IEEE WCCI/IJCNN 2024 Special Session

Włodzisław Duch (Nicolaus Copernicus University, Poland)
Tomasz M Rutkowski (RIKEN AIP, Japan; The University of Tokyo, Tokyo, Japan; Nicolaus Copernicus University, Poland)

In this session, we will explore the intersection of machine learning and signal processing in the context of brain and behavioral signal analysis. The topics we will cover include the latest advances in machine learning algorithms and signal processing techniques and their applications in neuroscience and psychology. In recent years, there have been significant developments in EEG, MEG, fMRI, fNIRS, and other methods of measuring brain signals, which can significantly benefit clinical psychology, including the therapeutic application of neurofeedback. The session will begin with an overview of the current state of brain signal analysis. It will include methods of brain signal representation, embeddings, decomposition, feature extraction, classification, simulations, analysis of neurodynamics, recurrence analysis, network analysis, visualization, microstates, brain fingerprints, spectral methods, and their applications to diagnose various brain disorders. We will also discuss challenges and opportunities in this field in a panel at the end of the session. Additionally, the session will cover the latest advances in machine learning and signal processing to analyze behavioral data.

Please use the IEEE WCCI 2024 double-blind submission procedure when submitting your paper for our special session. Conference formatting templates and submission guidelines can be found at https://2024.ieeewcci.org/submission.
Tick the radio button on the left to select our session title as a track - Special Session: Machine Learning and Signal Processing for Brain or Behavioral Analysis - when submitting your IJCNN 2024 Special Session Papers at https://edas.info/N31614.