Deep Multi-State Dynamic Recurrent Neural Networks Operating on Wavelet Based Neural Features for Robust Brain Machine Interfaces

We present a new deep multi-state Dynamic Recurrent Neural Network (DRNN) architecture for Brain Machine Interface (BMI) applications. Our DRNN is used to predict Cartesian representation of a computer cursor movement kinematics from open-loop neural data recorded from the posterior parietal cortex (PPC) of a human subject in a BMI system. We design the algorithm to achieve a reasonable trade-off between performance and robustness, and we constrain memory usage in favor of future hardware implementation. We feed the predictions of the network back to the input to improve prediction performance and robustness. We apply a scheduled sampling approach to the model in order to solve a statistical distribution mismatch between the ground truth and predictions. Additionally, we configure a small DRNN to operate with a short history of input, reducing the required buffering of input data and number of memory accesses. This configuration lowers the expected power consumption in a neural network accelerator. Operating on wavelet-based neural features, we show that the average performance of DRNN surpasses other state-of-the-art methods in the literature on both single- and multi-day data recorded over 43 days. Results show that multi-state DRNN has the potential to model the nonlinear relationships between the neural data and kinematics for robust BMIs

Deep Multi-State Dynamic Recurrent Neural Networks Operating on Wavelet Based Neural Features for Robust Brain Machine Interfaces

We present a new deep multi-state Dynamic Recurrent Neural Network (DRNN) architecture for Brain Machine Interface (BMI) applications. Our DRNN is used to predict Cartesian representation of a computer cursor movement kinematics from open-loop neural data recorded from the posterior parietal cortex (PPC) of a human subject in a BMI system. We design the algorithm to achieve a reasonable trade-off between performance and robustness, and we constrain memory usage in favor of future hardware implementation. We feed the predictions of the network back to the input to improve prediction performance and robustness. We apply a scheduled sampling approach to the model in order to solve a statistical distribution mismatch between the ground truth and predictions. Additionally, we configure a small DRNN to operate with a short history of input, reducing the required buffering of input data and number of memory accesses. This configuration lowers the expected power consumption in a neural network accelerator. Operating on wavelet-based neural features, we show that the average performance of DRNN surpasses other state-of-the-art methods in the literature on both single- and multi-day data recorded over 43 days. Results show that multi-state DRNN has the potential to model the nonlinear relationships between the neural data and kinematics for robust BMIs

Pooled analysis of iron-related genes in Parkinson's disease: Association with transferrin

Pathologic features of Parkinson's disease (PD) include death of dopaminergic neurons in the substantia nigra, presence of α-synuclein containing Lewy bodies, and iron accumulation in PD-related brain regions. The observed iron accumulation may be contributing to PD etiology but it also may be a byproduct of cell death or cellular dysfunction. To elucidate the possible role of iron accumulation in PD, we investigated genetic variation in 16 genes related to iron homeostasis in three case-control studies from the United States, Australia, and France. After screening 90 haplotype tagging single nucleotide polymorphisms (SNPs) within the genes of interest in the US study population, we investigated the five most promising gene regions in two additional independent case-control studies. For the pooled data set (1289 cases, 1391 controls) we observed a protective association (OR. = 0.83, 95% CI: 0.71-0.96) between PD and a haplotype composed of the A allele at rs1880669 and the T allele at rs1049296 in transferrin (TF; GeneID: 7018). Additionally, we observed a suggestive protective association (OR. = 0.87, 95% CI: 0.74-1.02) between PD and a haplotype composed of the G allele at rs10247962 and the A allele at rs4434553 in transferrin receptor 2 (TFR2; GeneID: 7036). We observed no associations in our pooled sample for haplotypes in SLC40A1, CYB561, or HFE. Taken together with previous findings in model systems, our results suggest that TF or a TF- TFR2 complex may have a role in the etiology of PD, possibly through iron misregulation or mitochondrial dysfunction within dopaminergic neurons

Genome-wide Association Meta-analysis of Childhood and Adolescent Internalizing Symptoms

Objective: To investigate the genetic architecture of internalizing symptoms in childhood and adolescence. Method: In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument. Results: The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, n(effective) = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (vertical bar r(g)vertical bar > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range vertical bar r(g)vertical bar = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Conclusion: Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.Peer reviewe

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness

Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P<5 x 10(-8)) in combined analyses. A number of these loci contain genes implicated in structure and function of skeletal muscle fibres (ACTG1), neuronal maintenance and signal transduction (PEX14, TGFA, SYT1), or monogenic syndromes with involvement of psychomotor impairment (PEX14, LRPPRC and KANSL1). Mendelian randomization analyses are consistent with a causal effect of higher genetically predicted grip strength on lower fracture risk. In conclusion, our findings provide new biological insight into the mechanistic underpinnings of grip strength and the causal role of muscular strength in age-related morbidities and mortality

Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia

Schizophrenia has a heritability of 60–80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Meningkatkan Mutu Seorang Pemimpin (Konsep Pemimpin Kristen yang Melayani)

Pemimpin selalu menjadi standar utama dalam setiap pengambilan keputusan yang ada sehingga seorang pemimpin memerlukan dan memiliki mutu serta meningkatkan mutu dalam memimpin.Maka dengan demikian penulis mengadakan penelitian ini.Tujuan penelitian ini adalah untuk mengetahui bagaimana seorang pemimpin meningkatkan mutunya sehingga menjadi seorang pemimpin yang melayani. Metode penelitian yang digunakan adalah metode kualitatif dengan menggunakan pendekatan studi kasus.Yang menjadi sumber data adalah 5 Pemimpin Gereja GBI Glow FC dari 5 Wilayah.Objek Penelitiannya adalah Meningkatkan Mutu Seorang Pemimpin dengan Konsep Pemimpin yang Melayani.Hasil dari Penelitian ditemukan bahwa seorang Pemimpin memerlukan peningkatan mutu kepemimpinannya agar mampu menjadi pemimpin yang melayani