neurolib: A Simulation Framework for Whole-Brain Neural Mass Modeling
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F23%3A00547193" target="_blank" >RIV/67985807:_____/23:00547193 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s12559-021-09931-9" target="_blank" >http://dx.doi.org/10.1007/s12559-021-09931-9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s12559-021-09931-9" target="_blank" >10.1007/s12559-021-09931-9</a>
Alternative languages
Result language
angličtina
Original language name
neurolib: A Simulation Framework for Whole-Brain Neural Mass Modeling
Original language description
neurolib is a computational framework for whole-brain modeling written in Python. It provides a set of neural mass models that represent the average activity of a brain region on a mesoscopic scale. In a whole-brain network model, brain regions are connected with each other based on biologically informed structural connectivity, i.e., the connectome of the brain. neurolib can load structural and functional datasets, set up a whole-brain model, manage its parameters, simulate it, and organize its outputs for later analysis. The activity of each brain region can be converted into a simulated BOLD signal in order to calibrate the model against empirical data from functional magnetic resonance imaging (fMRI). Extensive model analysis is made possible using a parameter exploration module, which allows one to characterize a model’s behavior as a function of changing parameters. An optimization module is provided for fitting models to multimodal empirical data using evolutionary algorithms. neurolib is designed to be extendable and allows for easy implementation of custom neural mass models, offering a versatile platform for computational neuroscientists for prototyping models, managing large numerical experiments, studying the structure–function relationship of brain networks, and for performing in-silico optimization of whole-brain models.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30103 - Neurosciences (including psychophysiology)
Result continuities
Project
<a href="/en/project/EF19_074%2F0016209" target="_blank" >EF19_074/0016209: Modelling the sleeping brain: towards a neural mass model of sleep rhythms and their interactions</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Cognitive Computation
ISSN
1866-9956
e-ISSN
1866-9964
Volume of the periodical
15
Issue of the periodical within the volume
July 2023
Country of publishing house
US - UNITED STATES
Number of pages
21
Pages from-to
1132-1152
UT code for WoS article
000706010400001
EID of the result in the Scopus database
2-s2.0-85116942431