Brain Informatics View Homepage


Ontology type: schema:Periodical      Open Access: True


Journal Info

START YEAR

2014

PUBLISHER

Springer Berlin Heidelberg

LANGUAGE

en

HOMEPAGE

https://braininformatics.springeropen.com/about

Recent publications latest 20 shown

  • 2019-12 A machine learning approach to predict perceptual decisions: an insight into face pareidolia
  • 2019-12 How Amdahl's Law limits the performance of large artificial neural networks : why the functionality of full-scale brain simulation on processor-based simulators is limited.
  • 2019-12 Improved shuffled frog leaping algorithm on system reliability analysis
  • 2019-12 The role of artificial intelligence and machine learning in harmonization of high-resolution post-mortem MRI (virtopsy) with respect to brain microstructure
  • 2018-12 Brain MRI analysis for Alzheimer’s disease diagnosis using an ensemble system of deep convolutional neural networks
  • 2018-12 Side-channel attacks against the human brain: the PIN code case study (extended version)
  • 2018-12 A review and outlook on visual analytics for uncertainties in functional magnetic resonance imaging
  • 2018-12 A structural equation model for imaging genetics using spatial transcriptomics
  • 2018-12 Correction to: Two-step verification of brain tumor segmentation using watershed-matching algorithm
  • 2018-12 Automated epileptic seizures detection using multi-features and multilayer perceptron neural network
  • 2018-12 A 3D stereotactic atlas of the adult human skull base
  • 2018-12 Various epileptic seizure detection techniques using biomedical signals: a review
  • 2018-12 Review of EEG-based pattern classification frameworks for dyslexia
  • 2018-12 The effects of emotional states and traits on time perception
  • 2018-12 WaaS architecture-driven depressive mood status quantitative analysis based on forehead EEG and self-rating tool
  • 2018-12 Mental state and emotion detection from musically stimulated EEG
  • 2018-12 Two-step verification of brain tumor segmentation using watershed-matching algorithm
  • 2018-12 Thought Chart: tracking the thought with manifold learning during emotion regulation
  • 2018-12 DeepNeuron: an open deep learning toolbox for neuron tracing
  • 2018-03 Identification and classification of brain tumor MRI images with feature extraction using DWT and probabilistic neural network
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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.

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    For those of you who are US government employees or are prevented from being copyright holders for similar reasons, SpringerOpen can accommodate non-standard copyright lines. Please\u00a0contact info@springeropen.com\u00a0if further information is needed.

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