Greg M. Fleishman

The paper presents a challenge for 3D registration of expansion microscopy volumes, evaluates top methods, and highlights future directions for ExM registration.

This paper presents a cross-modal workflow linking in vivo neural activity to molecular cell types using spatial transcriptomics, achieving accurate alignment across thousands of neurons in the mouse dorsal hippocampus.

The paper presents a spatial omics framework combining protein and RNA imaging with machine learning to classify brain cell types and discover structural features at tissue scale.

The paper develops WARP, a platform integrating neuronal activity and gene expression data in zebrafish brains, revealing functional roles of molecularly defined cell populations and their activity correlations.

The paper shows that astrocyte activity drives brainwide changes in sensory, integrative, and motor computations during a passive state in zebrafish.

SpotDMix improves mRNA spot assignment to cells in spatial transcriptomics by using a mixture model and EM algorithm, outperforming simple methods in accuracy and exclusivity.

The paper shows that the L2/3 continuum in the mouse visual cortex develops through two phases: a genetically programmed initial phase and a visually experience-driven second phase.

The paper develops an all-optical system to study whole-brain neuronal dynamics during gut interoception in zebrafish, revealing how nutrient delivery and sensory stimuli are encoded across brain regions.

This paper introduces cycleHCR technology for high-resolution spatial transcriptomics and protein imaging in thick tissues, demonstrating its application in mouse embryos and brain slices.

This study maps cell types and axon projections in the central nucleus of the amygdala using single-cell RNA-sequencing and spatial techniques, revealing distinct molecular and connectivity patterns.

The paper introduces EASI-FISH, a method for spatial gene expression profiling in thick brain sections, and applies it to discover novel subregions in the lateral hypothalamus.

The paper introduces a statistical technique to count distinct multiple sclerosis lesions from MRI data, showing it correlates with gold-standard counts and provides disease-related insights.