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Python for the practicing  neuroscientist: an online educational resource
  • +5
  • Emily Schlafly,
  • Anthea Cheung,
  • Samantha W Michalka,
  • Paul A. Lipton,
  • Caroline Moore-Kochlacs,
  • Jason Bohland,
  • Uri T. Eden,
  • Mark Kramer
Emily Schlafly
Graduate Program in Neuroscience, Boston University, Massachusetts 02215
Anthea Cheung
Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215
Samantha W Michalka
Olin College of Engineering, Needham, MA 02492
Paul A. Lipton
Princeton School of Public and International Affairs, Princeton University, Princeton NJ 08544
Caroline Moore-Kochlacs
Graduate Program in Neuroscience, Boston University, Massachusetts 02215
Jason Bohland
Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA 15260
Uri T. Eden
Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215
Mark Kramer
Center for Systems Neuroscience, Boston University, Boston, Massachusetts 02215 , Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215
Author Profile

Abstract

As neuronal data accumulates worldwide, accessible - yet rigorous - resources to develop hands-on experience with modern data analysis techniques are required. We present here an online educational resource for neural data analysis (https://mark-kramer.github.io/Case-Studies-Python). To reach the biologists, psychologists, and clinicians collecting neuronal data, we assume only a basic mathematics background, common to those trained in biological sciences. Through an interdisciplinary case-study approach, we use real-world data to motivate the study of modern quantitative analysis methods in Python. A modular format provides multiple coherent learning paths through the material, and thereby allows personalized learning for individuals with varying quantitative backgrounds and research interests, and flexible curation of material for redeployment in other curricula. Developed using Jupyter notebooks, the material supports fully interactive environments in most web browsers, and hosted on GitHub, the material is freely available for reuse, modification, and further development by the community.