The subcortical confinement hypothesis: A neurological model for schizotypal hallucinations

Introduction Different types of hallucinations are symptomatic of different conditions. Schizotypal hallucinations are unique in that they follow existing delusional narrative patterns: they are often bizarre, they are generally multimodal, and they are particularly vivid (the experience of a newsreader abusing you personally over the TV is both visual and aural. Patients who feel and hear silicone chips under their skin suffer from haptic hallucinations as well as aural ones, etc.) Although there are a number of hypotheses for hallucinations, few cogently grapple the sheer bizarreness of the ones experienced in schizotypal psychosis. Methods A review-based hypothesis, traversing theory from the molecular level to phenomenological expression as a distinct and recognizable symptomatology. Conclusion Hallucinations appear to be caused by a two-fold dysfunction in the mesofrontal dopamine pathway, which is considered here to mediate attention of different types: in the anterior medial frontal lobe, the receptors (largely D1 type) mediate declarative awareness, whereas the receptors in the striatum (largely D2 type) mediate latent awareness of known schemata. In healthy perception, most of the perceptual load is performed by the latter: by the top-down predictive and mimetic engine, with the bottom-up mechanism being used as a secondary tool to bring conscious deliberation to stimuli that fails to match up against expectations. In schizophrenia, the predictive mode is over-stimulated, while the bottom-up feedback mechanism atrophies. The dysfunctional distribution pattern effectively confines dopamine activity to the striatum, thereby stimulating the structural components of thought and behaviour: well-learned routines, narrative structures, lexica, grammar, schemata, archetypes, and other procedural resources. Meanwhile, the loss of activity in the frontal complex reduces the capacity for declarative awareness and for processing anything that fails to meet expectations.

Common psychotic symptoms can be explained by the theory of ecological perception

The symptoms of psychiatric illness are diverse, as are the causes of the illnesses that cause them. Yet, regardless of the heterogeneity of cause and presentation, a great deal of symptoms can be explained by the failure of a single perceptual function – the reprocessing of ecological perception. It is a central tenet of the ecological theory of perception that we perceive opportunities to act. It has also been found that perception automatically causes actions and thoughts to occur unless this primary action pathway is inhibited. Inhibition allows perceptions to be reprocessed into more appropriate alternative actions and thoughts. Reprocessing of this kind takes place over the entire frontal lobe and it renders action optional. Choice about what action to take (if any) is the basis for the feeling of autonomy and ultimately for the sense-of-self. When thoughts and actions occur automatically (without choice) they appear to originate outside of the self, thereby providing prima facie evidence for some of the bizarre delusions that define schizophrenia such as delusional misidentification, delusions of control and Cotard’s delusion. Automatic actions and thoughts are triggered by residual stimulation whenever reprocessing is insufficient to balance automatic excitatory cues (for whatever reason). These may not be noticed if they are neutral and therefore unimportant whereas actions and thoughts with a positive bias are desirable. Responses to negative stimulus, on the other hand, are always unwelcome, because the actions that are triggered will carry the negative bias. Automatic thoughts may include spontaneous positive feelings of love and joy, but automatic negative thoughts and visualisations are experienced as hallucinations. Not only do these feel like they emerge from elsewhere but they carry a negative bias (they are most commonly critical, rude and are irrationally paranoid). Automatic positive actions may include laughter and smiling and these are welcome. Automatic behaviours that carry a negative bias, however, are unwelcome and like hallucinations, occur without a sense of choice. These include crying, stereotypies, perseveration, ataxia, utilization and imitation behaviours and catatonia.

Strong inference in functional neuroimaging

A recurring question for cognitive science is whether functional neuroimaging data can provide evidence for or against psychological theories. As posed, the question reflects an adherence to a popular scientific method known as 'strong inference'. The method entails constructing multiple hypotheses (Hs) and designing experiments so that alternative possible outcomes will refute at least one (i.e., 'falsify' it). In this article, after first delineating some well-documented limitations of strong inference, I provide examples of functional neuroimaging data being used to test Hs from rival modular information-processing models of spoken word production. 'Strong inference' for neuroimaging involves first establishing a systematic mapping of 'processes to processors' for a common modular architecture. Alternate Hs are then constructed from psychological theories that attribute the outcome of manipulating an experimental factor to two or more distinct processing stages within this architecture. Hs are then refutable by a finding of activity differentiated spatially and chronometrically by experimental condition. When employed in this manner, the data offered by functional neuroimaging may be more useful for adjudicating between accounts of processing loci than behavioural measures.

