Kelsey D. Montgomery

This study maps the spatiomolecular organization of the human habenula using multi-omic approaches, identifying molecular signatures and spatial domains linked to psychiatric disorders.

This study creates a spatiomolecular atlas of the human nucleus accumbens using spatial transcriptomics and single-nucleus RNA sequencing, revealing spatial gradients and conserved features across species.

The paper creates a single-cell atlas of sex-differentially expressed genes in human hypothalamus regions, revealing molecular sex differences and their links to neurodevelopmental disorders.

spaTransfer transfers cell type or spatial domain labels between single-cell and spatial transcriptomics datasets using non-negative matrix factorization and a multinomial model.

The paper performs transcriptomic analysis of the human habenula and identifies molecular changes associated with schizophrenia risk and illness state.

The paper analyzes the transcriptomic landscape of the human locus coeruleus in relation to Alzheimer's disease risk factors and neuromelanin content using spatially-resolved transcriptomics.

The paper benchmarks cellular deconvolution methods using a multi-assay dataset from human prefrontal cortex, finding Bisque and hspe to be the most accurate.

This study identifies Reelin as a marker of cocaine-activated neuronal ensembles in the rat nucleus accumbens and shows its role in cocaine reward and neuronal excitability.

The paper generates a molecular neuroanatomical map of the human prefrontal cortex using spatial transcriptomics and single nucleus RNA-sequencing, revealing novel spatial domains and cell-cell interactions linked to psychiatric disorders.

The paper introduces a data-driven method to identify Total RNA Expression Genes (TREGs) for estimating RNA abundance in heterogeneous cell types and identifies AKT3 as a top TREG in brain regions.

The paper characterizes the molecular landscape of the human locus coeruleus using spatially-resolved transcriptomics and single-nucleus RNA-sequencing, providing a publicly accessible resource.

The paper uses snRNA-seq to analyze five human brain regions, identifies novel neuronal subpopulations, and links them to psychiatric and substance use risks.