Difference between revisions of "NeuronConnectionsResearch"
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* connection is made between two neurons | * connection is made between two neurons | ||
| − | + | ** connection is uni-directional | |
| − | + | ** source of connection is always axon branch of first neuron | |
| − | + | ** target of connection can be dendrite, soma or initial axon segment of second neuron | |
| − | + | ** axon-axon connections are usually ignored in neural network models | |
* axon-dendrite connection elements are: | * axon-dendrite connection elements are: | ||
| − | + | ** neuron1 soma | |
| − | + | ** neuron1 initial axon segment | |
| − | + | ** neuron1 axon trunk (myelinated) | |
| − | + | ** neuron1 axon branchX | |
| − | + | ** neuron1 axon branchX terminal | |
| − | + | ** inter-neuron space (synaptic cleft) | |
| − | + | ** receptors of post-synaptic cell membrane on spine of neuron2 dendrite | |
| − | + | ** neuron2 dendrite trunk | |
| − | + | ** neuron2 soma | |
* there are two types of synapses, electrical and chemical | * there are two types of synapses, electrical and chemical | ||
| − | + | ** '''electrical synapse''' - protein junction forms hole between axon terminal and post-synaptic neuron membranes, allowing the electrical signal to pass directly from one cell to another; | |
| − | + | ** electrical synapse is much faster than chemical synapse, but unlike chemical synapse, cannot be regulated or controlled | |
| − | + | ** '''chemical synapses''' may be regulated and are affected by methamphetamine, signals always travel from presynaptic membrane, through synaptic cleft, and to postsynaptic membrane | |
== Connection dynamics == | == Connection dynamics == | ||
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* when signal propagates through connection | * when signal propagates through connection | ||
* when action potential encounters fire state (Hebb's learning), e.g.: | * when action potential encounters fire state (Hebb's learning), e.g.: | ||
| − | + | ** just after firing there is negative potential in all dendrites | |
| − | + | ** which electically attracts axon terminal having positive action potential | |
| − | + | ** while firing is impossible (refractory period) and action potential energy is spent for increasing connectivity factor | |
* using interneurons and non-neuron interneuron matter (glia) | * using interneurons and non-neuron interneuron matter (glia) | ||
* using complex structures as controllers (bump attractors and so on) | * using complex structures as controllers (bump attractors and so on) | ||
Revision as of 10:50, 16 June 2015
Neural Connections Research
@@Home -> NeuralNetworksResearch -> NeuronConnectionsResearch
What are connections
- connection is made between two neurons
- connection is uni-directional
- source of connection is always axon branch of first neuron
- target of connection can be dendrite, soma or initial axon segment of second neuron
- axon-axon connections are usually ignored in neural network models
- axon-dendrite connection elements are:
- neuron1 soma
- neuron1 initial axon segment
- neuron1 axon trunk (myelinated)
- neuron1 axon branchX
- neuron1 axon branchX terminal
- inter-neuron space (synaptic cleft)
- receptors of post-synaptic cell membrane on spine of neuron2 dendrite
- neuron2 dendrite trunk
- neuron2 soma
- there are two types of synapses, electrical and chemical
- electrical synapse - protein junction forms hole between axon terminal and post-synaptic neuron membranes, allowing the electrical signal to pass directly from one cell to another;
- electrical synapse is much faster than chemical synapse, but unlike chemical synapse, cannot be regulated or controlled
- chemical synapses may be regulated and are affected by methamphetamine, signals always travel from presynaptic membrane, through synaptic cleft, and to postsynaptic membrane
Connection dynamics
- connection can be stronger or weaker, thus having connectivity factor (see Jeff Hawkins)
- above certain connectivity factor threshold connection allows signal propagation, when presynaptic signal (action potential) produces post-synaptic signal
- below threshold connection still exists, because activity in both neurons affects connectivity factor
- connectivity factor differs from connection weight of classical neural networks, as weight always produces output which depends on weight value; connectivity factor is continuous, but its effect is binary
When connection is enforced
- Options under consideration*:
- when signal propagates through connection
- when action potential encounters fire state (Hebb's learning), e.g.:
- just after firing there is negative potential in all dendrites
- which electically attracts axon terminal having positive action potential
- while firing is impossible (refractory period) and action potential energy is spent for increasing connectivity factor
- using interneurons and non-neuron interneuron matter (glia)
- using complex structures as controllers (bump attractors and so on)
