Neural and Behavioral Psychology Studies

Latest papers

• $R^3$-Bench: LLMs Struggle with Resource-Rational Reasoning under Shared Budgets

  Peisong Wang, Zhiwei Ma, Bowen Liu, Feixue Liu, Aochuan Chen, Chenyi Zi, Hongchuan Zeng, Yuhan Li, Jia Li · 18 August 2026

  In cognitive science, resource rationality asks how an agent should allocate limited computation to maximize expected value. Most reasoning and agent benchmarks use independent per-task budgets; existing shared-budget studies do not calibrate suite performance against the same model's demonstrated s…

• Reward Valuation in Vision Language Models: Causal Mechanisms Underlying Anhedonia

  Melika Honarmand, Samin Mahdipour Aghabagher, Martin Schrimpf · 9 July 2026

  Recent Vision-Language Models capture increasingly complex aspects of human cognition. Here we ask whether this alignment extends to reward valuation, which we assess in a mechanistic framework built on clinical tests that were developed to evaluate anhedonia and motivational deficits in major depre…

• Reward function compression facilitates goal-dependent reinforcement learning

  Gaia Molinaro, Anne G. E. Collins · 2 July 2026

  Humans can uniquely assign value to novel, abstract outcomes to support reinforcement learning. However, this flexibility is cognitively costly and reduces learning efficiency. We propose that goal-dependent learning initially relies on capacity-limited working memory. With consistent experience, le…

• Do vision-language models search like humans? Reasoning tokens as a reaction-time analog in classic visual-search paradigms

  Farahnaz Wick · 25 June 2026

  Visual search has been one of the most productive paradigms in the study of visual attention: the way reaction time scales with the number of items distinguishes parallel, "pop-out" search from serial, attention-demanding search. I ask whether vision-language models (VLMs) exhibit the same behaviora…

• Spectral Probe-Circuits: A Three-Step Recipe for Identifying Attention-Head Circuits in Pretrained Transformers

  Yongzhong Xu · 26 May 2026

  We present a three-step recipe for identifying attention-head circuits in pretrained transformers. A per-head spectral signal -- the time-integrated participation ratio of each head's attention output -- ranks heads doing sustained content-dependent computation without labels or attribution gradient…

• Option-Order Randomisation Reveals a Distributional Position Attractor in Prompted Sandbagging

  Jon-Paul Cacioli · 30 April 2026

  A predecessor pilot (Cacioli, 2026) found that Llama-3-8B implements prompted sandbagging as positional collapse rather than answer avoidance. However, fixed option ordering in MMLU-Pro left open whether this reflected a model-level position-dominant policy or dataset-level distractor structure. Thi…

• Contextual Control without Memory Growth in a Context-Switching Task

  Song-Ju Kim · 7 April 2026

  Context-dependent sequential decision making is commonly addressed either by providing context explicitly as an input or by increasing recurrent memory so that contextual information can be represented internally. We study a third alternative: realizing contextual dependence by intervening on a shar…

• Gaze patterns predict preference and confidence in pairwise AI image evaluation

  Nikolas Papadopoulos, Shreenithi Navaneethan, Sheng Bai, Ankur Samanta, Paul Sajda · 27 March 2026

  Preference learning methods, such as Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO), rely on pairwise human judgments, yet little is known about the cognitive processes underlying these judgments. We investigate whether eye-tracking can reveal preference f…

• Social Comparison without Explicit Inference of Others' Reward Values: A Constructive Approach Using a Probabilistic Generative Model

  Yosuke Taniuchi, Chie Hieida, Atsushi Noritake, Kazushi Ikeda, Masaki Isoda · 24 March 2026

  Social comparison$\unicode{x2014}$the process of evaluating one's rewards relative to others$\unicode{x2014}$is an essential feature of social emotions such as envy and plays a fundamental role in primate social cognition. However, it remains unknown how information about others' rewards affects one…

• Task learning increases information redundancy of neural responses in macaque visual cortex

  Shizhao Liu, Anton Pletenev, Ralf M. Haefner, Adam C. Snyder · 10 March 2026

  How does the brain optimize sensory information for decision-making in new tasks? One hypothesis suggests learning reduces redundancy in neural representations to improve efficiency, while another, based on Bayesian inference, predicts learning increases redundancy by distributing information across…

• Is It Thinking or Cheating? Detecting Implicit Reward Hacking by Measuring Reasoning Effort

