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Jeffress' model proposes that two signals even from an asynchronous arrival of sound in the cochlea of each ear will converge synchronously on a coincidence detector in the auditory cortex based on the magnitude of the ITD (Fig. 2). Therefore, the ITD should correspond to an anatomical map that can be found within the brain.
In neurobiology, the length constant (λ) is a mathematical constant used to quantify the distance that a graded electric potential will travel along a neurite via passive electrical conduction. The greater the value of the length constant, the further the potential will travel.
If the time constant of the cell membrane is sufficiently long, as is the case for the cell body, then the amount of summation is increased. [6] The amplitude of one postsynaptic potential at the time point when the next one begins will algebraically summate with it, generating a larger potential than the individual potentials.
The higher the axoplasmic resistance, , the smaller the value of , the harder it will be for current to travel through the axoplasm, and the shorter the current will be able to travel. It is possible to solve equation ( 12 ) and arrive at the following equation (which is valid in steady-state conditions, i.e. when time approaches infinity):
Molecular neuroscience is a branch of neuroscience that observes concepts in molecular biology applied to the nervous systems of animals. The scope of this subject covers topics such as molecular neuroanatomy, mechanisms of molecular signaling in the nervous system, the effects of genetics and epigenetics on neuronal development, and the molecular basis for neuroplasticity and ...
Neurogenetics is a field that is rapidly expanding and growing. The current areas of research are very diverse in their focuses. One area deals with molecular processes and the function of certain proteins, often in conjunction with cell signaling and neurotransmitter release, cell development and repair, or neuronal plasticity.
“The one thing Kylie makes me do is trash,” said Jason, 37. “Like, that is firmly my job, and I suck at it. I miss it all the time because we're traveling right now, but I try to really stay ...
For input () that changes over time or is far away from the bifurcation point, it is preferable to work with the exponential integrate-and-fire model (if one wants to stay in the class of one-dimensional neuron models), because real neurons exhibit the nonlinearity of the exponential integrate-and-fire model.