Effectiveness of Vision Therapy as an Adjunct to Occupational Therapy in Improving Visual Motor Skills in Learning Disabled Children

INTRODUCTION: “Learning disability is defined as a disorder in one of the more basic psychological process involved in understanding or in using language, spoken or written, which may manifest itself in an imperfect ability to listen, think, speak, read, write or do mathematical calculation - from public law 94 – 142, the Education for All handicapped Children Act. Learning disability constitutes a diverse group of disorders in which children who generally posses at-least average intelligence have problems processing information or generating output. OBJECTIVE: The purpose of the study is to determine the effectiveness of occupational therapy in improving Visual Motor skills along with vision therapy in children with learning disability. METHOD: In this study a total of 30 children from the age group of 7 to 10 years participated, and were divided into 15 each in experimental and control group. The control group received only Occupational Therapy where as the experimental group received both Occupational Therapy and Vision Therapy. The Visual Motor Integration scale was used as the outcome measure for both the groups at the start of intervention and later after 3 months intervention. The data’s were recorded and analyzed for statistical analysis. RESULTS: Statistical significance is present in experimental group than control group with regard to effect of vision therapy activities with occupational therapy intervention. The data analyzed, the pretest score of control group 12.33 and post test score being 13.07, where as in experimental group the pretest score 12.53 and post test score 15.40.The paired ‘t’ test for experimental group is p < 0.01. CONCLUSION: The findings of study suggest, “Vision therapy when given along with Occupational Therapy has significant effect on improving Visuo Motor integration skills” in children with learning disability

Bimanual grasp planning reflects changing rather than fixed constraint dominance

We studied whether motor-control constraints for grasping objects that are moved to new positions reflect a rigid constraint hierarchy or a flexible constraint hierarchy. In two experiments, we asked participants to move two plungers from the same start locations to different target locations (both high, both low, or one high and one low). We found that participants grasped the plungers symmetrically and at heights that ensured comfortable or easy-to-control end postures when the plungers had the same target heights, but these grasp tendencies were reduced when the plungers had different target heights. In addition, when the plungers had different mass distributions, participants behaved in ways that suggested still-different emphases of the relevant grasp constraints. When the plungers had different mass distributions, participants sacrificed bimanual symmetry for end-state comfort. The results suggest that bimanual grasp planning relies on a flexible rather than static hierarchy. Different constraints take on different degrees of importance depending on the nature of the task and on the level of task experience. The results have implications for the understanding of perceptual-motor skill learning. It may be that one mechanism underlying such learning is changing the priorities of task constraints

Factors of Micromanipulation Accuracy and Learning

Micromanipulation refers to the manipulation under a microscope in order to perform delicate procedures. It is difficult for humans to manipulate objects accurately under a microscope due to tremor and imperfect perception, limiting performance. This project seeks to understand factors affecting accuracy in micromanipulation, and to propose strategies for learning improving accuracy. Psychomotor experiments were conducted using computer-controlled setups to determine how various feedback modalities and learning methods can influence micromanipulation performance. In a first experiment, static and motion accuracy of surgeons, medical students and non-medical students under different magniification levels and grip force settings were compared. A second experiment investigated whether the non-dominant hand placed close to the target can contribute to accurate pointing of the dominant hand. A third experiment tested a training strategy for micromanipulation using unstable dynamics to magnify motion error, a strategy shown to be decreasing deviation in large arm movements. Two virtual reality (VR) modules were then developed to train needle grasping and needle insertion tasks, two primitive tasks in a microsurgery suturing procedure. The modules provided the trainee with a visual display in stereoscopic view and information on their grip, tool position and angles. Using the VR module, a study examining effects of visual cues was conducted to train tool orientation. Results from these studies suggested that it is possible to learn and improve accuracy in micromanipulation using appropriate sensorimotor feedback and training

Illusions of visual orientation: comparisons between perceptual and visuo-motor tasks

The Milner and Goodale (1995) model of dual cortical visual systems suggests that, in the primate cortex, separate neural substrates dominate the tasks of visual perception and visuo-motor control. This model derives from a number of independent sources of evidence: anatomical, physiological and behavioural. Neuropsychological evidence in humans suggests that visual perception and visuo-motor control can be selectively impaired through damage to the ventral and dorsal visual streams respectively. Evidence has emerged that in the healthy human visual cortex, differentiable effects of visual illusions can be found between the two measures of perception and visuo- motor control. This evidence has been cited to support the Milner and Goodale (1995) model. The series of studies reported in this dissertation used a similar, but methodologically revised application of the illusion paradigm in the novel domain of orientation. Using two types of visual illusions, the simultaneous tilt illusion (STI) and the rod-and-frame illusion (RFI), a series of studies found patterns of association, dissociation and interaction that strongly support the Mihier and Goodale model. The critical issue, in terms of predicting the pattern of effects across perception and visuo-motor control tasks, was found to be the siting of the causal mechanisms underlying the illusion employed

How Do Gestures Influence Thinking and Speaking? The Gesture-for-Conceptualization Hypothesis.

Peer reviewedPostprin

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Neural Representations for Sensory-Motor Control, II: Learning a Head-Centered Visuomotor Representation of 3-D Target Position

A neural network model is described for how an invariant head-centered representation of 3-D target position can be autonomously learned by the brain in real time. Once learned, such a target representation may be used to control both eye and limb movements. The target representation is derived from the positions of both eyes in the head, and the locations which the target activates on the retinas of both eyes. A Vector Associative Map, or YAM, learns the many-to-one transformation from multiple combinations of eye-and-retinal position to invariant 3-D target position. Eye position is derived from outflow movement signals to the eye muscles. Two successive stages of opponent processing convert these corollary discharges into a. head-centered representation that closely approximates the azimuth, elevation, and vergence of the eyes' gaze position with respect to a cyclopean origin located between the eyes. YAM learning combines this cyclopean representation of present gaze position with binocular retinal information about target position into an invariant representation of 3-D target position with respect to the head. YAM learning can use a teaching vector that is externally derived from the positions of the eyes when they foveate the target. A YAM can also autonomously discover and learn the invariant representation, without an explicit teacher, by generating internal error signals from environmental fluctuations in which these invariant properties are implicit. YAM error signals are computed by Difference Vectors, or DVs, that are zeroed by the YAM learning process. YAMs may be organized into YAM Cascades for learning and performing both sensory-to-spatial maps and spatial-to-motor maps. These multiple uses clarify why DV-type properties are computed by cells in the parietal, frontal, and motor cortices of many mammals. YAMs are modulated by gating signals that express different aspects of the will-to-act. These signals transform a single invariant representation into movements of different speed (GO signal) and size (GRO signal), and thereby enable YAM controllers to match a planned action sequence to variable environmental conditions.National Science Foundation (IRI-87-16960, IRI-90-24877); Office of Naval Research (N00014-92-J-1309