Advances in Neuroimaging for Human Cognition, Behavior, Brain Modulation and Prediction
A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Neuroimaging and Neuroinformatics".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 430
Special Issue Editor
Interests: visual optics; optical design; image processing; neurosciences
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent decades, research on cortical activity has shifted from being primarily descriptive to playing a more disruptive role: discovering the underlying mechanisms of cortical activity and the ways to modulate it precisely and non-invasively. The ability to intervene in specific brain neural networks expands the horizons of clinical and technological innovation. However, achieving effective modulation depends primarily on neuroimaging techniques that can capture the spatiotemporal dynamics of cortical activity with high resolution. This Special Issue welcomes contributions that connect recent advances in neuroimaging with applications in the modulation of cortical activity. We invite submissions of studies that employ neuroimaging modalities, such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS), diffusion imaging, positron emission tomography (PET), and other multimodal tools. Of particular interest is research integrating these imaging tools with neuromodulation techniques, such as transcranial magnetic or electrical stimulation, to investigate how they influence cortical organization and plasticity. In that sense, this Special Issue calls for recent research in visual neuroscience, visual cognition, and human behavior that employs neuroimaging as a fundamental methodological approach for understanding the mechanisms underlying perception, decision-making, and interaction with the environment. Submissions are especially encouraged in emerging areas such as:
- Human–computer interaction;
- Brain–computer interfaces;
- Design of computational models to analyze and predict cortical activity in conjunction with behavioral aspects.
This Special Issue aims to focus on interdisciplinary work among neuroimaging, neuromodulation, and computational modeling that will take us beyond image observation and analysis, toward a deeper understanding of brain function.
Dr. Francisco Ávila Gómez
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
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. Journal of Imaging 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 1800 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
- neuroimaging
- human cognition
- behavior prediction
- brain stimulation
- cortical modulation
- multimodal integration
- machine learning
- human–machine interaction
- predictive modeling
- cognitive neuroscience
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