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https://www.readbyqxmd.com/read/28241028/deploying-a-quantum-annealing-processor-to-detect-tree-cover-in-aerial-imagery-of-california
#1
Edward Boyda, Saikat Basu, Sangram Ganguly, Andrew Michaelis, Supratik Mukhopadhyay, Ramakrishna R Nemani
Quantum annealing is an experimental and potentially breakthrough computational technology for handling hard optimization problems, including problems of computer vision. We present a case study in training a production-scale classifier of tree cover in remote sensing imagery, using early-generation quantum annealing hardware built by D-wave Systems, Inc. Beginning within a known boosting framework, we train decision stumps on texture features and vegetation indices extracted from four-band, one-meter-resolution aerial imagery from the state of California...
2017: PloS One
https://www.readbyqxmd.com/read/28240722/brain-correlates-to-facial-motor-imagery-and-its-somatotopy-in-the-primary-motor-cortex
#2
Ramy S Soliman, Sanghoon Lee, Seulgi Eun, Abdalla Z Mohamed, Jeungchan Lee, Eunyoung Lee, Meena M Makary, Seung Min Kathy Lee, Hwa-Jin Lee, Woo Suk Choi, Kyungmo Park
Motor imagery (MI) has attracted increased interest for motor rehabilitation as many studies have shown that MI shares the same neural networks as motor execution (ME). Nevertheless, MI in terms of facial movement has not been studied extensively; thus, in the present study, we investigated shared neural networks between facial motor imagery (FMI) and facial motor execution (FME). In addition, FMI somatotopy within-face was investigated between the forehead and the mouth. Functional MRI was used to examine 34 healthy individuals with ME and MI paradigms for the forehead and the mouth...
February 24, 2017: Neuroreport
https://www.readbyqxmd.com/read/28240674/a-second-wind-for-the-cholinergic-system-in-alzheimer-s-therapy
#3
Vincent Douchamps, Chantal Mathis
Notwithstanding tremendous research efforts, the cause of Alzheimer's disease (AD) remains elusive and there is no curative treatment. The cholinergic hypothesis presented 35 years ago was the first major evidence-based hypothesis on the etiology of AD. It proposed that the depletion of brain acetylcholine was a primary cause of cognitive decline in advanced age and AD. It relied on a series of observations obtained in aged animals, elderly, and AD patients that pointed to dysfunctions of cholinergic basal forebrain, similarities between cognitive impairments induced by anticholinergic drugs and those found in advanced age and AD, and beneficial effects of drugs stimulating cholinergic activity...
February 24, 2017: Behavioural Pharmacology
https://www.readbyqxmd.com/read/28240252/novel-quantitative-pigmentation-phenotyping-enhances-genetic-association-epistasis-and-prediction-of-human-eye-colour
#4
Andreas Wollstein, Susan Walsh, Fan Liu, Usha Chakravarthy, Mati Rahu, Johan H Seland, Gisèle Soubrane, Laura Tomazzoli, Fotis Topouzis, Johannes R Vingerling, Jesus Vioque, Stefan Böhringer, Astrid E Fletcher, Manfred Kayser
Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study...
February 27, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28239336/effect-of-constrained-arm-posture-on-the-processing-of-action-verbs
#5
Masaaki Yasuda, John F Stins, Takahiro Higuchi
Evidence is increasing that brain areas that are responsible for action planning and execution are activated during the information processing of action-related verbs (e.g., pick or kick). To obtain further evidence, we conducted three experiments to see if constraining arm posture, which could disturb the motor planning and imagery for that arm, would lead to delayed judgment of verbs referring to arm actions. In all experiments, native Japanese speakers judged as quickly as possible whether the presented object and the verb would be compatible (e...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28239214/mental-imagery-based-training-to-modify-mood-and-cognitive-bias-in-adolescents-effects-of-valence-and-perspective
#6
S Burnett Heyes, A Pictet, H Mitchell, S M Raeder, J Y F Lau, E A Holmes, S E Blackwell
Mental imagery has a powerful impact on emotion and cognitive processing in adults, and is implicated in emotional disorders. Research suggests the perspective adopted in mental imagery modulates its emotional impact. However, little is known about the impact of mental imagery in adolescence, despite adolescence being the key time for the onset of emotional dysfunction. We administered computerised positive versus mixed valence picture-word mental imagery training to male adolescent participants (N = 60, aged 11-16 years) across separate field and observer perspective sessions...
