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DATA-COMPRESSION FOR CHECK PROCESSING MACHINES

PROCEEDINGS OF THE IEEE 1980年第7期68卷 874-885页

作者： YASUDA, Y DUBOIS, M HUANG, TS PURDUE UNIV SCH ELECT ENGNW LAFAYETTEIN 47907

A technique of compressing image data derived from personal checks which possess several gray levels is described. Check images consist of both essential information such as printed and handwritten characters and nonessential background pattern or picture. Only the character plane is to be coded. Our proposed technique is divided into two phases: character plane extraction and character plane coding. In the first phase, a character plane which is composed of character pels on a uniform background is extracted from an original digital check image by using a combination of fundamental techniques of image segmentation. In the second phase, the extracted character plane is separated into a bit plane and a gray-level plane. The bit plane which preserves the position information of character pels on the character plane is conditional entropy coded. An adaptive two- or one-dimensional predictive coding scheme is applied to the gray-level plane which consists of only the character pels on the character plane. The check data are stored for further use as a combination of the codes derived from the bit plane encoder and the gray-level encoder in a check processing machine. A comparative study shows that the proposed coding scheme performs much better than conventional predictive coding schemes. For 8 gray-level image data, a compression factor of about 8:1 has been achieved.

关键词： Data compression TV Image coding Data mining Facsimile Image storage Image segmentation predictive coding Pulse modulation Costs

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Prior probability and feature predictability interactively bias perceptual decisions

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NEUROPSYCHOLOGIA 2014年第1期61卷 210-221页

作者： Dunovan, Kyle E. Tremel, Joshua J. Wheeler, Mark E. Univ Pittsburgh Dept Psychol Pittsburgh PA 15260 USA Univ Pittsburgh Ctr Learning Res & Dev Pittsburgh PA 15260 USA Univ Pittsburgh Ctr Neural Basis Cognit Pittsburgh PA 15260 USA Univ Pittsburgh Ctr Neurosci Pittsburgh PA 15260 USA Georgia Inst Technol Sch Psychol Atlanta GA 30332 USA

Anticipating a forthcoming sensory experience facilitates perception for expected stimuli but also hinders perception for less likely alternatives. Recent neuroimaging studies suggest that expectation biases arise from feature-level predictions that enhance early sensory representations and facilitate evidence accumulation for contextually probable stimuli while suppressing alternatives. Reasonably then, the extent to which prior knowledge biases subsequent sensory processing should depend on the precision of expectations at the feature level as well as the degree to which expected features match those of an observed stimulus. In the present study we investigated how these two sources of uncertainty modulated pre- and post-stimulus bias mechanisms in the drift-diffusion model during a probabilistic face/house discrimination task. We tested several plausible models of choice bias, concluding that predictive cues led to a bias in both the starting-point and rate of evidence accumulation favoring the more probable stimulus category. We further tested the hypotheses that prior bias in the starting-point was conditional on the feature-level uncertainty of category expectations and that dynamic bias in the drift-rate was modulated by the match between expected and observed stimulus features. Starting-point estimates suggested that subjects formed a constant prior bias in favor of the face category, which exhibits less feature-level variability, that was strengthened or weakened by trial-wise predictive cues. Furthermore, we found that the gain on face/house evidence was increased for stimuli with less ambiguous features and that this relationship was enhanced by valid category expectations. These findings offer new evidence that bridges psychological models of decision-making with recent predictive coding theories of perception. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Expectation Perceptual decision-making Drift-diffusion model predictive coding

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Egocentric biases are predicted by the precision of self-related predictions

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CORTEX 2022年 154卷 322-332页

作者： Sevi, Leora Stantic, Mirta Murphy, Jennifer Coll, Michel-Pierre Catmur, Caroline Bird, Geoffrey Univ Oxford Dept Expt Psychol Oxford England Royal Holloway Univ London Dept Psychol Egham Surrey England Laval Univ Sch Psychol Quebec City PQ Canada Kings Coll London Inst Psychiat Psychol & Neurosci Dept Psychol London England Kings Coll London Inst Psychiat Psychol & Neurosci Social Genet & Dev Psychiat Ctr London England Univ Oxford Dept Expt Psychol Anna Watts BldgWoodstock Rd Oxford OX2 6GG England

