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Bowen Zheng

@bwz-brain.bsky.social
152 followers 278 following 17 posts

MIT BCS | grad Full time human

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Reposted by Bowen Zheng
Richard Sever @richardsever.bsky.social · 27/08/2026
$3.7 billion spent on APCs in 2025. That's ~1000X more than it costs to run bioRxiv/medRxiv. Worth thinking about as we consider how to fund infrastructure... arxiv.org/pdf/2608.16322
arxiv.org
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Yasmine El-Shamayleh @elshamayleh.bsky.social · 26/08/2026
Excited to share the lab’s first publication, co-led by talented postdoc Chuyi Su @chuyisu.bsky.social We leveraged cell type-specific optogenetics in the macaque cerebral cortex to elucidate the role of excitatory and inhibitory neurons in visual form processing. www.nature.com/articles/s41...
nature.com
Optotagging in primate cortex uncovers excitatory and inhibitory neuron specializations in form vision - Nature Communications
This study leverages cell type-specific optogenetics in the monkey cerebral cortex to elucidate the unique functional contributions of excitatory and inhibitory neurons in visual form processing. The ...
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Adrian Roggenbach @a-roggenbach.bsky.social · 24/08/2026
⚠️PREPRINT ALERT⚠️ How can we better understand distributed brain activity across temporal and spatial scales? In this collaborative project, we combined ultra-flexible electrodes with two-photon imaging to illuminate brain-wide neural dynamics. Link: doi.org/10.21203/rs.... 1/8
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Tianyuan Teng @tyteng.bsky.social · 13/08/2026
You'd think people prefer the simplest explanation of an uncertain world — Occam's razor. Our data says no, across 2 modalities, 2 tasks, 8 experiments: people often perceive illusory structure that isn't there and prefer moderate complexity. Out now in Nature Comms! www.nature.com/articles/s41...
nature.com
Human learning of probability distributions is biased toward moderate structural complexity - Nature Communications
Humans build internal models from online observations to adapt to new environments. Here, the authors show that individuals are biased towards building models with moderate structural complexity, rega...
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Philip Ball @philipcball.bsky.social · 10/08/2026
"The central challenge is no longer building models that reproduce biological behavior, but building models from which causal structure can be inferred." Very sensible paper about not just throwing everything into your simulation or model. arxiv.org/abs/2608.06998
arxiv.org
Simulating is not always understanding: When model complexity obscures biology
In cell biology, computational models of biological systems range from minimal representations with a handful of parameters to whole-cell simulations tracking thousands of molecular species across a c...
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Stanley Heinze @stanley-heinze.bsky.social · 30/07/2026
New preprint! www.biorxiv.org/content/10.6... Nearly a decade after starting the project, the first major results from our comparative connectomics work is online! Comparing the head direction circuits of the central complex in bees, ants and flies, recapitulating >300million years of evolution.
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Richard Gast @rgast.bsky.social · 27/07/2026
The Ott-Antonsen ansatz revolutionized our understanding of coupled oscillator systems with heterogeneous oscillators. We developed a multi-ensemble method that increases the applicability of the OA ansatz to empirical data substantially arxiv.org/abs/2607.09516, as we demonstrate on neural data.
arxiv.org
A multi-ensemble mean-field reduction method for networks of globally coupled phase oscillators with arbitrary parameter distributions
Understanding the dynamical properties of coupled phase oscillator systems with heterogeneous oscillator frequencies has been a long-standing challenge of complex systems theory. While the seminal wor...
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Grace Lindsay @neurograce.bsky.social · 26/06/2026
Updated preprint and code from my lab. If you want to explore more realistic neural dynamics in models that can still perform visual tasks, check it out! www.biorxiv.org/content/10.1...
biorxiv.org
Modeling Dynamical Vision with Biologically Plausible Recurrent Convolutional Networks
Convolutional Neural Networks (CNNs) trained for image recognition have demonstrated remarkable conceptual similarities to the primate ventral visual pathway, but their standard feedforward architectu...
