[WEB SITE] A virtual brain helps decrypt epilepsy – Medical News Today

Researchers at CNRS, INSERM, Aix-Marseille University and AP-HM have just created a virtual brain that can reconstitute the brain of a person affected by epilepsy for the first time. From this work we understand better how the disease works and can also better prepare for surgery. These results are published in Neuroimage.

Worldwide, one percent of the population suffers from epilepsy. The disease affects individuals differently, so personalized diagnosis and treatment are important. Currently we have few ways to understand the pathology’s mechanisms of action, and mainly use visual interpretation of an MRI and electroencephalogram. This is especially difficult because 50% of patients do not present anomalies visible in MRI, so the cause of their epilepsy is unknown.

Researchers have succeeded for the first time in developing a personalized virtual brain, by designing a base “template” and adding individual patient information, such as the specific way the brain’s regions are organized and connected in each individual. Mathematical models that cause cerebral activity can be tested on the virtual brain. In this way, scientists have been able to reproduce the place where epilepsy seizures initiate and how they propagate. This brain therefore has real value in predicting how seizures occur in each patient, which could lead to much more precise diagnosis.

Moreover, 30% of epileptic patients do not respond to drugs, so their only hope remains surgery. This is effective if the surgeon has good indications of where to operate. The virtual brain gives surgeons a virtual “platform.” In this way they can determine where to operate while avoiding invasive procedures, and especially prepare for the operation by testing different surgical possibilities, seeing which would be most effective and what the consequences would be, something that is obviously impossible to do on the patient.

In the long run, the team’s goal is to provide personalized medicine for the brain, by offering virtual, tailored, therapeutic solutions that are specific for each patient. The researchers are currently working on clinical trials to demonstrate the predictive value of their discovery. This technology is also being tested on other pathologies that affect the brain, such as strokes, Alzheimer’s, degenerative neurological diseases, and multiple sclerosis.

Article: The Virtual Epileptic Patient: Individualized whole-brain models of epilepsy spread, Jirsa VK, Proix T, Perdikis D, Woodman MM, Wang H, Gonzalez-Martinez J, Bernard C, Bénar C, Guye M, Chauvel P, Bartolomei F, Neuroimage, doi:10.1016/j.neuroimage.2016.04.049, published 28 July 2016.

Fig. 2. Different types of epileptic seizures are recorded with SEEG electrodes in this patient. (A) Simple seizure. The simple seizures started in the right hippocampus (red zone on the left picture, channel B1–2 on the SEEG time series) and remained restricted to this area. (B) Complex seizure. The complex seizures started in the right hippocampus (channel B1–2) before spreading to the contralateral hippocampus (channel B′1–2) and further spreading in the left temporal lobe. (C) Stimulated seizure. After stimulating the left hippocampus (channel C′3–4), a seizure was triggered, spreading to the remainder of the left temporal lobe, but not propagating to the right hemisphere. In particular, the hypothalamic hamartoma was recruited. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Source: A virtual brain helps decrypt epilepsy – Medical News Today

[ARTICLE] May clinical neurophysiology help to predict the recovery of neurological early rehabilitation patients? – Full Text HTML

Abstract

Background: So far, the role of clinical neurophysiology in the prediction of outcome from neurological and neurosurgical early rehabilitation is unclear.

Methods: Clinical and neurophysiological data of a large sample of 803 early rehabilitation cases of the BDH-Clinic Hessisch Oldendorf in Northern Germany have been carefully reviewed. Most patients (43.5 %) were transferred to rehabilitation after stroke, mean age was 66.6 (15.5) years. Median somatosensory (SEP), auditory (AEP) and visual evoked potentials (VEP) along with EEG recordings took place within the first two weeks after admission. Length of stay (LOS) in early rehabilitation was 38.3 (37.2) days.

Results: Absence of SEP on one or both sides was associated with poor outcome, χ2 = 12.98 (p = 0.005); only 12.5 % had a good outcome (defined as Barthel index, BI ≥50) when SEP were missing on both sides. In AEP, significantly longer bilateral latencies III were observed in the poor outcome group (p < 0.05). Flash VEP showed that patients in the poor outcome group had a significantly longer latency III on both sides (p < 0.05). The longer latency III, the smaller BI changes (BI discharge minus admission) were observed (latency III right r = −0.145, p < 0.01; left r = −0.206, p < 0.001). While about half of the patients with alpha EEG activity belonged to the good outcome group (80/159, 50.3 %), only 39/125 (31.2 %) with theta and 5/41 (12.2 %) with delta rhythm had a favourable outcome, χ2 = 24.2, p < 0.001.

Conclusions: Results from this study suggest that loss of median SEP, prolongation of wave III in AEP and flash-VEP as well as theta or delta rhythms in EEG are associated with poor outcome from neurological early rehabilitation. Further studies on this topic are strongly encouraged.

When patients had alpha EEG-activity, BI on admission, at discharge and changes of BI (discharge minus admission) were significantly higher than patients with theta or delta activity (ANOVAs with LSD-tests, p < 0.001)

Continue —> May clinical neurophysiology help to predict the recovery of neurological early rehabilitation patients? – Springer