Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

Projected sequential Gaussian processes: flexible interpolation for large data sets

Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential framework for inference in such projected processes is presented, where the observations are considered one at a time. We introduce a C++ library for carrying out such projected, sequential estimation which adds several novel features. In particular we have incorporated the ability to use a generic observation operator, or sensor model, to permit data fusion. We can also cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the variogram parameters is based on maximum likelihood estimation. We illustrate the projected sequential method in application to synthetic and real data sets. We discuss the software implementation and suggest possible future extensions.

Synchronization processes in nonlinear systems and their relation to cortical oscillatory dynamics

This thesis was focused on theoretical models of synchronization to cortical dynamics as measured by magnetoencephalography (MEG). Dynamical systems theory was used in both identifying relevant variables for brain coordination and also in devising methods for their quantification. We presented a method for studying interactions of linear and chaotic neuronal sources using MEG beamforming techniques. We showed that such sources can be accurately reconstructed in terms of their location, temporal dynamics and possible interactions. Synchronization in low-dimensional nonlinear systems was studied to explore specific correlates of functional integration and segregation. In the case of interacting dissimilar systems, relevant coordination phenomena involved generalized and phase synchronization, which were often intermittent. Spatially-extended systems were then studied. For locally-coupled dissimilar systems, as in the case of cortical columns, clustering behaviour occurred. Synchronized clusters emerged at different frequencies and their boundaries were marked through oscillation death. The macroscopic mean field revealed sharp spectral peaks at the frequencies of the clusters and broader spectral drops at their boundaries. These results question existing models of Event Related Synchronization and Desynchronization. We re-examined the concept of the steady-state evoked response following an AM stimulus. We showed that very little variability in the AM following response could be accounted by system noise. We presented a methodology for detecting local and global nonlinear interactions from MEG data in order to account for residual variability. We found crosshemispheric nonlinear interactions of ongoing cortical rhythms concurrent with the stimulus and interactions of these rhythms with the following AM responses. Finally, we hypothesized that holistic spatial stimuli would be accompanied by the emergence of clusters in primary visual cortex resulting in frequency-specific MEG oscillations. Indeed, we found different frequency distributions in induced gamma oscillations for different spatial stimuli, which was suggestive of temporal coding of these spatial stimuli. Further, we addressed the bursting character of these oscillations, which was suggestive of intermittent nonlinear dynamics. However, we did not observe the characteristic-3/2 power-law scaling in the distribution of interburst intervals. Further, this distribution was only seldom significantly different to the one obtained in surrogate data, where nonlinear structure was destroyed. In conclusion, the work presented in this thesis suggests that advances in dynamical systems theory in conjunction with developments in magnetoencephalography may facilitate a mapping between levels of description int he brain. this may potentially represent a major advancement in neuroscience.

A three dimensional numerical investigation of hillslope flow processes

Physically based distributed models of catchment hydrology are likely to be made available as engineering tools in the near future. Although these models are based on theoretically acceptable equations of continuity, there are still limitations in the present modelling strategy. Of interest to this thesis are the current modelling assumptions made concerning the effects of soil spatial variability, including formations producing distinct zones of preferential flow. The thesis contains a review of current physically based modelling strategies and a field based assessment of soil spatial variability. In order to investigate the effects of soil nonuniformity a fully three dimensional model of variability saturated flow in porous media is developed. The model is based on a Galerkin finite element approximation to Richards equation. Accessibility to a vector processor permits numerical solutions on grids containing several thousand node points. The model is applied to a single hillslope segment under various degrees of soil spatial variability. Such variability is introduced by generating random fields of saturated hydraulic conductivity using the turning bands method. Similar experiments are performed under conditions of preferred soil moisture movement. The results show that the influence of soil variability on subsurface flow may be less significant than suggested in the literature, due to the integrating effects of three dimensional flow. Under conditions of widespread infiltration excess runoff, the results indicate a greater significance of soil nonuniformity. The recognition of zones of preferential flow is also shown to be an important factor in accurate rainfall-runoff modelling. Using the results of various fields of soil variability, experiments are carried out to assess the validity of the commonly used concept of `effective parameters'. The results of these experiments suggest that such a concept may be valid in modelling subsurface flow. However, the effective parameter is observed to be event dependent when the dominating mechanism is infiltration excess runoff.