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Bowen Zheng @bwz-brain.bsky.social · 20/06/2026
Finally putting this work out as a preprint :) Thanks to Emery Brown and @earlkmiller.bsky.social for helping conceptualize this work! Code: github.com/Bowen-Zheng-... and a tutorial notebook on the key ideas: github.com/Bowen-Zheng-... A 3-min overview below: (1/)
github.com
GitHub - Bowen-Zheng-99/joint-ssmt: Bayesian state-space model for joint inference of oscillatory dynamics and point-process coupling
Bayesian state-space model for joint inference of oscillatory dynamics and point-process coupling - Bowen-Zheng-99/joint-ssmt
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Laura Rustarazo-Calvo @laura-rustarazo.bsky.social · 27/03/2025
🎉 Excited to share our new work: “Adhesion-driven tissue rigidification triggers epithelial cell polarity”, now on @biorxivpreprint.bsky.social ! A huge thank you to @nicolettapetridou.bsky.social, Bernat, @crisp-c.bsky.social, Adrián, and everyone involved! 🙌 🧵⤵️
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peterdoohan.bsky.social @peterdoohan.bsky.social · 11/06/2026
How do brains plan actions towards goals? To get at this question we studied mice navigating complex mazes as goals changed on every trial 🧵 Work with @thomasakam.bsky.social @behrenstimb.bsky.social @kristorpjensen.bsky.social now on BioRxiv: www.biorxiv.org/content/10.6...
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Takaki Komiyama @takakikomiyama.bsky.social · 03/06/2026
Our new paper is out in Current Biology! We learn many things in parallel, and brain circuits are constantly rewiring across brain areas. It is notoriously difficult to understand which rewiring events are responsible for which type of learning. www.sciencedirect.com/science/arti...
sciencedirect.com
Local plasticity underlies the reorganization of cortical circuit dynamics during motor learning
During learning, neural circuits reorganize to encode new information and adapt behavioral responses. Ca2+/calmodulin-dependent protein kinase II (CaM…
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Drew Schreiner @schreinerdrew.bsky.social · 13/05/2026
Where, exactly, does learning happen in the brain? Out today in @nature.com, we identify a synaptic locus of birdsong learning and show that the circuit can be tuned to make birds learn faster - but at a cost. Read on👇 #neuroskyence 🧪 #prattle 💬 #bioacoustics Shareable link: rdcu.be/fiyrS
nature.com
A synaptic locus of song learning - Nature
Combining a computational framework and optogenetic and chemogenetic manipulations within and downstream of the cortico-basal ganglia circuit identifies the specific cortico-basal ganglia synapse...
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Edvard I Moser @edvardmoser.bsky.social · 11/03/2026
Is spatial navigation innate 🧠? Using #NeuroPixels we show that the #torus 🍩 underlying the #GridCell map exists already on day 10 in rats — before pups open eyes and ears and before they start upright walking. 🧵1:4 👇 www.biorxiv.org/content/10.6...
biorxiv.org
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SP Arun @sparuniisc.bsky.social · 22/04/2026
Preprint alert! We've done the first ever brain recording simultaneously from IT & PMv in two monkeys interacting socially in natural setting! Dynamic tracking of social variables in simultaneous brain recordings of socially interacting monkeys www.biorxiv.org/content/10.6...
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Tommaso Patriarchi @tpatriarchi.bsky.social · 27/03/2026
Wait… localized norepinephrine transients in the awake visual cortex?! Who would have guessed this neuromodulatory signal is that spatially precise, right where visual processing is happening. Brain state control just got a lot more local. @ruedigersarah.bsky.social www.nature.com/articles/s41...
