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BI 143 Rodolphe Sepulchre: Mixed Feedback Control

BI 143 Rodolphe Sepulchre: Mixed Feedback Control

FromBrain Inspired


BI 143 Rodolphe Sepulchre: Mixed Feedback Control

FromBrain Inspired

ratings:
Length:
85 minutes
Released:
Aug 5, 2022
Format:
Podcast episode

Description

Check out my free video series about what's missing in AI and Neuroscience






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Rodolphe Sepulchre is a control engineer and theorist at Cambridge University. He focuses on applying feedback control engineering principles to build circuits that model neurons and neuronal circuits. We discuss his work on mixed feedback control - positive and negative - as an underlying principle of the mixed digital and analog brain signals,, the role of neuromodulation as a controller, applying these principles to Eve Marder's lobster/crab neural circuits, building mixed-feedback neuromorphics, some feedback control history, and how "If you wish to contribute original work, be prepared to face loneliness," among other topics.



Rodolphe's website.Related papersSpiking Control Systems.Control Across Scales by Positive and Negative Feedback.Neuromorphic control. (arXiv version)Related episodes:BI 130 Eve Marder: Modulation of NetworksBI 119 Henry Yin: The Crisis in Neuroscience



0:00 - Intro
4:38 - Control engineer
9:52 - Control vs. dynamical systems
13:34 - Building vs. understanding
17:38 - Mixed feedback signals
26:00 - Robustness
28:28 - Eve Marder
32:00 - Loneliness
37:35 - Across levels
44:04 - Neuromorphics and neuromodulation
52:15 - Barrier to adopting neuromorphics
54:40 - Deep learning influence
58:04 - Beyond energy efficiency
1:02:02 - Deep learning for neuro
1:14:15 - Role of philosophy
1:16:43 - Doing it right
Released:
Aug 5, 2022
Format:
Podcast episode

Titles in the series (99)

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.