Ever since Hans Berger recorded the first electroencephalogram (EEG) in 1924, scientists
have struggled to understand which exact regions of the brain are causing the signal
on the scalp. This inverse problem has proved quite difficult to crack, despite decades
of research. Some researchers have used electrodes within the brain (electrocorticograms)
simultaneously with surface electrodes to try to understand the source. Others have
recorded functional magnetic resonance imaging (fMRI) blood oxygen level–dependent
(BOLD) signals with concurrent surface EEG. There have been other partial solutions
at finding the source of the surface signal, such as low-resolution electromagnetic
tomography (
1
). However, the problem is a tricky one. In the article in this issue, Keynan et al. (
2
) used a hybrid approach in which they estimate the source of an EEG signal for a
large database where they recorded EEGs within an MRI scanner for a group of individuals
and then used this to build a database to use on others, outside of the MRI scanner.
They coin a new term for this solution to the inverse problem, fMRI-inspired EEG (
3
). EEG purists will no doubt have numerous criticisms of this group-average approach.
The authors admit that the surface amygdala signal likely comes from multiple sources,
not just the amygdala. However, using this probabilistic anatomically inspired approach
is certainly easier and less expensive than having each person undergo an EEG-fMRI
session or using BOLD fMRI feedback within the scanner (
4
).To read this article in full you will need to make a payment
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References
- Extracranial localization of intracranial interictal epileptiform activity using LORETA (low resolution electromagnetic tomography).Electroencephalogr Clin Neurophysiol. 1997; 102: 414-422
- Limbic activity modulation guided by functional magnetic resonance imaging-inspired electroencephalography improves implicit emotion regulation.Biol Psychiatry. 2016; 80: 490-496
- One-class fMRI-inspired EEG model for self-regulation training.PLoS One. 2016; 11: e0154968
- Intermittent "real-time" fMRI feedback is superior to continuous presentation for a motor imagery task: A pilot study.J Neuroimaging. 2012; 22: 58-66
- Learned regulation of spatially localized brain activation using real-time fMRI.Neuroimage. 2004; 21: 436-443
- Individualized real-time fMRI neurofeedback to attenuate craving in nicotine-dependent smokers.J Psychiatry Neurosci. 2016; 41: 48-55
- Volitional reduction of anterior cingulate cortex activity produces decreased cue craving in smoking cessation: A preliminary real-time fMRI study.Addict Biol. 2013; 18: 739-748
Article info
Publication history
Accepted:
July 14,
2016
Received:
July 13,
2016
Identification
Copyright
© Society of Biological Psychiatry, 2016.
ScienceDirect
Access this article on ScienceDirectLinked Article
- Limbic Activity Modulation Guided by Functional Magnetic Resonance Imaging–Inspired Electroencephalography Improves Implicit Emotion RegulationBiological PsychiatryVol. 80Issue 6
- PreviewThe amygdala has a pivotal role in processing traumatic stress; hence, gaining control over its activity could facilitate adaptive mechanism and recovery. To date, amygdala volitional regulation could be obtained only via real-time functional magnetic resonance imaging (fMRI), a highly inaccessible procedure. The current article presents high-impact neurobehavioral implications of a novel imaging approach that enables bedside monitoring of amygdala activity using fMRI-inspired electroencephalography (EEG), hereafter termed amygdala-electrical fingerprint (amyg-EFP).
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