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Marlene Cohen @marlenecohen.bsky.social · 20/03/2026
New preprint: our lab’s first Alzheimer’s paper! “Loss of neuronal population organization links pathology to behavior in a model of Alzheimer's disease” www.biorxiv.org/content/10.6... 🧪🧵1/
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David Barner @drbarner.bsky.social · 19/02/2026
Bots have made their way to Prolific experiments. Our lab has stopped online testing of adults entirely now for this reason - we want to know if what we study is real. Probably data collected 2-3 years ago are ok, but moving forward we just can't know. www.pnas.org/doi/10.1073/...
pnas.org
PNAS
Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...
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Kevin Healy @healyke.bsky.social · 24/02/2026
Our new paper is now out showing how time perception in animals is linked to their ecology. Using data from 237 species we show temporal perception is faster in species that fly and pursuit predators www.nature.com/articles/s41... 🌐
nature.com
Pace of ecology drives the tempo of visual perception across the animal kingdom
Nature Ecology & Evolution - Using phylogenetic comparative methods across 237 species from disparate phyla, the authors show that species with fast-paced ecologies have higher temporal...
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Nicole Rust @nicolecrust.bsky.social · 04/01/2026
Beautiful - recommended! Here, @sasolla.bsky.social recaps her decades-long journey from physics to neural networks (working with LeCun & Hopfield) to motor cortex, & and from industry (including Bell Labs) to academia, all driven by curiosity and awe (which flows from her voice). Inspiring!
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Marcus Ghosh @marcusghosh.bsky.social · 22/12/2025
Toy models, just in time for Christmas! Excited to share my first article for @thetransmitter.bsky.social #neuroskyence
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Alicia Chen @aliciamchen.bsky.social · 26/11/2025
Human speech is continuous, and many meaning spaces (like color) are continuous too. Yet we use discrete words like “blue” and “green” that carve these spaces into categories. In our new paper, we ask: How do people turn continuous spaces into structured, word-like systems for communication? (1/8)
academic.oup.com
Discrete and systematic communication in a continuous signal-meaning space
Abstract. Human spoken language uses a continuous stream of acoustic signals to communicate about continuous features of the world, by using discrete forms
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Colton Casto @coltoncasto.bsky.social · 26/11/2025
What does it mean to understand language? We argue that the brain’s core language system is limited, and that *deeply* understanding language requires EXPORTING info to other brain regions. w/ @neuranna.bsky.social @evfedorenko.bsky.social @nancykanwisher.bsky.social arxiv.org/abs/2511.19757 1/n🧵👇
arxiv.org
What does it mean to understand language?
Language understanding entails not just extracting the surface-level meaning of the linguistic input, but constructing rich mental models of the situation it describes. Here we propose that because pr...
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Tim Vogels @tpvogels.bsky.social · 23/11/2025
"Spiking Networks Hate It! Find Out the One Plasticity Trick They Don’t Want You to Know! Never stabilise models by hand again." - I woke up thinking we missed an opportunity with the title of this one. :/ www.science.org/doi/10.1126/... Also: It snowed in Vienna, 10cm white fluffies! Happy Sunday!
science.org
Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks
Plasticity at inhibitory synapses maintains balanced excitatory and inhibitory synaptic inputs at cortical neurons.
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Blake Richards @tyrellturing.bsky.social · 14/11/2025
This raises what I like to call the "AI test for tasks". If many people use AI to do task X, then that tells you that task X is actually just a brainless administrative exercise. Any such task should probably be eliminated, and if that's not an option, modified to make automation even easier.
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Paolo Crosetto @paolocrosetto.bsky.social · 12/11/2025
What is the most profitable industry in the world, this side of the law? Not oil, not IT, not pharma. It's *scientific publishing*. We call this the Drain of Scientific Publishing. Paper: arxiv.org/abs/2511.04820 Background: doi.org/10.1162/qss_... Thread @markhanson.fediscience.org.ap.brid.gy 👇
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Shahab Bakhtiari @shahabbakht.bsky.social · 04/10/2025
The way Sutton himself interprets the “bitter lesson” in this interview definitely caught a lot of bitter lesson enthusiasts off guard. LLMs not actually being an example of the bitter lesson was quite a nuance no one saw coming. youtu.be/21EYKqUsPfg?...
