This is also a live debate in philosophy of science about eliminativism vs. pluralism regarding concepts with multiple meanings
Attention and emotion are both cases

press.uchicago.edu/ucp/books/bo...

link.springer.com/article/10.1...

Finally, Patrick McGivern pronouncing the Metabolic Turn in philosophy of cognition, with work on the role of metabolism for non-neural cognition, such as bacteria chemotaxis (4/4)

Thanks to all speakers and participants for the great Q&A!

#philsky
#neuroskyence
#cognition
#metabolism

Turning to evolution, Matthew Sims (in joint work w Marta Halina) explained how predictive brain models may have evolved from corollary discharge, which itself resulted from the need to distinguish external input from sensory feedback once nervous systems relied on sensorimotor integration (3/4)

Next was a talk by @jtheriault.bsky.social presenting a metabolic model of „activity“ in neuroimaging, suggesting that stimulus elicited BOLD responses Track prediction error processing in the brain, but not baseline metabolic load related to processing predictions (2/4)

There’s also the Journal of Unsolved questions that only accepts failed experiments etc

www.mainz.uni-mainz.de/activities/j...

Agreed! I’m usually skeptical of edited volumes,but could see the value here bc many will know failure cases from their respective disciplines

I wrote on conceptual retirement here www.sciencedirect.com/science/arti...
This preprint also has more general thoughts on revising concepts (basis for one of the chapters): philsci-archive.pitt.edu/21213/

I’m also very interested in that (as I’m writing a book on successful and failed conceptual development atm) @smellosopher.bsky.social has a paper on failure in neuroscience here www.frontiersin.org/journals/neu...
But yes, there might be a problem of the archive in finding out about failures, no?

If you agree with our 5 requests to our universities, please sign 🖊️ the open letter and don’t forget to confirm your email! ☺️🙏

openletter.earth/open-letter-...

It’s an epistemic notion of reduction, where it’s about the explanatory knowledge gained. I’m not defending it as the right notion of reduction, just clarifying what Dan Burnston means by it. If you have a stronger view of reduction, then sure it’s not reductive.

I mean it all depends about what you mean by „reductive“. For the author of the paper it means that 1) there’s a conceptual link between decision and accumulation to bound and 2) that the neural models have explanatory advantages (more detailed prediction, unification, explaining anomalies) (1/2)

whether there are implicit ontological assumptions even in this epistemic approach, or whether we’d allow ‚weird‘ reductions where neuroscience is reduced to some future higher order cybernetic science. Check out the paper here link.springer.com/article/10.1...

#philsky
#neuroskyence
#philsci

Also tried to make it all more precise when being a bit more mature here: link.springer.com/article/10.1...

Nice to see that some like @jtheriault.bsky.social are moving broadly in that direction (or a my mentor would say: they’re barking up the same alley ;)

I wrote about this when a was a Phil sci kid here: www.frontiersin.org/article/10.3...
(Getting some hmms from neuroskeptic back in the day @micahgallen.com )

(2/2) the role of information theory for efficient coding explanations, realistic and idealistic interpretations of computational models, and how Chirimuuta‘s thinking on this developed into the book „The Brain Abstracted“ mitpress.mit.edu/978026254804...

#neuroskyence
#philsci
#philosophy
#edusky

2/2 (when should we accept or reject characterizations of phenomena?), and big picture issues (realism vs conventionalism). Here’s the link to Dave’s paper: www.sciencedirect.com/science/arti...
Also stay tuned for his upcoming book on the history of memory transfer and the philosophy of memory!