Tootfinder

Researchers detail Centaur, a modified version of Llama trained on 10M responses from 160 psychological experiments, in an attempt to mimic human cognition (Carl Zimmer/New York Times)
https://www.nytimes.com/2025/07/02/science

Scientist Use A.I. To Mimic the Mind, Warts and All
To better understand human cognition, scientists trained a large language model on 10 million psychology experiment questions. It now answers questions much like we do.

A "Wenlu" Brain System for Multimodal Cognition and Embodied Decision-Making: A Secure New Architecture for Deep Integration of Foundation Models and Domain Knowledge
Liang Geng
https://arxiv.org/abs/2506.00570

A "Wenlu" Brain System for Multimodal Cognition and Embodied Decision-Making: A Secure New Architecture for Deep Integration of Foundation Models and Domain Knowledge
With the rapid penetration of artificial intelligence across industries and scenarios, a key challenge in building the next-generation intelligent core lies in effectively integrating the language understanding capabilities of foundation models with domain-specific knowledge bases in complex real-world applications. This paper proposes a multimodal cognition and embodied decision-making brain system, ``Wenlu", designed to enable secure fusion of private knowledge and public models, unified proc…

Partially-shared Imaging Regression on Integrating Heterogeneous Brain-Cognition Associations across Alzheimer's Diagnoses
Yang Sui, Qi Xu, Ting Li, Yang Bai, Annie Qu
https://arxiv.org/abs/2505.24259

Partially-shared Imaging Regression on Integrating Heterogeneous Brain-Cognition Associations across Alzheimer's Diagnoses
This paper is motivated by the heterogeneous associations among demographic covariates, imaging data, and cognitive performances across different diagnostic groups within the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We propose a novel PArtially-shared Imaging Regression (PAIR) model with smooth spatial component integration to capture heterogeneous imaging coefficients across multiple data sources. The model assumes that each imaging coefficient can be represented as a weighted…

Constructing a bridge between functioning of oscillatory neuronal networks and quantum-like cognition along with quantum-inspired computation and AI
Andrei Khrennikov, Atsushi Iriki, Irina Basieva
https://arxiv.org/abs/2506.00040

Constructing a bridge between functioning of oscillatory neuronal networks and quantum-like cognition along with quantum-inspired computation and AI
Quantum-like (QL) modeling, one of the outcomes of the quantum information revolution, extends quantum theory methods beyond physics to decision theory and cognitive psychology. While effective in explaining paradoxes in decision making and effects in cognitive psychology, such as conjunction, disjunction, order, and response replicability, it lacks a direct link to neural information processing in the brain. This study bridges neurophysiology, neuropsychology, and cognitive psychology, explori…

Contrasting Cognitive Styles in Vision-Language Models: Holistic Attention in Japanese Versus Analytical Focus in English
Ahmed Sabir, Azinovi\v{c} Gasper, Mengsay Loem, Rajesh Sharma
https://arxiv.org/abs/2507.00700

Contrasting Cognitive Styles in Vision-Language Models: Holistic Attention in Japanese Versus Analytical Focus in English
Cross-cultural research in perception and cognition has shown that individuals from different cultural backgrounds process visual information in distinct ways. East Asians, for example, tend to adopt a holistic perspective, attending to contextual relationships, whereas Westerners often employ an analytical approach, focusing on individual objects and their attributes. In this study, we investigate whether Vision-Language Models (VLMs) trained predominantly on different languages, specifically …

This https://arxiv.org/abs/2505.21581 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

CogAD: Cognitive-Hierarchy Guided End-to-End Autonomous Driving
While end-to-end autonomous driving has advanced significantly, prevailing methods remain fundamentally misaligned with human cognitive principles in both perception and planning. In this paper, we propose CogAD, a novel end-to-end autonomous driving model that emulates the hierarchical cognition mechanisms of human drivers. CogAD implements dual hierarchical mechanisms: global-to-local context processing for human-like perception and intent-conditioned multi-mode trajectory generation for cogn…

Invisible Architectures of Thought: Toward a New Science of AI as Cognitive Infrastructure
Giuseppe Riva
https://arxiv.org/abs/2507.22893 https://arxiv.org…

Invisible Architectures of Thought: Toward a New Science of AI as Cognitive Infrastructure
Contemporary human-AI interaction research overlooks how AI systems fundamentally reshape human cognition pre-consciously, a critical blind spot for understanding distributed cognition. This paper introduces "Cognitive Infrastructure Studies" (CIS) as a new interdisciplinary domain to reconceptualize AI as "cognitive infrastructures": foundational, often invisible systems conditioning what is knowable and actionable in digital societies. These semantic infrastructures transport meaning, operate…

There’ve been articles all over lately, based on a single small (n=55) study that purports to show adverse effects of cannabis use by the elderly. Here’s some evidence to the contrary. A series of studies show improved working memory function with cannabis use for those over 65 years of age. Heading on down to the dispensary as soon as I post this toot. It’s science, friends.

The Benefits of Daily Cannabis for the Middle-Aged Brain
Even daily use of low-level cannabis does not have a negative impact on cognition in older adults, recent research finds.

