Fahimeh Baftizadeh

The paper integrates transcriptomic, morphological, and electrophysiological data to define neuron types in mouse visual cortex and predict their projection targets.

MMIDAS jointly infers discrete cell types and continuous type-specific variability in single-cell datasets, improving reproducibility and robustness in cell type identification.

The paper investigates how electric fields affect different cortical neuron classes, finding frequency-dependent entrainment and class-specific responses in rodent and human neurons.

This study defines a comprehensive transcriptomic cell type taxonomy of the adult mouse isocortex and hippocampal formation using single-cell RNA-sequencing.

The paper develops coupled autoencoders to identify cortical neurons across modalities and finds consistent cell types in transcriptomic and electrophysiological data.

The paper characterizes transcriptomic and physiological properties of GABAergic cortical neurons in mice, identifying 20 interneuron met-types with consistent features across modalities.