Visual Cortex

The neurosciences have experienced tremendous and wonderful progress in many areas, and the spectrum encompassing the neurosciences is expansive. Suffice it to mention a few classical fields: electrophysiology, genetics, physics, computer sciences, and more recently, social and marketing neurosciences. Of course, this large growth resulted in the production of many books. Perhaps the visual system and the visual cortex were in the vanguard because most animals do not produce their own light and offer thus the invaluable advantage of allowing investigators to conduct experiments in full control of the stimulus. In addition, the fascinating evolution of scientific techniques, the immense productivity of recent research, and the ensuing literature make it virtually impossible to publish in a single volume all worthwhile work accomplished throughout the scientific world. The days when a single individual, as Diderot, could undertake the production of an encyclopedia are gone forever. Indeed most approaches to studying the nervous system are valid and neuroscientists produce an almost astronomical number of interesting data accompanied by extremely worthy hypotheses which in turn generate new ventures in search of brain functions. Yet, it is fully justified to make an encore and to publish a book dedicated to visual cortex and beyond. Many reasons validate a book assembling chapters written by active researchers. Each has the opportunity to bind together data and explore original ideas whose fate will not fall into the hands of uncompromising reviewers of traditional journals. This book focuses on the cerebral cortex with a large emphasis on vision. Yet it offers the reader diverse approaches employed to investigate the brain, for instance, computer simulation, cellular responses, or rivalry between various targets and goal directed actions. This volume thus covers a large spectrum of research even though it is impossible to include all topics in the extremely diverse field of neurosciences

Optics in Self-Assembled Metamaterials

How does an object scatter or absorb electromagnetic radiation? A very elegant analytic solution can be found for a single sphere with the Mie coefficients. In this thesis, an approach is used that is very similar. The amplitudes of the incident and scattered fields are connected by the T-matrix. We present a method to obtain the T-matrix of arbitrary objects. Furthermore, an extension is shown, where the scattering from several of such objects forming a cluster can be calculated

Neural Correlates of Conscious Perception. The Role of Primary Visual Cortex in Visual Awareness.

This study investigates which neural populations represent low-level dimensions of conscious perception. First, a general framework is presented that will allow the separation of different aspects of visual awareness. A set of six criteria is developed that allows one to assess whether a neural population could in principle represent a dimension of conscious perception. These criteria are then applied to previous studies on the neurophysiology and neuropsychology of conscious perception. In the following empirical section a study on the relationship between perceived contrast and activity in primary visual cortex is performed using a combination of EEG, MEG and psychophysics. Lateral masking was used to dissociate the physical and the perceived contrast of a target grating. Transient potentials and magnetic fields evoked by the flashed target gratings were recorded and compared to psychophysical judgements of perceived contrast. At all investigated contrast levels, the amplitudes of electrophysiological transients correlated better with perceived than with physical target contrast. This held especially for the late transient. Source localisation indicated that the transients in question are likely to originate in primary visual cortex. The study presented here is the first ever to study perceptual constancy by recording psychophysics and physiological responses synchronously. The results identify the activity of primary visual cortex as the most likely neural basis of perceived contrast

Interactive molecular docking with haptics and advanced graphics

Biomolecular interactions underpin many of the processes that make up life. Molecular docking is the study of these interactions in silico. Interactive docking applications put the user in control of the docking process, allowing them to use their knowledge and intuition to determine how molecules bind together. Interactive molecular docking applications often use haptic devices as a method of controlling the docking process. These devices allow the user to easily manipulate the structures in 3D space, whilst feeling the forces that occur in response to their manipulations. As a result of the force refresh rate requirements of haptic devices, haptic assisted docking applications are often limited, in that they model the interacting proteins as rigid, use low fidelity visualisations or require expensive propriety equipment to use. The research in this thesis aims to address some of these limitations. Firstly, the development of a visualisation algorithm capable of rendering a depiction of a deforming protein at an interactive refresh rate, with per-pixel shadows and ambient occlusion, is discussed. Then, a novel approach to modelling molecular flexibility whilst maintaining a stable haptic refresh rate is developed. Together these algorithms are presented within Haptimol FlexiDock, the first haptic-assisted molecular docking application to support receptor flexibility with high fidelity graphics, whilst also maintaining interactive refresh rates on both the haptic device and visual display. Using Haptimol FlexiDock, docking experiments were performed between two protein-ligand pairs: Maltodextrin Binding Protein and Maltose, and glutamine Binding Protein and Glucose. When the ligand was placed in its approximate binding site, the direction of over 80% of the intra-molecular movement aligned with that seen in the experimental structures. Furthermore, over 50% of the expected backbone motion was present in the structures generated with FlexiDock. Calculating the deformation of a biomolecule in real time, whilst maintaining an interactive refresh rate on the haptic device (> 500Hz) is a breakthrough in the field of interactive molecular docking, as, previous approaches either model protein flexibility, but fail to achieve the required haptic refresh rate, or do not consider biomolecular flexibility at all