Using LLMs to Advance the Cognitive Science of Collectives
Ilia Sucholutsky, Katherine M. Collins, Nori Jacoby, Bill D. Thompson, Robert D. Hawkins
https://arxiv.org/abs/2506.00052

Using LLMs to Advance the Cognitive Science of Collectives
LLMs are already transforming the study of individual cognition, but their application to studying collective cognition has been underexplored. We lay out how LLMs may be able to address the complexity that has hindered the study of collectives and raise possible risks that warrant new methods.

This https://arxiv.org/abs/2406.13948 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

CityGPT: Empowering Urban Spatial Cognition of Large Language Models
Large language models(LLMs), with their powerful language generation and reasoning capabilities, have already achieved notable success in many domains, e.g., math and code generation. However, they often fall short when tackling real-life geospatial tasks within urban environments. This limitation stems from a lack of physical world knowledge and relevant data during training. To address this gap, we propose \textit{CityGPT}, a systematic framework designed to enhance LLMs' understanding of urb…

A Quantum-Inspired Conceptual Model of Collective Subjective Evaluation via Bloch Sphere Dynamics and Like-Polarization
Bumned Soodchomshom
https://arxiv.org/abs/2506.01847

A Quantum-Inspired Conceptual Model of Collective Subjective Evaluation via Bloch Sphere Dynamics and Like-Polarization
We propose a conceptual quantum-inspired model to describe subjective evaluation processes such as taste testing or consumer preference scoring-through the continuous time evolution of cognitive states represented on the Bloch sphere. Unlike conventional quantum cognition models that rely on projective measurements and state collapse, our framework treats evaluation as a weak or generalized measurement, preserving quantum coherence during the act of judgment. The mental state of preference is m…

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models
Xiaoxiao Long, Qingrui Zhao, Kaiwen Zhang, Zihao Zhang, Dingrui Wang, Yumeng Liu, Zhengjie Shu, Yi Lu, Shouzheng Wang, Xinzhe Wei, Wei Li, Wei Yin, Yao Yao, Jia Pan, Qiu Shen, Ruigang Yang, Xun Cao, Qionghai Dai
https://arxiv.org/abs/2507.00917

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models
The pursuit of artificial general intelligence (AGI) has placed embodied intelligence at the forefront of robotics research. Embodied intelligence focuses on agents capable of perceiving, reasoning, and acting within the physical world. Achieving robust embodied intelligence requires not only advanced perception and control, but also the ability to ground abstract cognition in real-world interactions. Two foundational technologies, physical simulators and world models, have emerged as critical …

Sources: Cognition, which makes the coding assistant Devin, is in talks to raise $300M at a $10B valuation; it was reportedly valued at $4B in March (Richard Nieva/Forbes)
https://www.forbes.com/sites/richardnieva/

AI Coding Startup Cognition In Talks To Raise At $10 Billion Valuation
The deal, backed by Founders Fund and Khosla Ventures, comes as the startup announced it is buying up the remains of rival Windsurf.

Sleep Brain and Cardiac Activity Predict Cognitive Flexibility and Conceptual Reasoning Using Deep Learning
Boshra Khajehpiri, Eric Granger, Massimiliano de Zambotti, Fiona C. Baker, Mohamad Forouzanfar
https://arxiv.org/abs/2506.00279

Sleep Brain and Cardiac Activity Predict Cognitive Flexibility and Conceptual Reasoning Using Deep Learning
Despite extensive research on the relationship between sleep and cognition, the connection between sleep microstructure and human performance across specific cognitive domains remains underexplored. This study investigates whether deep learning models can predict executive functions, particularly cognitive adaptability and conceptual reasoning from physiological processes during a night's sleep. To address this, we introduce CogPSGFormer, a multi-scale convolutional-transformer model designed t…

TRIBE: TRImodal Brain Encoder for whole-brain fMRI response prediction
St\'ephane d'Ascoli, J\'er\'emy Rapin, Yohann Benchetrit, Hubert Banville, Jean-R\'emi King
https://arxiv.org/abs/2507.22229

TRIBE: TRImodal Brain Encoder for whole-brain fMRI response prediction
Historically, neuroscience has progressed by fragmenting into specialized domains, each focusing on isolated modalities, tasks, or brain regions. While fruitful, this approach hinders the development of a unified model of cognition. Here, we introduce TRIBE, the first deep neural network trained to predict brain responses to stimuli across multiple modalities, cortical areas and individuals. By combining the pretrained representations of text, audio and video foundational models and handling th…

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Storing overlapping associative memories on latent manifolds in low-rank spiking networks
William F. Podlaski, Christian K. Machens

Cash and Cognition: The Impact of Transfer Timing on Standardized Test Performance and Human Capital
Axel Eizmendi Larrinaga, Germ\'an Reyes
https://arxiv.org/abs/2507.21393

Cash and Cognition: The Impact of Transfer Timing on Standardized Test Performance and Human Capital
This paper shows that the timing of monetary transfers to low-income families affects students' cognitive performance on high-stakes standardized tests. We combine administrative records from the world's largest conditional cash transfer program with college admission exam results of 185,000 high school students from beneficiary families. Exploiting random variation in payment dates, we find that receiving the transfer in the days preceding the exam increases test scores by 0.01 standard deviat…

Position: Olfaction Standardization is Essential for the Advancement of Embodied Artificial Intelligence
Kordel K. France, Rohith Peddi, Nik Dennler, Ovidiu Daescu
https://arxiv.org/abs/2506.00398

