The disabilities of chronic schizophrenia: A search for neurological correlates

This study was designed to define in standardised fashion, the deficits of chronic schizophrenia and the correlates of these, and to evaluate two neurological parameters - spontaneous involuntary movements and lateral ventricular enlargement - in relation to the illness and its treatment. The study population comprised all those schizophrenics receiving long-term care in the one mental hospital who conformed to the St. Louis criteria for schizophrenia and who had been in-patients for at least 1 year continuously. This basic group consisted of 510 subjects. Analysis of standardised assessments covering mental state, cognition, neurological status and behaviour showed these patients to be extremely impaired. While historical correlates of functioning in particular spheres could be identified, the present clinical picture was in general related to the form of the initial illness and to factors reflecting the passage of time. Past physical treatment was not related to present deficits. Two broad patterns of disability were established. While the presence of prominent productive features in the mental state was not associated with the presence of deficits in other areas examined, prominent 'negative' features were related to the presence of cognitive impairment, extrapyramidal neurological signs and behavioural deterioration. Involuntary movements were assessed in 411 subjects using two standardised recording schedules. Abnormality was extremely common. The base-line prevalence of disorder in those with no history of neuroleptic exposure was comparable with that of those treated with neuroleptics, although with factors reflecting the passage of time accounted for, movement disorder was associated with past neuroleptic treatment. In addition however, the presence of abnormal movements related to features of the illness itself - namely 'negative' mental state features, cognitive impairment and behavioural deterioration. C.T. scans from 110 of the total population described above and controls representing non-institutionalised out-patient (18) and first episode (8) schizophrenics, institutionalised and out-patient manic-depressives (10 and 22 respectively) and neurotic out-patients (19), demonstrated that schizophrenia is associated with enlargement of the lateral ventricles, although only the institutionalised schizophrenics differed significantly from the neurotic controls. The group mean differences were not great and there was considerable overlap between groups. There was no evidence of a characteristic radiological change associated with schizophrenia. Lateral ventricular enlargement in schizophrenia was not consequent upon physical treatments administered in the past. The historical and examination variables which related to increased ventricular size in the long-stay schizophrenic population were few and the nature of certain relationships surprising. While behavioural deterioration and involuntary movements were significantly and linearly associated with ventricular enlargement, 'negative' mental state features, cognitive impairment and an absence of hallucinations were more commonly found in those at both extremes of ventricle size. The results suggest that although brain structure is genuinely altered in certain schizophrenics, the relationship between cerebral structure and clinical aspects of the condition is not straightforward. This study indicates that both neurological abnormality and structural brain change can be related to certain clinical features of established schizophrenia when other potentially relevant historical and treatment variables are accounted for. Such a general conclusion refers to statistical associations within large groups of patients and the relationship between neurology and psychopathology is complex. Nonetheless, the findings lend support to the view that in some patients at least, schizophrenia is a brain disorder whose cerebral basis can be inferred from the nature of some of the associated multiple deficits

A Theory of Mind investigation into the appreciation of visual jokes in schizophrenia

BACKGROUND: There is evidence that groups of people with schizophrenia have deficits in Theory of Mind (ToM) capabilities. Previous studies have found these to be linked to psychotic symptoms (or psychotic symptom severity) particularly the presence of delusions and hallucinations. METHODS: A visual joke ToM paradigm was employed where subjects were asked to describe two types of cartoon images, those of a purely Physical nature and those requiring inferences of mental states for interpretation, and to grade them for humour and difficulty. Twenty individuals with a DSM-lV diagnosis of schizophrenia and 20 healthy matched controls were studied. Severity of current psychopathology was measured using the Krawiecka standardized scale of psychotic symptoms. IQ was estimated using the Ammons and Ammons quick test. RESULTS: Individuals with schizophrenia performed significantly worse than controls in both conditions, this difference being most marked in the ToM condition. No relationship was found for poor ToM performance and psychotic positive symptomatology, specifically delusions and hallucinations. CONCLUSION: There was evidence for a compromised ToM capability in the schizophrenia group on this visual joke task. In this instance this could not be linked to particular symptomatology

Class Discovery in Galaxy Classification

In recent years, automated, supervised classification techniques have been fruitfully applied to labeling and organizing large astronomical databases. These methods require off-line classifier training, based on labeled examples from each of the (known) object classes. In practice, only a small batch of labeled examples, hand-labeled by a human expert, may be available for training. Moreover, there may be no labeled examples for some classes present in the data, i.e. the database may contain several unknown classes. Unknown classes may be present due to 1) uncertainty in or lack of knowledge of the measurement process, 2) an inability to adequately ``survey'' a massive database to assess its content (classes), and/or 3) an incomplete scientific hypothesis. In recent work, new class discovery in mixed labeled/unlabeled data was formally posed, with a proposed solution based on mixture models. In this work we investigate this approach, propose a competing technique suitable for class discovery in neural networks, and evaluate both methods for classification and class discovery on several astronomical data sets. Our results demonstrate up to a 57% reduction in classification error compared to a standard neural network classifier that uses only labeled data

