Academic Journal
Q1Brain Informatics
About Brain Informatics
Brain Informatics is a scholarly journal published by Springer Science and Business Media Deutschland GmbH. SCImago 2025 lists it in Q1, with an SJR of 1.413 and H-index of 42.
Coverage: 2014-2026. Research categories: Cognitive Neuroscience (Q1); Computer Science Applications (Q1); Neurology (Q1).
Open-access policies and author information
Reported in the official DOAJ public CSV snapshot (2026-09-01), downloaded 2026-10-03. Record updated 2026-03-17. This snapshot does not establish today’s listing status or fee quotation.
Publisher policy links recorded by DOAJ
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Source: DOAJ journal record. Journal metadata is distributed by DOAJ under CC0. Confirm current fees, tax, eligibility and waiver terms with the publisher.
Source-backed journal facts
Topics in published research
EEG and Brain-Computer Interfaces; Functional Brain Connectivity Studies; Neural dynamics and brain function; Emotion and Mood Recognition; Blind Source Separation Techniques; Brain Tumor Detection and Classification.
OpenAlex classifies topics from published works. These topics are not the publisher’s official aims and scope.
Source: OpenAlex source record. Retrieved 2026-10-03. Source record updated 2026-10-02. OpenAlex metrics are different from SCImago metrics and the Clarivate Journal Impact Factor.
Journal Metrics
Quartile, SJR and the listed SCImago H-index use the 2025 imported SCImago dataset. A quartile may vary by subject category. Values without a source or reporting year are unverified historical entries. Verify the current Journal Impact Factor with Clarivate or the publisher before using it.
Aims & Scope
The publisher’s official aims and scope have not yet been verified for this profile. Use the journal website to check subject fit and accepted article types before submitting.
Recent Research Articles
Latest publications matched automatically by ISSN.
Quantifying emotional arousal through pupillary response: a novel approach for isolating the luminosity effect and predicting affective states
Zeel Pansara, Gabriele Navyte, Tatiana Freitas Mendes, Camila Bottger et al.
2026-09-29 · DOI: 10.1186/s40708-026-00332-yEarly prediction of in-hospital complications following acute traumatic brain injury: a retrospective study using multiple machine learning models
Mei-Hua Wang, Rui Li, Jiang Fang, Xinyu Deng et al.
2026-09-18 · DOI: 10.1186/s40708-026-00334-wDiscrimination of seizure topographical images utilizing transfer learning approaches
Athar Al-azzawi, Saif Al-jumaili, Adil Deniz Duru, Osman Nuri Uçan et al.
2026-09-18 · DOI: 10.1186/s40708-026-00330-0Parallel command principle in sensorimotor control for brain-inspired AI design
Xu Chen, Xiaoxue Shi, Biyu Ren, Yu Chen et al.
2026-09-09 · DOI: 10.1186/s40708-026-00333-xInterpretable brain-age modeling reveals network-level reorganization in functional brain aging
Yikang Cao, Marco Castellaro, Marco Zorzi, Alessandra Bertoldo et al.
2026-08-30 · DOI: 10.1186/s40708-026-00331-zEffects of chlorpyrifos exposure on autism-associated genes: an integrative analysis using network toxicology, transcriptomics, and molecular dynamics simulations
Boli Cheng, Enyu Wan, Xiaoqin Wei, Si Wang et al.
2026-08-28 · DOI: 10.1186/s40708-026-00329-7Integrating convolutional variational autoencoders and the Gaussian mixture model for efficient manifold learning and clustering of spatially preserved EEG topographic maps
Saheed Faremi, Luca Longo
2026-08-24 · DOI: 10.1186/s40708-026-00327-9Brain dysconnectivity patterns associated with chronic back pain development
Stephan Wunderlich, Enrico Schulz, Florian Ringel, Veit M. Stoecklein et al.
2026-12 · DOI: 10.1186/s40708-026-00328-8DRBD-Mamba for robust and efficient brain tumor segmentation with analytical insights
Danish Ali, Ajmal Mian, Naveed Akhtar, Ghulam Mubashar Hassan et al.
2026-08-19 · DOI: 10.1186/s40708-026-00326-wInvestigating functional brain networks in multiple sclerosis patients: a graph theory approach for evaluating working memory impairment
Sareh Yousefi, Mohammad Reza Daliri
2026-12 · DOI: 10.1186/s40708-026-00324-yCAE-BrainNet: a statistically validated class-adaptive attention ensemble model for explainable brain tumor classification from MRI
Mehedi Hasan Meraj, Mashfiquzzaman Tajbid, Mayen Uddin Mojumdar, Narayan Ranjan Chakraborty et al.
2026-12 · DOI: 10.1186/s40708-026-00325-xDecoding neuronal gene expression: integrative insights from omics and AI
Aranyak Goswami, Rushikesh R. Lagad, Shakil Rafi
2026-12 · DOI: 10.1186/s40708-026-00323-zAdaptive frequency band attention-guided CNN–BiLSTM for Spatial–Spectral–Temporal EEG emotion recognition
Rabita Hasan, Sheikh Md. Rabiul Islam
2026-12 · DOI: 10.1186/s40708-026-00319-9Effiformer: a unified data-efficient vision transformer-CNN framework for interpretable epileptic seizure detection
Aaranay Aadi, Divyansh Sukhija, Rishabh Shetty, Praveen Shukla et al.
2026-12 · DOI: 10.1186/s40708-026-00320-2Hybrid self-supervised EEG emotion representation: masked reconstruction joint with mutual information bounds
Haoyu Liu, Xinyu Li, Haiyan Zhou, Jiajin Huang et al.
2026-12 · DOI: 10.1186/s40708-026-00322-0EEG-DBNet: a dual-branch framework for temporal-spectral representation learning of motor imagery electroencephalography
Youxi Qu, Xicheng Lou, Hongying Meng, Zhangyong Li et al.
2026-12 · DOI: 10.1186/s40708-026-00321-1Cross-attention-guided subject-adaptive graph learning for multimodal autism classification: integrating structural and functional MRI data
Yan Tang, Chao Yang, Yihang Xu, Hao Zhang et al.
2026-12 · DOI: 10.1186/s40708-026-00318-wGeneralizable and explainable deep learning for brain MRI: a multi-cohort evaluation of 3D architectures for age and sex prediction
Radhika Juglan, Marta Ligero, Zunamys I. Carrero, Asier Rabasco Meneghetti et al.
2026-12 · DOI: 10.1186/s40708-026-00316-yParkinson’s disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography
Khosro Rezaee, Hossein Ghayoumi Zadeh, Ali Fayazi
2026-12 · DOI: 10.1186/s40708-026-00317-xA quantitative and precision‑oriented neuronal reconstruction approach based on data grading
Mingwei Liao, Chi Xiao, Xiaojun Wang, Qingming Luo et al.
2026-12 · DOI: 10.1186/s40708-026-00314-0Reviews
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Version History
October 4, 2026 at 8:53 pm
September 25, 2026