Position: Olfaction Standardization is Essential for the Advancement of Embodied Artificial Intelligence
Despite extraordinary progress in artificial intelligence (AI), modern systems remain incomplete representations of human cognition. Vision, audition, and language have received disproportionate attention due to well-defined benchmarks, standardized datasets, and consensus-driven scientific foundations. In contrast, olfaction - a high-bandwidth, evolutionarily critical sense - has been largely overlooked. This omission presents a foundational gap in the construction of truly embodied and ethica…

The death of the student essay - and the future of cognition https://www.forkingpaths.co/p/the-death-of-the-student-essayand "Next year, my courses will be assessed with in-person exams";

The Death of the Student Essay—and the Future of Cognition
One professor's reflections on the end of an era, as AI tools such as ChatGPT have murdered the student essay (RIP). Here's why that threatens the future of human cognition—and how to save ourselves.

CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding
Yuchen Zhou, Jiamin Wu, Zichen Ren, Zhouheng Yao, Weiheng Lu, Kunyu Peng, Qihao Zheng, Chunfeng Song, Wanli Ouyang, Chao Gou
https://arxiv.org/abs/2506.23075

CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding
Understanding and decoding brain activity from electroencephalography (EEG) signals is a fundamental challenge in neuroscience and AI, with applications in cognition, emotion recognition, diagnosis, and brain-computer interfaces. While recent EEG foundation models advance generalized decoding via unified architectures and large-scale pretraining, they adopt a scale-agnostic dense modeling paradigm inherited from NLP and vision. This design neglects a core property of neural activity: cross-scal…

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Strong, but not weak, noise correlations are beneficial for population coding
Gabriel Mahuas, Thomas Buffet, Olivier Marre, Ulisse Ferrari, Thierry Mora

Cognition acquires Windsurf, saying Windsurf employees will have vesting cliffs waived and receive fully accelerated vesting for their work to date (Mike Isaac/New York Times)
https://www.nytimes.com/2025/07/14/technology/cognition-ai-windsurf.html

Cognition AI Buys Windsurf as A.I. Frenzy Escalates
The deal follows Google’s $2.4 billion investment in Windsurf, an A.I. start-up, as companies race to gain technological talent and provide A.I. tools.

"This isn’t to say that AI is uniformly bad—it’s clearly not—but that we must not fall into the trap of mistaking the outputs of writing (…) from the value of the cognitive process of writing (…).
It would be a catastrophically unwise decision for humanity to abandon a key step in training young brains simply because they can now clack a few keys and produce something that sounds intelligent even as they never become intelligent."

The Death of the Student Essay—and the Future of Cognition
One professor's reflections on the end of an era, as AI tools such as ChatGPT have murdered the student essay (RIP). Here's why that threatens the future of human cognition—and how to save ourselves.

Distributed AI Agents for Cognitive Underwater Robot Autonomy
Markus Buchholz, Ignacio Carlucho, Michele Grimaldi, Yvan R. Petillot
https://arxiv.org/abs/2507.23735 https://

Distributed AI Agents for Cognitive Underwater Robot Autonomy
Achieving robust cognitive autonomy in robots navigating complex, unpredictable environments remains a fundamental challenge in robotics. This paper presents Underwater Robot Self-Organizing Autonomy (UROSA), a groundbreaking architecture leveraging distributed Large Language Model AI agents integrated within the Robot Operating System 2 (ROS 2) framework to enable advanced cognitive capabilities in Autonomous Underwater Vehicles. UROSA decentralises cognition into specialised AI agents respons…

[2025-06-02 Mon (UTC), 4 new articles found for q-bio.NC Neurons and Cognition]
#toXiv_bot_toot

Towards Cognitive Synergy in LLM-Based Multi-Agent Systems: Integrating Theory of Mind and Critical Evaluation
Adam Kostka, Jaros{\l}aw A. Chudziak
https://arxiv.org/abs/2507.21969

Towards Cognitive Synergy in LLM-Based Multi-Agent Systems: Integrating Theory of Mind and Critical Evaluation
Recently, the field of Multi-Agent Systems (MAS) has gained popularity as researchers are trying to develop artificial intelligence capable of efficient collective reasoning. Agents based on Large Language Models (LLMs) perform well in isolated tasks, yet struggle with higher-order cognition required for adaptive collaboration. Human teams achieve synergy not only through knowledge sharing, but also through recursive reasoning, structured critique, and the ability to infer others' mental states…

A foundation model to predict and capture human cognition.
https://www.nature.com/articles/s41586-025-09215-4
And the reaction and criticism,

A foundation model to predict and capture human cognition - Nature
A computational model called Centaur, developed by fine-tuning a language model on a huge dataset called Psych-101, can predict and simulate human nature in experiments expressible in natural language, even in previously unseen situations.

