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Bistable Neuron |
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Bistable Neuron Description
Bistable neurons are similar to the flip-flop devices used in electronic circuitry for RAM memory. The brain does not use
these types of neurons to store binary information. But they are a simple form of memory that is used in the brain. A bistable neuron
has two stable states that it can switch between. Typically these states are
quiescence and tonic bursting. It switches between the states when it receives a current stimulus that is sufficient to push it over into
the new state. Just as in the pacemaker neuron, bistability arises through some complex dynamical interactions between the various currents that
enter the cell. Understanding all of those dynamics is beyond the scope of this discussion and the the bistable neuron essentially abstracts
away these complex dynamics. It does not use a complicated set of differential equations to produce its bistability. This has good points and
bad points. On the plus side, it greatly reduces the complexity of the system and reduces what users need to understand in order to use it. Also,
since we are not using sets of differential equations, but instead are using a simple algorithm, it means that this model can run much more quickly.
On the minus side you are eliminating the rich detail that it is possible to get by using the differential equations to specify this type of behavior.
But since the goal behind these neural models is to be as fast as possible while still retaining as many of the core biological concepts, using
an algorithmic approach makes sense in this case. If you really want to be able to specify the indiviudal equations for each ion channel then you
will need to wait until we add a new neural plug-in that allows you to do this, or add your own. We currently have plans to another plug-in
that would allow you to do just that, but it is still a little ways off. Bistable Neuron PropertiesThe bistable neuron has all of the properties associated with a regular neuron: Cm, Gm, Vth, Fmin, and Gain. For a description of them please see the text that discusses the normal neuron. The properties that are unique for the pacemaker are listed below with a description of each. IhThe high current that is switched on when the membrane voltage of the cell exceeds Vsth. This should be sufficient to keep the voltage above the switch threshold. Default value: 10 na. Acceptable range:Any Value. Il The low current that is switched on when the membrane voltage of the cell falls below Vsth. This should be low enough to ensure that the voltage does not exceed the switch threshold. Default value: 0 na. Acceptable range:Any Value. Vsth The switch voltage threshold value. When the membrane voltage exceeds this value the Ih current is turned on. When the membrane voltage is below this value the Il current is turned on. Default value: 10 mv. Acceptable range:Any Value. Bistable Neuron Output
Figure 2 shows the output from a bistable neuron. At 2 seconds 3 na of current is injected into the neuron
causing its membrane voltage to go above 10 Bistable Neuron OverviewBistable neurons provide you with a simple form of binary memory for use in your neural circuits. These types of neurons are found in real living systems, but they are not used in the same way that electrical circuit designers use them to store binary numbers. One of the more basic functions that these neurons give you is a simple on/off form of memory. Has something happened or not? By connecting these these neurons to larger networks you can incorporate this type of memory into your neural designs. |
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