A cross-coupling model of vertical vergence adaptation.
ABSTRACT Vertical disparity vergence aligns the two eyes in response to vertical misalignment (disparity) of the two ocular images. An adaptive response to vertical disparity vergence is demonstrated by the continuation of vertical vergence when one eye is occluded. The adaptive response is quantified by vertical phoria, the eye alignment error during monocular viewing. Vertical phoria can be differentially adapted to vertical disparities of opposite sign located at two positions along the horizontal or vertical head-referenced axes. Vertical phoria aftereffects vary in amplitude as the eyes move from one adapted direction of gaze to another along the adaptation axis. A cross-coupling model was developed to account for the spatial variations of vertical phoria aftereffects. The model is constrained according to both single cell recordings of eye position sensitive neurons, and eye position measurements during and following adaptation. The vertical phoria is computed by scaling the activities of eye position sensitive neurons and converting the scaled activities into a vertical vergence signal. The three components of the model are: neural activities associated with conjugate eye position, cross-coupling weights to scale the activities, and vertical vergence transducers to convert the weighted activities to vertical vergence. The model provides a biologically plausible mechanism for vertical vergence adaptation.
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ABSTRACT: Convergence–accommodation, one of several cross-linkages in the oculomotor system is manifested by opening the accommodative feedback loop and increasing the vergence input. We elicited this response in human infants aged 3–6 months by placing a 15Δ prism (base-out) before one eye while they viewed a diffuse patch of light. Accommodation was measured and ocular alignment was confirmed with a video photorefractor. The convergence–accommodation response is therefore present during a time when blur driven accommodation and disparity vergence are maturing. The gain of convergence–accommodation (expressed as the stimulus CA/C ratio) appeared to be greater for infants than adults.Vision Research 02/2000; · 2.14 Impact Factor
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ABSTRACT: Dynamics of disparity vergence eye movements can be modified by adaptive stimuli that generate large transient disparities. These modifications were observed for convergence as well as divergence eye movements. After modification, the peak velocities of the step responses for convergence and divergence were substantially higher than in normal baseline responses, a change observed in all four subjects studied. The change in peak velocity of a step response occurred very rapidly after presentation of the adaptive stimuli. Main sequence plots showed that first-order dynamic characteristics increased for post-adaptive responses with respect to normal step responses. Hence, response modification could be quantified as a change in gain accompanied with an increase in the effective response time constant. The adaptive responses to convergent and divergent ‘disappearing’ step stimuli revealed that the adaptation process modifies the high-velocity component of both disparity convergence and divergence eye movements. Moreover, a gain change in this component alone could account for both the gain and the time constant modifications seen in the overall response. A process of recovery or de-adaptation was also observed for both convergence and divergence eye movements. This observed short-term modification demonstrates a unique control mechanism for vergence eye movements that is effective in either direction.Vision Research 06/1999; · 2.14 Impact Factor
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ABSTRACT: In this paper, the current published knowledge about smart and adaptive engineering systems in medicine is reviewed. The achievements of frontier research in this particular field within medical engineering are described. A multi-disciplinary approach to the applications of adaptive systems is observed from the literature surveyed. The three modalities of diagnosis, imaging and therapy are considered to be an appropriate classification method for the analysis of smart systems being applied to specified medical sub-disciplines. It is expected that future research in biomedicine should identify subject areas where more advanced intelligent systems could be applied than is currently evident. The literature provides evidence of hybridisation of different types of adaptive and smart systems with applications in different areas of medical specifications.Artificial Intelligence in Medicine 01/2002; 26:179-209. · 1.36 Impact Factor