Incorporating episodic memory into quantum models of judgment and decision
Jerome R. Busemeyer, Masanao Ozawa, Emmanuel M. Pothos, Naotsugu Tsuchiya
https://arxiv.org/abs/2505.21521

Incorporating episodic memory into quantum models of judgment and decision
An important challenge for quantum theories of cognition and decision concerns the incorporation of memory for recently made judgments and their effects on later judgments. First, we review a general approach to measurement based on system plus environment representations of states and measurement instruments. These more general measurement models provide ways to incorporate effects of recent judgments on later judgments. Then we compare three different measurement models that are based on thes…

@… Your episode 52 on emotions had me wondering if you'd ever done anything on Maturana and Varela's ideas of autopoiesis and (loose) structural coupling. I'd be interested to hear you on that, also because these were ideas outside software actually applied to software via Winograd and Flores' _Understanding Computers and Cognition_. Lots of animal per…

[2025-06-03 Tue (UTC), 8 new articles found for q-bio.NC Neurons and Cognition]
#toXiv_bot_toot

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- The Relationship between Cognition and Computation: "Global-first" Cognition versus Local-first C...
Lin Chen

Cognition and the Media
https://ift.tt/bkt9UlD
updated: Thursday, June 26, 2025 - 9:35amfull name / name of organization: G. d'Annunzio University…
via Input 4 RELCFP https://

SpeechIQ: Speech Intelligence Quotient Across Cognitive Levels in Voice Understanding Large Language Models
Zhen Wan, Chao-Han Huck Yang, Yahan Yu, Jinchuan Tian, Sheng Li, Ke Hu, Zhehuai Chen, Shinji Watanabe, Fei Cheng, Chenhui Chu, Sadao Kurohashi
https://arxiv.org/abs/2507.19361

SpeechIQ: Speech Intelligence Quotient Across Cognitive Levels in Voice Understanding Large Language Models
We introduce Speech-based Intelligence Quotient (SIQ) as a new form of human cognition-inspired evaluation pipeline for voice understanding large language models, LLM Voice, designed to assess their voice understanding ability. Moving beyond popular voice understanding metrics such as word error rate (WER), SIQ examines LLM Voice across three cognitive levels motivated by Bloom's Taxonomy: (1) Remembering (i.e., WER for verbatim accuracy); (2) Understanding (i.e., similarity of LLM's interpreta…

[2025-07-02 Wed (UTC), 2 new articles found for q-bio.NC Neurons and Cognition]
toXiv_bot_toot

Exploiting Cognition in ISAR Processing for Spectral Compatibility Applications
Massimo Rosamilia, Augusto Aubry, Alessio Balleri, Antonio De Maio, Marco Martorella
https://arxiv.org/abs/2507.08423

Exploiting Cognition in ISAR Processing for Spectral Compatibility Applications
This paper introduces and analyzes the concept of a cognitive inverse synthetic aperture radar (ISAR) ensuring spectral compatibility in crowded electromagnetic environments. In such a context, the proposed approach alternates between environmental perception, recognizing possible emitters in its frequency range, and an action stage, synthesizing and transmitting a tailored radar waveform to achieve the desired imaging task while guaranteeing spectral coexistence with overlaid emitters. The per…

From Prompts to Constructs: A Dual-Validity Framework for LLM Research in Psychology
Zhicheng Lin
https://arxiv.org/abs/2506.16697 https://

From Prompts to Constructs: A Dual-Validity Framework for LLM Research in Psychology
Large language models (LLMs) are rapidly being adopted across psychology, serving as research tools, experimental subjects, human simulators, and computational models of cognition. However, the application of human measurement tools to these systems can produce contradictory results, raising concerns that many findings are measurement phantoms--statistical artifacts rather than genuine psychological phenomena. In this Perspective, we argue that building a robust science of AI psychology require…

Transition of AI Models in dependence of noise
Thomas Seidler, Markus Abel
https://arxiv.org/abs/2506.16715 https://arxiv.org/pdf/250…

Transition of AI Models in dependence of noise
We investigate the dependence of the score on noise in the data, and on the network size. As a result, we obtain the so-called "cognition transition" from good performance to zero with increasing noise. The understanding of this transition is of fundamental scientific and practical interest. We use concepts from statistical mechanics to understand how a changing finite size of models affects the cognition ability under the presence or corrupted data. On one hand, we study if there is a universa…

Stereotype graph: A mathematical framework of category stereotypes via graph theory
Yijia Yan
https://arxiv.org/abs/2506.12533 https://

Stereotype graph: A mathematical framework of category stereotypes via graph theory
In social psychology and cognitive science, there has been much interest in studying category stereotypes. However, we still lack a consensual mathematical definition or framework, which is necessary for us to hold a deeper understanding of stereotypes in human cognition. In this paper, we use graph theory to portray category stereotypes in human cognition, based on pairs of labels having special relations. By using methods and conclusions in graph theory (including algebraic graph theory and v…

[2025-07-03 Thu (UTC), 2 new articles found for q-bio.NC Neurons and Cognition]
toXiv_bot_toot

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability
Giuseppe Di Caro, Vahagn Kirakosyan, Alexander G. Abanov, Luca Candelori, Nadine Hartmann, Ernest T. Lam, Kharen Musaelian, Ryan Samson, Dario Villani, Martin T. Wells, Richard J. Wenstrup, Mengjia Xu
https://arxiv.org/abs/2506.03199

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability
The accurate prediction of chromosomal instability from the morphology of circulating tumor cells (CTCs) enables real-time detection of CTCs with high metastatic potential in the context of liquid biopsy diagnostics. However, it presents a significant challenge due to the high dimensionality and complexity of single-cell digital pathology data. Here, we introduce the application of Quantum Cognition Machine Learning (QCML), a quantum-inspired computational framework, to estimate morphology-pred…

