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Computer Science - Artificial Intelligence | Brain Informatics - a SpringerOpen journal

Brain Informatics

Brain Informatics

Brain Data Computing and Health Studies

Editors-in-Chief: N. Zhong; J. Liu

ISSN: 2198-4018 (print version)
ISSN: 2198-4026 (electronic version)

Journal no. 40708

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Brain Informatics is an international, peer-reviewed, interdisciplinary open-access journal published under the brand SpringerOpen, which provides a unique platform for researchers and practitioners to disseminate original research on computational technologies related to the human brain and cognition. This journal will publish high-quality original research papers, brief reports and critical reviews in all theoretical, technological, clinical and interdisciplinary studies that make up the field of brain informatics and its applications in brain-inspired intelligent systems, health studies, etc.

The Brain Informatics journal addresses the computational, cognitive, physiological, biological, physical, ecological and social perspectives of brain informatics, as well as topics relating to mental health and well-being. It also welcomes emerging information technologies, including but not limited to Internet/Web of Things (IoT/WoT), cloud computing, big data analytics and interactive knowledge discovery related to brain research. The journal also encourages submissions that explore how advanced computing technologies are applied to and make a difference in various large-scale brain studies and their applications.

Informatics-enabled studies are transforming brain science. New methodologies enhance human interpretive powers when dealing with big data sets increasingly derived from advanced neuro-imaging technologies, including fMRI, PET, MEG, EEG and fNIRS, as well as from other sources like eye-tracking and from wearable, portable, micro and nano devices. New experimental methods, such as in toto imaging, deep tissue imaging, opto-genetics and dense-electrode recording are generating massive amounts of brain data at very fine spatial and temporal resolutions. These technologies allow measuring, modeling, managing and mining of multiple forms of big brain data. Brain informatics techniques for analyzing all the data will help achieve a better understanding of human thought, memory, learning, decision-making, emotion, consciousness and social behaviors. These methods also assist in building brain-inspired, human-level wisdom-computing paradigms and technologies, improving the treatment efficacy of mental health and brain disorders.

This is an open access journal, which is freely accessible online to anyone, anywhere. The open access fees (article-processing charges) are fully sponsored. Authors can publish in the journal without any additional charges.

Related subjects » Artificial Intelligence - Cognitive Psychology - Neuroscience - Theoretical Computer Science

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    Brain Informatics is an international, peer-reviewed, interdisciplinary open-access journal published under the brand SpringerOpen, which provides a unique platform for researchers and practitioners to disseminate original research on computational technologies related to the human brain and cognition. This journal will publish high-quality original research papers, brief reports and critical reviews in all theoretical, technological, clinical and interdisciplinary studies that make up the field of brain informatics and its applications in brain-inspired intelligent systems, health studies, etc.

    The Brain Informatics journal addresses the computational, cognitive, physiological, biological, physical, ecological and social perspectives of brain informatics, as well as topics relating to mental health and well-being. It also welcomes emerging information technologies, including but not limited to Internet/Web of Things (IoT/WoT), cloud computing, big data analytics and interactive knowledge discovery related to brain research. The journal also encourages submissions that explore how advanced computing technologies are applied to and make a difference in various large-scale brain studies and their applications.

    Informatics-enabled studies are transforming brain science. New methodologies enhance human interpretive powers when dealing with big data sets increasingly derived from advanced neuro-imaging technologies, including fMRI, PET, MEG, EEG and fNIRS, as well as from other sources like eye-tracking and from wearable, portable, micro and nano devices. New experimental methods, such as in toto imaging, deep tissue imaging, opto-genetics and dense-electrode recording are generating massive amounts of brain data at very fine spatial and temporal resolutions. These technologies allow measuring, modeling, managing and mining of multiple forms of big brain data. Brain informatics techniques for analyzing all the data will help achieve a better understanding of human thought, memory, learning, decision-making, emotion, consciousness and social behaviors. These methods also assist in building brain-inspired, human-level wisdom-computing paradigms and technologies, improving the treatment efficacy of mental health and brain disorders.

    This is an open access journal, which is freely accessible online to anyone, anywhere. The open access fees (article-processing charges) are fully sponsored. Authors can publish in the journal without any additional charges.

