Benjamin Lindner

This paper investigates how population sparseness affects learning speed and memory capacity in a network model with Hebbian plasticity, finding that optimal learning speed increases with sparseness and capacity depends non-monotonically on input sparseness.

The paper identifies nonlinear spectral response components in electroreceptor afferents under weakly nonlinear conditions, showing interactions between stimulus frequencies and baseline firing rates.

The paper shows bursts enhance nonlinear encoding in electroreceptor afferents, improving detection of weak signals in complex environments.

The paper explains the mechanism of intra-ripple frequency accommodation (IFA) in a computational model of hippocampal ripple oscillations, showing it arises from a speed-dependent hysteresis effect in interneuron dynamics.

The paper models the rat barrel cortex with a network of neurons and shows that a differentiator circuit can reliably detect single-neuron stimulation, aligning with experimental behavioral responses.

The paper investigates how cellular and circuit mechanisms transform dense to sparse odor representations in the insect olfactory system, identifying spike-frequency adaptation and lateral inhibition as key factors.

The paper models gap junction coupling in retinal ganglion cells to explain the speed and nucleation rate of stage I retinal waves through theoretical and simulation studies.