Social cognitive processes, particularly Theory of Mind (ToM) reasoning, appear to differ between autistic and non-autistic individuals. This has been proposed to reflect the autistic core symptomatology of communicat...
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Social cognitive processes, particularly Theory of Mind (ToM) reasoning, appear to differ between autistic and non-autistic individuals. This has been proposed to reflect the autistic core symptomatology of communication and social interaction difficulties. According to the predictive coding theory, autistic individuals' ToM reasoning difficulties arise from an attenuated use of prior information about others' mental states to explain and predict their behavior. This reduced use of prior assumptions makes the social world less predictable for autistic people, causing interactive mismatch and stress. Despite strong theoretical claims, robust and replicable neural differences in ToM brain regions remain elusive. Here, we investigated whether brain regions supporting ToM reasoning anticipate a narrative during repeated exposure (i.e., the narrative anticipation effect) in non-autistic adults (Experiment 1) and tested whether this effect was attenuated in autistic adults (Experiment 2). We presented a short movie with a plot including mental states with associated actions, twice, to 61 non-autistic adults who underwent functional magnetic resonance imaging [Experiment 1: M(SD)age = 25.9(4.4) years]. In Experiment 2, we used the same protocol with 30 autistic [M(SD)age = 32.4(10.7) years] and 30 non-autistic adults [M(SD)age = 33.2(10.1) years]. Analyses revealed no narrative anticipation effect in the ToM network in either group. Exploratory reverse correlation analyses identified a ToM scene that evoked a smaller difference in response between movie viewings (i.e., less repetition suppression) in autistic adults, compared to non-autistic adults. In sum, our study shows that predictive processing in the ToM network during a naturalistic movie-viewing experiment was absent in adults. Subtle differences in a key scene provide preliminary neural evidence for the predictive coding theory and open a promising avenue for future research to better understand the nature of diff
This paper investigates the design of a system of predictive vector quantizers for distributed sources with memory, in which linear prediction is used to exploit the source memory, while distributed quantization is us...
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This paper investigates the design of a system of predictive vector quantizers for distributed sources with memory, in which linear prediction is used to exploit the source memory, while distributed quantization is used to exploit the correlation between sources. A training-based algorithm is proposed for jointly designing the predictors, binning functions, and reconstruction codebooks of the given system to match the intra-and inter-source correlations. In order to demonstrate the effectiveness of the algorithm, experimental results obtained by designing both scalar and vector quantizers for a set of distributed Gauss-Markov sources are presented. While the optimality of these designs is unknown, it is shown that they convincingly outperform several other alternatives.
A quadtree segmented two-dimensional predictive coding technique is presented in this paper for exploiting correlation between adjacent image blocks and uniformity in variable block size image blocks. Visual pattern b...
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A quadtree segmented two-dimensional predictive coding technique is presented in this paper for exploiting correlation between adjacent image blocks and uniformity in variable block size image blocks. Visual pattern block truncation coding (VP-BTC) is employed to code the high activity 4/spl times/4 image blocks, with a set of sixteen visual patterns used to encode the 4/spl times/4 bitmaps. Simulation results showed that the new coding technique achieved substantial bit rate reduction with good subjective quality.
Multiple Description (MD) coding of predictively coded sources is of practical interest in several multimedia applications such as redundant storage of video/audio data, and real-time video/audio telephony. A key prob...
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ISBN:
(纸本)0780375106
Multiple Description (MD) coding of predictively coded sources is of practical interest in several multimedia applications such as redundant storage of video/audio data, and real-time video/audio telephony. A key problem associated with predictive MD coding is the occurrence of predictive mismatch. In the present paper, we pose the problem of predictive MD coding as a variant of the Wyner-Ziv decoder side-in formation problem. We propose an approach based on the use of coset codes for predictive MD coding, which avoids predictive mismatch without requiring restrictive channel assumptions or high latency. We specifically consider two-channel predictive MD coding of a first-order Gauss-Markov process. Results indicate that the proposed approach significantly out-performs alternative approaches in terms of rate-distortion performance.
Repetition suppression (RS) refers to the reduction of neuronal responses to repeated stimuli as compared to nonrepeated stimuli. The predictive coding account of RS proposes that its magnitude is modulated by repetit...
