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https://www.readbyqxmd.com/read/29028191/deep-neural-networks-for-no-reference-and-full-reference-image-quality-assessment
#1
Sebastian Bosse, Dominique Maniry, Klaus-Robert Muller, Thomas Wiegand, Wojciech Samek
We present a deep neural network-based approach to image quality assessment (IQA). The network is trained endto- end and comprises 10 convolutional layers and 5 pooling layers for feature extraction, and 2 fully connected layers for regression, which makes it significantly deeper than related IQA models. Unique features of the proposed architecture are that (1) with slight adaptations it can be used in a no-reference (NR) as well as in a full-reference (FR) IQA setting and (2) it allows for joint learning of local quality and local weights, i...
October 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/29017140/lifelong-learning-of-human-actions-with-deep-neural-network-self-organization
#2
German I Parisi, Jun Tani, Cornelius Weber, Stefan Wermter
Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences...
September 20, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28994790/modelling-zika-virus-infection-of-the-developing-human-brain-in-vitro-using-stem-cell-derived-cerebral-organoids
#3
Max R Salick, Michael F Wells, Kevin Eggan, Ajamete Kaykas
The recent emergence of Zika virus (ZIKV) in susceptible populations has led to an abrupt increase in microcephaly and other neurodevelopmental conditions in newborn infants. While mosquitos are the main route of viral transmission, it has also been shown to spread via sexual contact and vertical mother-to-fetus transmission. In this latter case of transmission, due to the unique viral tropism of ZIKV, the virus is believed to predominantly target the neural progenitor cells (NPCs) of the developing brain. Here a method for modeling ZIKV infection, and the resulting microcephaly, that occur when human cerebral organoids are exposed to live ZIKV is described...
September 19, 2017: Journal of Visualized Experiments: JoVE
https://www.readbyqxmd.com/read/28968804/neural-substrate-for-metacognitive-accuracy-of-tactile-working-memory
#4
Juha Gogulski, Rasmus Zetter, Mikko Nyrhinen, Antti Pertovaara, Synnöve Carlson
The human prefrontal cortex (PFC) has been shown to be important for metacognition, the capacity to monitor and control one's own cognitive processes. Here we dissected the neural architecture of somatosensory metacognition using navigated single-pulse transcranial magnetic stimulation (TMS) to modulate tactile working memory (WM) processing. We asked subjects to perform tactile WM tasks and to give a confidence rating for their performance after each trial. We circumvented the challenge of interindividual variability in functional brain anatomy by applying TMS to two PFC areas that, according to tractography, were neurally connected with the primary somatosensory cortex (S1): one area in the superior frontal gyrus (SFG), another in the middle frontal gyrus (MFG)...
August 28, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28955272/recurrent-convolutional-neural-networks-a-better-model-of-biological-object-recognition
#5
Courtney J Spoerer, Patrick McClure, Nikolaus Kriegeskorte
Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28939991/when-three-is-greater-than-five-eeg-and-fmri-signatures-of-errors-in-numerical-and-physical-comparisons
#6
Ewa Beldzik, Aleksandra Domagalik, Magda Gawlowska, Tadeusz Marek, Justyna Mojsa-Kaja
Unravelling the neural mechanisms, which determine performance accuracy, is one of the key concepts in cognitive neuroscience. When compared to correct responses, shorter reaction times are commonly observed behavioural feature of errors committed in typical conflict tasks. Yet, little is known about the origins of this phenomenon. In this study, EEG and fMRI experiments were conducted using the numerical version of the Stroop paradigm, which yielded unique behavioural outcomes. Particularly, errors in numerical comparison had shorter reaction times than correct trials, whereas physical comparison resulted in the opposite pattern...
September 22, 2017: Brain Structure & Function
https://www.readbyqxmd.com/read/28932991/automated-reference-free-detection-of-motion-artifacts-in-magnetic-resonance-images
#7
Thomas Küstner, Annika Liebgott, Lukas Mauch, Petros Martirosian, Fabian Bamberg, Konstantin Nikolaou, Bin Yang, Fritz Schick, Sergios Gatidis
OBJECTIVES: Our objectives were to provide an automated method for spatially resolved detection and quantification of motion artifacts in MR images of the head and abdomen as well as a quality control of the trained architecture. MATERIALS AND METHODS: T1-weighted MR images of the head and the upper abdomen were acquired in 16 healthy volunteers under rest and under motion. Images were divided into overlapping patches of different sizes achieving spatial separation...