2017: Cognitive Therapy and Research
https://www.readbyqxmd.com/read/28238944/brain-correlates-of-hypnosis-a-systematic-review-and-meta-analytic-exploration
#7
REVIEW
Mathieu Landry, Michael Lifshitz, Amir Raz
Imaging of the living human brain elucidates the neural dynamics of hypnosis; however, few reliable brain patterns emerge across studies. Here, we methodically assess neuroimaging assays of hypnosis to uncover common neural configurations using a twofold approach. First, we systematically review research on the neural correlates of hypnotic phenomena; then, we meta-analyze these collective data seeking specific activation and deactivation patterns that typify hypnosis. Anchored around the role of top-down control processes, our comprehensive examination focuses on the involvement of intrinsic brain networks known to operationalize cognitive control and self-referential cognition, including the executive, salience, and default networks...
February 23, 2017: Neuroscience and Biobehavioral Reviews
https://www.readbyqxmd.com/read/28238485/stormwater-runoff-plumes-in-the-southern-california-bight-a-comparison-study-with-sar-and-modis-imagery
#8
Benjamin Holt, Rebecca Trinh, Michelle M Gierach
Stormwater runoff is the largest source of pollution in the Southern California Bight (SCB), resulting from untreated runoff and pollutants from urban watersheds entering the coastal waters after rainstorms. We make use of both satellite SAR and MODIS-Aqua ocean color imagery to examine two different components of runoff plumes, the surface slick and the sediment discharge. We expand on earlier satellite SAR studies by examining an extensive collection of multi-platform SAR imagery, spanning from 1992 to 2014, that provides a more comprehensive view of the plume surface slick characteristics, illustrated with distribution maps of the extent and flow direction of the plumes...
February 23, 2017: Marine Pollution Bulletin
https://www.readbyqxmd.com/read/28238175/classification-of-multi-class-motor-imagery-with-a-novel-hierarchical-svm-algorithm-for-brain-computer-interfaces
#9
Enzeng Dong, Changhai Li, Liting Li, Shengzhi Du, Abdelkader Nasreddine Belkacem, Chao Chen
Pattern classification algorithm is the crucial step in developing brain-computer interface (BCI) applications. In this paper, a hierarchical support vector machine (HSVM) algorithm is proposed to address an EEG-based four-class motor imagery classification task. Wavelet packet transform is employed to decompose raw EEG signals. Thereafter, EEG signals with effective frequency sub-bands are grouped and reconstructed. EEG feature vectors are extracted from the reconstructed EEG signals with one versus the rest common spatial patterns (OVR-CSP) and one versus one common spatial patterns (OVO-CSP)...
February 25, 2017: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/28235663/the-perceptual-and-phenomenal-capacity-of-mental-imagery
#10
Rebecca Keogh, Joel Pearson
Despite the brain's immense processing power, it has finite resources. Where do these resource limits come from? Little research has examined possible low-level sensory contributions to these limitations. Mental imagery is a fundamental part of human cognition that bridges cognition with sensory representations. Hence, imagery serves as a good candidate sensory process for probing how low capacity limitations might extend down the processing hierarchy. Here we introduce a novel technique to measure the sensory capacity of mental imagery, while removing the need for memory and any direct subjective reports...
