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Neural backpropagation is the phenomenon in which, after the action potential of a neuron creates a voltage spike down the axon (normal propagation), another impulse is generated from the soma and propagates towards the apical portions of the dendritic arbor or dendrites (from which much of the original input current originated).
In neuroscience, retrograde signaling (or retrograde neurotransmission) refers more specifically to the process by which a retrograde messenger, such as anandamide or nitric oxide, is released by a postsynaptic dendrite or cell body, and travels "backwards" across a chemical synapse to bind to the axon terminal of a presynaptic neuron.
In machine learning, backpropagation is a gradient estimation method commonly used for training a neural network to compute its parameter updates.. It is an efficient application of the chain rule to neural networks.
Dendritic spikes most commonly propagate backwards from the soma to distal dendritic branches [citation needed]. Backward propagation serves a number of functions in the neuron, and these functions vary based on the type of neuron. In general, backward propagation serves to communicate output information to the postsynaptic membrane. [4]
The presynaptic neuron (top) releases a neurotransmitter, which activates receptors on the nearby postsynaptic cell (bottom). Ligand-gated ion channel showing the binding of transmitter (Tr) and changing of membrane potential (Vm)
These back-propagating action potentials depolarize the dendritic membrane and provide a crucial signal for synapse modulation and long-term potentiation. Back-propagation is not completely passive, but modulated by the presence of dendritic voltage-gated potassium channels.
1. Choose the right propagation method. Propagating plants via stem cuttings is less invasive than root division propagation and is the recommended method for winter propagation. Stem cuttings can ...
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