Philipp Haueis

More press about our BBS paper on metabolism and cognition:

aktuell.uni-bielefeld.de/2025/11/24/t...

#neuroskyence #cogsky #philsci

Bei Gehirnmodellen den Stoffwechsel mitdenken MCMP-Studie: Kognitive Theorien sollten metabolische Grenzen berücksichtigen

For German speakers, LMU just posted a press release on our BBS target article „Metabolic considerations for cognitive modeling“

www.lmu.de/de/newsroom/...

#cogsky #neuroskyence #philsky #philsci

#philsci #cogsky #CognitiveNeuroscience

@phaueis.bsky.social and I have had our paper, “Metabolic considerations for cognitive modeling,” accepted as a target article in Behavioral and Brain Sciences.

www.cambridge.org/core/journal...

You can access the preprint here: doi.org/10.1017/S014...

Also, consider writing a commentary if this falls in your area of expertise! (3/3)

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Our philosophical framework has foundational implications for psychological models of mental effort, medium independence of computation and comparing biological cognition and AI (2/3)

Very exciting news to share! Me and @davidcolaco.bsky.social published a target article in BBs on metabolism and cognition! We argue that models of cognition should incorporate metabolism - either to evaluate if existing models are biologically plausible, or to generate new models (1/3)

One of my favorite papers! If you want to go further and delve intro the philosophy of science discussion: www.cambridge.org/core/journal...
🐸🧠

A chalkboard showing a patchwork model of the gene concept. On the left is the classical gene patch, with the technique of cross-breeding, scale of whole organisms, and the property of patterns of inheritance. On the right is the molecular gene patch, with X Ray crystallography as technique, the molecular scale and the property of DNA. The patches partially overlap because the DNA is involved in intergenerational inheritance between parent and offspring, but also explains how proteins are produced while offspring develops.

This is why it’s fun to teach on your research: today we discussed a chapter of my book on patchwork concepts in science. The students asked if we try can build a patchwork, and so we used the case of “gene“ from the previous session, which I hadn’t analyzed explicitly before!
#philsci

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...

School of Ideas in Neuroscience 2025 has started today with a talk by @phaueis.bsky.social!

The deadline is approaching! We wait for your applications till Monday, July 21st!

Philosopher Patrick McGivern, wearing a white shirt and blue jeans, explaining the „metabolic turn“, i.e. the importance of metabolism for understanding cognition

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

Philosopher Matthew Sims, wearing a black shirt and beige pants showing a slide on ctenophores, a creature with external passive sensory receptors and epithelial sheets for locomotion

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)

Neuroscientist Jordan Theriault wearing a blue shirt and black pants pointing at a slide that shows the relation between glucose metabolism and signals measured with functional magnetic resonance imaging.

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)

Philosopher David Colaço, eating a black suit jacket, white shirt and black tie in front of an image with a white balloon with „energy“ written in blue, a blue sky and white clouds on the back, some green tree canopies in front.

Had a great session on the relation between metabolism and cognition at BSPS Glasgow, organized by @davidcolaco.bsky.social . We presented joint work on using metabolism to constrain and generate cognitive models (1/2)

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

The death of the cortical column? Patchwork structure and conceptual retirement in neuroscientific practice In 1981, David Hubel and Torsten Wiesel received the Nobel Prize for their research on cortical columns—vertical bands of neurons with similar functio…

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/

Frontiers | The Value of Failure in Science: The Story of Grandmother Cells in Neuroscience The annals of science are filled with successes. In footnotes do we hear about the failures, the cul-de-sacs, and the forgotten ideas. Failure is how researc...

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?

• Resist the introduction of AI in our own software systems, from Microsoft to OpenAI to Apple. It is not in our interests to let our processes be corrupted and give away our data to be used to train models that are not only useless to us, but also harmful. • Ban AI use in the classroom for student assignments, in the same way we ban essay mills and other forms of plagiarism. Students must be protected from de-skilling and allowed space and time to perform their assignments themselves. • Cease normalising the AI hype and the lies which are prevalent in the technology industry's framing of these technologies. The technologies do not have the advertised capacities and their adoption puts students and academics at risk of violating ethical, legal, scholarly, and scientific standards of reliability, sustainability, and safety. • Fortify our academic freedom as university staff to enforce these principles and standards in our classrooms and our research as well as on the computer systems we are obliged to use as part of our work. We as academics have the right to our own spaces. • Sustain critical thinking on AI and promote critical engagement with technology on a firm academic footing. Scholarly discussion must be free from the conflicts of interest caused by industry funding, and reasoned resistance must always be an option.

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)

Epistemic reduction of the concept of ‘decision’ - Synthese “Reduction” is a widely rejected view of how commonsense psychological notions relate to neuroscience. I argue that there is a particular view of reduction on which reduction of the key commonsense co...

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...

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As the semester days get hot, our Phil neuroscience readings are hot off the press: today we talked about Dan Burnston’s latest: epistemic reduction of ‚decision‘ to accumulate to bound models in neuroscience. We discussed which aspects of decision can or cannot be reduced by these models (1/2)

Beyond cognitive myopia: a patchwork approach to the concept of neural function - Synthese In this paper, I argue that looking at the concept of neural function through the lens of cognition alone risks cognitive myopia: it leads neuroscientists to focus only on mechanisms with cognitive fu...

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 ;)

Frontiers | Meeting the brain on its own terms In contemporary human brain mapping, it is commonly assumed that the “mind is what the brain does”. Based on that assumption, task-based imaging studies of t...

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 )

Serious question:

why is theory development in neuroscience so damn hard?

New research from MIT found that those who used ChatGPT can’t remember any of the content of their essays.

Key takeaway: the product doesn’t suffer, but the process does. And when it comes to essays, the process *is* how they learn.

arxiv.org/pdf/2506.088...

The Brain Abstracted All science needs to simplify, but when the object of research is something as complicated as the brain, this challenge can stretch the limits of scientific ...

(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...

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#philosophy
#edusky

Another gem from our Phil Neuroscience seminar: Mazviita Chirimuuta on canonical computations and explanation in neuroscience: link.springer.com/article/10.1...
We discussed what distinguishes mechanistic from minimal model explanations, how to identify neural details relevant to explanation (1/2)