A comparative study of a theoretical neural net model with MEG data from epileptic patients and normal individuals

OBJECTIVE: The aim of this study was to compare a theoretical neural net model with MEG data from epileptic patients and normal individuals. METHODS: Our experimental study population included 10 epilepsy sufferers and 10 healthy subjects. The recordings were obtained with a one-channel biomagnetometer SQUID in a magnetically shielded room. RESULTS: Using the method of x(2)-fitting it was found that the MEG amplitudes in epileptic patients and normal subjects had Poisson and Gauss distributions respectively. The Poisson connectivity derived from the theoretical neural model represents the state of epilepsy, whereas the Gauss connectivity represents normal behavior. The MEG data obtained from epileptic areas had higher amplitudes than the MEG from normal regions and were comparable with the theoretical magnetic fields from Poisson and Gauss distributions. Furthermore, the magnetic field derived from the theoretical model had amplitudes in the same order as the recorded MEG from the 20 participants. CONCLUSION: The approximation of the theoretical neural net model with real MEG data provides information about the structure of the brain function in epileptic and normal states encouraging further studies to be conducted

Author Correction: Gap junction protein Connexin-43 is a direct transcriptional regulator of N-cadherin in vivo

Correction to: Nature Communications (2018); https://doi.org/10.1038/s41467-018-06368-x, published online 21 September 2018. The original version of this Article contained an error in the spelling of the author Alexandra Schambony, which was incorrectly given as Alexandra Schambon. This has now been corrected in both the PDF and HTML versions of the Article

Gap junction protein Connexin-43 is a direct transcriptional regulator of N-cadherin in vivo

Connexins are the primary components of gap junctions, providing direct links between cells under many physiological processes. Here, we demonstrate that in addition to this canonical role, Connexins act as transcriptional regulators. We show that Connexin 43 (Cx43) controls neural crest cell migration in vivo by directly regulating N-cadherin transcription. This activity requires interaction between Cx43 carboxy tail and the basic transcription factor-3, which drives the translocation of Cx43 tail to the nucleus. Once in the nucleus they form a complex with PolII which directly binds to the N-cadherin promoter. We found that this mechanism is conserved between amphibian and mammalian cells. Given the strong evolutionary conservation of connexins across vertebrates, this may reflect a common mechanism of gene regulation by a protein whose function was previously ascribed only to gap junctional communication

The influence of low-grade glioma on resting state oscillatory brain activity: a magnetoencephalography study

Purpose In the present MEG-study, power spectral analysis of oscillatory brain activity was used to compare resting state brain activity in both low-grade glioma (LGG) patients and healthy controls. We hypothesized that LGG patients show local as well as diffuse slowing of resting state brain activity compared to healthy controls and that particularly global slowing correlates with neurocognitive dysfunction. Patient and methods Resting state MEG recordings were obtained from 17 LGG patients and 17 age-, sex-, and education-matched healthy controls. Relative spectral power was calculated in the delta, theta, upper and lower alpha, beta, and gamma frequency band. A battery of standardized neurocognitive tests measuring 6 neurocognitive domains was administered. Results LGG patients showed a slowing of the resting state brain activity when compared to healthy controls. Decrease in relative power was mainly found in the gamma frequency band in the bilateral frontocentral MEG regions, whereas an increase in relative power was found in the theta frequency band in the left parietal region. An increase of the relative power in the theta and lower alpha band correlated with impaired executive functioning, information processing, and working memory. Conclusion LGG patients are characterized by global slowing of their resting state brain activity and this slowing phenomenon correlates with the observed neurocognitive deficits

Complexity Analysis of Resting-State MEG Activity in Early-Stage Parkinson's Disease Patients

The aim of the present study was to analyze resting-state brain activity in patients with Parkinson's disease (PD), a degenerative disorder of the nervous system. Magnetoencephalography (MEG) signals were recorded with a 151-channel whole-head radial gradiometer MEG system in 18 early-stage untreated PD patients and 20 age-matched control subjects. Artifact-free epochs of 4 s (1250 samples) were analyzed with Lempel-Ziv complexity (LZC), applying two- and three-symbol sequence conversion methods. The results showed that MEG signals from PD patients are less complex than control subjects' recordings. We found significant group differences (p-values <0.01) for the 10 major cortical areas analyzed (e.g., bilateral frontal, central, temporal, parietal, and occipital regions). In addition, using receiver-operating characteristic curves with a leave-one-out cross-validation procedure, a classification accuracy of 81.58% was obtained. In order to investigate the best combination of LZC results for classification purposes, a forward stepwise linear discriminant analysis with leave-one out cross-validation was employed. LZC results (three-symbol sequence conversion) from right parietal and temporal brain regions were automatically selected by the model. With this procedure, an accuracy of 84.21% (77.78% sensitivity, 90.0% specificity) was achieved. Our findings demonstrate the usefulness of LZC to detect an abnormal type of dynamics associated with PD