Fuzzy Systems for Brain Sciences and Brain-Computer Interfaces (BCI) Under Uncertainty


Given the important challenges associated with the processing of brain signals obtained from neuroimaging modalities, fuzzy sets and systems have been proposed as a useful and effective framework for the analysis of brain activity as well as to enable a direct communication pathway between the brain and external devices (brain computer/machine interfaces). While there has been an increasing interest in these questions, the contribution of fuzzy systems has been diverse depending on the area of application. On the one hand, considering the decoding of brain activity, advanced computational intelligence methods that handles uncertainty such as fuzzy sets and systems, represent an excellent tool to overcome the challenge of processing extremely noisy signals that are very likely to be affected by non-stationarities, invariants and poor generalisation. On the other hand, as regards neuroscience research, possibility and fuzziness has equally been employed for the measurement of smooth integration between synapses, neurons, and brain regions or areas. In this context, the proposed special session aims at providing a specialised forum for researchers interested in employing advanced methods of computational intelligence and fuzzy systems to model and represent uncertainty for the analysis of brain signals and neuroimaging data. Contributions can be on any related disciplines such as computational neuroscience, brain computer/machine interfaces, neuroscience, neuroinformatics, neuroergonomics, computational cognitive neuroscience, affective neuroscience, neurobiology, brain mapping, neuro-engineering, and neurotechnology.

Main topics:

The topics include but are not limited to:

· Application of fuzzy systems for the analysis of brain signals from any functional or structural neuroimaging modalities (fMRI /MRI, PET/SPECT, EEG, MEG, fNIRS, DOI, EROS, etc.)

· Fuzzy systems for uncertain modelling of brain computer/machine interfaces (BCI/BMI).

· Brain computer/machine interfaces (all paradigms, transfer learning, multi-modal BCI, Neural Prostheses) powered by Fuzzy Systems.

· Fuzzy systems the simulation of brain processes in computational


· Fuzzy systems for Neuroscience applications and the understanding of brain processes.

· Neuroinformatic tools based on fuzzy systems.

· Edge-technologies for neurotechnology.

Important Dates:

Paper Submission Deadline: 15th January, 2020

Select Special Session 'FUZZ-IEEE-35'

CT Lin

Technical University of Sidney


Javier Andreu-Perez

University of Essex

United Kingdom

Amit Konar

Jadavpur University


Mukesh Prasad

Technical University of Sidney


Associated Competition:

Clinical BCI Challenge WCCI 2020 (Supported by IEEE FSTC TFs)

Submission Deadline 5th, 23:59 (GMT)