Sentence examples for generation of action potential from inspiring English sources

The mathematical modeling of the determination of the expected time for the generation of action potential in the nerve cells by random synaptic inputs in dendrites includes a general boundary-value problem for singularly perturbed differential difference equation with shifts.

However, it is combined with lumped models for the generation of action potential activity from PPPs and slow EPSPs.

The aim of the current study was to test whether the properties of HFP and LFB neurons recorded extracellularly in the primate GPe are linked to cellular mechanisms underlying the generation of action potential (AP) firing.

Generation of action potential has also been shown in several non-neuronal cells including pituitary endocrine [ 135], adrenocortical [ 136], pancreatic beta [ 137], osteoblastic [ 138], as well as chromaffin cells [ 139].

In this way, they are crucial players for the generation of action potentials in excitable cells.

Voltage-gated sodium channels (VGSCs) are critical for the generation of action potentials (APs) in these neurons.

Depolarization block is a state of silence at membrane potentials more depolarized than those that support the generation of action potentials, also called spikes.

Spatio-temporally clustered postsynaptic potentials (PSP, green) can give rise to NMDA-spikes (red) which superimpose additively in the soma (blue) controlling the generation of action potentials (AP).

FC has been employed in neuroscience to characterize the generation of action potentials and spiking patters but also in characterizing bio-systems (e.g. vegetable tissues).

The generation of action potentials is regulated by internal drivers (e.g., the active gating variables of the neuron) as well as exogenous factors like excitatory and inhibitory synaptic conductances produced by pools of connected neurons.

From the cellular mechanisms of synaptic transmission and the generation of action potentials, to interactions among networks of neurons, and to the high-level processes of perception and memory, computational models provide new sources of insight into the complex machinery that underlies human behavior.