293 research outputs found

    The interaction between human vision and eye movements in health and disease

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    Human motor behaviour depends on the successful integration of vision and eye movements. Many studies have investigated neural correlates of visual processing in humans, but typically with the eyes stationary and fixated centrally. Similarly, many studies have sought to characterise which brain areas are responsible for oculomotor control, but generally in the absence of visual stimulation. The few studies to explicitly study the interaction between visual perception and eye movements suggest strong influences of both static and dynamic eye position on visual processing and modulation of oculomotor structures by properties of visual stimuli. However, the neural mechanisms underlying these interactions are poorly understood. This thesis uses a range of fMRI methodologies such as retinotopic mapping, multivariate analsyis techniques, dynamic causal modelling and ultra high resolution imaging to examine the interactions between the oculomotor and visual systems in the normal human brain. The results of the experiments presented in this thesis demonstrate that oculomotor behaviour has complex effects on activity in visual areas, while spatial properites of visual stimuli modify activity in oculomotor areas. Specifically, responses in the lateral geniculate nucleus and early cortical visual areas are modulated by saccadic eye movements (a process potentially mediated by the frontal eye fields) and by changes in static eye position. Additionally, responses in oculomotor structures such as the superior colliculus are biased for visual stimuli presented in the temporal rather than nasal hemifield. These findings reveal that although the visual and oculomotor systems are spatially segregated in the brain, they show a high degree of integration at the neural level. This is consistent with our everyday experience of the visual world where frequent eye movements do not lead to disruption of visual continuity and visual information is seamlessly transformed into motor behaviour

    Eye-Head-Hand Coordination During Visually Guided Reaches in Head-Unrestrained Macaques

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    Our goal was to determine if reaching influences eye-head coordination (and vice versa) in Rhesus macaques. Eye, head, and hand motion were recorded in two animals using search coil and touch screen technology, respectively. Animals were seated in a customized chair which allowed unencumbered head motion and reaching in depth. In the reach condition, animals were trained to touch a central LED at waist level while maintaining central gaze and were then rewarded if they touched a target appearing at one of 15 locations. In other variants, initial hand or gaze position were varied in the horizontal plane. In similar control tasks, animals were rewarded for gaze accuracy. In the reach task, animals made eye-head gaze shifts toward the target followed by reaches that were accompanied by prolonged head motion toward the target. This resulted in significantly larger velocities and final ranges of head position compared with the gaze control

    Contrast Dependence of Smooth Pursuit Eye Movements following a Saccade to Superimposed Targets

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    Dorsal stream areas provide motion information used by the oculomotor system to generate pursuit eye movements. Neurons in these areas saturate at low levels of luminance contrast. We therefore hypothesized that during the early phase of pursuit, eye velocity would exhibit an oculomotor gain function that saturates at low luminance contrast. To test this, we recorded eye movements in two macaques trained to saccade to an aperture in which a pattern of dots moved left or right. Shortly after the end of the saccade, the eyes followed the direction of motion with an oculomotor gain that increased with contrast before saturating. The addition of a second pattern of dots, moving in the opposite direction and superimposed on the first, resulted in a rightward shift of the contrast-dependent oculomotor gain function. The magnitude of this shift increased with the contrast of the second pattern of dots. Motion was nulled when the two patterns were equal in contrast. Next, we varied contrast over time. Contrast differences that disappeared before saccade onset biased post-saccadic eye movements at short latency. Changes in contrast occurring during or after saccade termination did not influence eye movements for approximately 150 ms. Earlier studies found that eye movements can be explained by a vector average computation when both targets are equal in contrast. We suggest that this averaging computation may reflect a special case of divisive normalization, yielding saturating contrast response functions that shift to the right with opposed motion, averaging motions when targets are equated in contrast

    ELECTRICAL MICROSTIMULATION OF THE MONKEY DORSOLATERAL PREFRONTAL CORTEX IMPAIRS ANTISACCADE PERFORMANCE

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    The dorsolateral prefrontal cortex (DLPFC) has been implicated in response suppression. This function is frequently investigated with the antisaccade task, which requires suppression of the automatic tendency to look toward a flashed peripheral stimulus (prosaccade) and generation of a voluntary saccade to the mirror location. To test the functional relationship between DLPFC activity and antisaccade performance, we applied electrical microstimulation to the DLPFC of two monkeys while they performed randomly interleaved pro- and anti-saccade trials. Microstimulation increased the number of direction errors and slowed saccadic reaction times (SRTs) on antisaccade trials when the visual stimulus is presented on the side contralateral to the stimulated hemisphere. Also, we observed shorter SRTs for contralateral prosaccades and longer SRTs for ipsilateral prosaccades on microstimulation trials. These findings do not support a role for the DLPFC in response suppression, but suggest a more general role in attentional selection of the contralateral field

    Real-time synthetic primate vision

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    A Unified Cognitive Model of Visual Filling-In Based on an Emergic Network Architecture

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    The Emergic Cognitive Model (ECM) is a unified computational model of visual filling-in based on the Emergic Network architecture. The Emergic Network was designed to help realize systems undergoing continuous change. In this thesis, eight different filling-in phenomena are demonstrated under a regime of continuous eye movement (and under static eye conditions as well). ECM indirectly demonstrates the power of unification inherent with Emergic Networks when cognition is decomposed according to finer-grained functions supporting change. These can interact to raise additional emergent behaviours via cognitive re-use, hence the Emergic prefix throughout. Nevertheless, the model is robust and parameter free. Differential re-use occurs in the nature of model interaction with a particular testing paradigm. ECM has a novel decomposition due to the requirements of handling motion and of supporting unified modelling via finer functional grains. The breadth of phenomenal behaviour covered is largely to lend credence to our novel decomposition. The Emergic Network architecture is a hybrid between classical connectionism and classical computationalism that facilitates the construction of unified cognitive models. It helps cutting up of functionalism into finer-grains distributed over space (by harnessing massive recurrence) and over time (by harnessing continuous change), yet simplifies by using standard computer code to focus on the interaction of information flows. Thus while the structure of the network looks neurocentric, the dynamics are best understood in flowcentric terms. Surprisingly, dynamic system analysis (as usually understood) is not involved. An Emergic Network is engineered much like straightforward software or hardware systems that deal with continuously varying inputs. Ultimately, this thesis addresses the problem of reduction and induction over complex systems, and the Emergic Network architecture is merely a tool to assist in this epistemic endeavour. ECM is strictly a sensory model and apart from perception, yet it is informed by phenomenology. It addresses the attribution problem of how much of a phenomenon is best explained at a sensory level of analysis, rather than at a perceptual one. As the causal information flows are stable under eye movement, we hypothesize that they are the locus of consciousness, howsoever it is ultimately realized
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