According to predictive processing theories, emotional inference involves simultaneously minimising discrepancies between predictions and sensory evidence relating to both one's own and others' states, achievable by altering either one's own state (empathy) or perception of another's state (egocentric bias) so they are more congruent. We tested a key hypothesis of these accounts, that predictions are weighted in inference according to their precision (inverse variance). If correct, increasingly precise self-related predictions should be associated with increasingly biased perception of another's emotional expression. We manipulated predictions about upcoming own-pain (low or high magnitude) using cues that afforded either precise (a narrow range of possible magnitudes) or imprecise (a wide range) predictions. Participants judged pained facial expressions presented concurrently with own-pain to be more intense when own-pain was greater, and precise cues increased this biasing effect. Implications of conceptualising interpersonal influence in terms of predictive processing are discussed. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Emotion recognition predictive coding Empathy Generative model Precision predictive interoceptive coding

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Active inference, communication and hermeneutics

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CORTEX 2015年 68卷 129-143页

作者： Friston, Karl J. Frith, Christopher D. Inst Neurol Wellcome Trust Ctr Neuroimaging London WC1N 3BG England

Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then-in-principle they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. (C) 2015 The Authors. Published by Elsevier Ltd.

关键词： Communication Neuronal Hermeneutics Theory of mind Active inference predictive coding Bayesian Synchronisation of chaos

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Perceptual Gains and Losses in Synesthesia and Schizophrenia

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SCHIZOPHRENIA BULLETIN 2021年第3期47卷 722-730页

作者： van Leeuwen, Tessa M. Sauer, Andreas Jurjut, Anna-Maria Wibral, Michael Uhlhaas, Peter J. Singer, Wolf Melloni, Lucia Max Planck Inst Brain Res Dept Neurophysiol Frankfurt Germany Max Planck Gesell Ernst Strungmann Inst ESI Neurosci Frankfurt Germany Radboud Univ Nijmegen Donders Inst Brain Cognit & Behav Nijmegen Netherlands Goethe Univ Frankfurt Brain Imaging Ctr Magnetoencephal Unit Frankfurt Germany Univ Glasgow Inst Neurosci & Psychol Glasgow Lanark Scotland Charite Dept Child & Adolescent Psychiat Berlin Germany Goethe Univ Frankfurt Frankfurt Inst Adv Studies Frankfurt Germany NYU Dept Neurol Sch Med New York NY 10016 USA Max Planck Inst Empir Aesthet Dept Neurosci Gruneburgweg 14 D-60322 Frankfurt Germany

Individual differences in perception are widespread. Considering inter-individual variability, synesthetes experience stable additional sensations;schizophrenia patients suffer perceptual deficits in, eg, perceptual organization (alongside hallucinations and delusions). Is there a unifying principle explaining inter-individual variability in perception? There is good reason to believe perceptual experience results from inferential processes whereby sensory evidence is weighted by prior knowledge about the world. Perceptual variability may result from different precision weighting of sensory evidence and prior knowledge. We tested this hypothesis by comparing visibility thresholds in a perceptual hysteresis task across medicated schizophrenia patients (N = 20), synesthetes (N = 20), and controls (N = 26). Participants rated the subjective visibility of stimuli embedded in noise while we parametrically manipulated the availability of sensory evidence. Additionally, precise long-term priors in synesthetes were leveraged by presenting either synesthesia-inducing or neutral stimuli. Schizophrenia patients showed increased visibility thresholds, consistent with overreliance on sensory evidence. In contrast, synesthetes exhibited lowered thresholds exclusively for synesthesia-inducing stimuli suggesting high-precision long-term priors. Additionally, in both synesthetes and schizophrenia patients explicit, short-term priors-introduced during the hysteresis experiment-lowered thresholds but did not normalize perception. Our results imply that perceptual variability might result from differences in the precision afforded to prior beliefs and sensory evidence, respectively.

