An automated method for clustering single sweep local field potentials recorded from rat barrel cortex

Since the very beginning of neuroscience, neuroscientists have put their efforts in deciphering the brain's information processing capabilities. At different times they have discovered different information processing pathways. Sensing capabilities in mammals has always been an interesting area. For the rodents, whisking is the natural way to sense the environment. Using the Local Field Potentials (LFPs) recorded from the barrel columns of the rat somatosensory cortex (S1) is one of the ways to extract information about the pathway during tactile information processing. Studies have shown that intra- and trans-columnar microcircuits in the barrel cortex segregate and integrate information during this pathway activation. During each experiment many single sweeps of signal are recorded as a result of underlying network activity and averaged to extract information from them. However, mostly these single sweeps are very different in their shapes and extracting the information provided by the shape is the most common way to decode the transmitted information about the network. In this work, we propose a method capable of classifying these single sweeps from an experiment based on their shapes. The shape specific information of the single sweeps provided by this method can be used in decoding the tactile information processing pathway with a higher precision.