Visual recognition of objects : behavioral, computational, and neurobiological aspects

I surveyed work on visual object recognition and perception. In animals, vision has been studied mainly on the behavioral and neurobiological levels. Behavioral data typically show what the visual system, by itself or together with the rest of the organism, is capable of. They show, for example, that humans can recognie objects regardless of size and position, but that rotated objects pose problems. Important insights into the organization of behavior have also been provided by people who suffered localized brain damage. We have learned that the brain is divided into areas subserving different and relatively well-defined behaviors. The visual system itself is also organized in different subsystems; the visual cortex alone contains nearly twenty maps of the visual field. And individual neurons respond selectively to visual stimuli, e.g., the orientation of line segments, color, direction of motion, and, most intriguingly, faces. The question is how the actions of all these neurons produce the behavior we observe. How do neurons represent the shape of objects such that they can be recognized? Before we can answer the question, we have to understand the computational aspect of shape representation, the nature of the problem as it were. Many methods for representing shape have been explored, mainly by computer scientists, but so far no satisfactory answers have been found

Three-Dimensional Interactive Connection Diagrams for Knowledge Engineering

This thesis describes research into human factors aspects of the use of 3-dimensional node and link diagrams, called Interactive Connection Diagrams (leDs), in the human-computer interface of tools for knowledge engineering. This research was carried out in two main stages: the first concentrated on perceptual aspects of 3-d ICDs, and the second on more general aspects of their use in realistic situations. A final section looked briefly at the possibility of formally specifying 3-d ICD representations. The main aim of the first stage was to investigate whether users were able to make effective judgements about the relative depths of components in 3-d ICDs. Controlled experiments were carried out to determine the extent to which such judgements were supported by the use of a particular approach to creating the illusion of depth. The results of these experiments showed that users were able to make reasonably effective judgements about the relative depths of components in 3-d ICDs. 3-d ICDs produced using the approach of interest were therefore argued to be suitable for use in the second stage of the study. In the second stage, case studies were used to investigate the utility in more realistic knowledge engineering situations of tools supporting 3-d ICDs, and the usability of depth-related features of a prototype tool which permits 3-d leDs to be viewed and edited. On the basis of the findings of these studies it is claimed that tools supporting 3-d ICDs will, in some situations, be more useful than those which employ only more conventional 2-d versions. It was found that depth-related features of the prototype tool were usable but should be improved upon in future implementations. The third and final section of work involved a preliminary investigation into the formal specification of the 3-d ICD representations of the kind used in the second set of studies. A scheme for specifying the range of 3-d leO languages currently supported by the prototype tool was developed, and each of the particular 3-d ICD languages used in the case studies were specified. Implications of the results of this work are discussed and a number of suggestions regarding directions for future work are made. The overall conclusion is that 3-d ICDs have considerable potential as a medium in which to represent knowledge structures for use in knowledge engineering

Applied Visualization in the Neurosciences and the Enhancement of Visualization through Computer Graphics

