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Computational models provide a framework for integrating data across spatial scales and for exploring hypotheses about the biological mechanisms underlying neuronal and network dynamics. However, as models increase in complexity, additional barriers emerge to the creation, exchange, and re-use of models. Successful projects have created standards for describing complex models in neuroscience and provide open source tools to address these issues. This lecture provides an overview of these projects and make a case for expanded use of resources in support of reproducibility and validation of models against experimental data.

Difficulty level: Beginner
Duration: 1:00:39
Speaker: : Sharon Crook

NWB: An ecosystem for neurophysiology data standardization

Difficulty level: Beginner
Duration: 29:53
Speaker: : Oliver Ruebel

Introductory presentation on how data science can help with scientific reproducibility.

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.

Difficulty level: Beginner
Duration: 37:51

Introduction to the principal of anatomical organization of neural systems in the human brain and spinal cord that mediate sensation, integrate signals, and motivate behavior.

Difficulty level: Beginner
Duration: 59:57

This lecture focuses on the comprehension of nociception and pain sensation. It highlights how the somatosensory system and different molecular partners are involved in nociception and how nociception and pain sensation are studied in rodents and humans and the development of pain therapy.

Difficulty level: Beginner
Duration: 28:09
Speaker: : Serena Quarta