Victoria Bosch
@initself.bsky.social
neuromantic - ML and cognitive computational neuroscience - PhD student at Kietzmann Lab, Osnabrück University.
⛓️ https://init-self.com
⛓️ https://init-self.com
Pinned
Victoria Bosch
@initself.bsky.social
· Nov 3
Introducing CorText: a framework that fuses brain data directly into a large language model, allowing for interactive neural readout using natural language.
tl;dr: you can now chat with a brain scan 🧠💬
1/n
tl;dr: you can now chat with a brain scan 🧠💬
1/n
Reposted by Victoria Bosch
What you see right now is not a livestream, but is delayed & edited by your brain 🧠.
The brain uses a short time buffer to rewrite what you thought you saw using info that comes in later (postdiction). We study how (7T fMRI, retinotopy).
Read our preprint: www.biorxiv.org/content/10.6... 👀 (1/N)
The brain uses a short time buffer to rewrite what you thought you saw using info that comes in later (postdiction). We study how (7T fMRI, retinotopy).
Read our preprint: www.biorxiv.org/content/10.6... 👀 (1/N)
www.biorxiv.org
September 11, 2026 at 11:33 AM
What you see right now is not a livestream, but is delayed & edited by your brain 🧠.
The brain uses a short time buffer to rewrite what you thought you saw using info that comes in later (postdiction). We study how (7T fMRI, retinotopy).
Read our preprint: www.biorxiv.org/content/10.6... 👀 (1/N)
The brain uses a short time buffer to rewrite what you thought you saw using info that comes in later (postdiction). We study how (7T fMRI, retinotopy).
Read our preprint: www.biorxiv.org/content/10.6... 👀 (1/N)
Reposted by Victoria Bosch
New paper, co-authored with Justin Wood, in @cp-trendscognsci.bsky.social:
The Nativist-Empiricist Debate Is Broken
We argue that radical nativism and radical empiricism are compatible and, in some cases, both plausibly true. So something is wrong.
🧵
Author share link here, valid til Oct 31:
The Nativist-Empiricist Debate Is Broken
We argue that radical nativism and radical empiricism are compatible and, in some cases, both plausibly true. So something is wrong.
🧵
Author share link here, valid til Oct 31:
September 11, 2026 at 4:25 PM
New paper, co-authored with Justin Wood, in @cp-trendscognsci.bsky.social:
The Nativist-Empiricist Debate Is Broken
We argue that radical nativism and radical empiricism are compatible and, in some cases, both plausibly true. So something is wrong.
🧵
Author share link here, valid til Oct 31:
The Nativist-Empiricist Debate Is Broken
We argue that radical nativism and radical empiricism are compatible and, in some cases, both plausibly true. So something is wrong.
🧵
Author share link here, valid til Oct 31:
Reposted by Victoria Bosch
Our group discovered that reasoning models produce fractals when asked to solve hard problems. We can use nonlinear dynamics to probe the thinking processes of recurrent depth models on Sudoku, mathematics, and even ARC-AGI (1/N)
arxiv.org/abs/2609.04963
arxiv.org/abs/2609.04963
September 8, 2026 at 4:14 PM
Our group discovered that reasoning models produce fractals when asked to solve hard problems. We can use nonlinear dynamics to probe the thinking processes of recurrent depth models on Sudoku, mathematics, and even ARC-AGI (1/N)
arxiv.org/abs/2609.04963
arxiv.org/abs/2609.04963
Reposted by Victoria Bosch
How can we design experiments that make computational models disagree? One section of our new @natrevneuro.nature.com Review with @kriegeskorte.bsky.social and @heikoschuett.bsky.social examines studies that used stimulus sets designed to elicit distinct predictions from competing models. 1/16
August 28, 2026 at 7:10 PM
How can we design experiments that make computational models disagree? One section of our new @natrevneuro.nature.com Review with @kriegeskorte.bsky.social and @heikoschuett.bsky.social examines studies that used stimulus sets designed to elicit distinct predictions from competing models. 1/16
Reposted by Victoria Bosch
The journal version is out! www.cell.com/trends-open/...
