Neuroscience

Related lectures (32)

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Covers principles of simulation neuroscience, dense reconstructions, bottom-up approach, and modeling trade-offs.

Explores the gap between AI and human intelligence through neuroscience-inspired models and algorithms.

Explores systems neuroscience and brain interactions using various technologies for potential clinical applications.

Introduces modeling in neuroscience, focusing on the brain's complexity and investigation methods.

Covers downloading, extracting, compiling, and visualizing single cell models for analysis and simulation.

Covers the use of eFEL for automated analysis of neuronal traces and parameter optimisation.

Presents the Master in Neuro-X program, emphasizing its interdisciplinary approach and career opportunities in neurotechnology.

Delves into brain network modules, modularity, and community structure, including dynamic modularity and upcoming midterm details.

Explores brain fingerprinting, maximizing identifiability, and the potential clinical applications of the concept.

Introduces the basics of brain connectomics, including terminology, data preprocessing, functional MRI, connectivity measures, and modular structure.