Abstract
Patch-seq enables the integration of electrophysiological recordings, single-cell RNA sequencing (scRNA-seq), and morphological reconstruction within the same neuron, but establishing mechanistic links between transcriptomic and physiological properties remains a major challenge. Bernaerts et al.(1) developed a new statistical-biophysical model based on biophysical simulations and modern machine learning techniques. They applied this model to gene expression and established a quantitative link between gene expression and electrophysiological activity patterns. This work is an important advance toward closing the gap between gene expression and neuronal physiology.