AI is turning machine consciousness into a societal issue.
Biological Naturalism (BN), the idea that only biological systems can be conscious, is gaining traction.
We argue: either BN is untestable, or it is compatible with functionalism.
AI is turning machine consciousness into a societal issue.
Biological Naturalism (BN), the idea that only biological systems can be conscious, is gaining traction.
We argue: either BN is untestable, or it is compatible with functionalism.
August 21, 2026 at 9:09 AM
The journal version is out! www.cell.com/trends-open/...
AI is turning machine consciousness into a societal issue.
Biological Naturalism (BN), the idea that only biological systems can be conscious, is gaining traction.
We argue: either BN is untestable, or it is compatible with functionalism.
AI is turning machine consciousness into a societal issue.
Biological Naturalism (BN), the idea that only biological systems can be conscious, is gaining traction.
We argue: either BN is untestable, or it is compatible with functionalism.
Are brains and artificial neural networks converging onto universal representations?
There is a seductive idea making the rounds in NeuroAI / machine learning: train systems well enough, and they all converge on the same representation of reality (i.e. a unique world model).
We have thoughts™
1/n
There is a seductive idea making the rounds in NeuroAI / machine learning: train systems well enough, and they all converge on the same representation of reality (i.e. a unique world model).
We have thoughts™
1/n
The Umwelt Representation Hypothesis: rethinking Universality
Recent studies reveal striking representational alignment between artificial neural
networks (ANNs) and biological brains, leading to proposals that all sufficiently
capable systems converge on univer...
www.cell.com
August 28, 2026 at 2:59 PM
Are brains and artificial neural networks converging onto universal representations?
There is a seductive idea making the rounds in NeuroAI / machine learning: train systems well enough, and they all converge on the same representation of reality (i.e. a unique world model).
We have thoughts™
1/n
There is a seductive idea making the rounds in NeuroAI / machine learning: train systems well enough, and they all converge on the same representation of reality (i.e. a unique world model).
We have thoughts™
1/n
Reposted by Victoria Bosch
New preprint www.biorxiv.org/content/10.6...: brain alignment in DNNs is almost fully complete at 3% of training. Features involved in classification are largely independent of those that predict the brain. With @niklasmuller.bsky.social , @irisgroen.bsky.social. @marcelvangerven.bsky.social
August 27, 2026 at 2:14 PM
New preprint www.biorxiv.org/content/10.6...: brain alignment in DNNs is almost fully complete at 3% of training. Features involved in classification are largely independent of those that predict the brain. With @niklasmuller.bsky.social , @irisgroen.bsky.social. @marcelvangerven.bsky.social
Reposted by Victoria Bosch
Excited to share our preprint! w/ @martinhebart.bsky.social
To understand how primates visually process objects in the world, we rely on both research in human and macaque IT. But what representations of object space are actually shared between them?
biorxiv.org/content/10.6...
Quick thread 🧵
To understand how primates visually process objects in the world, we rely on both research in human and macaque IT. But what representations of object space are actually shared between them?
biorxiv.org/content/10.6...
Quick thread 🧵
Shared and Distinct High-Dimensional Object Spaces in Human and Macaque Inferotemporal Cortex
Human and macaque studies of inferotemporal cortex (IT) have shaped our understanding of object vision, yet the extent of their representational alignment and the precise nature of this correspondence...
biorxiv.org
August 12, 2026 at 1:55 PM
Excited to share our preprint! w/ @martinhebart.bsky.social
To understand how primates visually process objects in the world, we rely on both research in human and macaque IT. But what representations of object space are actually shared between them?
biorxiv.org/content/10.6...
Quick thread 🧵
To understand how primates visually process objects in the world, we rely on both research in human and macaque IT. But what representations of object space are actually shared between them?
biorxiv.org/content/10.6...
