Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.
https://braininspired.co/series/brain-inspired/
BI 061 Jörn Diedrichsen and Niko Kriegeskorte: Brain Representations
Jörn, Niko and I continue the discussion of mental representation from last episode with Michael Rescorla, then we discuss their review paper, Peeling The Onion of Brain Representations, about different ways to extract and understand what information is represented in measured brain activity patterns.
Show notes:
- Jörn's lab website.
- Niko's lab website.
- Jörn on twitter: DiedrichsenLab.
- Niko on twitter: KriegeskorteLab.
- The papers we discuss or mention:
- Peeling the Onion of Brain Representations. Annual Review of Neuroscience, 2019
- Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis. PLoS, 2017.