Fig. 5
From: Challenging the point neuron dogma: FS basket cells as 2-stage nonlinear integrators
Reduction of multi-compartmental models into ANN abstractions. Two types of abstractions are examined: (a) a Linear ANN, in which the input from all dendrites (xi = number of synapses in dendrite i, N = number of dendrites) is linearly combined at the cell body and (b) a two-layer modular ANN, in which the input is fed into two parallel, separated hidden layers. The supralinear-layer receives the number of inputs landing onto supralinear branches (a = number of supralinear dendrites) while the sublinear layer receives the number of inputs landing onto sublinear dendrites (b = number of sublinear dendrites). Neurons in both hidden layers are equipped with nonlinear transfer functions, a logistic sigmoid in the supralinear layer and a sublinear function in the sublinear layer. The somatic transfer functions of both ANNs are linear