关键词： perceptual closure predictive coding precision weighting inter-individual variability synaesthesia schizophrenia

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Delusion, Proper Function, and Justification

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NEUROETHICS 2021年第2期14卷 113-124页

作者： Crutchfield, Parker Western Michigan Univ Homer Stryker MD Sch Med Med Eth Humanities & Law Kalamazoo MI 49008 USA

Among psychiatric conditions, delusions have received significant attention in the philosophical literature. This is partly due to the fact that many delusions are bizarre, and their contents interesting in and of themselves. But the disproportionate attention is also due to the notion that by studying what happens when perception, cognition, and belief go wrong, we can better understand what happens when these go right. In this paper, I attend to delusions for the second reason-by evaluating the epistemology of delusions, we can better understand the epistemology of ordinary belief. More specifically, given recent advancements in our understanding of how delusions are formed, the epistemology of delusions motivates a proper functionalist account of the justification of belief. Proper functionalist accounts of the justification of belief hold that whether a belief is justified is partly determined by whether the system that produces the belief is functioning properly. Whatever pathology is responsible for delusion formation, restoring it to its proper function resolves the epistemic condition, an effect which motivates proper functionalism.

关键词： Delusion Justification Proper function Rationality predictive coding

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Neural prediction of higher-order auditory sequence statistics

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NEUROIMAGE 2011年第3期54卷 2267-2277页

作者： Furl, Nicholas Kumar, Sukhbinder Alter, Kai Durrant, Simon Shawe-Taylor, John Griffiths, Timothy D. UCL Dept Comp Sci London WC1E 6BT England Newcastle Univ Inst Neurosci Newcastle Upon Tyne NE2 4HH Tyne & Wear England Univ Manchester Sch Psychol Sci Manchester M13 9PL Lancs England

During auditory perception, we are required to abstract information from complex temporal sequences such as those in music and speech. Here, we investigated how higher-order statistics modulate the neural responses to sound sequences, hypothesizing that these modulations are associated with higher levels of the peri-Sylvian auditory hierarchy. We devised second-order Markov sequences of pure tones with uniform first-order transition probabilities. Participants learned to discriminate these sequences from random ones. Magnetoencephalography was used to identify evoked fields in which second-order transition probabilities were encoded. We show that improbable tones evoked heightened neural responses after 200 ms post-tone onset during exposure at the learning stage or around 150 ms during the subsequent test stage, originating near the right temporoparietal junction. These signal changes reflected higher-order statistical learning, which can contribute to the perception of natural sounds with hierarchical structures. We propose that our results reflect hierarchical predictive representations, which can contribute to the experiences of speech and music. Published by Elsevier Inc.

关键词： Magnetoencephalography (MEG) predictive coding Temporoparietal junction (TPJ) Statistical learning

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Neural representation in active inference: Using generative models to interact with-and understand-the lived world

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ANNALS OF THE NEW YORK ACADEMY OF SCIENCES 2024年第1期1534卷 45-68页

作者： Pezzulo, Giovanni D'Amato, Leo Mannella, Francesco Priorelli, Matteo van de Maele, Toon Stoianov, Ivilin Peev Friston, Karl CNR Inst Cognit Sci & Technol Rome Italy Polytech Univ Turin Turin Italy Inst Cognit Sci & Technol Natl Res Council Padua Italy Ghent Univ Imec Dept Informat Technol IDLab Ghent Belgium UCL Wellcome Ctr Human Neuroimaging Queen Sq Inst Neurol London England VERSES Res Lab Los Angeles CA USA Inst Cognit Sci & Technol Natl Res Council Via S Martino Battaglia 44 I-00185 Rome Italy

