Gaze control modelling and robotic implementation

Although we have the impression that we can process the entire visual field in a single fixation, in reality we would be unable to fully process the information outside of foveal vision if we were unable to move our eyes. Because of acuity limitations in the retina, eye movements are necessary for processing the details of the array. Our ability to discriminate fine detail drops off markedly outside of the fovea in the parafovea (extending out to about 5 degrees on either side of fixation) and in the periphery (everything beyond the parafovea). While we are reading or searching a visual array for a target or simply looking at a new scene, our eyes move every 200-350 ms. These eye movements serve to move the fovea (the high resolution part of the retina encompassing 2 degrees at the centre of the visual field) to an area of interest in order to process it in greater detail. During the actual eye movement (or saccade), vision is suppressed and new information is acquired only during the fixation (the period of time when the eyes remain relatively still). While it is true that we can move our attention independently of where the eyes are fixated, it does not seem to be the case in everyday viewing. The separation between attention and fixation is often attained in very simple tasks; however, in tasks like reading, visual search, and scene perception, covert attention and overt attention (the exact eye location) are tightly linked. Because eye movements are essentially motor movements, it takes time to plan and execute a saccade. In addition, the end-point is pre-selected before the beginning of the movement. There is considerable evidence that the nature of the task influences eye movements. Depending on the task, there is considerable variability both in terms of fixation durations and saccade lengths. It is possible to outline five separate movement systems that put the fovea on a target and keep it there. Each of these movement systems shares the same effector pathway—the three bilateral groups of oculomotor neurons in the brain stem. These five systems include three that keep the fovea on a visual target in the environment and two that stabilize the eye during head movement. Saccadic eye movements shift the fovea rapidly to a visual target in the periphery. Smooth pursuit movements keep the image of a moving target on the fovea. Vergence movements move the eyes in opposite directions so that the image is positioned on both foveae. Vestibulo-ocular movements hold images still on the retina during brief head movements and are driven by signals from the vestibular system. Optokinetic movements hold images during sustained head rotation and are driven by visual stimuli. All eye movements but vergence movements are conjugate: each eye moves the same amount in the same direction. Vergence movements are disconjugate: The eyes move in different directions and sometimes by different amounts. Finally, there are times that the eye must stay still in the orbit so that it can examine a stationary object. Thus, a sixth system, the fixation system, holds the eye still during intent gaze. This requires active suppression of eye movement. Vision is most accurate when the eyes are still. When we look at an object of interest a neural system of fixation actively prevents the eyes from moving. The fixation system is not as active when we are doing something that does not require vision, for example, mental arithmetic. Our eyes explore the world in a series of active fixations connected by saccades. The purpose of the saccade is to move the eyes as quickly as possible. Saccades are highly stereotyped; they have a standard waveform with a single smooth increase and decrease of eye velocity. Saccades are extremely fast, occurring within a fraction of a second, at speeds up to 900°/s. Only the distance of the target from the fovea determines the velocity of a saccadic eye movement. We can change the amplitude and direction of our saccades voluntarily but we cannot change their velocities. Ordinarily there is no time for visual feedback to modify the course of the saccade; corrections to the direction of movement are made in successive saccades. Only fatigue, drugs, or pathological states can slow saccades. Accurate saccades can be made not only to visual targets but also to sounds, tactile stimuli, memories of locations in space, and even verbal commands (“look left”). The smooth pursuit system keeps the image of a moving target on the fovea by calculating how fast the target is moving and moving the eyes accordingly. The system requires a moving stimulus in order to calculate the proper eye velocity. Thus, a verbal command or an imagined stimulus cannot produce smooth pursuit. Smooth pursuit movements have a maximum velocity of about 100°/s, much slower than saccades. The saccadic and smooth pursuit systems have very different central control systems. A coherent integration of these different eye movements, together with the other movements, essentially corresponds to a gating-like effect on the brain areas controlled. The gaze control can be seen in a system that decides which action should be enabled and which should be inhibited and in another that improves the action performance when it is executed. It follows that the underlying guiding principle of the gaze control is the kind of stimuli that are presented to the system, by linking therefore the task that is going to be executed. This thesis aims at validating the strong relation between actions and gaze. In the first part a gaze controller has been studied and implemented in a robotic platform in order to understand the specific features of prediction and learning showed by the biological system. The eye movements integration opens the problem of the best action that should be selected when a new stimuli is presented. The action selection problem is solved by the basal ganglia brain structures that react to the different salience values of the environment. In the second part of this work the gaze behaviour has been studied during a locomotion task. The final objective is to show how the different tasks, such as the locomotion task, imply the salience values that drives the gaze

Saccade Planning and Execution by the Lateral and Medial Cerebellum

In dit proefschrift wordt beschreven hoe het cerebellum saccadische oogbewegingen plant en uitvoert. De resultaten van metingen aan the neuronen in het cerebellum van rhesus makaken geven inzicht in welke processen ten grondslag liggen aan dit type oogbeweging

