Neuroscience

One of the grand challenges in neuroscience is to understand the developing brain ‘in action and in context’ in complex natural settings. To address this challenge, it is imperative to acquire brain data from freely-behaving children to assay the variability and individuality of neural patterns across gender and age.

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  • Neuroscience
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34

    Recent advances in scalp electroencephalography (EEG) as a neuroimaging tool have now allowed researchers to overcome technical challenges and movement restrictions typical in traditional neuroimaging studies.  Fortunately, recent mobile EEG devices have enabled studies involving cognition and motor control in natural environments that require mobility, such as during art perception and production in a museum setting, and during locomotion tasks.

    1247 views
  • Biomedical and Health Sciences
  • Last Updated On: 
    Tue, 11/12/2019 - 10:38

    This dataset is associated with the paper, Jackson & Hall 2016, which is open source, and can be found here: http://ieeexplore.ieee.org/document/7742994/

    The DataPort Repository contains the data used primarily for generating Figure 1.

    687 views
  • Biomedical and Health Sciences
  • Last Updated On: 
    Sat, 06/16/2018 - 23:05

    Ten volunteers were trained through a series of twelve daily lessons to type in a computer using the Colemak keyboard layout. During the fourth-, eight-, and eleventh-session, electroencephalography (EEG) measurements were acquired for the five trials each subject performed in the corresponding lesson. Electrocardiography (ECG) data at each of those trials were acquired as well. The purpose of this experiment is to aim in the development of different methods to assess the process of learning a new task.

    320 views
  • Neuroscience
  • Last Updated On: 
    Thu, 06/25/2020 - 17:14

    This Dataset contains EEG recordings from epileptic rats. The genetic absence epilepsy rats (GAERS) are one of the best-established rodent models for generalized epilepsy. The rats show seizures with characteristic "spike and wave discharge" EEG patterns. Experiments were performed in accordance with the German law on animal protection and were approved by the Animal Care and Ethics Committee of the University of Kiel.

    32 views
  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 07/09/2020 - 16:06

     

    Participants were 61 children with ADHD and 60 healthy controls (boys and girls, ages 7-12). The ADHD children were diagnosed by an experienced psychiatrist to DSM-IV criteria, and have taken Ritalin for up to 6 months. None of the children in the control group had a history of psychiatric disorders, epilepsy, or any report of high-risk behaviors.

     

    546 views
  • Machine Learning
  • Last Updated On: 
    Mon, 06/15/2020 - 02:42

    The behavioral and ERP Data of online shopping festival experiment

    36 views
  • Neuroscience
  • Last Updated On: 
    Mon, 05/25/2020 - 21:44

    Dataset asscociated with a paper to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence

    "The perils and pitfalls of block design for EEG classification experiments"

    The paper has been accepted and is in production.

    We will upload the dataset when the paper is published.

    This is a placeholder so we can obtain a DOI to include in the paper.

    74 views
  • Artificial Intelligence
  • Last Updated On: 
    Fri, 04/24/2020 - 16:39

    EEG signals of various subjects in text files are uploaded. It can be useful for various EEG signal processing algorithms- filtering, linear prediction, abnormality detection, PCA, ICA etc.

    124 views
  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 06/11/2020 - 06:34

    BCI-Double-ErrP-Dataset is an EEG dataset recorded while participants used a P300-based BCI speller. This speller uses a P300 post-detection based on Error-related potentials (ErrPs) to detect and correct errors (i.e. when the detected symbol does not match the user’s intention). After the P300 detection, an automatic correction is made when an ErrP is detected (this is called a “Primary ErrP”). The correction proposed by the system is also evaluated, eventually eliciting a “Secondary ErrP” if the correction is wrong.

    200 views
  • Machine Learning
  • Last Updated On: 
    Fri, 03/20/2020 - 08:13

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