Call for Papers: Special Issue on Brain Simulation and Spiking Neural Networks

Guest Editors

Jordi Solé-Casals (jordi.sole@uvic.cat)

Cesar F. Caiafa (ccaiafa@fi.uba.ar)

Zhe Sun (zhe.sun.vk@riken.jp)

Vassilis Cutsuridis (vcutsuridis@lincoln.ac.uk)

Scope and Motivation

During the past 10 years, many experiments have been implemented with the aim of improving our understanding on the brain’s structure and function. Alongside, simulation neuroscience has become an important strategy to investigate how the brain works. The Human Connectome Project in the US started in 2009, and aimed to provide a big human brain mapping dataset on which many brain models have already been tested. In the Human Brain Project in the EU, a large-scale virtual rodent brain simulation is being built with the purpose of revealing various brain activities. In Japan, whole human-scale brain simulations on the Fugaku supercomputer are being established to investigate how neural networks develop their learning process.

On the other hand, the foundation of cognitive computing and control mechanism can be revealed from the simulations of brain circuits and the neural dynamics. Moreover, these are also critical to improve current artificial intelligent systems and for building brain intelligence level algorithms.

In this special issue, we invite researchers to present their state-of-the-art approaches, introduce recent advances and therefore show the potential of brain-simulation-related technologies.

Topics

Topics include but are not limited to:

  • Brain Connectivity mapping and functional mapping
  • Data analysis methods for connectome data
  • Multi-scale neural system simulation
  • Neuromorphic hardware 
  • High-performance computing system for large scale simulations
  • Neural system inspired spiking neural network
  • Neuro-robotics systems
  • Sensorimotor learning model

Deadlines

Submissions Deadline: April 1, 2021
First notification of acceptance: June 1, 2021
Submission of revised papers: August 1, 2021
Final notification to the authors: Oct 1, 2021
Submission of final/camera-ready papers: Nov 1, 2021
Publication of special issue: Nov 22, 2021

Submission Instruction:
Prepare your paper in accordance with the Journal guidelines: www.springer.com/12559. Submit manuscripts at:  http://www.editorialmanager.com/cogn/.  Select “SI: Brain Simulation and Spiking Neural Networks” for the special issue under “Additional Information.”  Your paper must contain significant and original work that has not been published nor submitted to any journals. All papers will be reviewed following standard reviewing procedures of the Journal.

Author Resources

Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals.  

All papers will be reviewed following standard reviewing procedures for the Journal. 

Papers must be prepared in accordance with the Journal guidelines: www.springer.com/12559

Springer provides a host of information about publishing in a Springer Journal on our Journal Author Resources page, including  FAQs,  Tutorials  along with  Help and Support.

Other links include:

Guest Editor Bios

Jordi Solé-Casals currently holds a permanent position as a Full Professor of the Department of Engineering of the University of Vic – Central University of Catalonia and is the Head of the Data and Signal Processing Research Group (DSP, UVic-UCC).  He is also Visiting Scientist (2016 ~) at the Brain Mapping Unit of the Department of Psychiatry of the University of Cambridge (UK) and Visiting Scientist (2020 ~) at the College of Artificial Intelligence, Nankai University (China). He was Visiting Research/Scientist with the GIPSA Lab. in Grenoble (France), the Lab. for Advanced Brain Signal Processing, BSI-RIKEN in Wako (Japan) and the Tensor Learning Team, at the RIKEN Center for Advanced Intelligence Project (AIP), Tokyo (Japan). Currently he continues the relationships with these laboratories. He is Associate Editor of Springer-Nature’s Cognitive Computation, Frontiers in Computer Sciences and Frontiers in Psychology journals, and the MDPI Signals journal.  His research interests include signal processing specially in the biomedical field (EEG, fMRI, speech, handwritten, biometric applications), machine learning/deep learning and statistical modelling for applied sciences.


Dr. Cesar F. Caiafa currently holds a permanent position as Independent Researcher (2010~) at IAR – CONICET and Adjunct Professor (2015~) at Engineering Faculty – University of Buenos Aires, Argentina. He is also Visiting Scientist (2018 ~) at the Tensor Learning Team, RIKEN Center for Advanced Intelligence Project (AIP), Tokyo, Japan. He was Research Scientist (2016 – 2018) at the Psychology and Brain Sciences Department, Indiana University, Bloomington, Indiana, USA. Research Scientist (2008 – 2010) and Visiting Scientist (2011 – 2018) at Lab. for Advanced Brain Signal Processing, BSI-RIKEN, Wako, Japan. He currently works on the development of machine learning algorithms exploiting tensor decompositions and sparsity with diverse applications ranging from Neuroscience to Astronomy.

Zhe Sun is currently a Research Scientist with the Image Processing Research Team, Center for Advanced Photonics, RIKEN National Science Institute, Japan. He is a researcher in Japanese AVATAR X Project and Fugaku Supercomputer Project. In Fugaku Supercomputer Project, he is currently focusing on human scale brain simulation. He joined RIKEN, in 2015, as a Research Support Assistant. He obtained the Ph.D. degree in 2017 from Yokohama City University, Japan. He has been a Research Scientist with RIKEN, since 2017. From 2014, his research topics were the development of spiking neuron model and spiking neural network to understand end elucidate brain functions. His current research interests include brain inspired vision system, large-scale brain simulation, high-performance computing and neuromorphic engineering.



Vassilis Cutsuridis is an Associate Professor in Computer Science, and a member of the Machine Learning research group at the University of Lincoln. He has led research for over 15 years on biomimetic artificial intelligence including neural computation, cognitive systems and machine learning. His research work ranges from models of biomimetic learning rules and neural network models of learning and memory, to machine learning applications to drug discovery, to systems level models of deep brain stimulation, to deep neurocognitive models of perception-cognition-action in robots, to AI behavioral models of eye movements in neurodegenerative diseases. He has published over 100 articles in journals, conferences and books. He has edited 5 books including the famous Hippocampal Microcircuits: A computational modeller’s resource book and the Perception-action cycle: Models, algorithms and hardware book. He has participated/coordinated Greek, European and UK grants. He is currently co-I in the SMARTGREEN project. He is associate editor of Springer-Nature’s Cognitive Computation and the Frontiers in Systems Neuroscience journals.