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https://www.readbyqxmd.com/read/29459370/visual-working-memory-is-independent-of-the-cortical-spacing-between-memoranda
#1
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
#2
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...
February 2, 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
#3
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
#4
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
#5
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
https://www.readbyqxmd.com/read/29422941/role-of-graph-architecture-in-controlling-dynamical-networks-with-applications-to-neural-systems
#6
Jason Z Kim, Jonathan M Soffer, Ari E Kahn, Jean M Vettel, Fabio Pasqualetti, Danielle S Bassett
Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems...
2018: Nature Physics
https://www.readbyqxmd.com/read/29401206/parallel-trends-in-cortical-gray-and-white-matter-architecture-and-connections-in-primates-allow-fine-study-of-pathways-in-humans-and-reveal-network-disruptions-in-autism
#7
Basilis Zikopoulos, Miguel Ángel García-Cabezas, Helen Barbas
Noninvasive imaging and tractography methods have yielded information on broad communication networks but lack resolution to delineate intralaminar cortical and subcortical pathways in humans. An important unanswered question is whether we can use the wealth of precise information on pathways from monkeys to understand connections in humans. We addressed this question within a theoretical framework of systematic cortical variation and used identical high-resolution methods to compare the architecture of cortical gray matter and the white matter beneath, which gives rise to short- and long-distance pathways in humans and rhesus monkeys...
February 5, 2018: PLoS Biology
https://www.readbyqxmd.com/read/29397900/neural-mechanisms-of-early-life-social-stress-as-a-developmental-risk-factor-for-severe-psychiatric-disorders
#8
Jonathan Rochus Reinwald, Robert Becker, Anne Stephanie Mallien, Claudia Falfan-Melgoza, Markus Sack, Christian Clemm von Hohenberg, Urs Braun, Alejandro Cosa Linan, Natalia Gass, Andrei-Nicolae Vasilescu, Fabian Tollens, Philipp Lebhardt, Natascha Pfeiffer, Dragos Inta, Andreas Meyer-Lindenberg, Peter Gass, Alexander Sartorius, Wolfgang Weber-Fahr
BACKGROUND: To explore the domain-general risk factor of early-life social stress in mental illness, rearing rodents in persistent postweaning social isolation has been established as a widely used animal model with translational relevance for neurodevelopmental psychiatric disorders such as schizophrenia. Although changes in resting-state brain connectivity are a transdiagnostic key finding in neurodevelopmental diseases, a characterization of imaging correlates elicited by early-life social stress is lacking...
December 28, 2017: Biological Psychiatry
https://www.readbyqxmd.com/read/29378297/deconstructing-arousal-into-wakeful-autonomic-and-affective-varieties
#9
REVIEW
Ajay B Satpute, Philip A Kragel, Lisa Feldman Barrett, Tor D Wager, Marta Bianciardi
Arousal plays a central role in a wide variety of phenomena, including wakefulness, autonomic function, affect and emotion. Despite its importance, it remains unclear as to how the neural mechanisms for arousal are organized across them. In this article, we review neuroscience findings for three of the most common origins of arousal: wakeful arousal, autonomic arousal, and affective arousal. Our review makes two overarching points. First, research conducted primarily in non-human animals underscores the importance of several subcortical nuclei that contribute to various sources of arousal, motivating the need for an integrative framework...
January 26, 2018: Neuroscience Letters
https://www.readbyqxmd.com/read/29358365/cortical-connections-position-primate-area-25-as-a-keystone-for-interoception-emotion-and-memory
#10
Mary Kate P Joyce, Helen Barbas
The structural and functional integrity of subgenual cingulate area 25 (A25) is crucial for emotional expression and equilibrium. A25 has a key role in affective networks, and its disruption has been linked to mood disorders, but its cortical connections have yet to be systematically or fully studied. Using neural tracers in rhesus monkeys, we found that A25 was densely connected with other ventromedial and posterior orbitofrontal areas associated with emotions and homeostasis. A moderate pathway linked A25 with frontopolar area 10, an area associated with complex cognition, which may regulate emotions and dampen negative affect...
January 22, 2018: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/29356229/brain-tumor-segmentation-in-multi-spectral-mri-using-convolutional-neural-networks-cnn
#11
Sajid Iqbal, M Usman Ghani, Tanzila Saba, Amjad Rehman
A tumor could be found in any area of the brain and could be of any size, shape, and contrast. There may exist multiple tumors of different types in a human brain at the same time. Accurate tumor area segmentation is considered primary step for treatment of brain tumors. Deep Learning is a set of promising techniques that could provide better results as compared to nondeep learning techniques for segmenting timorous part inside a brain. This article presents a deep convolutional neural network (CNN) to segment brain tumors in MRIs...
January 22, 2018: Microscopy Research and Technique
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/29313301/identification-and-classification-of-brain-tumor-mri-images-with-feature-extraction-using-dwt-and-probabilistic-neural-network
#13
N Varuna Shree, T N R Kumar
The identification, segmentation and detection of infecting area in brain tumor MRI images are a tedious and time-consuming task. The different anatomy structure of human body can be visualized by an image processing concepts. It is very difficult to have vision about the abnormal structures of human brain using simple imaging techniques. Magnetic resonance imaging technique distinguishes and clarifies the neural architecture of human brain. MRI technique contains many imaging modalities that scans and capture the internal structure of human brain...
