Objective: The current article set out to review all research conducted to date investigating prospective memory (PM) in autism. Method: All studies on PM in autism are first described, followed by a critical review a...
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Objective: The current article set out to review all research conducted to date investigating prospective memory (PM) in autism. Method: All studies on PM in autism are first described, followed by a critical review and discussion of experimental findings within the multiprocess framework. PM in autism is then considered through an embodied predictive-coding account of autism. Results: Overall, despite somewhat inconsistent methodologies, a general deficit in PM in autism is observed, with evidence mostly in line with the multiprocess framework. That is, for tasks that are high in cognitive and attentional demand (e.g. time-based tasks;event-based cues of non-focality or low salience) PM performance of autistic participants is impaired. Building upon previous work in predictive-coding, and the way in which expected precision modulates attention, we postulate mechanisms that underpin PM and the potential deficits seen in autism. Furthermore, a unifying predictive-coding account of autism is extended under embodied predictive-coding models, to show how a predictive-coding impairment accounts not only for characteristic autistic difficulties, but also for commonly found differences in autistic movement. Conclusions: We show how differences in perception and action, core to the development of autism, lead directly to problems seen in PM. Using this link between movement and PM, we then put forward a number of holistic, embodied interventions to support PM in autism.
Objective: The study sought to assess the presence of auditory N100 gating deficits in patients with schizophrenia by meta-analysis. Methods: Literature was screened for studies on patients with schizophrenia that use...
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Objective: The study sought to assess the presence of auditory N100 gating deficits in patients with schizophrenia by meta-analysis. Methods: Literature was screened for studies on patients with schizophrenia that used the paired-click paradigm and reported N100 data. Both electroencephalographic and magnetoencephalographic studies were considered. N100 gating measures as well as the N100 amplitudes to the initial and repeated stimulus were extracted and subjected to a meta-analysis. Results: The literature research revealed 29 studies, reporting either N100 gating or N100 amplitude measures in paired-click experiments. Patients with schizophrenia exhibited less N100 gating than healthy controls across studies (mean g = -0.405, SE = 0.051). However, what appeared as a gating deficit in patients was due to reduced N100 amplitudes to the initial stimulus in this group (mean g = 0.610, SE = 0.075). Patients and controls did not differ in their N100 amplitudes to the repeated stimulus (mean g = 0.042, SE = 0.066). Conclusion: There is no evidence for an auditory N100 gating deficit in schizophrenia, but for an impaired N100 response recovery. Significance: Previous findings on impaired N100 gating in schizophrenia patients reflect deficient processing of auditory salience rather than defective inhibition of repeating redundant auditory stimulation. (C) 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
A given pattern of optical stimulation can arise from countless possible real-world sources, creating a dilemma for vision: What in the world actually gives rise to the current pattern? This dilemma was pointed out ce...
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A given pattern of optical stimulation can arise from countless possible real-world sources, creating a dilemma for vision: What in the world actually gives rise to the current pattern? This dilemma was pointed out centuries ago by the astronomer and mathematician Ibn Al-Haytham and was forcefully restated 150 years ago when von Helmholtz characterized perception as unconscious inference. To buttress his contention, von Helmholtz cited multistable perception: recurring changes in perception despite unchanging sensory input. Recent neuroscientific studies have exploited multistable perception to identify brain areas uniquely activated in association with these perceptual changes, but the specific roles of those activations remain controversial. This article provides an overview of theoretical models of multistable perception, a review of recent neuroimaging and brain stimulation studies focused on mechanisms associated with these perceptual changes, and a synthesis of available evidence within the context of current notions about Bayesian inference that find their historical roots in von Helmholtz's work.
Networks of "conscious agents" (CAs) as defined by Hoffman and Prakash (2014) are shown to provide a robust and intuitive representation of perceptual and cognitive processes in the context of the Interface ...
