Neuron synchronization mathematical phenomenology

1999 ◽  
Author(s):  
M. Balduzzo ◽  
F. Ferro Milone ◽  
T.A. Minelli ◽  
L. Turicchia
Keyword(s):  
Neuron Synchronization

scholarly journals Dopamine and GPCR-mediated modulation of DN1 clock neurons gates the circadian timing of sleep

2021 ◽  
Author(s):  
Matthias Schlichting ◽  
Shlesha Richhariya ◽  
Nicholas Herndon ◽  
Dingbang Ma ◽  
Jason Xin ◽  
...  
Keyword(s):  
G Protein Coupled Receptors ◽  
Sleep Regulation ◽  
Single Cell Sequencing ◽  
Sleep Timing ◽  
Clock Network ◽  
Sleep Centers ◽  
Neuron Synchronization ◽  
G Protein Coupled ◽  
Behavioral Screen

The metronome-like circadian regulation of sleep timing must still adapt to an uncertain environment. Recent studies in Drosophila indicate that neuromodulation not only plays a key role in clock neuron synchronization but also affects interactions between the clock network and brain sleep centers. We show here that the targets of neuromodulators, G-Protein Coupled Receptors (GPCRs), are highly enriched in the fly brain circadian clock network. Single cell sequencing indicates that they are not only differentially expressed but also define clock neuron identity. We generated a comprehensive guide library to mutagenize individual GPCRs in specific neurons and verified the strategy with a targeted sequencing approach. Combined with a behavioral screen, the mutagenesis strategy revealed a novel role of dopamine in sleep regulation by identifying two dopamine receptors and a clock neuron subpopulation that gate the timing of sleep.

Dynamics of Consciousness

2010 ◽  
Vol 24 (2) ◽  
pp. 141-148 ◽  
Author(s):  
F. T. Arecchi
Keyword(s):  
Degrees Of Freedom ◽  
Loss Rate ◽  
Deterministic Chaos ◽  
Collective State ◽  
Control Of Chaos ◽  
Time Control ◽  
Cognitive Problem ◽  
Neuron Synchronization ◽  
The Brain ◽  
Neuron Dynamics

The cognitive problem is how a given sensorial input elicits a decision. Since the neuron dynamics are affected by deterministic chaos, information is lost over the course of time. Control of chaos reduces such a loss rate by adding extra degrees of freedom. This addition is a change of code; such a recoding occurs on two time scales, namely, (A) the cognitive one (lasting up to 3 s), within which the brain reaches a collective state associated with a perception, and (B) the linguistic one (beyond 3 s), whereby memory retrieves different (A) units and compares them. In (A) the neurons are mutually coupled in large networks; collective synchronization of neuron arrays elicit decisions. In (B), different (A) slots are compared after retrieval. This requires a subject to be conscious of him/herself as well as that the pieces of the stream be correlated. While in (A) the neuron synchronization is described in dynamic terms, in (B) the slot comparison is formalized by an inverse Bayes rule. Distinction of (A), where coherent perceptions are built, from (B), where we formulate attributions of truth, recovers the fundamental philosophical difference between apprehension and judgment.

scholarly journals Nonlinear Dynamics of Controlled Synchronizations of Manipulator System

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Qingkai Han ◽  
Hao Zhang ◽  
Jinguo Liu
Keyword(s):  
Nonlinear Dynamics ◽  
Control Strategies ◽  
Adaptive Synchronization ◽  
State Variables ◽  
Motion Patterns ◽  
Joint Friction ◽  
Synchronization Errors ◽  
Robust Adaptive ◽  
The Stability ◽  
Neuron Synchronization

The nonlinear dynamics of the manipulator system which is controlled to achieve the synchronization motions is investigated in the paper. Firstly, the control strategies and modeling approaches of the manipulator system are given, in which the synchronization goal is defined by both synchronization errors and its derivatives. The synchronization controllers applied on the manipulator system include neuron synchronization controller, improved OPCL synchronization controller, and MRAC-PD synchronization controller. Then, an improved adaptive synchronized control strategy is proposed in order to estimate online the unknown structure parameters and state variables of the manipulator system and to realize the needed synchronous compensation. Furthermore, a robust adaptive synchronization controller is also researched to guarantee the dynamic stability of the system. Finally, the stability of motion synchronizations of the manipulator system possessing nonlinear component is discussed, together with the effect of control parameters and joint friction and others. Some typical motions such as motion bifurcations and the loss of synchronization of it are obtained and illustrated as periodic, multiperiodic, and/or chaotic motion patterns.

Neuron synchronization in the rat gracilis nucleus facilitates sensory transmission in the somatosensory pathway

2009 ◽  
Vol 30 (4) ◽  
pp. 593-601 ◽  
Author(s):  
Eduardo Malmierca ◽  
Nazareth P. Castellanos ◽  
Alberto Nuñez-Medina ◽  
Valeri A. Makarov ◽  
Angel Nuñez
Keyword(s):  
Sensory Transmission ◽  
Somatosensory Pathway ◽  
Neuron Synchronization
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