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Brain Circuits Behind Psychedelics’ Anti-Anxiety Power Decoded - Neuroscience News
Neuroscience News provides research news for neuroscience, neurology, psychology, AI, brain science, mental health, robotics and cognitive sciences.

A Computational Framework to Identify Self-Aspects in Text
Jaya Caporusso, Matthew Purver, Senja Pollak
https://arxiv.org/abs/2507.13115 https://

A Computational Framework to Identify Self-Aspects in Text
This Ph.D. proposal introduces a plan to develop a computational framework to identify Self-aspects in text. The Self is a multifaceted construct and it is reflected in language. While it is described across disciplines like cognitive science and phenomenology, it remains underexplored in natural language processing (NLP). Many of the aspects of the Self align with psychological and other well-researched phenomena (e.g., those related to mental health), highlighting the need for systematic NLP-…

Humans, Machine Learning, and Language Models in Union: A Cognitive Study on Table Unionability
Sreeram Marimuthu, Nina Klimenkova, Roee Shraga
https://arxiv.org/abs/2506.12990

Humans, Machine Learning, and Language Models in Union: A Cognitive Study on Table Unionability
Data discovery and table unionability in particular became key tasks in modern Data Science. However, the human perspective for these tasks is still under-explored. Thus, this research investigates the human behavior in determining table unionability within data discovery. We have designed an experimental survey and conducted a comprehensive analysis, in which we assess human decision-making for table unionability. We use the observations from the analysis to develop a machine learning framewor…

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…

Music-induced cognitive change and whole-brain network flexibility: a pilot study https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1567605/full Now what might visual-to-auditory sensory substitution train…

Frontiers | Music-induced cognitive change and whole-brain network flexibility: a pilot study
IntroductionCognitive impairment that exceeds age-related cognitive decline is a risk factor for Alzheimer’s disease and related dementias. As the older adul...

We've been studying the cognitive science of *diagrams*, and have recently put out a new (very) lightweight programming language and tool for diagramming models in formal methods. Check it out here!
https://blog.brownplt.org/2025/06/09/copeanddrag.html

From Anxiety to Alzheimer’s, Music Makes a Difference https://neurosciencenews.com/alzheimers-anxiety-music-28655/?utm_source=dlvr.it&utm_content=NeuroscienceNew%…

From Anxiety to Alzheimer’s, Music Makes a Difference - Neuroscience News
Neuroscience News provides research news for neuroscience, neurology, psychology, AI, brain science, mental health, robotics and cognitive sciences.

Do AI tutors empower or enslave learners? Toward a critical use of AI in education
Lucile Favero, Juan-Antonio P\'erez-Ortiz, Tanja K\"aser, Nuria Oliver
https://arxiv.org/abs/2507.06878

Do AI tutors empower or enslave learners? Toward a critical use of AI in education
The increasing integration of AI tools in education presents both opportunities and challenges, particularly regarding the development of the students' critical thinking skills. This position paper argues that while AI can support learning, its unchecked use may lead to cognitive atrophy, loss of agency, emotional risks, and ethical concerns, ultimately undermining the core goals of education. Drawing on cognitive science and pedagogy, the paper explores how over-reliance on AI can disrupt mean…

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/2412.13631 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Mind Your Theory: Theory of Mind Goes Deeper Than Reasoning
Theory of Mind (ToM) capabilities in LLMs have recently become a central object of investigation. Cognitive science distinguishes between two steps required for ToM tasks: 1) determine whether to invoke ToM, which includes the appropriate Depth of Mentalizing (DoM), or level of recursion required to complete a task; and 2) applying the correct inference given the DoM. In this position paper, we first identify several lines of work in different communities in AI, including LLM benchmarking, ToM …

This https://arxiv.org/abs/2505.12018 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

