Brain Inspired

BI 148 Gaute Einevoll: Brain Simulations

Sep 25, 2022

01:28:48

Creator website

Highlights

AI Chapters

Episode notes

Neural Oscillatory Dynamics

03:54

How Do You Extract Principles From Complex Model Simulations?

04:41

Synapses and Synaptic Plasticity

02:57

Introduction

3min

The Difference Between Beautiful and Ugly Models

2min

Ugly Models

6min

Is the Human Brain Project Going to End?

3min

Is There Pushback From the Neuroscience Community?

2min

A Review of the Scientific Case for Brain Simulations

6min

The Degeneracy in Neuroscience

2min

Isfot Reglan, You're a Patrand Subscriber to Podcast

3min

How Do You Extract Principles From Complex Model Simulations?

5min

10.

A and Hen Be Able to Extract Some Principles From Comparing the Different Granularity Models

2min

11.

Agnostic Tools

3min

12.

Predicting Local Field Potentials of a Neural Network

2min

13.

The History of Spikes in the Brain of an Animal

2min

14.

The Local Field Potential Is a Spectral Measurement of the Neurons

2min

15.

Do Lf P Signals Predict Spikes?

3min

16.

Measurement Physics

5min

17.

The Usefulness Form for Modelling Signals

2min

18.

Computition Neuro Science Community Is Not So Big, Right?

4min

19.

Synapses and Synaptic Plasticity

3min

20.

How Do You Decide How Many Components?

2min

21.

The Importance of Local Field Potentials in Paramidal Neurons

3min

22.

Aspects of Forward Modeling of Electrical A, Electrical Signals

4min

23.

Scaling Up Neural Field Models

5min

24.

Is Local Field Potential a Way to Predict an LFP Signal?

2min

25.

Neural Oscillatory Dynamics

4min

26.

How to Measure a Neural Network?

2min

27.

I Think It's a Fantastic Opportunity for for Newer Scinceone

3min

28.

The Connection Between Deep Learning and Nervo Science

3min

29.

Do You Think Simulation Based Deep Learning Could Help Artificial Intelligence?

4min

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Gaute Einevoll is a professor at the University of Oslo and Norwegian University of Life Sciences. Use develops detailed models of brain networks to use as simulations, so neuroscientists can test their various theories and hypotheses about how networks implement various functions. Thus, the models are tools. The goal is to create models that are multi-level, to test questions at various levels of biological detail; and multi-modal, to predict that handful of signals neuroscientists measure from real brains (something Gaute calls "measurement physics"). We also discuss Gaute's thoughts on Carina Curto's "beautiful vs ugly models", and his reaction to Noah Hutton's In Silico documentary about the Blue Brain and Human Brain projects (Gaute has been funded by the Human Brain Project since its inception).

Gaute's website.
Twitter: @GauteEinevoll.
Related papers:
LFPy: a Python module for calculation of extracellular potentials from multicompartment neuron models.
Gaute's Sense and Science podcast.

0:00 - Intro 3:25 - Beautiful and messy models 6:34 - In Silico 9:47 - Goals of human brain project 15:50 - Brain simulation approach 21:35 - Degeneracy in parameters 26:24 - Abstract principles from simulations 32:58 - Models as tools 35:34 - Predicting brain signals 41:45 - LFPs closer to average 53:57 - Plasticity in simulations 56:53 - How detailed should we model neurons? 59:09 - Lessons from predicting signals 1:06:07 - Scaling up 1:10:54 - Simulation as a tool 1:12:35 - Oscillations 1:16:24 - Manifolds and simulations 1:20:22 - Modeling cortex like Hodgkin and Huxley