Neurochemical regulation of auditory information processing studied with EEG/MEG: application to schizophrenia

Cognitive impairments of attention, memory and executive functions are a fundamental feature of the pathophysiology of schizophrenia. The neurophysiological and neurochemical changes in the auditory cortex are shown to underlie cognitive impairmentsin schizophrenia patients. Functional state of the neural substrate of auditory information processing could be objectively and non-invasively probed with auditory event-related potentials (ERPs) and event- related fields (ERFs). In the current work, we explored the neurochemical effect on the neural origins of auditory information processing in relation to schizophrenia. By means of ERPs/ERFs we aimed to determine how neural substrates of auditory information processing are modulated by antipsychotic medication in schizophrenia spectrum patients (Studies I, II) and by neuropharmacological challenges in healthy human subjects (Studies III, IV). First, with auditory ERPs we investigated the effects of olanzapine (Study I) and risperidone (Study II) in a group of patients with schizophrenia spectrum disorders. After 2 and 4 weeks of treatment, olanzapine has no significant effects on mismatch negativity(MMN) and P300, which, as it has been suggested, respectively reflect preattentive and attention-dependent information processing. After 2 weeks of treatment, risperidone has no significant effect on P300, however risperidone reduces P200 amplitude. This latter effect of risperidone on neural resources responsible for P200 generation could be partly explained through the action of dopamine. Subsequently, we used simultaneous EEG/MEG to investigate the effects of memantine (Study III) and methylphenidate (Study IV) in healthy subjects. We found that memantine modulates MMN response without changing other ERP components. This could be interpreted as being due to the possible influence of memantine through the NMDA receptors on auditory change- detection mechanism, with processing of auditory stimuli remaining otherwise unchanged. Further, we found that methylphenidate does not modulate the MMN response. This finding could indicate no association between catecholaminergic activities and electrophysiological measures of preattentive auditory discrimination processes reflected in the MMN. However, methylphenidate decreases the P200 amplitudes. This could be interpreted as a modulation of auditory information processing reflected in P200 by dopaminergic and noradrenergic systems. Taken together, our set of studies indicates a complex pattern of neurochemical influences produced by the antipsychotic drugs in the neural substrate of auditory information processing in patients with schizophrenia spectrum disorders and by the pharmacological challenges in healthy subjects studied with ERPs and ERFs.

Constructing skilled images

When experts construct mental images, they do not rely only on perceptual features; they also access domain-specific knowledge and skills in long-term memory, which enables them to exceed the capacity limitations of the short-term working memory system. The central question of the present dissertation was whether the facilitating effect of long-term memory knowledge on working memory imagery tasks is primarily based on perceptual chunking or whether it relies on higher-level conceptual knowledge. Three domains of expertise were studied: chess, music, and taxi driving. The effects of skill level, stimulus surface features, and the stimulus structure on incremental construction of mental images were investigated. A method was developed to capture the chunking mechanisms that experts use in constructing images: chess pieces, street names, and visual notes were presented in a piecemeal fashion for later recall. Over 150 experts and non-experts participated in a total of 13 experiments, as reported in five publications. The results showed skill effects in all of the studied domains when experts performed memory and problem solving tasks that required mental imagery. Furthermore, only experts' construction of mental images benefited from meaningful stimuli. Manipulation of the stimulus surface features, such as replacing chess pieces with dots, did not significantly affect experts' performance in the imagery tasks. In contrast, the structure of the stimuli had a significant effect on experts' performance in every task domain. For example, taxi drivers recalled more street names from lists that formed a spatially continuous route than from alphabetically organised lists. The results suggest that the mechanisms of conceptual chunking rather than automatic perceptual pattern matching underlie expert performance, even though the tasks of the present studies required perception-like mental representations. The results show that experts are able to construct skilled images that surpass working memory capacity, and that their images are conceptually organised and interpreted rather than merely depictive.

Stress-induced phase transformation and pseudo-elastic/pseudo-plastic recovery in intermetallic Ni-Al nanowires

Extensive molecular dynamics (MD) simulations have been performed in a B2-NiAl nanowire using an embedded atom method (EAM) potential. We show a stress induced B2 -> body-centered-tetragonal (BCT) phase transformation and a novel temperature and cross-section dependent pseudo-elastic/pseudo-plastic recovery from such an unstable BCT phase with a recoverable strain of similar to 30% as compared to 5-8% in polycrystalline materials. Such a temperature and cross-section dependent pseudo-elastic/pseudo-plastic strain recovery can be useful in various interesting applications of shape memory and strain sensing in nanoscale devices. Effects of size, temperature, and strain rate on the structural and mechanical properties have also been analyzed in detail. For a given size of the nanowire the yield stress of both the B2 and the BCT phases is found to decrease with increasing temperature, whereas for a given temperature and strain rate the yield stress of both the B2 and the BCT phase is found to increase with increase in the cross-sectional dimensions of the nanowire. A constant elastic modulus of similar to 80 GPa of the B2 phase is observed in the temperature range of 200-500 K for nanowires of cross-sectional dimensions in the range of 17.22-28.712 angstrom, whereas the elastic modulus of the BCT phase shows a decreasing trend with an increase in the temperature.

