| 111. |
- Córdova-Palomera, Aldo, et al.
(författare)
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Genetic control of variability in subcortical and intracranial volumes
- 2021
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Ingår i: Molecular Psychiatry. - : Nature Publishing Group. - 1359-4184 .- 1476-5578. ; 26:8, s. 3876-3883
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Tidskriftsartikel (refereegranskat)abstract
- Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in ten key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume, cortical surface area, and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n = 25,575 individuals; 8-89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in thalamus volume and cortical thickness. The variance-controlling loci involved genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.
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| 112. |
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| 113. |
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| 114. |
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| 115. |
- Gajic, D., et al.
(författare)
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Classification of EEG signals for detection of epileptic seizures based on wavelets and statistical pattern recognition
- 2014
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Ingår i: Biomedical Engineering: Applications, Basis and Communications. - : World Scientific. - 1016-2372 .- 1793-7132. ; 26:2, s. 1450021-
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Tidskriftsartikel (refereegranskat)abstract
- The electroencephalogram (EEG) signal is very important in the diagnosis of epilepsy. Long-term EEG recordings of an epileptic patient contain a huge amount of EEG data. The detection of epileptic activity is, therefore, a very demanding process that requires a detailed analysis of the entire length of the EEG data, usually performed by an expert. This paper describes an automated classification of EEG signals for the detection of epileptic seizures using wavelet transform and statistical pattern recognition. The decision making process is comprised of three main stages: (a) feature extraction based on wavelet transform, (b) feature space dimension reduction using scatter matrices and (c) classification by quadratic classifiers. The proposed methodology was applied on EEG data sets that belong to three subject groups: (a) healthy subjects, (b) epileptic subjects during a seizure-free interval and (c) epileptic subjects during a seizure. An overall classification accuracy of 99% was achieved. The results confirmed that the proposed algorithm has a potential in the classification of EEG signals and detection of epileptic seizures, and could thus further improve the diagnosis of epilepsy.
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| 116. |
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| 117. |
- Jönsson, Erik G., et al.
(författare)
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Two methylenetetrahydrofolate reductase gene (MTHFR) polymorphisms, schizophrenia and bipolar disorder : An association study
- 2008
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Ingår i: American journal of medical genetics. Part B, Neuropsychiatric genetics. - : Wiley. - 1552-4841. ; 147B:6, s. 976-982
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Tidskriftsartikel (refereegranskat)abstract
- Recent meta-analyses of the methylenetetrahydrofolate reductase gene (MTHFR) have suggested association between two of its functional single gene polymorphisms (SNPs, C677T and A1298C) and schizophrenia. Studies have also suggested association between MTHFR C677T and A1298C variation and bipolar disorder. In a replication attempt the MTHFR C677T and A1298C SNPs were analyzed in three Scandinavian schizophrenia case-control samples. In addition, Norwegian patients with bipolar disorder were investigated. There were no statistically significant allele or genotype case-control differences. The present Scandinavian results do not verify previous associations between the putative functional MTHFR gene polymorphisms and schizophrenia or bipolar disorder. However, when combined with previous studies in meta-analyses there is still evidence for association between the MTHFR C677T polymorphism. and schizophrenia. Additional studies are warranted to shed further light on these relationships. (c) 2007 Wiley-Liss, Inc.
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| 118. |
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| 119. |
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| 120. |
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