February 21, 2017: Cognition
https://www.readbyqxmd.com/read/28228739/touchscreen-tablets-coordinating-action-and-perception-for-mathematical-cognition
#11
Carolien A C G Duijzer, Shakila Shayan, Arthur Bakker, Marieke F Van der Schaaf, Dor Abrahamson
Proportional reasoning is important and yet difficult for many students, who often use additive strategies, where multiplicative strategies are better suited. In our research we explore the potential of an interactive touchscreen tablet application to promote proportional reasoning by creating conditions that steer students toward multiplicative strategies. The design of this application (Mathematical Imagery Trainer) was inspired by arguments from embodied-cognition theory that mathematical understanding is grounded in sensorimotor schemes...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28227980/motor-imagery-based-brain-computer-interface-using-transform-domain-features
#12
Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Mohamed A Oransa, Khaled S Sayed, Ayman M Mohamed, Ahmed T Ahmed, Ahmed M Elbaz, Ayman M Eldeib
Brain Computer Interface (BCI) is a channel of communication between the human brain and an external device through brain electrical activity. In this paper, we extracted different features to boost the classification accuracy as well as the mutual information of BCI systems. The extracted features include the magnitude of the discrete Fourier transform and the wavelet coefficients for the EEG signals in addition to distance series values and invariant moments calculated for the reconstructed phase space of the EEG measurements...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227856/multiquadric-spline-based-interactive-segmentation-of-vascular-networks
#13
Sachin Meena, V B Surya Prasath, Yasmin M Kassim, Richard J Maude, Olga V Glinskii, Vladislav V Glinsky, Virginia H Huxley, Kannappan Palaniappan, Sachin Meena, V B Surya Prasath, Yasmin M Kassim, Richard J Maude, Olga V Glinskii, Vladislav V Glinsky, Virginia H Huxley, Kannappan Palaniappan, Virginia H Huxley, Yasmin M Kassim, Sachin Meena, Kannappan Palaniappan, Vladislav V Glinsky, Olga V Glinskii, Richard J Maude, V B Surya Prasath
Commonly used drawing tools for interactive image segmentation and labeling include active contours or boundaries, scribbles, rectangles and other shapes. Thin vessel shapes in images of vascular networks are difficult to segment using automatic or interactive methods. This paper introduces the novel use of a sparse set of user-defined seed points (supervised labels) for precisely, quickly and robustly segmenting complex biomedical images. A multiquadric spline-based binary classifier is proposed as a unique approach for interactive segmentation using as features color values and the location of seed points...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227845/high-performance-wearable-two-channel-hybrid-bci-system-with-eye-closure-assist
#14
Yubing Jiang, Hyeonseok Lee, Gang Li, Wan-Young Chung, Yubing Jiang, Hyeonseok Lee, Gang Li, Wan-Young Chung, Wan-Young Chung, Gang Li, Hyeonseok Lee, Yubing Jiang
Generally, eye closure (EC) and eye opening (EO)-based alpha blocking has widely recognized advantages, such as being easy to use, requiring little user training, while motor imagery (MI) is difficult for some users to have concrete feelings. This study presents a hybrid brain-computer interface (BCI) combining MI and EC strategies - such an approach aims to overcome some disadvantages of MI-based BCI, improve the performance and universality of the BCI. The EC/EO is employed to control the machine to switch in different states including forward, stop, changing direction motions, while the MI is used to control the machine to turn left or right for 90° by imagining the hands grasp motions when the system is switched into "changing direction" state...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227844/maximum-entropy-based-common-spatial-patterns-for-motor-imagery-classification
#15
Syed Salman Ali, Lei Zhang, Syed Salman Ali, Lei Zhang, Syed Salman Ali, Lei Zhang
The common spatial pattern (CSP) is extensively used to extract discriminative feature from raw Electroencephalography (EEG) signals for motor imagery classification. The CSP is a statistical signal processing technique, which relies on sample based covariance matrix estimation to give discriminative information from raw EEG signals. The sample based estimation of covariance matrix becomes a problem when the number of training samples is limited, which causes the performance of CSP based brain computer interface (BCI) to degrade significantly...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227843/investigating-motor-imagery-tasks-by-their-neural-effects-a-case-study
#16
