Guido Widman

Nonlinear EEG analysis in epilepsy: its possible use for interictal focus localization, seizure anticipation, and prevention.

Several recent studies emphasize the high value of nonlinear EEG analysis particularly for improved characterization of epileptic brain states. In this review the authors report their work to increase insight into the spatial and temporal dynamics of the epileptogenic process. Specifically, they discuss possibilities for seizure anticipation, which is one of the most challenging aspects of epileptology. Although there are numerous studies exploring basic neuronal mechanisms that are likely to be associated with seizures, to date no definite information is available regarding how, when, or why a seizure occurs. Nonlinear EEG analysis now provides strong evidence that the interictal-ictal state transition is not an abrupt phenomenon. Rather, findings indicate that it is indeed possible to detect a preseizure phase. The unequivocal definition of such a state with a sufficient length would enable investigations of basic mechanisms leading to seizure initiation in humans, and development of adequate seizure prevention strategies.Summary: Several recent studies emphasize the high value of nonlinear EEG analysis particularly for improved characterization of epileptic brain states. In this review the authors report their work to increase insight into the spatial and temporal dynamics of the epileptogenic process. Specifically, they discuss possibilities for seizure anticipation, which is one of the most challenging aspects of epileptology. Although there are numerous studies exploring basic neuronal mechanisms that are likely to be associated with seizures, to date no definite information is available regarding how, when, or why a seizure occurs. Nonlinear EEG analysis now provides strong evidence that the interictal‐ictal state transition is not an abrupt phenomenon. Rather, findings indicate that it is indeed possible to detect a preseizure phase. The unequivocal definition of such a state with a sufficient length would enable investigations of basic mechanisms leading to seizure initiation in humans, and development of adequate seizure prevention strategies.

The epileptic process as nonlinear deterministic dynamics in a stochastic environment: an evaluation on mesial temporal lobe epilepsy

The theory of deterministic chaos addresses simple deterministic dynamics in which nonlinearity gives rise to complex temporal behavior. Although biological neuronal networks such as the brain are highly complicated, a number of studies provide growing evidence that nonlinear time series analysis of brain electrical activity in patients with epilepsy is capable of providing potentially useful diagnostic information. In the present study, this analysis framework was extended by introducing a new measure xi, designed to discriminate between nonlinear deterministic and linear stochastic dynamics. For the evaluation of its discriminative power, xi was extracted from intracranial multi-channel EEGs recorded during the interictal state in 25 patients with unilateral mesial temporal lobe epilepsy. Strong indications of nonlinear determinism were found in recordings from within the epileptogenic zone, while EEG signals from other sites mainly resembled linear stochastic dynamics. In all investigated cases, this differentiation allowed to retrospectively determine the side of the epileptogenic zone in full agreement with results of the presurgical workup.

Classifying EEG and ECoG signals without subject training for fast BCI implementation: comparison of nonparalyzed and completely paralyzed subjects

We summarize results from a series of related studies that aim to develop a motor-imagery-based brain-computer interface using a single recording session of electroencephalogram (EEG) or electrocorticogram (ECoG) signals for each subject. We apply the same experimental and analytical methods to 11 nonparalysed subjects (eight EEG, three ECoG), and to five paralyzed subjects (four EEG, one ECoG) who had been unable to communicate for some time. While it was relatively easy to obtain classifiable signals quickly from most of the nonparalyzed subjects, it proved impossible to classify the signals obtained from the paralyzed patients by the same methods. This highlights the fact that though certain BCI paradigms may work well with healthy subjects, this does not necessarily indicate success with the target user group. We outline possible reasons for this failure to transfer.

Nonlinear EEG Analysis and Its Potential Role in Epileptology

Summary: Deterministic chaos offers a striking explanation for apparently irregular behavior of the brain that is evidenced in the EEG. Recent developments in the physical–mathematical framework of the theory of nonlinear dynamics (colloquially often termed chaos theory) provide new concepts and powerful algorithms to analyze such time series. Because of its high versatility, nonlinear time series analysis has already gone beyond the physical sciences and, at present, is being successfully applied in a variety of disciplines, including cardiology, neurology, psychiatry, and epileptology. However, it is well known that different influencing factors limit the use of nonlinear measures to characterize EEG dynamics in a strict sense. Nevertheless, when interpreted with care, relative estimates of, e.g., the correlation dimension or the Lyapunov exponents, can reliably characterize different states of normal and pathologic brain function. In epileptology, extraction of nonlinear measures from the intracranially recorded EEG promises to be important for clinical practice. In addition to an immense reduction of information content of long‐lasting EEG recordings, previous studies have shown that these measures enable (a) localization of the primary epileptogenic area in different cerebral regions during the interictal state, (b) investigations of antiepileptic drug effects, (c) analyses of spatio‐temporal interactions between the epileptogenic zone and other brain areas, and (d) detection of features predictive of imminent seizure activity. Nonlinear time series analysis provides new and supplementary information about the epileptogenic process and thus contributes to an improvement in presurgical evaluation.

