Abstract
INTRODUCTION
Surgical localization of epileptogenic networks requires significant intensive-care stays and facilitation of seizures for visual inspection. Multivariate Granger Causality ...(MVGC) provides a method of calculating the directional influence from each node to every other node during interictal data before seizures are facilitated after implantation of electrodes. MVGC is an efficient method of detecting biological coupling and has been shown to be robust against noise. Nodes identified as influential by MVGC have recently been shown to correlate with predicted seizure zones.
METHODS
Electrocorticography was examined and analyzed for five patients undergoing seizure localization surgery. Used ECOG channels were sampled at greater than 1.5 KHz for all patients. Model estimation was performed, and MVGC was used to calculate patterns of directional coupling over 100 second time windows. MVGC was performed on entire stays for two patients and on subsampled data for 3 patients. Coupling was also examined in the frequency domain to establish frequency basis of information exchange. Comparisons were made after blinded analysis was complete with seizure nodes identified by epileptologists.
RESULTS
>Five patients were included with more than 12 weeks of recorded data. MVGC adjacency matrices from interictal data over time from each patient revealed significant dominance by few nodes (average 1.8). Coupling changed little over time with highly accurate reconstructions after an average of 184 minutes when compared to the average matrix over the entire stay. On comparison to seizure onset nodes determined by epileptologist, the analysis found concordance 92.1% of the time with high significance compared to randomly selected channels (P < 0.00001).
CONCLUSION
MVGC is a method of detecting directional coupling in ECOG recordings. Previous and current work suggests that influential nodes during interictal data may predict epileptogenic hubs. Data collection may only require a few hours to reproduce the predicted influential nodes, potentially dramatically reducing the required length of stay.
Introduction: Fungus ball (aspergiloma) can be defined as spheric or ovoid conglomeration of fungal hypha, mucus and cellular debris with a fibrous wall located in cavities (mostly tuberculosis ...cavitiy) of the lung. A CT guided transthoracic FNA material showed fungal organisms, PNLs, hypha (45 degree angulation in some of them) which represents aspergilus (picture 2).
Inside Back Cover
Chinese journal of chemistry,
11/2022, Letnik:
40, Številka:
21
Journal Article
Recenzirano
Pentagon defects and zigzag edges are sites for spin‐localization in the open‐shell nanogaphene molecules. With tailored molecular design, it was found that the spin distribution can be shifted from ...the pentagon sites to the zigzag edges along with π‐lengthening. More details are discussed in the article by Sun et al. on page 2525—2530.
Front cover: When synaptogenesis begins, splicing of the Kalrn gene changes, leading to expression of several isoforms of this Rho GEF. One major isoform contains a phosphoinositide-binding ...amphipathic helix (cKal) preceding its Sec14 domain and a PDZ binding motif at the COOH-terminus (Kal7). Rat hippocampal neurons (22 DIV) expressing farnesylated-EGFP (fEGFP) were immunostained with antibodies specific for cKal (red), Vglut1 (blue) and GFP (green); the image is a compressed Z-stack. cKal localized to PSD-positive puncta apposed to Vglut1 positive presynaptic terminals. cKal7 differs from the other major Kal7 isoform (bKal7) in its localization and effect on spine morphology. Mutagenesis which eliminated the ability of cKal7 to interact with phosphoinositides altered its localization. Read the full article 'Alternate promoter usage generates two subpopulations of the neuronal RhoGEF Kalirin-7' by M. B. Miller, Y. Yan, Y. Wu, B. Hao, R. E. Mains and B. A. Eipper (J. Neurochem. 2017, vol. 140 (6), pp. 889-902) on doi: 10.1111/jnc.13749
The subject of this book is how the brain works. In order to understand this, it is essential to know what is computed by different brain systems; and how the computations are performed. The aim of ...this book is to elucidate what is computed in different brain systems; and to describe current computational approaches and models of how each of these brain systems computes. Understanding the brain in this way has enormous potential for understanding ourselves better in health and in disease. Potential applications of this understanding are to the treatment of the brain in disease; and to artificial intelligence which will benefit from knowledge of how the brain performs many of its extraordinarily impressive functions. This book is pioneering in taking this approach to brain function: to consider what is computed by many of our brain systems; and how it is computed. The book is also pioneering in taking biologically plausible approaches to brain computation. The book is also pioneering in incorporating evidence on the connectivity of 360 cortical regions in the human brain, making the book highly relevant to understanding the human brain. The book will be of interest to all scientists interested in brain function and how the brain works, whether they are from neuroscience, or from medical sciences including neurology and psychiatry, or from the area of computational science including machine learning and artificial intelligence, or from areas such as theoretical physics.
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