Exploring Interarea Communication during a Birdsong Learning Task via Local Field Potential
Abstract
I had the opportunity to conduct an analysis of neuroelectrophysiological data recorded in songbirds. I applied my computing skills to create an exploratory GUI using Matlab. The goal was to observe local field potentials (LFPs) and spiking activity. I was able to prove that the dynamics of signals from two different brain areas responsible for the generation of song diversity tend to synchronize during sleep stages. I also applied a similar analysis on a bird performing a pitch-learning task to search for the presence of phase-lock LFP signals, which indicate signs of learning. This project allowed me to improve my skills in signal processing and big data analysis, as well as offering me a solid introduction to spiking activity and communication between populations of neurons.
Personal Outcome
Firstly, I was happy to identify within the dataset the well-known Slow sleep wave, a phenomenon I had heard about in numerous studies. Later on, I found myself captivated by the progression of these coherence waves through time.