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6th International Congress on Image and Signal Processing (CISP)

作者： Wen, Quan Chen, Juan Liu, Wenhao Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu 610054 Peoples R China Hangzhou Normal Univ Dept Comp Sci & Technol Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781479927630

In this paper, we propose a predictive coding approach to identify microvessel subimages using Single-Opponent (SO) signal. First, we simulate the signal from SO neurons in the positive red and negative cyan channel to segment microvessel regions. Second, the SO signal is convolved with a Laplacian of Gaussian (LoG) filter and then processed in a predictive coding and biased competition (PC/BC) neural network. The texture patterns from SO signal is learnt and represented by the PC/BC model. Finally, we employ Support Vector Machine (SVM) with Spatial Pyramid Matching (SPM) scheme to classify the microvessel subimages on the learnt texture patterns. We have carried out extensive experiments on the identification of microvessel subimages. The proposed method is about 10% superior in F1-measure compared with direct classification on subimages in RGB channel.

关键词： predictive coding single-opponent microvessel identification neural network spatial pyramid matching

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Real-Time Human Body Sensors Data Classification using Supervised Machine Learning

Real-Time Human Body Sensors Data Classification using Super...

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Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Muhammad Sajid Farooq Muhammad Farhan Khan Dept. of Computer Science Lahore Garrison University Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan Dept. of Forensic Sciences University of Health Sciences Lahore Pakistan

Supervised learning algorithms have recently been brought to the classification of medical data in an effort to boost diagnostic throughput and eliminate human-caused diagnostic errors. This measure was taken to improve diagnostic precision. To be carried out, the fully supervised learning process needs a large amount of accurately labelled data. Annotating data material, on the other hand, demands a large expenditure of time, effort, and resources. Using the self- supervised learning approach to solve this challenge has the potential to provide a variety of beneficial outcomes for everyone. When there is no direct supervision, pretext projects are regularly employed in independent study scenarios. This is done so that massive volumes of unsupervised data may be utilized to obtain supervised knowledge. Furthermore, by utilizing specialized, supervised information, the network is prepared to obtain representations that will be beneficial for still-growing professions. The two-step CPC-based classification framework (TCC) model is built completely using contrastive predictive coding and is divided into two distinct phases that are carried out in sequential order. Making use of the contrastive predictive coding (CPC) model, the initial step is to build a fictional position. It must be completed as quickly as possible. This activity must utilize the encoder to extract appropriate features from a broad variety of classes in order to achieve the goal that it has set out to achieve. The encoder will employ the skills they learned while working on the pretext in the second half, which will take place in a training setting under the guidance of an expert teacher. Finally, we assess the proposed framework by comparing it to the most recent and innovative research in the field. This allows us to highlight the framework’s success by displaying how well it compares to other cutting-edge and current industry efforts. Experiments will be conducted to compare the efficacy of the pr

关键词： Training Adaptation models Supervised learning Machine learning predictive coding predictive models Feature extraction

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Actions of a shaken heart: Interoception interacts with action processing

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BIOLOGICAL PSYCHOLOGY 2022年第0期169卷 108288-108288页

作者： Becev, Ondrej Kozakova, Eva Sakalosova, Lenka Marecek, Radek Majchrowicz, Bartosz Roman, Robert Brazdil, Milan Masaryk Univ CEITEC Cent European Inst Technol Behav & Social Neurosci Kamenice 753-5 Brno Czech Republic Masaryk Univ CEITEC Cent European Inst Technol Multimodal & Funct Neuroimaging Res Grp Kamenice 753-5 Brno Czech Republic Natl Inst Mental Hlth Clin Res Program Topolova 748 Klecany Czech Republic Jagiellonian Univ Inst Psychol Consciousness Lab Ingardena 6 Krakow Poland UCL Inst Cognit Neurosci 17-19 Queen Sq London England Masaryk Univ St Annes Univ Hosp Fac Med Dept Neurol 1 Pekarsk 664-53 Brno Czech Republic CEITEC MU Kamenice 753-5 Brno Czech Republic

In the present study, we investigated the modulatory influence of the unconscious, bodily arousal on motor related embodied information. Specifically, we examined how the interoceptive prediction error interacts with the event-related potentials linked to action-effect processing. Participants were asked to perform a task with self-initiated or externally-triggered sounds while receiving synchronous or false auditory cardiac feedback. The results found that interaction of interoceptive manipulation and action-effect processing modulates the frontal subcomponent of the P3 response. During the synchronous cardiac feedback, the P3 response to self-initiated tones was enhanced. During the false cardiac feedback, the frontal cortical response was reversed. N1 and P2 components were affected by the interoceptive manipulation, but not by the interaction of interoception and action processing. These findings provide experimental support for the theoretical accounts of the interaction between interoception and action processing within a framework of predictive coding, manifested particularly in the higher stages of action processing.

