The behavioral and neural sciences are a nerdy interest of mine, but I didn’t dedicate any episode to that topic yet. But life brings you gifts sometimes (especially around Christmas…), and here that gift is a book, Bayesian Data Analysis for the Behavioral and Neural Sciences, by Todd Hudson.
Todd is a part of the faculty at New York University Grossman School of Medicine and also the New York University Tandon School of Engineering. He is a computational neuroscientist working in several areas including: early detection and grading of neurological disease; computational models of movement planning and learning; development of new computational and experimental techniques.
He also co-founded Tactile Navigation Tools, which develops navigation aids for the visually impaired, and Third Eye Technologies, which develops low cost laboratory- and clinical-grade eyetracking technologies.
As you’ll hear, Todd wanted his book to bypass the need for advanced mathematics normally considered a prerequisite for this type of material. Basically, he wants students to be able to write code and models and understand equations, even they are not specialized in writing those equations.
We’ll also touch on some of the neural sciences examples he’s got in the book, as well as the two general algorithms he uses for model measurement and model selection.
Ow, I almost forgot the most important: Todd loves beekeeping and gardening — he’s got 25 apple trees, 4 cherry trees, nectarines, figs, strawberries, etc!
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !
Thank you to my Patrons for making this episode possible!
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