January 8, 2018: Brain Informatics
https://www.readbyqxmd.com/read/29289617/the-anterior-ventrolateral-temporal-lobe-contributes-to-boosting-visual-working-memory-capacity-for-items-carrying-semantic-information
#14
Rocco Chiou, Matthew A Lambon Ralph
Working memory (WM) is a buffer that temporarily maintains information, be it visual or auditory, in an active state, caching its contents for online rehearsal or manipulation. How the brain enables long-term semantic knowledge to affect the WM buffer is a theoretically significant issue awaiting further investigation. In the present study, we capitalise on the knowledge about famous individuals as a 'test-case' to study how it impinges upon WM capacity for human faces and its neural substrate. Using continuous theta-burst transcranial stimulation combined with a psychophysical task probing WM storage for varying contents, we provide compelling evidence that (1) faces (regardless of familiarity) continued to accrue in the WM buffer with longer encoding time, whereas for meaningless stimuli (colour shades) there was little increment; (2) the rate of WM accrual was significantly more efficient for famous faces, compared to unknown faces; (3) the right anterior-ventrolateral temporal lobe (ATL) causally mediated this superior WM storage for famous faces...
December 28, 2017: NeuroImage
https://www.readbyqxmd.com/read/29261684/neural-mechanisms-underlying-sensitivity-to-reverse-phi-motion-in-the-fly
#15
Aljoscha Leonhardt, Matthias Meier, Etienne Serbe, Hubert Eichner, Alexander Borst
Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster...
2017: PloS One
https://www.readbyqxmd.com/read/29226965/brain-reflections-a-circuit-based-framework-for-understanding-information-processing-and-cognitive-control
#16
Gabriele Gratton
Here, I propose a view of the architecture of the human information processing system, and of how it can be adapted to changing task demands (which is the hallmark of cognitive control). This view is informed by an interpretation of brain activity as reflecting the excitability level of neural representations, encoding not only stimuli and temporal contexts, but also action plans and task goals. The proposed cognitive architecture includes three types of circuits: open circuits, involved in feed-forward processing such as that connecting stimuli with responses and characterized by brief, transient brain activity; and two types of closed circuits, positive feedback circuits (characterized by sustained, high-frequency oscillatory activity), which help select and maintain representations, and negative feedback circuits (characterized by brief, low-frequency oscillatory bursts), which are instead associated with changes in representations...
December 11, 2017: Psychophysiology
https://www.readbyqxmd.com/read/29219068/predicting-enhancers-with-deep-convolutional-neural-networks
#17
Xu Min, Wanwen Zeng, Shengquan Chen, Ning Chen, Ting Chen, Rui Jiang
BACKGROUND: With the rapid development of deep sequencing techniques in the recent years, enhancers have been systematically identified in such projects as FANTOM and ENCODE, forming genome-wide landscapes in a series of human cell lines. Nevertheless, experimental approaches are still costly and time consuming for large scale identification of enhancers across a variety of tissues under different disease status, making computational identification of enhancers indispensable. RESULTS: To facilitate the identification of enhancers, we propose a computational framework, named DeepEnhancer, to distinguish enhancers from background genomic sequences...
December 1, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29217875/deep-auto-context-convolutional-neural-networks-for-standard-dose-pet-image-estimation-from-low-dose-pet-mri
#18
Lei Xiang, Yu Qiao, Dong Nie, Le An, Qian Wang, Dinggang Shen
Positron emission tomography (PET) is an essential technique in many clinical applications such as tumor detection and brain disorder diagnosis. In order to obtain high-quality PET images, a standard-dose radioactive tracer is needed, which inevitably causes the risk of radiation exposure damage. For reducing the patient's exposure to radiation and maintaining the high quality of PET images, in this paper, we propose a deep learning architecture to estimate the high-quality standard-dose PET (SPET) image from the combination of the low-quality low-dose PET (LPET) image and the accompanying T1-weighted acquisition from magnetic resonance imaging (MRI)...
December 6, 2017: Neurocomputing
https://www.readbyqxmd.com/read/29195422/a-transfer-learning-approach-to-goodness-of-pronunciation-based-automatic-mispronunciation-detection
#19
Hao Huang, Haihua Xu, Ying Hu, Gang Zhou
Goodness of pronunciation (GOP) is the most widely used method for automatic mispronunciation detection. In this paper, a transfer learning approach to GOP based mispronunciation detection when applying maximum F1-score criterion (MFC) training to deep neural network (DNN)-hidden Markov model based acoustic models is proposed. Rather than train the whole network using MFC, a DNN is used, whose hidden layers are borrowed from native speech recognition with only the softmax layer trained according to the MFC objective function...
November 2017: Journal of the Acoustical Society of America
https://www.readbyqxmd.com/read/29188111/automatic-detection-of-the-foveal-center-in-optical-coherence-tomography
#20
Bart Liefers, Freerk G Venhuizen, Vivian Schreur, Bram van Ginneken, Carel Hoyng, Sascha Fauser, Thomas Theelen, Clara I Sánchez
We propose a method for automatic detection of the foveal center in optical coherence tomography (OCT). The method is based on a pixel-wise classification of all pixels in an OCT volume using a fully convolutional neural network (CNN) with dilated convolution filters. The CNN-architecture contains anisotropic dilated filters and a shortcut connection and has been trained using a dynamic training procedure where the network identifies its own relevant training samples. The performance of the proposed method is evaluated on a data set of 400 OCT scans of patients affected by age-related macular degeneration (AMD) at different severity levels...
November 1, 2017: Biomedical Optics Express
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