The Neuronal Model and the Test of Experience

2021 ◽  
pp. 70-133
Keyword(s):  
2016 ◽  
Author(s):  
Daniele Quintella Mendes ◽  
Luís Alfredo V. Carvalho ◽  
Roseli S. Wedemann
Keyword(s):  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chialin Cheng ◽  
Surya A. Reis ◽  
Emily T. Adams ◽  
Daniel M. Fass ◽  
Steven P. Angus ◽  
...  

AbstractMutations in MAPT (microtubule-associated protein tau) cause frontotemporal dementia (FTD). MAPT mutations are associated with abnormal tau phosphorylation levels and accumulation of misfolded tau protein that can propagate between neurons ultimately leading to cell death (tauopathy). Recently, a p.A152T tau variant was identified as a risk factor for FTD, Alzheimer's disease, and synucleinopathies. Here we used induced pluripotent stem cells (iPSC) from a patient carrying this p.A152T variant to create a robust, functional cellular assay system for probing pathophysiological tau accumulation and phosphorylation. Using stably transduced iPSC-derived neural progenitor cells engineered to enable inducible expression of the pro-neural transcription factor Neurogenin 2 (Ngn2), we generated disease-relevant, cortical-like glutamatergic neurons in a scalable, high-throughput screening compatible format. Utilizing automated confocal microscopy, and an advanced image-processing pipeline optimized for analysis of morphologically complex human neuronal cultures, we report quantitative, subcellular localization-specific effects of multiple kinase inhibitors on tau, including ones under clinical investigation not previously reported to affect tau phosphorylation. These results demonstrate the potential for using patient iPSC-derived ex vivo models of tauopathy as genetically accurate, disease-relevant systems to probe tau biochemistry and support the discovery of novel therapeutics for tauopathies.


2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Alessandra Lucchetti ◽  
Mogens H. Jensen ◽  
Mathias L. Heltberg

2006 ◽  
Vol 929 (1) ◽  
pp. 152-165 ◽  
Author(s):  
STANISLAS DEHAENE ◽  
MICHEL KERSZBERG ◽  
JEAN-PIERRE CHANGEUX

2002 ◽  
Vol 17 (S3) ◽  
pp. S49-S62 ◽  
Author(s):  
Jerrold L. Vitek
Keyword(s):  

2018 ◽  
Vol 32 (28) ◽  
pp. 1850308
Author(s):  
Shi-Dong Liang ◽  
Haoqi Li ◽  
Yuefan Deng

The neuronal dynamics plays an important role in understanding the neurological phenomena. We study the mechanism of the dynamic phase transition and its Lyapunov stability of a single Hindmarsh–Rose (HR) neuronal model. We propose an index [Formula: see text] to express the dynamical phase of the HR neurons. When [Formula: see text] the neuron is in the pure resting state, and when [Formula: see text] the neuron closes to the pure spiking phase, while when [Formula: see text] the neuron runs in the bursting phase. Based on this method, we investigate numerically the phase diagram of the HR neuronal model in the parameter space. We find that two mechanisms governed the HR neuronal dynamic phase transition, the phase transition and crossover transition in the different regions of the parameter space. Moreover, we analyze the equilibrium point stability of the HR neuronal model based on the Lyapunov stability method. We study the synchronous stability of the HR neuronal network based on the master stability function method and give the phase diagrams of the maximum Lyapunov exponents in the parameter space of networks. The regions of the synchronous stabilities in the parameter space depend on the couplings of the HR neurons of the membrane potential and the flux of the fast ion channel between the HR neurons. These results help to understand the HR neuronal dynamics and the synchronous stability of the HR neuronal networks.


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