NeuroElectro Publications

Article: Hebbian Wiring Plasticity Generates Efficient Network Structures for Robust Inference with Synaptic Weight Plasticity.

Full Text (publisher's website) ; Article Metadata ; Article Data (extracted)
Hiratani N; Fukai T
Front Neural Circuits, 2016

Table 1

Definitions of main variables and parameters.

Name	Description	Definition
st	Hidden external state at time t	Section Details of Simulation
rX,jt	Firing rate of input neuron j at time t	Equation (5)
rY,it	Firing rate of output neuron i at time t	Equation (1)
wij	Synaptic weight from input neuron i to output neuron j	Constant (Figures 1–3)Equation (2) (Figures 4–8)
cij	Number of connection from input neuron i to output neuron j (Note that here cij = 0 or 1)	Section Synaptic Connection Learning
ρij	Connection probability from input neuron i to output neuron j	Constant (Figures 1–4)Equation (3) (Figures 5, 6)Equation (4) (Figures 6I, 7, 8)
	The dual Hebbian rule	Equation (2) + Equation (3)
	The approximated dual Hebbian rule	Equation (2) + Equation (4)
θjμ	Response parameter of neuron j to hidden state μ	Section Gaussian Model, Poisson Model
qjμ	Normalized response parameter of neuron j to hidden state μ. Especially in the Gaussian model, qjμ = θjμ/σX2	qjμ = h(θjμ)
Ωμ	Set of output neurons that selective for hidden state μ	Section Accuracy of Estimation
hw	Input threshold	Section Details of Simulation
σX	Noise in input neuron firing rate	σX = 1.0
γ	Parameter for sparseness of connectivity	Sections Weight Coding and Connectivity Coding and Dual Coding and Cut-Off Coding
bh	Strength of homeostatic plasticity	Equation (2)
τc	Timescale of rewiring	Section Synaptic Connection Learning
κm	Ratio between constant and variable component in θjμ	θjμ = 1Z[κmθjμconst+(1-κm)θjμvar]
θconst, θvar	Two component of input structures used in Figure 6	Section Gaussian Model
T2	Interval between update of the variable component θvar	T2 = 105
θctrl,θtraining	Two input structures used for modeling control and training phases in Figure 8	Section Gaussian Model

Inferred neuron-electrophysiology data values

Neuron Type	Neuron Description	Ephys Prop	Extracted Value	Standardized Value	Content Source