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https://www.readbyqxmd.com/read/29353213/multiple-cortical-thickness-sub-networks-and-cognitive-impairments-in-first-episode-drug-na%C3%A3-ve-patients-with-late-life-depression-a-graph-theory-analysis
#1
Jeong-Hyeon Shin, Yu Hyun Um, Chang Uk Lee, Hyun Kook Lim, Joon-Kyung Seong
BACKGROUND: Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD. METHODS: In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients...
January 5, 2018: Journal of Affective Disorders
https://www.readbyqxmd.com/read/29353136/mutual-inhibition-of-lateral-inhibition-a-network-motif-for-an-elementary-computation-in-the-brain
#2
REVIEW
Minoru Koyama, Avinash Pujala
A series of classical studies in non-human primates has revealed the neuronal activity patterns underlying decision-making. However, the circuit mechanisms for such patterns remain largely unknown. Recent detailed circuit analyses in simpler neural systems have started to reveal the connectivity patterns underlying analogous processes. Here we review a few of these systems that share a particular connectivity pattern, namely mutual inhibition of lateral inhibition. Close examination of these systems suggests that this recurring connectivity pattern ('network motif') is a building block to enforce particular dynamics, which can be used not only for simple behavioral choice but also for more complex choices and other brain functions...
January 16, 2018: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/29352661/mechanistic-insights-into-the-genetics-of-affective-psychosis-from-prader-willi-syndrome
#3
REVIEW
Lucie C S Aman, Katherine E Manning, Joyce E Whittington, Anthony J Holland
Schizophrenia and bipolar disorder are common, severe, and disabling psychotic disorders, which are difficult to research. We argue that the genetically determined neurodevelopmental disorder Prader-Willi syndrome (PWS), which is associated with a high risk of affective psychotic illness, can provide a window into genetic mechanisms and associated neural pathways. People with PWS can all show non-psychotic psychopathology and problem behaviours, but the prevalence of psychotic illness differs markedly by genetic subtype; people with PWS due to chromosome 15 maternal uniparental disomy have higher prevalence of psychotic illness compared with patients with PWS due to 15q11-13 deletions of paternal origin...
January 15, 2018: Lancet Psychiatry
https://www.readbyqxmd.com/read/29352405/virus-particle-detection-by-convolutional-neural-network-in-transmission-electron-microscopy-images
#4
Eisuke Ito, Takaaki Sato, Daisuke Sano, Etsuko Utagawa, Tsuyoshi Kato
A new computational method for the detection of virus particles in transmission electron microscopy (TEM) images is presented. Our approach is to use a convolutional neural network that transforms a TEM image to a probabilistic map that indicates where virus particles exist in the image. Our proposed approach automatically and simultaneously learns both discriminative features and classifier for virus particle detection by machine learning, in contrast to existing methods that are based on handcrafted features that yield many false positives and require several postprocessing steps...
January 19, 2018: Food and Environmental Virology
https://www.readbyqxmd.com/read/29352285/deep-neural-networks-show-an-equivalent-and-often-superior-performance-to-dermatologists-in-onychomycosis-diagnosis-automatic-construction-of-onychomycosis-datasets-by-region-based-convolutional-deep-neural-network
#5
Seung Seog Han, Gyeong Hun Park, Woohyung Lim, Myoung Shin Kim, Jung Im Na, Ilwoo Park, Sung Eun Chang
Although there have been reports of the successful diagnosis of skin disorders using deep learning, unrealistically large clinical image datasets are required for artificial intelligence (AI) training. We created datasets of standardized nail images using a region-based convolutional neural network (R-CNN) trained to distinguish the nail from the background. We used R-CNN to generate training datasets of 49,567 images, which we then used to fine-tune the ResNet-152 and VGG-19 models. The validation datasets comprised 100 and 194 images from Inje University (B1 and B2 datasets, respectively), 125 images from Hallym University (C dataset), and 939 images from Seoul National University (D dataset)...
2018: PloS One
https://www.readbyqxmd.com/read/29352028/the-mysteries-of-remote-memory
#6
REVIEW
Zimbul Albo, Johannes Gräff
Long-lasting memories form the basis of our identity as individuals and lie central in shaping future behaviours that guide survival. Surprisingly, however, our current knowledge of how such memories are stored in the brain and retrieved, as well as the dynamics of the circuits involved, remains scarce despite seminal technical and experimental breakthroughs in recent years. Traditionally, it has been proposed that, over time, information initially learnt in the hippocampus is stored in distributed cortical networks...
March 19, 2018: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
https://www.readbyqxmd.com/read/29351717/prediction-of-protein-configurational-entropy-popcoen
#7
Martin Goethe, Jan Gleixner, Ignacio Fita, J Miguel Rubi
A knowledge-based method for configurational entropy prediction of proteins is presented which is extremely fast compared to previous approaches because it does not involve any kind of configurational sampling. Instead, the configurational entropy of a query fold is estimated by evaluating an artificial neural network which was trained on molecular-dynamics simulations of about 1000 proteins. The predicted entropy can be incorporated into a large class of protein software based on cost-function minimization/evaluation in which configurational entropy is currently neglected for performance reasons...
