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Informatica


A Comparative Study of Stochastic Optimizers for Fitting Neuron Models. Application to the Cerebellar Granule Cell
Volume 32, Issue 3 (2021), pp. 477–498
Pub. online: 12 April 2021      Type: Research Article      Open accessOpen Access
Received
1 November 2020
Accepted
1 April 2021
Published
12 April 2021

Abstract

This work compares different algorithms to replace the genetic optimizer used in a recent methodology for creating realistic and computationally efficient neuron models. That method focuses on single-neuron processing and has been applied to cerebellar granule cells. It relies on the adaptive-exponential integrate-and-fire (AdEx) model, which must be adjusted with experimental data. The alternatives considered are: i) a memetic extension of the original genetic method, ii) Differential Evolution, iii) Teaching-Learning-Based Optimization, and iv) a local optimizer within a multi-start procedure. All of them ultimately outperform the original method, and the last two do it in all the scenarios considered.

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Biographies

Cruz Nicolás C.
ncalvocruz@ual.es

N.C. Cruz is a researcher at the Supercomputing – Algorithms (SAL) Research Group at the University of Almería, Spain. He obtained his PhD from the University of Almería. His publications can be found on https://publons.com/researcher/1487279/nc-cruz/. His research interests include high-performance computing, global optimization and applications. Personal web page: http://hpca.ual.es/~ncalvo/.

Marín Milagros
mmarin@ugr.es

M. Marín is a predoctoral student at the department of Biochemistry and Molecular Biology at the University of Granada. She is currently pursuing her PhD within the Applied Computational Neuroscience group at the Research Centre for Information and Communications Technologies. She is a young researcher participating in the international project Human Brain Project (HBP). Some of her publications are available at https://publons.com/researcher/3213167/milagros-marin/. Her interdisciplinary research interests are located between Health and Biochemistry (Cerebellum, Molecular Biology and Biomedicine) and Information and Communication Technologies (Computational Neuroscience and Bioinformatics). Personal web page: http://acn.ugr.es/people/mmarin/.

Redondo Juana L.
jlredondo@ual.es

J.L. Redondo is an assistant professor at the Informatics Department at the University of Almería, Spain. She obtained her PhD from the University of Almería. Her publications can be found on https://www.scopus.com/authid/detail.uri?authorId=35206862500. Her research interests include high performance-computing, global optimization and applications. Personal web page: https://sites.google.com/ual.es/jlredondo.

Ortigosa Eva M.
ortigosa@ugr.es

E. M. Ortigosa is an assistant professor at the Computer Architecture and Technology Department at the University of Granada, Spain. She received her PhD degree in computer engineering from the University of Málaga, Spain. She has participated in the creation of the spin-off company Seven Solutions, S.L. It is an EBT (Technology-Based Company) that has received numerous awards. Her research interests include computational neuroscience and efficient network simulation methods, bioinformatics, and hardware implementation of digital circuits for real time processing in embedded systems. Personal web page: https://atc.ugr.es/informacion/directorio-personal/eva-martinez-ortigosa.

Ortigosa Pilar M.
ortigosa@ual.es

P.M. Ortigosa is a full professor at the Informatics Department at the University of Almería, Spain. She obtained her PhD from the University of Málaga, Spain. Her publications can be found on https://www.scopus.com/authid/detail.uri?authorId=6602759441. Her research interests include high-performance computing, global optimization and applications. Personal web page: https://sites.google.com/ual.es/pmortigosa.


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© 2021 Vilnius University
Open access article under the CC BY license.

Keywords
granule cell neuron model model tuning optimization meta-heuristics

Funding
This research has been funded by the Human Brain Project Specific Grant Agreement 3 (H2020-RIA. 945539), the Spanish Ministry of Economy and Competitiveness (RTI2018-095993-B-I00), the National Grant INTSENSO (MICINN-FEDER-PID2019-109991GB-I00), the Junta de Andalucía (FEDER-JA P18-FR-2378, P18-RT-1193), and the University of Almería (UAL18-TIC-A020-B).

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