Mikael Djurfeldt

KTH Royal Institute of Technology — Sweden

Neuroscience · Life Sciences

14h-index1.7kcitations37works0.02yr avg
OpenAlex↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Neural dynamics and brain function(22), Advanced Memory and Neural Computing(15), Functional Brain Connectivity Studies(9), Neuroscience and Neural Engineering(7), Neural Networks and Applications(4)

Publications36 total

Connectivity concepts in neuronal network modeling
PLoS Computational Biology·2022· 46 citedOpen Access
Connectivity Concepts in Neuronal Network Modeling
Kölner Universitäts PublikationsServer (Universität zu Köln)·2021Open Access
NeuroModelingTalk (NMT) Approaching the complexity barrier in neuroscientific modeling
2020
Efficient Spike Communication in the MUSIC Framework on a Blue Gene/Q Supercomputer
KTH Publication Database DiVA (KTH Royal Institute of Technology)·2020Open Access
Connectivity Concepts for Neuronal Networks
JuSER (Forschungszentrum Jülich)·2019· 1 cited
1st INCF Workshop on Large-scale Modeling of the Nervous System
Faculty of 1000 Research Ltd·2018Open Access
Multirate method for co-simulation of electrical-chemical systems in multiscale modeling
Journal of Computational Neuroscience·2017· 2 citedOpen Access
Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations
Frontiers in Computational Neuroscience·2016· 6 citedOpen Access
Closed Loop Interactions between Spiking Neural Network and Robotic Simulators Based on MUSIC and ROS
Frontiers in Neuroinformatics·2016· 24 citedOpen Access
Efficient generation of connectivity in neuronal networks from simulator-independent descriptions
Frontiers in Neuroinformatics·2014· 9 citedOpen Access
Creating, documenting and sharing network models
Network Computation in Neural Systems·2012· 15 cited
The Connection-set Algebra—A Novel Formalism for the Representation of Connectivity Structure in Neuronal Network Models
Neuroinformatics·2012· 29 cited
This is the pre-peer-reviewed version of the following article:
2012· 9 cited
Learning and Adaptation of Sensorimotor Contingencies: Prism-Adaptation, a Case Study
Lecture notes in computer science·2012· 2 citedOpen Access
NineML: the network interchange for ne uroscience modeling language
BMC Neuroscience·2011· 31 citedOpen Access
Interfacing a parallel simulation of a neuronal network to robotic hardware using MUSIC, with application to real-time figure-ground segregation
BMC Neuroscience·2011· 1 citedOpen Access
Efficient spike communication in the MUSIC multi-simulation framework
BMC Neuroscience·2011· 2 citedOpen Access
The Connection-set Algebra: a formalism for the representation of connectivity structure in neuronal network models, implementations in Python and C++, and their use in simulators
BMC Neuroscience·2011· 1 citedOpen Access
Connecting MOOSE and NeuroRD through MUSIC: towards a communication framework for multi-scale modeling
BMC Neuroscience·2011· 10 citedOpen Access
Parallel implementation of a biologically inspired model of figure-ground segregation: Application to real-time data using MUSIC
Frontiers in Neuroinformatics·2011Open Access
page 1 of 2Next →

Frequent Co-authors

Anders Lansner(9), Örjan Ekeberg(8), Birgit Kriener(7), Markus Diesmann(6), Hans Ekkehard Pleßer(6), Andrew P. Davison(5), Sacha J. van Albada(5), Ekaterina Brocke(5), Abigail Morrison(4), Jochen Martin Eppler(4), Upinder S. Bhalla(4), Jeanette Hellgren Kotaleski(4), Johanna Senk(4), Nicole Voges(4), Eilif Müller(3), Mikael Lundqvist(3), Martin Rehn(3), Lisa Schüttler(3), Gabriele Gramelsberger(3), Robert C. Cannon(3)