Clinical studies of spatial and temporal aspects of vision: an investigation using psychophysical and electrophysiological techniques

Separate physiological mechanisms which respond to spatial and temporal stimulation have been identified in the visual system. Some pathological conditions may selectively affect these mechanisms, offering a unique opportunity to investigate how psychophysical and electrophysiological tests reflect these visual processes, and thus enhance the use of the tests in clinical diagnosis. Amblyopia and optical blur were studied, representing spatial visual defects of neural and optical origin, respectively. Selective defects of the visual pathways were also studied - optic neuritis which affects the optic nerve, and dementia of the Alzheimer type in which the higher association areas are believed to be affected, but the primary projections spared. Seventy control subjects from 10 to 79 years of age were investigated. This provided material for an additional study of the effect of age on the psychophysical and electrophysiological responses. Spatial processing was measured by visual acuity, the contrast sensitivity function, or spatial modulation transfer function (MTF), and the pattern reversal and pattern onset-offset visual evoked potential (VEP). Temporal, or luminance, processing was measured by the de Lange curve, or temporal MTF, and the flash VEP. The pattern VEP was shown to reflect the integrity of the optic nerve, geniculo striate pathway and primary projections, and was related to high temporal frequency processing. The individual components of the flash VEP differed in their characteristics. The results suggested that the P2 component reflects the function of the higher association areas and is related to low temporal frequency processing, while the Pl component reflects the primary projection areas. The combination of a delayed flash P2 component and a normal latency pattern VEP appears to be specific to dementia of the Alzheimer type and represents an important diagnostic test for this condition.

Pooling and suppression in human spatial vision

A distinct feature of several recent models of contrast masking is that detecting mechanisms are divisively inhibited by a broadly tuned ‘gain pool’ of narrow-band spatial pattern mechanisms. The contrast gain control provided by this ‘cross-channel’ architecture achieves contrast normalisation of early pattern mechanisms, which is important for keeping them within the non-saturating part of their biological operating characteristic. These models superseded earlier ‘within-channel’ models, which had supposed that masking arose from direct stimulation of the detecting mechanism by the mask. To reveal the extent of masking, I measured the levels produced with large ranges of pattern spatial relationships that have not been explored before. Substantial interactions between channels tuned to different orientations and spatial frequencies were found. Differences in the masking levels produced with single and multiple component mask patterns provided insights into the summation rules within the gain pool. A widely used cross-channel masking model was tested on these data and was found to perform poorly. The model was developed and a version in which linear summation was allowed between all components within the gain pool but with the exception of the self-suppressing route typically provided the best account of the data. Subsequently, an adaptation paradigm was used to probe the processes underlying pooled responses in masking. This delivered less insight into the pooling than the other studies and areas were identified that require investigation for a new unifying model of masking and adaptation. In further experiments, levels of cross-channel masking were found to be greatly influenced by the spatio-temporal tuning of the channels involved. Old masking experiments and ideas relying on within-channel models were re-elevated in terms of contemporary cross-channel models (e.g. estimations of channel bandwidths from orientation masking functions) and this led to different conclusions than those originally arrived at. The investigation of effects with spatio-temporally superimposed patterns is focussed upon throughout this work, though it is shown how these enquiries might be extended to investigate effects across spatial and temporal position.

In situ imaging and height reconstruction of phase separation processes in polymer blends during spin coating

Spin coating polymer blend thin films provides a method to produce multiphase functional layers of high uniformity covering large surface areas. Applications for such layers include photovoltaics and light-emitting diodes where performance relies upon the nanoscale phase separation morphology of the spun film. Furthermore, at micrometer scales, phase separation provides a route to produce self-organized structures for templating applications. Understanding the factors that determine the final phase-separated morphology in these systems is consequently an important goal. However, it has to date proved problematic to fully test theoretical models for phase separation during spin coating, due to the high spin speeds, which has limited the spatial resolution of experimental data obtained during the coating process. Without this fundamental understanding, production of optimized micro- and nanoscale structures is hampered. Here, we have employed synchronized stroboscopic illumination together with the high light gathering sensitivity of an electron-multiplying charge-coupled device camera to optically observe structure evolution in such blends during spin coating. Furthermore the use of monochromatic illumination has allowed interference reconstruction of three-dimensional topographies of the spin-coated film as it dries and phase separates with nanometer precision. We have used this new method to directly observe the phase separation process during spinning for a polymer blend (PS-PI) for the first time, providing new insights into the spin-coating process and opening up a route to understand and control phase separation structures. © 2011 American Chemical Society.

