This lesson provides an overview of the database of Genotypes and Phenotypes (dbGaP), which was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in humans.

This lecture covers the ethical implications of the use of brain-computer interfaces, brain-machine interfaces, and deep brain stimulation to enhance brain functions and was part of the Neuro Day Workshop held by the NeuroSchool of Aix Marseille University.

This module covers many types of invasive neurotechnology devices/interfaces for the central and peripheral nervous systems. Invasive neurotech devices are crucial, as they often provide the greatest accuracy and long-term use applicability.

This lesson gives an introduction to the Mathematics chapter of Datalabcc's Foundations in Data Science series.

This lesson serves a primer on elementary algebra.

This lesson provides a primer on linear algebra, aiming to demonstrate how such operations are fundamental to many data science. 

In this lesson, users will learn about linear equation systems, as well as follow along some practical use cases.

This talk gives a primer on calculus, emphasizing its role in data science.

This lesson clarifies how calculus relates to optimization in a data science context. 

This lesson covers Big O notation, a mathematical notation that describes the limiting behavior of a function as it tends towards a certain value or infinity, proving useful for data scientists who want to evaluate their algorithms' efficiency.

This lesson serves as a primer on the fundamental concepts underlying probability. 

Serving as good refresher, this lesson explains the maths and logic concepts that are important for programmers to understand, including sets, propositional logic, conditional statements, and more.

This compilation is courtesy of freeCodeCamp.

This lesson provides a useful refresher which will facilitate the use of Matlab, Octave, and various matrix-manipulation and machine-learning software.

This lesson was created by RootMath.

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 lecture provides an introduction to Plato’s concept of rationality and Aristotle’s concept of empiricism, and the enduring discussion between rationalism and empiricism to this day.

This lecture covers different perspectives on the study of the mental, focusing on the difference between Mind and Brain. 

This lecture covers the three big questions: What is the universe?, what is life?, and what is consciousness?

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.