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https://www.readbyqxmd.com/read/28212113/age-and-gender-dependency-of-physiological-networks-in-sleep
#1
Dagmar Krefting, Christoph Jansen, Thomas Penzel, Fang Han, Jan Kantelhardt
Recently, time delay stability analysis of biosignals has been successfully applied as a multivariate time series analysis method to assess the human physiological network in young adults. The degree of connectivity between different network nodes is described by the so-called link strength. Based on polysomnographic recordings (PSGs), it could be shown that the network changes with the sleep stage. Here, we apply the method to a large set of healthy controls spanning six decades of age. As it is well known, that the overall sleep architecture is dependent both on age and on gender, we particularly address the question, if these changes are also found in the network dynamics...
February 17, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28186883/detection-and-localization-of-robotic-tools-in-robot-assisted-surgery-videos-using-deep-neural-networks-for-region-proposal-and-detection
#2
Duygu Sarikaya, Jason Corso, Khurshid Guru
Video understanding of robot-assisted surgery (RAS) videos is an active research area. Modeling the gestures and skill level of surgeons presents an interesting problem. The insights drawn may be applied in effective skill acquisition, objective skill assessment, real-time feedback, and human-robot collaborative surgeries. We propose a solution to the tool detection and localization open problem in RAS video understanding, using a strictly computer vision approach and the recent advances of deep learning. We propose an architecture using multimodal convolutional neural networks for fast detection and localization of tools in RAS videos...
February 8, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28179882/connecting-artificial-brains-to-robots-in-a-comprehensive-simulation-framework-the-neurorobotics-platform
#3
Egidio Falotico, Lorenzo Vannucci, Alessandro Ambrosano, Ugo Albanese, Stefan Ulbrich, Juan Camilo Vasquez Tieck, Georg Hinkel, Jacques Kaiser, Igor Peric, Oliver Denninger, Nino Cauli, Murat Kirtay, Arne Roennau, Gudrun Klinker, Axel Von Arnim, Luc Guyot, Daniel Peppicelli, Pablo Martínez-Cañada, Eduardo Ros, Patrick Maier, Sandro Weber, Manuel Huber, David Plecher, Florian Röhrbein, Stefan Deser, Alina Roitberg, Patrick van der Smagt, Rüdiger Dillman, Paul Levi, Cecilia Laschi, Alois C Knoll, Marc-Oliver Gewaltig
Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28179553/mouth-and-voice-a-relationship-between-visual-and-auditory-preference-in-the-human-superior-temporal-sulcus
#4
Lin L Zhu, Michael S Beauchamp
Cortex in and around the human posterior superior temporal sulcus (pSTS) is known to be critical for speech perception. The pSTS responds to both the visual modality (especially biological motion) and the auditory modality (especially human voices). Using fMRI in single subjects with no spatial smoothing, we show that visual and auditory selectivity are linked. Regions of the pSTS were identified that preferred visually-presented moving mouths (presented in isolation or as part of a whole face) or moving eyes...
February 8, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28158264/recognition-of-prokaryotic-and-eukaryotic-promoters-using-convolutional-deep-learning-neural-networks
#5
Ramzan Kh Umarov, Victor V Solovyev
Accurate computational identification of promoters remains a challenge as these key DNA regulatory regions have variable structures composed of functional motifs that provide gene-specific initiation of transcription. In this paper we utilize Convolutional Neural Networks (CNN) to analyze sequence characteristics of prokaryotic and eukaryotic promoters and build their predictive models. We trained a similar CNN architecture on promoters of five distant organisms: human, mouse, plant (Arabidopsis), and two bacteria (Escherichia coli and Bacillus subtilis)...
2017: PloS One
https://www.readbyqxmd.com/read/28157638/probing-human-brain-evolution-and-development-in-organoids
#6
REVIEW
Stefano L Giandomenico, Madeline A Lancaster
Expansion of the neocortex is thought to underpin the higher cognitive abilities of a number of mammalian lineages, such as cetaceans, elephants, and primates, with humans exhibiting a particularly enlarged and dense cerebral cortex. However, the evolutionary and developmental mechanisms that led to this expansion are not well-understood and limited to correlative observations. Historically, this has been due to technical and ethical limitations owing to the intractability of various species for functional studies...