Combining temporal and spectral information with spatial mapping to identify differences between phonological and semantic networks:a magnetoencephalographic approach

Early, lesion-based models of language processing suggested that semantic and phonological processes are associated with distinct temporal and parietal regions respectively, with frontal areas more indirectly involved. Contemporary spatial brain mapping techniques have not supported such clear-cut segregation, with strong evidence of activation in left temporal areas by both processes and disputed evidence of involvement of frontal areas in both processes. We suggest that combining spatial information with temporal and spectral data may allow a closer scrutiny of the differential involvement of closely overlapping cortical areas in language processing. Using beamforming techniques to analyze magnetoencephalography data, we localized the neuronal substrates underlying primed responses to nouns requiring either phonological or semantic processing, and examined the associated measures of time and frequency in those areas where activation was common to both tasks. Power changes in the beta (14-30 Hz) and gamma (30-50 Hz) frequency bandswere analyzed in pre-selected time windows of 350-550 and 500-700ms In left temporal regions, both tasks elicited power changes in the same time window (350-550 ms), but with different spectral characteristics, low beta (14-20 Hz) for the phonological task and high beta (20-30 Hz) for the semantic task. In frontal areas (BA10), both tasks elicited power changes in the gamma band (30-50 Hz), but in different time windows, 500-700ms for the phonological task and 350-550ms for the semantic task. In the left inferior parietal area (BA40), both tasks elicited changes in the 20-30 Hz beta frequency band but in different time windows, 350-550ms for the phonological task and 500-700ms for the semantic task. Our findings suggest that, where spatial measures may indicate overlapping areas of involvement, additional beamforming techniques can demonstrate differential activation in time and frequency domains. © 2012 McNab, Hillebrand, Swithenby and Rippon.

The embodied nature of spatial perspective taking:embodied transformation versus sensorimotor interference

Humans are able to mentally adopt the spatial perspective of others and understand the world from their point of view. We propose that spatial perspective taking (SPT) could have developed from the physical alignment of perspectives. This would support the notion that others have put forward claiming that SPT is an embodied cognitive process. We investigated this issue by contrasting several accounts in terms of the assumed processes and the nature of the embodiment. In a series of four experiments we found substantial evidence that the transformations during SPT comprise large parts of the body schema, which we did not observe for object rotation. We further conclude that the embodiment of SPT is best conceptualised as the self-initiated emulation of a body movement, supporting the notion of endogenous motoric embodiment. Overall our results are much more in agreement with an ‘embodied’ transformation account than with the notion of sensorimotor interference. Finally we discuss our findings in terms of SPT as a possible evolutionary stepping stone towards more complex alignments of socio-cognitive perspectives.

The two forms of visuo-spatial perspective taking are differently embodied and subserve different spatial prepositions

We set out to distinguish level 1 (VPT-1) and level 2 (VPT-2) perspective taking with respect to the embodied nature of the underlying processes as well as to investigate their dependence or independence of response modality (motor vs. verbal). While VPT-1 reflects understanding of what lies within someone else’s line of sight, VPT-2 involves mentally adopting someone else’s spatial point of view. Perspective taking is a high-level conscious and deliberate mental transformation that is crucially placed at the convergence of perception, mental imagery, communication, and even theory of mind in the case of VPT-2. The differences between VPT-1 and VPT-2 mark a qualitative boundary between humans and apes, with the latter being capable of VPT-1 but not of VPT-2. However, our recent data showed that VPT-2 is best conceptualized as the deliberate simulation or emulation of a movement, thus underpinning its embodied origins. In the work presented here we compared VPT-2 to VPT-1 and found that VPT-1 is not at all, or very differently embodied. In a second experiment we replicated the qualitatively different patterns for VPT-1 and VPT-2 with verbal responses that employed spatial prepositions. We conclude that VPT-1 is the cognitive process that subserves verbal localizations using “in front” and “behind,” while VPT-2 subserves “left” and “right” from a perspective other than the egocentric. We further conclude that both processes are grounded and situated, but only VPT-2 is embodied in the form of a deliberate movement simulation that increases in mental effort with distance and incongruent proprioception. The differences in cognitive effort predict differences in the use of the associated prepositions. Our findings, therefore, shed light on the situated, grounded and embodied basis of spatial localizations and on the psychology of their use.

