Benjamin Y. Hayden

This study shows that neural timescales hierarchy changes with behavioral demands in freely moving rhesus macaques, with task engagement affecting timescale magnitudes across brain areas.

The paper analyzes neural activity in macaques during a foraging task to show how prefrontal regions represent and control actions in a modular and hierarchical manner.

The paper investigates functional differences between dorsal and ventral posterior cingulate cortex in humans using intracranial recordings, finding distinct population and single-neuron selectivity for executive and episodic processing.

The paper extends the PRO model to explain decision-making under risk in humans and macaques, showing ACC represents outcome variance and links to mean-variance theories.

The paper examines neural coding for value in six brain regions and finds no explicit value neurons, but shows value is encoded implicitly through orthogonal yet linked population subspaces.

The paper shows that pre-trial firing rate patterns in human dlPFC predict conflict resolution in cognitive tasks, with distinct but related patterns for different conflict types.

The paper investigates how the brain binds features of options during decision-making using aligned and orthogonal subspaces in neural activity.

This study shows that the dorsal anterior cingulate cortex (dACC) in macaques encodes both world-centric and avatar-centric variables during pursuit and evasion tasks.

This study examines how neurons in reward regions of macaques encode safe and risky offers during a gambling task, finding distinct response subspaces for each type of offer.

OpenMonkeyStudio provides a deep learning-based system for markerless 3D pose estimation in freely moving macaques, enabling automatic tracking and action recognition in unconstrained environments.

This paper demonstrates ultra-high field (10.5 T) resting state fMRI in macaques, revealing detailed and robust resting state components similar to human connectomes.

The paper identifies two subregions of the orbitofrontal cortex (OFC) with distinct connectivity to the posterior cingulate cortex (PCC) and shows that the OFCin-PCC circuit relays choice signals from value to action space.

The paper examines hierarchical organization in medial prefrontal cortex regions during risky choices in macaques, finding increased decodability and longer timescales along a specific pathway.

The paper explores the relationship between curiosity, latent learning, and cognitive maps, proposing roles for OFC and dACC in curiosity-driven learning.

The paper shows that increased tonic firing in dACC predicts stronger information-seeking behavior in rhesus macaques.

The paper shows that conflict in the dorsal anterior cingulate cortex (dACC) amplifies task-relevant information across neurons, rather than relying on specific conflict-encoding neurons or coactivation of action plans.

The paper models decision-making under limited capacity, showing that optimal strategies shift from breadth to depth as capacity increases.

Monkeys predict future prey positions during pursuit, and dACC neurons encode these predictions.

The paper uses a Bayesian regression approach to show that dACC neurons partially integrate value determinants, indicating they are neither pre- nor post-evaluative.

The paper investigates how rules affect neural representations during decision-making, finding that rules warp neural activity to prioritize relevant information.

This study shows that exploratory noise influences both cognitive flexibility and spontaneous errors, with cocaine reducing exploration and improving performance by lowering lapse rates.

This study compares non-human primate and deep reinforcement learning agent performance in a virtual pursuit-avoidance task, finding agents primarily learn first-order physics while the primate exhibits second-order physics.

This study identifies distinct neural ensemble patterns in the orbitofrontal cortex that differentiate successful from failed inhibition during a stop signal task in macaques.

The paper examines macaque pupil responses to offered and anticipated rewards, finding opposing correlations that challenge the simulation hypothesis and suggest an accept-reject model of comparison.

This study shows that orbitofrontal cortex activity predicts both economic choice and stopping in macaques, suggesting shared neural processes for these tasks.

This study shows that monkeys exhibit flexible risk attitudes, with varying utility and probability weighting functions across tasks, suggesting dynamic construction of reward value rather than fixed traits.

Rhesus macaques predict virtual prey trajectories using Newtonian physics principles, ignoring other behavioral patterns despite training.

The paper proposes a neuronal theory explaining sequential economic choice through dynamic attention and value coding mechanisms.

The paper applies foraging theory to economic choice, framing decisions as evolved psychological processes similar to foraging, with implications for self-control and binary choice mechanisms.

The paper introduces a Bayesian method to classify neurons into clusters based on response properties, finding that neurons fall into two clusters: task-sensitive and non-selective.