Matthias Köhler

The paper demonstrates that a spinal cord model can learn rhythmic movements using the BCM learning rule, without requiring rhythm generating neurons or genetically defined connectivity.

The paper investigates spinal interneuron connectivity in cats and finds that input patterns form a continuum rather than distinct classes.

The paper introduces a non-spiking neuron model with dynamic leak to assess stability in recurrent networks, finding it reduces spurious high-frequency noise and scales with network size.

The paper questions the validity of self-inhibitory mechanisms in the half-center model of locomotion control using in vivo data and functional evaluations.