Quick thread 🧵
Obligatory pictures of pittoresque Tübingen - had a lovely time here, presenting our work on CorText at the ICCSSS summer school. @iiccsss.bsky.social Thank you for the invitation!
August 20, 2026 at 11:09 AM
Obligatory pictures of pittoresque Tübingen - had a lovely time here, presenting our work on CorText at the ICCSSS summer school. @iiccsss.bsky.social Thank you for the invitation!
Reposted by Victoria Bosch
Excited to share our new paper: "Probing the content of semantic representations in body-selective regions"
We propose a framework based on object co-occurrence to interpret semantic representations of natural scenes predicted by LLM embeddings.
doi.org/10.1162/IMAG...
We propose a framework based on object co-occurrence to interpret semantic representations of natural scenes predicted by LLM embeddings.
doi.org/10.1162/IMAG...
Probing the content of semantic representations in body-selective regions
Abstract. Recent advances in neural networks trained on natural language have revealed that category-selective regions encode complex semantics and contextual information of natural scenes in addition...
doi.org
August 11, 2026 at 3:02 PM
Excited to share our new paper: "Probing the content of semantic representations in body-selective regions"
We propose a framework based on object co-occurrence to interpret semantic representations of natural scenes predicted by LLM embeddings.
doi.org/10.1162/IMAG...
We propose a framework based on object co-occurrence to interpret semantic representations of natural scenes predicted by LLM embeddings.
doi.org/10.1162/IMAG...
Reposted by Victoria Bosch
Excited to share that I'll be starting as a junior professor and Emmy Noether awardee at the University of Göttingen this October! 🥳
🚀 I'll be hiring #phd students and #postdoc across #machinelearning, #neuroscience and #cogsci:
modirlab.github.io/open-positio...
Please spread the word! 🙏
🚀 I'll be hiring #phd students and #postdoc across #machinelearning, #neuroscience and #cogsci:
modirlab.github.io/open-positio...
Please spread the word! 🙏
August 15, 2026 at 12:30 PM
Excited to share that I'll be starting as a junior professor and Emmy Noether awardee at the University of Göttingen this October! 🥳
🚀 I'll be hiring #phd students and #postdoc across #machinelearning, #neuroscience and #cogsci:
modirlab.github.io/open-positio...
Please spread the word! 🙏
🚀 I'll be hiring #phd students and #postdoc across #machinelearning, #neuroscience and #cogsci:
modirlab.github.io/open-positio...
Please spread the word! 🙏
Reposted by Victoria Bosch
All session recordings from #CCN2026 in New York City are now available on YouTube.
Thank you again to all speakers, attendees, and sponsors for making this exciting event possible.
Thank you again to all speakers, attendees, and sponsors for making this exciting event possible.
CCN 2026 - YouTube
Videos from CCN 2026, held in New York City, USA, August 3-6 2026 For full details of the 2026 program, visit https://2026.ccneuro.org/schedule-of-events/
www.youtube.com
August 13, 2026 at 2:14 PM
All session recordings from #CCN2026 in New York City are now available on YouTube.
Thank you again to all speakers, attendees, and sponsors for making this exciting event possible.
Thank you again to all speakers, attendees, and sponsors for making this exciting event possible.
Reposted by Victoria Bosch
Online Now: The Umwelt Representation Hypothesis: rethinking Universality
The Umwelt Representation Hypothesis: rethinking Universality
Recent studies reveal striking representational alignment between artificial neural networks (ANNs) and biological brains, leading to proposals that all sufficiently capable systems converge on universal representations of reality. We argue that this claim of Universality is premature. We introduce the Umwelt Representation Hypothesis, which proposes that alignment arises not from convergence toward a single global optimum but from overlap in the ecological constraints under which systems develop. We review empirical evidence showing that representational differences between species, individuals, and ANNs are systematic and adaptive, which is difficult to reconcile with Universality. Finally, we reframe ANN model comparison as a method for mapping clusters of alignment in the ecological constraint space rather than as a search for a single optimal world model.
dlvr.it
August 8, 2026 at 12:40 PM
Online Now: The Umwelt Representation Hypothesis: rethinking Universality
Reposted by Victoria Bosch
Excited to share our review in @cp-neuron.bsky.social with @lauriebayet.bsky.social and @mickbonner.bsky.social!
