Altered visual conscious awareness in patients with vestibular dysfunctions; a cross-sectional observation study.

BACKGROUND: Patients with vestibular dysfunctions often experience visual-induced symptoms. Here we asked whether such visual dependence can be related to alterations in visual conscious awareness in these patients. METHODS: To measure visual conscious awareness, we used the effect of motion-induced blindness (MIB,) in which the perceptual awareness of the visual stimulus alternates despite its unchanged physical characteristics. In this phenomenon, a salient visual target spontaneously disappears and subsequently reappears from visual perception when presented against a moving visual background. The number of perceptual switches during the experience of the MIB stimulus was measured for 120 s in 15 healthy controls, 15 patients with vestibular migraine, 15 patients with benign positional paroxysmal vertigo (BPPV) and 15 with migraine without vestibular symptoms. RESULTS: Patients with vestibular dysfunctions (i.e., both vestibular migraine and BPPV) exhibited increased perceptual fluctuations during MIB compared to healthy controls and migraine patients without vertigo. In VM patients, those with more severe symptoms exhibited higher fluctuations of visual awareness (i.e., positive correlation), whereas, in BPPV patients, those with more severe symptoms had lower fluctuations of visual awareness (i.e., negative correlation). IMPLICATIONS: Taken together, these findings show that fluctuations of visual awareness are linked to the severity of visual-induced symptoms in patients with vestibular dysfunctions, and distinct pathophysiological mechanisms may mediate visual vertigo in peripheral versus central vestibular dysfunctions.

A continuous source reinstatement model of true and false recollection.

In studies of false recognition, subjects not only endorse items that they have never seen, but they also make subjective judgments that they remember consciously experiencing them. This is a difficult problem for most models of recognition memory, as they propose that false memories should be based on familiarity, not recollection. We present a new computational model of recollection, based on the Recognition through Semantic Synchronization (RSS) model of Johns, Jones, & Mewhort (Cognitive Psychology, 2012, 65, 486), and fuzzy trace theory (Brainerd & Reyna, Current Directions in Psychological Science, 2002, 11, 164), that offers a solution to this problem. In addition to standard true and false recognition results, the model successfully extends to explain multiple studies on both true and false recollection. This work suggests that recollection does not have to be thought of as a separate process from recognition, but instead as one that is reliant upon different information sources. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The basis of report-difference superiority in delayed perceptual comparison tasks.

A major role for visual short-term memory (VSTM) is to mediate perceptual comparisons of visual information across successive glances and brief temporal interruptions. Research that has focused on the comparison process has noted a marked tendency for performance to be better when participants are required to report a difference between the displays rather than report the absence of a difference (i.e. a sameness). We refer to this performance asymmetry as report-difference superiority (RDS). It has been suggested that RDS reflects the operation of a reflexive mechanism that generates a mismatch signal during the comparison of visual input with information maintained in VSTM. This bottom-up mechanism therefore gives evidence for the presence of a feature change but not for the absence of such a change; consequently, a sameness is harder to detect than a difference between two displays. We test this explanation, and determine whether by itself it is a sufficient explanation of the RDS. In a delayed comparison task we find the RDS effect is most prevalent when items retain the same display locations; however, the effect does persist even when compared item locations were scrambled across memory and test arrays. However, with a conjunction task this scrambling of locations was effective in wholly abolishing the RDS effect. We consider that the RDS effect is a consequence of local comparisons of features, as well as global statistical comparisons.

The Role of Negative Information in Distributional Semantic Learning.

Distributional models of semantics learn word meanings from contextual co-occurrence patterns across a large sample of natural language. Early models, such as LSA and HAL (Landauer & Dumais, 1997; Lund & Burgess, 1996), counted co-occurrence events; later models, such as BEAGLE (Jones & Mewhort, 2007), replaced counting co-occurrences with vector accumulation. All of these models learned from positive information only: Words that occur together within a context become related to each other. A recent class of distributional models, referred to as neural embedding models, are based on a prediction process embedded in the functioning of a neural network: Such models predict words that should surround a target word in a given context (e.g., word2vec; Mikolov, Sutskever, Chen, Corrado, & Dean, 2013). An error signal derived from the prediction is used to update each word's representation via backpropagation. However, another key difference in predictive models is their use of negative information in addition to positive information to develop a semantic representation. The models use negative examples to predict words that should not surround a word in a given context. As before, an error signal derived from the prediction prompts an update of the word's representation, a procedure referred to as negative sampling. Standard uses of word2vec recommend a greater or equal ratio of negative to positive sampling. The use of negative information in developing a representation of semantic information is often thought to be intimately associated with word2vec's prediction process. We assess the role of negative information in developing a semantic representation and show that its power does not reflect the use of a prediction mechanism. Finally, we show how negative information can be efficiently integrated into classic count-based semantic models using parameter-free analytical transformations.

Refining the law of practice.

The "law of practice"-a simple nonlinear function describing the relationship between mean response time (RT) and practice-has provided a practically and theoretically useful way of quantifying the speed-up that characterizes skill acquisition. Early work favored a power law, but this was shown to be an artifact of biases caused by averaging over participants who are individually better described by an exponential law. However, both power and exponential functions make the strong assumption that the speedup always proceeds at a steadily decreasing rate, even though there are sometimes clear exceptions. We propose a new law that can both accommodate an initial delay resulting in a slower-faster-slower rate of learning, with either power or exponential forms as limiting cases, and which can account for not only mean RT but also the effect of practice on the entire distribution of RT. We evaluate this proposal with data from a broad array of tasks using hierarchical Bayesian modeling, which pools data across participants while minimizing averaging artifacts, and using inference procedures that take into account differences in flexibility among laws. In a clear majority of paradigms our results supported a delayed exponential law. (PsycINFO Database Record

The response of relativistic outflowing gas to the inner accretion disk of a black hole.

