User profiles for Alexander Seeholzer
 | Alexander SeeholzerÉcole polytechnique fédérale de Lausanne Verified email at alumni.epfl.ch Cited by 398 |
[HTML][HTML] Stability of working memory in continuous attractor networks under the control of short-term plasticity
Continuous attractor models of working-memory store continuous-valued information in
continuous state-spaces, but are sensitive to noise processes that degrade memory retention. …
continuous state-spaces, but are sensitive to noise processes that degrade memory retention. …
Algorithmic composition of melodies with deep recurrent neural networks
A big challenge in algorithmic composition is to devise a model that is both easily trainable
and able to reproduce the long-range temporal dependencies typical of music. Here we …
and able to reproduce the long-range temporal dependencies typical of music. Here we …
Deep artificial composer: A creative neural network model for automated melody generation
The inherent complexity and structure on long timescales make the automated composition
of music a challenging problem. Here we present the Deep Artificial Composer (DAC), a …
of music a challenging problem. Here we present the Deep Artificial Composer (DAC), a …
Mapping the function of neuronal ion channels in model and experiment
10.7554/eLife.22152.001 Ion channel models are the building blocks of computational
neuron models. Their biological fidelity is therefore crucial for the interpretation of simulations. …
neuron models. Their biological fidelity is therefore crucial for the interpretation of simulations. …
[HTML][HTML] Synaptic patterning and the timescales of cortical dynamics
Neocortical circuits, as large heterogeneous recurrent networks, can potentially operate and
process signals at multiple timescales, but appear to be differentially tuned to operate within …
process signals at multiple timescales, but appear to be differentially tuned to operate within …
Nest 2.12. 0
…, D Terhorst, A Shusharin, H Bos, A Rao, A Seeholzer… - 2017 - juser.fz-juelich.de
NEST is a simulator for spiking neural network models that focuses on the dynamics, size and
structure of neural systems rather than on the exact morphology of individual neurons. For …
structure of neural systems rather than on the exact morphology of individual neurons. For …
Multicontact Co-operativity in Spike-Timing–Dependent Structural Plasticity Stabilizes Networks
Excitatory synaptic connections in the adult neocortex consist of multiple synaptic contacts,
almost exclusively formed on dendritic spines. Changes of spine volume, a correlate of …
almost exclusively formed on dendritic spines. Changes of spine volume, a correlate of …
NEST 2.10. 0
…, F Michler, HE Plesser, J Hahne, A Seeholzer… - 2015 - juser.fz-juelich.de
NEST 2.10.0 - JuSER guest :: login JuSER Search Submit Personalize Your alerts Your
baskets Your searches Help Home > Publications database > NEST 2.10.0 Information …
baskets Your searches Help Home > Publications database > NEST 2.10.0 Information …
Multi-contact synapses for stable networks: a spike-timing dependent model of dendritic spine plasticity and turnover
Excitatory synaptic connections in the adult neocortex consist of multiple synaptic contacts,
almost exclusively formed on dendritic spines. Changes of dendritic spine shape and volume, …
almost exclusively formed on dendritic spines. Changes of dendritic spine shape and volume, …
ICGenealogy: Mapping the function of neuronal ion channels in model and experiment
Ion channel models are the building blocks of computational neuron models. Their biological
fidelity is therefore crucial for the interpretability of simulations. However, the number of …
fidelity is therefore crucial for the interpretability of simulations. However, the number of …