We describe how implementing principles from child development can advance the mechanistic plausibility and capacities of AI models
We packed A LOT into this review, here's a quick 🧵
We describe how implementing principles from child development can advance the mechanistic plausibility and capacities of AI models
We packed A LOT into this review, here's a quick 🧵
July 22, 2026 at 12:52 PM
Excited to share our review in @cp-neuron.bsky.social with @lauriebayet.bsky.social and @mickbonner.bsky.social!
We describe how implementing principles from child development can advance the mechanistic plausibility and capacities of AI models
We packed A LOT into this review, here's a quick 🧵
We describe how implementing principles from child development can advance the mechanistic plausibility and capacities of AI models
We packed A LOT into this review, here's a quick 🧵
Reposted by Victoria Bosch
1/5 Over a decade of comparing deep neural networks to the human brain—but what have we actually learned? Our new @cp-trendscognsci.bsky.social Feature Review synthesizes a decade of brain–DNN comparisons, asking what they reveal about brain function across vision and language.
July 21, 2026 at 5:58 PM
1/5 Over a decade of comparing deep neural networks to the human brain—but what have we actually learned? Our new @cp-trendscognsci.bsky.social Feature Review synthesizes a decade of brain–DNN comparisons, asking what they reveal about brain function across vision and language.
Reposted by Victoria Bosch
I am *thrilled* to share this review in @currentbiology.bsky.social out today, by yours truly, @myoo.bsky.social, @michalk.bsky.social, Taro Toyoizumi, @tyrellturing.bsky.social, @taylorwwebb.bsky.social, & @hakwan.bsky.social
www.sciencedirect.com/science/arti...
🧵👇
www.sciencedirect.com/science/arti...
🧵👇
Looking to the brain to improve energy efficiency of AI
Modern artificial intelligence (AI) systems have achieved remarkable capabilities, but at an extraordinary energy cost. Training and running large-sca…
www.sciencedirect.com
July 20, 2026 at 4:22 PM
I am *thrilled* to share this review in @currentbiology.bsky.social out today, by yours truly, @myoo.bsky.social, @michalk.bsky.social, Taro Toyoizumi, @tyrellturing.bsky.social, @taylorwwebb.bsky.social, & @hakwan.bsky.social
www.sciencedirect.com/science/arti...
🧵👇
www.sciencedirect.com/science/arti...
🧵👇
Reposted by Victoria Bosch
Alpha rhythm determines speech perception rate? And speeding it up makes unintelligibly fast speech comprehensible? This is nuts!
www.pnas.org/doi/abs/10.1...
www.pnas.org/doi/abs/10.1...
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...
www.pnas.org
July 20, 2026 at 9:05 PM
Alpha rhythm determines speech perception rate? And speeding it up makes unintelligibly fast speech comprehensible? This is nuts!
www.pnas.org/doi/abs/10.1...
www.pnas.org/doi/abs/10.1...
Reposted by Victoria Bosch
Out today on @nature.com! Connecting neural specialization, population geometry, and their functional implications across the cortical hierarchy. So grateful for this beautiful and fun collaboration with @shuqiw.bsky.social, S Muscinelli, L Paninski, and @stefanofusi.bsky.social!
Rarely categorical, highly separable representations along the cortical hierarchy - Nature
Cortical circuits prioritize diversity over categorical structure, supporting a computational regime geared towards high-dimensional, highly separable neural representations.
www.nature.com
July 15, 2026 at 4:47 PM
Out today on @nature.com! Connecting neural specialization, population geometry, and their functional implications across the cortical hierarchy. So grateful for this beautiful and fun collaboration with @shuqiw.bsky.social, S Muscinelli, L Paninski, and @stefanofusi.bsky.social!
