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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

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NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

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Embedding a concurrent autonomous agent in a microcontrollers network

Embedding a concurrent autonomous agent in a microcontroller...

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Diego Stefano F. Ferreira Rafael R. da Silva Augusto Loureiro da Costa Universidade Federal da Bahia Salvador BA BR Robotics Laboratory Postgraduate Program in Electrical Engineering Federal University of Bahia Salvador Bahia Brazil

In this paper, a microcontroller heterogeneous network is proposed to embed a concurrent autonomous agent. The network was designed to fit the concurrency requirements of the cognitive model of the aforementioned agent. The architecture of the agent comprises three levels, namely, the reactive level, instinctive level and the cognitive level, which runs concurrently. The reactive level is embedded in a PSoC 5LP, consisting of behaviours created over a embedded kinematic controller. The instinctive level runs in a mbed NXP LPC1768, which receives perceptions from and sends the active behaviour to the reactive level through a CAN bus. And The cognitive level runs on a DNP/2486 which, in turn, receives symbolic information from and sends new local goals to instinctive level through an Ethernet network. Finally, the architecture used in the experiments is presented, followed by the results.

关键词： Computer architecture Autonomous agents Hardware Microcontrollers Mobile robots Robot sensing systems

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Acquisition, processing of myoelectrics signals and Support-Vector Machine for movement characterization of hand-arm segment

Acquisition, processing of myoelectrics signals and Support-...

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Clairê de Pauli Nilson Alexandre Balbinot Federal University of Rio Grande do Sul Postgraduate Program in Electrical Engineering Laboratory of Instrumentation Electrical and Electronics

The electrical engineering has been contributed with medical science to improve the knowledge and the practical applications in disabled ones life. In general, these researches aim to restore mobility and freedom to the disabled. This paper intends to develop a system that uses Surface Electromyography and Support-Vector Machines (SVM) for the characterization of specific movements of a human arm enabling the future integration in rehabilitation systems. At first, myoelectric signals are obtained in the arm muscles of a volunteer by means of surface electrodes attached to an Electromyography. The signal is acquired using a virtual model as pattern demonstrating to the volunteer the hand-arm movements which are to be replicated by the subject. The system acquires the myoelectric signals as the volunteer reproduces the visualized movements on a screen. After this, these signals are processed to extract their characteristics. Some of them (such as RMS, standard deviation, variance, mean, kurtosis, skewness) are the input data in the Support-Vector Machine. The output data is a valid or invalid movement recognition. At the end of the process the nine different movements reached an average hit rate of 79.4%.

关键词： Electromyography Support vector machines Wrist Muscles Electrodes Neural networks Data acquisition

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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Extrinsic calibration of non-overlapping camera-laser system using structured environment

Extrinsic calibration of non-overlapping camera-laser system...

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2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Yunsu Bok Dong-Geol Choi Pascal Vasseur In So Kweon Division of Future Vehicle KAIST Korea Robotics Program KAIST Korea Laboratory LITIS Université de Rouen France Department of Electrical Engineering KAIST Korea

In this paper are presented simple and practical solutions to extrinsic calibration between a camera and a 2D laser sensor, without overlap. Previous methods utilized a plane or an intersecting line of two planes as a geometric constraint with enough common field-of-view. These required additional sensors to calibrate non-overlapping systems. In this paper, we present two methods for solving the problem - one utilizes a plane; the other utilizes an intersecting line of two planes. For each method, an initial solution of the relative positions of a non-overlapping camera and a laser sensor, was computed by adopting a reasonable assumption about geometric structures. Then we refined it via non-linear optimization, even if the assumption was not perfectly satisfied. Both simulation results and experiments using real data showed that the proposed methods provided reliable results compared to ground-truth, and similar or better results than those provided by a conventional method.

关键词： Cameras Robot sensing systems Vectors Calibration Optimization Lasers Feature extraction

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Omnidirectional mobile robots navigation: A joint approach combining reinforcement learning and knowledge-based systems

Omnidirectional mobile robots navigation: A joint approach c...