Enhancing skill acquisition and expertise in high performance programmes

Our research programme with elite athletes has investigated and implemented learning design from an ecological dynamics perspective, examining its effects on movement coordination and control and the acquisition of expertise. Ecological dynamics is a systemsoriented theoretical rationale for understanding the emergent relations in a complex system formed by each performer and a performance environment. This approach has identified the individual-environment relationship as the relevant scale of analysis for modelling how processes of perception, cognition and action underpin expert performance in sport (Davids et al., 2014; Zelaznik, 2014). In this chapter we elucidate key concepts from ecological dynamics and exemplify how they have informed our understanding of relevant psychological processes including: movement coordination and its acquisition, learning and transfer, impacting on practice task design in high performance programmes.

Early-onset depressive disorders,related mental health disorders and substance use-A prospective : longitudinal study of Finnish twins born 1983-1987

Early-onset psychiatric illnesses effects scatter to academic achievements as well as functioning in familial and social environments. From a public health point of view, depressive disorders are the most significant mental health disorders that begin in adolescence. Using prospective and longitudinal design, this study aimed to increase the understanding of early-onset depressive disorders, related mental health disorders and developing substance use in a large population-derived sample of adolescent Finnish twins. The participants of this study, FinnTwin12, an ongoing longitudinal population-based study, came from Finnish families with twins born in 1983-87 (exhaustive of five birth cohorts, identified from Finland s Central Population Register). With follow-up ongoing at age 20-24, this thesis assessed adolescent mental health in the first three waves, starting from baseline age 11-12 to follow-ups at age 14 and 17½. Some 5600 twins participated in questionnaire assessments of a wide range of health related behaviors. Mental health was further assessed among an intensively studied subsample of 1852 adolescents, who completed also professionally administered interviews at age 14, which provided data for full DSM-IV/III-R (Diagnostic and Statistical Manual for Mental Health disorders, 4th and 3rd editions) diagnoses. The participation rates of the study were 87-92%. The results of the study suggest, that the diagnostic criteria for major depressive disorder (MDD) may not capture youth with clinically significant early-onset depressive conditions outside clinical settings. Milder cases of depression, namely adolescents fulfilling the diagnostic criteria for minor depressive disorder, a qualitatively similar condition to MDD with fewer symptoms are also associated with marked suicidal thoughts, plans and attempts, recurrences and a high degree of comorbidity. Prospectively and longitudinally, early-onset depressive disorders were of substantial importance in the context of other mental health disorders and substance use behaviors: These data from a large population-derived sample established a substantial overlap between early-onset depressive disorders and attention deficit hyperactivity disorder in adolescent females, both of them significantly predictive for development of substance use among girls. Only in females baseline DSM-IV ADHD symptoms were strong predictors of alcohol abuse and dependence and illicit drug use at age 14 and frequent alcohol use and illicit drug use at age 17.½ when conduct disorder and previous substance use were controlled for. Early-onset depressive disorders were also prospectively and longitudinally associated to daily smoking behavior, smokeless tobacco use, frequent alcohol use and illicit drug use and eating disorders. Analysis of discordant twins suggested that these predictive associations were independent of familial confounds, such as family income, structure and parental models. In sum, early-onset depressive disorders predict subsequent involvement of substance use and psychiatric morbidity. A heightened risk for substance use is substantial also among those depressed below categorical diagnosis of MDD. Whether early recognition and interventions among these young people hold potential for substance use prevention further in their lives has potential public health significance and calls for more research. Data from this population-derived sample with balanced representation of boys and girls, suggested that boys and girls with ADHD behaviors may differ from each other in their vulnerability to substance use and depressive disorders: the data suggest more adverse substance use outcome for girls that was not attenuated by conduct disorder or previous substance use. Further, the prospective associations of early-onset depressive disorders and future elevated levels of addictive substance use is not explained by familial factors supporting future substance use, which could have important implications for substance use prevention.

Breedcow and Dynama software redevelopment

The project renewed the Breedcow and Dynama software making it compatible with modern computer operating systems and platforms. Enhancements were also made to the linkages between the individual programs and their operation. The suite of programs is a critical component of the skill set required to make soundly based plans and production choices in the north Australian beef industry.

Middleware for Mobile Sensing Applications in Urban Environments

Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.

