Beyond Time and Space:The Effect of a Lateralized Sustained Attention Task and Brain Stimulation on Spatial and Selective Attention

The Theory of Visual Attention (TVA) provides a mathematical formalisation of the “biased competition” account of visual attention. Applying this model to individual performance in a free recall task allows the estimation of 5 independent attentional parameters: visual short-term memory (VSTM) capacity, speed of information processing, perceptual threshold of visual detection; attentional weights representing spatial distribution of attention (spatial bias), and the top-down selectivity index. While the TVA focuses on selection in space, complementary accounts of attention describe how attention is maintained over time, and how temporal processes interact with selection. A growing body of evidence indicates that different facets of attention interact and share common neural substrates. The aim of the current study was to modulate a spatial attentional bias via transfer effects, based on a mechanistic understanding of the interplay between spatial, selective and temporal aspects of attention. Specifically, we examined here: (i) whether a single administration of a lateralized sustained attention task could prime spatial orienting and lead to transferable changes in attentional weights (assigned to the left vs right hemi-field) and/or other attentional parameters assessed within the framework of TVA (Experiment 1); (ii) whether the effects of such spatial-priming on TVA parameters could be further enhanced by bi-parietal high frequency transcranial random noise stimulation (tRNS) (Experiment 2). Our results demonstrate that spatial attentional bias, as assessed within the TVA framework, was primed by sustaining attention towards the right hemi-field, but this spatial-priming effect did not occur when sustaining attention towards the left. Furthermore, we show that bi-parietal high-frequency tRNS combined with the rightward spatial-priming resulted in an increased attentional selectivity. To conclude, we present a novel, theory-driven method for attentional modulation providing important insights into how the spatial and temporal processes in attention interact with attentional selection

Linking food web functioning and habitat diversity for an ecosystem based management: A Mediterranean lagoon case-study

We propose a modelling approach relating the functioning of a transitional ecosystem with the spatial extension of its habitats. A test case is presented for the lagoon of Venice, discussing the results in the context of the application of current EU directives. The effects on food web functioning due to changes related to manageable and unmanageable drivers were investigated. The modelling procedure involved the use of steady-state food web models and network analysis, respectively applied to estimate the fluxes of energy associated with trophic interactions, and to compute indices of food web functioning. On the long term (hundred years) temporal scale, the model indicated that the expected loss of salt marshes will produce further changes at the system level, with a lagoon showing a decrease in the energy processing efficiency. On the short term scale, simulation results indicated that fishery management accompanied by seagrass restoration measures would produce a slight transition towards a more healthy system, with higher energy cycling, and maintaining a good balance between processing efficiency and resilience. Scenarios presented suggest that the effectiveness of short term management strategies can be better evaluated when contextualized in the long term trends of evolution of a system. We also remark the need for further studying the relationship between habitat diversity and indicators of food web functioning

Space, time and motion in a multisensory world

When interacting with environmental events, humans acquire information from different senses and combine these inputs within a coherent representation of the world. The present doctoral thesis aims at investigating how humans represent space, time, and motion through auditory and visual sensory modalities. It has been widely demonstrated a predisposition of different sensory systems towards the processing of different domains of representation, with hearing that prevails in representing the time domain and vision that is the most reliable sense for processing the space domain. Given this strong link between sensory modality and domain of representation, one objective of this thesis is to deepen the knowledge of the neural organization of multisensory spatial and temporal skills in healthy adults. In addition, by using blindness as a model to unravel the role of vision in the development of spatio-temporal abilities, this thesis explores the interaction of the spatial and temporal domains in the acoustic motion perception of early blind individuals. The interplay between space and time has also been explained as the result of humans performing actions in the surrounding environment since to carry out goal-directed motor behaviors it is useful for a person to associate the spatial and temporal information of one’s target into a shared mental map. In this regard, the present project also questions how the brain processes spatio-temporal cues of external events when it comes to manually intercepting moving objects with one hand. Finally, in light of the above results, this dissertation incorporates the development of a novel portable device, named MultiTab, for the behavioral evaluation of the processing of space, time, and motor responses, through the visual and acoustic sensory modality. For the purposes of this thesis, four methodological approaches have been employed: i) electroencephalogram (EEG) technique, to explore the cortical activation associated with multisensory spatial and temporal tasks; ii) psychophysical methods, to measure the relationship between stimuli in motion and the acoustic speed perception of blind and sighted individuals; iii) motion capture techniques, to measure indices of movements during an object’s interception task; iv) design and technical-behavioral validation of a new portable device. Studies of the present dissertation indicate the following results. First, this thesis highlights an early cortical gain modulation of sensory areas that depends on the domain of representation to process, with auditory areas mainly involved in the multisensory processing of temporal inputs, and visual areas of spatial inputs. Moreover, for the spatial domain specifically, the neural modulation of visual areas is also influenced by the kind of spatial layout representing multisensory stimuli. Second, this project shows that lack of vision influences the ability to process the speed of moving sounds by altering how blind individuals make use of the sounds’ temporal features. This result suggests that visual experience in the first years of life is a crucial factor when dealing with combined spatio-temporal information. Third, data of this thesis demonstrate that typically developing individuals manually intercepting a moving object with one hand take into consideration the item’s spatio-temporal cues, by adjusting their interceptive movements according to the object’s speed. Finally, the design and validation of MultiTab show its utility in the evaluation of multisensory processing such as the manual localization of audiovisual spatialized stimuli. Overall, findings from this thesis contribute to a more in-depth picture of how the human brain represents space, time, and motion through different senses. Moreover, they provide promising implications in exploring novel technological methods for the assessment and training of these dimensions in typical and atypical populations