January 19, 2018: Journal of Chemical Theory and Computation
https://www.readbyqxmd.com/read/29351662/the-versatile-tanycyte-a-hypothalamic-integrator-of-reproduction-and-energy-metabolism
#8
Vincent Prevot, Bénédicte Dehouck, Ariane Sharif, Philippe Ciofi, Paolo Giacobini, Jerome Clasadonte
The fertility and survival of an individual rely on the ability of the periphery to promptly, effectively and reproducibly communicate with brain neural networks that control reproduction, food intake and energy homeostasis. Tanycytes, a specialized glial cell type lining the wall of the third ventricle in the median eminence of the hypothalamus, appear to act as the linchpin of these processes by dynamically controlling the secretion of neuropeptides into the portal vasculature by hypothalamic neurons and regulating blood-brain and blood-cerebrospinal fluid exchanges, both processes that depend on the ability of these cells to adapt their morphology to the physiological state of the individual...
January 17, 2018: Endocrine Reviews
https://www.readbyqxmd.com/read/29351656/evaluation-of-a-new-neutron-energy-spectrum-unfolding-code-based-on-an-adaptive-neuro-fuzzy-inference-system-anfis
#9
Seyed Abolfazl Hosseini, Iman Esmaili Paeen Afrakoti
The purpose of the present study was to reconstruct the energy spectrum of a poly-energetic neutron source using an algorithm developed based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is a kind of artificial neural network based on the Takagi-Sugeno fuzzy inference system. The ANFIS algorithm uses the advantages of both fuzzy inference systems and artificial neural networks to improve the effectiveness of algorithms in various applications such as modeling, control and classification. The neutron pulse height distributions used as input data in the training procedure for the ANFIS algorithm were obtained from the simulations performed by MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif University of Technology)...
January 17, 2018: Journal of Radiation Research
https://www.readbyqxmd.com/read/29351512/physiology-of-astroglia
#10
Alexei Verkhratsky, Maiken Nedergaard
Astrocytes are neural cells of ectodermal, neuroepithelial origin that provide for homeostasis and defense of the central nervous system (CNS). Astrocytes are highly heterogeneous in morphological appearance; they express a multitude of receptors, channels, and membrane transporters. This complement underlies their remarkable adaptive plasticity that defines the functional maintenance of the CNS in development and aging. Astrocytes are tightly integrated into neural networks and act within the context of neural tissue; astrocytes control homeostasis of the CNS at all levels of organization from molecular to the whole organ...
January 1, 2018: Physiological Reviews
https://www.readbyqxmd.com/read/29351281/automatic-labeling-of-molecular-biomarkers-of-immunohistochemistry-images-using-fully-convolutional-networks
#11
Fahime Sheikhzadeh, Rabab K Ward, Dirk van Niekerk, Martial Guillaud
This paper addresses the problem of quantifying biomarkers in multi-stained tissues based on the color and spatial information of microscopy images of the tissue. A deep learning-based method that can automatically localize and quantify the regions expressing biomarker(s) in any selected area on a whole slide image is proposed. The deep learning network, which we refer to as Whole Image (WI)-Net, is a fully convolutional network whose input is the true RGB color image of a tissue and output is a map showing the locations of each biomarker...
2018: PloS One
https://www.readbyqxmd.com/read/29351262/imu-to-segment-assignment-and-orientation-alignment-for-the-lower-body-using-deep-learning
#12
Tobias Zimmermann, Bertram Taetz, Gabriele Bleser
Human body motion analysis based on wearable inertial measurement units (IMUs) receives a lot of attention from both the research community and the and industrial community. This is due to the significant role in, for instance, mobile health systems, sports and human computer interaction. In sensor based activity recognition, one of the major issues for obtaining reliable results is the sensor placement/assignment on the body. For inertial motion capture (joint kinematics estimation) and analysis, the IMU-to-segment (I2S) assignment and alignment are central issues to obtain biomechanical joint angles...
January 19, 2018: Sensors
https://www.readbyqxmd.com/read/29351240/machine-learning-and-infrared-thermography-for-fiber-orientation-assessment-on-randomly-oriented-strands-parts
#13
Henrique Fernandes, Hai Zhang, Alisson Figueiredo, Fernando Malheiros, Luis Henrique Ignacio, Stefano Sfarra, Clemente Ibarra-Castanedo, Gilmar Guimaraes, Xavier Maldague
The use of fiber reinforced materials such as randomly-oriented strands has grown in recent years, especially for manufacturing of aerospace composite structures. This growth is mainly due to their advantageous properties: they are lighter and more resistant to corrosion when compared to metals and are more easily shaped than continuous fiber composites. The resistance and stiffness of these materials are directly related to their fiber orientation. Thus, efficient approaches to assess their fiber orientation are in demand...