Persistent cognitive impairment, hippocampal atrophy and EEG changes in sepsis survivors

Objectives The objective of this preliminary study was to explore long-term changes in neurobehavioral parameters, brain morphology and electroencephalography of sepsis patients who received intensive care compared to non-septic intensive care unit (ICU) patients. Methods Two-centre follow-up study 6–24 months after discharge from hospital using published norms and existing databases of healthy controls for comparison. Patients included 25 septic and 19 non-septic ICU survivors who were recruited from two ICUs of a university and community hospital. Measurements used include brain morphology, standard electroencephalography, cognition and psychiatric health and health-related quality of life. Results Sepsis survivors showed cognitive deficits in verbal learning and memory and had a significant reduction of left hippocampal volume compared to healthy controls. Moreover, sepsis and to some extent non-septic ICU patients had more low-frequency activity in the EEG indicating unspecific brain dysfunction. No differences were found in health-related quality of life, psychological functioning or depressive symptoms, and depression could be ruled out as a confounding factor. Conclusions This study demonstrates permanent cognitive impairment in several domains in both septic and non-septic ICU survivors and unspecific brain dysfunction. In the sepsis group, left-sided hippocampal atrophy was found compared to healthy controls. Further study is needed to clarify what contribution sepsis and other factors at the ICU make to these outcomes. Specific neuroprotective therapies are warranted to prevent persisting brain changes in ICU patients.

Digital photography and 3D MRI-based multimodal imaging for individualized planning of resective neocortical epilepsy surgery

Summary:  Purpose: Invasive presurgical work up of pharmacoresistant epilepsies presumes integration of multiple diagnostic modalities into a comprehensive picture of seizure onset and eloquent brain areas. During resection, reliable transfer of evaluation results to the patients individual anatomy must be made. We investigated the value of digital photography–based grid localization in combination with preoperative three‐dimensional (3D) magnetic resonance imaging (MRI) for clinical routine.

Aggressive behavior of epilepsy patients in the course of levetiracetam add-on therapy: report of 33 mild to severe cases

Levetiracetam (LEV) was shown to be very efficacious and well tolerated as add-on therapy for refractory epilepsy. Here we report 33 patients with longstanding histories of epilepsy who experienced aggressive episodes during LEV therapy. This corresponds to 3.5% of LEV-treated patients as compared with less than 1% of patients not on LEV. Among these cases, 24 showed only moderate, partly transient irritability, with 10 patients requiring reduction or discontinuation of LEV. More strikingly, 9 patients displayed severe symptoms of aggression with physical violence and, in 2 cases, the need for psychiatric emergency treatment. One patient developed additional psychotic symptoms. We suggest that, specifically in patients with a previous history of aggression, behavioral tolerability of LEV should be carefully monitored.

Antiepileptic drugs interact with folate and vitamin B12 serum levels

Antiepileptic drugs (AEDs) are important for the treatment of epilepsy, psychiatric diseases, and pain syndromes. Small studies have suggested that AED treatment reduces serum levels of folate and vitamin B12.

Are there physical risk factors for psychogenic non-epileptic seizures in patients with epilepsy?

UNLABELLED Patients with epilepsy may have additional psychogenic non-epileptic seizures (PNES). It has been suggested that PNES are more common if patients with epilepsy are female, develop epilepsy later in life and have right-sided brain lesions. We examine whether these or other physical factors affect the risk of PNES in patients with epilepsy in a controlled study. METHODS Ninety consecutive patients with PNES and concurrent epilepsy (PNES+E group) and 90 consecutive patients with epilepsy alone (epilepsy group) were compared with regard to the variables sex, age at onset of epilepsy, epilepsy type (focal/generalised), location and lateralisation of epileptogenic zone, aetiology of epilepsy, interictal epileptiform potentials, magnetic resonance imaging (MRI) abnormalities, neuropsychological (NPS) deficits and intelligence quotient (IQ). RESULTS Female sex (P<0.001), abnormal visual memory (P=0.012), global NPS impairment (P=0.029), and low IQ category (P=0.005) were associated with a higher risk of PNES. Other variables did not differ between the groups. CONCLUSIONS In patients with epilepsy, female sex, poor visual memory or global neuropsychological underperformance and low IQ are associated with an increased risk of PNES. MRI changes, epileptiform EEG abnormalities and location of epileptogenic zone do not show a predilection for one hemisphere.

Improved spatial characterization of the epileptic brain by focusing on nonlinearity

An advanced characterization of the complicated dynamical system brain is one of sciences biggest challenges. Nonlinear time series analysis allows characterizing nonlinear dynamical systems in which low-dimensional nonlinearity gives rise to complex and irregular behavior. While several studies indicate that nonlinear methods can extract valuable information from neuronal dynamics, others doubt their necessity and conjecture that the same information can be obtained using classical linear techniques. To address this issue, we compared these two concepts, but included furthermore a combination of nonlinear measures with surrogates, an approach that has been designed to specifically focus on nonlinearity. As a benchmark we used the discriminative power to detect the seizure-generating hemisphere in medically intractable mesial temporal lobe epilepsy. We analyzed intracranial electroencephalographic recordings from the seizure-free interval of 29 patients. While the performance of both linear and nonlinear measures was weak, if not insignificant, a very high performance was obtained by the use of surrogate-corrected measures. Focusing on nonlinearity by using a combination of nonlinear measures with surrogates appears as the key to a successful characterization of the spatial distribution of the epileptic process.