For a fixed number of neurons, the network may follow either of these dynamics, depending on the initialization.
we show that kernel dynamics correspond to interpolation with cubic splines, whereas active dynamics yields adaptive linear splines, where neurons accumulate at the discontinuities and yield piecewise linear approximations.