Brian 2, an intuitive and efficient neural simulator
Brian 2 allows scientists to simply and efficiently simulate spiking neural network models.
These models can feature novel dynamical equations, their interactions with the …
These models can feature novel dynamical equations, their interactions with the …
Connectivity concepts in neuronal network modeling
J Senk, B Kriener, M Djurfeldt, N Voges… - PLoS computational …, 2022 - journals.plos.org
Sustainable research on computational models of neuronal networks requires published
models to be understandable, reproducible, and extendable. Missing details or ambiguities …
models to be understandable, reproducible, and extendable. Missing details or ambiguities …
Modeling the cerebellar microcircuit: new strategies for a long-standing issue
The cerebellar microcircuit has been the work bench for theoretical and computational
modeling since the beginning of neuroscientific research. The regular neural architecture of …
modeling since the beginning of neuroscientific research. The regular neural architecture of …
Performance comparison of the digital neuromorphic hardware SpiNNaker and the neural network simulation software NEST for a full-scale cortical microcircuit model
The digital neuromorphic hardware SpiNNaker has been developed with the aim of
enabling large-scale neural network simulations in real time and with low power …
enabling large-scale neural network simulations in real time and with low power …
Equation-oriented specification of neural models for simulations
Simulating biological neuronal networks is a core method of research in computational
neuroscience. A full specification of such a network model includes a description of the …
neuroscience. A full specification of such a network model includes a description of the …
Scalability of asynchronous networks is limited by one-to-one map** between effective connectivity and correlations
SJ Van Albada, M Helias… - PLoS computational …, 2015 - journals.plos.org
Network models are routinely downscaled compared to nature in terms of numbers of nodes
or edges because of a lack of computational resources, often without explicit mention of the …
or edges because of a lack of computational resources, often without explicit mention of the …
NESTML: a modeling language for spiking neurons
D Plotnikov, B Rumpe, I Blundell, T Ippen… - arxiv preprint arxiv …, 2016 - arxiv.org
Biological nervous systems exhibit astonishing complexity. Neuroscientists aim to capture
this com-plexity by modeling and simulation of biological processes. Often very comple xm …
this com-plexity by modeling and simulation of biological processes. Often very comple xm …
Handling metadata in a neurophysiology laboratory
To date, non-reproducibility of neurophysiological research is a matter of intense discussion
in the scientific community. A crucial component to enhance reproducibility is to …
in the scientific community. A crucial component to enhance reproducibility is to …
Constructing neuronal network models in massively parallel environments
T Ippen, JM Eppler, HE Plesser… - Frontiers in …, 2017 - frontiersin.org
Recent advances in the development of data structures to represent spiking neuron network
models enable us to exploit the complete memory of petascale computers for a single brain …
models enable us to exploit the complete memory of petascale computers for a single brain …
Efficient generation of connectivity in neuronal networks from simulator-independent descriptions
M Djurfeldt, AP Davison, JM Eppler - Frontiers in neuroinformatics, 2014 - frontiersin.org
Simulator-independent descriptions of connectivity in neuronal networks promise greater
ease of model sharing, improved reproducibility of simulation results, and reduced …
ease of model sharing, improved reproducibility of simulation results, and reduced …