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As can be seen, the neuron is not selective.
Hereby, upon repeated presentation of a stimulus, the response of the neuron is not perfectly reproducible but exhibits trial-to-trial variability.
Each neuron is not only a microprocessor but also a chemical factory, producing chemicals needed to transmit the message at the connection between two neurons.
Using STAs rather than signals with a specific frequency is necessary for our setting, since the dynamics of the quiescent neuron is not associated with a specific intrinsic frequency.
Although, characteristic events in a raster plot are spikes (neuron fires), it is useful in subsequent developments to consider also the case when neuron is not firing ( ω k ( n ) = 0 ).
Our results show that the magnetic field several centimeters from the centre of the neuron is well approximated by a dipole source, but the field close to the neuron is not, a finding particularly important for understanding the possible contrast mechanism underlying the use of MRI to detect and locate these currents.
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The length, branching, and number of primary dendrites per neuron were not significantly altered upon Lpd knockdown (data not shown).
In the first trial, the neuron was not able to fire spikes because it was strongly inhibited by Purkinje cells.
Unfortunately, like the α-cell, the signaling pathways used by the GI neuron are not well understood.
This arises because the identities of both the presynaptic and the postsynaptic neuron are not usually known.
In other words, having infinitely many neurons is not a sufficient condition for getting independence, because also infinite connections per neuron are required.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com