Amanda J. Foust

Light-field deep learning enables high-throughput, scattering-mitigated calcium imaging

This paper introduces a deep learning method to improve calcium imaging by reducing scattering and increasing throughput in light-field microscopy.

Physics-based Deep Learning for Imaging Neuronal Activity via Two-photon and Light Field Microscopy

This paper develops a physics-driven deep learning method to reconstruct neuronal activity from light field microscopy images, outperforming existing methods in quality and speed.

Membrane voltage fluctuations in human breast cancer cells

This study characterizes membrane voltage fluctuations in human breast cancer and non-cancerous cells, identifying distinct dynamic patterns linked to cellular transformation.

Subcellular resolution 3D light field imaging with genetically encoded voltage indicators

This study demonstrates sub-cellular resolution 3D light field imaging of voltage signals in acute mouse brain slices using genetically encoded voltage indicators.

Dendrites enable a robust mechanism for neuronal stimulus selectivity

The paper demonstrates how dendritic non-linear processing enables stimulus selectivity in neurons, even when preferred stimulus input is not dominant, and shows increased robustness to synaptic and dendritic failures.

On the distribution and function of synaptic clusters

This paper investigates how synaptic clusters form and function in neurons, showing that specific rules govern their distribution and that changes in input statistics can reshape these clusters, with implications for both biological learning and artificial neural networks.