The brightness of an active galactic nucleus is set by the gas falling onto it from the galaxy, and the gas infall rate is regulated by the brightness of the active galactic nucleus; this feedback loop is the process by which supermassive black holes in the centres of galaxies may moderate the growth of their hosts. Gas outflows (in the form of disk winds) release huge quantities of energy into the interstellar medium, potentially clearing the surrounding gas. The most extreme (in terms of speed and energy) of these-the ultrafast outflows-are the subset of X-ray-detected outflows with velocities higher than 10,000 kilometres per second, believed to originate in relativistic (that is, near the speed of light) disk winds a few hundred gravitational radii from the black hole. The absorption features produced by these outflows are variable, but no clear link has been found between the behaviour of the X-ray continuum and the velocity or optical depth of the outflows, owing to the long timescales of quasar variability. Here we report the observation of multiple absorption lines from an extreme ultrafast gas flow in the X-ray spectrum of the active galactic nucleus IRAS 13224-3809, at 0.236 ± 0.006 times the speed of light (71,000 kilometres per second), where the absorption is strongly anti-correlated with the emission of X-rays from the inner regions of the accretion disk. If the gas flow is identified as a genuine outflow then it is in the fastest five per cent of such winds, and its variability is hundreds of times faster than in other variable winds, allowing us to observe in hours what would take months in a quasar. We find X-ray spectral signatures of the wind simultaneously in both low- and high-energy detectors, suggesting a single ionized outflow, linking the low- and high-energy absorption lines. That this disk wind is responding to the emission from the inner accretion disk demonstrates a connection between accretion processes occurring on very different scales: the X-ray emission from within a few gravitational radii of the black hole ionizing the disk wind hundreds of gravitational radii further away as the X-ray flux rises.

A synchronization account of false recognition.

We describe a computational model to explain a variety of results in both standard and false recognition. A key attribute of the model is that it uses plausible semantic representations for words, built through exposure to a linguistic corpus. A study list is encoded in the model as a gist trace, similar to the proposal of fuzzy trace theory (Brainerd & Reyna, 2002), but based on realistically structured semantic representations of the component words. The model uses a decision process based on the principles of neural synchronization and information accumulation. The decision process operates by synchronizing a probe with the gist trace of a study context, allowing information to be accumulated about whether the word did or did not occur on the study list, and the efficiency of synchronization determines recognition. We demonstrate that the model is capable of accounting for standard recognition results that are challenging for classic global memory models, and can also explain a wide variety of false recognition effects and make item-specific predictions for critical lures. The model demonstrates that both standard and false recognition results may be explained within a single formal framework by integrating realistic representation assumptions with a simple processing mechanism.

Serial-position effects for lures in short-term recognition memory.

Serial-position curves for targets in short-term recognition memory show modest primacy and marked recency. To construct serial-position curves for lures, we tested orthographic neighbours of study words and assigned each lure to the position of its studied neighbour. The curve for lures was parallel to that for targets. In Experiment 2, only half the lures were neighbours of study words; the other half overlapped a study word by a single letter. The serial-position curve for neighbours of study items was now flatter than the curve for targets. The results are inconsistent with theories in which any factor that benefits targets must hinder lures. Instead, they demand a decision mechanism that assigns a role to item-specific information, as well as to general familiarity information, such as dual-process theory.

The changing face of infection: a comparative review of admissions to a regional infection unit over three decades.

BACKGROUND AND AIMS: Our group previously published retrospective analyses of 12 months of admissions to the Grampian Regional Infectious Diseases Unit from 1980-81 and from 1991. This study aimed to collect data in 2001 and to compare annual admission numbers, diagnoses, duration of stay and outcome in 1980-81, 1991 and 2001. METHODS: Data on all admissions was collected prospectively throughout 2001. This was compared with the previously published data. RESULTS: Total admissions rose from 605 in 1980-81 to 900 in 1991 and to 1152 in 2001. Sixty one percent of admissions in 1980-81 were confirmed as having infection compared to 72% in 1991 and to 83% in 2001. The most common reason for admission in 2001 was skin and soft tissue infection, but this was only the ninth commonest reason in 1981. Mean length of stay fell from 9.6 days in 1980-81 to 7.4 days in 1991 and to 5.5 days in 2001. The mortality rate fell from 3.1% in 1981 and 1991 to 1.0% in 2001. CONCLUSIONS: This study demonstrates significant changes in type, number and outcome of admissions to a regional infection unit. We discuss possible reasons for these changes.

Representing word meaning and order information in a composite holographic lexicon.

The authors present a computational model that builds a holographic lexicon representing both word meaning and word order from unsupervised experience with natural language. The model uses simple convolution and superposition mechanisms (cf. B. B. Murdock, 1982) to learn distributed holographic representations for words. The structure of the resulting lexicon can account for empirical data from classic experiments studying semantic typicality, categorization, priming, and semantic constraint in sentence completions. Furthermore, order information can be retrieved from the holographic representations, allowing the model to account for limited word transitions without the need for built-in transition rules. The model demonstrates that a broad range of psychological data can be accounted for directly from the structure of lexical representations learned in this way, without the need for complexity to be built into either the processing mechanisms or the representations. The holographic representations are an appropriate knowledge representation to be used by higher order models of language comprehension, relieving the complexity required at the higher level.