Reconstructing subcortical and cortical somatosensory activity via the RAMUS inverse source analysis technique using median nerve SEP data
Atena Rezaei,
Joonas Lahtinen,
Frank Neugebauer,
Marios Antonakakis,
Maria Carla Piastra,
Alexandra Koulouri,
Carsten H. Wolters,
Sampsa Pursiainen
Affiliations
Atena Rezaei
Corresponding author.; Faculty of Information and Communication Sciences, Unit of Computing Sciences, Tampere University, P.O. Box 1001, Tampere 33014, Finland
Joonas Lahtinen
Faculty of Information and Communication Sciences, Unit of Computing Sciences, Tampere University, P.O. Box 1001, Tampere 33014, Finland
Frank Neugebauer
Faculty of Information and Communication Sciences, Unit of Computing Sciences, Tampere University, P.O. Box 1001, Tampere 33014, Finland; Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, Münster D-48149, Germany
Marios Antonakakis
Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, Münster D-48149, Germany; School of Electrical and Computer Engineering, Technical University of Crete, Akrotiri Campus Chania 73100, Crete, Greece
Maria Carla Piastra
Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, Nijmegen 6525 EN, the Netherlands
Alexandra Koulouri
Faculty of Information and Communication Sciences, Unit of Computing Sciences, Tampere University, P.O. Box 1001, Tampere 33014, Finland
Carsten H. Wolters
Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, Münster D-48149, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster D-48149, Germany
Sampsa Pursiainen
Faculty of Information and Communication Sciences, Unit of Computing Sciences, Tampere University, P.O. Box 1001, Tampere 33014, Finland
This study concerns reconstructing brain activity at various depths based on non-invasive EEG (electroencephalography) scalp measurements. We aimed at demonstrating the potential of the RAMUS (randomized multiresolution scanning) technique in localizing weakly distinguishable far-field sources in combination with coinciding cortical activity. As we have shown earlier theoretically and through simulations, RAMUS is a novel mathematical method that by employing the multigrid concept, allows marginalizing noise and depth bias effects and thus enables the recovery of both cortical and subcortical brain activity. To show this capability with experimental data, we examined the 14–30 ms post-stimulus somatosensory evoked potential (SEP) responses of human median nerve stimulation in three healthy adult subjects. We aim at reconstructing the different response components by evaluating a RAMUS-based estimate for the primary current density in the nervous tissue. We present source reconstructions obtained with RAMUS and compare them with the literature knowledge of the SEP components and the outcome of the unit-noise gain beamformer (UGNB) and standardized low-resolution brain electromagnetic tomography (sLORETA). We also analyzed the effect of the iterative alternating sequential technique, the optimization technique of RAMUS, compared to the classical minimum norm estimation (MNE) technique. Matching with our previous numerical studies, the current results suggest that RAMUS could have the potential to enhance the detection of simultaneous deep and cortical components and the distinction between the evoked sulcal and gyral activity.
