This lesson provides a brief introduction to the Neuroscience Information Exchange (NIX) Format data model, which allows storing fully annotated scientific datasets, i.e., data combined with rich metadata and their relations in a consistent, comprehensive format.

This lesson provides an overview of Neurodata Without Borders (NWB), an ecosystem for neurophysiology data standardization. The lecture also introduces some NWB-enabled tools. 

This lecture discusses the FAIR principles as they apply to electrophysiology data and metadata, the building blocks for community tools and standards, platforms and grassroots initiatives, and the challenges therein.

This lecture contains an overview of electrophysiology data reuse within the EBRAINS ecosystem.

This lecture contains an overview of the Distributed Archives for Neurophysiology Data Integration (DANDI) archive, its ties to FAIR and open-source, integrations with other programs, and upcoming features.

This lecture contains an overview of the Australian Electrophysiology Data Analytics Platform (AEDAPT), how it works, how to scale it, and how it fits into the FAIR ecosystem.

This lecture discusses how to standardize electrophysiology data organization to move towards being more FAIR.

This lecture will provide an overview of the INCF Training Suite, a collection of tools that embraces the FAIR principles developed by members of the INCF Community. This will include an overview of TrainingSpace, Neurostars, and KnowledgeSpace.

This lecture contains an overview of the China-Cuba-Canada neuroinformatics ecosystem for Quantitative Tomographic EEG Analysis (qEEGt).

This lecture covers the emergence of cognitive science after the Second World War as an interdisciplinary field for studying the mind, with influences from anthropology, cybernetics, and artificial intelligence.

This lesson provides an introduction to neurons, synaptic transmission, and ion channels.

This lecture consists of the second half of the introduction to signal transduction, here focusing on cell receptors and signalling cascades.

This lecture gives an introduction to the types of glial cells, homeostasis (influence of cerebral blood flow and influence on neurons), insulation and protection of axons (myelin sheath; nodes of Ranvier), microglia and reactions of the CNS to injury.

Followers of this lesson wilul learn about the origin and differentiation of myelinating cell types, molecular mechanisms defining onset and progression of myelination, as well as demyelination and remyelination after injury.

This lecture covers integrating information within a network, modulating and controlling networks, functions and dysfunctions of hippocampal networks, and the integrative network controlling sleep and arousal.

This lecture focuses on the comprehension of nociception and pain sensation, highlighting how the somatosensory system and different molecular partners are involved in nociception.

This lesson provides an overview of how to construct computational pipelines for neurophysiological data using DataJoint.

This lesson covers the ionic basis of the action potential, including the Hodgkin-Huxley model. 

In this lesson you will learn about the ionic basis of the action potential, including the Hodgkin-Huxley model. 

This lesson covers membrane potential of neurons, and how parameters around this potential have direct consequences on cellular communication at both the individual and population level.