Programmed cell death (PCD) processes begin extremely early in Alstroemeria petal senescence

-In the Liliaceous species Alstroemeria, petal senescence is characterized by wilting and inrolling, terminating in abscission 8-10 d after flower opening. -In many species, flower development and senescence involves programmed cell death (PCD). PCD in Alstroemeria petals was investigated by light (LM) and transmission electron microscopy (TEM) (to study nuclear degradation and cellular integrity), DNA laddering and the expression programme of the DAD-1 gene. -TEM showed nuclear and cellular degradation commenced before the flowers were fully open and that epidermal cells remained intact whilst the mesophyll cells degenerated completely. DNA laddering increased throughout petal development. Expression of the ALSDAD-1 partial cDNA was shown to be downregulated after flower opening. -We conclude that some PCD processes are started extremely early and proceed throughout flower opening and senescence, whereas others occur more rapidly between stages 4-6 (i.e. postanthesis). The spatial distribution of PCD across the petals is discussed. Several molecular and physiological markers of PCD are present during Alstroemeria petal senescence. © New Phytologist (2003).

Projected sequential Gaussian processes:a C++ tool for interpolation of large datasets with heterogeneous noise

Heterogeneous datasets arise naturally in most applications due to the use of a variety of sensors and measuring platforms. Such datasets can be heterogeneous in terms of the error characteristics and sensor models. Treating such data is most naturally accomplished using a Bayesian or model-based geostatistical approach; however, such methods generally scale rather badly with the size of dataset, and require computationally expensive Monte Carlo based inference. Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential Bayesian framework for inference in such projected processes is presented. The observations are considered one at a time which avoids the need for high dimensional integrals typically required in a Bayesian approach. A C++ library, gptk, which is part of the INTAMAP web service, is introduced which implements projected, sequential estimation and adds several novel features. In particular the library includes the ability to use a generic observation operator, or sensor model, to permit data fusion. It is also possible to cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the covariance parameters is explored, including the impact of the projected process approximation on likelihood profiles. We illustrate the projected sequential method in application to synthetic and real datasets. Limitations and extensions are discussed. © 2010 Elsevier Ltd.

Spatial ecological complexity measures in GRASS GIS

Good estimates of ecosystem complexity are essential for a number of ecological tasks: from biodiversity estimation, to forest structure variable retrieval, to feature extraction by edge detection and generation of multifractal surface as neutral models for e.g. feature change assessment. Hence, measuring ecological complexity over space becomes crucial in macroecology and geography. Many geospatial tools have been advocated in spatial ecology to estimate ecosystem complexity and its changes over space and time. Among these tools, free and open source options especially offer opportunities to guarantee the robustness of algorithms and reproducibility. In this paper we will summarize the most straightforward measures of spatial complexity available in the Free and Open Source Software GRASS GIS, relating them to key ecological patterns and processes.

PDNAsite:identification of DNA-binding site from protein sequence by incorporating spatial and sequence context

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community.

Understanding anuran community dynamics in temporary wetlands: The interaction and importance of landscape and biotic processes

The major objective of this study was to determine the relative importance of landscape factors, local abiotic factors, and biotic interactions in influencing tadpole community structure in temporary wetlands. I also examined the influence of agricultural activities in South-central Florida by comparing tadpole communities in native prairie wetlands (a relatively unmodified habitat) at the Kissimmee Prairie Sanctuary (KPS) to tadpole communities in three agriculturally modified habitats found at MacArthur Agro-Ecology Research Center (MAERC). Environmental characteristics were measured in 24 isolated wetlands, and tadpoles were sampled using throw-traps and dipnets during the 1999 wet season (June–October). Landscape characteristics were expected to predominately influence all aspects of community structure because anurans associated with temporary wetland systems are likely to exist as metapopulations. Both landscape characteristics (wetland proximity to nearest woodland and the amount of woodland surrounding the wetland) and biotic interactions (fish predation) had the largest influence on tadpole community structure. Predatory fish influenced tadpole communities more than expected due to the ubiquity of wetlands, lack of topographic relief, and dispersal abilities of several fish species. Differences in tadpole community structure among habitat types were attributed to differences in woodland attributes and susceptibility to fish colonization. Furthermore, agricultural modification of prairie habitats in South-central Florida may benefit amphibian communities, particularly woodland-dwelling species that are unable to coexist with predatory fish. From a conservation standpoint, temporary wetlands proximal to woodland areas and isolated from permanent water sources appear to be most important to amphibians. In addition, the high tadpole densities attained in these wetlands suggest that these wetlands serve as biological hotspots within the landscape, and their benefits extend into the adjacent terrestrial matrix. Further research efforts are needed to quantify the biological productivity of these systems and determine spatial dynamics of anurans in surrounding terrestrial habitats. ^