January 31, 2017: Current Opinion in Cell Biology
https://www.readbyqxmd.com/read/28130264/vagal-innervation-is-required-for-pulmonary-function-phenotype-in-htr4-mice
#7
John House, Cody E Nichols, Huiling Li, Christina Brandenberger, Rohan Virgincar, Laura Miller, Bastiaan Driehuys, Darryl C Zeldin, Stephanie London
Human genome-wide association studies (GWASs) have identified over 50 loci associated with pulmonary function and related phenotypes, yet follow-up studies to determine causal genes or variants are rare. Single nucleotide polymorphisms (SNPs) in serotonin receptor 4 (HTR4) are associated with human pulmonary function in genome-wide association studies and follow-up animal work has demonstrated that Htr4 is causally associated with pulmonary function in mice, although the precise mechanisms were not identified...
January 27, 2017: American Journal of Physiology. Lung Cellular and Molecular Physiology
https://www.readbyqxmd.com/read/28126336/modular-neuromuscular-control-of-human-locomotion-by-central-pattern-generator
#8
Seyyed Arash Haghpanah, Farzam Farahmand, Hassan Zohoor
The central pattern generators (CPG) in the spinal cord are thought to be responsible for producing the rhythmic motor patterns during rhythmic activities. For locomotor tasks, this involves much complexity, due to a redundant system of muscle actuators with a large number of highly nonlinear muscles. This study proposes a reduced neural control strategy for the CPG, based on modular organization of the co-active muscles, i.e., muscle synergies. Four synergies were extracted from the EMG data of the major leg muscles of two subjects, during two gait trials each, using non-negative matrix factorization algorithm...
January 19, 2017: Journal of Biomechanics
https://www.readbyqxmd.com/read/28123020/dynamic-reconfiguration-of-visuomotor-related-functional-connectivity-networks
#9
Andrea Brovelli, Jean-Michel Badier, Francesca Bonini, Fabrice Bartolomei, Olivier Coulon, Guillaume Auzias
: Cognitive functions arise from the coordination of large-scale brain networks. However, the principles governing interareal functional connectivity dynamics (FCD) remain elusive. Here, we tested the hypothesis that human executive functions arise from the dynamic interplay of multiple networks. To do so, we investigated FCD mediating a key executing function, known as arbitrary visuomotor mapping, using brain connectivity analyses of high-gamma activity recorded using MEG and intracranial EEG...
January 25, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28120807/the-speed-curvature-power-law-in-drosophila-larval-locomotion
#10
Myrka Zago, Francesco Lacquaniti, Alex Gomez-Marin
We report the discovery that the locomotor trajectories of Drosophila larvae follow the power-law relationship between speed and curvature previously found in the movements of human and non-human primates. Using high-resolution behavioural tracking in controlled but naturalistic sensory environments, we tested the law in maggots tracing different trajectory types, from reaching-like movements to scribbles. For most but not all flies, we found that the law holds robustly, with an exponent close to three-quarters rather than to the usual two-thirds found in almost all human situations, suggesting dynamic effects adding on purely kinematic constraints...
October 2016: Biology Letters
https://www.readbyqxmd.com/read/28120318/the-human-infant-brain-a-neural-architecture-able-to-learn-language
#11
Ghislaine Dehaene-Lambertz
To understand the type of neural computations that may explain how human infants acquire their native language in only a few months, the study of their neural architecture is necessary. The development of brain imaging techniques has opened the possibilities of studying human infants without discomfort, and although these studies are still sparse, several characteristics are noticeable in the human infant's brain: first, parallel and hierarchical processing pathways are observed before intense exposure to speech with an efficient temporal coding in the left hemisphere and, second, frontal regions are involved from the start in infants' cognition...
January 24, 2017: Psychonomic Bulletin & Review
https://www.readbyqxmd.com/read/28113278/a-comprehensive-study-on-cross-view-gait-based-human-identification-with-deep-cnns
#12
Zifeng Wu, Yongzhen Huang, Liang Wang, Xiaogang Wang, Tieniu Tan
This paper studies an approach to gait based human identification via similarity learning by deep convolutional neural networks (CNNs).With a pretty small group of labeled multi-view human walking videos, we can train deep networks to recognize the most discriminative changes of gait patterns which suggest the change of human identity. To the best of our knowledge, this is the first work based on deep CNNs for gait recognition in the literature. Here, we provide an extensive empirical evaluation in terms of various scenarios, namely, cross-view and cross-walkingcondition, with different preprocessing approaches and network architectures...
March 23, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28111643/mathematical-modeling-and-evaluation-of-human-motions-in-physical-therapy-using-mixture-density-neural-networks
#13
A Vakanski, J M Ferguson, S Lee
OBJECTIVE: The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient's exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient's physician with recommendations for improvement...