  Xinpeng Wang, Nitish Joshi, Barbara Plank, Rico Angell, He He · 3 March 2026

  Reward hacking, where a reasoning model exploits loopholes in a reward function to achieve high rewards without solving the intended task, poses a significant threat. This behavior may be explicit, i.e. verbalized in the model's chain-of-thought (CoT), or implicit, where the CoT appears benign thus …

• Motivation is Something You Need

  Mehdi Acheli, Walid Gaaloul · 25 February 2026

  This work introduces a novel training paradigm that draws from affective neuroscience. Inspired by the interplay of emotions and cognition in the human brain and more specifically the SEEKING motivational state, we design a dual-model framework where a smaller base model is trained continuously, whi…

• Learning under noisy supervision is governed by a feedback-truth gap

  Elan Schonfeld, Elias Wisnia · 20 February 2026

  When feedback is absorbed faster than task structure can be evaluated, the learner will favor feedback over truth. A two-timescale model shows this feedback-truth gap is inevitable whenever the two rates differ and vanishes only when they match. We test this prediction across neural networks trained…

• Primate-like perceptual decision making emerges through deep recurrent reinforcement learning

  Nathan J. Wispinski, Scott A. Stone, Anthony Singhal, Patrick M. Pilarski, Craig S. Chapman · 21 January 2026

  Progress has led to a detailed understanding of the neural mechanisms that underlie decision making in primates. However, less is known about why such mechanisms are present in the first place. Theory suggests that primate decision making mechanisms, and their resultant behavioral abilities, emerged…

• Social Comparison without Explicit Inference of Others' Reward Values: A Constructive Approach Using a Probabilistic Generative Model

  Yosuke Taniuchi, Chie Hieida, Atsushi Noritake, Kazushi Ikeda, Masaki Isoda · 6 January 2026

  Social comparison$\unicode{x2014}$the process of evaluating one's rewards relative to others$\unicode{x2014}$plays a fundamental role in primate social cognition. However, it remains unknown from a computational perspective how information about others' rewards affects the evaluation of one's own re…

• An Inference-Based Architecture for Intent and Affordance Saturation in Decision-Making

  Wendyam Eric Lionel Ilboudo, Saori C Tanaka · 30 December 2025

  Decision paralysis, i.e. hesitation, freezing, or failure to act despite full knowledge and motivation, poses a challenge for choice models that assume options are already specified and readily comparable. Drawing on qualitative reports in autism research that are especially salient, we propose a co…

• Social Comparison without Explicit Inference of Others' Reward Values: A Constructive Approach Using a Probabilistic Generative Model

  Yosuke Taniuchi, Chie Hieida, Atsushi Noritake, Kazushi Ikeda, Masaki Isoda · 24 December 2025

  Social comparison$\unicode{x2014}$the process of evaluating one's rewards relative to others$\unicode{x2014}$plays a fundamental role in primate social cognition. However, it remains unknown from a computational perspective how information about others' rewards affects the evaluation of one's own re…

• Reasoning or Memorization? Unreliable Results of Reinforcement Learning Due to Data Contamination

  Mingqi Wu, Zhihao Zhang, Qiaole Dong, Zhiheng Xi, Jun Zhao, Senjie Jin, Xiaoran Fan, Yuhao Zhou, Huijie Lv, Ming Zhang, Yanwei Fu, Qin Liu, Songyang Zhang, Qi Zhang · 18 December 2025

  Reasoning in large language models has long been a central research focus, and recent studies employing reinforcement learning (RL) have introduced diverse methods that yield substantial performance gains with minimal or even no external supervision. Surprisingly, some studies even suggest that rand…

• Noise-based reward-modulated learning

  Jes\'us Garc\'ia Fern\'andez, Nasir Ahmad, Marcel van Gerven · 5 November 2025

  The pursuit of energy-efficient and adaptive artificial intelligence (AI) has positioned neuromorphic computing as a promising alternative to conventional computing. However, achieving learning on these platforms requires techniques that prioritize local information while enabling effective credit a…

• Dopamine-driven synaptic credit assignment in neural networks

  Saranraj Nambusubramaniyan, Shervin Safavi, Raja Guru, Andreas Knoblauch · 28 October 2025

  Solving the synaptic Credit Assignment Problem(CAP) is central to learning in both biological and artificial neural systems. Finding an optimal solution for synaptic CAP means setting the synaptic weights that assign credit to each neuron for influencing the final output and behavior of neural netwo…