1. Temporal resolution

Of course, we would see higher frequencies. But would these be informative? Aren't the frequencies measured today near the border to noise?

2. Spatial resolution

I guess LFP measurement goes in this direction (closer to the sources of the signals being measured). But what would we learn by that? Finding small-scale regions (below Brodman area size) which behave phase-locked/synchronously?

3. fMRI

The same questions could be asked with respect to fMRI. But I guess, as long as temporal resolution is as poor as it is today (and which cannot be much better), we don't have to ask for spatial resolution, or do we?

  • $\begingroup$ Short answer: No. The limiting factor is not the resolution (it cannot get much better), is the fact that is a signal coming from billions of cells doing different things so by definition noisy and messy. Only when there is very high synchronicity we can get something out of it (e.g. sleep phases). $\endgroup$
    – have fun
    Aug 30, 2017 at 14:06
  • $\begingroup$ I assume you answer to question 3. Billions of cells? $\endgroup$ Aug 30, 2017 at 14:27
  • $\begingroup$ No, for fMRT the problem at the moment is "poor" temporal and spatial resolution. If we had faster imaging we could have better spatial resolution. However remember that fMRT it's only a proxy for neurons activity...hence it measure slightly different things than electrophysiology and will never have its resolution. $\endgroup$
    – have fun
    Aug 30, 2017 at 14:48
  • $\begingroup$ I've read that MRT measures process that take up to a few seconds to occur (neurovascular). What benefits could a higher temporal resolution have? $\endgroup$ Aug 30, 2017 at 16:01

1 Answer 1


The temporal resolution of EEG is already considered to be very good. The problem is spatial resolution. Even the loss of very high frequency activity, like individual spikes, is really a problem of spatial rather than temporal resolution: the spiking cells are too far away, so it is only possible to detect them if they are very synchronized (in which case they still show up as lower frequency signals).

Because EEG recordings are so far from the sources they are recording from, and because even structures deep in the brain can contribute to surface potentials,the signals end up as complex averages over a large space. There is an entire field called EEG source modeling that tries to use signal processing methods to improve this spatial resolution.

However, you don't really have to ask this as a hypothetical question, since we already have methods that have better resolution than EEG. Electrocorticograms (ECoG) are the most similar, and most applicable to human studies. ECoG arrays are very similar to EEG, but they are placed directly on the dura, under the skull. They increase spatial resolution because they cut down distances dramatically by not having to record through the skull.

As you mention in your question, local field potentials (LFP) get even closer to where the measured currents are occurring, by recording from within the brain itself. The spatial resolution of LFPs themselves can also be improved by recording from multiple electrodes and computing a current source density. This also helps mitigate the effects of volume conduction.

fMRI is a completely separate issue. Often, EEG and fMRI results can act in conjunction, using EEG to determine time and fMRI to determine space (note that although there are limits to the spatial resolution of fMRI, for a human subject it is dramatically more spatially precise than EEG, especially for any structures not at the very surface of the brain, including any of the sulci of neocortex). fMRI spatial resolution can be improved by using stronger magnets, but eventually there are technological (and expense) limitations, but as you say the temporal resolution is fixed, and even the spatial resolution has some practical limitations.

To generally answer your title question: if the spatial resolution of EEG is improved (practically, this means either source modeling or using ECoG or LFP), one is better able to identify the brain structures that are producing the signals observed in the EEG, and able to be more confident that the signals observed are "real" rather than an artifact of filtering over space. For example, a higher-frequency traveling wave could appear as a lower-frequency signal on an EEG, or a localized, high-intensity event could appear like a generalized, low-intensity event; higher spatial resolution would allow you to distinguish between the two in both cases.

  • $\begingroup$ May I contact you directly by email? If so, please confirm, when you grabbed my mail address: [email protected] - so I can delete this comment as soon as possible. $\endgroup$ Sep 6, 2017 at 14:10
  • $\begingroup$ @HansStricker You can invite me to chat here if you'd like. $\endgroup$
    – Bryan Krause
    Sep 6, 2017 at 19:27

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