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Networks of "conscious agents" (CAs) as defined by Hoffman and Prakash (2014) are shown to provide a robust and intuitive representation of perceptual and cognitive processes in the context of the Interface Theory of Perception (Hoffman, Singh and Prakash, 2015). The behavior of the simplest CA networks is analyzed exhaustively. The construction of short-and long-term memories and the implementation of attention, categorization and case-based planning are demonstrated. These results show that robust perception and cognition can be modelled independently of any ontological assumptions about the world in which an agent is embedded. Any agent-world interaction can, in particular, also be represented as an agent-agent interaction. (C) 2017 Elsevier B.V. All rights reserved.
Background People react very differently when sick, and there are only poor correlations between the intensity of the immune response and sickness behavior. Yet, alternative predictors of the individual differences in...
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Background People react very differently when sick, and there are only poor correlations between the intensity of the immune response and sickness behavior. Yet, alternative predictors of the individual differences in sickness are under-investigated. Based on the predictive coding model of placebo responses, where health outcomes are function of bottom-up sensory information and top-down expectancies, we hypothesized that individual differences in behavioral changes during sickness could be explained by individual top-down expectancies and prediction errors. Methods: Twenty-two healthy participants were made sick by intravenously administering lipopolysaccharide (2 ng/kg body weight). Their expectations of becoming sick were assessed before the injection. Results: Participants having lower expectations of becoming sick before the injection reacted with more emotional distress (i.e., more negative affect and lower emotional arousal) than those with high expectations of becoming sick, despite having similar overall sickness behavior (i.e., a combined factor including fatigue, pain, nausea and social withdrawal). In keeping with a predictive coding model, the "prediction error signal", i.e., the discrepancy between the immune signal and sickness expectancy, predicted emotional distress (reduction in emotional arousal in particular). Conclusion: The current findings suggest that the emotional component of sickness behavior is, at least partly, shaped by top-down expectations. Helping patients having a realistic expectation of symptoms during treatment of an illness may thus reduce aggravated emotional responses, and ultimately improve patients' quality of life and treatment compliance.
Detecting regularities in the sensory environment licenses predictions that enable adaptive behaviour. However, it is unclear whether predictions about object category, location, or both dimensions are mediated by ove...
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Detecting regularities in the sensory environment licenses predictions that enable adaptive behaviour. However, it is unclear whether predictions about object category, location, or both dimensions are mediated by overlapping systems, and relatedly, whether constructing predictions about both category and location is associated with processing bottlenecks. To examine this issue, in an fMRI study, we presented participants with image-series in which non-deterministic transition probabilities enabled predictions about either the location of the next image, its semantic category, both dimensions, or neither (the latter forming a "no-regularity" random baseline condition). Speaking to a common system, all three predictable conditions resulted in reduced BOLD activity in four clusters: left rostral anterior cingulate cortex;bilateral putamen, caudate and thalamus;right precentral gyrus, and left visual cortex. Pointing to a processing bottleneck, in some regions, a significant interaction between the two factors was found whereby category-predictable series were associated with lower activity -but only when location regularity was absent. Finally, category regularity decreased activation in areas of the ventral visual stream and semantic areas of lateral temporal cortex, and location regularity decreased activation in a dorsal fronto-parietal cluster, long implicated in the endogenous control of spatial attention. Our findings confirm and expand a role for dACC/dmPFC and striatum in monitoring or responding to uncertainty in the environment and point to a limited capacity bottleneck when multiple predictions are concurrently licensed.
Mismatch negativity (MMN) represents an event-related potential (ERP) component which is elicited by deviant sound events in an otherwise regular, repetitive stimulation. The MMN amplitude typically decreases when two...