youtu.be
Richard Sutton – Father of RL thinks LLMs are a dead end
YouTube video by Dwarkesh Patel
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todd gureckis @toddgureckis.bsky.social · 26/09/2025
So far, learning traps seem robust to social learning in our cases. Surprisingly, despite many manipulations that have tried to reduce this learning trap, the most effective has been simply being a child (see @emilyliquin.bsky.social's work on traps in children) osf.io/preprints/ps...
osf.io
OSF
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Aaron Milstein @neurosutras.bsky.social · 03/10/2025
Interesting new data on BTSP mechanisms from my old Janelia colleague @hiallen72.bsky.social www.biorxiv.org/content/10.1...
biorxiv.org
Ca2+ Plateau Potentials Reflect Cross-Theta Cortico-Hippocampal Input Dynamics and Acetylcholine for Rapid Formation of Efficient Place-Cell Code
A central tenet of Systems Neuroscience lies in an understanding of memory and behavior through learning rules, but synaptic plasticity has rarely been shown to create functional single-neuron code in...
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Marlene Cohen @marlenecohen.bsky.social · 23/09/2025
New preprint! How can you remember an image you saw once, even after seeing thousands of them? We find a role for humble mid-level visual cortex in high-capacity, one-shot learning. doi.org/10.1101/2025.09.22.677855 🧵🧪1/
doi.org
Neuronal signatures of successful one-shot memory in mid-level visual cortex
High-capacity, one-shot visual recognition memory challenges theories of learning and neural coding because it requires rapid, robust, and durable representations. Most studies have focused on the hip...
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Mark Histed @markhisted.org · 22/09/2025
The New York Times piece today about US science is terrible and wrong—in many ways. I could write a whole article about this, but as one example: “To close observers, the original crisis began well before any of this…” No. I’m a close observer of science, and this is incorrect.
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Ricard Solé @ricardsole.bsky.social · 10/09/2025
Can a single cell learn? Even without a brain, some microbes show simple forms of cognition. Can this basal cognition be engineered? Check our new paper with @jordiplam.bsky.social on the minimal synthetic circuits & their cognitive limits. @drmichaellevin.bsky.social www.biorxiv.org/content/10.1...
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Iris van Rooij 💭 @irisvanrooij.bsky.social · 22/08/2025
LLRX republished the blogpost www.llrx.com/2025/08/ai-s...
llrx.com
AI slop and the destruction of knowledge – LLRX
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Ann Kennedy @antihebbiann.bsky.social · 20/08/2025
I wrote a Comment on neurotheory, and now you can read it! Some thoughts on where neurotheory has and has not taken root within the neuroscience community, how it has shaped those subfields, and where we theorists might look next for fresh adventures. www.nature.com/articles/s41...
nature.com
Theoretical neuroscience has room to grow
Nature Reviews Neuroscience - The goal of theoretical neuroscience is to uncover principles of neural computation through careful design and interpretation of mathematical models. Here, I examine...
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Dare Obasanjo @carnage4life.bsky.social · 20/08/2025
MIT’s NANDA initiative found that 95% of generative AI deployments fail after interviewing 150 execs, surveying 350 workers, and analyzing 300 projects. The real “productivity gains” seem to come from layoffs and squeezing more work from fewer people not AI.
fortune.com
MIT report: 95% of generative AI pilots at companies are failing
There’s a stark difference in success rates between companies that purchase AI tools from vendors and those that build them internally.
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Iris van Rooij 💭 @irisvanrooij.bsky.social · 12/08/2025
AI slop and the destruction of knowledge irisvanrooijcogsci.com/2025/08/12/a...
irisvanrooijcogsci.com
AI slop and the destruction of knowledge
This week I was looking for info on what cognitive scientists mean when they speak of ‘domain-general’ cognition. I was curious, because the nuances are relevant for something I am researching at t…
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Miguel Aguilera @maguilera.net · 24/07/2025
Our paper just out in Nature Communications! www.nature.com/articles/s41... We introduce curved neural networks naturally introducing high-order interactions showing: • explosive phase transitions • enhanced memory retrieval via self-annealing • increased memory capacity through geometric curvature
nature.com
Explosive neural networks via higher-order interactions in curved statistical manifolds - Nature Communications
Higher-order interactions shape complex neural dynamics but are hard to model. Here, authors use a generalization of the maximum entropy principle to introduce a family of curved neural networks, reve...
