Lisa Marie Giocomo

This paper develops inverse reinforcement learning to infer evolving objectives from animal behavior and shows it can identify time-varying objectives in mice.

This study shows that subicular neurons encode predictive spatial representations by integrating behavioral biases into the successor representation framework, explaining their diverse activity patterns.

The paper shows that precise CA1 input topography shapes subicular spatial coding and network dynamics, while preserving single-cell tuning and impairing boundary vector coding and long-term stability.

The paper introduces a platform for studying navigation in rats that combines free movement with controlled stimuli and rewards, revealing spatial coding in the medial entorhinal cortex.

This study shows that postsynaptic membrane fusion via Stx3 is essential for specific hippocampal computations like novelty processing and memory consolidation, but not for presynaptic representations.

The paper uses Gaussian Process inference to analyze 4D tuning curves of grid cells in rats, revealing non-separability of position and velocity tuning.

The paper investigates how environmental novelty affects cortical plasticity during navigation using optogenetic stimulation and calcium imaging in mice.

The paper introduces a method to monitor and control neural activity at cellular resolution in mice, discovering new cell types with unique functional properties.

This study examines spatial coding dysfunction and network instability in aged medial entorhinal cortex using in vivo electrophysiology and gene expression analysis in mice.

The paper shows that hippocampal sequences adapt to reward locations, with reward-relative cells spanning task structure and increasing with experience.

The paper shows that grid cells in the entorhinal cortex form stable maps of novel environments quickly and with minimal distortion, enabling flexible navigation through downstream plasticity.

The paper shows that MEC neurons represent remote task-relevant locations during immobility, independent of CA1 activity.

The paper improves positively tuned voltage indicators by enhancing their kinetics and contrast for better spike detection.

This study investigates how parahippocampal neurons encode task-relevant information during goal-directed navigation in dynamic environments, finding that neural activity mismatches correlate with task performance.

This study investigates how ketamine affects spatial coding in the entorhinal cortex and hippocampus, finding acute disruption and long-term reorganization of spatial representations.

This paper introduces positively tuned GEVIs that enhance spike detection in vivo with standard imaging systems, offering higher temporal resolution than calcium indicators.

This study uses recurrent neural networks to model how navigational circuits can maintain local computations while responding to global context changes, showing activity patterns similar to entorhinal cortex remapping.

The paper identifies separate neural populations in the subiculum that encode concave and convex environmental corners.

The paper reassesses claims about grid cell emergence in path-integrator circuits, finding consistency with prior theory.

This paper shows that hexagonal grid cell patterns emerge in neural networks trained for path integration and develops methods to analyze these networks for mechanistic insights.

This study uses a novel approach to block long-term potentiation and finds that it selectively enhances salience coding in hippocampal neurons without affecting spatial memory.

This study uses task-driven neural networks to show that heterogeneous MEC cells are functionally significant and that reward-modulated models better capture MEC response profiles than traditional models.

This study shows how drug-context associations are encoded in hippocampal neurons and how ketamine blocks these changes and drug-seeking behavior.

The paper shows that the medial entorhinal cortex can spontaneously switch between spatial maps in an unchanging environment, with population-level features preserved despite individual neuron changes.

This paper shows that hippocampal place cell remapping is driven by prior beliefs about context frequency and represents an optimal estimate of location in a multi-dimensional stimulus space.

The paper shows that medial entorhinal cortex uses Kalman filtering to integrate path integration and landmarks, while visual cortex codes position retrospectively and retrosplenial cortex is intermediate.

This study shows that entorhinal velocity signals rescale with environmental geometry and head direction cells reorganize in response to environmental changes.

The paper develops a neural attractor model that explains how animals construct spatial maps using self-motion and landmark cues, showing emergent elasticity in grid cell firing patterns.

NeuroRoots is a bio-inspired, multi-channel implant that enables long-term stable neural recording in rats, maintaining signal quality for at least 7 weeks.