Toward a Better Understanding of the Cortical Function: Entrained Periodical Modular Language Decoding

Abstract

The use of speech for organizing collective activity is the hallmark of our species. For such a purpose, the speaker’s brain activity have to modulate that of the listener, what requires the sound the speaker produces to synchronize listener's brain activity. Recent results reported in the literature show that speech production and decoding result from a Cortical Oscillatory Modular Processing (COMP). In this context, speech comprehension depends on how speaker’s COMPs produce a modular organized speech to entrain listener’s COMP speech decoding. The purpose of the present paper is to investigate this process by analyzing the EEG recorded during a text listening. The sentences of this text were composed by 5 clauses of 2 seconds duration each. Event Related Activity (ERA) technique, Polynomial Regression, Spectral and LORETA analyses were used to identify the different COMP components, to study the cortical oscillatory activity supporting this processing and to try to localize the sources of these oscillations. ERA and Polynomial analyses show that clause decoding correlates to identified COMPs that are composed by several different cyclic components. Spectral and LORETA analyses revealed that three components are generated by different time locking oscillatory activities recorded at many different and widely distributed cortical areas. A model to reconstruct the EEG from these identified cyclic components is proposed and shown to statistically mimic the recorded cortical activity. Based on all these results, a hypothesis for linking speech decoding and cyclic COMP activity is presented and discussed. This is one of three paper exploring this idea.