EEG and fMRI Applications in Exploring Brain Activity

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".

Deadline for manuscript submissions: 15 March 2026 | Viewed by 764

Special Issue Editors


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Guest Editor
Faculty of Psychology and Education Sciences, University of Porto, 4200-135 Porto, Portugal
Interests: fMRI; brain methods; MRI; MRS; machine learning; statistics; neuroendocrinology
Special Issues, Collections and Topics in MDPI journals

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Guest Editor Assistant
Research Unit in Medical Imaging and Radiotherapy, Cross I&D Lisbon Research Center, Escola Superior de Saúde da Cruz Vermelha Portuguesa, 1300-125 Lisbon, Portugal
Interests: neuroimaging; radiomics; MRI; biostatistics; machine learning

Special Issue Information

Dear Colleagues,

Background and history of this topic: In recent years, our understanding of the central nervous system has expanded significantly thanks to the use of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). These advancements have coincided with the development of more complex quantitative methods for analyzing MRI images and EEG signals. Additionally, researchers have created more sophisticated paradigms and designs to study emotional and cognitive functions.

Aim and scope of the Special Issue: The current Special Issue aims to gather significant advancements in EEG and fMRI applications, covering methods and theoretical aspects that help disentangle and explore brain activity. 

Cutting-edge research: Specifically, submissions should focus on novel advancements in EEG and fMRI in terms of methods and paradigms. 

What kind of papers we are soliciting: We strongly encourage the submission of EEG-, fMRI-, and multimodal-imaging-related studies. Meta-analyses and systematic reviews are also welcome.

Dr. Nicoletta Cera
Guest Editor

Dr. Faustino Ricardo
Guest Editor Assistant

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fMRI
  • EEG
  • resting state
  • data-driven analysis
  • machine learning
  • emotion
  • cognitive functions
  • aging
  • multimodal imaging

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Published Papers (1 paper)

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Research

20 pages, 2131 KB  
Article
Charting Early Brain Plasticity in Radiological Training: Functional Brain Reorganization During Early Radiological Expertise Acquisition
by Weilu Chai, Yuxin Bai, Jia Wu, Hongmei Wang, Jimin Liang, Xuemei Xie, Chenwang Jin and Minghao Dong
Brain Sci. 2025, 15(12), 1279; https://doi.org/10.3390/brainsci15121279 - 28 Nov 2025
Viewed by 312
Abstract
Background/Objectives: Radiological expertise draws on semantic knowledge and perceptual–cognitive mechanisms that support diagnostic reasoning. Early radiological training is a formative period when key cognitive processes begin to integrate. Nevertheless, how the brain pattern of early radiological expertise reorganizes during the first weeks of [...] Read more.
Background/Objectives: Radiological expertise draws on semantic knowledge and perceptual–cognitive mechanisms that support diagnostic reasoning. Early radiological training is a formative period when key cognitive processes begin to integrate. Nevertheless, how the brain pattern of early radiological expertise reorganizes during the first weeks of clinical exposure remains unknown, as prior work has relied mainly on cross-sectional designs comparing mature experts to beginners. Methods: We therefore conducted a longitudinal resting-state fMRI study in radiology interns (n = 43; 41 valid) scanned before and after short-term training. Behavioral performance improved significantly after training (p < 0.01). Regional homogeneity (ReHo) was computed for 246 Brainnetome ROIs for each subject. Results: Using a Support Vector Machine (SVM)-based recursive feature elimination (RFE) pipeline, 14 of these 246 features were identified as most discriminative, spanning regions involved in visual, semantic, memory, attentional, and decision-making processes. An SVM trained on these features effectively differentiated pre- and post-training brain states (training set: 86.67% accuracy, AUC = 0.97; validation set: 81.82% accuracy, AUC = 0.72). Conclusions: The observed neuroplastic changes provide direct evidence that multidimensional cognitive functions reorganize early in radiological expertise development and offer neural targets to inform evidence-based curriculum design, personalized training, and brain-targeted interventions (e.g., neuromodulation or neurofeedback) in radiology education. Full article
(This article belongs to the Special Issue EEG and fMRI Applications in Exploring Brain Activity)
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