List of works - Robert Legenstein

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

scientific article

A comparison of manual neuronal reconstruction from biocytin histology or 2-photon imaging: morphometry and computer modeling

scientific article

A compound memristive synapse model for statistical learning through STDP in spiking neural networks

scientific article published on 16 December 2014

A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback

scientific article

A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task

scientific article

A solution to the learning dilemma for recurrent networks of spiking neurons

scientific article published on 17 July 2020

Branch-specific plasticity enables self-organization of nonlinear computation in single neurons.

scientific article published in July 2011

Computer science: Nanoscale connections for brain-like circuits

scientific article

Correction of tailor's bunion with the Boesch technique: a retrospective study

scientific article

Cortical oscillations support sampling-based computations in spiking neural networks

scientific article published on 24 March 2022

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

scientific article (publication date: 2015)

Emergence of complex computational structures from chaotic neural networks through reward-modulated Hebbian learning

scientific article

Ensembles of spiking neurons with noise support optimal probabilistic inference in a dynamically changing environment

scientific article

Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs

scientific article

Indomethacin versus meloxicam for prevention of heterotopic ossification after total hip arthroplasty

scientific article published on 28 March 2003

Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons

scientific article

Integration of nanoscale memristor synapses in neuromorphic computing architectures

scientific article published on 02 September 2013

Network Plasticity as Bayesian Inference ⬇️

scientific article published on 6 November 2015

Reinforcement learning on slow features of high-dimensional input streams

scientific article

Spiking neurons can learn to solve information bottleneck problems and extract independent components

scientific article published in April 2009

The location of the axon initial segment affects the bandwidth of spike initiation dynamics

scientific article published on 23 July 2020

Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses

scientific article published on 29 September 2016

List of works by Robert Legenstein

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

A comparison of manual neuronal reconstruction from biocytin histology or 2-photon imaging: morphometry and computer modeling

A compound memristive synapse model for statistical learning through STDP in spiking neural networks

A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback

A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task

A solution to the learning dilemma for recurrent networks of spiking neurons

Branch-specific plasticity enables self-organization of nonlinear computation in single neurons.

Computer science: Nanoscale connections for brain-like circuits

Correction of tailor's bunion with the Boesch technique: a retrospective study

Cortical oscillations support sampling-based computations in spiking neural networks

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

Emergence of complex computational structures from chaotic neural networks through reward-modulated Hebbian learning

Ensembles of spiking neurons with noise support optimal probabilistic inference in a dynamically changing environment

Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs

Indomethacin versus meloxicam for prevention of heterotopic ossification after total hip arthroplasty

Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons

Integration of nanoscale memristor synapses in neuromorphic computing architectures

Network Plasticity as Bayesian Inference ⬇️

Reinforcement learning on slow features of high-dimensional input streams

Spiking neurons can learn to solve information bottleneck problems and extract independent components

The location of the axon initial segment affects the bandwidth of spike initiation dynamics

Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses