A Neural Model of Surface Perception: Lightness, Anchoring, and Filling-in

This article develops a neural model of how the visual system processes natural images under variable illumination conditions to generate surface lightness percepts. Previous models have clarified how the brain can compute the relative contrast of images from variably illuminate scenes. How the brain determines an absolute lightness scale that "anchors" percepts of surface lightness to us the full dynamic range of neurons remains an unsolved problem. Lightness anchoring properties include articulation, insulation, configuration, and are effects. The model quantatively simulates these and other lightness data such as discounting the illuminant, the double brilliant illusion, lightness constancy and contrast, Mondrian contrast constancy, and the Craik-O'Brien-Cornsweet illusion. The model also clarifies the functional significance for lightness perception of anatomical and neurophysiological data, including gain control at retinal photoreceptors, and spatioal contrast adaptation at the negative feedback circuit between the inner segment of photoreceptors and interacting horizontal cells. The model retina can hereby adjust its sensitivity to input intensities ranging from dim moonlight to dazzling sunlight. A later model cortical processing stages, boundary representations gate the filling-in of surface lightness via long-range horizontal connections. Variants of this filling-in mechanism run 100-1000 times faster than diffusion mechanisms of previous biological filling-in models, and shows how filling-in can occur at realistic speeds. A new anchoring mechanism called the Blurred-Highest-Luminance-As-White (BHLAW) rule helps simulate how surface lightness becomes sensitive to the spatial scale of objects in a scene. The model is also able to process natural images under variable lighting conditions.

Laminar Cortical Dynamics of 3D Surface Perception: Stratification, transparency, and Neon Color Spreading

How does the laminar organization of cortical circuitry in areas VI and V2 give rise to 3D percepts of stratification, transparency, and neon color spreading in response to 2D pictures and 3D scenes? Psychophysical experiments have shown that such 3D percepts are sensitive to whether contiguous image regions have the same relative contrast polarity (dark-light or lightdark), yet long-range perceptual grouping is known to pool over opposite contrast polarities. The ocularity of contiguous regions is also critical for neon color spreading: Having different ocularity despite the contrast relationship that favors neon spreading blocks the spread. In addition, half visible points in a stereogram can induce near-depth transparency if the contrast relationship favors transparency in the half visible areas. It thus seems critical to have the whole contrast relationship in a monocular configuration, since splitting it between two stereogram images cancels the effect. What adaptive functions of perceptual grouping enable it to both preserve sensitivity to monocular contrast and also to pool over opposite contrasts? Aspects of cortical development, grouping, attention, perceptual learning, stereopsis and 3D planar surface perception have previously been analyzed using a 3D LAMINART model of cortical areas VI, V2, and V4. The present work consistently extends this model to show how like-polarity competition between VI simple cells in layer 4 may be combined with other LAMINART grouping mechanisms, such as cooperative pooling of opposite polarities at layer 2/3 complex cells. The model also explains how the Metelli Rules can lead to transparent percepts, how bistable transparency percepts can arise in which either surface can be perceived as transparent, and how such a transparency reversal can be facilitated by an attention shift. The like-polarity inhibition prediction is consistent with lateral masking experiments in which two f1anking Gabor patches with the same contrast polarity as the target increase the target detection threshold when they approach the target. It is also consistent with LAMINART simulations of cortical development. Other model explanations and testable predictions will also be presented.

Fast Synchronization of Perpetual Grouping in Laminar Visual Cortical Circuits

Perceptual grouping is well-known to be a fundamental process during visual perception, notably grouping across scenic regions that do not receive contrastive visual inputs. Illusory contours are a classical example of such groupings. Recent psychophysical and neurophysiological evidence have shown that the grouping process can facilitate rapid synchronization of the cells that are bound together by a grouping, even when the grouping must be completed across regions that receive no contrastive inputs. Synchronous grouping can hereby bind together different object parts that may have become desynchronized due to a variety of factors, and can enhance the efficiency of cortical transmission. Neural models of perceptual grouping have clarified how such fast synchronization may occur by using bipole grouping cells, whose predicted properties have been supported by psychophysical, anatomical, and neurophysiological experiments. These models have not, however, incorporated some of the realistic constraints on which groupings in the brain are conditioned, notably the measured spatial extent of long-range interactions in layer 2/3 of a grouping network, and realistic synaptic and axonal signaling delays within and across cells in different cortical layers. This work addresses the question: Can long-range interactions that obey the bipole constraint achieve fast synchronization under realistic anatomical and neurophysiological constraints that initially desynchronize grouping signals? Can the cells that synchronize retain their analog sensitivity to changing input amplitudes? Can the grouping process complete and synchronize illusory contours across gaps in bottom-up inputs? Our simulations show that the answer to these questions is Yes.

