[Eeglablist] How many electrodes tolerated for interpolation?

[장진원]

Dear Prof. Makeig,

I appreciate your suggestion. Is source-level EEG analysis more reliable
than scalp-level analysis? I wonder whether source-level EEG analysis (such
as dipole fitting) achieves high test-retest reliability and replicability
over different datasets, especially in clinical populations (depression vs
healthy controls, as an example)? I am not sure whether source-level
analysis is applicable in clinical research.

Best Regards,
Jinwon Chang

2025년 11월 18일 (화) 오후 1:19, Scott Makeig <smakeig at gmail.com>님이 작성:

> I would question the value of channel interpolation - except for making
> smooth pictures of particular scalp distributions. Individual
> electrode-signal-difference scalp channels are inherently vague measures
> that sum electrical activities generated in many unrelated parts of cortex.
> Scalp channel signals are not more deserving of attention than individual
> radio-frequency channels in an fMRI system ...
>
>  I do understand that (at least in the US) clinicians need to work in
> terms that insurance companies will reimburse. But cortical source-resolved
> EEG recording and analysis is technically quite feasible, as our work at
> SCCN over the last 30 years has abundantly demonstrated -- and allows more
> exact interpretation (and high statistical certainty) than scalp-level data
> interpretation.
>
> Scott Makeig
>
> On Tue, Nov 18, 2025 at 9:41 AM 장진원 via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
>
>> Thank for your kind reply. I understand it.
>>
>> Best Regards,
>> Jinwon
>>
>> On Mon, Nov 17, 2025 at 7:23 PM fernandez luis via eeglablist <
>> eeglablist at sccn.ucsd.edu> wrote:
>>
>> > > Hi Jinwon,
>> > >
>> > > Accurate EEG channel interpolation is methodologically feasible
>> across a
>> > broad spectrum of montage densities, including low-density
>> configurations
>> > such as 19- and 32-channel systems, intermediate-density arrays such as
>> 64
>> > channels, and high-density systems such as 128 channels. Importantly,
>> the
>> > methodological validity of interpolation does not primarily depend on
>> the
>> > absolute number of electrodes, but on the availability of non-artifacted
>> > neighboring electrodes with adequate spatial distribution surrounding
>> the
>> > channel to be reconstructed.
>> > >
>> > >
>> > > EEG interpolation is a spatial estimation procedure in which the
>> signal
>> > of an artifacted electrode is reconstructed using mathematically
>> weighted
>> > contributions from the nearest clean surrounding electrodes.
>> Accordingly,
>> > if the spatially adjacent electrodes are also artifacted, interpolation
>> > becomes unreliable or methodologically inappropriate, because the
>> > reconstruction process would be driven by distorted input data—violating
>> > key assumptions underlying spherical spline interpolation,
>> inverse-distance
>> > weighting, and other spatial estimation algorithms.
>> > >
>> > >
>> > > In low-density montages (e.g., 19 or 32 channels), interpolation
>> remains
>> > technically feasible; however, the reduced spatial sampling inherently
>> > limits the anatomical precision and spatial granularity of the
>> > reconstructed signal. Nevertheless, interpolation in these systems can
>> > yield clinically acceptable results as long as the electrodes used as
>> > sources for reconstruction are clean, stable, and sufficiently
>> distributed
>> > around the artifacted location.
>> > >
>> > >
>> > > Intermediate-density systems such as 64-channel EEG offer improved
>> > spatial resolution that allows more accurate reconstruction of missing
>> > channels due to enhanced scalp coverage. High-density montages,
>> > particularly 128-channel EEG systems, provide dense and homogeneous
>> spatial
>> > sampling, minimizing interpolation error and generating reconstructions
>> > that are more physiologically plausible and quantitatively reliable.
>> This
>> > level of spatial resolution is advantageous for applications requiring
>> > high-fidelity scalp mapping, microstate analysis, connectivity
>> estimation,
>> > and source localization.
>> > >
>> > >
>> > > Despite differences in resolution across montage densities, a
>> > fundamental methodological requirement remains invariant: interpolation
>> > must be performed exclusively using clean, non-artifacted surrounding
>> > electrodes. Reconstruction based on artifacted neighbors compromises the
>> > physiological validity of the estimated signal and undermines the
>> > mathematical assumptions intrinsic to spatial interpolation algorithms.
>> > >
>> > >
>> > > Technical Comparison: Conventional vs. High-Density EEG Interpolation
>> > >
>> > >
>> > > 1. Interpolation in conventional EEG (19–32 channels)
>> > >
>> > >
>> > > Low-density EEG systems rely on sparse spatial sampling, which imposes
>> > several methodological constraints:
>> > >
>> > >
>> > > • Wide inter-electrode spacing
>> > >
>> > > • Higher vulnerability to local contamination
>> > >
>> > > • Reduced capacity to capture rapid spatial changes
>> > >
>> > > • Acceptable but limited reliability
>> > >
>> > >
>> > > 2. Interpolation in high-density EEG (64–128 channels)
>> > >
>> > >
>> > > High-density EEG (HD-EEG) significantly enhances the reliability of
>> > interpolation due to:
>> > >
>> > >
>> > > • Dense and homogeneous spatial sampling
>> > >
>> > > • Robustness to isolated corrupted channels
>> > >
>> > > • Improved modeling of spatial gradients
>> > >
>> > > • Near-physiological reconstruction in 128-channel systems
>> > >
>> > > Best
>> > > Luis Fernandez, MSc
>> > > Clinical Neuropsychologist
>> > >
>> >
>> > > El 17 nov 2025, a las 20:41, 장진원 via eeglablist <
>> > eeglablist at sccn.ucsd.edu> escribió:
>> > >
>> > > Hi all,
>> > >
>> > > I'm a clinical psychiatrist, so I am not really familiar with
>> engineering
>> > > concept of interpolation. I believe in high-density setting (128
>> channel)
>> > > interpolation of a few channels are acceptable, but what if more than
>> 10
>> > > bad channels in 64 channel setting? Is it tolerable or detrimental for
>> > > maintenance of true signal?
>> > >
>> > > Best regards,
>> > > Jinwon Chang
>> > > _______________________________________________
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>
>
> --
> Scott Makeig, Research Scientist and Director, Swartz Center for
> Computational Neuroscience, Institute for Neural Computation, University of
> California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott 
>