David Rotermund

This study determines the minimum number of phosphenes needed for object recognition in prosthetic vision, finding that 65 phosphenes suffice, with segments requiring fewer fragments.

The paper introduces a spiking neural network framework called SbS that matches CNN performance on clean data and shows superior robustness to unseen noise.

The paper designs an open-source closed-loop system for neuro-prosthetic research that can stimulate and measure neuronal activity with high precision and scalability.

This paper develops a learning rule for deep Spike-by-Spike networks and demonstrates its effectiveness on MNIST classification with 99.3% accuracy.

The paper develops FPGA hardware for Spike-By-Spike networks, demonstrating efficient parallelization and optimization for spiking neural network computations.

This paper introduces a framework of spiking neurons with local learning rules that achieve performance comparable to artificial deep networks in image classification.

The paper presents a fully wireless sub-cranial neuro-implant using commercial components to measure electrocorticography signals at 128 brain locations, with open-source design files.

The paper investigates how attention gates afferent signal transmission in area V4 by showing low-frequency components from attended stimuli are transmitted while higher frequencies are attenuated.