Neural backpropagation
Encyclopedia
Neural backpropagation is the phenomenon in which the action potential
of a neuron
creates a voltage spike both at the end of the axon
(normal propagation) and back through to the dendritic arbor or dendrites, from which much of the original input current originated. It has been shown that this simple process can be used in a manner similar to the backpropagation
algorithm used in multilayer perceptron
s, a type of artificial neural network
. In addition to active backpropagation the action potential, there is also passive electrotonic spread.
from synaptic activation are not large enough to activate the dendritic voltage-gated calcium channels (usually on the order of a couple milliAmps each) so backpropagation is believed to happen only when the cell is activated to fire an AP.
generate an action potential
, or voltage spike, that travels both through the axon
to signal the next neuron and backpropagates through the dendrites sending a retrograde signal to its presynaptic signaling neurons. This current decays significantly with travel length along the dendrites, so effects are predicted to be more significant for neurons whose synapses are near the postsynaptic cell body, with magnitude depending mainly on sodium-channel density in the dendrite. It is also dependent on the shape of the dendritic tree and, more importantly, on the rate of signal currents to the neuron. On average, a backpropagating spike loses about half its voltage after traveling nearly 500 micrometres.
Backpropagation occurs actively in the neocortex
, hippocampus
, substantia nigra
, and spinal cord
, while in the cerebellum
it occurs relatively passively. This is consistent with observations that synaptic plasticity
is much more apparent in areas like the hippocampus, which controls memory, than the cerebellum, which controls more unconscious and vegetative functions.
The backpropagating current also causes a voltage change that increases the concentration of Ca2+ in the dendrites, an event which coincides with certain models of synaptic plasticity. This change also affects future integration of signals, leading to at least a short-term response difference between the presynaptic signals and the postsynaptic spike.
Backpropagation is believed to help form LTP (long term potentiation) and Hebbian plasticity at hippocampal synapses. Since artificial LTP induction, using microelectrode stimulation, voltage clamp, etc. requires the postsynaptic cell to be slightly depolarized when EPSPs are elicited, backpropagation can serve as the means of depolarization of the postsynaptic cell.
algorithm. However, simple linear topologies have shown that effective computation is possible through signal backpropagation in this biological sense.
Action potential
In physiology, an action potential is a short-lasting event in which the electrical membrane potential of a cell rapidly rises and falls, following a consistent trajectory. Action potentials occur in several types of animal cells, called excitable cells, which include neurons, muscle cells, and...
of a neuron
Neuron
A neuron is an electrically excitable cell that processes and transmits information by electrical and chemical signaling. Chemical signaling occurs via synapses, specialized connections with other cells. Neurons connect to each other to form networks. Neurons are the core components of the nervous...
creates a voltage spike both at the end of the axon
Axon
An axon is a long, slender projection of a nerve cell, or neuron, that conducts electrical impulses away from the neuron's cell body or soma....
(normal propagation) and back through to the dendritic arbor or dendrites, from which much of the original input current originated. It has been shown that this simple process can be used in a manner similar to the backpropagation
Backpropagation
Backpropagation is a common method of teaching artificial neural networks how to perform a given task. Arthur E. Bryson and Yu-Chi Ho described it as a multi-stage dynamic system optimization method in 1969 . It wasn't until 1974 and later, when applied in the context of neural networks and...
algorithm used in multilayer perceptron
Multilayer perceptron
A multilayer perceptron is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate output. An MLP consists of multiple layers of nodes in a directed graph, with each layer fully connected to the next one. Except for the input nodes, each node is a...
s, a type of artificial neural network
Artificial neural network
An artificial neural network , usually called neural network , is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes...
. In addition to active backpropagation the action potential, there is also passive electrotonic spread.
Mechanism
When a neuron fires an action potential, it is initiated at the axon hillock. An action potential spreads down the axon because of the gating properties of voltage-gated sodium channels and voltage-gated potassium channels. However, the cell body or soma can also become depolarized when an AP is initiated, and this depolarization can spread out to the dendritic tree where there are voltage-gated calcium channels. Voltage-gated calcium channels can then lead to a propagating (most of the time) dendritic action potential. EPSPsExcitatory postsynaptic potential
In neuroscience, an excitatory postsynaptic potential is a temporary depolarization of postsynaptic membrane potential caused by the flow of positively charged ions into the postsynaptic cell as a result of opening of ligand-sensitive channels...
from synaptic activation are not large enough to activate the dendritic voltage-gated calcium channels (usually on the order of a couple milliAmps each) so backpropagation is believed to happen only when the cell is activated to fire an AP.
