(ISSN 2573-4407)
OBM Neurobiology is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. By design, the scope of OBM Neurobiology is broad, so as to reflect the multidisciplinary nature of the field of Neurobiology that interfaces biology with the fundamental and clinical neurosciences. As such, OBM Neurobiology embraces rigorous multidisciplinary investigations into the form and function of neurons and glia that make up the nervous system, either individually or in ensemble, in health or disease. OBM Neurobiology welcomes original contributions that employ a combination of molecular, cellular, systems and behavioral approaches to report novel neuroanatomical, neuropharmacological, neurophysiological and neurobehavioral findings related to the following aspects of the nervous system: Signal Transduction and Neurotransmission; Neural Circuits and Systems Neurobiology; Nervous System Development and Aging; Neurobiology of Nervous System Diseases (e.g., Developmental Brain Disorders; Neurodegenerative Disorders).
OBM Neurobiology publishes a variety of article types (Original Research, Review, Communication, Opinion, Comment, Conference Report, Technical Note, Book Review, etc.). Although the OBM Neurobiology Editorial Board encourages authors to be succinct, there is no restriction on the length of the papers. Authors should present their results in as much detail as possible, as reviewers are encouraged to emphasize scientific rigor and reproducibility.
Publication Speed (median values for papers published in 2024): Submission to First Decision: 7.6 weeks; Submission to Acceptance: 13.6 weeks; Acceptance to Publication: 6 days (1-2 days of FREE language polishing included)
Special Issue
Applications of Brain–Computer Interface (BCI) and EEG Signals Analysis
Submission Deadline: July 15, 2026 (Open) Submit Now
Guest Editor
Hadi Seyedarabi, PhD
Professor of Electrical Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
Research Interests: Image segmentation; computer vision; neural networks; social psychology; emotional communication; medical signal processing; pattern recognition; AI in healthcare
Co-Editor
Mahsa Zeynali, PhD
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
Research Interests: Machine learning and deep learning; brain-computer interface (BCI); biomedical signals and image processing; cognitive neuroscience; explainable AI
About This Topic
Brain–Computer Interfaces (BCIs), which establish a direct pathway between the human brain and computational systems, have enabled remarkable progress in areas such as medical applications, rehabilitation, neurofeedback, and brain-controlled devices. At the core of these systems lies electroencephalogram (EEG) signal analysis, which provides valuable insights into brain activity and supports the development of reliable and efficient BCI technologies.
With the growing interest in practical applications, a wide range of methods—spanning signal processing, machine learning, and hybrid computational approaches—are being applied to improve performance and expand the usability of BCIs. This issue invites researchers to share their contributions on innovative applications, methodological advances, and experimental findings that strengthen the role of EEG analysis in shaping the future of brain–computer interface systems, while also addressing the needs of end-users through accuracy, usability, and—where relevant—explainable approaches that foster trust and adoption.
Keywords
Brain–computer interfaces (BCIs); electroencephalogram (EEG); EEG signal analysis; machine learning; deep learning; brain signals; explainable AI (XAI)
Manuscript Submission Information
Manuscripts should be submitted through the LIDSEN Submission System. Detailed information on manuscript preparation and submission is available in the Instructions for Authors. All submitted articles will be thoroughly refereed through a single-blind peer-review process and will be processed following the Editorial Process and Quality Control policy. Upon acceptance, the article will be immediately published in a regular issue of the journal and will be listed together on the special issue website, with a label that the article belongs to the Special Issue. LIDSEN distributes articles under the Creative Commons Attribution (CC BY 4.0) License in an open-access model. The authors own the copyright to the article, and the article can be free to access, distribute, and reuse provided that the original work is correctly cited.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). Research articles and review articles are highly invited. Authors are encouraged to send the tentative title and abstract of the planned paper to the Editorial Office (neurobiology@lidsen.com) for record. If you have any questions, please do not hesitate to contact the Editorial Office.
Welcome your submission!
Publication
Image Generation Inspired by Electroencephalography for Neuromarketing Applications Using Extracted Features from Transformer-Based ModelsAbstract The design of products in Neuromarketing using machine learning methods has been a continuous challenge in Computer-aided design. Previously, deep learning techniques have been applied to generate random images for domains such as furniture, fashion, and product design. However, using deep generative methods requires a large amount of data [...] |
Interactive and Deep Learning-Powered EEG-BCI for Wrist Rehabilitation: A Game-based Prototype StudyAbstract Motor deficits induced by neurological disorders impose a severe impact on activities of daily life. Conventional rehabilitation practices necessitate ongoing clinical supervision, which is costly and inaccessible. EEG-based brain-computer interface (BCI) systems offer a viable solution by facilitating neurorehabilitation through the direct [...] |
| 2024 |  |
|
| CiteScore | SJR | SNIP |
| 1.2 | 0.205 | 0.249 |
TOP
