Discovery of recurrent multiple brain states in non-convulsive status epilepticus
Introduction
In various neurological conditions, the EEG shows abrupt transitions between periods of relatively low-voltage activity and large-amplitude burst-like events in the form of spikes, poly spikes or sharp and slow waves. These burst-suppression (BS) patterns may occur in states of severe cerebral damage in postanoxic encephalopathy, anesthesia, or prematuritas. Remarkably, burst-like transients are also observed in neuronal cell cultures (van Pelt et al., 2004a, van Pelt et al., 2004b).
Similar EEG phenomena can sometimes be observed in patients suffering from a generalized status epilepticus. Treiman (Treiman et al., 1990) describes five identifiable EEG patterns in a predictable sequence during the course of a generalized convulsive status epilepticus in humans. Treiman stage I, for instance, is characterized by discrete seizures, with interictal slowing, and Treiman stage IV by ictal discharges with relatively quiescent periods of generalized low-voltage activity with a duration of 0.5–8 s. The phenomena observed during the ictal discharges in these patients are periodic or almost periodic, while this may be less prominent in a BS EEG pattern.
However, one of the pronounced similarities between a BS-pattern and the states as described by Treiman is the presence of relatively abrupt large-amplitude events punctuated by low-amplitude events. The common clinical feature is that in all these burst-like conditions, consciousness is severely reduced or absent. It is indicative of abnormal or – in the case of prematuritas – immature, brain function.
Various attempts have been made to explain the cause and dynamics of the brain derangement that is present in burst-like brain conditions. Some theories suggest a reduction of thalamic afferent input (Andersen et al., 1967) or, alternatively, a loss of the insulating properties of white matter (van Leeuwen, 1964). To explain burst-like conditions, these theories need to take into account a marked variation in both the burst-like and suppression durations. Rae-Grant (Rae-Grant and Kim, 1994) proposes that a burst-suppression pattern is consistent with type III intermittency (Pomeau and Maneville, 1980) behavior. This behavior is reminiscent of that of nonlinear dynamical systems operating at a transition to chaos. Their study included eight patients, suffering from head injury or anoxic encephalopathy. Type III intermittency is presumably also present in some cases of human partial epilepsy. By quantitative analysis of the duration of the burst-like regular or almost periodic phases during the ictal events, Perez Velazquez et al. (Velazquez et al., 1999) suggest the presence of transient stabilizations of otherwise unstable states. Quite generally, however, the phenomenology of a change of stability in a nonlinear system (with a fixed number of degrees of freedom) is difficult to distinguish from a neural network with intermittent levels of interconnectivity.
In this paper, we study the phenomenology of the onset of burst-like transients in two patients suffering from a non-convulsive SE. In this pathology, the burst-phenomena show distinct patterns of repeating behavior, even when the bursts themselves appear randomly in time. In Section 2, we discuss the patients’ history and our method of EEG analysis. The results are described in Section 3, and we summarize our findings in Section 4.
Section snippets
Patients and methods
Patient G, a 55-year-old female, was admitted to our hospital for analysis of potential renal failure. In the morning of the second day in the hospital she was found unconscious. Computed tomography showed no abnormalities; laboratory investigation showed high urea and creatinine, without additional abnormalities. Suspicion of a non-convulsive status epilepticus was raised. Subsequent EEG recording showed more or less periodic epochs with epileptiform discharges and periods with low-voltage
Results
An illustration of the time series, with the corresponding ‘envelope’, is presented in Fig. 3. By setting the appropriate threshold, the beginning and end of all epileptiform discharges was identified.
To obtain a first impression of the time course of the various events, we estimated the spectrum of the envelope. Results of this analysis are presented in Fig. 4. At least two significant peak frequencies are observed. Patient G shows dominant frequencies at approximately 0.01 and 0.1 Hz, where
Discussion
The electroencephalographic discharges that can be observed during status epilepticus show a rich phenomenology, which includes continuous and discontinuous patterns, as well as periodic and non-periodic features. In patients suffering from generalized convulsive status epilepticus, Treiman et al. described five different EEG patterns, which occur in a predictable sequence (Treiman et al., 1990). Similar phenomena can be observed in experimental epilepsy models in rats as well (Treiman et al.,
Acknowledgements
We thank the anonymous reviewers for their valuable comments and suggestions.
References (14)
- et al.
Electrocorticographic changes during generalized convulsive status epilepticus in soman intoxicated rats
Epilepsy Res
(1998) - et al.
Type III intermittency: a nonlinear dynamic model of EEG burst suppression
Electroencephalogr Clin Neurophysiol
(1994) - et al.
Dynamics of non-convulsive epileptic phenomena modeled by a bistable neuronal network
Neuroscience
(2004) - et al.
A progressive sequence of electroencephalographic changes during generalized convulsive status epilepticus
Epilepsy Res
(1990) - et al.
Longterm stability and developmental changes in spontaneous network burst firing patterns in dissociated rat cerebral cortex cell cultures on multielectrode arrays
Neurosci Lett
(2004) - et al.
Some factors involved in the thalamic control of spontaneous barbiturate spindles
J Physiol (Lond)
(1967) - Bak P. How Nature...
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