Sentence examples for behavior of neuron populations from inspiring English sources
Finally, Chizhov and Graham [64] have recently proposed a new method based on a population density approach allowing to characterize the mesoscopic behavior of neuron populations in conductance-based models.
The potential jump size is h = 5, the coupling parameter— J = 3 and the basic current— I b = − 1. Single neuron models such as the LIF or the QIF models have a weak electrophysiological basis, but thanks to their simplicity, they are quite useful for simulations of the behavior of populations of neurons.
Despite all its qualities, this approach implicitly makes the assumption that the effect of noise vanishes at the mesoscopic and macroscopic scales and hence that the behavior of such populations of neurons is deterministic.
Macromolecules drive the complex behavior of neurons.
Dr. George has studied the behavior of neurons with a sodium-channel defect that occurs in a certain type of inherited epilepsy.
Future research is needed to directly examine the role of different vagal afferent neuron populations in anxiety-like behavior.
Identification of spatiotemporal interactions within/between neuron populations is critical for detection and characterization of large-scale neuronal interactions underlying perception, cognition, and behavior.
The vomeronasal organ is strongly implicated in the display of sexual and reproductive behaviors in female mice, yet the roles that apical and basal vomeronasal neuron populations play in controlling these gender-specific behaviors remain largely unclear.
IBM makes neuromorphic chips by using collections of 6,000 transistors to emulate the electrical spiking behavior of a neuron and then wiring those silicon neurons together.
In contrast to previous single neurons studies where behaviors were tailored to best drive a given neuron (e.g., preferred and anti-preferred saccade direction), another novelty of the task resides in the fact that we used a fixed and finite set of oculomotor behaviors to drive neuronal populations as a whole.
The population density approach leading to partial differential equations is suited for very large populations of neurons; we think that mathematical studies on the qualitative behavior of population density models may help for the choice of the particular single neuron model used to describe the internal state of the neurons of the population, and give insights on the results.
