilana Shapira ◽  
...  
Keyword(s):  
Neural Circuits ◽  
Gabab Receptor ◽  
Snare Complex ◽  
Homeostatic Plasticity ◽  
Calcium Flux ◽  
Neuronal Homeostasis ◽  
Protein Receptor ◽  
Presynaptic Calcium ◽  
Hippocampal Networks ◽  
Synaptic Vesicle Release

Stabilization of neuronal activity by homeostatic control systems is fundamental for proper functioning of neural circuits. Failure in neuronal homeostasis has been hypothesized to underlie common pathophysiological mechanisms in a variety of brain disorders. However, the key molecules regulating homeostasis in central mammalian neural circuits remain obscure. Here, we show that selective inactivation of GABAB, but not GABAA, receptors impairs firing rate homeostasis by disrupting synaptic homeostatic plasticity in hippocampal networks. Pharmacological GABAB receptor (GABABR) blockade or genetic deletion of the GB1a receptor subunit disrupts homeostatic regulation of synaptic vesicle release. GABABRs mediate adaptive presynaptic enhancement to neuronal inactivity by two principle mechanisms: First, neuronal silencing promotes syntaxin-1 switch from a closed to an open conformation to accelerate soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex assembly, and second, it boosts spike-evoked presynaptic calcium flux. In both cases, neuronal inactivity removes tonic block imposed by the presynaptic, GB1a-containing receptors on syntaxin-1 opening and calcium entry to enhance probability of vesicle fusion. We identified the GB1a intracellular domain essential for the presynaptic homeostatic response by tuning intermolecular interactions among the receptor, syntaxin-1, and the CaV2.2 channel. The presynaptic adaptations were accompanied by scaling of excitatory quantal amplitude via the postsynaptic, GB1b-containing receptors. Thus, GABABRs sense chronic perturbations in GABA levels and transduce it to homeostatic changes in synaptic strength. Our results reveal a novel role for GABABR as a key regulator of population firing stability and propose that disruption of homeostatic synaptic plasticity may underlie seizure's persistence in the absence of functional GABABRs.

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 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 GluA4 subunit of AMPA receptors mediates the early synaptic response to altered network activity in the developing hippocampus

2016 ◽  
Vol 115 (6) ◽  
pp. 2989-2996 ◽  
Author(s):  
J. Huupponen ◽  
T. Atanasova ◽  
T. Taira ◽  
S. E. Lauri
Keyword(s):  
Ampa Receptors ◽  
Pyramidal Neurons ◽  
Activity Patterns ◽  
Critical Role ◽  
Long Term Potentiation ◽  
Postnatal Period ◽  
Homeostatic Plasticity ◽  
Network Activity ◽  
Hippocampal Pyramidal Neurons ◽  
Activity Dependent

Development of the neuronal circuitry involves both Hebbian and homeostatic plasticity mechanisms that orchestrate activity-dependent refinement of the synaptic connectivity. AMPA receptor subunit GluA4 is expressed in hippocampal pyramidal neurons during early postnatal period and is critical for neonatal long-term potentiation; however, its role in homeostatic plasticity is unknown. Here we show that GluA4-dependent plasticity mechanisms allow immature synapses to promptly respond to alterations in network activity. In the neonatal CA3, the threshold for homeostatic plasticity is low, and a 15-h activity blockage with tetrodotoxin triggers homeostatic upregulation of glutamatergic transmission. On the other hand, attenuation of the correlated high-frequency bursting in the CA3-CA1 circuitry leads to weakening of AMPA transmission in CA1, thus reflecting a critical role for Hebbian synapse induction in the developing CA3-CA1. Both of these developmentally restricted forms of plasticity were absent in GluA4 −/− mice. These data suggest that GluA4 enables efficient homeostatic upscaling and responsiveness to temporal activity patterns during the critical period of activity-dependent refinement of the circuitry.

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 Membrane Capacitance Measurements Revisited: Dependence of Capacitance Value on Measurement Method in Nonisopotential Neurons

2009 ◽  
Vol 102 (4) ◽  
pp. 2161-2175 ◽  
Author(s):  
Jorge Golowasch ◽  
Gladis Thomas ◽  
Adam L. Taylor ◽  
Arif Patel ◽  
Arlene Pineda ◽  
...  
Keyword(s):  
Surface Area ◽  
Voltage Clamp ◽  
Computational Models ◽  
Model Neuron ◽  
Compartment Model ◽  
Membrane Capacitance ◽  
Current Clamp ◽  
Capacitance Measurements ◽  
Fitting Procedures ◽  
Total Membrane

During growth or degeneration neuronal surface area can change dramatically. Measurements of membrane protein concentration, as in ion channel or ionic conductance density, are often normalized by membrane capacitance, which is proportional to the surface area, to express changes independently from cell surface variations. Several electrophysiological protocols are used to measure cell capacitance, all based on the assumption of membrane isopotentiality. Yet, most neurons violate this assumption because of their complex anatomical structure, raising the question of which protocol yields measurements that are closest to the actual total membrane capacitance. We measured the capacitance of identified neurons from crab stomatogastric ganglia using three different protocols: the current-clamp step, the voltage-clamp step, and the voltage-clamp ramp protocols. We observed that the current-clamp protocol produced significantly higher capacitance values than those of either voltage-clamp protocol. Computational models of various anatomical complexities suggest that the current-clamp protocol can yield accurate capacitance estimates. In contrast, the voltage-clamp protocol estimates rapidly deteriorate as isopotentiality is reduced. We provide a mathematical description of these results by analyzing a simple two-compartment model neuron to facilitate an intuitive understanding of these methods. Together, the experiments, modeling, and mathematical analysis indicate that accurate total membrane capacitance measurements cannot be obtained with voltage-clamp protocols in nonisopotential neurons. Furthermore, although current-clamp steps can theoretically yield accurate measurements, experimentalists should be aware of limitations imposed by step duration and numerical errors during fitting procedures to obtain the membrane time constant.

scholarly journals Multiple shared mechanisms for homeostatic plasticity in rodent somatosensory and visual cortex

2017 ◽  
Vol 372 (1715) ◽  
pp. 20160157 ◽  
Author(s):  
Melanie A. Gainey ◽  
Daniel E. Feldman
Keyword(s):  
Visual Cortex ◽  
Sensory Deprivation ◽  
Homeostatic Plasticity ◽  
Intrinsic Excitability ◽  
Synaptic Scaling ◽  
Cellular Mechanisms ◽  
Firing Rates ◽  
Parvalbumin Interneuron ◽  
Activity Dependent ◽  
V1 Cortex

We compare the circuit and cellular mechanisms for homeostatic plasticity that have been discovered in rodent somatosensory (S1) and visual (V1) cortex. Both areas use similar mechanisms to restore mean firing rate after sensory deprivation. Two time scales of homeostasis are evident, with distinct mechanisms. Slow homeostasis occurs over several days, and is mediated by homeostatic synaptic scaling in excitatory networks and, in some cases, homeostatic adjustment of pyramidal cell intrinsic excitability. Fast homeostasis occurs within less than 1 day, and is mediated by rapid disinhibition, implemented by activity-dependent plasticity in parvalbumin interneuron circuits. These processes interact with Hebbian synaptic plasticity to maintain cortical firing rates during learned adjustments in sensory representations. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.

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