A brief review of magnetic fields from the human visual system

Both the eye and brain generate magnetic fields when stimulated with a variety of visual cues. These magnetic fields can be measured with a magnetometer; a device which uses superconducting technology. The application of this technique to measuring the magnetooculogram, magnetoretinogram and visually evoked fields from the brain is described. So far the main use of this technique has been in pure research. Its potential for diagnosing ocular and neurological diseases is discussed.

The human immune system: Part 1

The immune system protects the human body against infectious and maligant disease. The concept of an immune system arose because of the observation that an attack of measles or mumps, two common childhood diseases, conferred an immunity on the individual, the immunity being specific to the disease. It was only much later that it was discovered that a system in the body conferred this immunity.

The human immune system Part 2: auto-immune disorders

For the immune system to function effectively, the body must be able to distinguish foreign antigens from self-antigens. However, the mechanisms which maintain this distinction may break down and result in auto-immune disease in which self-reacting antibodies and T-cells are produced. This article discusses first, the evidence for the existence of human auto-immune disease and second, the auto-immune diseases which have characteristic ocular symptoms.

The human immune system: Part 1

The immune system protects the human body against infectious and malignant disease. The concept of an immune system arose because of the observation that an attack of measles or mumps, two common childhood disease, conferred an immunity on the individual, the immunity being specific to the disease. It was only much later that it was discovered that a system in the body conferred this immunity. This article discusses the various components of the immune system, how they develop and their action in conferring immunity.

The human immune system: Part 2

For the immune system to function effectively, the body must be able to distinguish foreign antigens from self antigens. However, the mechanisms which maintain this distinction may break down and result in an auto-immune disease in which self-reacting antibodies and T-cells are produced. This article discusses first, the evidence for the existence of human auto-immune disease and second, the auto-immune diseases which have characteristic ocular symptoms.

Development and application of magnetoencephalographic methods in the investigation of the human visual system

This thesis is an exploration of the organisation and functioning of the human visual system using the non-invasive functional imaging modality magnetoencephalography (MEG). Chapters one and two provide an introduction to the ‘human visual system and magnetoencephalographic methodologies. These chapters subsequently describe the methods by which MEG can be used to measure neuronal activity from the visual cortex. Chapter three describes the development and implementation of novel analytical tools; including beamforming based analyses, spectrographic movies and an optimisation of group imaging methods. Chapter four focuses on the use of established and contemporary analytical tools in the investigation of visual function. This is initiated with an investigation of visually evoked and induced responses; covering visual evoked potentials (VEPs) and event related synchronisation/desynchronisation (ERS/ERD). Chapter five describes the employment of novel methods in the investigation of cortical contrast response and demonstrates distinct contrast response functions in striate and extra-striate regions of visual cortex. Chapter six use synthetic aperture magnetometry (SAM) to investigate the phenomena of visual cortical gamma oscillations in response to various visual stimuli; concluding that pattern is central to its generation and that it increases in amplitude linearly as a function of stimulus contrast, consistent with results from invasive electrode studies in the macaque monkey. Chapter seven describes the use of driven visual stimuli and tuned SAM methods in a pilot study of retinotopic mapping using MEG; finding that activity in the primary visual cortex can be distinguished in four quadrants and two eccentricities of the visual field. Chapter eight is a novel implementation of the SAM beamforming method in the investigation of a subject with migraine visual aura; the method reveals desynchronisation of the alpha and gamma frequency bands in occipital and temporal regions contralateral to observed visual abnormalities. The final chapter is a summary of main conclusions and suggested further work.

From detection of complex motion to descriptions of moving surfaces in human vision

A preliminary study by Freeman et al (1996b) has suggested that when complex patterns of motion elicit impressions of 2-dimensionality, odd-item-out detection improves given targets can be differentiated on the basis of surface properties. Their results can be accounted for, it if is supposed that observers are permitted efficient access to 3-D surface descriptions but access to 2-D motion descriptions is restricted. To test the hypothesis, a standard search technique was employed, in which targets could be discussed on the basis of slant sign. In one experiment, slant impressions were induced through the summing of deformation and translation components. In a second theory were induced through the summing of shear and translation components. Neither showed any evidence of efficient access. A third experiment explored the possibility that access to these representations may have been hindered by a lack of grouping between the stimuli. Attempts to improve grouping failed to produce convincing evidence in support of life. An alternative explanation is that complex patterns of motion are simply not processed simultaneously. Psychophysical and physiological studies have, however, suggested that multiple mechanisms selective for complex motion do exist. Using a subthreshold summation technique I found evidence supporting the notion that complex motions are processed in parallel. Furthermore, in a spatial summation experiment, coherence thresholds were measured for displays containing different numbers of complex motion patches. Consistent with the idea that complex motion processing proceeds in parallel, increases in the number of motion patches were seen to decrease thresholds, both for expansion and rotation. Moreover, the rates of decrease were higher than those typically expected from probability summation, thus implying mechanisms are available, which can pool signals from spatially distinct complex motion flows.