September 20, 2017: Magma
https://www.readbyqxmd.com/read/28917697/trajectories-of-brain-system-maturation-from-childhood-to-older-adulthood-implications-for-lifespan-cognitive-functioning
#8
Raluca Petrican, Margot J Taylor, Cheryl L Grady
The human brain's intrinsic functional architecture reflects behavioural history and can help elucidate the neural mechanisms underlying age-related cognitive changes. To probe this issue, we used resting state (N = 586) and behavioural (N = 255) data from a lifespan sample and tested the interactions among ten intrinsic neural systems, derived from a well-established whole-brain parcellation. Our results revealed three distinguishable profiles, whose expression strengthened with increasing age and which characterized developmental differences in connectivity within the ten systems, between networks thought to underlie cognitive control and non-control systems, and among the non-control networks...
September 14, 2017: NeuroImage
https://www.readbyqxmd.com/read/28901728/gaba-type-a-receptor-trafficking-and-the-architecture-of-synaptic-inhibition
#9
REVIEW
Joshua M Lorenz-Guertin, Tija C Jacob
Ubiquitous expression of GABA type A receptors (GABAA R) in the central nervous system establishes their central role in coordinating most aspects of neural function and development. Dysregulation of GABAergic neurotransmission manifests in a number of human health disorders and conditions that in certain cases can be alleviated by drugs targeting these receptors. Precise changes in the quantity or activity of GABAA Rs localized at the cell surface and at GABAergic postsynaptic sites directly impact the strength of inhibition...
September 13, 2017: Developmental Neurobiology
https://www.readbyqxmd.com/read/28901192/neuronal-cell-sheets-of-cortical-motor-neuron-phenotype-derived-from-human-ipscs
#10
Noboru Suzuki, Nagisa Arimitsu, Jun Shimizu, Kenji Takai, Chieko Hirotsu, Yuji Ueda, Sueshige Wakisaka, Naruyoshi Fujiwara, Tomoko Suzuki
Transplantation of stem cells that differentiate into more mature neural cells brings about functional improvement in preclinical studies of stroke. Previous transplant approaches in the diseased brain utilized injection of the cells in a cell suspension. In addition, neural stem cells were preferentially used for grafting. However, these cells had no specific relationship to the damaged tissue of stroke and brain injury patients. The injection of cells in a suspension destroyed the cell-cell interactions that are suggested to be important for promoting functional integrity of cortical motor neurons...
August 2017: Cell Transplantation
https://www.readbyqxmd.com/read/28898253/engineering-human-cell-spheroids-to-model-embryonic-tissue-fusion-in-vitro
#11
David G Belair, Cynthia J Wolf, Carmen Wood, Hongzu Ren, Rachel Grindstaff, William Padgett, Adam Swank, Denise MacMillan, Anna Fisher, Witold Winnik, Barbara D Abbott
Epithelial-mesenchymal interactions drive embryonic fusion events during development, and perturbations of these interactions can result in birth defects. Cleft palate and neural tube defects can result from genetic defects or environmental exposures during development, yet very little is known about the effect of chemical exposures on fusion events during human development because of a lack of relevant and robust human in vitro assays of developmental fusion behavior. Given the etiology and prevalence of cleft palate and the relatively simple architecture and composition of the embryonic palate, we sought to develop a three-dimensional culture system that mimics the embryonic palate and could be used to study fusion behavior in vitro using human cells...
2017: PloS One
https://www.readbyqxmd.com/read/28894461/a-grey-wolf-optimizer-for-modular-granular-neural-networks-for-human-recognition
#12
Daniela Sánchez, Patricia Melin, Oscar Castillo
A grey wolf optimizer for modular neural network (MNN) with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its effectiveness benchmark databases of ear, iris, and face biometric measures are used to perform tests and comparisons against other works. The design of a modular granular neural network (MGNN) consists in finding optimal parameters of its architecture; these parameters are the number of subgranules, percentage of data for the training phase, learning algorithm, goal error, number of hidden layers, and their number of neurons...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28887387/neural-architecture-of-selective-stopping-strategies-distinct-brain-activity-patterns-are-associated-with-attentional-capture-but-not-with-outright-stopping
#13
Alexandra Sebastian, Kora Rössler, Michael Wibral, Arian Mobascher, Klaus Lieb, Patrick Jung, Oliver Tüscher
In stimulus-selective stop-signal tasks, the salient stop signal needs attentional processing before genuine response inhibition is completed. Differential prefrontal involvement in attentional capture and response inhibition has been linked to the right inferior frontal junction (IFJ) and ventrolateral prefrontal cortex (VLPFC), respectively. Recently, it has been suggested that stimulus-selective stopping may be accomplished by the following different strategies: individuals may selectively inhibit their response only upon detecting a stop signal (independent discriminate then stop strategy) or unselectively whenever detecting a stop or attentional capture signal (stop then discriminate strategy)...
October 4, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28880190/learning-semantic-aligned-action-representation
#14
Bingbing Ni, Teng Li, Xiaokang Yang
A fundamental bottleneck for achieving highly discriminative action representation is that local motion/appearance features are usually not semantic aligned. Namely, a local feature, such as a motion vector or motion trajectory, does not possess any attribute that indicates which moving body part or operated object it is associated with. This mostly leads to global feature pooling/representation learning methods that are often too coarse. Inspired by the recent success of end-to-end (pixel-to-pixel) deep convolutional neural networks (DCNNs), in this paper, we first propose a DCNN architecture, which maps a human centric image region onto human body part response maps...
