The revised brain symmetry index
Introduction
Symmetry is ubiquitous in nature and an important property in the evaluation of various clinical conditions. For example, in patients with one-sided complaints, the clinical examination is typically facilitated by an explicit comparison of the left and right side (line symmetry). In clinical neurophysiology, symmetry plays a significant role, as well. It is rather common to compare if significant differences of a measurand exist between the symptomatic and the asymptomatic side, e.g. in the estimation of motor or sensory nerve action potentials (Levin and Lüders, 2000). Line symmetry exists as well between the cerebral hemispheres. This holds not only for the gross anatomy, but also applies to particular properties of the human electroencephalogram (EEG). Although various EEG rhythms may show a modest physiological asymmetry (Niedermeyer and Lopes da Silva, 1999, Weber, 2005), the mean spectral characteristics of the left and right hemispheric EEG, as estimated during a particular time frame, are nearly symmetrical (van Putten et al., 2004, van Putten and Tavy, 2004, Niedermeyer and Lopes da Silva, 1999), notwithstanding various significant differences in functional lateralization.
Evaluation of left–right symmetry, therefore, is an important characteristic of the EEG, for instance in the decision for selective shunting during carotid endarterectomy. Several EEG features have been proposed, including changes in relative power or spectral edge frequency (Hanowell et al., 1992, Minicucci et al., 2000, Laman et al., 2001, Laman et al., 2005, Cursi et al., 2005). Recently, the brain symmetry index (BSI) was introduced as a measure to quantify the interhemispheric spectral symmetry of the EEG (van Putten et al., 2004). This feature was originally designed to assist in the visual interpretation of the EEG during carotid endarterectomies, but has found applications in monitoring stroke patients, and detection of focal seizure activity, as well (van Putten and Tavy, 2004, van Putten et al., 2005). An extension to this index included a measure to capture diffuse changes (which could be regarded as differences in time symmetry), effectively resulting in two features, the standard BSI (sBSI), quantifying interhemispheric asymmetry, and the temporal BSI (tBSI), quantifying diffuse changes (van Putten, 2006).
Recent insights and improvements in the algorithm, leaving the original concept unchanged, motivatedc us to report in more detail on various characteristics of these two indices. Using artificially generated EEG signals, we simulate various conditions as may occur during ischaemia, for instance in carotid surgery.
Section snippets
Quantifying left–right symmetry
The (standard) brain symmetry index (sBSI) quantifies the difference between the spectral characteristics of the left and right hemisphere. For each discrete time series Xch,t with t discrete time, t = 1, 2, … , N recorded from a bipolar derivation or channel ch = 1, 2, … , M, we write for the discrete Fourier transformwith K the number of discrete frequencies, ωi. This is the usual model for a process with a purely discrete spectrum (harmonic model) (Priestley, 1981).
The
Amplitude or power spectrum
In Fig. 1a we illustrate the difference in sensitivity between the sBSI as based on the ratio of the spectral amplitudes and the r-sBSI as based on the ratio of the spectral power, both as a function of the amplitude ratio β = Ri/Li. In a typical range of interest, where the amplitude ratio Ri/Li ∼ 2, we find that this ratio is ∼2, as well. The general expression of the differences in sensitivity between the sBSI and its revision is given by (Eq. (9)).
If symmetry is present, within the
Discussion and conclusions
The BSI was originally proposed to quantify hemispheric asymmetry, as may occur during carotid surgery (van Putten et al., 2004). By now, various additional applications include monitoring of stroke patients (van Putten and Tavy, 2004), detection of focal seizure activity (van Putten et al., 2005) and the detection of diffuse EEG changes in ischaemia (van Putten, 2006). The primary motivation for the current paper was to present a detailed description of a modified and improved algorithm, with
Note added in the proof
If γ is erroneously estimated too large, an increase in asymmetry may result in a reduction of the value of the r-tBSI. It is recommended, therefore, to use a conservative value, and accept a small residual.
References (16)
- et al.
Computed electroencephalographic topographic brain mapping. A new and accurate monitor of cerebral circulation and function for patients having carotid endarterectomy
J Vasc Surg
(1988) - et al.
Electroencephalographic background desynchronization during cerebral blood flow reduction
Clin Neurophysiol
(2005) - et al.
EEG power changes are more sensitive than spectral edge frequency variation for detection of cerebral ischemia during carotid artery surgery: a prospective assessment of processed EEG monitoring
J Cardiothorac Vasc Anesth
(1992) Extended BSI for continuous EEG monitoring in carotid endarterectomy
Clin Neurophysiol
(2006)- et al.
A brain symmetry index (BSI) for online EEG monitoring in carotid endarterectomy
Clin Neurophysiol
(2004) - et al.
Detecting temporal lobe seizures from scalp EEG recordings: a comparison of various features
Clin Neurophysiol
(2005) - et al.
Continuous electroencephalographic monitoring and selective shunting reduces neurologic morbidity rates in carotid endarterectomy
J Vasc Surg
(1997) - et al.
EEG evidence for shunt requirement during carotid endarterectomy: optimal EEG derivations with respect to frequency bands and anesthetic regimen
J Clin Neurophysiol
(2001)
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