Resnet-conformer network with shared weights and attention mechanism for sound event localization, detection, and distance estimation
Quoc Thinh Vo, David Han
https://arxiv.org/abs/2507.17941

Resnet-conformer network with shared weights and attention mechanism for sound event localization, detection, and distance estimation
This technical report outlines our approach to Task 3A of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2024, focusing on Sound Event Localization and Detection (SELD). SELD provides valuable insights by estimating sound event localization and detection, aiding in various machine cognition tasks such as environmental inference, navigation, and other sound localization-related applications. This year's challenge evaluates models using either audio-only (Track A) or audio…

Supervised Similarity for Firm Linkages
Ryan Samson, Adrian Banner, Luca Candelori, Sebastien Cottrell, Tiziana Di Matteo, Paul Duchnowski, Vahagn Kirakosyan, Jose Marques, Kharen Musaelian, Stefano Pasquali, Ryan Stever, Dario Villani
https://arxiv.org/abs/2506.19856

Supervised Similarity for Firm Linkages
We introduce a novel proxy for firm linkages, Characteristic Vector Linkages (CVLs). We use this concept to estimate firm linkages, first through Euclidean similarity, and then by applying Quantum Cognition Machine Learning (QCML) to similarity learning. We demonstrate that both methods can be used to construct profitable momentum spillover trading strategies, but QCML similarity outperforms the simpler Euclidean similarity.

These pieces are much harsher than Fred’s, much more in the LLM-bashing camp, but feel relevant here:
https://softwarecrisis.dev/letters/llmentalist/
https://pivot-to-ai.com/2025/06/05/generative-ai-runs-on-gambling-addiction-just-one-more-prompt-bro/
Fred’s point is that a bad interaction model creates hidden work, then humans do that work and “the machine claims the praise.” These other two pieces make the point that this phenomenon of giving the machine credit for unrecognized human work is age-old, taps into some deep trapdoors in human cognition.
10/

I believe I have "mild” (relative to others I've heard about) Long COVID and my symptoms include, fatigue, memory loss, loss of focus, loss of motivation, worse sleep.
It's real folks.
https://mastodon.social/@augieray/114841505817793827

Driving factors of auditory category learning success
Nan Wang, Gangyi Feng
https://arxiv.org/abs/2506.01508 https://arxiv.org/pdf/25…

Driving factors of auditory category learning success
Our brain learns to update its mental model of the environment by abstracting sensory experiences for adaptation and survival. Learning to categorize sounds is one essential abstracting process for high-level human cognition, such as speech perception, but it is also challenging due to the variable nature of auditory signals and their dynamic contexts. To overcome these learning challenges and enhance learner performance, it is essential to identify the impact of learning-related factors in dev…

Conscious agent networks: Formal analysis and application to cognition (2018) - ScienceDirect
https://www.sciencedirect.com/science/article/abs/pii/S1389041717300827
Full paper: https://escholarship.org/content/qt2d34n6zf/qt2d34n6zf.pdf?t=p2ng2g

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models
Lionel Wong, Katherine M. Collins, Lance Ying, Cedegao E. Zhang, Adrian Weller, Tobias Gersternberg, Timothy O'Donnell, Alexander K. Lew, Jacob D. Andreas, Joshua B. Tenenbaum, Tyler Brooke-Wilson
https://arxiv.org/abs/2507.12547

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models
When faced with novel situations, people are able to marshal relevant considerations from a wide range of background knowledge and put these to use in inferences and predictions. What permits us to draw in globally relevant information and reason over it coherently? Here, we explore the hypothesis that people use a combination of distributed and symbolic representations to construct bespoke mental models tailored to novel situations. We propose a computational implementation of this idea -- a `…

Your Ride, Your Rules: Psychology and Cognition Enabled Automated Driving Systems
Zhipeng Bao, Qianwen Li
https://arxiv.org/abs/2506.11842 https://

Your Ride, Your Rules: Psychology and Cognition Enabled Automated Driving Systems
Despite rapid advances in autonomous driving, current autonomous vehicles (AVs) lack effective bidirectional communication with occupants, limiting personalization and recovery from immobilization. This reduces comfort and trust, potentially slowing broader AV adoption. We propose PACE-ADS (Psychology and Cognition Enabled Automated Driving Systems), a human-centered autonomy framework that enables AVs to sense, interpret, and respond to both external traffic and internal occupant states. PACE-…

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Unable to Forget: Proactive Interference Reveals Working Memory Limits in LLMs Beyond Context Length
Chupei Wang (University of Virginia), Jiaqiu Vince Sun (New York University)

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Peripheral brain interfacing: Reading high-frequency brain signals from the output of the nervous...
Jaime Ib\'a\~nez, Blanka Zicher, Etienne Burdet, Stuart N. Baker, Carsten Mehring, Dari…

Windsurf CEO Jeff Wang on what happened after co-founders Varun Mohan and Douglas Chen left for Google, and how Cognition's deal to acquire Windsurf unfolded (Jeff Wang/@jeffwsurf)
https://x.com/jeffwsurf/status/1946376139959841084

Jeff Wang (@jeffwsurf) on X
To put it mildly, the past week at Windsurf has been crazy. There have been a lot of different rumors and reports, so I want to share a transparent account of how it actually went down. Before I start, I just want to say that Varun and Douglas were great founders and this