August 31, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28875035/classification-of-crystal-structure-using-a-convolutional-neural-network
#15
Woon Bae Park, Jiyong Chung, Jaeyoung Jung, Keemin Sohn, Satendra Pal Singh, Myoungho Pyo, Namsoo Shin, Kee-Sun Sohn
A deep machine-learning technique based on a convolutional neural network (CNN) is introduced. It has been used for the classification of powder X-ray diffraction (XRD) patterns in terms of crystal system, extinction group and space group. About 150 000 powder XRD patterns were collected and used as input for the CNN with no handcrafted engineering involved, and thereby an appropriate CNN architecture was obtained that allowed determination of the crystal system, extinction group and space group. In sharp contrast with the traditional use of powder XRD pattern analysis, the CNN never treats powder XRD patterns as a deconvoluted and discrete peak position or as intensity data, but instead the XRD patterns are regarded as nothing but a pattern similar to a picture...
July 1, 2017: IUCrJ
https://www.readbyqxmd.com/read/28871030/spatiochromatic-interactions-between-individual-cone-photoreceptors-in-the-human-retina
#16
William S Tuten, Wolf M Harmening, Ramkumar Sabesan, Austin Roorda, Lawrence C Sincich
A remarkable feature of human vision is that the retina and brain have evolved circuitry to extract useful spatial and spectral information from signals originating in a photoreceptor mosaic with trichromatic constituents that vary widely in their relative numbers and local spatial configurations. A critical early transformation applied to cone signals is horizontal-cell-mediated lateral inhibition, which imparts a spatially antagonistic surround to individual cone receptive fields, a signature inherited by downstream neurons and implicated in color signaling...
September 27, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28869034/plasticity-and-function-of-human-skeletal-muscle-in-relation-to-disuse-and-rehabilitation-influence-of-ageing-and-surgery
#17
Charlotte Suetta
In order to study the influence of disuse and aging on skeletal muscle homeostasis, different human models were employed. Effects of chronic disuse were investigated in elderly patients suffering from uni-lateral hip-osteoarthritis, whereas the effect of short-term disuse (4 and 14 days of unilateral lower limb immobilisation) was assessed in healthy young and old individuals. In summary, chronic muscle disuse in the elderly was associated with marked quantitative as well as qualitative neuromuscular impairments...
August 2017: Danish Medical Journal
https://www.readbyqxmd.com/read/28866543/deepeyes-progressive-visual-analytics-for-designing-deep-neural-networks
#18
Nicola Pezzotti, Thomas Hollt, Jan van Gemert, Boudewijn P F Lelieveldt, Elmar Eisemann, Anna Vilanova
Deep neural networks are now rivaling human accuracy in several pattern recognition problems. Compared to traditional classifiers, where features are handcrafted, neural networks learn increasingly complex features directly from the data. Instead of handcrafting the features, it is now the network architecture that is manually engineered. The network architecture parameters such as the number of layers or the number of filters per layer and their interconnections are essential for good performance. Even though basic design guidelines exist, designing a neural network is an iterative trial-and-error process that takes days or even weeks to perform due to the large datasets used for training...
August 29, 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/28794190/model-of-rhythmic-ball-bouncing-using-a-visually-controlled-neural-oscillator
#19
Guillaume Avrin, Isabelle Anne Siegler, Maria Makarov, Pedro Rodriguez-Ayerbe
The present paper investigates the sensory-driven modulations of Central Pattern Generators dynamics that can be expected to reproduce human behavior during rhythmic hybrid tasks. We propose a theoretical model of human sensorimotor behavior able to account for the observed data from the ball-bouncing task. The novel control architecture is composed of a Matsuoka neural oscillator parametrically controlled by a sensorimotor controller and coupled with the environment through visual sensory feedback. The architecture's ability to reproduce human-like performance during the ball-bouncing task in the presence of perturbations is quantified by comparison of simulated and recorded trials...
August 9, 2017: Journal of Neurophysiology
https://www.readbyqxmd.com/read/28756955/whole-brain-calcium-imaging-reveals-an-intrinsic-functional-network-in-drosophila
#20
Kevin Mann, Courtney L Gallen, Thomas R Clandinin
A long-standing goal of neuroscience has been to understand how computations are implemented across large-scale brain networks. By correlating spontaneous activity during "resting states" [1], studies of intrinsic brain networks in humans have demonstrated a correspondence with task-related activation patterns [2], relationships to behavior [3], and alterations in processes such as aging [4] and brain disorders [5], highlighting the importance of resting-state measurements for understanding brain function...
August 7, 2017: Current Biology: CB
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