Biologically Inspired Approaches to Automated Feature Extraction and Target Recognition

Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and figure/ground segmentation, and memory models create attentionally controlled recognition codes that intrinsically cornbine botton-up activation and top-down learned expectations. These two streams of research form the foundation of novel dynamically integrated systems for image understanding. Simulations using multispectral images illustrate road completion across occlusions in a cluttered scene and information fusion from incorrect labels that are simultaneously inconsistent and correct. The CNS Vision and Technology Labs (cns.bu.edulvisionlab and cns.bu.edu/techlab) are further integrating science and technology through analysis, testing, and development of cognitive and neural models for large-scale applications, complemented by software specification and code distribution.

Processing of Synthetic Aperture Radar Images by a Multiscale Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. The segmentation is performed by three "copies" of the BCS and FCS, of small, medium, and large scales, wherein the "short-range" and "long-range" interactions within each scale occur over smaller or larger distances, corresponding to the size of the early filters of each scale. A diffusive filling-in operation within the segmented regions at each scale produces coherent surface representations. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

Preattentive Texture Segmentation and Grouping by the Boundary Contour System

An improved Boundary Contour System (BCS) neural network model of preattentive vision is applied to two images that produce strong "pop-out" of emergent groupings in humans. In humans these images generate groupings collinear with or perpendicular to image contrasts. Analogous groupings occur in computer simulations of the model. Long-range cooperative and short-range competitive processes of the BCS dynamically form the stable groupings of texture regions in response to the images.

Processing of Synthetic Aperture Radar Images by the Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to two large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. Finally, a diffusive filling-in operation within the segmented regions produces coherent visible structures. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

Development of block copolymer lithography for device structure fabrication

This thesis investigated well-ordered block copolymer (BCP) thin film characteristics and their use for nanoscale pattern formation using a series of polystyrene-block-polymethylmethacrylate (PS-b-PMMA), polystyrene-blockpolydimethylsiloxane (PS-b-PDMS) and polystyrene-block-poly(ethylene oxide) (PS-b-PEO) systems of various molecular weights. BCP thin films, which act as an ‘on-chip’ etch mask and material templates, are highly promising self-assembling process for future scalable nanolithography. Unlike conventional BCP processing methods, the work in this thesis demonstrates that well-ordered patterns can be achieved in a few seconds compared to several hours by use of a non-conventional microwave assisted technique. As a result, well-ordered BCP nanoscale structures can be developed in industry appropriate periods facilitating their incorporation into current technologies. An optimised and controlled plasma dry etch process was used for successful pattern transfer to the underlying silicon substrate. Long range ordered BCP templates were further modified by selective metal inclusion technique to form a hard mask template towards fabrication of high aspect ratio nanopillars and nanowires. The work described here is centred on how these templates might be used to generate function at substrate surfaces. Herein we describe a number of innovations which might allow their successful uptake in a number of applications.

Use of pulsed field gel electrophoresis to characterize BCR gene involvement in CML patients lacking M-BCR rearrangement.

We studied the pattern of BCR involvement in 52 patients with chronic myeloid leukemia by Southern blotting. Of 33 Philadelphia (Ph)-positive patients, 30 had evidence of M-BCR rearrangement, two cases were difficult to interpret, and one clearly lacked evidence of M-BCR rearrangement. Of 19 Ph-negative patients, nine showed M-BCR rearrangement, nine showed no rearrangement, and one result was uncertain. We selected for more detailed study eight patients (three Ph-positive and five Ph-negative). Two of the Ph-positive patients, whose Southern blots were difficult to interpret, had rearranged bands when the BCR gene was studied by pulsed field gel electrophoresis (PFGE). Results of PFGE studies and in situ hybridization to metaphase chromosomes in the third Ph-positive patient, whose DNA clearly lacked M-BCR rearrangement on Southern analysis, were consistent with a breakpoint on chromosome 22 located 3' of all known exons of the BCR gene. However, mRNA studied with the polymerase chain reaction showed evidence of a classical b2-a2 linkage. The findings in this patient may be explained by an unusual genomic breakpoint downstream of the BCR gene associated with long range splicing that excluded all of the 3' BCR exons. Of the five patients with Ph-negative M-BCR non-rearranged CML studied by PFGE for BCR gene rearrangement, none had evidence of rearranged bands. We conclude that PFGE is a valuable adjunct to standard molecular techniques for the study of atypical cases of CML. Occasional patients with Ph-positive CML have breakpoints outside M-BCR. The BCR gene is probably not involved in patients with Ph-negative, M-BCR non-rearranged CML.