Excited to share that our paper has been accepted for a talk at #CogSci2026:
Path Integration and Object-Location Binding Emerge in an Action-Conditioned Predictive Sequence Network
Linda Ariel Ventura, Victoria Bosch, Tim C. Kietzmann, and Sushrut Thorat.
Preprint: arxiv.org/abs/2602.03490.
⛓️
Path Integration and Object-Location Binding Emerge in an Action-Conditioned Predictive Sequence Network
Linda Ariel Ventura, Victoria Bosch, Tim C. Kietzmann, and Sushrut Thorat.
Preprint: arxiv.org/abs/2602.03490.
⛓️
Path Integration and Object-Location Binding Emerge in an Action-Conditioned Predictive Sequence Network
Adaptive cognition requires structured internal models of objects and their relations. Predictive neural networks are often proposed to learn such world models, but how these are instantiated and how ...
arxiv.org
July 15, 2026 at 1:05 PM
Excited to share that our paper has been accepted for a talk at #CogSci2026:
Path Integration and Object-Location Binding Emerge in an Action-Conditioned Predictive Sequence Network
Linda Ariel Ventura, Victoria Bosch, Tim C. Kietzmann, and Sushrut Thorat.
Preprint: arxiv.org/abs/2602.03490.
⛓️
Path Integration and Object-Location Binding Emerge in an Action-Conditioned Predictive Sequence Network
Linda Ariel Ventura, Victoria Bosch, Tim C. Kietzmann, and Sushrut Thorat.
Preprint: arxiv.org/abs/2602.03490.
⛓️
Reposted by Victoria Bosch
🎉 This is finally out on @natcomms.nature.com @natureportfolio.nature.com!
Ever wondered what happens to your #brain when you become an expert at something? 🧠
If the answer is “yes” (+bonus points if you like #chess), check out our latest #fMRI work below!
www.nature.com/articles/s41...
Ever wondered what happens to your #brain when you become an expert at something? 🧠
If the answer is “yes” (+bonus points if you like #chess), check out our latest #fMRI work below!
www.nature.com/articles/s41...
July 7, 2026 at 9:01 PM
🎉 This is finally out on @natcomms.nature.com @natureportfolio.nature.com!
Ever wondered what happens to your #brain when you become an expert at something? 🧠
If the answer is “yes” (+bonus points if you like #chess), check out our latest #fMRI work below!
www.nature.com/articles/s41...
Ever wondered what happens to your #brain when you become an expert at something? 🧠
If the answer is “yes” (+bonus points if you like #chess), check out our latest #fMRI work below!
www.nature.com/articles/s41...
Reposted by Victoria Bosch
#CCN2026 will feature three GAC debates:
Does NeuroAI adopt suitable methods & frameworks to understand mind & brain?
Do world models emerge in prediction networks?
Should neural population activity explain representations or transformations?
The review period is now open.
🖥️ 2026.ccneuro.org/gac
Does NeuroAI adopt suitable methods & frameworks to understand mind & brain?
Do world models emerge in prediction networks?
Should neural population activity explain representations or transformations?
The review period is now open.
🖥️ 2026.ccneuro.org/gac
June 5, 2026 at 8:55 AM
#CCN2026 will feature three GAC debates:
Does NeuroAI adopt suitable methods & frameworks to understand mind & brain?
Do world models emerge in prediction networks?
Should neural population activity explain representations or transformations?
The review period is now open.
🖥️ 2026.ccneuro.org/gac
Does NeuroAI adopt suitable methods & frameworks to understand mind & brain?
Do world models emerge in prediction networks?
Should neural population activity explain representations or transformations?
The review period is now open.