关键词： Interoception Agency predictive coding Sensory attenuation Event-related potentials (ERP) Motor prediction Action-effect processing

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Temporal-spectral signaling of sensory information and expectations in the cerebral processing of pain

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2022年第1期119卷 e2116616119-e2116616119页

作者： Nickel, Moritz M. Tiemann, Laura Hohn, Vanessa D. May, Elisabeth S. Avila, Cristina Gil Eippert, Falk Ploner, Markus Tech Univ Munich Sch Med Dept Neurol D-81675 Munich Germany Tech Univ Munich Neuroimaging Ctr Sch Med D-81675 Munich Germany Max Planck Inst Human Cognit & Brain Sci Max Planck Res Grp Pain Percept D-04103 Leipzig Germany Tech Univ Munich Ctr Interdisciplinary Pain Med Sch Med D-81675 Munich Germany

The perception of pain is shaped by somatosensory information about threat. However, pain is also influenced by an individual's expectations. Such expectations can result in clinically relevant modulations and abnormalities of pain. In the brain, sensory information, expectations (predictions), and discrepancies thereof (prediction errors) are signaled by an extended network of brain areas which generate evoked potentials and oscillatory responses at different latencies and frequencies. However, a comprehensive picture of how evoked and oscillatory brain responses signal sensory information, predictions, and prediction errors in the processing of pain is lacking so far. Here, we therefore applied brief painful stimuli to 48 healthy human participants and independently modulated sensory information (stimulus intensity) and expectations of pain intensity while measuring brain activity using electroencephalography (EEG). Pain ratings confirmed that pain intensity was shaped by both sensory information and expectations. In contrast, Bayesian analyses revealed that stimulus-induced EEG responses at different latencies (the N1, N2, and P2 components) and frequencies (alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Expectations, however, shaped alpha and beta oscillations before the painful stimuli. These findings indicate that commonly analyzed EEG responses to painful stimuli are more involved in signaling sensory information than in signaling expectations or mismatches of sensory information and expectations. Moreover, they indicate that the effects of expectations on pain are served by brain mechanisms which differ from those conveying effects of sensory information on pain.

关键词： pain brain electroencephalography oscillations predictive coding

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Efficient scheme for WCE image compression based on strategic chroma subsampling and encoding

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2022年第PartB期71卷 103184-103184页

作者： Babu, Caren Chandy, D. Abraham Christinal, Hepzibah A. Christ Coll Engn Dept Elect & Commun Engn Irinjalakuda India Karunya Inst Technol & Sci Dept Elect & Commun Engn Coimbatore India Karunya Inst Technol & Sci Dept Math Coimbatore India

The data generated in wireless capsule endoscopy during the examination of the gastrointestinal tract is huge and demands large storage and processing time. One of the essential components of the capsule is the compression module that needs to be low power and a low complexity one. This paper aims to bring significant improvement in pre-processing, chroma subsampling and encoding stages of image compression. Among various chrominance based color spaces, YEF being a best alternative for the RGB endoscopic image is analyzed in terms of statistical measures. New chroma subsampling patterns are tested, which has shown improved data reduction. In the encoder part, the combination of proposed predictive coder and the modified Golomb Rice coder generated better compressed bit stream. The cubic spline interpolation is the method used for image reconstruction during decompression. The endoscopic images from databases namely Gastrolab and WEO Clinical Endoscopy Atlas are utilized in the experimentation. The results show that the proposed near-lossless compression scheme performs better than the competing techniques in terms of compression rate, peak signal to noise ratio and structural similarity index.