January 19, 2018: Sensors
https://www.readbyqxmd.com/read/29351215/multi-sensor-data-integration-using-deep-learning-for-characterization-of-defects-in-steel-elements
#14
Grzegorz Psuj
Nowadays, there is a strong demand for inspection systems integrating both high sensitivity under various testing conditions and advanced processing allowing automatic identification of the examined object state and detection of threats. This paper presents the possibility of utilization of a magnetic multi-sensor matrix transducer for characterization of defected areas in steel elements and a deep learning based algorithm for integration of data and final identification of the object state. The transducer allows sensing of a magnetic vector in a single location in different directions...
January 19, 2018: Sensors
https://www.readbyqxmd.com/read/29350328/uyghur-text-matching-in-graphic-images-for-biomedical-semantic-analysis
#15
Shancheng Fang, Hongtao Xie, Zhineng Chen, Yizhi Liu, Yan Li
How to read Uyghur text from biomedical graphic images is a challenge problem due to the complex layout and cursive writing of Uyghur. In this paper, we propose a system that extracts text from Uyghur biomedical images, and matches the text in a specific lexicon for semantic analysis. The proposed system possesses following distinctive properties: first, it is an integrated system which firstly detects and crops the Uyghur text lines using a single fully convolutional neural network, and then keywords in the lexicon are matched by a well-designed matching network...
January 19, 2018: Neuroinformatics
https://www.readbyqxmd.com/read/29350187/multifractal-dynamics-of-resting-state-functional-connectivity-in-the-prefrontal-cortex
#16
Frigyes Samuel Racz, Peter Mukli, Zoltan Nagy, Andras Eke
Brain function is organized as a network of functional connections between different neuronal populations with connection strengths dynamically changing in time and space. Studies investigating functional connectivity (FC) usually follow a static approach when describing FC by considering the connectivity strengths constant, however a dynamic approach seems more reasonable, as this way the spatio-temporal dynamics of the underlying system can also be captured. Objective: The scale-free, i.e. fractal nature of neural dynamics is an inherent property of the nervous system...
January 19, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/29350183/integrated-biocircuits-engineering-functional-multicellular-circuits-and-devices
#17
Jordan Prox, Tory Smith, Chad Holl, Nick Chehade, Liang Guo
Novel in vitro platforms are currently revolutionizing the study and reconstruction of cellular circuitry to bypass the pertaining obstacles of data retrieval in vivo. While earlier approaches have provided great insights into culturing circuits in planar dissociated cell culture systems, the lack of full control over network activity and formation limits our understanding of their functionality. Thus, integrating various controllable parameters are required in creating a suitable microenvironment including cell patterning, highly-specified electrical and chemical stimuli, and rational circuit formation via logic functions...
January 19, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29349736/application-of-experimental-design-for-the-optimization-of-artificial-neural-network-based-water-quality-model-a-case-study-of-dissolved-oxygen-prediction
#18
Aleksandra Šiljić Tomić, Davor Antanasijević, Mirjana Ristić, Aleksandra Perić-Grujić, Viktor Pocajt
This paper presents an application of experimental design for the optimization of artificial neural network (ANN) for the prediction of dissolved oxygen (DO) content in the Danube River. The aim of this research was to obtain a more reliable ANN model that uses fewer monitoring records, by simultaneous optimization of the following model parameters: number of monitoring sites, number of historical monitoring data (expressed in years), and number of input water quality parameters used. Box-Behnken three-factor at three levels experimental design was applied for simultaneous spatial, temporal, and input variables optimization of the ANN model...
January 18, 2018: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/29349505/embracing-your-emotions-affective-state-impacts-lateralisation-of-human-embraces
#19
Julian Packheiser, Noemi Rook, Zeynep Dursun, Janne Mesenhöller, Alrescha Wenglorz, Onur Güntürkün, Sebastian Ocklenburg
Humans are highly social animals that show a wide variety of verbal and non-verbal behaviours to communicate social intent. One of the most frequently used non-verbal social behaviours is embracing, commonly used as an expression of love and affection. However, it can also occur in a large variety of social situations entailing negative (fear or sadness) or neutral emotionality (formal greetings). Embracing is also experienced from birth onwards in mother-infant interactions and is thus accompanying human social interaction across the whole lifespan...
January 18, 2018: Psychological Research
https://www.readbyqxmd.com/read/29349278/machine-learning-approaches-to-the-social-determinants-of-health-in-the-health-and-retirement-study
#20
Benjamin Seligman, Shripad Tuljapurkar, David Rehkopf
Background: Social and economic factors are important predictors of health and of recognized importance for health systems. However, machine learning, used elsewhere in the biomedical literature, has not been extensively applied to study relationships between society and health. We investigate how machine learning may add to our understanding of social determinants of health using data from the Health and Retirement Study. Methods: A linear regression of age and gender, and a parsimonious theory-based regression additionally incorporating income, wealth, and education, were used to predict systolic blood pressure, body mass index, waist circumference, and telomere length...
April 2018: SSM—Population Health
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