Statistical guidelines for clinical studies of human vision

Citation information: Armstrong RA, Davies LN, Dunne MCM & Gilmartin B. Statistical guidelines for clinical studies of human vision. Ophthalmic Physiol Opt 2011, 31, 123-136. doi: 10.1111/j.1475-1313.2010.00815.x ABSTRACT: Statistical analysis of data can be complex and different statisticians may disagree as to the correct approach leading to conflict between authors, editors, and reviewers. The objective of this article is to provide some statistical advice for contributors to optometric and ophthalmic journals, to provide advice specifically relevant to clinical studies of human vision, and to recommend statistical analyses that could be used in a variety of circumstances. In submitting an article, in which quantitative data are reported, authors should describe clearly the statistical procedures that they have used and to justify each stage of the analysis. This is especially important if more complex or 'non-standard' analyses have been carried out. The article begins with some general comments relating to data analysis concerning sample size and 'power', hypothesis testing, parametric and non-parametric variables, 'bootstrap methods', one and two-tail testing, and the Bonferroni correction. More specific advice is then given with reference to particular statistical procedures that can be used on a variety of types of data. Where relevant, examples of correct statistical practice are given with reference to recently published articles in the optometric and ophthalmic literature.

Low level feature detection in human vision

Influential models of edge detection have generally supposed that an edge is detected at peaks in the 1st derivative of the luminance profile, or at zero-crossings in the 2nd derivative. However, when presented with blurred triangle-wave images, observers consistently marked edges not at these locations, but at peaks in the 3rd derivative. This new phenomenon, termed ‘Mach edges’ persisted when a luminance ramp was added to the blurred triangle-wave. Modelling of these Mach edge detection data required the addition of a physiologically plausible filter, prior to the 3rd derivative computation. A viable alternative model was examined, on the basis of data obtained with short-duration, high spatial-frequency stimuli. Detection and feature-making methods were used to examine the perception of Mach bands in an image set that spanned a range of Mach band detectabilities. A scale-space model that computed edge and bar features in parallel provided a better fit to the data than 4 competing models that combined information across scale in a different manner, or computed edge or bar features at a single scale. The perception of luminance bars was examined in 2 experiments. Data for one image-set suggested a simple rule for perception of a small Gaussian bar on a larger inverted Gaussian bar background. In previous research, discriminability (d’) has typically been reported to be a power function of contrast, where the exponent (p) is 2 to 3. However, using bar, grating, and Gaussian edge stimuli, with several methodologies, values of p were obtained that ranged from 1 to 1.7 across 6 experiments. This novel finding was explained by appealing to low stimulus uncertainty, or a near-linear transducer.

Modelling the human accommodation system using finite element analysis

The human accommodation system has been extensively examined for over a century, with a particular focus on trying to understand the mechanisms that lead to the loss of accommodative ability with age (Presbyopia). The accommodative process, along with the potential causes of presbyopia, are disputed; hindering efforts to develop methods of restoring accommodation in the presbyopic eye. One method that can be used to provide insight into this complex area is Finite Element Analysis (FEA). The effectiveness of FEA in modelling the accommodative process has been illustrated by a number of accommodative FEA models developed to date. However, there have been limitations to these previous models; principally due to the variation in data on the geometry of the accommodative components, combined with sparse measurements of their material properties. Despite advances in available data, continued oversimplification has occurred in the modelling of the crystalline lens structure and the zonular fibres that surround the lens. A new accommodation model was proposed by the author that aims to eliminate these limitations. A novel representation of the zonular structure was developed, combined with updated lens and capsule modelling methods. The model has been designed to be adaptable so that a range of different age accommodation systems can be modelled, allowing the age related changes that occur to be simulated. The new modelling methods were validated by comparing the changes induced within the model to available in vivo data, leading to the definition of three different age models. These were used in an extended sensitivity study on age related changes, where individual parameters were altered to investigate their effect on the accommodative process. The material properties were found to have the largest impact on the decline in accommodative ability, in particular compared to changes in ciliary body movement or zonular structure. Novel data on the importance of the capsule stiffness and thickness was also established. The new model detailed within this thesis provides further insight into the accommodation mechanism, as well as a foundation for future, more detailed investigations into accommodation, presbyopia and accommodative restoration techniques.

Grid-texture mechanisms in human vision:contrast detection of regular sparse micro-patterns requires specialist templates

Previous work has shown that human vision performs spatial integration of luminance contrast energy, where signals are squared and summed (with internal noise) over area at detection threshold. We tested that model here in an experiment using arrays of micro-pattern textures that varied in overall stimulus area and sparseness of their target elements, where the contrast of each element was normalised for sensitivity across the visual field. We found a power-law improvement in performance with stimulus area, and a decrease in sensitivity with sparseness. While the contrast integrator model performed well when target elements constituted 50–100% of the target area (replicating previous results), observers outperformed the model when texture elements were sparser than this. This result required the inclusion of further templates in our model, selective for grids of various regular texture densities. By assuming a MAX operation across these noisy mechanisms the model also accounted for the increase in the slope of the psychometric function that occurred as texture density decreased. Thus, for the first time, mechanisms that are selective for texture density have been revealed at contrast detection threshold. We suggest that these mechanisms have a role to play in the perception of visual textures.

