(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.
Special Issue
Artificial Intelligence and Neural Networks: New Perspectives for Psychological Research
Submission Deadline: September 30, 2026 (Open) Submit Now
Guest Editor
Vsevolod Konstantinov, PhD
Professor and Head, Department of General Psychology, Penza State University, 440026 Penza, Russia
Research Interests: Problems of adaptation of migrants in new living conditions; artificial intelligence tools in psychology; transformation of migrant identity; ethnic identity; local community; integration; migrants; refugees
Co-Editor
Pavel Ustin, PhD
Head of the Department of General Psychology, Kazan Federal University, 420111, Kazan, Russia
Research Interests: Personality behavior in digital environments; neural network modeling of personality behavior; artificial intelligence tools in psychology; social network psychology; big data in psychology; ethical personality psychology
About This Topic
The rapid development of the digital environment and information and communication technologies opens new horizons for psychological research. On the one hand, people's behaviour and their interaction with each other are changing. Virtual forms of behaviour of users of the digital environment are emerging. Social networks emerge with their unprecedented possibilities of disseminating information and misinformation, manipulating consciousness, uniting like-minded people from all over the world and splitting societies into many information bubbles. On the other hand, artificial intelligence and neural networks significantly expand the research capabilities of psychologists: conducting psychodiagnostic slices on huge samples (big data), automation of psychological analysis and interpretation of research results with the identification of hidden and implicit patterns, digital modelling of various psychological phenomena. The special issue welcomes empirical research related to the problems of artificial intelligence, artificial neural networks and personality in the digital environment. In particular, these may include the following topics: peculiarities of personality behaviour in the digital environment, communication and interaction of social network users; peculiarities of intercultural communication and personality adaptation in the digital environment; the use of neural networks and artificial intelligence for cross-cultural psychological research; predictors of personality behaviour in the digital environment; modelling of psychological phenomena using machine learning methods; neural network models of cognitive, behavioural and socio-psychological phenomena in the digital environment; neural network models of cognitive, behavioural and socio-psychological phenomena. In this special issue, we would welcome manuscripts of different types, such as articles, reviews and conceptual papers of disciplinary or interdisciplinary nature that will contribute to the analysis of the problem field of artificial intelligence and neural networks from new perspectives.
Keywords
Artificial intelligence; neural networks; social networks; personality in the digital environment; personality adaptation in the digital environment; neural network models of cognitive; behavioural and socio-psychological phenomena
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
Knowledge and Information in Epistemic DynamicsAbstract This paper proposes a general theory of cognitive systems that inverts the conventional relationship between information and knowledge. While classical approaches define knowledge as the byproduct of processed information, we establish knowledge as a primitive concept and formulate information as a measure emerging from the process of assimila [...] |
| 2025 |  |
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| CiteScore | SJR | SNIP |
| 1.8 | 0.261 | 0.274 |
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