Cliff Slaughterbeck

The paper introduces Seq-o-Matic, an open-source automated in situ sequencer that reduces hands-on time and improves sequencing consistency across tissue sections.

The paper presents a database of spiking activity in the mouse visual system during an image change detection task, revealing task-specific coding patterns across brain regions.

The paper introduces MerQuaCo, an open-source tool to automatically detect and quantify imperfections in spatial transcriptomics data, improving quality assessment.

This paper creates a high-resolution transcriptomic and spatial cell type atlas of the whole adult mouse brain, revealing spatial organization and transcription factor codes for cell types.

The paper presents a synaptic physiology dataset and analysis platform to study cortical microcircuit structure and synaptic properties in mouse and human neocortex, revealing layer-dependent connectivity and subclass-specific dynamics.

The paper presents a dataset and analysis of spiking activity across multiple mouse visual areas, revealing that functional connectivity mirrors anatomical hierarchy.

The paper presents a large-scale dataset of neural activity in the mouse visual cortex and shows that responses to different stimuli are largely independent, suggesting multi-layer hierarchical computation.

The paper classifies neurons in mouse visual cortex into 17 electrophysiological and 35 morphological types using unsupervised methods and links them to transcriptomic types.

The paper quantifies biological variation in the sizes, shapes, and locations of 11 visual cortical areas in mice, finding substantial size variation across the population.