keyword
MENU ▼
Read by QxMD icon Read
search

Neural networks

keyword
https://www.readbyqxmd.com/read/29783124/neural-organization-of-ventral-white-matter-tracts-parallels-the-initial-steps-of-reading-development-a-dti-tractography-study
#1
Jolijn Vanderauwera, Astrid De Vos, Stephanie J Forkel, Marco Catani, Jan Wouters, Maaike Vandermosten, Pol Ghesquière
Insight in the developmental trajectory of the neuroanatomical reading correlates is important to understand related cognitive processes and disorders. In adults, a dual pathway model has been suggested encompassing a dorsal phonological and a ventral orthographic white matter system. This dichotomy seems not present in pre-readers, and the specific role of ventral white matter in reading remains unclear. Therefore, the present longitudinal study investigated the relation between ventral white matter and cognitive processes underlying reading in children with a broad range of reading skills (n = 61)...
May 18, 2018: Brain and Language
https://www.readbyqxmd.com/read/29783122/bix-01294-promotes-the-differentiation-of-adipose-mesenchymal-stem-cells-into-adipocytes-and-neural-cells-in-arbas-cashmere-goats
#2
Qing Wang, Xiao Wang, Defang Lai, Jin Deng, Zhuang Hou, Hao Liang, Dongjun Liu
Chromatin remodeling plays an essential role in regulating gene transcription. BIX-01294 is a specific inhibitor of histone methyltransferase G9a, which is responsible for methylation of histone H3 lysine 9 (H3K9) that can also regulate DNA methylation and chromatin remodeling. The purpose of this study was to investigate the effects of BIX-01294 on the potential of goat adipose derived stem cells (gADSCs) to differentiate into adipocytes and neural cells. To accomplish this, BIX-01294 was used to treat gADSCs for 24 h, and the global level of DNA methylation as well as the expression of genes related to cell proliferation, apoptosis and pluripotency were detected...
May 14, 2018: Research in Veterinary Science
https://www.readbyqxmd.com/read/29783079/altered-neural-encoding-of-prediction-errors-in-assault-related-posttraumatic-stress-disorder
#3
Marisa C Ross, Jennifer K Lenow, Clinton D Kilts, Josh M Cisler
Posttraumatic stress disorder (PTSD) is widely associated with deficits in extinguishing learned fear responses, which relies on mechanisms of reinforcement learning (e.g., updating expectations based on prediction errors). However, the degree to which PTSD is associated with impairments in general reinforcement learning (i.e., outside of the context of fear stimuli) remains poorly understood. Here, we investigate brain and behavioral differences in general reinforcement learning between adult women with and without a current diagnosis of PTSD...
May 12, 2018: Journal of Psychiatric Research
https://www.readbyqxmd.com/read/29783076/disrupted-reward-and-cognitive-control-networks-contribute-to-anhedonia-in-depression
#4
Liang Gong, Cancan He, Haisan Zhang, Hongxing Zhang, Zhijun Zhang, Chunming Xie
Neuroimaging studies have identified that anhedonia, a core feature of major depressive disorder (MDD), is associated with dysfunction in reward and cognitive control processing. However, it is still not clear how the reward network (β-network) and the cognitive control network (δ-network) are linked to biased anhedonia in MDD patients. Sixty-eight MDD patients and 64 cognitively normal (CN) subjects underwent a resting-state functional magnetic resonance imaging scan. A 2*2 ANCOVA analysis was used to explore the differences in the nucleus accumbens-based, voxelwise functional connectivity (FC) between the groups...
May 12, 2018: Journal of Psychiatric Research
https://www.readbyqxmd.com/read/29783042/synchronization-of-hybrid-coupled-reaction-diffusion-neural-networks-with-time-delays-via-generalized-intermittent-control-with-spacial-sampled-data
#5
Binglong Lu, Haijun Jiang, Cheng Hu, Abdujelil Abdurahman
The exponential synchronization of hybrid coupled reaction-diffusion neural networks with time delays is discussed in this article. At first, a generalized intermittent control with spacial sampled-data is introduced, which is intermittent in time and data sampling in space. This type of control strategy not only can unify the traditional periodic intermittent control and the aperiodic case, but also can lower the update rate of the controller in both temporal and spatial domains. Next, based on the designed control protocol and the Lyapunov-Krasovskii functional approach, some novel and readily verified criteria are established to guarantee the exponential synchronization of the considered networks...
