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https://www.readbyqxmd.com/read/29675882/diffusion-tensor-imaging-using-multiple-coils-for-mouse-brain-connectomics
#1
John C Nouls, Alexandra Badea, Robert B J Anderson, Gary P Cofer, G Allan Johnson
The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non-destructively and three-dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7-T preclinical scanner, we present a novel two-coil system in which each coil is shielded, placed off-isocenter along the axis of the magnet and connected to a receiver circuit of the scanner...
April 19, 2018: NMR in Biomedicine
https://www.readbyqxmd.com/read/29675776/pluripotent-stem-cells-for-retinal-tissue-engineering-current-status-and-future-prospects
#2
REVIEW
Ratnesh Singh, Oscar Cuzzani, François Binette, Hal Sternberg, Michael D West, Igor O Nasonkin
The retina is a very fine and layered neural tissue, which vitally depends on the preservation of cells, structure, connectivity and vasculature to maintain vision. There is an urgent need to find technical and biological solutions to major challenges associated with functional replacement of retinal cells. The major unmet challenges include generating sufficient numbers of specific cell types, achieving functional integration of transplanted cells, especially photoreceptors, and surgical delivery of retinal cells or tissue without triggering immune responses, inflammation and/or remodeling...
April 19, 2018: Stem Cell Reviews
https://www.readbyqxmd.com/read/29670045/what-we-know-about-the-brain-structure-function-relationship
#3
REVIEW
Karla Batista-García-Ramó, Caridad Ivette Fernández-Verdecia
How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied...
April 18, 2018: Behavioral Sciences
https://www.readbyqxmd.com/read/29614253/understanding-the-mechanisms-of-familiar-voice-identity-recognition-in-the-human-brain
#4
Corrina Maguinness, Claudia Roswandowitz, Katharina Von Kriegstein
Humans have a remarkable skill for voice-identity recognition: most of us can remember many voices that surround us as 'unique'. In this review, we explore the computational and neural mechanisms which may support our ability to represent and recognise a unique voice-identity. We examine the functional architecture of voice-sensitive regions in the superior temporal gyrus/sulcus, and bring together findings on how these regions may interact with each other, and additional face-sensitive regions, to support voice-identity processing...
March 31, 2018: Neuropsychologia
https://www.readbyqxmd.com/read/29609054/fully-automatic-detection-and-segmentation-of-abdominal-aortic-thrombus-in-post-operative-cta-images-using-deep-convolutional-neural-networks
#5
Karen López-Linares, Nerea Aranjuelo, Luis Kabongo, Gregory Maclair, Nerea Lete, Mario Ceresa, Ainhoa García-Familiar, Iván Macía, Miguel A González Ballester
Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is essential to evaluate the progress of the patient and detect complications. In this context, accurate quantification of post-operative thrombus volume is required. However, a proper evaluation is hindered by the lack of automatic, robust and reproducible thrombus segmentation algorithms. We propose a new fully automatic approach based on Deep Convolutional Neural Networks (DCNN) for robust and reproducible thrombus region of interest detection and subsequent fine thrombus segmentation...
March 27, 2018: Medical Image Analysis
https://www.readbyqxmd.com/read/29603278/deep-nets-vs-expert-designed-features-in-medical-physics-an-imrt-qa-case-study
#6
Yannet Interian, Vincent Rideout, Vasant P Kearney, Gennatas Efstathios, Olivier Morin, Joey Cheung, Timothy Solberg, Gilmer Valdes
PURPOSE: To compare the performance of Deep Neural Networks against a technique designed by domain experts in the prediction of gamma passing rates for Intensity Modulated Radiation Therapy Quality Assurance (IMRT QA). METHOD: 498 IMRT plans across all treatment sites were planned in Eclipse version 11 and delivered using a dynamic sliding window technique on Clinac iX or TrueBeam Linacs. Measurements were performed using a commercial 2D diode array, and passing rates for 3%/3 mm local dose/distance-to-agreement (DTA) were recorded...
March 30, 2018: Medical Physics
https://www.readbyqxmd.com/read/29593053/functional-organization-of-the-temporal-parietal-junction-for-theory-of-mind-in-preverbal-infants-a-near-infrared-spectroscopy-study
#7
Daniel C Hyde, Charline E Simon, Fransisca Ting, Julia Nikolaeva
Successful human social life requires imagining what others believe or think to understand and predict behavior. This ability, often referred to as theory of mind, reliably engages a specialized network of temporal and prefrontal brain regions in older children and adults, including selective recruitment of temporal-parietal junction (TPJ). To date, how and when this specialized brain organization for ToM arises is unknown due to limitations in functional neuroimaging at younger ages. Here we employed the emerging technique of functional near-infrared spectroscopy (fNIRS) to measure the functional brain response across the parietal, temporal, and prefrontal regions in 7-month old male and female infants as they viewed different video scenarios of a person searching for a hidden object...
