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Unsupervised Thinking


A podcast about neuroscience, artificial intelligence, and science more broadly, run by a group of computational neuroscientists.

Popular episodes

Models of the Mind: How physics, engineering and mathematics have shaped our understanding of the brain

Jun 16 • 01:18:47
Grace wrote a book! And she talked to Brain Inspired host Paul Middlebrooks about it.
The book is about the many different ways mathematical methods have influenced neuroscience, from models of single cells all the way up to equations to explain behavior. You can learn more about the book and how to get it in ebook, audiobook, and hard cover worldwide by visiting tinyurl.c...

E50: Brain Organoids

Oct 30 • 01:00:28
Most neuroscience research takes place in a full, live animal. But brain organoids are different. Brain organoids are three-dimensional blobs of brain grown from human stem cells and they offer novel access to the study of human brain development. On this episode we go beyond our computational comfort zone to talk about the history of stem cells, the potion of chemicals ne...

E49: How Important is Learning?

Oct 1 • 01:06:42
The age-old debate of nature versus nurture is now being played out between artificial intelligence and neuroscience. The dominant approach in AI, machine learning, puts an emphasis on adapting processing to fit the data at hand. Animals, on the other hand, seem to have a lot of built in structure and tendencies, that mean they function well right out of the womb. So are m...

E48: Studying the Brain in Light of Evolution

Aug 29 • 59:58
The brain is the result of evolution. A lot of evolution. Most neuroscientists don't really think about this fact. Should we? On this episode we talk about two papers---one focused on brains and the other on AI---that argue that following evolution is the path to success. As part of this argument, they make the point that, in evolution, each stage along the way needs to be...

E47: Deep Learning to Understand the Brain

Jul 30 • 01:05:00
The recent advances in deep learning have done more than just make money for startups and tech companies. They've also infiltrated neuroscience! Deep neural networks---models originally inspired by the basics of the nervous system---are finding ever more applications in the quest to understand the brain. We talk about many of those uses in the episode. After first describi...

E46: What We Learn from Model Organisms

Jun 27 • 01:01:05
From worms to flies, and mice to macaques, neuroscientists study a range (but not very large range...) of animals when they study "the brain". On this episode we ask a lot of questions about these model organisms, such as: how are they chosen? should we use more diverse ones? and what is a model organism actually a model of? We also talk about how the development of geneti...

E45: How Working Memory Works

May 29 • 59:20
Working memory is the ability to keep something in mind several seconds after it's gone. Neurons don't tend to keep firing when their input is removed, so how does the brain hold on to information when it's out of sight? Scientists have been probing this question for decades. On this episode, we talk about how working memory is studied and the traditional view of how it wo...

E44: Can a Biologist Fix a Radio?

Apr 25 • 01:05:15
In 2002, cancer biologist Yuri Lazebnik raised and addressed the semi-facetious question "Can a biologist fix a radio?" in a short paper. The paper is a critique of current practices in the biological sciences, claiming they are inefficient at getting to truth. We discuss the stages of research progress in biological science Yuri describes, including the "paradoxical" stag...

E43: What Are Glia Up to?

Mar 28 • 01:05:07
Despite the fact that the brain is full of them, glial cells don't get much attention from neuroscientists. The traditional view of these non-neurons is that they are supportive cells---there to silently help neurons do what they need to do. On this episode we start by describing this traditional view, including types of glial cells and their roles. Then we get into the mo...

E42: Learning Rules, Biological vs. Artificial

Feb 26 • 01:02:30
For decades, neuroscientists have explored the ways in which neurons update and control the strength of their connections. For slightly fewer decades, machine learning researchers have been developing ways to train the connections between artificial neurons in their networks. The former endeavour shows us what happens in the brain and the latter shows us what's actually ne...

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