Robust Machine Learning Applied to Astronomical Datasets I: Star-Galaxy Classification of the SDSS DR3 Using Decision Trees

We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that these star/galaxy classifications are expected to be reliable for approximately 22 million objects with r < ~20. The general machine learning environment Data-to-Knowledge and supercomputing resources enabled extensive investigation of the decision tree parameter space. This work presents the first public release of objects classified in this way for an entire SDSS data release. The objects are classified as either galaxy, star or nsng (neither star nor galaxy), with an associated probability for each class. To demonstrate how to effectively make use of these classifications, we perform several important tests. First, we detail selection criteria within the probability space defined by the three classes to extract samples of stars and galaxies to a given completeness and efficiency. Second, we investigate the efficacy of the classifications and the effect of extrapolating from the spectroscopic regime by performing blind tests on objects in the SDSS, 2dF Galaxy Redshift and 2dF QSO Redshift (2QZ) surveys. Given the photometric limits of our spectroscopic training data, we effectively begin to extrapolate past our star-galaxy training set at r ~ 18. By comparing the number counts of our training sample with the classified sources, however, we find that our efficiencies appear to remain robust to r ~ 20. As a result, we expect our classifications to be accurate for 900,000 galaxies and 6.7 million stars, and remain robust via extrapolation for a total of 8.0 million galaxies and 13.9 million stars. [Abridged]Comment: 27 pages, 12 figures, to be published in ApJ, uses emulateapj.cl

Evaluation of a Screening Instrument for Autism Spectrum Disorders in Prisoners

There have been concerns that individuals with autism spectrum disorders (ASDs) are over-represented but not recognised in prison populations. A screening tool for ASDs in prisons has therefore been developed

Objective Subclass Determination of Sloan Digital Sky Survey Unknown Spectral Objects

We analyze a portion of the SDSS photometric catalog, consisting of approximately 10,000 objects that have been spectroscopically classified into stars, galaxies, QSOs, late-type stars and unknown objects (spectroscopically unclassified objects, SUOs), in order to investigate the existence and nature of subclasses of the unclassified objects. We use a modified mixture modeling approach that makes use of both labeled and unlabeled data and performs class discovery on the data set. The modeling was done using four colors derived from the SDSS photometry: (u-g), (g-r), (r-i), and (i-z). This technique discovers putative novel classes by identifying compact clusters that largely contain objects from the spectroscopically unclassified class of objects. These clusters are of possible scientific interest because they represent structured groups of outliers, relative to the known object classes. We identify two such well defined subclasses of the SUOs. One subclass contains 58% SUOs, 40% stars, and 2% galaxies, QSOs, and late-type stars. The other contains 91% SUOs, 6% late-type stars, and 3% stars, galaxies, and QSOs. We discuss possible interpretations of these subclasses while also noting some caution must be applied to purely color-based object classifications. As a side benefit of this limited study we also find two distinct classes, consisting largely of galaxies, that coincide with the recently discussed bimodal galaxy color distribution.Comment: 31 pages; 6 figures; revised version accepted for Ap. J. Added one figure, added discussion, compared method with another approach, added appendix with algorithmic detail

Existence and learning of oscillations in recurrent neural networks

We study a particular class of n-node recurrent neural networks (RNNs). In the 3-node case we use monotone dynamical systems theory to show, for a well-defined set of parameters, that, generically, every orbit of the RNN is asymptotic to a periodic orbit. We then investigate whether RNNs of this class can adapt their internal parameters so as to ?learn? and then replicate autonomously (in feedback) certain external periodic signals. Our learning algorithm is similar to the identification algorithms in adaptive control theory. The main feature of the algorithm is that global exponential convergence of parameters is guaranteed. We also obtain partial convergence results in the n-node cas

High-p_T pion and kaon production in relativistic nuclear collisions

High-p_T pion and kaon production is studied in relativistic proton-proton, proton-nucleus, and nucleus-nucleus collisions in a wide energy range. Cross sections are calculated based on perturbative QCD, augmented by a phenomenological transverse momentum distribution of partons (``intrinsic k_T''). An energy dependent width of the transverse momentum distribution is extracted from pion and charged hadron production data in proton-proton/proton-antiproton collisions. Effects of multiscattering and shadowing in the strongly interacting medium are taken into account. Enhancement of the transverse momentum width is introduced and parameterized to explain the Cronin effect. In collisions between heavy nuclei, the model over-predicts central pion production cross sections (more significantly at higher energies), hinting at the presence of jet quenching. Predictions are made for proton-nucleus and nucleus-nucleus collisions at RHIC energies.Comment: 26 pages in Latex, 19 EPS figure

Identifying the science and technology dimensions of emerging public policy issues through horizon scanning

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security