Carlos D. Brody

The paper shows that neural manifolds in the medial prefrontal cortex and hippocampus represent task variables as smooth gradients in low-dimensional space, with time-aligned geometry across brain areas.

This study shows that hippocampal engrams can configure prefrontal cortex representations to guide flexible decision-making in mice during context-dependent tasks.

The paper investigates how cortical connectivity changes during different phases of a decision-making task in mice, finding phase-specific modulation of causal connectivity.

The paper develops two neural circuit models for evidence accumulation through sequential neuronal activity and tests them against neural recordings from four brain regions during a decision-making task.

This study shows that rats' anterodorsal striatum and prefrontal cortex work together in a recurrent circuit for evidence accumulation, with bidirectional communication and robustness to perturbations.

The paper shows that working memory tasks involve a shared low-dimensional neural structure with more disjoint firing fields compared to simpler tasks, supporting cognitive processes.

FixGrower is a standardized protocol for training center-port fixation in rodents, reducing training time by 61% and lowering violation rates across species and task difficulty.

The paper presents a multi-region brain model to study how hippocampal circuits contribute to spatial decision-making, finding that a specific architecture optimizes learning and matches experimental data.

The paper tests whether rats use an integration strategy or degenerate strategies in a perceptual decision-making task and finds they predominantly use integration.

This study investigates decision-making phases in the brain using simultaneous recordings, supporting a single accumulator model and revealing abrupt covert commitment transitions.

The paper develops a framework to model neural and behavioral data together, revealing distinct evidence accumulation dynamics in three rat brain regions.

This study develops a process model to explain how rats adjust waiting times based on confidence and environmental factors, finding their behavior aligns with optimal strategies when travel times are considered.

The paper introduces a magnetic voluntary head-fixation system for longitudinal imaging of hippocampal neurons in transgenic rats.

The paper introduces a dynamic model to analyze strategy shifts in reward learning, showing a progression from model-based exploration to exploitation and reduced engagement in rats.

The paper introduces a cell-type dynamical systems model to better capture neural dynamics by considering distinct cell classes, showing improved accuracy and biological interpretability in decoding behavior and simulating perturbations.

This study validates chronic functional ultrasound imaging in freely moving rodents during cognitive tasks, showing stable recordings and nonlinear relationships between brain dynamics and task difficulty.

The paper identifies transitions in neural dynamics and modes during perceptual decision-making in rats, linking these transitions to decision commitment.

This paper develops a theoretical framework explaining individual variability in decision-making by analyzing neural and behavioral data from rats performing a context-dependent task.

This paper introduces a probabilistic model to analyze multi-region neural dynamics and communication, showing it outperforms existing models on mouse neural datasets.

This study investigates whether value representations in the rodent orbitofrontal cortex drive choice or support learning, finding that they instead signal expected reward information to a learning process elsewhere in the brain.

The paper investigates how different cortical areas contribute to sensory evidence accumulation by manipulating their activity and observing changes in decision-making.

The paper evaluates a correction method for slow drifts in decision criterion, showing it fails for common updating strategies and proposes a model-based approach to better disambiguate drifts from systematic updates.

The paper investigates how neural populations encode complex task information efficiently and sequentially in mice, finding that task variables are represented by uncorrelated neural modes and that encoding is multiplexed with sequential dynamics.

The paper identifies subpopulations of lOFC neurons that encode reward history and choice during decision-making in rats.

This paper introduces emergent property inference (EPI), a method using deep learning to solve inverse problems in theoretical neuroscience by learning parameter distributions consistent with computational properties.

This study shows that the superior colliculus (SC) plays a key role in non-spatial cognitive processes in rats, challenging the view that cognition relies primarily on prefrontal cortex.

This study investigates how rats represent provisional decisions in dynamic environments, finding that Frontal Orienting Fields (FOF) encode evidence with temporal gain modulation and rapidly update during changes of mind.

This paper introduces a method to analyze time-varying decision-making strategies in animals and applies it to data from mice, rats, and humans.

This paper demonstrates a method for long-term, multi-probe Neuropixels recordings in freely moving rats over multiple months, showing high yield and probe reusability.

The paper investigates how mice accumulate visual evidence during decision-making and finds that neural responses show amplitude modulations and deviations from Weber's Law, suggesting a feedback-based accumulation mechanism.