This lecture provides an introduction to optogenetics, a biological technique to control the activity of neurons or other cell types with light.
This primer on optogenetics primer discusses how to manipulate neuronal populations with light at millisecond resolution and offers possible applications such as curing the blind and "playing the piano" with cortical neurons.
This lecture covers the history of behaviorism and the ultimate challenge to behaviorism.
In this lesson, you will learn how to utilize various features and tools included in the EBRAINS platform, particularly focusing on rodent brain atlases and how to incorporate them into your analyses.
This talk describes how to use DataLad for your data management and curation techniques when dealing with animal datasets, which often contain several disparate types of data, including MRI, microscopy, histology, electrocorticography, and behavioral measurements.
In this short talk you will learn about The Neural System Laboratory, which aims to develop and implement new technologies for analysis of brain architecture, connectivity, and brain-wide gene and molecular level organization.
In this lesson, you will learn about the connectome, the collective system of neural pathways in an organism, with a closer look at the neurons, synapses, and connections of particular species.
This lesson introduces the practical exercises which accompany the previous lessons on animal and human connectomes in the brain and nervous system.
In this lecture, attendees will learn how Mutant Mouse Resource and Research Center (MMRRC) archives, cryopreserves, and distributes scientifically valuable genetically engineered mouse strains and mouse ES cell lines for the genetics and biomedical research community.
This lecture discusses how to standardize electrophysiology data organization to move towards being more FAIR.
This lesson contains practical exercises which accompanies the first few lessons of the Neuroscience for Machine Learners (Neuro4ML) course.
This video briefly goes over the exercises accompanying Week 6 of the Neuroscience for Machine Learners (Neuro4ML) course, Understanding Neural Networks.
This lecture covers the description and characterization of an input-output relationship in a information-theoretic context.
This lesson is part 1 of 2 of a tutorial on statistical models for neural data.
This lesson is part 2 of 2 of a tutorial on statistical models for neural data.
This lesson provides an introduction to modeling single neurons, as well as stability analysis of neural models.
This lesson continues a thorough description of the concepts, theories, and methods involved in the modeling of single neurons.
In this lesson you will learn about fundamental neural phenomena such as oscillations and bursting, and the effects these have on cortical networks.
This lesson continues discussing properties of neural oscillations and networks.
In this lecture, you will learn about rules governing coupled oscillators, neural synchrony in networks, and theoretical assumptions underlying current understanding.