Python source | JSON | Reconstructed source
An example with four Nodes, as in other environments.
Python source | JSON | Reconstructed source
A three-Node example with Conditions.
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The same model as in SimpleLinear-conditional with Conditions for timeline scheduling. Note: these conditions are still not fully implemented by the scheduler.
Python source | JSON | Reconstructed source
A model with several Nodes in two Graphs, one of which contains the other.
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A similar model as in Nested without scheduling with Conditions.
Python source | JSON | Reconstructed source
An example with a single Node using the PsyNeuLink implementation of the FitzHugh–Nagumo model.
Python source | JSON | Reconstructed source
The same model as in SimpleFN with Conditions for timeline scheduling. Note: these conditions are still not fully implemented by the scheduler.
Python source | JSON | Reconstructed source
The same model in SimpleFN with scheduling Conditions that mimic the behavior in SimpleFN-timing.
Python source | JSON | Reconstructed source
A model representing the Stroop effect with conflict monitoring that uses Conditions.