Representation of sound localization cues in the auditory thalamus of the barn owl

Barn owls can localize a sound source using either the map of auditory space contained in the optic tectum or the auditory forebrain. The auditory thalamus, nucleus ovoidalis (N.Ov), is situated between these two auditory areas, and its inactivation precludes the use of the auditory forebrain for sound localization. We examined the sources of inputs to the N.Ov as well as their patterns of termination within the nucleus. We also examined the response of single neurons within the N.Ov to tonal stimuli and sound localization cues. Afferents to the N.Ov originated with a diffuse population of neurons located bilaterally within the lateral shell, core, and medial shell subdivisions of the central nucleus of the inferior colliculus. Additional afferent input originated from the ipsilateral ventral nucleus of the lateral lemniscus. No afferent input was provided to the N.Ov from the external nucleus of the inferior colliculus or the optic tectum. The N.Ov was tonotopically organized with high frequencies represented dorsally and low frequencies ventrally. Although neurons in the N.Ov responded to localization cues, there was no apparent topographic mapping of these cues within the nucleus, in contrast to the tectal pathway. However, nearly all possible types of binaural response to sound localization cues were represented. These findings suggest that in the thalamo-telencephalic auditory pathway, sound localization is subserved by a nontopographic representation of auditory space.

Maintenance of a somatotopic cortical map in the face of diminishing thalamocortical inputs

This study addresses the extent of divergence in the ascending somatosensory pathways of primates. Divergence of inputs from a particular body part at each successive synaptic step in these pathways results in a potential magnification of the representation of that body part in the somatosensory cortex, so that the representation can be expanded when peripheral input from other parts is lost, as in nerve lesions or amputations. Lesions of increasing size were placed in the representation of a finger in the ventral posterior thalamic nucleus (VPL) of macaque monkeys. After a survival period of 1–5 weeks, area 3b of the somatosensory cortex ipsilateral to the lesion was mapped physiologically, and the extent of the representation of the affected and adjacent fingers was determined. Lesions affecting less than 30% of the thalamic VPL nucleus were without effect upon the cortical representation of the finger whose thalamic representation was at the center of the lesion. Lesions affecting about 35% of the VPL nucleus resulted in a shrinkage of the cortical representation of the finger whose thalamic representation was lesioned, with concomitant expansion of the representations of adjacent fingers. Beyond 35–40%, the whole cortical representation of the hand became silent. These results suggest that divergence of brainstem and thalamocortical projections, although normally not expressed, are sufficiently great to maintain a representation after a major loss of inputs from the periphery. This is likely to be one mechanism of representational plasticity in the cerebral cortex.

Molecular Interaction Map of the Mammalian Cell Cycle Control and DNA Repair Systems

Eventually to understand the integrated function of the cell cycle regulatory network, we must organize the known interactions in the form of a diagram, map, and/or database. A diagram convention was designed capable of unambiguous representation of networks containing multiprotein complexes, protein modifications, and enzymes that are substrates of other enzymes. To facilitate linkage to a database, each molecular species is symbolically represented only once in each diagram. Molecular species can be located on the map by means of indexed grid coordinates. Each interaction is referenced to an annotation list where pertinent information and references can be found. Parts of the network are grouped into functional subsystems. The map shows how multiprotein complexes could assemble and function at gene promoter sites and at sites of DNA damage. It also portrays the richness of connections between the p53-Mdm2 subsystem and other parts of the network.

The representation of the world in national Arab news agencies: an exploration of (trans)national networks in the official Arab media

The purpose of this paper is to draw a map of the representation of the world and of Arab states as reflected by the countries of the region. To do so, we have analysed the news (4,093 news randomly collected on February and August 2005) produced by the governments of the Arab states through their national news agencies. Several regional and world maps had been constructed to show the official Arab representation of the World, the Arab countries conflict agenda, the persistence of colonial ties (with the European metropolis) and the emergence of new relationships (Asian countries). The representation of the world that appeared in the analysis focuses its interest on the USA, the war in Iraq, the Israel-Palestine conflict, the United Kingdom, France, and Iran. The Arab regional powers organise the flow of information (Saudi Arabia and Egypt) and the colonial past determines the current structure of communication (French-speaking bloc and English-speaking bloc).

Representation and learning of visual information for pose recognition

Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

AstroWeb – A Graphical Representation of an Astronomical WFPDB Database Using a Web-Based Open Source Geographical Information System

ACM Computing Classification System (1998): H.5.2, H.2.8, J.2, H.5.3.

Body representation alterations in personal but not in extrapersonal neglect patients

There is still a matter of debate around the nature of personal neglect. Is it an attention disorder or a body representation disorder? Here we investigate the presence of body representation deficits (i.e., the visuo-spatial body map) in right and left brain-damaged patients and in particular in those affected by personal neglect. 23 unilateral brain-damaged patients (5 left-brain-damaged and 18 right-brain-damaged patients) and 15 healthy controls took part in the study. The visuo-spatial body map was assessed by means of the “Frontal body-evocation subtest (FBE),” in which participants have to put tiles representing body parts on a small wooden board where only the head is depicted as a reference point. In order to compare performance on the FBE with performance on an inanimate object that had well-defined right and left sides, participants also performed the “Car test.” Group statistical analysis shows that the performance of patients with personal neglect is significantly worse than that of the controls and patients without personal neglect in the FBE but not in the Car test. Single case analyses of the five patients with pure personal neglect confirm the results of group analysis. Our data supports the hypothesis that personal neglect is a pervasive body representation disorder.

Map of North African dust emission

Changes in the emission, transport and deposition of aeolian dust have profound effects on regional climate, so that characterizing the lifecycle of dust in observations and improving the representation of dust in global climate models is necessary. A fundamental aspect of characterizing the dust cycle is quantifying surface dust fluxes, yet no spatially explicit estimates of this flux exist for the World's major source regions. Here we present a novel technique for creating a map of the annual mean emitted dust flux for North Africa based on retrievals of dust storm frequency from the Meteosat Second Generation Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the relationship between dust storm frequency and emitted mass flux derived from the output of five models that simulate dust. Our results suggest that 64 (±16)% of all dust emitted from North Africa is from the Bodélé depression, and that 13 (±3)% of the North African dust flux is from a depression lying in the lee of the Aïr and Hoggar Mountains, making this area the second most important region of emission within North Africa.

The Visual Representation of a Systematic Metaphor in a UK Media Text

Much has been written on the organizational power of metaphor in discourse, eg on metaphor ‘chains’ and ‘clusters’ of linguistic metaphor in discourse (Koller 2003, Cameron & Stelma 2004, Semino 2008) and the role of extended and systematic metaphor in organizing long stretches of language, even whole texts (Cameron et al 2009, Cameron & Maslen 2010, Deignan et al 2013, Semino et al 2013). However, at times, this work belies the intricacies of how a single metaphoric idea can impact on a text. The focus of this paper is a UK media article derived from a HM Treasury press release on alleviating poverty. The language of the article draws heavily on orientational (spatial) metaphors, particularly metaphors of movement around GOOD IS UP. Although GOOD IS UP can be considered a single metaphoric idea, the picture the reader builds up as they move line by line through this text is complex and multifaceted. I take the idea of “building up a picture” literally in order to investigate the schema of motion relating to GOOD IS UP. To do this, fifteen informants (Masters students at a London university), tutored in Cognitive Metaphor Theory, were asked to read the article and underline words and expressions they felt related to GOOD IS UP. The text was then read back to the informant with emphasis given to the words they had underlined, while they drew a pictorial representation of the article based on the meanings of these words, integrating their drawings into a single picture as they went along. I present examples of the drawings the informants produced. I propose that using Metaphor-led Discourse Analysis to produce visual material in this way offers useful insights into how metaphor contributes to meaning making at text level. It shows how a metaphoric idea, such as GOOD IS UP, provides the text producer with a rich and versatile meaning-making resource for constructing text; and gives a ‘mind-map’ of how certain aspects of a media text are decoded by the text receiver. It also offers a partial representation of the elusive, intermediate ‘deverbalized’ stage of translation (Lederer 1987), where the sense of the source text is held in the mind before it is transferred to the target language. References Cameron, L., R. Maslen, Z. Todd, J. Maule, P. Stratton & N. Stanley. 2009. ‘The discourse dynamic approach to metaphor and metaphor-led analysis’. Metaphor and Symbol, 24(2), 63-89. Cameron, L. & R. Maslen (eds). 2010. Metaphor Analysis: Research Practice in Applied Linguistics, Social Sciences and Humanities. London: Equinox. Cameron, L. & J. Stelma. 2004. ‘Metaphor Clusters in Discourse’. Journal of Applied Linguistics, 1(2), 107-136. Deignan, A., J. Littlemore & E. Semino. 2013. Figurative Language, Genre and Register. Cambridge: Cambridge University Press. Koller, V. 2003. ‘Metaphor Clusters, Metaphor Chains: Analyzing the Multifunctionality of Metaphor in Text’. metaphorik.de, 5, 115-134. Lederer, M. 1987. ‘La théorie interprétative de la traduction’ in Retour à La Traduction. Le Francais dans Le Monde. Semino, E. 2008. Metaphor in Discourse. Cambridge: Cambridge University Press. Semino, E., A. Deignan & J. Littlemore. 2013. ‘Metaphor, Genre, and Recontextualization’. Metaphor and Symbol. 28(1), 41-59.

