Inverse Algorithm from Sensor to Deep Areas (hippocampus, thalamus, amygdala)

Hi all,

I have one technical question and really appreciate it if anyone can give me some professional suggestions on that. In short, the question is: is there any reliable inverse algorithm to map the scalp EEG, fNIRS, or MEG, from the sensor level to deep brain areas, like, hippocampus, thalamus, and(or) amygdala?

I understand the volume conduction makes it very difficult to detect the deep brain potential from scalp EEG. And fNIRS can only measure the BOLD activities at the cortical area. But, is it 100% impossible to scratch something from the deep brain areas by non-invasive method?

Nothing's impossible, but some things are harder :wink:
It is a matter of sensitivity and signal-to-noise ratio. These latter can be boosted by specific aspects of the study design and some tailored signal extraction techniques.
There are some recent MEG studies that have reported meaningful effects from as deep as the brainstem or hippocampus and amygdala.


Hi, Dr. Sylvain, thanks for sharing the interesting papers. It is very helpful. So, I have two more questions here:

  1. how to map the MEG sensor data to the source level, is there any function in Brainstorm?
  2. is it possible to map the scalp EEG or fNIRs to deep areas (hippocampus, etc), instead of MEG? Since it is very hard to control the SNR of scalp EEG for deep-brain-mapping, how about mapping in resting-state?

Yes to all the above. Please follow the main Brainstorm tutorials and they will take you there.