This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize the discrepancy between predictions and observations (as scored with variational free energy). The ensuing analysis suggests that the brain learns generative models to navigate the world adaptively, not (or not solely) to understand it. Different living organisms may possess an array of generative models, spanning from those that support action-perception cycles to those that underwrite planning and imagination;namely, from explicit models that entail variables for predicting concurrent sensations, like objects, faces, or people-to action-oriented models that predict action outcomes. It then elucidates how generative models and belief dynamics might link to neural representation and the implications of different types of generative models for understanding an agent's cognitive capabilities in relation to its ecological niche. The paper concludes with open questions regarding the evolution of generative models and the development of advanced cognitive abilities-and the gradual transition from pragmatic to detached neural representations. The analysis on offer foregrounds the diverse roles that generative models play in cognitive processes and the evolution of neural representation. This paper examines neural representation under active inference. Organisms employ generative models to navigate the world adaptively, not (or not solely) to understand it. Crucially, different organisms might employ different types of generative models, ranging from action-oriented models (predicting outcomes) to explicit models (reconstructing the external environment). Connecting meaning to agentive action to the array of generative models imparts diverse forms of understanding of an organism's ecological niche. image

关键词： action-oriented models active inference explicit models generative model neural representation predictive coding

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Visual speech speeds up the neural processing of auditory speech

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2005年第4期102卷 1181-1186页

作者： van Wassenhove, V Grant, KW Poeppel, D Univ Maryland Neurosci & Cognit Sci Program College Pk MD 20742 USA Univ Maryland Dept Biol College Pk MD 20742 USA Univ Maryland Dept Linguist College Pk MD 20742 USA Walter Reed Army Med Ctr Auditory Visual Speech Lab Washington DC 20307 USA

Synchronous presentation of stimuli to the auditory and visual systems can modify the formation of a percept in either modality. For example, perception of auditory speech is improved when the speaker's facial articulatory movements are visible. Neural convergence onto multisensory sites exhibiting supra-additivity has been proposed as the principal mechanism for integration. Recent findings, however, have suggested that putative sensory-specific cortices are responsive to inputs presented through a different modality. Consequently, when and where audiovisual representations emerge remain unsettled. In combined psychophysical and electroencephalography experiments we show that visual speech speeds up the cortical processing of auditory signals early (within 100 ms of signal onset). The auditory-visual interaction is reflected as an articulator-specific temporal facilitation (as well as a nonspecific amplitude reduction). The latency facilitation systematically depends on the degree to which the visual signal predicts possible auditory targets. The observed auditory-visual data support the view that there exist abstract internal representations that constrain the analysis of subsequent speech inputs. This is evidence for the existence of an "analysis-by-synthesis" mechanism in auditory-visual speech perception.

关键词： EEG multisensory predictive coding

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Pain and Reorganization after Amputation: Is Interoceptive Prediction a Key?

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NEUROSCIENTIST 2023年第6期29卷 665-675页

作者： Weiss, Thomas Koehler, Hanna Croy, Ilona Friedrich Schiller Univ Jena Dept Psychol Clin Psychol Steiger 3 Haus 1 D-07743 Jena Germany Jena Univ Hosp Biomagnet Ctr Jena Germany

There is an ongoing discussion on the relevance of brain reorganization following amputation for phantom limb pain. Recent attempts to provide explanations for seemingly controversial findings-specifically, maladaptive plasticity versus persistent functional representation as a complementary process-acknowledged that reorganization in the primary somatosensory cortex is not sufficient to explain phantom limb pain satisfactorily. Here we provide theoretical considerations that might help integrate the data reviewed and suppose a possible additional driver of the development of phantom limb pain-namely, an error in interoceptive predictions to somatosensory sensations and movements of the missing limb. Finally, we derive empirically testable consequences based on our considerations to guide future research.

关键词： phantom limb pain cortical reorganization interoception prediction error predictive coding

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