Determination of optimal trajectory under design constraints for a satellite launch vehicle

An optimal pitch steering programme of a solid-fuel satellite launch vehicle to maximize either (1) the injection velocity at a given altitude, or (2) the size of circular orbit, for a given payload is presented. The two-dimensional model includes the rotation of atmosphere with the Earth, the vehicle's lift and drag, variation of thrust with time and altitude, inverse-square gravitational field, and the specified initial vertical take-off. The inequality constraints on the aerodynamic load, control force, and turning rates are also imposed. Using the properties of the central force motion the terminal constraint conditions at coast apogee are transferred to the penultimate stage burnout. Such a transformation converts a time-free problem into a time-fixed one, reduces the number of terminal constraints, improves accuracy, besides demanding less computer memory and time. The adjoint equations are developed in a compact matrix form. The problem is solved on an IBM 360/44 computer using a steepest ascent algorithm. An illustrative analysis of a typical launch vehicle establishes the speed of convergence, and accuracy and applicability of the algorithm.

Steady-state dendritic cells expressing cognate antigen terminate memory CD8+ T-cell responses

Antigen stimulation of naive T cells in conjunction with strong costimulatory signals elicits the generation of effector and memory populations. Such terminal differentiation transforms naive T cells capable of differentiating along several terminal pathways in response to pertinent environmental cues into cells that have lost developmental plasticity and exhibit heightened responsiveness. Because these cells exhibit little or no need for the strong costimulatory signals required for full activation of naive T cells, it is generally considered memory and effector T cells are released from the capacity to be inactivated. Here, we show that steadystate dendritic cells constitutively presenting an endogenously expressed antigen inactivate fully differentiated memory and effector CD8+ T cells in vivo through deletion and inactivation. These findings indicate that fully differentiated effector and memory T cells exhibit a previously unappreciated level of plasticity and provide insight into how memory and effector T-cell populations may be regulated. © 2008 by The American Society of Hematology.

Functional imaging of peripheral vision and dorsal stream function in the human cerebral cortex

Visual information processing in brain proceeds in both serial and parallel fashion throughout various functionally distinct hierarchically organised cortical areas. Feedforward signals from retina and hierarchically lower cortical levels are the major activators of visual neurons, but top-down and feedback signals from higher level cortical areas have a modulating effect on neural processing. My work concentrates on visual encoding in hierarchically low level cortical visual areas in human brain and examines neural processing especially in cortical representation of visual field periphery. I use magnetoencephalography and functional magnetic resonance imaging to measure neuromagnetic and hemodynamic responses during visual stimulation and oculomotor and cognitive tasks from healthy volunteers. My thesis comprises six publications. Visual cortex forms a great challenge for modeling of neuromagnetic sources. My work shows that a priori information of source locations are needed for modeling of neuromagnetic sources in visual cortex. In addition, my work examines other potential confounding factors in vision studies such as light scatter inside the eye which may result in erroneous responses in cortex outside the representation of stimulated region, and eye movements and attention. I mapped cortical representations of peripheral visual field and identified a putative human homologue of functional area V6 of the macaque in the posterior bank of parieto-occipital sulcus. My work shows that human V6 activates during eye-movements and that it responds to visual motion at short latencies. These findings suggest that human V6, like its monkey homologue, is related to fast processing of visual stimuli and visually guided movements. I demonstrate that peripheral vision is functionally related to eye-movements and connected to rapid stream of functional areas that process visual motion. In addition, my work shows two different forms of top-down modulation of neural processing in the hierachically lowest cortical levels; one that is related to dorsal stream activation and may reflect motor processing or resetting signals that prepare visual cortex for change in the environment and another local signal enhancement at the attended region that reflects local feed-back signal and may perceptionally increase the stimulus saliency.

Deploying speaker verification techniques to vision-based RPA detect and avoid

Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.

Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition

We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using dynamic time warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later. We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.

Pathways to health : Determinants of health, health behaviour and health inequalities in early adulthood

