Ioana, Konrad, and I talk about ways causality can be inferred using data from quasi-experiments, the role economics and econometrics has played, causality in AI, some of the ins and outs of marriage in academia, and plenty more.
Kendrick and I discuss his models that predict how the human brain responds to pictures of faces and words, how we make decisions about those pictures, and how our brain gears up for such tasks. We also discuss models in general- what they are, how we should judge them, and so on, plus a few of his other projects and…. wait for it… lots more.
John and I discuss how understanding behaviors first will improve understanding how brains generate those behaviors, the state of neuroscience, plus the role of philosophy in science, lots of resources along those lines, and lots more.
Tim and I discuss his work suggesting grid cell-like coding could provide a map for us to navigate abstract concepts in our minds – a cognitive map. We talk about the discovery of place cells and grid cells and the work suggesting they contribute to spatial navigation. We also touch on how Tim’s work is related to meta-reinforcement learning (a la Matt Botvinick, see episode 21), and how grid cell codes might contribute to AI systems moving forward.
Marcel and I discuss his recent work using generative adversarial networks to decode brain activity to reconstruct images people saw, his work to restore vision to blind humans by stimulating early visual cortex, general AI, and even — shutter — consciousness a bit.