A Human Study of Cognitive Biases in CTF Challenges
Cybersecurity training has become a crucial part of computer science education and industrial onboarding. Capture the Flag (CTF) competitions have emerged as a valuable, gamified approach for developing and refining the skills of cybersecurity and software engineering professionals. However, while CTFs provide a controlled environment for tackling real world challenges, the participants' decision making and problem solving processes remain under explored. Recognizing that psychology may play a …

Inside you are many wolves: Using cognitive models to interpret value trade-offs in LLMs
Sonia K. Murthy, Rosie Zhao, Jennifer Hu, Sham Kakade, Markus Wulfmeier, Peng Qian, Tomer Ullman
https://arxiv.org/abs/2506.20666

Inside you are many wolves: Using cognitive models to interpret value trade-offs in LLMs
Navigating everyday social situations often requires juggling conflicting goals, such as conveying a harsh truth, maintaining trust, all while still being mindful of another person's feelings. These value trade-offs are an integral part of human decision-making and language use, however, current tools for interpreting such dynamic and multi-faceted notions of values in LLMs are limited. In cognitive science, so-called "cognitive models" provide formal accounts of these trade-offs in humans, by …

This https://arxiv.org/abs/2211.00694 has been replaced.
link: https://scholar.google.com/scholar?q=a

What we talk about when we talk about physics problem solving
I am a second-year cognitive science major, and as a student who has completed my physical science distributive requirements, I will likely never again come across Gauss's law. So why do I feel that the time and effort I devoted to solving Gauss's law problems was worth it? Partly, I inherently enjoy the learning process and the new perspective on the physical world I have acquired by understanding electromagnetism. But I was also inspired by the ways in which physics problems train the mind in…

Risk-Guided Diffusion: Toward Deploying Robot Foundation Models in Space, Where Failure Is Not An Option
Rohan Thakker, Adarsh Patnaik, Vince Kurtz, Jonas Frey, Jonathan Becktor, Sangwoo Moon, Rob Royce, Marcel Kaufmann, Georgios Georgakis, Pascal Roth, Joel Burdick, Marco Hutter, Shehryar Khattak
https://arxiv.org/abs/2506.1760…

Risk-Guided Diffusion: Toward Deploying Robot Foundation Models in Space, Where Failure Is Not An Option
Safe, reliable navigation in extreme, unfamiliar terrain is required for future robotic space exploration missions. Recent generative-AI methods learn semantically aware navigation policies from large, cross-embodiment datasets, but offer limited safety guarantees. Inspired by human cognitive science, we propose a risk-guided diffusion framework that fuses a fast, learned "System-1" with a slow, physics-based "System-2", sharing computation at both training and inference to couple adaptability …

Ghost in the Machine: Examining the Philosophical Implications of Recursive Algorithms in Artificial Intelligence Systems
Llewellin RG Jegels
https://arxiv.org/abs/2507.01967

Ghost in the Machine: Examining the Philosophical Implications of Recursive Algorithms in Artificial Intelligence Systems
This paper investigates whether contemporary AI architectures employing deep recursion, meta-learning, and self-referential mechanisms provide evidence of machine consciousness. Integrating philosophical history, cognitive science, and AI engineering, it situates recursive algorithms within a lineage spanning Cartesian dualism, Husserlian intentionality, Integrated Information Theory, the Global Workspace model, and enactivist perspectives. The argument proceeds through textual analysis, compar…

Enhancing Large Language Models through Structured Reasoning
Yubo Dong, Hehe Fan
https://arxiv.org/abs/2506.20241 https://arxiv.org/p…

Enhancing Large Language Models through Structured Reasoning
Recent Large Language Models (LLMs) have significantly advanced natural language processing and automated decision-making. However, these models still encounter difficulties when performing complex reasoning tasks involving logical deduction and systematic planning, primarily due to their reliance on implicit statistical relationships without structured knowledge representation.Inspired by cognitive science and neurosymbolic AI, we introduce a novel approach to enhance LLMs through explicit str…