关键词： Data compression Endoscopes Color space Subsampling predictive coding Golomb Rice coding

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Efficient Temporal coding in the Early Visual System: Existing Evidence and Future Directions

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FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 2022年 16卷 929348页

作者： Price, Byron H. Gavornik, Jeffrey P. Boston Univ Ctr Syst Neurosci Dept Biol Grad Program Neurosci Boston MA 02215 USA

While it is universally accepted that the brain makes predictions, there is little agreement about how this is accomplished and under which conditions. Accurate prediction requires neural circuits to learn and store spatiotemporal patterns observed in the natural environment, but it is not obvious how such information should be stored, or encoded. Information theory provides a mathematical formalism that can be used to measure the efficiency and utility of different coding schemes for data transfer and storage. This theory shows that codes become efficient when they remove predictable, redundant spatial and temporal information. Efficient coding has been used to understand retinal computations and may also be relevant to understanding more complicated temporal processing in visual cortex. However, the literature on efficient coding in cortex is varied and can be confusing since the same terms are used to mean different things in different experimental and theoretical contexts. In this work, we attempt to provide a clear summary of the theoretical relationship between efficient coding and temporal prediction, and review evidence that efficient coding principles explain computations in the retina. We then apply the same framework to computations occurring in early visuocortical areas, arguing that data from rodents is largely consistent with the predictions of this model. Finally, we review and respond to criticisms of efficient coding and suggest ways that this theory might be used to design future experiments, with particular focus on understanding the extent to which neural circuits make predictions from efficient representations of environmental statistics.

关键词： efficient coding predictive coding time temporal representations visual cortex

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A systematic review on resting state functional connectivity in patients with neurodegenerative disease and hallucinations

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NEUROIMAGE-CLINICAL 2022年第0期35卷 103112-103112页

作者： Spinosa, Vittoria Brattico, Elvira Campo, Fulvia Logroscino, Giancarlo Univ Bari Aldo Moro Pia Fdn Cardinale G Panico Ctr Neurodegenerat Dis & Aging Brain Dept Clin Res Neurol Tricase Lecce Italy Univ Bari Aldo Moro Dept Basic Med Neurosci & Sense Organs Bari Italy Aarhus Univ Ctr Mus Brain Dept Clin Med Aarhus Denmark Royal Acad Mus Aarhus Aalborg Aarhus Denmark Univ Bari Aldo Moro Dept Educ Psychol Commun Bari Italy Via San Pio X4 I-73039 Tricase LE Italy

Hallucinations are a complex and multidimensional phenomenon which can differ based on the involved pa-thology, typology and sensory modality. Hallucinations are common in patients with neurodegenerative diseases. Recent sparse evidence from resting state functional magnetic resonance imaging (rs-fMRI) studies has identified altered functional connectivity in those patients within several brain networks, such as the default mode, attentional and sensory ones, without, however, providing an organized picture of the mechanisms involved. This systematic review, following PRISMA guidelines, aims at critically analyzing the current literature on the brain networks associated with the phenomenon of hallucinations in patients with neurodegenerative diseases. Ten rs-fMRI studies fulfilled our selection criteria. All these studies focused on synucleinopathies, and most of them focused on visual hallucinations and were characterized by a heterogeneous methodology. Thus, instead of offering a definite picture of the mechanisms underlying hallucinations in neurodegeneration, this systematic review encourages further research especially concerning tauopathies. Notwithstanding, the findings overall suggest a disruption in the top-down (associated with memory intrusion and difficulty of inhibition) and in the bottom-up processes (associated with the sensory areas involved in the hallucinations). Further investigations are needed in order to disentangle the brain mechanisms involved in hallucinations and to overcome possible lim-itations characterizing the current literature.

关键词： Neurodegenerative disorders Hallucination Resting state fMRI Systematic review predictive coding

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Lossless medical image compression by IWT and predictive coding

Lossless medical image compression by IWT and predictive cod...