I E Nicolae, M M C Stefan, B Hurezeanu, D D Taralunga, R Strungaru, T M Vasile, O A Bajenaru, G M Ungureanu, I E Nicolae, M M C Stefan, B Hurezeanu, D D Taralunga, R Strungaru, T M Vasile, O A Bajenaru, G M Ungureanu, B Hurezeanu, R Strungaru, G M Ungureanu, O A Bajenaru, D D Taralunga, T M Vasile, I E Nicolae, M M C Stefan
Motor imagery, one of the first investigated neural process for Brain-Computer Interfaces (BCIs) still provides a great challenge nowadays. Aiming a better and more accurate control, multiple researches have been conducted by the scientific community. Nevertheless, there is still no robust and confident application developed. In order to augment the potential referring to motor imagery, and to attract user's interest, we propose multiple motor imagery tasks in combination with different visual or auditory stimuli...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227496/movement-imagery-classification-in-emotiv-cap-based-system-by-nai%C3%AC-ve-bayes
#17
Vinicius N Stock, Alexandre Balbinot, Vinicius N Stock, Alexandre Balbinot, Vinicius N Stock, Alexandre Balbinot
Brain-computer interfaces (BCI) provide means of communications and control, in assistive technology, which do not require motor activity from the user. The goal of this study is to promote classification of two types of imaginary movements, left and right hands, in an EMOTIV cap based system, using the Naïve Bayes classifier. A preliminary analysis with respect to results obtained by other experiments in this field is also conducted. Processing of the electroencephalography (EEG) signals is done applying Common Spatial Pattern filters...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227125/random-forests-for-dura-mater-microvasculature-segmentation-using-epifluorescence-images
#18
Yasmin M Kassim, V B Surya Prasath, Rengarajan Pelapur, Olga V Glinskii, Richard J Maude, Vladislav V Glinsky, Virginia H Huxley, Kannappan Palaniappan, Yasmin M Kassim, V B Surya Prasath, Rengarajan Pelapur, Olga V Glinskii, Richard J Maude, Vladislav V Glinsky, Virginia H Huxley, Kannappan Palaniappan, Virginia H Huxley, Yasmin M Kassim, Rengarajan Pelapur, Kannappan Palaniappan, Vladislav V Glinsky, Olga V Glinskii, Richard J Maude, V B Surya Prasath
Automatic segmentation of microvascular structures is a critical step in quantitatively characterizing vessel remodeling and other physiological changes in the dura mater or other tissues. We developed a supervised random forest (RF) classifier for segmenting thin vessel structures using multiscale features based on Hessian, oriented second derivatives, Laplacian of Gaussian and line features. The latter multiscale line detector feature helps in detecting and connecting faint vessel structures that would otherwise be missed...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227094/mutual-information-based-feature-selection-for-low-cost-bcis-based-on-motor-imagery
#19
L Schiatti, L Faes, J Tessadori, G Barresi, L Mattos, L Schiatti, L Faes, J Tessadori, G Barresi, L Mattos, G Barresi, L Mattos, J Tessadori, L Faes, L Schiatti
In the present study a feature selection algorithm based on mutual information (MI) was applied to electro-encephalographic (EEG) data acquired during three different motor imagery tasks from two dataset: Dataset I from BCI Competition IV including full scalp recordings from four subjects, and new data recorded from three subjects using the popular low-cost Emotiv EPOC EEG headset. The aim was to evaluate optimal channels and band-power (BP) features for motor imagery tasks discrimination, in order to assess the feasibility of a portable low-cost motor imagery based Brain-Computer Interface (BCI) system...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226800/towards-direct-speech-synthesis-from-ecog-a-pilot-study
#20
Christian Herff, Garett Johnson, Lorenz Diener, Jerry Shih, Dean Krusienski, Tanja Schultz, Christian Herff, Garett Johnson, Lorenz Diener, Jerry Shih, Dean Krusienski, Tanja Schultz, Lorenz Diener, Christian Herff, Jerry Shih, Tanja Schultz, Dean Krusienski, Garett Johnson
Most current Brain-Computer Interfaces (BCIs) achieve high information transfer rates using spelling paradigms based on stimulus-evoked potentials. Despite the success of this interfaces, this mode of communication can be cumbersome and unnatural. Direct synthesis of speech from neural activity represents a more natural mode of communication that would enable users to convey verbal messages in real-time. In this pilot study with one participant, we demonstrate that electrocoticography (ECoG) intracranial activity from temporal areas can be used to resynthesize speech in real-time...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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