NeuronVarByName returns the index of the variable in the Neuron, or error.

BurstCtxt are projections from Superficial layers to Deep layers that send DeepBurst activations drive updating of DeepCtxt excitatory conductance, at end of a DeepBurst quarter.

BurstTRC are projections from Superficial layers to TRC (thalamic relay cell) neurons (e.g., in the Pulvinar) that send DeepBurst activation continuously during the DeepBurst quarter(s), driving the TRCBurstGe value, which then drives the plus-phase activation state of the TRC representing the "outcome" against which prior predictions are (implicitly) compared via the temporal difference in TRC activation state.

Deep are deep-layer neurons, reflecting activation of layer 6 regular spiking CT corticothalamic neurons, which drive both attention in Super (via DeepAttn projections) and predictions in TRC (Pulvinar) via standard projections.

DeepAttn are projections from Deep layers (representing layer 6 regular-spiking CT corticothalamic neurons) up to corresponding Superficial layer neurons, that drive the attentional modulation of activations there (i.e., DeepAttn and DeepLrn values).

The DeepLeabra layer types.

The DeepLeabra prjn types.

Super are superficial-layer neurons, which also compute DeepBurst activation as a thresholded version of superficial activation, and send that to both TRC (for plus phase outcome) and Deep layers (for DeepCtxt temporal context).

TRC are thalamic relay cell neurons, typically in the Pulvinar, which alternately reflect predictions driven by Deep layer projections, and actual outcomes driven by BurstTRC projections from corresponding Super layer neurons that provide strong driving inputs to TRC neurons.

DeepAttnParams are parameters determining how the DeepAttn and DeepLrn attentional modulation is computed from the AttnGe inputs received via DeepAttn projections.

DeepBurstParams are parameters determining how the DeepBurst activation is computed from the superficial layer activation values.

DeepCtxtParams are parameters determining how the DeepCtxt temporal context state is computed based on BurstCtxt projections from Super layers to Deep layers.

DeepTRCParams provides parameters for how the plus-phase (outcome) state of thalamic relay cell (e.g., Pulvinar) neurons is computed from the BurstTRC projections that drive TRCBurstGe excitatory conductance.

deep.Layer is the DeepLeabra layer, based on basic rate-coded leabra.Layer.

deep.Network has parameters for running a DeepLeabra network.

deep.Neuron holds the extra neuron (unit) level variables for DeepLeabra computation.

deep.Pool contains extra statistics used in DeepLeabra.

deep.Prjn is the DeepLeabra projection, based on basic rate-coded leabra.Prjn.

DeepLayer defines the essential algorithmic API for DeepLeabra at the layer level.

DeepPrjn defines the essential algorithmic API for DeepLeabra at the projection level.