5 citations · 8 across the 5 of their papers we have counts for
5 papers
Dendritic structure enables powerful plasticity
Ben von Hünerbein, Federico Benitez, Kevin Max +10
Over the past decades, it has become increasingly clear that the complex morphology of cortical neurons is more than just a quirk of evolution, and that dendritic compartments serv…
A Variational Latent Equilibrium for Learning in Neuronal Circuits
Simon Brandt, Paul Haider, Walter Senn +2
Brains remain unrivaled in their ability to recognize and generate complex spatiotemporal patterns. While AI is able to reproduce some of these capabilities, deep learning algorith…
Prospective and retrospective coding in cortical neurons
Simon Brandt, Mihai Alexandru Petrovici, Walter Senn +2
Brains can process sensory information from different modalities at astonishing speed; this is surprising as the integration of inputs through the membrane of each individual neuro…
Backpropagation through space, time, and the brain
Benjamin Ellenberger, Paul Haider, Jakob Jordan +5
How physical networks of neurons, bound by spatio-temporal locality constraints, can perform efficient credit assignment, remains, to a large extent, an open question. In machine l…
ELiSe: Efficient Learning of Sequences in Structured Recurrent Networks
Laura Kriener, Kristin Völk, Kristin Spicher +6
Behavior can be described as a temporal sequence of actions driven by neural activity. To learn complex sequential patterns in neural networks, memories of past activities need to…