Pulfrich's phenomenon in unilateral cataract

AIMS—To determine whether unilateral cataract causes a pathological Pulfrich's phenomenon.
METHODS—29 subjects with unilateral cataract and contralateral pseudophakia were assessed on their ability to perceive the Pulfrich phenomenon. Using a computer generated pendulum image, and graded neutral density filters, a series of forced choice trials were performed in which the subject was required to describe the direction of any apparent pendulum rotation. A pathological Pulfrich effect was said to occur when apparent rotation was perceived in the presence of a zero strength neutral density filter. The size of any pathological Pulfrich effect which was present was quantified by neutralising the perceived pendulum rotation with neutral density filters of varying strength placed before the better seeing eye.
RESULTS—20 out of 29 subjects were able to perceive apparent pendulum rotation when uniocular filtering was performed. In the group (n=12) which was tested both before and after cataract extraction with intraocular lens implantation, a statistically significant pathological Pulfrich effect was demonstrated preoperatively, compared with a group of normal control subjects. This effect was abolished after cataract extraction (p=0.009). The median size of the effect was equivalent to a 0.25 log unit neutral density filter over the non-cataractous eye. The subjects who were unable to perceive the Pulfrich phenomenon at all had a significantly greater difference in the visual acuity of each eye (p=0.045) and significantly worse stereoacuity than those who were able to perceive the effect (p=0.002).
CONCLUSIONS—Unilateral cataract can cause a pathological Pulfrich phenomenon. This finding may explain why some patients with unilateral cataract complain of visual symptoms that are not easily accounted for in terms of visual acuity, contrast sensitivity, or stereoacuity.


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This chapter deals with three key issues related to designing and building intelligent agents. Firstly, determination of aims and objectives at any given time of an intelligent agent, followed by planning a series of actions to achieve these aims and objectives. And finally agents interaction with humans and other software agents to complete the objectives. The above issues are discussed under the heading of motivation, planning and interaction. Motivation as an area of study is important in understanding human and animal behavior. Also, from a computer science perspective, it could offer a substantially higher level of control than is currently available. Furthermore, planning is a sub-field of AI research which plays a vital role in the development of intelligent autonomous systems and in many application areas of cognitive systems. This chapter further classifies interactions into three types. The first is machine-machine interactions, including networking and information understanding. The second is people-machine interaction, often referred to as Human Computer Interaction (HCI). Finally, impacts of technology on person-to-person communication. © 2006 Elsevier Ltd. All rights reserved