AUTHOR=Karittevlis Christodoulos , Papadopoulos Michail , Lima Vinicius , Orphanides Gregoris A. , Tiwari Shubham , Antonakakis Marios , Papadopoulou Lesta Vicky , Ioannides Andreas A. 

TITLE=First activity and interactions in thalamus and cortex using raw single-trial EEG and MEG elicited by somatosensory stimulation

JOURNAL=Frontiers in Systems Neuroscience

VOLUME=Volume 17 - 2023

YEAR=2024

URL=https://www.frontiersin.org/journals/systems-neuroscience/articles/10.3389/fnsys.2023.1305022

DOI=10.3389/fnsys.2023.1305022

ISSN=1662-5137

ABSTRACT=One of the primary motivations for studying the human brain is to comprehend how external sensory input is processed and ultimately perceived by the brain. A good understanding of these processes can promote the identification of biomarkers for the diagnosis of various neurological disorders; it can also provide ways of evaluating therapeutic techniques. In this work, we seek the minimal requirements for identifying key stages of activity in the brain elicited by median nerve stimulation. We show that early responses in the thalamus and cortex can be identified using a priori knowledge, simple linear spatial filtering and clustering techniques applied on the single-trial (ST) raw Electroencephalography and Magnetoencephalography signals. Our method identifies two key aspects of the evoked response. Firstly, the early onset of activity in the thalamus and the somatosensory cortex, known as the P14 and P20 in EEG and the second M20 for MEG. Secondly, good estimates are obtained for the early timecourse of activity from these two areas. The spatial filter is defined first from the average EEG and MEG signals and then refined using consistency across ST. The refined spatial filter is then applied to extract the timecourses of each ST in each targeted generator. These ST timecourses are studied through clustering to quantify the ST variability. The nature of ST connectivity between thalamic and cortical generators is then studied within each identified cluster. The results confirm the existence of variability in ST brain activations and reveal distinct patterns of connectivity in different clusters.There are three important applications of our methodology. Firstly, it is demonstrated that we can 1 Karittevlis et al.extract new insights into stimulus processing without the use of computationally costly source reconstruction techniques which require detailed modeling of the brain, with each model making specific assumptions about the nature of the generators. Secondly, our methodology, thanks to its simplicity and minimal computational requirements has the potential for real-time applications such as in neurofeedback systems and brain-computer interfaces. Finally the conclusions reached using only the raw data properties can then be used in a detailed tomographic analysis targeted to test specific hypotheses.