Binocular contrast vision at and above threshold

A fundamental problem for any visual system with binocular overlap is the combination of information from the two eyes. Electrophysiology shows that binocular integration of luminance contrast occurs early in visual cortex, but a specific systems architecture has not been established for human vision. Here, we address this by performing binocular summation and monocular, binocular, and dichoptic masking experiments for horizontal 1 cycle per degree test and masking gratings. These data reject three previously published proposals, each of which predict too little binocular summation and insufficient dichoptic facilitation. However, a simple development of one of the rejected models (the twin summation model) and a completely new model (the two-stage model) provide very good fits to the data. Two features common to both models are gently accelerating (almost linear) contrast transduction prior to binocular summation and suppressive ocular interactions that contribute to contrast gain control. With all model parameters fixed, both models correctly predict (1) systematic variation in psychometric slopes, (2) dichoptic contrast matching, and (3) high levels of binocular summation for various levels of binocular pedestal contrast. A review of evidence from elsewhere leads us to favor the two-stage model. © 2006 ARVO.

What is second-order vision for? Discriminating illumination versus material changes

The human visual system is sensitive to second-order modulations of the local contrast (CM) or amplitude (AM) of a carrier signal. Second-order cues are detected independently of first-order luminance signals; however, it is not clear why vision should benet from second-order sensitivity. Analysis of the first-and second-order contents of natural images suggests that these cues tend to occur together, but their phase relationship varies. We have shown that in-phase combinations of LM and AM are perceived as a shaded corrugated surface whereas the anti-phase combination can be seen as corrugated when presented alone or as a flat material change when presented in a plaid containing the in-phase cue. We now extend these findings using new stimulus types and a novel haptic matching task. We also introduce a computational model based on initially separate first-and second-order channels that are combined within orientation and subsequently across orientation to produce a shading signal. Contrast gain control allows the LM + AM cue to suppress responses to the LM-AM when presented in a plaid. Thus, the model sees LM -AM as flat in these circumstances. We conclude that second-order vision plays a key role in disambiguating the origin of luminance changes within an image. © ARVO.

The vision strategy of golf putting

Golfers, coaches and researchers alike, have all keyed in on golf putting as an important aspect of overall golf performance. Of the three principle putting tasks (green reading, alignment and the putting action phase), the putting action phase has attracted the most attention from coaches, players and researchers alike. This phase includes the alignment of the club with the ball, the swing, and ball contact. A significant amount of research in this area has focused on measuring golfer’s vision strategies with eye tracking equipment. Unfortunately this research suffers from a number of shortcomings, which limit its usefulness. The purpose of this thesis was to address some of these shortcomings. The primary objective of this thesis was to re-evaluate golfer’s putting vision strategies using binocular eye tracking equipment and to define a new, optimal putting vision strategy which was associated with both higher skill and success. In order to facilitate this research, bespoke computer software was developed and validated, and new gaze behaviour criteria were defined. Additionally, the effects of training (habitual) and competition conditions on the putting vision strategy were examined, as was the effect of ocular dominance. Finally, methods for improving golfer’s binocular vision strategies are discussed, and a clinical plan for the optometric management of the golfer’s vision is presented. The clinical management plan includes the correction of fundamental aspects of golfers’ vision, including monocular refractive errors and binocular vision defects, as well as enhancement of their putting vision strategy, with the overall aim of improving performance on the golf course. This research has been undertaken in order to gain a better understanding of the human visual system and how it relates to the sport performance of golfers specifically. Ultimately, the analysis techniques and methods developed are applicable to the assessment of visual performance in all sports.

Natural images dominate in binocular rivalry

Ecological approaches to perception have demonstrated that information encoding by the visual system is informed by the natural environment, both in terms of simple image attributes like luminance and contrast, and more complex relationships corresponding to Gestalt principles of perceptual organization. Here, we ask if this optimization biases perception of visual inputs that are perceptually bistable. Using the binocular rivalry paradigm, we designed stimuli that varied in either their spatiotemporal amplitude spectra or their phase spectra. We found that noise stimuli with “natural” amplitude spectra (i.e., amplitude content proportional to 1/f, where f is spatial or temporal frequency) dominate over those with any other systematic spectral slope, along both spatial and temporal dimensions. This could not be explained by perceived contrast measurements, and occurred even though all stimuli had equal energy. Calculating the effective contrast following attenuation by a model contrast sensitivity function suggested that the strong contrast dependency of rivalry provides the mechanism by which binocular vision is optimized for viewing natural images. We also compared rivalry between natural and phase-scrambled images and found a strong preference for natural phase spectra that could not be accounted for by observer biases in a control task. We propose that this phase specificity relates to contour information, and arises either from the activity of V1 complex cells, or from later visual areas, consistent with recent neuroimaging and single-cell work. Our findings demonstrate that human vision integrates information across space, time, and phase to select the input most likely to hold behavioral relevance.