Toward a Behavioural Translation Style Space: Simulating the Temporal Dynamics of Affect, Behaviour, and Cognition in Human Translation Production
Michael Carl, Takanori Mizowaki, Aishvarya Ray, Masaru Yamada, Devi Sri Bandaru, Xinyue Ren
https://arxiv.org/abs/2507.12208

Toward a Behavioural Translation Style Space: Simulating the Temporal Dynamics of Affect, Behaviour, and Cognition in Human Translation Production
The paper introduces a Behavioural Translation Style Space (BTSS) that describes possible behavioural translation patterns. The suggested BTSS is organized as a hierarchical structure that entails various embedded processing layers. We posit that observable translation behaviour - i.e., eye and finger movements - is fundamental when executing the physical act of translation but it is caused and shaped by higher-order cognitive processes and affective translation states. We analyse records of ke…

Gender Similarities Dominate Mathematical Cognition at the Neural Level: A Japanese fMRI Study Using Advanced Wavelet Analysis and Generative AI
Tatsuru Kikuchi
https://arxiv.org/abs/2507.21140

Gender Similarities Dominate Mathematical Cognition at the Neural Level: A Japanese fMRI Study Using Advanced Wavelet Analysis and Generative AI
Recent large scale behavioral studies suggest early emergence of gender differences in mathematical performance within months of school entry. However, these findings lack direct neural evidence and are constrained by cultural contexts. We conducted functional magnetic resonance imaging (fMRI) during mathematical tasks in Japanese participants (N = 156), employing an advanced wavelet time frequency analysis to examine dynamic brain processes rather than static activation patterns. Wavelet decom…

[2025-08-01 Fri (UTC), 3 new articles found for q-bio.NC Neurons and Cognition]
toXiv_bot_toot

In-Home Social Robots Design for Cognitive Stimulation Therapy in Dementia Care
Emmanuel Akinrintoyo, Nicole Salomons
https://arxiv.org/abs/2507.13578 http…

In-Home Social Robots Design for Cognitive Stimulation Therapy in Dementia Care
Individual cognitive stimulation therapy (iCST) is a non-pharmacological intervention for improving the cognition and quality of life of persons with dementia (PwDs); however, its effectiveness is limited by low adherence to delivery by their family members. In this work, we present the user-centered design and evaluation of a novel socially assistive robotic system to provide iCST therapy to PwDs in their homes for long-term use. We consulted with 16 dementia caregivers and professionals. Thro…

[2025-07-01 Tue (UTC), 3 new articles found for q-bio.NC Neurons and Cognition]
toXiv_bot_toot

The Relationship between Cognition and Computation: "Global-first" Cognition versus Local-first Computation
Lin Chen
https://arxiv.org/abs/2506.17970

The Relationship between Cognition and Computation: "Global-first" Cognition versus Local-first Computation
What fundamental research questions are essential for advancing toward brain-like AI or AGI (Artificial General Intelligence) capable of performing any intellectual task a human can? Should it be something like the Turing machine (1936), which answers the question "What is computation?" and lays the foundation for the entire field of computer science? Or should it be something like Shannon's mathematical theory of communication (1948), which answers the question "What is information?" and forms…

Goldman Sachs CTO Marco Argenti says the bank is "going to start augmenting our workforce with Devin", Cognition's AI coding assistant, as Wall Street adopts AI (Hugh Son/CNBC)
https://www.cnbc.com/2025/07/11/goldman-sachs-auto…

Goldman Sachs is piloting its first autonomous coder in major AI milestone for Wall Street
The arrival of agentic AI at Goldman Sachs, in which programs don't just help with tasks but execute complex jobs, signals a shift on Wall Street.

Emergent Cognitive Convergence via Implementation: A Structured Loop Reflecting Four Theories of Mind (A Position Paper)
Myung Ho Kim
https://arxiv.org/abs/2507.16184

Emergent Cognitive Convergence via Implementation: A Structured Loop Reflecting Four Theories of Mind (A Position Paper)
We report the discovery of a structural convergence across four influential theories of mind: Kahneman's dual-system theory, Friston's predictive processing, Minsky's society of mind, and Clark's extended mind-emerging unintentionally within a practical AI agent architecture called Agentic Flow. Designed to address limitations in large language models (LLMs), Agentic Flow comprises five interdependent modules such as Retrieval, Cognition, Control, Memory, and Action arranged in a recurrent cogn…

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Agency Perception and Brain Synchrony: A Hyperscanning Study of Human-Human and Human-AI Interaction
Ghalavand, Hatami, Setarehdan, Nosrati, Ghalavand, Nikhalat-Jahromi

The Compositional Architecture of Regret in Large Language Models
Xiangxiang Cui, Shu Yang, Tianjin Huang, Wanyu Lin, Lijie Hu, Di Wang
https://arxiv.org/abs/2506.15617

The Compositional Architecture of Regret in Large Language Models
Regret in Large Language Models refers to their explicit regret expression when presented with evidence contradicting their previously generated misinformation. Studying the regret mechanism is crucial for enhancing model reliability and helps in revealing how cognition is coded in neural networks. To understand this mechanism, we need to first identify regret expressions in model outputs, then analyze their internal representation. This analysis requires examining the model's hidden states, wh…