May 4, 2018: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/29782993/generalized-recurrent-neural-network-accommodating-dynamic-causal-modeling-for-functional-mri-analysis
#6
Yuan Wang, Yao Wang, Yvonne W Lui
Dynamic Causal Modeling (DCM) is an advanced biophysical model which explicitly describes the entire process from experimental stimuli to functional magnetic resonance imaging (fMRI) signals via neural activity and cerebral hemodynamics. To conduct a DCM study, one needs to represent the experimental stimuli as a compact vector-valued function of time, which is hard in complex tasks such as book reading and natural movie watching. Deep learning provides the state-of-the-art signal representation solution, encoding complex signals into compact dense vectors while preserving the essence of the original signals...
May 18, 2018: NeuroImage
https://www.readbyqxmd.com/read/29782510/individual-differences-in-learning-correlate-with-modulation-of-brain-activity-induced-by-transcranial-direct-current-stimulation
#7
Brian Falcone, Atsushi Wada, Raja Parasuraman, Daniel E Callan
Transcranial direct current stimulation (tDCS) has been shown to enhance cognitive performance on a variety of tasks. It is hypothesized that tDCS enhances performance by affecting task related cortical excitability changes in networks underlying or connected to the site of stimulation facilitating long term potentiation. However, many recent studies have called into question the reliability and efficacy of tDCS to induce modulatory changes in brain activity. In this study, our goal is to investigate the individual differences in tDCS induced modulatory effects on brain activity related to the degree of enhancement in performance, providing insight into this lack of reliability...
2018: PloS One
https://www.readbyqxmd.com/read/29782491/community-based-benchmarking-improves-spike-rate-inference-from-two-photon-calcium-imaging-data
#8
Philipp Berens, Jeremy Freeman, Thomas Deneux, Nicolay Chenkov, Thomas McColgan, Artur Speiser, Jakob H Macke, Srinivas C Turaga, Patrick Mineault, Peter Rupprecht, Stephan Gerhard, Rainer W Friedrich, Johannes Friedrich, Liam Paninski, Marius Pachitariu, Kenneth D Harris, Ben Bolte, Timothy A Machado, Dario Ringach, Jasmine Stone, Luke E Rogerson, Nicolas J Sofroniew, Jacob Reimer, Emmanouil Froudarakis, Thomas Euler, Miroslav Román Rosón, Lucas Theis, Andreas S Tolias, Matthias Bethge
In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing...
May 21, 2018: PLoS Computational Biology
https://www.readbyqxmd.com/read/29781102/hierarchical-deep-convolutional-neural-networks-combine-spectral-and-spatial-information-for-highly-accurate-raman-microscopy-based-cytopathology
#9
Sascha D Krauß, Raphael Roy, Hesham K Yosef, Tatjana Lechtonen, Samir F El-Mashtoly, Klaus Gerwert, Axel Mosig
Hierarchical variants of so-called deep convolutional neural networks (DCNNs) have facilitated breakthrough results for numerous pattern recognition tasks in recent years. We assess the potential of these novel whole-image classifiers for Raman microscopy based cytopathology. Conceptually, DCNNs facilitate a flexible combination of spectral and spatial information for classifying cellular images as healthy or cancer affected cells. As we demonstrate, this conceptual advantage translates into practice, where DCNNs exceed the accuracy of both conventional classifiers based on pixel spectra as well as classifiers based on morphological features extracted from Raman microscopic images...