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Mismatch negativity (MMN) represents an event-related potential (ERP) component which is elicited by deviant sound events in an otherwise regular, repetitive stimulation. The MMN amplitude typically decreases when two identical deviants are presented in direct succession, but it remains stable when the two deviants vary from the standard in different features. Less is known about such repetition effects on another ERP component, the P3a, which usually follows the MMN. In the current study, we investigated how the P3a was affected by identical and non-identical repetitions of sound deviants. The ERP analysis revealed that the P3a amplitudes were strongly diminished when the repeated deviants were identical, but the P3a remained stable when the repeated deviants varied. The findings suggest that not only the deviance detection system, as reflected in the MMN, but also subsequent attention switch systems, as reflected in the P3a, operate independently across different sound features.
Spectral redundancy is a key element to be exploited in compression of remote sensing data. Combined with an entropy encoder, it can achieve competitive lossless coding performance. One of the latest techniques to dec...
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Spectral redundancy is a key element to be exploited in compression of remote sensing data. Combined with an entropy encoder, it can achieve competitive lossless coding performance. One of the latest techniques to decorrelate the spectral signal is the regression wavelet analysis (RWA). RWA applies a wavelet transform in the spectral domain and estimates the detail coefficients through the approximation coefficients using linear regression. RWA was originally coupled with JPEG 2000. This letter introduces a novel coding approach, where RWA is coupled with the predictor of CCSDS-123.0-B-1 standard and a lightweight contextual arithmetic coder. In addition, we also propose a smart strategy to select the number of RWA decomposition levels that maximize the coding performance. Experimental results indicate that, on average, the obtained coding gains vary between 0.1 and 1.35 bits-per-pixel-per-component compared with the other state-of-the-art coding techniques.
The construct of emotional intelligence (EI) broadly reflects the idea that individuals differ in their disposition/ability to adaptively generate, recognize, understand, and regulate the emotions of self and others. ...
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The construct of emotional intelligence (EI) broadly reflects the idea that individuals differ in their disposition/ability to adaptively generate, recognize, understand, and regulate the emotions of self and others. However, while the neural processes underlying such differences have begun to receive investigation, no brain-based model of EI has yet been proposed to help guide the design and interpretation of neuroimaging research in this area. In this article, we propose a neural model of EI to fill this need. This model incorporates recent insights from emotion theory, computational neuroscience, and large-scale network models of brain function. It also highlights several domain general processes - including those underlying conceptualization, automatic attention, habit formation, and cognitive control - that offer plausible targets for improving EI with training. Our model offers considerable promise in advancing understanding of intelligent emotional functioning and in guiding future neuroscience research on EI.
This paper features two studies confirming a lasting impact of first learning on how subsequent experience is weighted in early relevance-filtering processes. In both studies participants were exposed to sequences of ...
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This paper features two studies confirming a lasting impact of first learning on how subsequent experience is weighted in early relevance-filtering processes. In both studies participants were exposed to sequences of sound that contained a regular pattern on two different timescales. Regular patterning in sound is readily detected by the auditory system and used to form "prediction models" that define the most likely properties of sound to be encountered in a given context. The presence and strength of these prediction models is inferred from changes in automatically elicited components of auditory evoked potentials. Both studies employed sound sequences that contained both a local and longer-termpattern. The local pattern was defined by a regular repeating pure tone occasionally interrupted by a rare deviating tone (p=0.125) that was physically different (a 30 ms vs. 60 ms duration difference in one condition and a 1000 Hz vs. 1500 Hz frequency difference in the other). The longer-term pattern was defined by the rate at which the two tones alternated probabilities (i.e., the tone that was first rare became common and the tone that was firstcommon became rare). There was no task related to the tones and participants were asked to ignore them while focussing attention on a movie with subtitles. Auditory-evoked potentials revealed long lasting modulatory influences based on whether the tone was initially encountered as rare and unpredictable or common and predictable. The results are interpreted as evidence that probability (or indeed predictability) assigns a differential information-value to the two tones that in turn affects the extent to which prediction models are updated and imposed. These effects are exposed for both common and rare occurrences of the tones. The studies contribute to a body of work that reveals that probabilistic information is not faithfully represented in these early evoked potentials and instead exposes that predictability (or conversely unc
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