Support for an auto-associative model of spoken cued recall: Evidence from fMRI

Cued recall and item recognition are considered the standard episodic memory retrieval tasks. However, only the neural correlates of the latter have been studied in detail with fMRI. Using an event-related fMRI experimental design that permits spoken responses, we tested hypotheses from an auto-associative model of cued recall and item recognition [Chappell, M., & Humphreys, M. S. (1994). An auto-associative neural network for sparse representations: Analysis and application to models of recognition and cued recall. Psychological Review, 101, 103-128]. In brief, the model assumes that cues elicit a network of phonological short term memory (STM) and semantic long term memory (LTM) representations distributed throughout the neocortex as patterns of sparse activations. This information is transferred to the hippocampus which converges upon the item closest to a stored pattern and outputs a response. Word pairs were learned from a study list, with one member of the pair serving as the cue at test. Unstudied words were also intermingled at test in order to provide an analogue of yes/no recognition tasks. Compared to incorrectly rejected studied items (misses) and correctly rejected (CR) unstudied items, correctly recalled items (hits) elicited increased responses in the left hippocampus and neocortical regions including the left inferior prefrontal cortex (LIPC), left mid lateral temporal cortex and inferior parietal cortex, consistent with predictions from the model. This network was very similar to that observed in yes/no recognition studies, supporting proposals that cued recall and item recognition involve common rather than separate mechanisms.

Perfusion fMRI evidence for priming of shared feature-to-lexical connections during cumulative semantic interference in spoken word production

The speed at which target pictures are named increases monotonically as a function of prior retrieval of other exemplars of the same semantic category and is unaffected by the number of intervening items. This cumulative semantic interference effect is generally attributed to three mechanisms: shared feature activation, priming and lexical-level selection. However, at least two additional mechanisms have been proposed: (1) a 'booster' to amplify lexical-level activation and (2) retrieval-induced forgetting (RIF). In a perfusion functional Magnetic Resonance Imaging (fMRI) experiment, we tested hypotheses concerning the involvement of all five mechanisms. Our results demonstrate that the cumulative interference effect is associated with perfusion signal changes in the left perirhinal and middle temporal cortices that increase monotonically according to the ordinal position of exemplars being named. The left inferior frontal gyrus (LIFG) also showed significant perfusion signal changes across ordinal presentations; however, these responses did not conform to a monotonically increasing function. None of the cerebral regions linked with RIF in prior neuroimaging and modelling studies showed significant effects. This might be due to methodological differences between the RIF paradigm and continuous naming as the latter does not involve practicing particular information. We interpret the results as indicating priming of shared features and lexical-level selection mechanisms contribute to the cumulative interference effect, while adding noise to a booster mechanism could account for the pattern of responses observed in the LIFG.

Virtual community, purchasing behaviour, and emotional well-being

The benefits of virtual communities in increasing firms' profits, instilling knowledge in consumers, and enhancing consumers' social experience and enjoyment are widely recognised. However, relatively little is known about how the use of a virtual community could influence consumers' emotional well-being. This study examines the relationships among virtual community features (structural and experiential routes) as antecedents of virtual community engagement, including quality of use of virtual communities (time spent online and level of information exchange), electronic word-of-mouth (eWOM) purchasing behaviour, and consumers' emotional experience. Furthermore, by extending the cultural perspective to virtual community engagement, this study examines the role of collectivistic values on the aforementioned relationships. The proposed hypotheses are tested on the basis of data collected from 286 members of different virtual communities in Taiwan. The results partially support the theory that features of virtual communities influenced the quality of use, which then has a subsequent effect on consumer eWOM purchasing and emotional well-being. The results of the empirical analysis add credence to the proposed relationships. The role of collectivistic values is also partially supported. A detailed discussion of the findings and limitations of this study is provided.

