scholarly journals High-fidelity optical reporting of neuronal electrical activity with an ultrafast fluorescent voltage sensor

2014 ◽  
Vol 17 (6) ◽  
pp. 884-889 ◽  
Author(s):  
François St-Pierre ◽  
Jesse D Marshall ◽  
Ying Yang ◽  
Yiyang Gong ◽  
Mark J Schnitzer ◽  
...  
Keyword(s):  
Electrical Activity ◽  
Voltage Sensor ◽  
High Fidelity ◽  
Neuronal Electrical Activity

Direct detection of optogenetically evoked oscillatory neuronal electrical activity in rats using SLOE sequence

NeuroImage ◽  
2016 ◽  
Vol 125 ◽  
pp. 533-543 ◽  
Author(s):  
Yuhui Chai ◽  
Guoqiang Bi ◽  
Liping Wang ◽  
Fuqiang Xu ◽  
Ruiqi Wu ◽  
...  
Keyword(s):  
Electrical Activity ◽  
Direct Detection ◽  
Neuronal Electrical Activity

Spontaneous Electromagnetic Induction Modulating the Neuronal Dynamical Response

2019 ◽  
Vol 29 (01) ◽  
pp. 1950005 ◽  
Author(s):  
Rong Wang ◽  
Peihua Feng ◽  
Yongchen Fan ◽  
Ying Wu
Keyword(s):  
Electrical Activity ◽  
Electromagnetic Induction ◽  
Dynamic Properties ◽  
Oscillation Amplitude ◽  
Stable Limit Cycle ◽  
Dynamical Response ◽  
Stable Limit ◽  
External Stimulation ◽  
Brain Functions ◽  
Neuronal Electrical Activity

Spontaneous electromagnetic induction originating from neuronal electrical activity is believed to reflect the memory ability in the neural system and significantly modulates neural information transmission, but its fundamental effect on the neuronal dynamic properties is still not well understood. In this paper, we use a memristor to couple neuronal electrical activity and magnetic fields and study how the spontaneous electromagnetic induction modulates the neuronal dynamical response to external stimulation. It is found that the negative feedback of electromagnetic induction on the neuron significantly reduces the dynamical response range, decreases the oscillation amplitude and induces a higher firing frequency. Meanwhile, the memory effect on electromagnetic induction can induce two kinds of bistability, including the coexistence of a stable limit cycle and a fixed point, and the coexistence of two stable limit cycles. Furthermore, high electric driving for electromagnetic induction produces complex firing patterns with single, double and multiple frequencies. Our results not only further confirm the efficacy of spontaneous electromagnetic induction in modulating the neuronal dynamical properties but also provide insights into the possibilities of choosing suitable parameter spaces in studying the effects of external magnetic induction on brain functions.

scholarly journals The influence of neuronal electrical activity on the mammalian central clock metabolome

Metabolomics ◽  
2018 ◽  
Vol 14 (10) ◽  
Author(s):  
M. Renate Buijink ◽  
Michel van Weeghel ◽  
M. Can Gülersönmez ◽  
Amy C. Harms ◽  
Jos H. T. Rohling ◽  
...  
Keyword(s):  
Electrical Activity ◽  
Central Clock ◽  
Neuronal Electrical Activity

scholarly journals Direct magnetic resonance detection of neuronal electrical activity

2006 ◽  
Vol 103 (43) ◽  
pp. 16015-16020 ◽  
Author(s):  
N. Petridou ◽  
D. Plenz ◽  
A. C. Silva ◽  
M. Loew ◽  
J. Bodurka ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Electrical Activity ◽  
Resonance Detection ◽  
Neuronal Electrical Activity

scholarly journals Neuronal Synchronization of Electrical Activity, Using the Hodgkin-Huxley Model and RCLSJ Circuit

2016 ◽  
Vol 12 (23) ◽  
pp. 93-106 ◽  
Author(s):  
Jose A. Díaz M. ◽  
Oscar Téquita ◽  
Fernando Naranjo
Keyword(s):  
Electrical Activity ◽  
Josephson Junction ◽  
Action Potentials ◽  
Josephson Junctions ◽  
Lyapunov Functions ◽  
Neuronal Networks ◽  
Neuronal Dynamics ◽  
Neuronal Synchronization ◽  
Brain Behavior ◽  
Neuronal Electrical Activity

We simulated the neuronal electrical activity using the Hodgkin-Huxleymodel (HH) and a superconductor circuit, containing Josephson junctions. These HH model make possible simulate the main neuronal dynamics characteristics such as action potentials, firing thres hold and refractory period.The purpose of the manuscript is show a method to syncronize a RCL-shunted Josephson junction to a neuronal dynamics represented by the HH model. Thus the RCLSJ circuit is able to mimics the behavior of the HH neuron. We controlated the RCLSJ circuit, using and improved adaptative track scheme, that with the improved Lyapunov functions and thetwo controllable gain coefficients allowing synchronization of two neuronal models. Results will provide the path to follow forward the understanding neuronal networks synchronization about, generating the intrinsic brain behavior.

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