Hypothalamic Neuron Activation Under Stress and During Antigen Application

2012 ◽  
Vol 3 (3,4) ◽  
pp. 243-253 ◽  
Author(s):  
S.V. Perekrest ◽  
K.Z. Shainidze ◽  
N.S. Novikova ◽  
T.B. Kazakova ◽  
E.A. Korneva
2021 ◽  
pp. 0271678X2110103
Author(s):  
Nao Hatakeyama ◽  
Miyuki Unekawa ◽  
Juri Murata ◽  
Yutaka Tomita ◽  
Norihiro Suzuki ◽  
...  

A variety of brain cells participates in neurovascular coupling by transmitting and modulating vasoactive signals. The present study aimed to probe cell type-dependent cerebrovascular (i.e., pial and penetrating arterial) responses with optogenetics in the cortex of anesthetized mice. Two lines of the transgenic mice expressing a step function type of light-gated cation channel (channelrhodopsine-2; ChR2) in either cortical neurons (muscarinic acetylcholine receptors) or astrocytes (Mlc1-positive) were used in the experiments. Photo-activation of ChR2-expressing astrocytes resulted in a widespread increase in cerebral blood flow (CBF), extending to the nonstimulated periphery. In contrast, photo-activation of ChR2-expressing neurons led to a relatively localized increase in CBF. The differences in the spatial extent of the CBF responses are potentially explained by differences in the involvement of the vascular compartments. In vivo imaging of the cerebrovascular responses revealed that ChR2-expressing astrocyte activation led to the dilation of both pial and penetrating arteries, whereas ChR2-expressing neuron activation predominantly caused dilation of the penetrating arterioles. Pharmacological studies showed that cell type-specific signaling mechanisms participate in the optogenetically induced cerebrovascular responses. In conclusion, pial and penetrating arterial vasodilation were differentially evoked by ChR2-expressing astrocytes and neurons.


RNA ◽  
2020 ◽  
Vol 26 (10) ◽  
pp. 1414-1430 ◽  
Author(s):  
Bongmin Bae ◽  
Hannah N. Gruner ◽  
Maebh Lynch ◽  
Ting Feng ◽  
Kevin So ◽  
...  

Author(s):  
Ihor Konovalenko ◽  
Pavlo Maruschak ◽  
Vitaly Brevus

Abstract Steel defect diagnostics is important for industry task as it is tied to the product quality and production efficiency. The aim of this paper is evaluating the application of residual neural networks for recognition of industrial steel defects of three classes. Developed and investigated models based on deep residual neural networks for the recognition and classification of surface defects of rolled steel. Investigated the influence of various loss functions, optimizers and hyperparameters on the obtained result and selected optimal model parameters. Based on an ensemble of two deep residual neural networks ResNet50 and ResNet152, a classifier was constructed to detect defects of three classes on flat metal surfaces. The proposed technique allows classifying images with high accuracy. The average binary accuracy of classifying the test data is 96.7% for all images (including defect-free ones). The fields of neuron activation in the convolutional layers of the model were investigated. Feature maps formed in the process were found to reflect the position, size and shape of the objects of interest very well. The proposed ensemble model has proven to be robust and able to accurately recognize steel surface defects. Erroneous recognition cases of the classifier application are investigated. It was shown that errors most often occur in ambiguous situations, where surface artifacts of different types are similar.


2007 ◽  
Vol 17 (03) ◽  
pp. 207-218 ◽  
Author(s):  
BAOYONG ZHANG ◽  
SHENGYUAN XU ◽  
YONGMIN LI

This paper considers the problem of robust exponential stability for a class of recurrent neural networks with time-varying delays and parameter uncertainties. The time delays are not necessarily differentiable and the uncertainties are assumed to be time-varying but norm-bounded. Sufficient conditions, which guarantee that the concerned uncertain delayed neural network is robustly, globally, exponentially stable for all admissible parameter uncertainties, are obtained under a weak assumption on the neuron activation functions. These conditions are dependent on the size of the time delay and expressed in terms of linear matrix inequalities. Numerical examples are provided to demonstrate the effectiveness and less conservatism of the proposed stability results.


2004 ◽  
Vol 14 (05) ◽  
pp. 1807-1811 ◽  
Author(s):  
M. DI MARCO ◽  
M. FORTI ◽  
P. NISTRI ◽  
A. TESI

The paper addresses robustness of complete stability with respect to perturbations of the interconnections of nominal symmetric neural networks. The influence of the maximum neuron activation gain on complete stability robustness is discussed for a class of third-order neural networks. It is shown that high values of the gain lead to an extremely small complete stability margin of all nominal symmetric neural networks, thus allowing to conclude that complete stability robustness cannot be, in general, guaranteed.


2012 ◽  
Vol 15 (5) ◽  
pp. 657 ◽  
Author(s):  
Xiping Zhan ◽  
Werner M Graf

Purpose. Harmaline is one member of a class of tremorgenic harmala alkaloids that have been implicated in neuroprotective effects and neurodegenerative disorders. It has been reported to interact with several neurotransmitter receptors as well as ion exchangers and voltage-sensitive channels. One site of harmaline action in the brain is the inferior olive (IO). Either local or systemic harmaline injection has been reported to increase spiking rate and coherence in the inferior olive and this activation is thought to produce tremor and ataxia through inferior olivary neuron activation of target neurons in the cerebellum, but the cellular mechanism is not yet known. Methods. Here, we have performed whole cell voltage-clamp and current clamp recordings from olivary neurons in brain slices derived from newborn rats. Results. We found that both transient low-voltage activated (LVA) and sustained high voltage-activated (HVA) Ca2+ currents are significantly attenuated by 0.125 – 0.25 mM harmaline applied to the bath and that this attenuation is partially reversible. In current clamp recordings, spike-afterhyperpolarization complexes were evoked by brief positive current injections. Harmaline produced a small attenuation of spike amplitude, but large spike broadening associated with attenuation of the fast and medium afterhyperpolarization. Conclusion. Our data suggest that one mode of olivary neuron activation by harmaline involves attenuation of both HVA and LVA Ca2+ conductances and consequent attenuation of Ca2+-sensitive K+ conductances resulting in spike broadening and attenuation of the afterhyperpolarization. Both of HVA and LVA attenuation also suggests a role to regulate intracelluar Ca2+, thereby to protect neurons from apoptosis. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jonathan I. Benichov ◽  
Daniela Vallentin

AbstractVocal turn-taking is a fundamental organizing principle of human conversation but the neural circuit mechanisms that structure coordinated vocal interactions are unknown. The ability to exchange vocalizations in an alternating fashion is also exhibited by other species, including zebra finches. With a combination of behavioral testing, electrophysiological recordings, and pharmacological manipulations we demonstrate that activity within a cortical premotor nucleus orchestrates the timing of calls in socially interacting zebra finches. Within this circuit, local inhibition precedes premotor neuron activation associated with calling. Blocking inhibition results in faster vocal responses as well as an impaired ability to flexibly avoid overlapping with a partner. These results support a working model in which premotor inhibition regulates context-dependent timing of vocalizations and enables the precise interleaving of vocal signals during turn-taking.


2020 ◽  
Vol 126 ◽  
pp. 104870
Author(s):  
Julie M. Butler ◽  
Erandi M. Herath ◽  
Arohan Rimal ◽  
Sarah M. Whitlow ◽  
Karen P. Maruska

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