Jennifer A. Guidera

This paper introduces Generative Manifold Networks (GMNs) for modeling complex system dynamics, demonstrating their ability to predict and simulate chaotic and neural dynamics with explainability.

This study shows that meta-learning in rats involves changes in prefrontal cortical dynamics that enable rule-based reward learning.

This study shows that disrupting theta-timescale spiking during locomotion impairs learning but does not affect hippocampal replay during immobility in rats.

The paper shows that rat hippocampus generates flexible representations of alternative spatial locations during navigation, modulated by changing cognitive demands.

Spyglass provides a reproducible and shareable framework for neuroscience research, enabling data reuse and analysis across labs using standardized formats and pipelines.

The paper shows that while dmPFC and OFC encode similar task elements, their neural coding reliability differs, supporting distinct cognitive functions.

The paper investigates the synchronization between hippocampal spatial representations and limb movement rhythms in rats, finding coordinated timing between plant times and hippocampal spatial encoding.