May 21, 2018: Journal of Biophotonics
https://www.readbyqxmd.com/read/29780410/quantification-of-upper-limb-motor-recovery-and-eeg-power-changes-after-robot-assisted-bilateral-arm-training-in-chronic-stroke-patients-a-prospective-pilot-study
#10
Marialuisa Gandolfi, Emanuela Formaggio, Christian Geroin, Silvia Francesca Storti, Ilaria Boscolo Galazzo, Marta Bortolami, Leopold Saltuari, Alessandro Picelli, Andreas Waldner, Paolo Manganotti, Nicola Smania
Background: Bilateral arm training (BAT) has shown promise in expediting progress toward upper limb recovery in chronic stroke patients, but its neural correlates are poorly understood. Objective: To evaluate changes in upper limb function and EEG power after a robot-assisted BAT in chronic stroke patients. Methods: In a within-subject design, seven right-handed chronic stroke patients with upper limb paresis received 21 sessions (3 days/week) of the robot-assisted BAT...
2018: Neural Plasticity
https://www.readbyqxmd.com/read/29780407/deep-learning-methods-for-underwater-target-feature-extraction-and-recognition
#11
Gang Hu, Kejun Wang, Yuan Peng, Mengran Qiu, Jianfei Shi, Liangliang Liu
The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network...
2018: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/29780198/sva-shape-variation-analyzer
#12
Priscille de Dumast, Clement Mirabel, Beatriz Paniagua, Marilia Yatabe, Antonio Ruellas, Nina Tubau, Martin Styner, Lucia Cevidanes, Juan C Prieto
Temporo-mandibular osteo arthritis (TMJ OA) is characterized by progressive cartilage degradation and subchondral bone remodeling. The causes of this pathology remain unclear. Current research efforts are concentrated in finding new biomarkers that will help us understand disease progression and ultimately improve the treatment of the disease. In this work, we present Shape Variation Analyzer (SVA), the goal is to develop a noninvasive technique to provide information about shape changes in TMJ OA. SVA uses neural networks to classify morphological variations of 3D models of the mandibular condyle...
February 2018: Proceedings of SPIE
https://www.readbyqxmd.com/read/29780197/trafic-fiber-tract-classification-using-deep-learning
#13
Prince D Ngattai Lam, Gaetan Belhomme, Jessica Ferrall, Billie Patterson, Martin Styner, Juan C Prieto
We present TRAFIC, a fully automated tool for the labeling and classification of brain fiber tracts. TRAFIC classifies new fibers using a neural network trained using shape features computed from previously traced and manually corrected fiber tracts. It is independent from a DTI Atlas as it is applied to already traced fibers. This work is motivated by medical applications where the process of extracting fibers from a DTI atlas, or classifying fibers manually is time consuming and requires knowledge about brain anatomy...
February 2018: Proceedings of SPIE
https://www.readbyqxmd.com/read/29779940/encoding-of-articulatory-kinematic-trajectories-in-human-speech-sensorimotor-cortex
#14
Josh Chartier, Gopala K Anumanchipalli, Keith Johnson, Edward F Chang
When speaking, we dynamically coordinate movements of our jaw, tongue, lips, and larynx. To investigate the neural mechanisms underlying articulation, we used direct cortical recordings from human sensorimotor cortex while participants spoke natural sentences that included sounds spanning the entire English phonetic inventory. We used deep neural networks to infer speakers' articulator movements from produced speech acoustics. Individual electrodes encoded a diversity of articulatory kinematic trajectories (AKTs), each revealing coordinated articulator movements toward specific vocal tract shapes...
May 8, 2018: Neuron
https://www.readbyqxmd.com/read/29779744/exploring-collective-experience-in-watching-dance-through-intersubject-correlation-and-functional-connectivity-of-fmri-brain-activity
#15
Frank E Pollick, Staci Vicary, Katie Noble, Naree Kim, Seonhee Jang, Catherine J Stevens
How the brain contends with naturalistic viewing conditions when it must cope with concurrent streams of diverse sensory inputs and internally generated thoughts is still largely an open question. In this study, we used fMRI to record brain activity while a group of 18 participants watched an edited dance duet accompanied by a soundtrack. After scanning, participants performed a short behavioral task to identify neural correlates of dance segments that could later be recalled. Intersubject correlation (ISC) analysis was used to identify the brain regions correlated among observers, and the results of this ISC map were used to define a set of regions for subsequent analysis of functional connectivity...
