EEG

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.

  • Neuroscience
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Akshay Sujatha Ravindran, Jesus G. Cruz-Garza, Anastasiya Kopteva, Andrew Paek, Aryan Mobiny, Zachary Hernandez, Jose Luis Contreras-Vidal

    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.

  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Jesus G. Cruz-Garza, Justin A Brantley, Sho Nakagome, Kim Kontson, Dario Robleto, Jose L. Contreras-Vidal

    The provided EEG data were acquired from sixteen healthy young adults (age range 22 - 30 years) with no history of neurological, physical, or psychiatric illness. All the participants were naive BCI users who had not participated in any related experiments before. Informed consents were received from all participants.  The study has been approved by the Institutional Research Ethics Committee of Nazarbayev University.  

     

  • Medical Imaging
  • Last Updated On: 
    Sun, 05/19/2019 - 08:11

    Mobile Brain-Body Imaging (MoBI) technology was deployed at the Museo de Arte Contemporáneo (MARCO) in Monterrey, México, in an effort to collect Electroencefalographic (EEG) data from large numbers (N = ~1200) of participants and allow the study of the brain’s response to artistic stimuli, as part of the studies developed by University of Houston (TX, USA) and Tecnológico de Monterrey (MTY, México).

  • Neuroscience
  • Last Updated On: 
    Thu, 12/27/2018 - 12:23

    This dataset consists of raw EEG data from 48 subjects who participated in a multitasking workload experiment utilizing the SIMKAP multitasking test. The subjects’ brain activity at rest was also recorded before the test and is included as well. The Emotiv EPOC device, with sampling frequency of 128Hz and 14 channels was used to obtain the data, with 2.5 minutes of EEG recording for each case. Subjects were also asked to rate their perceived mental workload after each stage on a rating scale of 1 to 9 and the ratings are provided in a separate file.

  • Biophysiological Signals
  • Last Updated On: 
    Tue, 07/10/2018 - 02:19

    This hackathon is co-located with the 42nd IEEE International Conference on Computers, Software & Application. The hackathon event will take place July 23-24 in Tokyo, Japan.
    Register here: https://ieeecompsac.computer.org/2018/big-data-hackathon-registration/
    More details: https://bigdatawg.nist.gov/bdgmm_compsac2018.html

  • Neuroscience
  • Brain
  • Last Updated On: 
    Tue, 04/02/2019 - 11:51
    Citation Author(s): 
    J.A. Anguera, J. Boccanfuso, J.L. Rintoul, O. Al-Hashimi, F. Faraji, J. Janowich, E. Kong, Y.Larraburo, C. Rolle, E. Johnston and A. Gazzaley

    Previous neuroimaging research has been traditionally confined to strict laboratory environments due to the limits of technology. Only recently have more studies emerged exploring the use of mobile brain imaging outside the laboratory. This study uses electroencephalography (EEG) and signal processing techniques to provide new opportunities for studying mobile subjects moving outside of the laboratory and in real world settings. The purpose of this study was to document the current viability of using high density EEG for mobile brain imaging both indoors and outdoors.

  • Neuroscience
  • Last Updated On: 
    Sat, 06/16/2018 - 23:16