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Neurons generate action potentials resulting from changes in the electric membrane potential. Neurons can generate multiple action potentials in sequence forming so-called spike trains. These spike trains are the basis for neural coding and information transfer in the brain.
Myelinated axons only allow action potentials to occur at the unmyelinated nodes of Ranvier that occur between the myelinated internodes. It is by this restriction that saltatory conduction propagates an action potential along the axon of a neuron at rates significantly higher than would be possible in unmyelinated axons (150 m/s compared from 0.5 to 10 m/s). [1]
Nav1.6 has been identified in the dendrites of hippocampal CA1 neurons that generate dendritic spikes; the density of Nav1.6 in these neurons is 35-80 times lower than in the initial segments of axons. [7] Distribution of voltage-gated sodium channels along the dendritic membrane plays a crucial role in a dendrite's ability to propagate a signal.
[42] [43] Stochasticity in neurons has two important sources. First, even in a very controlled experiment where input current is injected directly into the soma, ion channels open and close stochastically [44] and this channel noise leads to a small amount of variability in the exact value of the membrane potential and the exact timing of ...
These up-and-down cycles are known as action potentials. In some types of neurons, the entire up-and-down cycle takes place in a few thousandths of a second. In muscle cells, a typical action potential lasts about a fifth of a second. In plant cells, an action potential may last three seconds or more. [4]
Basic ways that neurons can interact with each other when converting input to output. Summation, which includes both spatial summation and temporal summation, is the process that determines whether or not an action potential will be generated by the combined effects of excitatory and inhibitory signals, both from multiple simultaneous inputs (spatial summation), and from repeated inputs ...
Neuronal activity at the microscopic level has a stochastic character, with atomic collisions and agitation, that may be termed "noise." [4] While it isn't clear on what theoretical basis neuronal responses involved in perceptual processes can be segregated into a "neuronal noise" versus a "signal" component, and how such a proposed dichotomy could be corroborated empirically, a number of ...
The sparse code is when each item is encoded by the strong activation of a relatively small set of neurons. For each item to be encoded, this is a different subset of all available neurons. In contrast to sensor-sparse coding, sensor-dense coding implies that all information from possible sensor locations is known.