• pcdh19-epilepsy
• electrophysiology
• sleep
• slow wave activity
• single unit analysis

Pcdh19-epilepsy is a neurodevelopmental disease characterised by the mutation of the protocadherin 19 gene, encoding a cell-adhesion protein supposed to mediate synaptic connection. Genetic mosaicism underlies the pathological phenotype as, according to the cellular interference hypothesis, the co-existence of two distinct neuronal populations is believed to hinder cell-cell communication and network wiring. Slow wave activity resulted to be disrupted in a focal mouse model of Pcdh19-epilpesy. Single unit analysis is an ideal tool to extract single neurons’ behaviour from population recordings. Since the major contribution to local field potential is given by slow synaptic events and the brain impedance dampens down the high frequencies, detection of spikes is not immediate and is confined to the few neurons surrounding the electrode. Here, we provide a customizable algorithm to detect and classify single units in three steps: detection, feature extraction, and clustering. By applying single unit analysis on local field potential recordings from a PCDH19 mosaic mouse model, we expect to describe two neuronal activity patterns that could explain the disruption of slow wave activity at the level of the network.