Brain Inspired

BI 143 Rodolphe Sepulchre: Mixed Feedback Control

Aug 5, 2022

01:24:53

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Is There a Resurgence of Dynamical Systems Theory?

02:48

How Do You Know if You're Working on the Right Thing?

05:07

Sense of Robustness in a Neural Network

02:10

Introduction

5min

Control Engineers Are Really Engineering Science, Right?

3min

Is There No Room for Control Theorists and Machine Learning?

4min

Is There a Resurgence of Dynamical Systems Theory?

3min

Building a Braina

4min

Did You Look at a Neural Signal?

4min

Positive Fidback and Negative Feedback

2min

Logics and Neural Networks

2min

Design Principle Under Uncertainty

2min

10.

Eve's Work on the Stomatogastric Gang on of the Lobster N Crab

2min

11.

I've Had a Long Journey in My Career, I'm Thinking More About My Bisy Students and Pussos

4min

12.

The Challenge in Modelling the Stematogastric Ganglion

3min

13.

How Do You Think of Higher Cognitive Functions as Control?

2min

14.

Central Pattern Generator - How to Generate a Rate Out of a Single Syle

5min

15.

The Neuromorphic Approach to the St G

2min

16.

Are We at the Right Level of Abstraction?

2min

17.

How to Control a Spike

2min

18.

Sense of Robustness in a Neural Network

2min

19.

Is There a Theory to Handle Spikes?

3min

20.

We Don't Need Spikes. They're Irrelevant, Right?

3min

21.

Is There Something Besides Power Efficiency That We Can Add?

3min

22.

Using Deep Learning Models to Understand Brains

4min

23.

Is There a Convergence of Nora Science?

3min

24.

Neuro Science Needs More Engineers

5min

25.

I Think That We Need More Engineer in Neurau Science

2min

26.

Is There a Role for Philosophy in Science?

3min

27.

How Do You Know if You're Working on the Right Thing?

5min

28.

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3min

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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 papers
Related episodes:
- BI 130 Eve Marder: Modulation of Networks
- BI 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

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