Alexander Fleischmann

SCIGMA integrates spatial multi-omics data across modalities and platforms using a deep learning framework with uncertainty-aware contrastive learning, outperforming existing methods in domain detection and modality preservation.

The paper investigates how odor information is routed through feedforward and feedback pathways in the mouse olfactory cortex, finding distinct temporal encoding and plasticity in neurons projecting to different targets.

The paper shows that olfactory receptor expression in the nose follows a spatial code controlled by a retinoic acid gradient, aligning epithelial and brain maps.

The paper shows that odor and spatial information is differentially encoded in the piriform cortex and lateral entorhinal cortex of mice during odor navigation tasks.

This paper corrects optical aberrations in GRIN lens-based microendoscopes to improve imaging performance in deep brain regions.

This study identifies molecular signatures of ancestral cell types in mammalian olfactory cortex neurons by comparing transcriptomes across species and cortical layers.

The paper uses 3D spatial transcriptomics to map the molecular organization of the mouse olfactory bulb, revealing symmetric glomeruli and asymmetric deeper layer cells.

The paper shows that stochastic coding in odor representations improves discrimination in both flies and mice by leveraging variability in inhibitory circuits.

The paper shows that opposing epigenetic forces in olfactory progenitors spatially restrict stochastic OR choice through transcription and silencing influenced by NFIA, B, and X gradients.

The paper identifies molecular markers and gene regulatory mechanisms for projection neuron subtypes in the mouse olfactory bulb using single nucleus and bulk RNA sequencing.

This study identifies odor-specific neuronal ensembles in the mouse piriform cortex as necessary and sufficient for odor fear memory recall.