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International Conference on Energy Efficient Technologies for Sustainability (ICEETS)

作者： Shirsat, T. G. Bairagi, V. K. SAE Dept Elect Engn Pune Maharashtra India

ISBN: (纸本)9781467361507;9781467361491

The future of healthcare delivery systems and telemedical applications will undergo a radical change due to the developments in wearable technologies, medical sensors, mobile computing and communication techniques. When dealing with applications of collecting, sorting and transferring medical data from distant locations for performing remote medical collaborations and diagnosis. E-health was born with the integration of networks and telecommunications. In recent years healthcare systems rely on images acquired in two dimensional domains in the case of still images, or three dimensional domains for volumetric video sequences and images. Images are acquired with many modalities including X-ray, magnetic resonance imaging, ultrasound, positron emission tomography, computed axial tomography. Medical informationis either in multidimensional or multi-resolution form, this creates enormous amount of data. Retrieval, Efficient storage, management and transmission of this voluminous data are highly complex. One of the solutions to reduce this complex problem is to compress the medical data without any loss (i.e. lossless). Since the diagnostics capabilities are not compromised. This technique combines integer transforms and predictive coding to enhance the performance of lossless compression. The proposed techniques can be evaluated for performance using compression quality measures.

关键词： IWT Image compression predictive coding

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Graph-Based Transforms for Video coding

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2020年 29卷 9330-9344页

作者： Egilmez, Hilmi E. Chao, Yung-Hsuan Ortega, Antonio Qualcomm Technol Inc San Diego CA 92121 USA Univ Southern Calif Dept Elect & Comp Engn Los Angeles CA 90084 USA

In many state-of-the-art compression systems, signal transformation is an integral part of the encoding and decoding process, where transforms provide compact representations for the signals of interest. This paper introduces a class of transforms called graph-based transforms (GBTs) for video compression, and proposes two different techniques to design GBTs. In the first technique, we formulate an optimization problem to learn graphs from data and provide solutions for optimal separable and nonseparable GBT designs, called GL-GBTs. The optimality of the proposed GL-GBTs is also theoretically analyzed based on Gaussian-Markov random field (GMRF) models for intra and inter predicted block signals. The second technique develops edge-adaptive GBTs (EA-GBTs) in order to flexibly adapt transforms to block signals with image edges (discontinuities). The advantages of EA-GBTs are both theoretically and empirically demonstrated. Our experimental results show that the proposed transforms can significantly outperform the traditional Karhunen-Loeve transform (KLT).

关键词： Transforms Image coding Laplace equations Image edge detection Covariance matrices Symmetric matrices Video coding Transform coding predictive coding graph-based transforms video coding compression optimization statistical modeling

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From the inside out: Interoceptive feedback facilitates the integration of visceral signals for efficient sensory processing

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NEUROIMAGE 2022年 251卷 119011-119011页

作者： Marshall, Amanda C. Gentsch-Ebrahimzadeh, Antje Schutz-Bosbach, Simone Ludwig Maximilians Univ Munchen Gen & Expt Psychol Unit Dept Psychol Munich Germany

Neuroscientific studies have mainly focused on the way humans perceive and interact with the external world. Recent work in the interoceptive domain indicates that the brain predictively models information from inside the body such as the heartbeat and that the efficiency with which this is executed can have implications for exteroceptive processing. However, to date direct evidence underpinning these hypotheses is lacking. Here, we show how the brain predictively refines neural resources to process afferent cardiac feedback and uses these interoceptive cues to enable more efficient processing of external sensory information. Participants completed a repetition-suppression paradigm consisting of a neutral repeating face. During the first face presentation, they heard auditory feedback of their heartbeat which either coincided with the systole of the cardiac cycle, the time at which cardiac events are registered by the brain or the diastole during which the brain receives no internal cardiac feedback. We used electroencephalography to measure the heartbeat evoked potential (HEP) as well as auditory (AEP) and visual evoked potentials (VEP). Exteroceptive cardiac feedback which coincided with the systole produced significantly higher HEP amplitudes relative to feedback timed to the diastole. Elevation of the HEP in this condition was followed by significant suppression of the VEP in response to the repeated neutral face and a stepwise decrease of AEP amplitude to repeated heartbeat feedback. Our results hereby show that exteroceptive heartbeat feedback coinciding with interoceptive signals at systole enhanced interoceptive cardiac processing. Furthermore, the same cue facilitating interoceptive integration enabled efficient suppression of a visual stimulus, as well as repetition suppression of the AEP across successive auditory heartbeat feedback. Our findings provide evidence that the alignment of external to internal signals can enhance the efficiency of interoceptiv

关键词： Cardiac biofeedback EEG Heartbeat evoked potential Interoception Exteroceptive processing predictive coding

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