Constructing functional models from biophysically-detailed neurons
Fig 2
Network used during osNEF training.
The top half of the figure is the “oracle” stream, where the desired filters and transformations are applied analytically, and where the target activities are generated. The bottom half of the figure is the “network” stream, where synaptic connections realize the desired filters and transformations, and where osNEF training is applied to update the relevant synaptic parameters. Both streams are driven by an input x (we omit all time-dependencies, such as x(t) and J(t), for brevity). Arrows represent the signal travelling through each stream. Boxes letters (filters h, weights w, transformations I, and decoders d) indicate mathematical operations being applied to the signal. The resulting quantities (spikes δ, synaptic currents J, synaptic conductances σ, and states x) are shown above the arrow. The pink numbers reference Table 1, which lists the operations that are applied at each step. Circled abbreviations indicate neural populations, which receive synaptic inputs and produce spikes. Coloration indicates ReLU neurons (gray) or detailed neurons (blue), parameters updated by osNEF’s online learning rules (orange) or offline synaptic optimization (green), references (pink), and NEF operations (gray).