Representation of odometry errors on occupancy grids

SOUZA, Anderson A. S. ; SANTANA, André M. ; BRITTO, Ricardo S. ; GONÇALVES, Luiz Marcos G. ; MEDEIROS, Adelardo A. D. Representation of Odometry Errors on Occupancy Grids. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.

Representation of odometry errors on occupancy grids

SOUZA, Anderson A. S. ; SANTANA, André M. ; BRITTO, Ricardo S. ; GONÇALVES, Luiz Marcos G. ; MEDEIROS, Adelardo A. D. Representation of Odometry Errors on Occupancy Grids. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.

Contributions to 3D Data Registration and Representation

Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

Self-Organizing Map Neural Architectures Based on Limit Cycle Attractors

Recent efforts to develop large-scale neural architectures have paid relatively little attention to the use of self-organizing maps (SOMs). Part of the reason is that most conventional SOMs use a static encoding representation: Each input is typically represented by the fixed activation of a single node in the map layer. This not only carries information in an inefficient and unreliable way that impedes building robust multi-SOM neural architectures, but it is also inconsistent with rhythmic oscillations in biological neural networks. Here I develop and study an alternative encoding scheme that instead uses limit cycle attractors of multi-focal activity patterns to represent input patterns/sequences. Such a fundamental change in representation raises several questions: Can this be done effectively and reliably? If so, will map formation still occur? What properties would limit cycle SOMs exhibit? Could multiple such SOMs interact effectively? Could robust architectures based on such SOMs be built for practical applications? The principal results of examining these questions are as follows. First, conditions are established for limit cycle attractors to emerge in a SOM through self-organization when encoding both static and temporal sequence inputs. It is found that under appropriate conditions a set of learned limit cycles are stable, unique, and preserve input relationships. In spite of the continually changing activity in a limit cycle SOM, map formation continues to occur reliably. Next, associations between limit cycles in different SOMs are learned. It is shown that limit cycles in one SOM can be successfully retrieved by another SOM’s limit cycle activity. Control timings can be set quite arbitrarily during both training and activation. Importantly, the learned associations generalize to new inputs that have never been seen during training. Finally, a complete neural architecture based on multiple limit cycle SOMs is presented for robotic arm control. This architecture combines open-loop and closed-loop methods to achieve high accuracy and fast movements through smooth trajectories. The architecture is robust in that disrupting or damaging the system in a variety of ways does not completely destroy the system. I conclude that limit cycle SOMs have great potentials for use in constructing robust neural architectures.

Aspects of a noncommutative scalar/tensor duality

We study the noncommutative massless Kalb-Ramond gauge field coupled to a dynamical U(1) gauge field in the adjoint representation together with a compensating vector field. We derive the Seiberg-Witten map and obtain the corresponding mapped action to first order in theta. The (emergent) gravity structure found in other situations is not present here. The off-shell dual scalar theory is derived and it does not coincide with the Seiberg-Witten mapped scalar theory. Dispersion relations are also discussed. The p-form generalization of the Seiberg-Witten map to order theta is also derived.

Low dimensional behavior in three-dimensional coupled map lattices

The analysis of one-, two-, and three-dimensional coupled map lattices is here developed under a statistical and dynamical perspective. We show that the three-dimensional CML exhibits low dimensional behavior with long range correlation and the power spectrum follows 1/f noise. This approach leads to an integrated understanding of the most important properties of these universal models of spatiotemporal chaos. We perform a complete time series analysis of the model and investigate the dependence of the signal properties by change of dimension. (c) 2008 Elsevier Ltd. All rights reserved.