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#55 Neuropsychology, Illusions & Bending Reality, with Dominique Makowski

#55 Neuropsychology, Illusions & Bending Reality, with Dominique Makowski

FromLearning Bayesian Statistics


#55 Neuropsychology, Illusions & Bending Reality, with Dominique Makowski

FromLearning Bayesian Statistics

ratings:
Length:
74 minutes
Released:
Jan 31, 2022
Format:
Podcast episode

Description

What’s the common point between fiction, fake news, illusions and meditation? They can all be studied with Bayesian statistics, of course!
In this mind-bending episode, Dominique Makowski will for sure expand your horizon. Trained as a clinical neuropsychologist, he is currently working as a postdoc at the Clinical Brain Lab in Singapore, in which he leads the Reality Bending Team. What’s reality-bending you ask? Well, you’ll have to listen to the episode, but I can already tell you we’ll go through a journey in scientific methodology, history of art, religion, and philosophy — what else?
Beyond that, Dominique tries to improve the access to advanced analysis techniques by developing open-source software and tools, like the NeuroKit Python package or the bayestestR package in R.
Even better, he looks a lot like his figures of reference. Like Marcus Aurelius, he plays the piano and guitar. Like Sisyphus, he loves history of art and comparative mythology. And like Yoda, he is a wakeboard master.
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ (https://bababrinkman.com/) !
Thank you to my Patrons for making this episode possible!
Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Aaron Jones, Daniel Lindroth, Yoshiyuki Hamajima, Sven De Maeyer and Michael DeCrescenzo.
Visit https://www.patreon.com/learnbayesstats (https://www.patreon.com/learnbayesstats) to unlock exclusive Bayesian swag ;)
Links from the show:
To follow:
Dominique's website: https://dominiquemakowski.github.io/ (https://dominiquemakowski.github.io/)
Dominique on Twitter: https://twitter.com/Dom_Makowski (https://twitter.com/Dom_Makowski)
Dominique on GitHub: https://github.com/DominiqueMakowski (https://github.com/DominiqueMakowski)
Packages:
NeuroKit -- Python Toolbox for Neurophysiological Signal Processing: https://github.com/neuropsychology/NeuroKit (https://github.com/neuropsychology/NeuroKit)
bayestestR -- Become a Bayesian master you will: https://easystats.github.io/bayestestR/ (https://easystats.github.io/bayestestR/)
report -- From R to your manuscript: https://easystats.github.io/report/ (https://easystats.github.io/report/)
Research:
The Reality Bending League :https://realitybending.github.io/research/ (https://realitybending.github.io/research/)
What is Reality Bending: https://realitybending.github.io/post/2020-09-28-what_is_realitybending/ (https://realitybending.github.io/post/2020-09-28-what_is_realitybending/)
Art:
NeuropsyXart -- Neuroimaging methods to obtain visual representations of neurophysiological processes: https://dominiquemakowski.github.io/NeuropsyXart/ (https://dominiquemakowski.github.io/NeuropsyXart/)



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Released:
Jan 31, 2022
Format:
Podcast episode

Titles in the series (100)

Are you a researcher or data scientist / analyst / ninja? Do you want to learn Bayesian inference, stay up to date or simply want to understand what Bayesian inference is? Then this podcast is for you! You'll hear from researchers and practitioners of all fields about how they use Bayesian statistics, and how in turn YOU can apply these methods in your modeling workflow. When I started learning Bayesian methods, I really wished there were a podcast out there that could introduce me to the methods, the projects and the people who make all that possible. So I created "Learning Bayesian Statistics", where you'll get to hear how Bayesian statistics are used to detect black matter in outer space, forecast elections or understand how diseases spread and can ultimately be stopped. But this show is not only about successes -- it's also about failures, because that's how we learn best. So you'll often hear the guests talking about what *didn't* work in their projects, why, and how they overcame these challenges. Because, in the end, we're all lifelong learners! My name is Alex Andorra by the way, and I live in Paris. By day, I'm a data scientist and modeler at the https://www.pymc-labs.io/ (PyMC Labs) consultancy. By night, I don't (yet) fight crime, but I'm an open-source enthusiast and core contributor to the python packages https://docs.pymc.io/ (PyMC) and https://arviz-devs.github.io/arviz/ (ArviZ). I also love https://www.pollsposition.com/ (election forecasting) and, most importantly, Nutella. But I don't like talking about it – I prefer eating it. So, whether you want to learn Bayesian statistics or hear about the latest libraries, books and applications, this podcast is for you -- just subscribe! You can also support the show and https://www.patreon.com/learnbayesstats (unlock exclusive Bayesian swag on Patreon)! This podcast uses the following third-party services for analysis: Podcorn - https://podcorn.com/privacy