Publications by authors named "Andrew D Sheldon"

Computational psychiatry is a field aimed at developing formal models of information processing in the human brain, and how alterations in this processing can lead to clinical phenomena. There has been significant progress in the development of tasks and how to model them, presenting an opportunity to incorporate computational psychiatry methodologies into large- scale research projects or into clinical practice. In this viewpoint, we explore some of the barriers to incorporation of computational psychiatry tasks and models into wider mainstream research directions.

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Background: Recent advances in computational psychiatry have identified latent cognitive and perceptual states that predispose to psychotic symptoms. Behavioral data fit to Bayesian models have demonstrated an overreliance on priors (i.e.

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Recent advances in computational psychiatry have provided unique insights into the neural and cognitive underpinnings of psychotic symptoms. In particular, a host of new data has demonstrated the utility of computational frameworks for understanding how hallucinations might arise from alterations in typical perceptual processing. Of particular promise are models based in Bayesian inference that link hallucinatory perceptual experiences to latent states that may drive them.

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Auditory verbal hallucinations (AVH) frequently cause significant distress and dysfunction, and may be unresponsive to conventional treatments. Some voice-hearers report an ability to fully control the onset and offset of their AVH, making them significantly less disruptive. Measuring and understanding these abilities may lead to novel interventions to enhance control over AVH.

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What mechanisms underlie the prioritization of neural representations of visually perceived information to guide behavior? We assessed the dynamics whereby attention biases competition for representation of visual stimuli by enhancing representations of relevant information and suppressing the irrelevant. Multivariate pattern analysis (MVPA) classifiers were trained to discriminate patterns of fMRI activity associated with each of three stimuli, within several predefined ROIs. Participants performed a change-detection task wherein two of three presented items flashed at 1 Hz, one to each side of central fixation.

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Successful retrieval of an item from visual working memory (VWM) often requires an associated representation of the trial-unique context in which that item was presented. In experiment 1, fMRI of 16 male and female humans replicated a previous dissociation of the effects of manipulating memory load in comparison to the effects of manipulating context binding, by comparing VWM for one oriented line versus for three lines individuated by their location versus for three "heterogeneous" items drawn from different categories (orientation, color, and luminance): delay-period fMRI signal in frontal cortex and intraparietal sulcus (IPS) was sensitive to stimulus homogeneity rather than to memory load per se. Additionally, inspection of behavioral performance revealed a broad range of individual differences in the probability of responses to nontargets (also known as "swap errors"), and a comparison of high swap-error versus low swap-error groups generated several intriguing results: at recall, high swap-error subjects were seen to represent both the orientation and the location of the probed item less strongly, and with less differentiation from nonprobed items, and delay-period signal in IPS predicted behavioral and neural correlates of context binding at recall.

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Although humans can hold multiple items in mind simultaneously, the contents of working memory (WM) can be selectively prioritized to guide future behavior. We explored whether the "same-object" benefits in visual processing may also be observed in visual WM. fMRI data were collected while participants performed a multistep serial retrocuing task in which they first viewed two 2-D objects (coherently moving colored dots).

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Stimulus location is not always informative during visual short-term memory (VSTM) for nonspatial features. Nevertheless, there is considerable evidence for the automatic encoding and retention of location information, regardless of its task relevance. To explore the functional and neural bases of the representation of spatial context in VSTM for nonspatial information, functional magnetic resonance imaging was performed while subjects performed delayed recall for the orientation of individual stimuli.

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When subjects become unconscious, there is a characteristic change in the way the cerebral cortex responds to perturbations, as can be assessed using transcranial magnetic stimulation and electroencephalography (TMS-EEG). For instance, compared to wakefulness, during non-rapid eye movement (NREM) sleep TMS elicits a larger positive-negative wave, fewer phase-locked oscillations, and an overall simpler response. However, many physiological variables also change when subjects go from wake to sleep, anesthesia, or coma.

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Visual awareness is hypothesized to be intimately related to visual working memory (WM), such that information present in WM is thought to have necessarily been represented consciously. Recent work has challenged this longstanding view by demonstrating that visual stimuli rated by observers as unseen can nevertheless be maintained over a delay period. These experiments have been criticized, however, on the basis that subjective awareness ratings may contain response bias (e.

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