    The scope of papers includes the following topics:

     1. Thinking and perception-centric investigations of human information processing system (HIPS) and computational foundations of brain science

    • Adaptation and self-organization;
    • Bayesian models of the brain, and causal modeling of behaviour for neurology
    • Brain dynamics and functional/resting/structural networks;
    • Cognitive architectures and their relations to fMRI/EEG/MEG;
    • Computational mechanisms of learning and memory;
    • Computational models of sensory-motor control;
    • Conscious mental functions and subconscious information processing;
    • Emotion, heuristic search, information granularity, and autonomy related issues in reasoning and problem solving;
    • Higher-order cognitive functions and their relationships;
    • HIPS complex systems;
    • Investigating spatiotemporal characteristics and flow in HIPS and the related neural structures and neurobiological process;
    • Learning mechanisms (e.g., stability, personalized user/student models);
    • Methodologies for systematic design of cognitive experiments;
    • Models of executive function & prefrontal cortex;
    • Modeling brain information processing mechanisms (e.g., information organization, neuromechanism, mathematical, cognitive and computational models of HIPS);
    • Multi-perception mechanisms and visual, auditory, and tactile information processing;
    • Neural basis of decision-making;
    • Neural foundations of intelligent behavior;
    • Reasoning mechanisms (e.g., principles of deductive/inductive reasoning, common-sense reasoning, decision making, and problem solving);
    • Social brain communication.

    2. Information technologies for curating, mining, and using brain big data

    • Brain data collection, pre-processing, management, and analysis methodologies;
    • Brain connectome, functional connectivity, and multi-level brain networks;
    • Brain data grids and brain research support services;
    • Brain informatics provenances;
    • Brain mapping and visualization;
    • Cyber-individuals and individual differences;
    • Data brain modeling and formal conceptual models of brain data;
    • Databasing the brain, curating big data, and constructing brain data centers;
    • Development of data-driven markers of diseases, and behavioural biomarkers of neurological diseases;
    • fMRI and PET imaging registration and analysis;
    • Information technologies for simulating brain data;
    • Integrating multiple forms of brain big data obtained from atomic and molecular levels to the entire brain;
    • Knowledge representation and discovery in neuroimaging;
    • Large scale models and simulation of brains;
    • Machine learning algorithms for brain data analysis;
    • Measuring scale thresholds of brain big data;
    • Multi-aspect analysis in fMRI/DTI/EEG/ERP/MEG/PET/Eye-tracking data;
    • Multimedia brain data mining and reasoning;
    • Multimodal and combinatorial fusion for brain informatics;
    • Optogenetics and in-vivo cell imaging analytics;
    • Real-time fMRI and neurofeedback;
    • Remote neurological assessment;
    • Semantic technology for brain data integration;
    • Simulating and analysing spatiotemporal structure, characteristics and flows in HIPS and neural data;
    • Statistical analysis and pattern recognition in neuroimaging.

    3. Brain-inspired technologies, systems and applications

    • Affective computing and applications;
    • Brain/Cognition inspired computing and artificial systems;
    • Brain-computer interfaces and brain-robot interfaces;
    • Brains connecting to the Internet of Things;
    • Brain repair models and simulations;
    • Clinical diagnosis and pathology of brain and mind/mental-related diseases (e.g., mild cognitive impairment, alzheimers, dementia & neuro-degeneration, depression, epilepsy, autism, Parkinson’s disease, and cerebral palsy);
    • Cloud and semantic brain data services;
    • Cognitive and decision support;
    • Computational approaches to rehabilitation;
    • Computational intelligence methodologies for mental healthcare;
    • Computational psychiatry;
    • Digital, data, and computational brain;
    • e-Science, e-Health, and e-Medicine;
    • Mental healthcare knowledge abstraction, classification, representation, and summarization;
    • Mental healthcare knowledge computerization, execution, inference, and management;
    • Mental health risk evaluation and modeling;
    • Neuro/Emotional robotics, computer vision and intelligent robotic networks;
    • Neuroeconomics and neuromarketing;
    • Neuroeducation, neurolinguistics, and neuroinstrumentation;
    • New cognitive and computational models of intelligent systems;
    • Non-verbal communication;
    • Personal, wearable, ubiquitous, micro and nano devices for mental healthcare;
    • Remote neurological assessment;
    • Social networks, social media, and e-learning for spreading mental health awareness;
    • WaaS (Wisdom as a Service) and active services for mental healthcare.
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