Mehrdad Jazayeri

Compositional computations in the primate frontal cortex

The paper investigates how neural circuits in the primate frontal cortex support compositional generalization by separating computations into spatial and temporal components and identifying biases when these components are misaligned.

Physical sensorimotor contingencies facilitate learning in monkeys

This study shows that rhesus monkeys learn maze-solving tasks significantly faster in a physical environment than in a virtual one, with limited performance transfer between the two.

A Relational Code for Objects in Primate Frontal Cortex

This study shows that neurons in primate frontal cortex encode both object locations and their spatial relationships during working memory.

Structural generalization and continual learning enabled by factorized entorhinal-hippocampal memory and entorhinal-parietal action circuits

The paper develops a computational model of memory and learning in the brain that enables generalization and continual learning through factorized entorhinal-hippocampal and entorhinal-parietal circuits.

Adaptive problem solving in the primate frontal cortex

This study investigates how monkeys adaptively solve problems by analyzing neural activity in the frontal cortex during a decision task, revealing distinct dynamical regimes associated with different strategies.

A neural mechanism for online discovery of latent contexts

This paper introduces NeuraGEM, a neural architecture that models online discovery of latent contexts through fast transient activity and slow synaptic plasticity, reproducing human contextual learning features and brain-like dynamics.

Working Memory of Multi-Object Scenes in Primate Frontal Cortex

This study investigates how primates store multiple objects in working memory using neural data from monkeys, finding that a weighted-sum model better explains memory representation than slot or switching models.

Evidence accumulation from experience and observation in the cingulate cortex

This study investigates how the anterior cingulate cortex integrates experiential and observational evidence in a two-player game, revealing neural mechanisms for dynamic belief updating.

Computational basis of hierarchical and counterfactual information processing

This study investigates how humans solve complex decision problems by combining hierarchical and counterfactual reasoning, finding that these strategies are computationally rational under specific constraints.

MEDiCINe: Motion Correction for Neural Electrophysiology Recordings

MEDiCINe improves motion correction in neural electrophysiology recordings, leading to more accurate spike sorting.

Dynamic tracking of objects in the macaque dorsomedial frontal cortex

The paper tests the hypothesis that mental simulations underlie physical inferences by analyzing neural activity in monkeys during a ball interception task, finding a low-dimensional neural embedding that tracks the ball's position.

Sensory History Shapes Contrastive Neural Geometry in LP/Pulvinar-Prefrontal Cortex Circuits

The paper shows that the LP-ACC pathway in mice is essential for using prior stimulus history to guide decision-making by estimating differences in evidence between trials.

Parametric control of flexible timing through low-dimensional neural manifolds

The paper shows that low-dimensional neural manifolds enable parametric control of flexible timing through tonic inputs in trained recurrent networks and confirms this in monkey behavior.

Vector production via mental navigation in the entorhinal cortex

The paper demonstrates that monkeys use structured representations in the entorhinal cortex for mental navigation without sensory feedback, showing endogenous cognitive map recruitment.

A large-scale neural network training framework for generalized estimation of single-trial population dynamics

This paper introduces AutoLFADS, an automated framework for estimating neural population dynamics from neural data without supervisory information, validated on multiple datasets.

Mixture of Learning Strategies Underlies Rodent Behavior in Dynamic Foraging

This study identifies behavioral strategies in rodent foraging by analyzing switching dynamics and develops a method to infer mixed strategy use during dynamic tasks.

Synaptic basis of a sub-second representation of time

The paper investigates whether short-term synaptic plasticity can generate neural dynamics for sub-second temporal learning using cerebellar simulations.

Keeping time and rhythm by replaying a sensory-motor engram

The paper shows that primates internally maintain rhythms through widespread brain activity resembling a metronome, replaying sensory-motor engrams without external stimuli.

A precise and adaptive neural mechanism for predictive temporal processing in the frontal cortex

The paper identifies a precise neural mechanism in the frontal cortex of non-human primates that adapts to temporal statistics, supporting predictive processing of time.

The role of mental simulation in primate physical inference abilities

This study compares human and monkey behavior in a ball interception task with RNN models to test if mental simulation aids physical inference.

Reinforcement regulates timing variability in thalamus

This paper investigates how reinforcement affects timing variability in humans and monkeys, identifying two distinct sources of variability and their neural correlates in thalamus.

Low dimensional dynamics for working memory and time encoding

The paper analyzes neural activity in non-human primates during time delays to understand working memory and time encoding mechanisms, finding that time can be decoded with high precision and neural trajectories are low dimensional.

Engineering recurrent neural networks from task-relevant manifolds and dynamics

The paper develops a method to design recurrent neural networks with dynamics that solve specific tasks, demonstrating its application to a working memory task and exploring network flexibility and capacity.

Metamers of Bayesian computation

This study introduces a method to test whether humans use model-based Bayesian computations by assessing sensitivity to equivalent prior-cost pairs that require different internal models.

A neural circuit model for human sensorimotor timing

This paper develops a neural circuit model to explain how humans coordinate movements with expected and unexpected temporal events, showing it matches human behavior in various timing tasks.

Distinct spatiotemporal mechanisms underlie extra-classical receptive field modulation in macaque V1 microcircuits

The paper identifies three distinct spatiotemporal mechanisms of eCRF modulation in macaque V1 microcircuits and shows how they differ across layers and processing streams.

Bayesian computation through cortical latent dynamics

The paper shows how prior beliefs influence behavior by shaping cortical latent dynamics through neural activity in monkeys during a time interval reproduction task.

Entrainment and maintenance of an internal metronome in premotor cortex

This study investigates how the premotor cortex encodes and maintains rhythms and time perception in nonhuman primates during a visual metronome task.

A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise

The paper shows humans use a nonlinear updating algorithm for time interval estimation, leading to suboptimal performance under signal-dependent noise.

Flexible sensorimotor computations through rapid reconfiguration of cortical dynamics

The paper shows that sensorimotor computations in monkeys are controlled by dynamical system principles, using inputs and initial conditions to adjust behavior.