This lecture and tutorial focuses on measuring human functional brain networks. The lecture and tutorial were part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Lecture on functional brain parcellations and a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation which were part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Introduction to the central concepts of machine learning, and how they can be applied in Python using the Scikit-learn Package. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

This talk gives an overview of the Human Brain Project, a 10-year endeavour putting in place a cutting-edge research infrastructure that will allow scientific and industrial researchers to advance our knowledge in the fields of neuroscience, computing, and brain-related medicine.

This lecture gives an introduction to the European Academy of Neurology, ist recent achievements and ambitions.

This lecture covers NeuronUnit, a library that builds upon SciUnit and integrates with several existing neuroinformatics resources to support validating single-neuron models using data gathered by neurophysiologists.

An introduction to the NeuroElectro project, which aims to organize information on cellular neurophysiology. Speaker: Shreejoy Tripathy

Simultaneously recorded neurons in non-human primates coordinate their spiking activity in a sequential manner that mirrors the dominant wave propagation directions of the local field potentials.

This talk covers statistical analysis of spike train data, the modeling approach GLM, and the problem of assessing neural synchrony.

This talk covers statistical methods for characterizing neural population responses and extracting structure from high-dimensional neural data.

This presentation covers research to understand the activity of single neurons and populations of neurons in the visual system.

Learn how to create a standard extracellular electrophysiology dataset in NWB using Python

Learn how to create a standard calcium imaging dataset in NWB using Python

Learn how to create a standard intracellular electrophysiology dataset in NWB

Learn how to use the icephys-metadata extension to enter meta-data detailing your experimental paradigm

Learn how to build and share extensions in NWB

Learn how to build custom APIs for extension

Learn how to handle writing very large data in PyNWB

Learn how to create a standard extracellular electrophysiology dataset in NWB using MATLAB

Learn how to create a standard calcium imaging dataset in NWB using MATLAB