Lectures related to Biologically Inspired Computation

Neuronal Plasticity: Synaptic Changes and Brain Functioning

Explores neuronal plasticity, synaptic changes, brain functioning, and unconscious states through various mechanisms.

Engineering in the Age of AI: Innovations and Challenges

Examines the transformative impact of AI on engineering disciplines and the associated challenges.

Controlling Behavior in Animals and Robots

Explores embodied behavioral control in animals and robots through group presentations and hands-on exercises.

Building Physical Neural Networks

Discusses challenges in building physical neural networks, focusing on depth, connections, and trainability.

Introduction into the module MOOC: Simulation Neurocience

Introduces nerve cells' electrical activity, focusing on spikes and synaptic potentials.

Bio-Inspired Learning: Neural Networks, Genetic Algorithms

Explores bio-inspired learning with neural networks and genetic algorithms, covering structure, training, and practical applications.

Deep Learning: Fundamentals

Covers the fundamentals of deep learning, from artificial neurons to modern networks.

Neural Modeling: From Sensory Systems to Behavior

Explores neural modeling of sensory systems and behavior using deep neural networks and task-driven networks.

Understanding Neurorobotics

Explores the link between intelligence, the brain, and behavior through neurorobotics.

Cellular Mechanisms of Brain Function

Covers the structure of a neuroscience course, focusing on cell membrane, ion channels, synaptic transmission, and brain function.

Neural Networks

Explores neural networks, hidden layers, weight adjustments, activation functions, and the universal approximation theorem.

Understanding Proprioception: Neural Network Models Log in to Mediaspace to watch this video

Explores how neural networks can help understand proprioception and muscle contraction.

Neuroscience and Machine Learning: Understanding Visual Intelligence Log in to Mediaspace to watch this video

Explores the relationship between neuroscience and machine learning in visual intelligence.

Data-Driven Modeling in Neuroscience: Meenakshi Khosla Log in to Mediaspace to watch this video

By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.

Neural Taskonomy and Historical Perspectives in Visual Intelligence Log in to Mediaspace to watch this video

Covers Neural Taskonomy, the evolution of neural networks, and historical perspectives in visual intelligence.

Machine Learning Models for Neuroscience Log in to Mediaspace to watch this video

Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.

Introduction to Systems Neuroscience: Memory Systems Overview Log in to Mediaspace to watch this video

Introduces systems neuroscience, focusing on neural circuits, memory systems, and course logistics.

Neuroscience and AI: Bridging the Gap Log in to Mediaspace to watch this video

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

Graph Neural Networks: Interconnected World Log in to Mediaspace to watch this video

Explores learning from interconnected data with graphs, covering modern ML research goals, pioneering methods, interdisciplinary applications, and democratization of graph ML.

Computer Vision: Historical Insights and Project Inspirations Log in to Mediaspace to watch this video

Explores the historical development of computer vision and inspires innovative project ideas.