March 28, 2018: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/29570059/an-extreme-learning-machine-based-neuromorphic-tactile-sensing-system-for-texture-recognition
#8
Mahdi Rasouli, Yi Chen, Arindam Basu, Sunil L Kukreja, Nitish V Thakor
Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity...
April 2018: IEEE Transactions on Biomedical Circuits and Systems
https://www.readbyqxmd.com/read/29566671/completing-sparse-and-disconnected-protein-protein-network-by-deep-learning
#9
Lei Huang, Li Liao, Cathy H Wu
BACKGROUND: Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of cellular and intracellular processes. Recently, an increasing number of computational methods have shifted from pair-wise prediction to network level prediction. Many of the existing network level methods predict PPIs under the assumption that the training network should be connected. However, this assumption greatly affects the prediction power and limits the application area because the current golden standard PPI networks are usually very sparse and disconnected...
March 22, 2018: BMC Bioinformatics
https://www.readbyqxmd.com/read/29561236/functional-specificity-and-sex-differences-in-the-neural-circuits-supporting-the-inhibition-of-automatic-imitation
#10
Kohinoor M Darda, Emily E Butler, Richard Ramsey
Humans show an involuntary tendency to copy other people's actions. Although automatic imitation builds rapport and affiliation between individuals, we do not copy actions indiscriminately. Instead, copying behaviors are guided by a selection mechanism, which inhibits some actions and prioritizes others. To date, the neural underpinnings of the inhibition of automatic imitation and differences between the sexes in imitation control are not well understood. Previous studies involved small sample sizes and low statistical power, which produced mixed findings regarding the involvement of domain-general and domain-specific neural architectures...
March 21, 2018: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/29551969/detecting-large-scale-brain-networks-using-eeg-impact-of-electrode-density-head-modeling-and-source-localization
#11
Quanying Liu, Marco Ganzetti, Nicole Wenderoth, Dante Mantini
Resting state networks (RSNs) in the human brain were recently detected using high-density electroencephalography (hdEEG). This was done by using an advanced analysis workflow to estimate neural signals in the cortex and to assess functional connectivity (FC) between distant cortical regions. FC analyses were conducted either using temporal (tICA) or spatial independent component analysis (sICA). Notably, EEG-RSNs obtained with sICA were very similar to RSNs retrieved with sICA from functional magnetic resonance imaging data...
2018: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/29522900/deep-learning-and-its-applications-in-biomedicine
#12
REVIEW
Chensi Cao, Feng Liu, Hai Tan, Deshou Song, Wenjie Shu, Weizhong Li, Yiming Zhou, Xiaochen Bo, Zhi Xie
Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the understanding of human health and disease. Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data. The aim of this paper is to provide an overview of deep learning techniques and some of the state-of-the-art applications in the biomedical field...
March 6, 2018: Genomics, Proteomics & Bioinformatics
https://www.readbyqxmd.com/read/29497182/rebuilding-the-brain-with-psychotherapy
#13
REVIEW
Savita Malhotra, Swapnajeet Sahoo
Brain has been the most fascinating and mysterious organ of the human body. Researchers have tried to explore into each and every function of different parts of the human brain linking it up with various mental and neural processes, some of which are phylogenetically shared and many are unshared. It has been hypothesized that brain is built during development and can be rebuilt during psychotherapy. Recent research in neuroscience of socioemotional cognition, developmental neuroscience, coupled with advances in investigative techniques of brain functions has provided tremendous opportunities for the study of brain and the mind...
October 2017: Indian Journal of Psychiatry
https://www.readbyqxmd.com/read/29496144/epigenetic-analysis-of-human-postmortem-brain-tissue
#14
Sumaiya A Islam, Alexandre A Lussier, Michael S Kobor
Epigenomic profiles have been mapped across a broad range of brain regions and developmental contexts in postmortem human brain tissues, illuminating our understanding of epigenetic regulation in neural function and plasticity across the life course. Importantly, disease-associated epigenetic alterations in postmortem brain have provided compelling insights into the gene-regulatory architecture underlying neurobiologic disease susceptibility and pathogenesis. However, the use of postmortem brain tissues for molecular analyses warrants careful consideration of key technical and biologic factors that may confound epigenetic analyses...