December 2016: J Physiother Phys Rehabil
https://www.readbyqxmd.com/read/28111188/the-emergence-of-functional-architecture-during-early-brain-development
#14
Kristin Keunen, Serena J Counsell, Manon J N L Benders
Early human brain development constitutes a sequence of intricate processes resulting in the ontogeny of functionally operative neural circuits. Developmental trajectories of early brain network formation are genetically programmed and can be modified by epigenetic and environmental influences. Such alterations may exert profound effects on neurodevelopment, potentially persisting throughout the lifespan. This review focuses on the critical period of fetal and early postnatal brain development. Here we collate findings from neuroimaging studies, with a particular focus on functional MRI research that interrogated early brain network development in both health and high-risk or disease states...
January 20, 2017: NeuroImage
https://www.readbyqxmd.com/read/28093479/paired-stimulation-for-spike-timing-dependent-plasticity-in-primate-sensorimotor-cortex
#15
Stephanie C Seeman, Brian J Mogen, Eberhard E Fetz, Steve I Perlmutter
: Classic studies in vitro have described spike-timing dependent plasticity (STDP) at a synapse: the connection from neuron A to neuron B is strengthened (or weakened) when A fires before (or after) B within an optimal time window. Accordingly, more recent in vivo works have demonstrated behavioral effects consistent with an STDP mechanism; however many relied on single-unit recordings. The ability to modify cortical connections becomes useful in the context of injury when connectivity, and associated behavior, is compromised...
January 16, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28089676/multimodal-evaluation-of-the-amygdala-s-functional-connectivity
#16
Rebecca Kerestes, Henry W Chase, Mary L Phillips, Cecile D Ladouceur, Simon B Eickhoff
The amygdala is one of the most extensively studied human brain regions and undisputedly plays a central role in many psychiatric disorders. However, an outstanding question is whether connectivity of amygdala subregions, specifically the centromedial (CM), laterobasal (LB) and superficial (SF) nuclei, are modulated by brain state (i.e., task vs. rest). Here, using a multimodal approach, we directly compared meta-analytic connectivity modeling (MACM) and specific co-activation likelihood estimation (SCALE)-derived estimates of CM, LB and SF task-based co-activation to the functional connectivity of these nuclei as assessed by resting state fmri (rs-fmri)...
January 9, 2017: NeuroImage
https://www.readbyqxmd.com/read/28071765/neural-codes-of-seeing-architectural-styles
#17
Heeyoung Choo, Jack L Nasar, Bardia Nikrahei, Dirk B Walther
Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people's visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1...
January 10, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28059233/cytopathological-image-analysis-using-deep-learning-networks-in-microfluidic-microscopy
#18
G Gopakumar, K Hari Babu, Deepak Mishra, Sai Siva Gorthi, Gorthi R K Sai Subrahmanyam
Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing process. Several neural network architectures were designed to provide human expertise to machines. In this paper, we explore and propose the feasibility of using deep-learning networks for cytopathologic analysis by performing the classification of three important unlabeled, unstained leukemia cell lines (K562, MOLT, and HL60)...
January 1, 2017: Journal of the Optical Society of America. A, Optics, Image Science, and Vision
https://www.readbyqxmd.com/read/28057725/the-neuro-computational-architecture-of-value-based-selection-in-the-human-brain
#19
Philippe Domenech, Jérôme Redouté, Etienne Koechlin, Jean-Claude Dreher
Current neural models of value-based decision-making consider choices as a 2-stage process, proceeding from the "valuation" of each option under consideration to the "selection" of the best option on the basis of their subjective values. However, little is known about the computational mechanisms at play at the selection stage and its implementation in the human brain. Here, we used drift-diffusion models combined with model-based functional magnetic resonance imaging, effective connectivity, and multivariate pattern analysis to characterize the neuro-computational architecture of value-based decisions...
January 4, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/27993674/beyond-the-ffa-brain-behavior-correspondences-in-face-recognition-abilities
#20
Daniel B Elbich, Suzanne Scherf
Despite the thousands of papers investigating the neural basis of face perception in both humans and non-human primates, very little is known about how activation within this neural architecture relates to face processing behavior. Here, we investigated individual differences in brain-behavior correspondences within both core and extended regions of the face-processing system in healthy typically developing adults. To do so, we employed a set of behavioral and neural measures to capture a multifaceted perspective on assessing these brain-behavior relations...
February 15, 2017: NeuroImage
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