Cabrera9114/Eduardo-Cabrera-Lopez-ITAI4374-Neuroscience-AI

This repository documents an 11‑module course on neuroscience and brain‑inspired AI, aimed at graduate students, researchers, and engineers working at the NeuroAI/ML intersection. It covers foundational neuroscience (predictive coding, Bayesian brain, cortical columns), computational models (LIF neurons, spiking neural networks, surrogate gradients), memory and learning (hippocampal replay, experience replay, transformer/RAG memory), attention and consciousness (transformer attention, Global Workspace), decision making and world models (active inference, DreamerV3, MuZero), neuro‑symbolic integration, and embodied cognition/robotics. Key features: hands‑on labs and projects (Python and Wolfram simulations), neuromorphic hardware topics (Intel Loihi2), event‑based vision, multimodal perception exercises, and a semester Bio‑Inspired AI Audit of ChatGPT (scorecard, demos). Skills developed include AI experimentation, prompt engineering, technical reporting, and comparative neuroscience‑AI evaluation.