
Show Notes
As computational neuroscientists, the members of this podcast take for granted the fact that math can be used to describe the brain. But is this ability of math trivial or deeply surprising? On this episode we tackle the large philosophical issues behind computational sciences, with the help of a set of articles entitled "The Unreasonable Effectiveness of Mathematics in the Natural Sciences" (1960) and "The Unreasonable Effectiveness of Mathematics" (1980). These articles, written by mathematicians, claim that the ability of mathematics to explain the world is unexpectedly impressive. This leads us to a set of questions: What is math? What is the world? And how do we know what to expect from either? Is this ability of math truly unreasonable or did it just appear so at a certain time? As we explore these ideas we discuss thought experiments involving artificial intelligence and real experiments involving the Cold War. We also hypothesize on the role of elegance in mathematics and what "understanding" really means to us as humans.
More from Unsupervised Thinking
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.com/h9dn4bw7 On this cross-posting of Brain Inspired, Grace talks about the book and the field of computational neuroscience more generally. Give it a listen and go check out other episodes of Brain Inspired for more great conversations.
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 needed to get these little blobs to grow, and the extent to which they mimic features of the human brain when they do. We also discuss the promise of studying and treating disease through personalized organoids, and how this gets hard for higher level disorders like schizophrenia. Then we get into questions of embodiment and if giving these organoids more means to interact with the world would make them better models of the brain and of information processing. Finally we get to the ethics of it all, and find that bioethicists these days are actually chill AF. Throughout, we find out that Josh is not surprised by any of this, and we tackle the pressing moral issue of our time: is it OK to eat your thermostat?
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 needed to get these little blobs to grow, and the extent to which they mimic features of the human brain when they do. We also discuss the promise of studying and treating disease through personalized organoids, and how this gets hard for higher level disorders like schizophrenia. Then we get into questions of embodiment and if giving these organoids more means to interact with the world would make them better models of the brain and of information processing. Finally we get to the ethics of it all, and find that bioethicists these days are actually chill AF. Throughout, we find out that Josh is not surprised by any of this, and we tackle the pressing moral issue of our time: is it OK to eat your thermostat?
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 most of our abilities the result of genetically-encoded instructions, honed over generations of evolution? Or are our interactions with the environment key? We discuss the research that has been done on human brain development to try to get at the answers to these questions. We take about the compromise position that says animals may be "born to learn"---that is, innate tendencies help make sure the right training data is encountered and used efficiently during development. We also get into what all this means for AI and whether machine learning researchers should be learning less. Throughout, we ask if humans are special, argue that development can happen without learning, and discuss the special place of the octopus in the animal kingdom.
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 fully functional, which impacts the shape and role of the brain. As a result, the system is best thought of as a whole---not chunked into perception, cognition and action, as many psychologists and neuroscientists are wont to do. In discussing these arguments, we talk about the role of representations in intelligence, go through a bit of the evolution of the nervous system, and remind ourselves that evolution does not necessarily optimize. Throughout, we ask how this take on neuroscience impacts our own work and try to avoid saying "represents".