Technical resources

 

  • UC Davis DataLab

  • UC Davis DataLab is a cross-university effort that fosters, promotes, and facilitates data science to accelerate discovery within and across the scientific, engineering, social and humanities disciplines. 
    DataLab data scientists engage in all activities involved in working with this wealth of data—from identification to interpretation—to help extract meaning and generate critical insights for decision making and innovation.

    We combine computing, statistics, mathematics, visualization, software development, and domain knowledge to make inferences from various forms of information (including but not limited to numerical, text, audio, and visual data). Our workflows involve engineering, reproducibility and provenance, and often include software development and design.

    Training activities at the DataLab highlight the theory, methods, process, and tools for working with and interpreting data. We focus on cultivating curiosity and creativity as well as communication and critical thinking skills in students and researchers across UC Davis.

  • ERPLAB Toolbox
  • https://github.com/ucdavis/erplab
    This is a freely available, NIH-funded, open-source Matlab toolbox for processing and analyzing event-related potential data. Courtesy of professor Steve Luck.
  • ERP CORE
  • https://erpinfo.org/erp-core
    The ERP CORE is a freely available online resource consisting of optimized paradigms, experiment control scripts, example data from 40 participants, data processing pipelines and analysis scripts, and a broad set of results for 7 different ERP components obtained from 6 different ERP paradigms. Courtesy of professor Steve Luck.
  • Introduction to ERPs
  • https://courses.erpinfo.org/courses/Intro-to-ERPs 
    This is a free online course intended for anyone from undergraduates through senior faculty. It was launched on August 1, 2020. Courtesy of professor Steve Luck.
  • Luck, S. J. (2022). Applied Event-Related Potential Data Analysis. Free online book.
  • LibreTexts. https://doi.org/10.18115/D5QG92
    Courtesy of professor Steve Luck.
  • The Good Research Code Handbook
  • The Good Research Code Handbook by Patrick Mineault, PhD. This handbook is for grad students, postdocs and PIs who do a lot of programming as part of their research.
  • NEMAR.org - An NIMH data, tools, and compute resource for human electrophysiological data
  • NEMAR.org
    NEMAR is an open access data, tools, and compute resource for finding, assessing and processing human NeuroElectroMagnetic data (EEG, MEG, iEEG) shared by its authors thru OpenNeuro.org.
  • Essentials of Neuroscience with MATLAB - by Mike X Cohen, in collaboration with Mathworks
  • The Essentials of Neuroscience With MATLAB course was developed to provide advanced undergraduates and early graduate students with a basic familiarity with MATLAB programming with an opportunity to deepen their expertise in neuroscience data analysis using MATLAB. 
    It's 5 video-based modules that cover spiking, EEG, modeling, fMRI, and calcium imaging. Each module comes with detailed video explanations, code files, and exercises.
  • HPC for Absolute Beginners - by Virginia Scarlett, PhD, UC Santa Barbara
  • This guide is for absolute beginners to on-premises high-performance computing.