The effects of prediction, understanding, and control: A test of the stress antidote model

A study was undertaken to examine further the effects of perceived work control on employee adjustment. On the basis of the stress antidote model, it was proposed that high levels of prediction, understanding, and control of work-related events would have direct, indirect, and interactive effects on levels of employee adjustment. These hypotheses were tested in a short-term longitudinal study of 137 employees of a large retail organization. The stress antidote measures appeared to be indirectly related to employee adjustment, via their effects on perceptions of work stress. There was weak evidence for the proposal that prediction, understanding, and control would buffer the negative effects of work stress. Additional analyses indicated that the observed effects of prediction, understanding, and control were independent of employees' generalized control beliefs. However, there was no support for the proposal that the effects of the stress antidote measures would be dependent on employees' generalized control beliefs.

Incorporating visual information for spoken term detection

Spoken term detection (STD) is the task of looking up a spoken term in a large volume of speech segments. In order to provide fast search, speech segments are first indexed into an intermediate representation using speech recognition engines which provide multiple hypotheses for each speech segment. Approximate matching techniques are usually applied at the search stage to compensate the poor performance of automatic speech recognition engines during indexing. Recently, using visual information in addition to audio information has been shown to improve phone recognition performance, particularly in noisy environments. In this paper, we will make use of visual information in the form of lip movements of the speaker in indexing stage and will investigate its effect on STD performance. Particularly, we will investigate if gains in phone recognition accuracy will carry through the approximate matching stage to provide similar gains in the final audio-visual STD system over a traditional audio only approach. We will also investigate the effect of using visual information on STD performance in different noise environments.

Submarine record of volcanic island construction and collapse in the Lesser Antilles arc: First scientific drilling of submarine volcanic island landslides by IODP Expedition 340

IODP Expedition 340 successfully drilled a series of sites offshore Montserrat, Martinique and Dominica in the Lesser Antilles from March to April 2012. These are among the few drill sites gathered around volcanic islands, and the first scientific drilling of large and likely tsunamigenic volcanic island-arc landslide deposits. These cores provide evidence and tests of previous hypotheses for the composition and origin of those deposits. Sites U1394, U1399, and U1400 that penetrated landslide deposits recovered exclusively seafloor sediment, comprising mainly turbidites and hemipelagic deposits, and lacked debris avalanche deposits. This supports the concepts that i/ volcanic debris avalanches tend to stop at the slope break, and ii/ widespread and voluminous failures of preexisting low-gradient seafloor sediment can be triggered by initial emplacement of material from the volcano. Offshore Martinique (U1399 and 1400), the landslide deposits comprised blocks of parallel strata that were tilted or microfaulted, sometimes separated by intervals of homogenized sediment (intense shearing), while Site U1394 offshore Montserrat penetrated a flat-lying block of intact strata. The most likely mechanism for generating these large-scale seafloor sediment failures appears to be propagation of a decollement from proximal areas loaded and incised by a volcanic debris avalanche. These results have implications for the magnitude of tsunami generation. Under some conditions, volcanic island landslide deposits composed of mainly seafloor sediment will tend to form smaller magnitude tsunamis than equivalent volumes of subaerial block-rich mass flows rapidly entering water. Expedition 340 also successfully drilled sites to access the undisturbed record of eruption fallout layers intercalated with marine sediment which provide an outstanding high-resolution data set to analyze eruption and landslides cycles, improve understanding of magmatic evolution as well as offshore sedimentation processes.

The role of time pressure and different psychological safety climate referents in the prediction of nurses’ hand hygiene compliance

In this study of 638 Australian nurses, compliance to hand hygiene (HH), as defined by the “five moments” recommended by the World Health Organisation (2009), was examined. Hypotheses focused on the extent to which time pressure reduces compliance and safety climate (operationalised in relation to HH using colleagues, manager, and hospital as referents) increases compliance. It also was proposed that HH climate would interact with time pressure, such that the negative effects of time pressure would be less marked when HH climate is high. The extent to which the three HH climate variables would interact among each other, either in the form of boosting or compensatory effects, was tested in an exploratory manner. A prospective research design was used in which time pressure and the HH climate variables were assessed at Time 1 and compliance was assessed by self-report two weeks later. Compliance was high but varied significantly across the 5 HH Moments, suggesting that nurses make distinctions between inherent and elective HH and also seemed to engage in some implicit rationing of HH. Time pressure dominated the utility of HH climate to have its positive impact on compliance. The most conducive workplace for compliance was one low in time pressure and high in HH climate. Colleagues were very influential in determining compliance, more so than the manager and hospital. Manager and hospital support for HH enhanced the positive effects of colleagues on compliance. Providing training and enhancing knowledge was important, not just for compliance, but for safety climate.