2018: Handbook of Clinical Neurology
https://www.readbyqxmd.com/read/29491478/axondeepseg-automatic-axon-and-myelin-segmentation-from-microscopy-data-using-convolutional-neural-networks
#15
Aldo Zaimi, Maxime Wabartha, Victor Herman, Pierre-Louis Antonsanti, Christian S Perone, Julien Cohen-Adad
Segmentation of axon and myelin from microscopy images of the nervous system provides useful quantitative information about the tissue microstructure, such as axon density and myelin thickness. This could be used for instance to document cell morphometry across species, or to validate novel non-invasive quantitative magnetic resonance imaging techniques. Most currently-available segmentation algorithms are based on standard image processing and usually require multiple processing steps and/or parameter tuning by the user to adapt to different modalities...
February 28, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29459370/visual-working-memory-is-independent-of-the-cortical-spacing-between-memoranda
#16
William J Harrison, Paul M Bays
The sensory recruitment hypothesis states that visual short term memory is maintained in the same visual cortical areas that initially encode a stimulus' features. Although it is well established that the distance between features in visual cortex determines their visibility, a limitation known as crowding, it is unknown whether short term memory is similarly constrained by the cortical spacing of memory items. Here we investigated whether the cortical spacing between sequentially presented memoranda affects the fidelity of memory in humans (of both sexes)...
February 19, 2018: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/29455947/the-neural-exploitation-hypothesis-and-its-implications-for-an-embodied-approach-to-language-and-cognition-insights-from-the-study-of-action-verbs-processing-and-motor-disorders-in-parkinson-s-disease
#17
REVIEW
Vittorio Gallese, Valentina Cuccio
As it is widely known, Parkinson's disease is clinically characterized by motor disorders such as the loss of voluntary movement control, including resting tremor, postural instability, and bradykinesia (Bocanegra et al., 2015; Helmich, Hallett, Deuschl, Toni, & Bloem, 2012; Liu et al., 2006; Rosin, Topka, & Dichgans, 1997). In the last years, many empirical studies (e.g., Bocanegra et al., 2015; Spadacenta et al., 2012) have also shown that the processing of action verbs is selectively impaired in patients affected by this neurodegenerative disorder...
March 2018: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/29448128/hubs-in-the-human-fetal-brain-network
#18
Marion I van den Heuvel, Elise Turk, Janessa H Manning, Jasmine Hect, Edgar Hernandez-Andrade, Sonia S Hassan, Roberto Romero, Martijn P van den Heuvel, Moriah E Thomason
Advances in neuroimaging and network analyses have lead to discovery of highly connected regions, or hubs, in the connectional architecture of the human brain. Whether these hubs emerge in utero, has yet to be examined. The current study addresses this question and aims to determine the location of neural hubs in human fetuses. Fetal resting-state fMRI data (N = 105) was used to construct connectivity matrices for 197 discrete brain regions. We discovered that within the connectional functional organization of the human fetal brain key hubs are emerging...
February 6, 2018: Developmental Cognitive Neuroscience
https://www.readbyqxmd.com/read/29439729/application-of-neural-networks-for-classification-of-patau-edwards-down-turner-and-klinefelter-syndrome-based-on-first-trimester-maternal-serum-screening-data-ultrasonographic-findings-and-patient-demographics
#19
Aida Catic, Lejla Gurbeta, Amina Kurtovic-Kozaric, Senad Mehmedbasic, Almir Badnjevic
BACKGROUND: The usage of Artificial Neural Networks (ANNs) for genome-enabled classifications and establishing genome-phenotype correlations have been investigated more extensively over the past few years. The reason for this is that ANNs are good approximates of complex functions, so classification can be performed without the need for explicitly defined input-output model. This engineering tool can be applied for optimization of existing methods for disease/syndrome classification. Cytogenetic and molecular analyses are the most frequent tests used in prenatal diagnostic for the early detection of Turner, Klinefelter, Patau, Edwards and Down syndrome...
February 13, 2018: BMC Medical Genomics
https://www.readbyqxmd.com/read/29433038/deep-transfer-learning-for-characterizing-chondrocyte-patterns-in-phase-contrast-x-ray-computed-tomography-images-of-the-human-patellar-cartilage
#20
Anas Z Abidin, Botao Deng, Adora M DSouza, Mahesh B Nagarajan, Paola Coan, Axel Wismüller
Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated to be effective for visualization of the human cartilage matrix at micrometer resolution, thereby capturing osteoarthritis induced changes to chondrocyte organization. This study aims to systematically assess the efficacy of deep transfer learning methods for classifying between healthy and diseased tissue patterns. We extracted features from two different convolutional neural network architectures, CaffeNet and Inception-v3 for characterizing such patterns...
February 9, 2018: Computers in Biology and Medicine
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