Although morphology is a common and intuitive description of neurons, it reflects and serves the more fundamental purpose of achieving proper connectivity. Thus morphological variability likely belies the co-variation of pre- and post-synaptic neurites that preserves connectivity patterns (Seung and Sumbul, 2014). Indeed, morphological types can be reliably identified from dense connectomes by computational algorithms (Jonas and Kording, 2015). Beyond anatomical connectivity, the physiological operation of a neuron type transforms information contents embedded in its synaptic inputs (e.g. transmitter and modulator types, strength, spatiotemporal dynamics) to appropriate outputs (Kepecs and Fishell, 2014), which are often characterized by cell intrinsic style of neurochemical release (e.g. vesicle contents and release speed, dynamics, plasticity). Although highly valuable, most electrophysiological measurements at cell soma regions, often in artificial conditions, provide a limited window into the elaborate subcellular biophysical, signaling and metabolic processes. Our comprehensive transcription overview of the synaptic, intrinsic and release machineries reveals strikingly coherent molecular ensemble properties congruent with well characterized physiological, biophysical and release properties of PCPs. They further predict multiple novel physiological features that can be experimentally verified. Thus transcriptional
