scholarly journals Sleep promotes downward firing rate homeostasis

2019 ◽  
Author(s):  
Alejandro Torrado Pacheco ◽  
Juliet Bottorff ◽  
Gina G. Turrigiano
Keyword(s):  
Firing Rate ◽  
Homeostatic Plasticity ◽  
Stable Set ◽  
Set Point ◽  
Aspartate Receptor ◽  
Vigilance State ◽  
Hebbian Plasticity ◽  
Freely Behaving ◽  
Scaling Down

SUMMARYHomeostatic plasticity is hypothesized to regulate neuronal activity around a stable set point to compensate for learning-related plasticity. This regulation is predicted to be bidirectional but only upward firing rate homeostasis (FRH) has been demonstrated in vivo. We combined chronic electrophysiology in freely behaving animals with a protocol that induces robust plasticity in primary visual cortex (V1) to induce downward FRH and show that neurons bidirectionally regulate firing rates around an individual set point. Downward FRH did not require N-methyl-D-aspartate receptor (NMDAR) signaling and was associated with homeostatic scaling down of synaptic strengths. Like upward FRH, downward FRH was gated by vigilance state, but in the opposite direction: it occurred during sleep and not during wake. In contrast, FR changes associated with Hebbian plasticity happened independently of sleep and wake. Thus, we find that sleep’s impact on neuronal plasticity depends on the particular forms of plasticity that are engaged.

Hebbian Plasticity and Homeostasis in a Model of Hypercolumn of the Visual Cortex

2010 ◽  
Vol 22 (7) ◽  
pp. 1837-1859 ◽  
Author(s):  
R. Rossi Pool ◽  
G. Mato
Keyword(s):  
Nervous System ◽  
Visual Cortex ◽  
Simple Model ◽  
Firing Rate ◽  
Combined Effect ◽  
Homeostatic Plasticity ◽  
Initial Condition ◽  
Nontrivial Solutions ◽  
Hebbian Plasticity ◽  
Contrast Invariance

Neurons in the nervous system display a wide variety of plasticity processes. Among them are covariance-based rules and homeostatic plasticity. By themselves, the first ones tend to generate instabilities because of the unbounded potentiation of synapses. The second ones tend to stabilize the system by setting a target for the postsynaptic firing rate. In this work, we analyze the combined effect of these two mechanisms in a simple model of hypercolumn of the visual cortex. We find that the presence of homeostatic plasticity together with nonplastic uniform inhibition stabilizes the effect of Hebbian plasticity. The system can reach nontrivial solutions, where the recurrent intracortical connections are strongly modulated. The modulation is strong enough to generate contrast invariance. Moreover, this state can be reached even beginning from a weakly modulated initial condition.

scholarly journals Activity labeling in vivo using CaMPARI2 reveals electrophysiological differences between neurons with high and low firing rate set points

2019 ◽  
Author(s):  
Nicholas F Trojanowski ◽  
Gina G. Turrigiano
Keyword(s):  
Firing Rate ◽  
Single Cell ◽  
Pyramidal Neurons ◽  
Intrinsic Excitability ◽  
Cell Type ◽  
Set Point ◽  
Firing Rates ◽  
Single Cell Type ◽  
Low Activity

AbstractIndividual excitatory neurons in visual cortex (V1) display remarkably stable mean firing rates over many days, even though these rates can differ by several orders of magnitude between neurons. When perturbed, each neuron’s firing rate is slowly regulated back to its pre-perturbation level, demonstrating that neurons maintain their mean firing rate around an individual firing rate set point (FRSP). To better understand the mechanisms that neurons within a single cell type use to maintain different FRSPs in vivo, we implemented a novel method of activity labeling that uses CaMPARI2, a fluorescent protein that undergoes Ca2+- and UV-dependent green-to-red photoconversion, to permanently label neurons in freely behaving mice based on their firing rates. We found that immediate early gene (IEG) expression was correlated with CaMPARI2 red/green ratio following an activity stimulation paradigm, and that neurons with greater photoconversion in vivo tended to have a higher firing rate ex vivo. In layer 4 (L4) pyramidal neurons in mouse monocular V1, which comprise a single transcriptional cell type, we found that high activity neurons had a left-shifted F-I curve, lower rheobase current, and decreased spike adaptation index relative to low activity neurons, demonstrating increased intrinsic excitability. Surprisingly, we found no difference in total excitatory or inhibitory synaptic current or in E/I ratio between high and low activity neurons. Thus, within a single cell type differences in intrinsic excitability and spike frequency adaptation can contribute to divergent activity set points. These results reveal that E/I ratio plays only a minor role in determining the firing rate set point of L4 pyramidal neurons, while intrinsic excitability is an important factor.

scholarly journals A deep convolutional visual encoding model of neuronal responses in the LGN

