This lectures series provides Introduction to neuroinformatics.
Topics covered:
Data analysis and neuronal coding databases and ontologies, multiscale modeling, neuroengineering, simulation/computation/workflows, visualization
This lectures series provides Introduction to neuroinformatics.
Topics covered:
Data analysis and neuronal coding databases and ontologies, multiscale modeling, neuroengineering, simulation/computation/workflows, visualization
This lecture covers an introduction to neuroinformatics and its subfields, the content of the short course and future neuroinformatics applications.
This lecture covers an introduction to connectomics, and image processing tools for the study of connectomics.
This lecture covers modeling the neuron in silicon, modeling vision and audition and sensory fusion using a deep network.
This lecture gives an introduction to simulation, models, and the neural simulation tool NEST.
This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.
This lecture covers describing and characterizing an input-output relationship.
This lecture covers acquisition techniques, the physics of MRI, diffusion imaging, prediction using fMRI.
This lecture covers structured data, databases, federating neuroscience-relevant databases, ontologies.