Adaptive control of saccades

As we navigate through the world in our lifetime, our brains constantly adjust our movements to ensure their accuracy. How does the brain adaptively control our movements? In this dissertation, we looked at saccadic eye movements and performed behavioral and neural measurements to study different brain mechanisms for adaptive control of saccades. In ‎Chapter 2, we considered the effect of reward prediction error (RPE) as a strong modulator of dopamine on saccade vigor. We found that saccade vigor was affected in an orderly fashion by the magnitude and direction of the RPE event: the most vigorous saccades followed the largest positive-RPE, whereas the least vigorous saccades followed the largest negative-RPE. Thus, reward prediction error, and not reward per se, modulated the vigor of saccades. In ‎Chapter 3, we looked at corrective saccades during saccade adaptation and asked is there an implicit loss associated with the corrective movement that can modulate learning? We designed a novel paradigm that combined random dot motion discrimination with saccade adaptation to impose a cost on movement error. Our results demonstrated that when error cost was large, the brain learned more from error. Thus, during sensorimotor adaptation, the act of correcting for error carries an implicit cost for the brain which regulates the rates of learning. Next, we focused on the potential neural mechanisms for adaptive control of saccades and the role of the principal cells of the cerebellar cortex, Purkinje cells (P-cells), in control of saccades. We introduced marmoset monkeys as a new animal model to study motor control and motor learning. In ‎Chapter 4, we presented protocols to train marmoset monkeys to perform saccadic eye movement tasks and record from their cerebellum. In ‎Chapter 5, we introduced an open-source software package, named P-sort, to analyze the cerebellar neurophysiological data. Finally, in ‎Chapter 6, we analyzed the P-cell data (n=149 cells) by organizing them into populations that shared the same preference for error as measured via their complex spike response. We found that the population activity of simple spikes produced a burst-pause pattern that started before saccade onset and ended with saccade termination. Next, we looked at synchronous activity among pairs of simultaneously recorded P-cells (n=42 pairs). Our results demonstrated that the synchronization index reached its peak probability after deceleration onset but before saccade end. Thus, the cerebellar cortex relies on spike synchronization within a population of P-cells, not individual firing rates, to predict when to stop a movement

Investigating the effects of psychosocial stress on cerebellar function

Differences in cerebellar structure and function are consistently reported in individuals exposed to early-life stress and individuals with diagnosed stress-related psychopathology. Despite this, current neurobiological models of stress have not considered the role of the cerebellum in the regulation of the stress response. Furthermore, it is unclear the mechanism by which stress may affect cerebellar function. The studies presented in this thesis set out to address these questions by exploring the relationship between acute psychosocial stress and the cerebellum. To achieve this, two putative cerebellar functions were investigated: saccadic adaptation and postural balance control. Chapters 4 and 5 present two studies, which evaluated the effectiveness of each task, as well as individual differences in task performance. Chapter 4 presents evidence demonstrating a linear effect of saccadic adaptation across participants. Chapter 5 revealed improved postural balance control under perturbed balancing conditions. Individual differences in task performance were inconclusive. Each study was followed by an investigation on the effects of acute psychosocial stress on task performance. Particularly, Chapter 6 demonstrated that stress impaired the rate of saccadic adaptation, and that this impairment was associated with the stress-related endocrine response. The study presented in Chapter 7 showed no effect of psychosocial stress on postural balance control. Finally, Chapter 8 explored the effects of non-invasive cerebellar stimulation on saccadic adaptation and cortisol output, revealing that a decrease in cerebellar excitability yielded adaptation rates that were similar to those observed after stress. These findings suggest that psychosocial stress impairs error-driven feedforward computations specifically, via glucocorticoid signalling, thus contributing to the current neurobiological models of stress

Fine-Tuning and the Stability of Recurrent Neural Networks

A central criticism of standard theoretical approaches to constructing stable, recurrent model networks is that the synaptic connection weights need to be finely-tuned. This criticism is severe because proposed rules for learning these weights have been shown to have various limitations to their biological plausibility. Hence it is unlikely that such rules are used to continuously fine-tune the network in vivo. We describe a learning rule that is able to tune synaptic weights in a biologically plausible manner. We demonstrate and test this rule in the context of the oculomotor integrator, showing that only known neural signals are needed to tune the weights. We demonstrate that the rule appropriately accounts for a wide variety of experimental results, and is robust under several kinds of perturbation. Furthermore, we show that the rule is able to achieve stability as good as or better than that provided by the linearly optimal weights often used in recurrent models of the integrator. Finally, we discuss how this rule can be generalized to tune a wide variety of recurrent attractor networks, such as those found in head direction and path integration systems, suggesting that it may be used to tune a wide variety of stable neural systems

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