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Jason Climer @jrclimer.bsky.social · 23/07/2025
So what drives drift? We looked closely at the neurons and found that a small group of them were stable. These stable neurons were more excitable than neighboring cells, making the fate of the cells predictable.
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Alison Phipps አሊሰን @alisonphipps.bsky.social · 21/07/2025
DO EVERYTHING YOU CAN TO GET FOOD AND WATER IN TO GAZA. This is from Lemkin Institute begging..... we are all begging.
The Lemkin Institute for Genocide Prevention is
calling on every single leader in the world: DO EVERYTHING YOU CAN TO GET FOOD &
WATER INTO GAZA RIGHT AWAY. Even if it takes bypassing the reports, meetings, endless conferences, parliamentary sessions, UN sessions, and all the other regular diplomatic
channels that have led nowhere. Just do it. Genocide must not be allowed to continue while we all
watch. We must not allow mass starvation in Gaza.
We cannot wait any longer. IF YOU HAVE POWER, USE IT. HISTORY WILL DEMONSTRATE THE RECTITUDE OF
YOUR ACTIONS.
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Dan Levenstein @dlevenstein.bsky.social · 17/07/2025
Really interesting results, suggesting that long-term place field stability is not from long-lasting synaptic plasticity, but is instead from an increased *probability of plasticity induction* in subsequent days.
nature.com
Formation of an expanding memory representation in the hippocampus - Nature Neuroscience
Multiday imaging of CA1 neurons during learning reveals that the representation stabilizes as the number of readily retrievable, information-rich and stable place cells increases and suggests novel me...
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Rosanne Rademaker @rademaker.bsky.social · 02/07/2025
Who doesn't like a good model of the brain? Yet, from simple regression to neural nets, some limitations keep popping up (e.g., overfitting) @mjwolff.bsky.social & I saw some cool but puzzling data, ran a quick analysis & found one such limitation: model mimicry. Now in #naturecommunications &🧵below
rdcu.be
Model mimicry limits conclusions about neural tuning and can mistakenly imply unlikely priors
Nature Communications - Model mimicry limits conclusions about neural tuning and can mistakenly imply unlikely priors
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Hannah Payne @hannahpayne.bsky.social · 11/06/2025
My latest Aronov lab paper is now published @Nature! When a chickadee looks at a distant location, the same place cells activate as if it were actually there 👁️ The hippocampus encodes where the bird is looking, AND what it expects to see next -- enabling spatial reasoning from afar bit.ly/3HvWSum
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Kate Watson @loreandordure.com · 08/05/2025
It occurred to me last night that microwaves are kinda like LLMs. Remember when they first came out, people bought microwave cookbooks, and special vented plastic cookware, and they were going to change the way we cooked and ate forever? Now we use them for defrosting mince, and reheating cold tea.
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Jonathan A. Michaels @jonathanamichaels.bsky.social · 02/04/2025
We’re excited about this project! We present a model of motor savings without the need for context.