🖥️ 2026.ccneuro.org/gac
Reposted by Victoria Bosch
1/ 🚨 New opinion piece: "Can we automatize scientific discovery in the cognitive sciences?"
We lay out a vision for a fully automated, in-silico science of the mind, where modern AI systems run every stage of the scientific discovery cycle in cognitive science 🧵
#AutomatedDiscovery #AI4Science
We lay out a vision for a fully automated, in-silico science of the mind, where modern AI systems run every stage of the scientific discovery cycle in cognitive science 🧵
#AutomatedDiscovery #AI4Science
June 22, 2026 at 12:03 AM
1/ 🚨 New opinion piece: "Can we automatize scientific discovery in the cognitive sciences?"
We lay out a vision for a fully automated, in-silico science of the mind, where modern AI systems run every stage of the scientific discovery cycle in cognitive science 🧵
#AutomatedDiscovery #AI4Science
We lay out a vision for a fully automated, in-silico science of the mind, where modern AI systems run every stage of the scientific discovery cycle in cognitive science 🧵
#AutomatedDiscovery #AI4Science
Reposted by Victoria Bosch
Our latest story is finally in preprint! 🧠✨
How does the brain solve the (hierarchical) credit assignment problem efficiently? Cell-type-specific cortical feedback holds the key, closely approximating backprop.
Paper: doi.org/10.64898/202...
How does the brain solve the (hierarchical) credit assignment problem efficiently? Cell-type-specific cortical feedback holds the key, closely approximating backprop.
Paper: doi.org/10.64898/202...
Cell-type-specific cortical feedback coordinates hierarchical credit assignment
Learning is thought to arise from synaptic modifications embedded in brain-wide circuits, yet how such circuits coordinate plasticity to support complex behaviour is not known. Inspired by deep learni...
doi.org
June 18, 2026 at 11:01 AM
Our latest story is finally in preprint! 🧠✨
How does the brain solve the (hierarchical) credit assignment problem efficiently? Cell-type-specific cortical feedback holds the key, closely approximating backprop.
Paper: doi.org/10.64898/202...
How does the brain solve the (hierarchical) credit assignment problem efficiently? Cell-type-specific cortical feedback holds the key, closely approximating backprop.
Paper: doi.org/10.64898/202...
Reposted by Victoria Bosch
Now published in open access! Your one-stop shop for the philosophy of language models. It's the spiritual descendant of our two-part preprint from 2024, fully updated. This should be particularly useful for anyone looking for an entry point into this rapidly growing field.
The Philosophy of Language Models
The success of large language models (LLMs) across many domains of AI research has generated intense debate. Some attribute their impressive performance on complex tasks to human-like linguistic and ...
compass.onlinelibrary.wiley.com
June 11, 2026 at 5:15 PM
Now published in open access! Your one-stop shop for the philosophy of language models. It's the spiritual descendant of our two-part preprint from 2024, fully updated. This should be particularly useful for anyone looking for an entry point into this rapidly growing field.
Reposted by Victoria Bosch
NEW PAPER. Why do larger networks train better?
"Because they contain more candidate *sub*networks that can learn the task" → lottery tickets
This popular explanation uses an appealing but misleading metaphor🧵
We propose an intuitive alternative grounded in theory: escape dimensions
"Because they contain more candidate *sub*networks that can learn the task" → lottery tickets
This popular explanation uses an appealing but misleading metaphor🧵
We propose an intuitive alternative grounded in theory: escape dimensions
June 10, 2026 at 9:40 AM
NEW PAPER. Why do larger networks train better?
"Because they contain more candidate *sub*networks that can learn the task" → lottery tickets
This popular explanation uses an appealing but misleading metaphor🧵
We propose an intuitive alternative grounded in theory: escape dimensions
"Because they contain more candidate *sub*networks that can learn the task" → lottery tickets
This popular explanation uses an appealing but misleading metaphor🧵
We propose an intuitive alternative grounded in theory: escape dimensions