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eslam Mounier ◽  
Bassem Abdullah ◽  
Hani Mahdi ◽  
Seif Eldawlatly
Keyword(s):  
Firing Rate ◽  
Visual Information ◽  
Visual Stimulation ◽  
Neuronal Population ◽  
Neuronal Firing ◽  
Electrode Arrays ◽  
Deep Convolutional Neural Networks ◽  
Firing Rates ◽  
Spatiotemporal Representation

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.

scholarly journals High-Sugar, but Not High-Fat, Food Activates Supraoptic Nucleus Neurons in the Male Rat

Endocrinology ◽  
2017 ◽  
Vol 158 (7) ◽  
pp. 2200-2211 ◽  
Author(s):  
Catherine Hume ◽  
Nancy Sabatier ◽  
John Menzies
Keyword(s):  
Firing Rate ◽  
Supraoptic Nucleus ◽  
Male Rat ◽  
Plasma Sodium ◽  
Neural Activation ◽  
High Fat ◽  
Gastric Distention ◽  
High Sugar ◽  
Anesthetized Rats

Abstract Oxytocin is a potent anorexigen and is believed to have a role in satiety signaling. We developed rat models to study the activity of oxytocin neurons in response to voluntary consumption or oral gavage of foods using c-Fos immunohistochemistry and in vivo electrophysiology. Using c-Fos expression as an indirect marker of neural activation, we showed that the percentage of magnocellular oxytocin neurons expressing c-Fos increased with voluntary consumption of sweetened condensed milk (SCM). To model the effect of food in the stomach, we gavaged anesthetized rats with SCM. The percentage of supraoptic nucleus and paraventricular nucleus magnocellular oxytocin-immunoreactive neurons expressing c-Fos increased with SCM gavage but not with gastric distention. To further examine the activity of the supraoptic nucleus, we made in vivo electrophysiological recordings from SON neurons, where anesthetized rats were gavaged with SCM or single cream. Pharmacologically identified oxytocin neurons responded to SCM gavage with a linear, proportional, and sustained increase in firing rate, but cream gavage resulted in a transient reduction in firing rate. Blood glucose increased after SCM gavage but not cream gavage. Plasma osmolarity and plasma sodium were unchanged throughout. We show that in response to high-sugar, but not high-fat, food in the stomach, there is an increase in the activity of oxytocin neurons. This does not appear to be a consequence of stomach distention or changes in osmotic pressure. Our data suggest that the presence of specific foods with different macronutrient profiles in the stomach differentially regulates the activity of oxytocin neurons.

scholarly journals The Whisking Rhythm Generator: A Novel Mammalian Network for the Generation of Movement

2007 ◽  
Vol 97 (3) ◽  
pp. 2148-2158 ◽  
Author(s):  
Nathan P. Cramer ◽  
Ying Li ◽  
Asaf Keller
Keyword(s):  
Firing Rate ◽  
Serotonin Receptor ◽  
Central Pattern Generators ◽  
Rhythm Generator ◽  
Low Concentrations ◽  
Rhythmic Firing ◽  
Pattern Generators ◽  
Cortical Inputs

Using the rat vibrissa system, we provide evidence for a novel mechanism for the generation of movement. Like other central pattern generators (CPGs) that underlie many movements, the rhythm generator for whisking can operate without cortical inputs or sensory feedback. However, unlike conventional mammalian CPGs, vibrissa motoneurons (vMNs) actively participate in the rhythmogenesis by converting tonic serotonergic inputs into the patterned motor output responsible for movement of the vibrissae. We find that, in vitro, a serotonin receptor agonist, α-Me-5HT, facilitates a persistent inward current (PIC) and evokes rhythmic firing in vMNs. Within each motoneuron, increasing the concentration of α-Me-5HT significantly increases the both the magnitude of the PIC and the motoneuron's firing rate. Riluzole, which selectively suppresses the Na+ component of PICs at low concentrations, causes a reduction in both of these phenomena. The magnitude of this reduction is directly correlated with the concentration of riluzole. The joint effects of riluzole on PIC magnitude and firing rate in vMNs suggest that the two are causally related. In vivo we find that the tonic activity of putative serotonergic premotoneurons is positively correlated with the frequency of whisking evoked by cortical stimulation. Taken together, these results support the hypothesized novel mammalian mechanism for movement generation in the vibrissa motor system where vMNs actively participate in the rhythmogenesis in response to tonic drive from serotonergic premotoneurons.

scholarly journals Homeostatic plasticity and external input shape neural network dynamics

2018 ◽  
Author(s):  
Johannes Zierenberg ◽  
Jens Wilting ◽  
Viola Priesemann
Keyword(s):  
Neural Network ◽  
Brain Area ◽  
External Input ◽  
Homeostatic Plasticity ◽  
Dynamic State ◽  
Network Topologies ◽  
Neural Network Dynamics ◽  
Spiking Activity