A complex intronic enhancer regulates expression of the CFTR gene by direct interaction with the promoter.

Genes can maintain spatiotemporal expression patterns by long-range interactions between cis-acting elements. The cystic fibrosis transmembrane conductance regulator gene (CFTR) is expressed primarily in epithelial cells. An element located within a DNase I-hypersensitive site (DHS) 10 kb into the first intron was previously shown to augment CFTR promoter activity in a tissue-specific manner. Here, we reveal the mechanism by which this element influences CFTR transcription. We employed a high-resolution method of mapping DHS using tiled microarrays to accurately locate the intron 1 DHS. Transfection of promoter-reporter constructs demonstrated that the element displays classical tissue-specific enhancer properties and can independently recruit factors necessary for transcription initiation. In vitro DNase I footprinting analysis identified a protected region that corresponds to a conserved, predicted binding site for hepatocyte nuclear factor 1 (HNF1). We demonstrate by electromobility shift assays (EMSA) and chromatin immunoprecipitation (ChIP) that HNF1 binds to this element both in vitro and in vivo. Moreover, using chromosome conformation capture (3C) analysis, we show that this element interacts with the CFTR promoter in CFTR-expressing cells. These data provide the first insight into the three- dimensional (3D) structure of the CFTR locus and confirm the contribution of intronic cis-acting elements to the regulation of CFTR gene expression.

Modeling the Effects of Habitat Fragmentation on the Movements of the Mongolian Gazelle in the Eastern Mongolian Steppe

The Mongolian gazelle, Procapra gutturosa, resides in the immense and dynamic ecosystem of the Eastern Mongolian Steppe. The Mongolian Steppe ecosystem dynamics, including vegetation availability, change rapidly and dramatically due to unpredictable precipitation patterns. The Mongolian gazelle has adapted to this unpredictable vegetation availability by making long range nomadic movements. However, predicting these movements is challenging and requires a complex model. An accurate model of gazelle movements is needed, as rampant habitat fragmentation due to human development projects - which inhibit gazelles from obtaining essential resources - increasingly threaten this nomadic species. We created a novel model using an Individual-based Neural Network Genetic Algorithm (ING) to predict how habitat fragmentation affects animal movement, using the Mongolian Steppe as a model ecosystem. We used Global Positioning System (GPS) collar data from real gazelles to “train” our model to emulate characteristic patterns of Mongolian gazelle movement behavior. These patterns are: preferred vegetation resources (NDVI), displacement over certain time lags, and proximity to human areas. With this trained model, we then explored how potential scenarios of habitat fragmentation may affect gazelle movement. This model can be used to predict how fragmentation of the Mongolian Steppe may affect the Mongolian gazelle. In addition, this model is novel in that it can be applied to other ecological scenarios, since we designed it in modules that are easily interchanged.

Interactions spatiales et auto-organisation des végétations semi-arides

Les recherches récapitulées dans cette thèse de doctorat ont porté sur les causes de l’organisation spatiale des végétations périodiques. Ces structures paysagères aux motifs réguliers, tachetés, tigrés ou labyrinthiques, d’échelle décamétrique à hectométrique, couvrant des étendues considérables sur au moins trois continents, constituent un cas d’école dans l’étude des processus endogènes présidant à l’hétérogénéité du couvert végétal. Ces structures prennent place sur un substrat homogène, mis à part la rétroaction du couvert lui-même, et sont marquées par des écotones abrupts et la persistance d’une proportion considérable de sol nu. Plusieurs modèles ont mis en avant l’existence possible d’un phénomène d’auto-organisation du couvert, qui verrait une structure d’ensemble émerger des interactions locales entre individus. Ces modèles se basent sur le jeu simultané de la consommation de la ressource (compétition) et de l’amélioration de l’un ou l’autre des éléments du bilan de la même ressource par le couvert (facilitation). La condition à l’existence d’une structure d’ensemble spatialement périodique et stable réside dans une différence entre la portée de la compétition (plus grande) et celle de la facilitation. L’apparition de ces structures est modulée par le taux de croissance biologique, qui est le reflet des contraintes extérieures telles que l’aridité, le pâturage ou la coupe de bois. Le modus operandi des interactions spatiales supposées entre individus reste largement à préciser.