History
Since the 1950s, evidence has existed that neurons in the central nervous systemCentral nervous system
The central nervous system is the part of the nervous system that integrates the information that it receives from, and coordinates the activity of, all parts of the bodies of bilaterian animals—that is, all multicellular animals except sponges and radially symmetric animals such as jellyfish...
generate an action potential
Action potential
In physiology, an action potential is a short-lasting event in which the electrical membrane potential of a cell rapidly rises and falls, following a consistent trajectory. Action potentials occur in several types of animal cells, called excitable cells, which include neurons, muscle cells, and...
, or voltage spike, that travels both through the axon
Axon
An axon is a long, slender projection of a nerve cell, or neuron, that conducts electrical impulses away from the neuron's cell body or soma....
to signal the next neuron and backpropagates through the dendrites sending a retrograde signal to its presynaptic signaling neurons. This current decays significantly with travel length along the dendrites, so effects are predicted to be more significant for neurons whose synapses are near the postsynaptic cell body, with magnitude depending mainly on sodium-channel density in the dendrite. It is also dependent on the shape of the dendritic tree and, more importantly, on the rate of signal currents to the neuron. On average, a backpropagating spike loses about half its voltage after traveling nearly 500 micrometres.
Backpropagation occurs actively in the neocortex
Neocortex
The neocortex , also called the neopallium and isocortex , is a part of the brain of mammals. It is the outer layer of the cerebral hemispheres, and made up of six layers, labelled I to VI...
, hippocampus
Hippocampus
The hippocampus is a major component of the brains of humans and other vertebrates. It belongs to the limbic system and plays important roles in the consolidation of information from short-term memory to long-term memory and spatial navigation. Humans and other mammals have two hippocampi, one in...
, substantia nigra
Substantia nigra
The substantia nigra is a brain structure located in the mesencephalon that plays an important role in reward, addiction, and movement. Substantia nigra is Latin for "black substance", as parts of the substantia nigra appear darker than neighboring areas due to high levels of melanin in...
, and spinal cord
Spinal cord
The spinal cord is a long, thin, tubular bundle of nervous tissue and support cells that extends from the brain . The brain and spinal cord together make up the central nervous system...
, while in the cerebellum
Cerebellum
The cerebellum is a region of the brain that plays an important role in motor control. It may also be involved in some cognitive functions such as attention and language, and in regulating fear and pleasure responses, but its movement-related functions are the most solidly established...
it occurs relatively passively. This is consistent with observations that synaptic plasticity
Synaptic plasticity
In neuroscience, synaptic plasticity is the ability of the connection, or synapse, between two neurons to change in strength in response to either use or disuse of transmission over synaptic pathways. Plastic change also results from the alteration of the number of receptors located on a synapse...
is much more apparent in areas like the hippocampus, which controls memory, than the cerebellum, which controls more unconscious and vegetative functions.
The backpropagating current also causes a voltage change that increases the concentration of Ca2+ in the dendrites, an event which coincides with certain models of synaptic plasticity. This change also affects future integration of signals, leading to at least a short-term response difference between the presynaptic signals and the postsynaptic spike.
Functions
There are a number of hypotheses regarding the function of backpropagation of action potentials. In addition to synaptic plasticity, it is also hypothesized to be involved in dendrodendritic inhibition, boosting synaptic responses, resetting membrane potential, retrograde actions at synapses and conditional axonal output.Backpropagation is believed to help form LTP (long term potentiation) and Hebbian plasticity at hippocampal synapses. Since artificial LTP induction, using microelectrode stimulation, voltage clamp, etc. requires the postsynaptic cell to be slightly depolarized when EPSPs are elicited, backpropagation can serve as the means of depolarization of the postsynaptic cell.
Algorithm
While a backpropagating action potential can presumably cause changes in the weight of the presynaptic connections, there is no simple mechanism for an error signal to propagate through multiple layers of neurons, as in the computer backpropagationBackpropagation
Backpropagation is a common method of teaching artificial neural networks how to perform a given task. Arthur E. Bryson and Yu-Chi Ho described it as a multi-stage dynamic system optimization method in 1969 . It wasn't until 1974 and later, when applied in the context of neural networks and...
algorithm. However, simple linear topologies have shown that effective computation is possible through signal backpropagation in this biological sense.