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README.md
README.md
 
 
SimpleBranching-conditional.json
SimpleBranching-conditional.json
 
 
SimpleBranching-conditional.py
SimpleBranching-conditional.py
 
 
SimpleBranching-conditional.reconstructed.py
SimpleBranching-conditional.reconstructed.py
 
 
SimpleBranching-timing.json
SimpleBranching-timing.json
 
 
SimpleBranching-timing.py
SimpleBranching-timing.py
 
 
SimpleBranching-timing.reconstructed.py
SimpleBranching-timing.reconstructed.py
 
 
SimpleFN-conditional.json
SimpleFN-conditional.json
 
 
SimpleFN-conditional.py
SimpleFN-conditional.py
 
 
SimpleFN-conditional.reconstructed.py
SimpleFN-conditional.reconstructed.py
 
 
SimpleFN-timing.json
SimpleFN-timing.json
 
 
SimpleFN-timing.py
SimpleFN-timing.py
 
 
SimpleFN-timing.reconstructed.py
SimpleFN-timing.reconstructed.py
 
 
SimpleFN.json
SimpleFN.json
 
 
SimpleFN.py
SimpleFN.py
 
 
SimpleFN.reconstructed.py
SimpleFN.reconstructed.py
 
 
SimpleLinear-conditional.json
SimpleLinear-conditional.json
 
 
SimpleLinear-conditional.py
SimpleLinear-conditional.py
 
 
SimpleLinear-conditional.reconstructed.py
SimpleLinear-conditional.reconstructed.py
 
 
SimpleLinear-timing.json
SimpleLinear-timing.json
 
 
SimpleLinear-timing.py
SimpleLinear-timing.py
 
 
SimpleLinear-timing.reconstructed.py
SimpleLinear-timing.reconstructed.py
 
 
generate_json_and_scripts.py
generate_json_and_scripts.py
 
 
model_ABCD.json
model_ABCD.json
 
 
model_ABCD.py
model_ABCD.py
 
 
model_ABCD.reconstructed.py
model_ABCD.reconstructed.py
 
 
model_nested_comp_with_scheduler.json
model_nested_comp_with_scheduler.json
 
 
model_nested_comp_with_scheduler.py
model_nested_comp_with_scheduler.py
 
 
model_nested_comp_with_scheduler.reconstructed.py
model_nested_comp_with_scheduler.reconstructed.py
 
 
model_with_nested_graph.json
model_with_nested_graph.json
 
 
model_with_nested_graph.py
model_with_nested_graph.py
 
 
model_with_nested_graph.reconstructed.py
model_with_nested_graph.reconstructed.py
 
 
stroop_conflict_monitoring.json
stroop_conflict_monitoring.json
 
 
stroop_conflict_monitoring.py
stroop_conflict_monitoring.py
 
 
stroop_conflict_monitoring.reconstructed.py
stroop_conflict_monitoring.reconstructed.py
 
 

README.md

Interactions between PsyNeuLink and MDF

Simple

ABCD

Python source | JSON | Reconstructed source

An example with four Nodes, as in other environments.

SimpleLinear

SimpleLinear-conditional

Python source | JSON | Reconstructed source

A three-Node example with Conditions.

SimpleLinear-timing

Python source | JSON | Reconstructed source

The same model as in SimpleLinear-conditional with Conditions for timeline scheduling. Note: these conditions are still not fully implemented by the scheduler.

Nested

Nested without scheduling

Python source | JSON | Reconstructed source

A model with several Nodes in two Graphs, one of which contains the other.

Nested with scheduling

Python source | JSON | Reconstructed source

A similar model as in Nested without scheduling with Conditions.

SimpleFN

Python source | JSON | Reconstructed source

An example with a single Node using the PsyNeuLink implementation of the FitzHugh–Nagumo model.

SimpleFN-timing

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.

SimpleFN-conditional

Python source | JSON | Reconstructed source

The same model in SimpleFN with scheduling Conditions that mimic the behavior in SimpleFN-timing.

Stroop

Python source | JSON | Reconstructed source

A model representing the Stroop effect with conflict monitoring that uses Conditions.