The complexity and size of measured and simulated data in many fields of science is increasing constantly. The technical evolution allows for capturing smaller features and more complex structures in the data. To make this data accessible by the scientists, efficient and specialized visualization techniques are required. Maximum efficiency and value for the user can only be achieved by adapting visualization to the specific application area and the specific requirements of the scientific field. Part I: In the first part of my work, I address the visualization in the neurosciences. The neuroscience tries to understand the human brain; beginning at its smallest parts, up to its global infrastructure. To achieve this ambitious goal, the neuroscience uses a combination of three-dimensional data from a myriad of sources, like MRI, CT, or functional MRI. To handle this diversity of different data types and sources, the neuroscience need specialized and well evaluated visualization techniques. As a start, I will introduce an extensive software called \"OpenWalnut\". It forms the common base for developing and using visualization techniques with our neuroscientific collaborators. Using OpenWalnut, standard and novel visualization approaches are available to the neuroscientific researchers too. Afterwards, I am introducing a very specialized method to illustrate the causal relation of brain areas, which was, prior to that, only representable via abstract graph models. I will finalize the first part of my work with an evaluation of several standard visualization techniques in the context of simulated electrical fields in the brain. The goal of this evaluation was clarify the advantages and disadvantages of the used visualization techniques to the neuroscientific community. We exemplified these, using clinically relevant scenarios. Part II: Besides the data preprocessing, which plays a tremendous role in visualization, the final graphical representation of the data is essential to understand structure and features in the data. The graphical representation of data can be seen as the interface between the data and the human mind. The second part of my work is focused on the improvement of structural and spatial perception of visualization -- the improvement of the interface. Unfortunately, visual improvements using computer graphics methods of the computer game industry is often seen sceptically. In the second part, I will show that such methods can be applied to existing visualization techniques to improve spatiality and to emphasize structural details in the data. I will use a computer graphics paradigm called \"screen space rendering\". Its advantage, amongst others, is its seamless applicability to nearly every visualization technique. I will start with two methods that improve the perception of mesh-like structures on arbitrary surfaces. Those mesh structures represent second-order tensors and are generated by a method named \"TensorMesh\". Afterwards I show a novel approach to optimally shade line and point data renderings. With this technique it is possible for the first time to emphasize local details and global, spatial relations in dense line and point data.In vielen Bereichen der Wissenschaft nimmt die Größe und Komplexität von gemessenen und simulierten Daten zu. Die technische Entwicklung erlaubt das Erfassen immer kleinerer Strukturen und komplexerer Sachverhalte. Um solche Daten dem Menschen zugänglich zu machen, benötigt man effiziente und spezialisierte Visualisierungswerkzeuge. Nur die Anpassung der Visualisierung auf ein Anwendungsgebiet und dessen Anforderungen erlaubt maximale Effizienz und Nutzen für den Anwender. Teil I: Im ersten Teil meiner Arbeit befasse ich mich mit der Visualisierung im Bereich der Neurowissenschaften. Ihr Ziel ist es, das menschliche Gehirn zu begreifen; von seinen kleinsten Teilen bis hin zu seiner Gesamtstruktur. Um dieses ehrgeizige Ziel zu erreichen nutzt die Neurowissenschaft vor allem kombinierte, dreidimensionale Daten aus vielzähligen Quellen, wie MRT, CT oder funktionalem MRT. Um mit dieser Vielfalt umgehen zu können, benötigt man in der Neurowissenschaft vor allem spezialisierte und evaluierte Visualisierungsmethoden. Zunächst stelle ich ein umfangreiches Softwareprojekt namens \"OpenWalnut\" vor. Es bildet die gemeinsame Basis für die Entwicklung und Nutzung von Visualisierungstechniken mit unseren neurowissenschaftlichen Kollaborationspartnern. Auf dieser Basis sind klassische und neu entwickelte Visualisierungen auch für Neurowissenschaftler zugänglich. Anschließend stelle ich ein spezialisiertes Visualisierungsverfahren vor, welches es ermöglicht, den kausalen Zusammenhang zwischen Gehirnarealen zu illustrieren. Das war vorher nur durch abstrakte Graphenmodelle möglich. Den ersten Teil der Arbeit schließe ich mit einer Evaluation verschiedener Standardmethoden unter dem Blickwinkel simulierter elektrischer Felder im Gehirn ab. Das Ziel dieser Evaluation war es, der neurowissenschaftlichen Gemeinde die Vor- und Nachteile bestimmter Techniken zu verdeutlichen und anhand klinisch relevanter Fälle zu erläutern. Teil II: Neben der eigentlichen Datenvorverarbeitung, welche in der Visualisierung eine enorme Rolle spielt, ist die grafische Darstellung essenziell für das Verständnis der Strukturen und Bestandteile in den Daten. Die grafische Repräsentation von Daten bildet die Schnittstelle zum Gehirn des Menschen. Der zweite Teile meiner Arbeit befasst sich mit der Verbesserung der strukturellen und räumlichen Wahrnehmung in Visualisierungsverfahren -- mit der Verbesserung der Schnittstelle. Leider werden viele visuelle Verbesserungen durch Computergrafikmethoden der Spieleindustrie mit Argwohn beäugt. Im zweiten Teil meiner Arbeit werde ich zeigen, dass solche Methoden in der Visualisierung angewendet werden können um den räumlichen Eindruck zu verbessern und Strukturen in den Daten hervorzuheben. Dazu nutze ich ein in der Computergrafik bekanntes Paradigma: das \"Screen Space Rendering\". Dieses Paradigma hat den Vorteil, dass es auf nahezu jede existierende Visualiserungsmethode als Nachbearbeitunsgschritt angewendet werden kann. Zunächst führe ich zwei Methoden ein, die die Wahrnehmung von gitterartigen Strukturen auf beliebigen Oberflächen verbessern. Diese Gitter repräsentieren die Struktur von Tensoren zweiter Ordnung und wurden durch eine Methode namens \"TensorMesh\" erzeugt. Anschließend zeige ich eine neuartige Technik für die optimale Schattierung von Linien und Punktdaten. Mit dieser Technik ist es erstmals möglich sowohl lokale Details als auch globale räumliche Zusammenhänge in dichten Linien- und Punktdaten zu erfassen