There is increasing evidence that the origins of poor adult health and health inequalities can be traced back to circumstances preceding current socioeconomic position and living conditions. The life-course approach to examining the determinants of health has emphasised that exposure to adverse social and economic circumstances in earlier life or concurrent adverse circumstances due to unfavourable living conditions in earlier life may lead to poor health, health-damaging behaviour, disease or even premature death in adulthood. There is, however, still a lack of knowledge about the contribution of social and economic circumstances in childhood and youth to adult health and health inequalities, and even less is known about how environmental and behavioural factors in adulthood mediate the effects of earlier adverse experiences. The main purpose of this study was to deepen our understanding of the development of poor health, health-damaging behaviours and health inequalities during the life-course. Its aim was to find out which factors in earlier and current circumstances determine health, the most detrimental indicators of health behaviour (smoking, heavy drinking and obesity as a proxy for the balance between nutrition and exercise), and educational health differences in young adults in Finland. Following the ideas of the social pathway theory, it was assumed that childhood environment affects adult health and its proximal determinants via different pathways, including educational, work and family careers. Early adulthood was studied as a significant phase of life when many behavioural patterns and living conditions relevant to health are established. In addition, socioeconomic health inequalities seem to emerge rapidly when moving into adulthood; they are very small or non-existent in childhood and adolescence, but very marked by early middle age. The data of this study were collected in 2000 2001 as part of the Health 2000 Survey (N = 9,922), a cross-sectional and nationally representative health interview and examination survey. The main subset of data used in this thesis was the one comprising the age group 18 29 years (N = 1,894), which included information collected by standardised structured computer-aided interviews and self-administered questionnaires. The survey had a very high participation rate at almost 90% for the core questions. According to the results of this study, childhood circumstances predict the health of young adults. Almost all the childhood adversities studied were found to be associated with poor self-rated health and psychological distress in early adulthood, although fewer associations were found with the somatic morbidity typical of young adults. These effects seemed to be more or less independent of the young adult s own education. Childhood circumstances also had a strong effect on smoking and heavy drinking, although current circumstances and education in particular, played a role in mediating this effect. Parental smoking and alcohol abuse had an influence on the corresponding behaviours of offspring. Childhood circumstances had a role in the development of obesity and, to a lesser extent, overweight, particularly in women. The findings support the notion that parental education has a strong effect on early adult obesity, even independently of the young adult s own educational level. There were marked educational differences in self-rated health in early adulthood: those in the lowest educational category were most likely to have average or poorer health. Childhood social circumstances seemed to explain a substantial part of these educational differences. In addition, daily smoking and heavy drinking contributed substantially to educational health differences. However, the contribution of childhood circumstances was largely shared with health behaviours adopted by early adulthood. Employment also shared the effects of childhood circumstances on educational health differences. The results indicate that childhood circumstances are important in determining health, health behaviour and health inequalities in early adulthood. Early recognition of childhood adversities followed by relevant support measures may play an important role in preventing the unfortunate pathways leading to the development of poor health, health-damaging behaviour and health inequalities. It is crucially important to recognise the needs of children living in adverse circumstances as well as children of substance abusing parents. In addition, single-parent families would benefit from support. Differences in health and health behaviours between different sub-groups of the population mean that we can expect to see ever greater health differences when today s generation of young adults grows older. This presents a formidable challenge to national health and social policy as well as health promotion. Young adults with no more than primary level education are at greatest risk of poor health. Preventive policies should emphasise the role of low educational level as a key determinant of health-damaging behaviours and poor health. Keywords: health, health behaviour, health inequalities, life-course, socioeconomic position, education, childhood circumstances, self-rated health, psychological distress, somatic morbidity, smoking, heavy drinking, BMI, early adulthood

Information Technology in Construction – Domain Definition and Research Issues

This article discusses the scope of research on the application of information technology in construction (ITC). A model of the information and material activities which together constitute the construction process is presented, using the IDEF0 activity modelling methodology. Information technology is defined to include all kinds of technology used for the storage, transfer and manipulation of information, thus also including devices such as copying machines, faxes and mobile phones. Using the model the domain of ITC research is defined as the use of information technology to facilitate and re-engineer the information process component of construction. Developments during the last decades in IT use in construction is discussed against a background of a simplified model of generic information processing tasks. The scope of ITC is compared with the scopes of research in related areas such as design methodology, construction management and facilities management. Health care is proposed as an interesting alternative (to the often used car manufacturing industry), as an IT application domain to compare with. Some of the key areas of ITC research in recent years; expert systems, company IT strategies, and product modelling are shortly discussed. The article finishes with a short discussion of the problems of applying standard scientific methodology in ITC research, in particular in product model research.

GAP-RBF based NR image quality measurement for JPEG coded images

In this paper, we present a growing and pruning radial basis function based no-reference (NR) image quality model for JPEG-coded images. The quality of the images are estimated without referring to their original images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity factors such as edge amplitude, edge length, background activity and background luminance. Image quality estimation involves computation of functional relationship between HVS features and subjective test scores. Here, the problem of quality estimation is transformed to a function approximation problem and solved using GAP-RBF network. GAP-RBF network uses sequential learning algorithm to approximate the functional relationship. The computational complexity and memory requirement are less in GAP-RBF algorithm compared to other batch learning algorithms. Also, the GAP-RBF algorithm finds a compact image quality model and does not require retraining when the new image samples are presented. Experimental results prove that the GAP-RBF image quality model does emulate the mean opinion score (MOS). The subjective test results of the proposed metric are compared with JPEG no-reference image quality index as well as full-reference structural similarity image quality index and it is observed to outperform both.