This lecture covers the linking neuronal activity to behavior using AI-based online detection. 

This lesson gives an in-depth introduction of ethics in the field of artificial intelligence, particularly in the context of its impact on humans and public interest. As the healthcare sector becomes increasingly affected by the implementation of ever stronger AI algorithms, this lecture covers key interests which must be protected going forward, including privacy, consent, human autonomy, inclusiveness, and equity. 

This lecture provides an introduction to the course "Cognitive Science & Psychology: Mind, Brain, and Behavior".

This lecture goes into further detail about the hard problem of developing a scientific discipline for subjective consciousness.

This lecture covers a lot of post-war developments in the science of the mind, focusing first on the cognitive revolution, and concluding with living machines.

This brief talk goes into work being done at The Alan Turing Institute to solve real-world challenges and democratize computer vision methods to support interdisciplinary and international researchers. 

In this final lecture of the INCF Short Course: Introduction to Neuroinformatics, you will hear about new advances in the application of machine learning methods to clinical neuroscience data. In particular, this talk discusses the performance of SynthSeg, an image segmentation tool for automated analysis of highly heterogeneous brain MRI clinical scans.

This lecture covers computational principles that growth cones employ to detect and respond to environmental chemotactic gradients, focusing particularly on growth-cone shape dynamics.

In this lecture you will learn that in developing mouse somatosensory cortex, endogenous Btbd3 translocate to the cell nucleus in response to neuronal activity and oriente primary dendrites toward active axons in the barrel hollow.

In this presentation, the speaker describes some of their recent efforts to characterize the transcriptome of the developing human brain, and and introduction to the BrainSpan project.

How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.

This lesson describes a definitional framework for fairness and health equity in the age of the algorithm. While acknowledging the impressive capability of machine learning to positively affect health equity, this talk outlines potential (and actual) pitfalls which come with such powerful tools, ultimately making the case for collaborative, interdisciplinary, and transparent science as a way to operationalize fairness in health equity. 

This lesson is the first part of a three-part series on the development of neuroinformatic infrastructure to ensure compliance with European data privacy standards and laws. 

This is the second of three lectures around current challenges and opportunities facing neuroinformatic infrastructure for handling sensitive data. 

This lesson contains the first part of the lecture Data Science and Reproducibility. You will learn about the development of data science and what the term currently encompasses, as well as how neuroscience and data science intersect. 

This lecture gives a tour of what neuroethics is and how it applies to neuroscience and neurotechnology, while also addressing justice concerns within both fields. 

This lecture presents selected theories of ethics as applied to questions raised by the Human Brain Project.

The HBP as an ICT flagship project crucially relies on ICT and will contribute important input into the development of new computing principles and artefacts. Individuals working on the HBP should therefore be aware of the long history of ethical issues discussed in computing. This lessson provides an overview of the most widely discussed ethical issues in computing and demonstrate that privacy and data protection are by no means the only issue worth worrying about. 

This lecture explores two questions regarding the ethics of robot development and use. Firstly, the increasingly urgent question of the ethical use of robots: are there particular applications of robots that should be proscribed, in eldercare, or surveillance, or combat? Secondly, the talk deals with the longer-term question of whether intelligent robots themselves could or should be ethical.

In this lesson, attendees will learn about the challenges involved in working with life scientists to enhance their capacity for understanding, and taking responsibility for, the social implications of their research.