The Allen Mouse Brain Atlas is a genome-wide, high-resolution atlas of gene expression throughout the adult mouse brain. This tutorial describes the basic search and navigation features of the Allen Mouse Brain Atlas.

The Allen Developing Mouse Brain Atlas is a detailed atlas of gene expression across mouse brain development. This tutorial describes the basic search and navigation features of the Allen Developing Mouse Brain Atlas.

This tutorial demonstrates how to use the differential search feature of the Allen Mouse Brain Atlas to find gene markers for different regions of the brain, as well as to visualize this gene expression in three-dimensional space. Differential search is also available for the Allen Developing Mouse Brain Atlas and the Allen Human Brain Atlas.

This lesson gives an introduction, opening statements, and motivating arguments for this workshop. 

This lecture highlights the importance of correct annotation and assignment of location, and updated atlas resources to avoid errors in navigation and data interpretation.

We are at the exciting technological stage where it has become feasible to represent the anatomy of an entire human brain at the cellular level. This lecture discusses how neuroanatomy in the 21st Century has become an effort towards the virtualization and standardization of brain tissue.

This lecture covers essential features of digital brain models for neuroinformatics, particularly NeuroMaps. 

This presentation covers the neuroinformatics tools and techniques used and their relationship to neuroanatomy for the Allen Institute's atlases of the mouse, developing mouse, and mouse connectional atlas.

This module covers some basic anatomy such as the brain’s major divisions (brainstem, cerebellum, cerebrum), the cerebral lobes (frontal, temporal, parietal, and occipital), the central and peripheral nervous systems, theories of cognition, and brain orientation terms.

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

This lesson delves into the the structure of one of the brain's most elemental computational units, the neuron, and how said structure influences computational neural network models. 

Following the previous lesson on neuronal structure, this lesson discusses neuronal function, particularly focusing on spike triggering and propogation. 

This lesson goes over the basic mechanisms of neural synapses, the space between neurons where signals may be transmitted. 

While the previous lesson in the Neuro4ML course dealt with the mechanisms involved in individual synapses, this lesson discusses how synapses and their neurons' firing patterns may change over time. 

Whereas the previous two lessons described the biophysical and signalling properties of individual neurons, this lesson describes properties of those units when part of larger networks. 

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

This lesson provides an introduction to the myriad forms of cellular mechanisms whicn underpin healthy brain function and communication. 

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

This lesson provides an introduction to the course Cellular Mechanisms of Brain Function.

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.