Matters Arising: HLA-DR-DQ haplotypes and genotypes in Finnish patients with rheumatoid arthritis

We read with great interest the paper by Laivoranta-Nyman et al.1 They studied Finnish patients with rheumatoid arthritis (RA) and controls, and suggested that there exist susceptibility, neutral and protective HLA-DR-DQ haplotypes that do not match the predictions of current hypotheses for the mechanism of association of the HLA class II region and RA...

The Arctic Summer Cloud Ocean Study (ASCOS): overview and experimental design

The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol–cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007–2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21' N, 01°29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets.

Temporal and environmental influences on the vocal behaviour of a nocturnal bird

Temporal and environmental variation in vocal activity can provide information on avian behaviour and call function not available to short-term experimental studies. Intersexual differences in this variation can provide insight into selection effects. Yet factors influencing vocal behaviour have not been assessed in many birds, even those monitored by acoustic methods. This applies to the New Zealand kiwi (Apterygidae), for which call censuses are used extensively in conservation monitoring, yet which have poorly understood acoustic ecology. We investigated little spotted kiwi Apteryx owenii vocal behaviour over 3 yr, measuring influences on vocal activity in both sexes from time of night, season, weather conditions and lunar cycle. We tested hypotheses that call rate variation reflects call function, foraging efficiency, historic predation risk and variability in sound transmission, and that there are inter-sexual differences in call function. Significant seasonal variation showed that vocalisations were important in kiwi reproduction, and inter-sexual synchronisation of call rates indicated that contact, pair-bonding or resource defence were key functions. All weather variables significantly affected call rates, with elevated calling during increased humidity and ground moisture indicating a relation between vocal activity and foraging conditions. A significant decrease in calling activity on cloudy nights, combined with no moonlight effect, suggests an impact of light pollution in this species. These influences on vocal activity provide insight into kiwi call function, have direct consequences for conservation monitoring of kiwi, and have wider implications in understanding vocal behaviour in a range of nocturnal birds

The role of lysine-41 in RNase A catalysis - A quantum chemical study on the active site ligand complex

Several mechanisms have been proposed to explain the action of enzymes at the atomic level. Among them, the recent proposals involving short hydrogen bonds as a step in catalysis by Gerlt and Gassman [1] and proton transfer through low barrier hydrogen bonds (LBHBs) [2, 3] have attracted attention. There are several limitations to experimentally testing such hypotheses, Recent developments in computational methods facilitate the study of active site-ligand complexes to high levels of accuracy, Our previous studies, which involved the docking of the dinucleotide substrate UpA to the active site of RNase A [4, 5], enabled us to obtain a realistic model of the ligand-bound active site of RNase A. From these studies, based on empirical potential functions, we were able to obtain the molecular dynamics averaged coordinates of RNase A, bound to the ligand UpA. A quantum mechanical study is required to investigate the catalytic process which involves the cleavage and formation of covalent bonds. In the present study, we have investigated the strengths of some of the hydrogen bonds between the active site residues of RNase A and UpA at the ab initio quantum chemical level using the molecular dynamics averaged coordinates as the starting point. The 49 atom system and other model systems were optimized at the 3-21G level and the energies of the optimized systems were obtained at the 6-31G* level. The results clearly indicate the strengthening of hydrogen bonds between neutral residues due to the presence of charged species at appropriate positions. Such a strengthening manifests itself in the form of short hydrogen bonds and a low barrier for proton transfer. In the present study, the proton transfer between the 2'-OH of ribose (from the substrate) and the imidazole group from the H12 of RNase A is influenced by K41, which plays a crucial role in strengthening the neutral hydrogen bond, reducing the barrier for proton transfer.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.