2018: Progress in Brain Research
https://www.readbyqxmd.com/read/29779670/a-connectome-wide-functional-signature-of-transdiagnostic-risk-for-mental-illness
#16
Maxwell L Elliott, Adrienne Romer, Annchen R Knodt, Ahmad R Hariri
BACKGROUND: High rates of comorbidity, shared risk, and overlapping therapeutic mechanisms have led psychopathology research toward transdiagnostic dimensional investigations of clustered symptoms. One influential framework accounts for these transdiagnostic phenomena through a single general factor, sometimes referred to as the "p" factor, associated with risk for all common forms of mental illness. METHODS: We build on previous research identifying unique structural neural correlates of the p factor by conducting a data-driven analysis of connectome-wide intrinsic functional connectivity (n = 605)...
April 10, 2018: Biological Psychiatry
https://www.readbyqxmd.com/read/29779433/age-differences-in-the-neural-response-to-negative-feedback
#17
Holly J Bowen, Cheryl L Grady, Julia Spaniol
Affective processing is one domain that remains relatively intact in healthy aging. Investigations into the neural responses associated with reward anticipation have revealed that older and younger adults recruit the same midbrain reward regions, but other evidence suggests this recruitment may differ depending on the valence (gain, loss) of the incentive cue. The goal of the current study was to examine functional covariance during gain and loss feedback in younger and healthy older adults. A group of 15 older adults (mean age = 68...
May 21, 2018: Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition
https://www.readbyqxmd.com/read/29778931/monitoring-tool-usage-in-surgery-videos-using-boosted-convolutional-and-recurrent-neural-networks
#18
Hassan Al Hajj, Mathieu Lamard, Pierre-Henri Conze, Béatrice Cochener, Gwenolé Quellec
This paper investigates the automatic monitoring of tool usage during a surgery, with potential applications in report generation, surgical training and real-time decision support. Two surgeries are considered: cataract surgery, the most common surgical procedure, and cholecystectomy, one of the most common digestive surgeries. Tool usage is monitored in videos recorded either through a microscope (cataract surgery) or an endoscope (cholecystectomy). Following state-of-the-art video analysis solutions, each frame of the video is analyzed by convolutional neural networks (CNNs) whose outputs are fed to recurrent neural networks (RNNs) in order to take temporal relationships between events into account...
May 9, 2018: Medical Image Analysis
https://www.readbyqxmd.com/read/29778673/classifying-medical-relations-in-clinical-text-via-convolutional-neural-networks
#19
Bin He, Yi Guan, Rui Dai
Deep learning research on relation classification has achieved solid performance in the general domain. This study proposes a convolutional neural network (CNN) architecture with a multi-pooling operation for medical relation classification on clinical records and explores a loss function with a category-level constraint matrix. Experiments using the 2010 i2b2/VA relation corpus demonstrate these models, which do not depend on any external features, outperform previous single-model methods and our best model is competitive with the existing ensemble-based method...
May 16, 2018: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29778488/the-2016-bernard-sachs-lecture-timing-in-morphogenesis-and-genetic-gradients-during-normal-development-and-in-malformations-of-the-nervous-system
#20
REVIEW
Harvey B Sarnat
Nervous system development is quadradimensional. Both normal ontogenesis and developmental malformations are explained in the context of the fourth dimension, timing. Timing of the onset of either the genetic expression of a mutation or an epigenetic event that may be teratogenic is primordial in determining morphogenesis and the forms of malformations with their functional consequences. Multiple genotypes may cause similar phenotypes or a single genotype with different degrees of retained normal genetic expression may result in variable phenotypes...
March 30, 2018: Pediatric Neurology
keyword
keyword
15175
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"