Nos recherches ont été menées au sud-ouest de la République du Niger, à l’intérieur et dans les environs du parc Régional du W. Trois axes ont été explorés :(i) Une étude de la dépendance spatiale entre la structure de la végétation (biovolumes cartographiés) et les paramètres du milieu abiotique (relief, sol), sur base d’analyses spectrales et cross-spectrales par transformée de Fourier (1D et 2D). (ii) Une étude diachronique (1956, 1975 et 1996) à large échelle (3000 km²) de l’influence de l’aridité et des pressions d’origine anthropique sur l’auto-organisation des végétations périodiques, basée sur la caractérisation de la structure spatiale des paysages sur photos aériennes via la transformée de Fourier en 2D. (iii) Trois études portant sur les interactions spatiales entre individus :En premier lieu, via l’excavation des systèmes racinaires (air pulsé) ;Ensuite, par un suivi spatio-temporel du bilan hydrique du sol (blocs de gypse) ;Enfin, via le marquage de la ressource par du deutérium.

Nous avons ainsi pu établir que les végétations périodiques constituent bien un mode d’auto-organisation pouvant survenir sur substrat homogène et modulé par les contraintes climatiques et anthropiques. Un ajustement rapide entre l’organisation des végétations périodiques et le climat a pu être montrée en zone protégée. La superficie et l’organisation des végétations périodiques y ont tour à tour progressé et régressé en fonction d’épisodes secs ou humides. Par contre, en dehors de l’aire protégée, la possibilité d’une restauration du couvert semble fortement liée au taux d’exploitation des ressources végétales. Ces résultats ont d’importantes implications quant à la compréhension des interactions entre climat et écosystèmes et à l’évaluation de leurs capacités de charge. La caractérisation de la structure spatiale des végétations arides, notamment par la transformée de Fourier d’images HR, devrait être généralisée comme outil de monitoring de l’état de ces écosystèmes. Nos études portant sur les modes d’interactions spatiales ont permis de confirmer l’existence d’une facilitation à courte portée du couvert végétal sur la ressource. Cependant, cette facilitation ne semble pas s’exercer sur le terme du bilan hydrique traditionnellement avancé, à savoir l’infiltration, mais plutôt sur le taux d’évaporation (deux fois moindre à l’ombre des canopées). Ce mécanisme exclut l’existence de transferts diffusifs souterrains entre sols nu et fourrés. Des transferts inverses semblent d’ailleurs montrés par le marquage isotopique. L’étude du bilan hydrique et la cartographie du micro-relief, ainsi que la profondeur fortement réduite de la zone d’exploitation racinaire, jettent de sérieux doutes quant au rôle communément admis des transferts d’eau par ruissellement/diffusion de surface en tant que processus clé dans la compétition à distance entre les plantes. L’alternative réside dans l’existence d’une compétition racinaire de portée supérieure aux canopées. Cette hypothèse trouve une confirmation tant par les rhizosphères excavées, superficielles et étendues, que dans le marquage isotopique, montrant des contaminations d’arbustes situés à plus de 15 m de la zone d’apport. De même, l’étude du bilan hydrique met en évidence les influences simultanées et contradictoires (facilitation/compétition) des ligneux sur l’évapotranspiration.

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This PhD thesis gathers results of a research dealing with the causes of the spatial organisation of periodic vegetations. These landscape structures, featuring regular spotted, labyrinthine or banded patterns of decametric to hectometric scale, and extending over considerable areas on at least three continents, constitute a perfect study case to approach endogenous processes leading to vegetation heterogeneities. These patterns occur over homogeneous substratum, except for vegetation’s own feedbacks, and are marked by sharp ecotones and the persistence of a considerable amount of bare soil. A number of models suggested a possible case of self-organized patterning, in which the general structure would emerge from local interactions between individuals. Those models rest on the interplay of competitive and facilitative effects, relating to soil water consumption and to soil water budget enhancement by vegetation. A general necessary condition for pattern formation to occur is that negative interactions (competition) have a larger range than positive interactions (facilitation). Moreover, all models agree with the idea that patterning occurs when vegetation growth decreases, for instance as a result of reduced water availability, domestic grazing or wood cutting, therefore viewing patterns as a self-organised response to environmental constraints. However the modus operandi of the spatial interactions between individual plants remains largely to be specified.

We carried out a field research in South-West Niger, within and around the W Regional Park. Three research lines were explored: (i) The study of the spatial dependency between the vegetation pattern (mapped biovolumes) and the factors of the abiotic environment (soil, relief), on the basis of spectral and cross-spectral analyses with Fourier transform (1D and 2D). (ii) A broad scale diachronic study (1956, 1975, 1996) of the influence of aridity and human induced pressures on the vegetation self-patterning, based on the characterisation of patterns on high resolution remote sensing data via 2D Fourier transform. (iii) Three different approaches of the spatial interactions between individuals: via root systems excavation with pulsed air; via the monitoring in space and time of the soil water budget (gypsum blocks method); and via water resource labelling with deuterated water.

