Format

Send to

Choose Destination
Proc Natl Acad Sci U S A. 2017 Nov 28;114(48):E10465-E10474. doi: 10.1073/pnas.1705414114. Epub 2017 Nov 14.

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG.

Author information

1
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129.
2
Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Cambridge, MA 02139.
3
Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore 138632, Singapore.
4
Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114.
5
Harvard Medical School, Boston, MA 02115.
6
Department of Neurology, Massachusetts General Hospital, Charlestown, MA 02129.
7
Department of Electrical & Computer Engineering, University of Maryland, College Park, MD 20742.
8
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129; patrickp@nmr.mgh.harvard.edu msh@nmr.mgh.harvard.edu.
9
Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo 02150, Finland.
10
The Swedish National Facility for Magnetoencephalography (NatMEG), Department of Clinical Neuroscience, Karolinska Institute, Stockholm 17177, Sweden.
11
Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114; patrickp@nmr.mgh.harvard.edu msh@nmr.mgh.harvard.edu.

Abstract

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain.

KEYWORDS:

EEG; MEG; source localization; sparsity; subcortical structures

PMID:
29138310
PMCID:
PMC5715738
DOI:
10.1073/pnas.1705414114
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for HighWire Icon for PubMed Central
Loading ...
Support Center