In vitro and in vivo spiking activity clearly differ. Whereas networks in vitro develop strong bursts separated by periods of very little spiking activity, in vivo cortical networks show continuous activity. This is puzzling considering that both networks presumably share similar single-neuron dynamics and plasticity rules. We propose that the defining difference between in vitro and in vivo dynamics is the strength of external input. In vitro, networks are virtually isolated, whereas in vivo every brain area receives continuous input. We analyze a model of spiking neurons in which the input strength, mediated by spike rate homeostasis, determines the characteristics of the dynamical state. In more detail, our analytical and numerical results on various network topologies show consistently that under increasing input, homeostatic plasticity generates distinct dynamic states, from bursting, to close-to-critical, reverberating and irregular states. This implies that the dynamic state of a neural network is not fixed but can readily adapt to the input strengths. Indeed, our results match experimental spike recordings in vitro and in vivo: the in vitro bursting behavior is consistent with a state generated by very low network input (< 0.1%), whereas in vivo activity suggests that on the order of 1% recorded spikes are input-driven, resulting in reverberating dynamics. Importantly, this predicts that one can abolish the ubiquitous bursts of in vitro preparations, and instead impose dynamics comparable to in vivo activity by exposing the system to weak long-term stimulation, thereby opening new paths to establish an in vivo-like assay in vitro for basic as well as neurological studies.

scholarly journals Homeostatic plasticity rules control the wiring of axo-axonic synapses at the axon initial segment

2018 ◽  
Author(s):  
Alejandro Pan-Vazquez ◽  
Winnie Wefelmeyer ◽  
Victoria Gonzalez Sabater ◽  
Juan Burrone
Keyword(s):  
Initial Segment ◽  
Pyramidal Cells ◽  
Axon Initial Segment ◽  
Homeostatic Plasticity ◽  
Network Activity ◽  
Gabaergic Interneuron ◽  
Chandelier Cells ◽  
Local Circuits ◽  
And Function

AbstractGABAergic interneurons are chiefly responsible for controlling the activity of local circuits in the cortex1,2. However, the rules that govern the wiring of interneurons are not well understood3. Chandelier cells (ChCs) are a type of GABAergic interneuron that control the output of hundreds of neighbouring pyramidal cells through axo-axonic synapses which target the axon initial segment (AIS)4. Despite their importance in modulating circuit activity, our knowledge of the development and function of axo-axonic synapses remains elusive. In this study, we investigated the role of activity in the formation and plasticity of ChC synapses. In vivo imaging of ChCs during development uncovered a narrow window (P12-P18) over which axons arborized and formed connections. We found that increases in the activity of either pyramidal cells or individual ChCs during this temporal window resulted in a reversible decrease in axo-axonic connections. Voltage imaging of GABAergic transmission at the AIS showed that axo-axonic synapses were depolarising during this period. Identical manipulations of network activity in older mice (P40-P46), when ChC synapses are inhibitory, resulted in an increase in axo-axonic synapses. We propose that the direction of ChC plasticity follows homeostatic rules that depend on the polarity of axo-axonic synapses.

scholarly journals Hebbian Plasticity Guides Maturation of Glutamate Receptor Fields In Vivo

Cell Reports ◽  
2013 ◽  
Vol 3 (5) ◽  
pp. 1407-1413 ◽  
Author(s):  
Dmitrij Ljaschenko ◽  
Nadine Ehmann ◽  
Robert J. Kittel
Keyword(s):  
Glutamate Receptor ◽  
Hebbian Plasticity

scholarly journals Sparse bursts optimize information transmission in a multiplexed neural code

2018 ◽  
Vol 115 (27) ◽  
pp. E6329-E6338 ◽  
Author(s):  
Richard Naud ◽  
Henning Sprekeler
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
Neural Code ◽  
Spike Timing ◽  
Neural Ensemble ◽  
Multiple Input ◽  
Cortical Hierarchy ◽  
Connectivity Patterns ◽  
Rate Coding

Many cortical neurons combine the information ascending and descending the cortical hierarchy. In the classical view, this information is combined nonlinearly to give rise to a single firing-rate output, which collapses all input streams into one. We analyze the extent to which neurons can simultaneously represent multiple input streams by using a code that distinguishes spike timing patterns at the level of a neural ensemble. Using computational simulations constrained by experimental data, we show that cortical neurons are well suited to generate such multiplexing. Interestingly, this neural code maximizes information for short and sparse bursts, a regime consistent with in vivo recordings. Neurons can also demultiplex this information, using specific connectivity patterns. The anatomy of the adult mammalian cortex suggests that these connectivity patterns are used by the nervous system to maintain sparse bursting and optimal multiplexing. Contrary to firing-rate coding, our findings indicate that the physiology and anatomy of the cortex may be interpreted as optimizing the transmission of multiple independent signals to different targets.

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