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2013 4th ISSNIP-IEEE Biosignals and Biorobotics Conference: Biosignals and robotics for Better and Safer Living, BRC 2013

作者： Da Costa, Augusto Loureiro Ceonceicao, Andre Gustavo Scolari Cerqueira, Romulo Guedes Ribeiro, Tiago Trindade Robotics Laboratory Postgraduate Program in Electrical Engineering Universidade Federal da Bahia 40210-630 Salvador Bahia Brazil

ISBN: (纸本)9781467330244

A joint approach combining Reinforcement Learning, Knowledge Based Systems and a new methodology for environment mapping around the mobile robot neighborhood, for mobile robot navigation is presented in this paper. The new approach allows cognitive agent based on knowledge based systems, to uses Q-Iearning algorithms to interact successively with a specific domain, in a simulated environment, and once achieved the optimal policy, codes this optimal policy into a symbolic knowledge base that uses first order logic as knowledge representation formalism. Therefore, the knowledge base able to create free collision paths combining basic behaviors is embedded on a omnidirectional mobile robot. The paper also presents the experimental results, with real robots, obtained using the new methodology to capacity the omnidirectional mobile robot to navigate in a dynamic environments. The robot soccer, under the F180 category from RoboCup Federation, is used as an experimental domain. © 2013 IEEE.

关键词： Autonomous agents

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Evaluation of sensorimotor rhythms to control a wheelchair

Evaluation of sensorimotor rhythms to control a wheelchair

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Michel Carra Alexandre Balbinot Postgraduate Program in Electrical Engineering Laboratory of Instrumentation Electrical and Electronics Federal University of Rio Grande do Sul Brazil

Brain activity produces electrical signals that can be detected in a non-invasive or invasive way, and BCI (Brain-Computer Interface) systems can translate these signals into commands, which allow communication with devices without involvement of peripheral nerves and muscles. This paper shows the development of a non-invasive BCI system using brain signals from somatosensory cortex. The acquisition of signals was performed using one electrode cap in accordance with 10-20 system and using 3-channel EEG in order to command a motorized wheelchair without involvement of peripheral nerves and muscles. In the experiment with the wheelchair, 65.7% hit rates (average) were obtained for two directions, respectively.

关键词： Electroencephalography Feature extraction Wheelchairs Performance evaluation Tracking Electrodes Brain-computer interfaces

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A study of the Naive Bayes classifier for analyzing imaginary movement EEG signals using the Periodogram as spectral estimator

A study of the Naive Bayes classifier for analyzing imaginar...

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Juliano Machado Alexandre Balbinot Adalberto Schuck Postgraduate Program in Electrical Engineering Laboratory of Instrumentation Electrical and Electronics Federal University of Rio Grande do Sul Brazil Laboratory of Instrumentation Electrical and Electronics Federal University of Rio Grande do Sul Brazil

This study aims at applying algorithms for the spectral estimation and the classification of EEG signals during imaginary movements. Accordingly, it was used a database created by Graz University of Technology for the BCI Competition II. The database was created through an experiment in which an individual was asked to imagine the movement of her right or left hand while the EEG signal reading (Electroencephalogram) was being performed directly on the scalp by using three bipolar electrodes. In order to analyze the EEG signals for spectral estimation, it was used the Periodogram method computed in three different frequencies in μ-rythm (8 a 13Hz) and β-rythm (14 a 25Hz) frequencies to generate the Naive Bayes classifier entries. This database enabled to obtain a hit rate higher than 80%, which is consistent with results from the literature. Systems based on Brain-Computer Interface (BCI) can appropriate these algorithms to trigger and control devices through mental intentions only.

关键词： Electroencephalography Classification algorithms Feature extraction Training Estimation Databases Synchronization

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Development of a Brain-Computer Interface system based on sensorimotor rhythms

Development of a Brain-Computer Interface system based on se...

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2012 ISSNIP Biosignals and Biorobotics Conference: Biosignals and robotics for Better and Safer Living, BRC 2012

作者： Carra, Michel Balbinot, Alexandre Federal University of Rio Grande Do sul Postgraduate Program in Electrical Engineering Laboratory of Instrumentation Electrical and Electronics Brazil

ISBN: (纸本)9781467324762

In this work we developed a Brain-Computer Interface system using brain signals from somatosensory cortex. As stimulus, arrows were shown to the right and left to five subjects, who perform imaginary hand movement tasks to the side indicated by the arrow. Subject-specific parameters were selected using DSLVQ (Distinctive Sensitive Learning Vector Quantization) and Lateralization Index (LI), in order to extract the most relevant features, resulting in a higher hit rate in the classification stage. Online classification was performed with Linear Discriminant Analysis resulting in hit rates between 81 and 92.1%. © 2012 IEEE.

关键词： Brain computer interface

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Development of a Brain-Computer Interface system based on sensorimotor rhythms

Development of a Brain-Computer Interface system based on se...

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Michel Carra Alexandre Balbinot Postgraduate Program in Electrical Engineering Laboratory of Instrumentation Electrical and Electronics Federal University of Rio Grande do Sul Brazil

关键词： Feature extraction Electroencephalography Training Brain computer interfaces Performance evaluation Visualization Signal processing algorithms

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