We could establish that periodic vegetations are indeed the result of a self-organisation process, occurring in homogeneous substratum conditions and modulated by climate and human constraints. A rapid adjustment between vegetation patterning and climate could be observed in protected zones. The area and patterning of the periodic vegetations successively progressed and regressed, following drier or wetter climate conditions. On the other hand, outside protected areas, the restoration ability of vegetation appeared to depend on the degree of vegetation resource exploitation. These results have important implications regarding the study of vegetation-climate interactions and the evaluation of ecosystems’ carrying capacities. Spatial pattern characterisation in arid vegetations using Fourier transform of HR remote sensing data should be generalised for the monitoring of those ecosystems. Our studies dealing with spatial interaction mechanisms confirmed the existence of a short range facilitation of the cover on water resource. However, this facilitation does not seem to act through the commonly accepted infiltration component, but rather on the evaporative rate (twice less within thickets). This mechanism excludes underground diffusive transfers between bare ground and vegetation. Inverse transfers were even shown by deuterium labelling. Water budget study and micro-elevation mapping, along with consistent soil shallowness, together cast serious doubts on the traditional mechanism of run-off/diffusion of surface water as a key process of the long range competition between plants. An alternative explanation lies in long range root competition. This hypothesis find support as well in the excavated root systems, shallow and wide, as in isotopic labelling, showing contaminations of shrubs located up to 15 m of the irrigated area. Water budget study also evidenced simultaneous contradictory effects (facilitation/competition) of shrubs on evapotranspiration.

Forward and inverse transport of particulate matter and gaseous pollutants affecting the region bordering the English Channel

The ATTMA "Aerosol Transport in the Trans-Manche Atmosphere" project investigates the transportation and dispersion of air pollutants across the English Channel, in collaboration with local authorities and other Universities in Southern England and Northern France. The research is concerned with both forward and inverse (receptor based) tracking. Two alternative dispersion simulation methods are used: (a) Lagrangian Particle Dispersion (LPD) models, (b) Eulerian Finite Volume type models. This paper is concerned with part (a), the simulations based on LPD models. Two widely applied LPD models are used and compared. Since in many observed episodes the source of pollution is traced outside the region of interest, long range, trans-continental transport is also investigated.

Modelling high particulate matter and ozone episodes in the Trans-Manche region

There is concern in the Cross-Channel region of Nord-Pas-de-Calais (France) and Kent (Great Britain), regarding the extent of atmospheric pollution detected in the area from emitted gaseous (VOC, NOx, S02)and particulate substances. In particular, the air quality of the Cross-Channel or "Trans-Manche" region is highly affected by the heavily industrial area of Dunkerque, in addition to transportation sources linked to cross-channel traffic in Kent and Calais, posing threats to the environment and human health. In the framework of the cross-border EU Interreg IIIA activity, the joint Anglo-French project, ATTMA, has been commissioned to study Aerosol Transport in the Trans-Manche Atmosphere. Using ground monitoring data from UK and French networks and with the assistance of satellite images the project aims to determine dispersion patterns. and identify sources responsible for the pollutants. The findings of this study will increase awareness and have a bearing on future air quality policy in the region. Public interest is evident by the presence of local authorities on both sides of the English Channel as collaborators. The research is based on pollution transport simulations using (a) Lagrangian Particle Dispersion (LPD) models, (b) an Eulerian Receptor Based model. This paper is concerned with part (a), the LPD Models. Lagrangian Particle Dispersion (LPD) models are often used to numerically simulate the dispersion of a passive tracer in the planetary boundary layer by calculating the Lagrangian trajectories of thousands of notional particles. In this contribution, the project investigated the use of two widely used particle dispersion models: the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the model FLEXPART. In both models forward tracking and inverse (or·. receptor-based) modes are possible. Certain distinct pollution episodes have been selected from the monitor database EXPER/PF and from UK monitoring stations, and their likely trajectory predicted using prevailing weather data. Global meteorological datasets were downloaded from the ECMWF MARS archive. Part of the difficulty in identifying pollution sources arises from the fact that much of the pollution outside the monitoring area. For example heightened particulate concentrations are to originate from sand storms in the Sahara, or volcanic activity in Iceland or the Caribbean work identifies such long range influences. The output of the simulations shows that there are notable differences between the formulations of and Hysplit, although both models used the same meteorological data and source input, suggesting that the identification of the primary emissions during air pollution episodes may be rather uncertain.