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Guido Meijer @guidomeijer.com · 27/03/2025
Kilosort4 detects a LOT of neurons, I recorded 15k neurons in one year 🤯 Traditionally, one would curate these detected units to see if they are well isolated single neurons. This is not feasible anymore, so today let's look at three options that are out there to automate this process! 🤖👇
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Nancy Kanwisher @nancykanwisher.bsky.social · 26/03/2025
I’m hiring a full-time lab tech for two years starting May/June. Strong coding skills required, ML a plus. Our research on the human brain uses fMRI, ANNs, intracranial recording, and behavior. A great stepping stone to grad school. Apply here: careers.peopleclick.com/careerscp/cl... ......
careers.peopleclick.com
Technical Associate I, Kanwisher Lab
MIT - Technical Associate I, Kanwisher Lab - Cambridge MA 02139
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Nature Neuroscience @natneuro.nature.com · 25/03/2025
Behavioral timescale synaptic plasticity (BTSP), not Hebbian spike-timing-dependent plasticity (STDP), explains heterogenous place field shifting in the mouse hippocampus 🧠🧪 www.nature.com/articles/s41...
nature.com
Synaptic plasticity rules driving representational shifting in the hippocampus - Nature Neuroscience
Madar et al. report that behavioral timescale synaptic plasticity (BTSP), not spike-timing-dependent plasticity, explains heterogeneous place fields shifting in the hippocampus. The probability of BTS...
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Mark Haselgrove @markhaselgrove.bsky.social · 08/03/2025
In contrast to the wide spread applause that this piece seems to be getting, I disagree with a lot of what is said here. 1/N
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Olivia Guest · Ολίβια Γκεστ @olivia.science · 01/03/2025
Tired but happy to say this is out w @andreaeyleen.bsky.social: Are Neurocognitive Representations 'Small Cakes'? philsci-archive.pitt.edu/24834/ We analyse cog neuro theories showing how vicious regress, e.g. the homunculus fallacy, is (sadly) alive and well — and importantly how to avoid it. 1/
In order to understand cognition, we often recruit analogies as building blocks of theories to aid us in this quest. One such attempt, originating in folklore and alchemy, is the homunculus: a miniature human who resides in the skull and performs cognition. Perhaps surprisingly, this appears indistinguishable from the implicit proposal of many neurocognitive theories, including that of the 'cognitive map,' which proposes a representational substrate for episodic memories and navigational capacities. In such 'small cakes' cases, neurocognitive representations are assumed to be meaningful and about the world, though it is wholly unclear who is reading them, how they are interpreted, and how they come to mean what they do. We analyze the 'small cakes' problem in neurocognitive theories (including, but not limited to, the cognitive map) and find that such an approach a) causes infinite regress in the explanatory chain, requiring a human-in-the-loop to resolve, and b) results in a computationally inert account of representation, providing neither a function nor a mechanism. We caution against a 'small cakes' theoretical practice across computational cognitive modelling, neuroscience, and artificial intelligence, wherein the scientist inserts their (or other humans') cognition into models because otherwise the models neither perform as advertised, nor mean what they are purported to, without said 'cake insertion.' We argue that the solution is to tease apart explanandum and explanans for a given scientific investigation, with an eye towards avoiding van Rooij's (formal) or Ryle's (informal) infinite regresses.

Figure 1 in https://philsci-archive.pitt.edu/24834/Box 1 in https://philsci-archive.pitt.edu/24834/Box 2 in https://philsci-archive.pitt.edu/24834/
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Mushtaq Bilal, PhD @mushtaqbilalphd.bsky.social · 07/02/2025
Meta illegaly downloaded 80+ terabytes of books from LibGen, Anna's Archive, and Z-library to train their AI models. In 2010, Aaron Swartz downloaded only 70 GBs of articles from JSTOR (0.0875% of Meta). Faced $1 million in fine and 35 years in jail. Took his own life in 2013.
“Torrenting from a corporate laptop doesn’t feel right”: Meta emails unsealedA photo of Aaron Swartz (1986-2013) when he was 19.
Last month, Meta admitted to torrenting a controversial large dataset known as LibGen, which includes tens of millions of pirated books. But details around the torrenting were murky until yesterday, when Meta's unredacted emails were made public for the first time. The new evidence showed that Meta torrented "at least 81.7 terabytes of data across multiple shadow libraries through the site Anna’s Archive, including at least 35.7 terabytes of data from Z-Library and LibGen," the authors' court filing said. And "Meta also previously torrented 80.6 terabytes of data from LibGen."
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