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Repetition suppression (RS) refers to the reduction of neuronal responses to repeated stimuli as compared to nonrepeated stimuli. The predictive coding account of RS proposes that its magnitude is modulated by repetition probability (P(rep)) and that this modulation increases with prior experience with the stimulus category. To test these proposals, we examined RS and its modulation by P(rep) for three stimulus categories for which participants had different expertise (Asian faces, written Chinese words and animals) using EEG. Cantonese speakers watched paired stimuli (S1-S2) of a given category with S2 being the same or a different stimulus as S1. Attributes of S1 (e.g., the sex of the first face) served as a cue for the repetition probability of S2. There were significant repetition effects and distinct topographic distributions across stimulus categories. Repetition effects in the N250 component were present in all stimulus categories, but in words, they appeared earlier and showed distinct topographic patterns compared to faces and animals. These results suggest that repetition effects differ between stimulus categories, presumably depending on prior experience and stimulus properties, such as spatial frequency. Importantly, we failed to find evidence for effects of P(rep) across any of the three categories. These null findings of P(rep) effects are putatively indicating an absence of expectancy modulation of repetition effects.
Natural, continuous tone images have the very important property of high correlation of adjacent pixels. This property is cleverly exploited in lossless image compression where, prior to the statistical modeling and e...
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Natural, continuous tone images have the very important property of high correlation of adjacent pixels. This property is cleverly exploited in lossless image compression where, prior to the statistical modeling and entropy coding step, predictive coding is used as a decorrelation tool. The use of prediction for the current pixel also reduces the cost of the applied statistical model for entropy coding. Linear prediction, where the predicted value is a linear function of previously encoded pixels (causal template), has proven to give very good results as a decorrelation tool in lossless image compression. We concentrate on adaptive linear predictors used in lossless image coding and propose a new linear prediction method.
This paper presents a novel approach to compress depth maps envisioned for virtual view synthesis. This proposal uses a sophisticated prediction model, combining the HEVC intra prediction modes with a flexible partiti...
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ISBN:
(纸本)9781479923427
This paper presents a novel approach to compress depth maps envisioned for virtual view synthesis. This proposal uses a sophisticated prediction model, combining the HEVC intra prediction modes with a flexible partitioning scheme. It exhaustively evaluates the prediction modes for a large amount of block sizes, in order to find the minimum coding cost for each depth map block. Unlike HEVC, no transform is used, the residue being trivially encoded through the transmission of just its mean value. The experimental results show that, when the encoding evaluation metric is the quality of the view synthesized using the encoded depth map against the map encoding rate, the proposed algorithm generates reconstructed depth maps that provide, for most bitrates, some of the best performances among state-of-the-art depth maps encoders. In addition, it runs approximately as fast as the HEVC HM.
Acoustic Unit Discovery (AUD) aims to obtain phoneme-like units that preserve linguistically significant information while removing paralinguistic details. Although Contrastive predictive coding (CPC) has emerged as a...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
Acoustic Unit Discovery (AUD) aims to obtain phoneme-like units that preserve linguistically significant information while removing paralinguistic details. Although Contrastive predictive coding (CPC) has emerged as a leading self-supervised representation learning method for this task, CPC-based methods still suffer from the limitation that the learned representations are susceptible to paralinguistic information and less discriminative. Inspired by the theory of distinctive features, we propose a new approach that builds a binary discriminative representation space and employs binary contrastive learning based on CPC to tackle the aforementioned issues. Experimental results show that our method achieves better results in AUD task and produces discriminative binary representations.
Object Prediction, as a fundamental cognitive function of the brain, is the ability of reducing the uncertainty of upcoming events, which contributes a lot to our daily interactions with the constantly changing enviro...
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Object Prediction, as a fundamental cognitive function of the brain, is the ability of reducing the uncertainty of upcoming events, which contributes a lot to our daily interactions with the constantly changing environment. However, the underlying neural mechanism still remains unclear. A potential explanation is the predictive coding theory, which proposed that our perceptions are formed by forward transmitting the prediction errors between the intrinsic predictive template and incoming sensory inputs. It assumes that there is a hierarchical framework in the brain to integrate the top-down expectations with the bottom-up senses, and at each level, the predictive template is encoded by the representation unit, while the residual error is encoded by the error unit. However, it remains unknown whether the theory proposed for predicting "what" could apply to predicting "when". This study aims to examine the neural framework of predictive timing in the brain. Methods Two predictive timing templates of 400 ms and 600 ms durations were stably built up for each subject after 1-week training to discriminate three different intervals between two successive LED flashes, i.e. 400 ms, 600 ms and 900 ms. During electroencephalography(EEG) experiment, Subjects were required to judge the flash duration presented before them with three different mental tasks: 1. deciding whether the duration was 400 ms or not by pressing one of two alternative buttons as quickly as possible;2. Deciding whether the duration is 600 ms or not by pressing one of two alternative buttons as quickly as possible;3. Pressing a button after second flash as quickly as possible. The experiment or each subject contained 12 blocks which were equally distributed into the three mental tasks. Each block contained twelve trials of 400 ms durations, twelve trials of 600 ms durations and six trials of other random durations, which were displayed in a random sequence. Thirty-six healthy volunteers aged between 19 and 2
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