Assessing spontaneous sensory neuron activity using in vivo calcium imaging
Heightened spontaneous activity in sensory neurons is often reported in individuals living with chronic pain. It is possible to study this activity in rodents using electrophysiology, but these experiments require great skill and can be prone to bias. Here, we have examined whether in vivo calcium imaging with GCaMP6s can be used as an alternative approach. We show that spontaneously active calcium transients can be visualised in the fourth lumbar dorsal root ganglion (L4 DRG) via in vivo imaging in a mouse model of pain. Application of lidocaine to the nerve, between the inflamed site and the DRG, silenced spontaneous firing and revealed the true baseline level of calcium for spontaneously active neurons. We used this data to train a machine leaning algorithm to predict when a neuron is spontaneously active. We show that our algorithm is accurate in two different models of pain: intraplantar Complete Freunds Adjuvant and antigen-induced arthritis, with accuracies of 90.0% +/-1.2 and 85.9 % +/-2.1, respectively, assessed against visual inspection by an experienced observer. The algorithm can also detect neuronal activity in imaging experiments generated in a different lab using a different microscope configuration (Accuracy = 94.0 % +/2.2). We provide a Google Colaboratory Notebook to allow anyone easy access to this novel tool, for assessment of peripheral neuron activity in their own calcium imaging setups.