System 0: Transforming Artificial Intelligence into a Cognitive Extension
Massimo Chiriatti, Marianna Bergamaschi Ganapini, Enrico Panai, Brenda K. Wiederhold, Giuseppe Riva
https://arxiv.org/abs/2506.14376

System 0: Transforming Artificial Intelligence into a Cognitive Extension
This paper introduces System 0, a conceptual framework for understanding how artificial intelligence functions as a cognitive extension preceding both intuitive (System 1) and deliberative (System 2) thinking processes. As AI systems increasingly shape the informational substrate upon which human cognition operates, they transform from passive tools into active cognitive partners. Building on the Extended Mind hypothesis and Heersmink's criteria for cognitive extension, we argue that AI systems…

[2025-07-31 Thu (UTC), 4 new articles found for q-bio.NC Neurons and Cognition]
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[2025-06-30 Mon (UTC), 4 new articles found for q-bio.NC Neurons and Cognition]
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Causality in the human niche: lessons for machine learning
Richard D. Lange, Konrad P. Kording
https://arxiv.org/abs/2506.13803 https://

Causality in the human niche: lessons for machine learning
Humans interpret the world around them in terms of cause and effect and communicate their understanding of the world to each other in causal terms. These causal aspects of human cognition are thought to underlie humans' ability to generalize and learn efficiently in new domains, an area where current machine learning systems are weak. Building human-like causal competency into machine learning systems may facilitate the construction of effective and interpretable AI. Indeed, the machine learnin…

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Signed Higher-Order Interactions for Brain Disorder Diagnosis via Multi-Channel Transformers
Dengyi Zhao, Zhiheng Zhou, Guiying Yan, Dongxiao Yu, Xingqin Qi

Regulating Next-Generation Implantable Brain-Computer Interfaces: Recommendations for Ethical Development and Implementation
Renee Sirbu, Jessica Morley, Tyler Schroder, Mariarosaria Taddeo, Raghavendra Pradyumna Pothukuchi, Muhammed Ugur, Abhishek Bhattacharjee, Luciano Floridi
https://arxiv.org/abs/2506.12540

Regulating Next-Generation Implantable Brain-Computer Interfaces: Recommendations for Ethical Development and Implementation
Brain-computer interfaces offer significant therapeutic opportunities for a variety of neurophysiological and neuropsychiatric disorders and may perhaps one day lead to augmenting the cognition and decision-making of the healthy brain. However, existing regulatory frameworks designed for implantable medical devices are inadequate to address the unique ethical, legal, and social risks associated with next-generation networked brain-computer interfaces. In this article, we make nine recommendatio…

Decoding Neural Signatures of Semantic Evaluations in Depression and Suicidality
Woojae Jeong, Aditya Kommineni, Kleanthis Avramidis, Colin McDaniel, Donald Berry, Myzelle Hughes, Thomas McGee, Elsi Kaiser, Dani Byrd, Assal Habibi, B. Rael Cahn, Idan A. Blank, Kristina Lerman, Dimitrios Pantazis, Sudarsana R. Kadiri, Takfarinas Medani, Shrikanth Narayanan, Richard M. Leahy

Decoding Neural Signatures of Semantic Evaluations in Depression and Suicidality
Depression and suicidality profoundly impact cognition and emotion, yet objective neurophysiological biomarkers remain elusive. We investigated the spatiotemporal neural dynamics underlying affective semantic processing in individuals with varying levels of clinical severity of depression and suicidality using multivariate decoding of electroencephalography (EEG) data. Participants (N=137) completed a sentence evaluation task involving emotionally charged self-referential statements while EEG w…

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Advantageous and disadvantageous inequality aversion can be taught through vicarious learning of ...
Shen Zhang, Oriel FeldmanHall, S\'ebastien H\'etu, A. Ross Otto

[2025-05-30 Fri (UTC), 6 new articles found for q-bio.NC Neurons and Cognition]
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Brain rhythms in cognition -- controversies and future directions
Anne Keitel, Christian Keitel, Mohsen Alavash, Karin Bakardjian, Christopher S. Y. Benwell, Sophie Bouton, Niko A. Busch, Antonio Criscuolo, Keith B. Doelling, Laura Dugue, Laetitia Grabot, Joachim Gross, Simon Hanslmayr, Laura-Isabelle Klatt, Daniel S. Kluger, Gemma Learmonth, Raquel E. London, Christina Lubinus, Andrea E. Martin, Jonas Obleser, Johanna M. Rimmele, Vincenzo Romei, Manuela Ruzzoli, Felix Siebenhuhner, So…

Brain rhythms in cognition -- controversies and future directions
Brain rhythms seem central to understanding the neurophysiological basis of human cognition. Yet, despite significant advances, key questions remain unresolved. In this comprehensive position paper, we review the current state of the art on oscillatory mechanisms and their cognitive relevance. The paper critically examines physiological underpinnings, from phase-related dynamics like cyclic excitability, to amplitude-based phenomena, such as gating by inhibition, and their interactions, such as…

[2025-07-30 Wed (UTC), 3 new articles found for q-bio.NC Neurons and Cognition]
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Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- beta Hydroxybutyrate Targets C99 Driven Organelle Disruption in a Drosophila Model of Alzheimers ...
Hao Huang, Kaijing Xu, Michael Lardelli

