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Book
Brain Oscillations and Predictive Coding: What We Know and What We Should Learn
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Year: 2017 Publisher: Frontiers Media SA

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Abstract

Predictive coding (PC) is a neurocognitive concept, according to which the brain does not process the whole qualia of external information, but only residual mismatches occurring between incoming information and an individual, inner model of the world. At the time of issue initiation, I expected an essential focus on mismatch signals in the brain, especially those captured by neurophysiologic oscillations. This was because one most plausible approach to the PC concept is to identify and validate mismatch signals in the brain. Announcing the topic revealed a much deeper consideration of intelligible minds of researchers. It turned out that what was of fundamental interest was which brain mechanisms support the formation, maintenance and consolidation of the inner model determining PC. Is PC a dynamic construct continuously modulated by external environmental or internal mental information? The reader will be delighted to get acquainted with the current views and understanding of eminent scholars in the field. It will be challenging to discover the realm of sleep where both physiological, energy preserving and mental qualia principles build on the inner models to shape and transform the self. And where neurophysiologic oscillations may both transmit external information and translate inner models from state to state to preserve the self-continuity and compactness.


Book
Visual mismatch negativity (vMMN) : a prediction error signal in the visual modality
Authors: --- --- ---
Year: 2015 Publisher: Frontiers Media SA

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Current theories of visual change detection emphasize the importance of conscious attention to detect unexpected changes in the visual environment. However, an increasing body of studies shows that the human brain is capable of detecting even small visual changes, especially if such changes violate non-conscious probabilistic expectations based on repeating experiences. In other words, our brain automatically represents statistical regularities of our visual environmental. Since the discovery of the auditory mismatch negativity (MMN) event-related potential (ERP) component, the majority of research in the field has focused on auditory deviance detection. Such automatic change detection mechanisms operate in the visual modality too, as indicated by the visual mismatch negativity (vMMN) brain potential to rare changes. VMMN is typically elicited by stimuli with infrequent (deviant) features embedded in a stream of frequent (standard) stimuli, outside the focus of attention. In this research topic we aim to present vMMN as a prediction error signal. Predictive coding theories account for phenomena such as mismatch negativity and repetition suppression, and place them in a broader context of a general theory of cortical responses. A wide range of vMMN studies has been presented in this Research Topic. Twelve articles address roughly four general sub-themes including attention, language, face processing, and psychiatric disorders. Additionally, four articles focused on particular subjects such as the oblique effect, object formation, and development and time-frequency analysis of vMMN. Furthermore, a review paper presented vMMN in a hierarchical predictive coding framework. Each paper in this Research Topic is a valuable contribution to the field of automatic visual change detection and deepens our understanding of the short term plasticity underlying predictive processes of visual perceptual learning.


Book
Active inference : the free energy principle in mind, brain, and behavior
Authors: --- ---
ISBN: 0262369974 0262362287 0262045354 Year: 2022 Publisher: Cambridge, Massachusetts : The MIT Press,


Book
The Future of Hyperspectral Imaging
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ISBN: 3039218239 3039218220 Year: 2019 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

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Keywords

information theoretic analysis --- multiplexing system --- HSI for biology --- point target detection --- digital elevation model --- neural networks --- oxygen saturation --- black polymers --- PZT --- blood detection --- multivariate analysis --- integral imaging --- hemispherical conical reflectance factor (HCRF) --- sprouting --- fluorescence --- multitemporal hyperspectral images --- plant phenotyping --- hyperspectral data mining and compression --- Raman --- medical imaging by HSI --- compressive detection --- stereo imaging --- image processing --- wound healing --- quality control --- lossless compression --- infrared hyperspectral imaging --- spectral tracking --- time series --- remote sensing --- diabetic foot ulcer --- classification --- Raman spectroscopy --- imaging --- fingerprints --- fusion --- wavelength selection --- Cramer–Rao lower bound --- three-dimensional imaging --- chemical imaging --- CS-MUSI --- total variation --- coastal dynamics --- forward observation model --- hyperspectral imaging --- fluorescence hyperspectral imaging --- age determination --- potatoes --- painting samples --- predictive coding --- hyperspectral --- video --- bi-directional reflectance distribution function (BRDF) --- optimal binary filters --- watercolours --- deep learning --- spectroscopy --- moving vehicle imaging --- sorting --- maximum likelihood --- multivariate data analysis --- interval partial least squares --- disease detection --- Raman hyperspectral imaging --- primordial leaf count --- machine learning --- spatial light modulators (SLM) --- Virginia Coast Reserve Long Term Ecological Research (VCR LTER) --- digital micromirror device (DMD) --- hyperspectral microscopy --- alternating direction method of multipliers --- statistical methods for HSI --- multiband image fusion --- digital light processor (DLP) --- linear mixture model --- retouching pigments --- liquid crystal --- principal component analysis --- Chemometrics --- compressive sensing --- PLSR --- Hyperspectral imaging

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