A01Predictive coding on auditory processing: spatio-temporal structure of signal flow in whole-cortical electrocorticograms

 We are aiming to investigate the spatiotemporal structure of signal flow in the whole cortical electrocorticograms (ECoGs) related to the predictive coding on auditory processing.

 Our brain processes the incoming sensory inputs incessantly, and make predictions and generalizations of the environments to adapt our behavior. This process is often referred to as “predictive coding”. Variety of mathematical models of the predictive coding of the brain have been proposed already, and some of them are even thought that they were to reflect the layered structure of cortices and the cell types of neurons. Nowadays, these models have become basis of the deep learning models in terms of the machine learning. This deep learning theory is now considered to be one of the most powerful tools with the analysis of big data.

 However, even though we now have good mathematical models, there is a lot to be found out about what really happening in our brain.  Especially, with whole-brain level, we compared with other recording techniques. Through this research, we believe that we can examine the dynamical process of the predictive cording with the whole-cortical level and provide useful information to approve the algorithms of the deep learning.