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Inverse Reinforcement Learning via Convex Optimization
Hao Zhu, Yuan Zhang, Joschka Boedecker

[2025-05-29 Thu (UTC), 2 new articles found for q-bio.NC Neurons and Cognition]
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[2025-07-29 Tue (UTC), 4 new articles found for q-bio.NC Neurons and Cognition]
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Mapping Neural Theories of Consciousness onto the Common Model of Cognition
Paul S. Rosenbloom, John E. Laird, Christian Lebiere, Andrea Stocco
https://arxiv.org/abs/2506.12224

Mapping Neural Theories of Consciousness onto the Common Model of Cognition
A beginning is made at mapping four neural theories of consciousness onto the Common Model of Cognition. This highlights how the four jointly depend on recurrent local modules plus a cognitive cycle operating on a global working memory with complex states, and reveals how an existing integrative view of consciousness from a neural perspective aligns with the Com-mon Model.

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- In silico discovery of representational relationships across visual cortex
Alessandro T. Gifford, Maya A. Jastrz\k{e}bowska, Johannes J. D. Singer, Radoslaw M. Cichy

Spontaneous Spatial Cognition Emerges during Egocentric Video Viewing through Non-invasive BCI
Weichen Dai, Yuxuan Huang, Li Zhu, Dongjun Liu, Yu Zhang, Qibin Zhao, Andrzej Cichocki, Fabio Babiloni, Ke Li, Jianyu Qiu, Gangyong Jia, Wanzeng Kong, Qing Wu
https://arxiv.org/abs/2507.12417

Spontaneous Spatial Cognition Emerges during Egocentric Video Viewing through Non-invasive BCI
Humans possess a remarkable capacity for spatial cognition, allowing for self-localization even in novel or unfamiliar environments. While hippocampal neurons encoding position and orientation are well documented, the large-scale neural dynamics supporting spatial representation, particularly during naturalistic, passive experience, remain poorly understood. Here, we demonstrate for the first time that non-invasive brain-computer interfaces (BCIs) based on electroencephalography (EEG) can decod…

[2025-05-28 Wed (UTC), 2 new articles found for q-bio.NC Neurons and Cognition]
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[2025-07-28 Mon (UTC), 3 new articles found for q-bio.NC Neurons and Cognition]
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[2025-06-27 Fri (UTC), 5 new articles found for q-bio.NC Neurons and Cognition]
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Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Markov Blanket Density and Free Energy Minimization
Luca M. Possati

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Inverted Inference and Recursive Bootstrapping: A Primal-Dual Theory of Structured Cognition
Xin Li

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- EEG Foundation Models: A Critical Review of Current Progress and Future Directions
Gayal Kuruppu, Neeraj Wagh, Yogatheesan Varatharajah

[2025-06-26 Thu (UTC), 4 new articles found for q-bio.NC Neurons and Cognition]
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Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- From DDMs to DNNs: Using process data and models of decision-making to improve human-AI interactions
Mrugsen Nagsen Gopnarayan, Jaan Aru, Sebastian Gluth

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Anti-seizure medication load is not correlated with early termination of seizure spread
Nathan Evans, et al.

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Hodge-Decomposition of Functional Brain Networks
D. Vijay Anand, Anass B El-Yaagoubi, Hernando Ombao, Moo K. Chung

[2025-07-25 Fri (UTC), 1 new article found for q-bio.NC Neurons and Cognition]
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[2025-06-24 Tue (UTC), 6 new articles found for q-bio.NC Neurons and Cognition]
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Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- The content and structure of dreams are coupled to affect
Luke Leckie, Anya K. Bershad, Jes Heppler, Mason McClay, Sofiia Rappe, Jacob G. Foster

[2025-07-24 Thu (UTC), 2 new articles found for q-bio.NC Neurons and Cognition]
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[2025-07-23 Wed (UTC), 5 new articles found for q-bio.NC Neurons and Cognition]
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Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
Spatiotemporal Learning of Brain Dynamics from fMRI Using Frequency-Specific Multi-Band Attention...

[2025-07-22 Tue (UTC), 9 new articles found for q-bio.NC Neurons and Cognition]
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Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
- Geometric Hyperscanning of Affect under Active Inference
Hinrichs, Albarracin, Bolis, Jiang, Christov-Moore, Schilbach

Replaced article(s) found for q-bio.NC. https://arxiv.org/list/q-bio.NC/new
[1/1]:
Hodge-Decomposition of Brain Networks
https://

Rational Superautotrophic Diplomacy (SupraAD); A Conceptual Framework for Alignment Based on Interdisciplinary Findings on the Fundamentals of Cognition
Andrea Morris
https://arxiv.org/abs/2506.05389

Rational Superautotrophic Diplomacy (SupraAD); A Conceptual Framework for Alignment Based on Interdisciplinary Findings on the Fundamentals of Cognition
Populating our world with hyperintelligent machines obliges us to examine cognitive behaviors observed across domains that suggest autonomy may be a fundamental property of cognitive systems, and while not inherently adversarial, it inherently resists containment and control. If this principle holds, AI safety and alignment efforts must transition to mutualistic negotiation and reciprocal incentive structures, abandoning methods that assume we can contain and control an advanced artificial gene…

[2025-07-21 Mon (UTC), 2 new articles found for q-bio.NC Neurons and Cognition]
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