Since its discovery, the human electroencephalogram (EEG) has proven itself an indispensable tool for brain research. Despite this success story, there is a fundamental technical issue that has yet to be resolved: the selection of the correct EEG reference. Ideally one would like to measure neural activity restricted to certain brain regions. Since EEG amplifiers measure potential difference between the activities recorded by two electrodes, in addition to the active electrode, one must employ a reference electrode which should ideally be at zero. In theory, this might be achieved by placing the reference at a point infinitely far away. Yet the “infinite reference”, in practice, is an antenna for ambient noise which would preempt brain measurements—for example cephalic references that minimize unwanted signal pickup.
Examples of such references are the unilateral-mastoid, ear, linked mastoids or ears, vertex, the tip of the nose, neck ring, etc. Unfortunately all such references are doomed to fail since there is no point on the scalp or body surface where the potential is actually zero or a constant. This has serious consequences since the non-neutral reference may itself reflect physiological dynamic processes that will be inevitably embedded into all EEG recordings. Without solving the reference issue we are looking at brain activity, as it were, “through a glass, darkly”.
Recent attempts to make this “glass” more transparent have been based on mathematically constructing a reference based on physical principles and subtracting it from all EEG recordings. The best known example is the average reference (AVE). Originally proposed with an analog implementation, it was heuristically espoused by Lehman (1971) and later theoretically justified since the average of a dipole potential over a spherical surface is zero. Consequently, the AVE might be a good choice when a dense and whole brain coverage of an EEG montage is available, which explains why it is widely accepted.
Nevertheless, AVE has poor performance with a lower number of electrodes. An alternative is the Reference Electrode Standardization Technique (REST) which used a re-referencing method to reconstruct the desired zero or neutral reference, based on the fact that the underlying neural sources are the same no matter what a reference is actually adopted.
This Research Topic will encourage the objective comparison of the effect that various EEG references may have on inference about brain function and disorders—with respect to both physical and computational issues. The crucial point is to determine the reference that best identifies neural activity and therefore be the basis of improved estimates of various linear and non-linear EEG features. These include spectra, amplitude, latency, coherence/correlation, network, symmetry/asymmetry, fractal dimension, complexity, covariance and related statistical tests. If a single reference can be finally recognized universally as the optimal one for general use, we will have indeed rendered the “glass less opaque” and thus “know in part” more about brain function. To contribute to this end, we welcome our colleagues to submit paper with theoretical work, simulation studies, practical experimental data analysis as well as critical reviews.
Since its discovery, the human electroencephalogram (EEG) has proven itself an indispensable tool for brain research. Despite this success story, there is a fundamental technical issue that has yet to be resolved: the selection of the correct EEG reference. Ideally one would like to measure neural activity restricted to certain brain regions. Since EEG amplifiers measure potential difference between the activities recorded by two electrodes, in addition to the active electrode, one must employ a reference electrode which should ideally be at zero. In theory, this might be achieved by placing the reference at a point infinitely far away. Yet the “infinite reference”, in practice, is an antenna for ambient noise which would preempt brain measurements—for example cephalic references that minimize unwanted signal pickup.
Examples of such references are the unilateral-mastoid, ear, linked mastoids or ears, vertex, the tip of the nose, neck ring, etc. Unfortunately all such references are doomed to fail since there is no point on the scalp or body surface where the potential is actually zero or a constant. This has serious consequences since the non-neutral reference may itself reflect physiological dynamic processes that will be inevitably embedded into all EEG recordings. Without solving the reference issue we are looking at brain activity, as it were, “through a glass, darkly”.
Recent attempts to make this “glass” more transparent have been based on mathematically constructing a reference based on physical principles and subtracting it from all EEG recordings. The best known example is the average reference (AVE). Originally proposed with an analog implementation, it was heuristically espoused by Lehman (1971) and later theoretically justified since the average of a dipole potential over a spherical surface is zero. Consequently, the AVE might be a good choice when a dense and whole brain coverage of an EEG montage is available, which explains why it is widely accepted.
Nevertheless, AVE has poor performance with a lower number of electrodes. An alternative is the Reference Electrode Standardization Technique (REST) which used a re-referencing method to reconstruct the desired zero or neutral reference, based on the fact that the underlying neural sources are the same no matter what a reference is actually adopted.
This Research Topic will encourage the objective comparison of the effect that various EEG references may have on inference about brain function and disorders—with respect to both physical and computational issues. The crucial point is to determine the reference that best identifies neural activity and therefore be the basis of improved estimates of various linear and non-linear EEG features. These include spectra, amplitude, latency, coherence/correlation, network, symmetry/asymmetry, fractal dimension, complexity, covariance and related statistical tests. If a single reference can be finally recognized universally as the optimal one for general use, we will have indeed rendered the “glass less opaque” and thus “know in part” more about brain function. To contribute to this end, we welcome our colleagues to submit paper with theoretical work, simulation studies, practical experimental data analysis as well as critical reviews.