The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp)

The MESSAGE Integrated Assessment Model (IAM) developed by IIASA has been a central tool of energy-environment-economy systems analysis in the global scientific and policy arena. It played a major role in the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC); it provided marker scenarios of the Representative Concentration Pathways (RCPs) and the Shared Socio-Economic Pathways (SSPs); and it underpinned the analysis of the Global Energy Assessment (GEA). Alas, to provide relevant analysis for current and future challenges, numerical models of human and earth systems need to support higher spatial and temporal resolution, facilitate integration of data sources and methodologies across disciplines, and become open and transparent regarding the underlying data, methods, and the scientific workflow. In this manuscript, we present the building blocks of a new framework for an integrated assessment modeling platform; the \ecosystem" comprises: i) an open-source GAMS implementation of the MESSAGE energy++ system model integrated with the MACRO economic model; ii) a Java/database backend for version-controlled data management, iii) interfaces for the scientific programming languages Python & R for efficient input data and results processing workflows; and iv) a web-browser-based user interface for model/scenario management and intuitive \drag-and-drop" visualization of results. The framework aims to facilitate the highest level of openness for scientific analysis, bridging the need for transparency with efficient data processing and powerful numerical solvers. The platform is geared towards easy integration of data sources and models across disciplines, spatial scales and temporal disaggregation levels. All tools apply best-practice in collaborative software development, and comprehensive documentation of all building blocks and scripts is generated directly from the GAMS equations and the Java/Python/R source code

A simplified machine learning approach for recognizing human activity

With the wide ranges of real-time event feed capturing devices, there has been significant progress in the area of digital image processing towards activity detection and recognition. Irrespective of the presence of various such devices, they are not adequate to meet dynamic monitoring demands of the visual surveillance system, and their features are highly limited towards complex human activity recognition system.  Review of existing system confirms that still there is a large scope of enhancement as they lack applicability to real-life events and also doesn't offer optimal system performance. Therefore, the proposed manuscript presents a model for activity recognition system where the accuracy of recognition operation and system performance are retained with good balance. The study presents a simplified feature extraction process from spatial and temporal traits of the event feeds that is further subjected to the machine learning mechanism for boosting recognition performanc

Computing motion in the primate's visual system

Computing motion on the basis of the time-varying image intensity is a difficult problem for both artificial and biological vision systems. We will show how one well-known gradient-based computer algorithm for estimating visual motion can be implemented within the primate's visual system. This relaxation algorithm computes the optical flow field by minimizing a variational functional of a form commonly encountered in early vision, and is performed in two steps. In the first stage, local motion is computed, while in the second stage spatial integration occurs. Neurons in the second stage represent the optical flow field via a population-coding scheme, such that the vector sum of all neurons at each location codes for the direction and magnitude of the velocity at that location. The resulting network maps onto the magnocellular pathway of the primate visual system, in particular onto cells in the primary visual cortex (V1) as well as onto cells in the middle temporal area (MT). Our algorithm mimics a number of psychophysical phenomena and illusions (perception of coherent plaids, motion capture, motion coherence) as well as electrophysiological recordings. Thus, a single unifying principle ‘the final optical flow should be as smooth as possible’ (except at isolated motion discontinuities) explains a large number of phenomena and links single-cell behavior with perception and computational theory

Pemilihan kerjaya di kalangan pelajar aliran perdagangan sekolah menengah teknik : satu kajian kes

This research is a survey to determine the career chosen of form four student in commerce streams. The important aspect of the career chosen has been divided into three, first is information about career, type of career and factor that most influence students in choosing a career. The study was conducted at Sekolah Menengah Teknik Kajang, Selangor Darul Ehsan. Thirty six form four students was chosen by using non-random sampling purpose method as respondent. All information was gather by using questionnaire. Data collected has been analyzed in form of frequency, percentage and mean. Results are performed in table and graph. The finding show that information about career have been improved in students career chosen and mass media is the main factor influencing students in choosing their career

Detection of dirt impairments from archived film sequences : survey and evaluations

Film dirt is the most commonly encountered artifact in archive restoration applications. Since dirt usually appears as a temporally impulsive event, motion-compensated interframe processing is widely applied for its detection. However, motion-compensated prediction requires a high degree of complexity and can be unreliable when motion estimation fails. Consequently, many techniques using spatial or spatiotemporal filtering without motion were also been proposed as alternatives. A comprehensive survey and evaluation of existing methods is presented, in which both qualitative and quantitative performances are compared in terms of accuracy, robustness, and complexity. After analyzing these algorithms and identifying their limitations, we conclude with guidance in choosing from these algorithms and promising directions for future research