A Neural Model of Visually Guided Steering, Obstacle Avoidance, and Route Selection

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discontinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and posterior parietal cortex can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.Air Force Office of Scientific Research (F4960-01-1-0397); National Geospatial-Intelligence Agency (NMA201-01-1-2016); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

A Neural Model of Visually Guided Steering, Obstacle Avoidance, and Route Selection

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discotinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and VIP can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.Air Force Office of Scientific Research (F4960-01-1-0397); National Geospatial-Intelligence Agency (NMA201-01-1-2016); National Science Foundation (NSF SBE-0354378); Office of Naval Research (N00014-01-1-0624

Altered Velocity Processing in Schizophrenia during Pursuit Eye Tracking

Smooth pursuit eye movements (SPEM) are needed to keep the retinal image of slowly moving objects within the fovea. Depending on the task, about 50%–80% of patients with schizophrenia have difficulties in maintaining SPEM. We designed a study that comprised different target velocities as well as testing for internal (extraretinal) guidance of SPEM in the absence of a visual target. We applied event-related fMRI by presenting four velocities (5, 10, 15, 20°/s) both with and without intervals of target blanking. 17 patients and 16 healthy participants were included. Eye movements were registered during scanning sessions. Statistical analysis included mixed ANOVAs and regression analyses of the target velocity on the Blood Oxygen Level Dependency (BOLD) signal. The main effect group and the interaction of velocity×group revealed reduced activation in V5 and putamen but increased activation of cerebellar regions in patients. Regression analysis showed that activation in supplementary eye field, putamen, and cerebellum was not correlated to target velocity in patients in contrast to controls. Furthermore, activation in V5 and in intraparietal sulcus (putative LIP) bilaterally was less strongly correlated to target velocity in patients than controls. Altered correlation of target velocity and neural activation in the cortical network supporting SPEM (V5, SEF, LIP, putamen) implies impaired transformation of the visual motion signal into an adequate motor command in patients. Cerebellar regions seem to be involved in compensatory mechanisms although cerebellar activity in patients was not related to target velocity

Ageing, Motion Perception and the Compensation for Eye Movements

Smooth pursuit over a textured background introduces full-field motion to the retinal image in the direction opposing the eye movement. If this motion is not correctly attributed to the eye movement, it can be falsely perceived as motion in the world (Haarmeier, Thier, Repnow & Petersen, 1997). In order to correctly attribute retinal motion, the visual system must compensate for the effects of eye movements on the retinal image in motion perception. Visual motion perception is important for safely navigating the environment and has been linked to difficulties experienced by older adults while driving (Conlon & Herkes, 2008; Raghuram & Lakshminarayanan, 2006) and walking (Cavanaugh, 2002). The experiments reported in this thesis were devised in order to examine the effects of ageing on the perception of illusory motion during eye movements and therefore on the ability to compensate for eye movements in motion perception. The perception of motion during smooth pursuit eye movements was assessed in adults ranging in age from 17 to 79 years. The computer based task required participants to respond to the speed and direction of motion of a large-field random dot pattern while following a moving target dot with the eyes. For this task, a magnitude estimation tool was especially designed based on the direction response method of Bennett, Sekuler and Sekuler (2007). During the experimental session an eye tracker recorded the participant's eye movements. For the purposes of analysis, four groups were defined by age. It was found that the smooth pursuit of adults from ~40 years of age was slower than that of the younger age groups. With stationary eyes, the oldest age group ranging in age from 60 to 79 years tended to overestimate the speed of the dot pattern as compared to younger observers. This tendency decreased at higher background speeds. Eye movements appeared to affect the perception of the dot field's motion more in the group of participants ranging in age from 40 to 54 years than in the younger age groups. This also seemed to be the case for participants aged over 60 when viewing horizontal motion but not vertical motion. The results of this study suggest that older observers may be less able to compensate for the effects of eye movements on the retinal image. This could potentially affect their ability to safely and confidently navigate the environment

Eye velocity gain fields for visuo- motor coordinate transformations

’Gain-field-like’ tuning behavior is characterized by a modulation of the neuronal response depending on a certain variable, without changing the actual receptive field characteristics in relation to another variable. Eye position gain fields were first observed in area 7a of the posterior parietal cortex (PPC), where visually responsive neurons are modulated by ocular position. Analysis of artificial neural networks has shown that this type of tuning function might comprise the neuronal substrate for coordinate transformations. In this work, neuronal activity in the dorsal medial superior temporal area (MSTd) has been analyzed with an focus on it’s involvement in oculomotor control. MSTd is part of the extrastriate visual cortex and located in the PPC. Lesion studies suggested a participation of this cortical area in the control of eye movements. Inactivation of MSTd severely impairs the optokinetic response (OKR), which is an reflex-like kind of eye movement that compensates for motion of the whole visual scene. Using a novel, information-theory based approach for neuronal data analysis, we were able to identify those visual and eye movement related signals which were most correlated to the mean rate of spiking activity in MSTd neurons during optokinetic stimulation. In a majority of neurons firing rate was non-linearly related to a combination of retinal image velocity and eye velocity. The observed neuronal latency relative to these signals is in line with a system-level model of OKR, where an efference copy of the motor command signal is used to generate an internal estimate of the head-centered stimulus velocity signal. Tuning functions were obtained by using a probabilistic approach. In most MSTd neurons these functions exhibited gain-field-like shapes, with eye velocity modulating the visual response in a multiplicative manner. Population analysis revealed a large diversity of tuning forms including asymmetric and non-separable functions. The distribution of gain fields was almost identical to the predictions from a neural network model trained to perform the summation of image and eye velocity. These findings therefore strongly support the hypothesis of MSTd’s participation in the OKR control system by implementing the transformation from retinal image velocity to an estimate of stimulus velocity. In this sense, eye velocity gain fields constitute an intermediate step in transforming the eye-centered to a head-centered visual motion signal.Another aspect that was addressed in this work was the comparison of the irregularity of MSTd spiking activity during optokinetic response with the behavior during pure visual stimulation. The goal of this study was an evaluation of potential neuronal mechanisms underlying the observed gain field behavior. We found that both inter- and intra-trial variability were decreased with increasing retinal image velocity, but increased with eye velocity. This observation argues against a symmetrical integration of driving and modulating inputs. Instead, we propose an architecture where multiplicative gain modulation is achieved by simultaneous increase of excitatory and inhibitory background synaptic input. A conductance-based single-compartment model neuron was able to reproduce realistic gain modulation and the observed stimulus-dependence of neural variability, at the same time. In summary, this work leads to improved knowledge about MSTd’s role in visuomotor transformation by analyzing various functional and mechanistic aspects of eye velocity gain fields on a systems-, network-, and neuronal level

Investigating the cortical oscillatory correlates of smooth pursuit eye movements : a magnetoencephalographic study

Models of motion perception propose that eye movement estimates are integrated into middle temporal cortex (MT+) as a mechanism that disambiguates world motion from retinal motion induced by ego movement. Little is known about the relationship between eye movement signals in this area and cortical oscillations, a phenomenon linked to perceptual and motor processing. Magnetoencephalography was used to examine the significance of oscillations in this area during pursuit. Results from Experiment 1 suggest low-frequency suppression in MT+ reflects eye position during sinusoidal tracking. A control study (Experiment 2) examining activity in response to retinal slip suggests this was not due to pursuit error when the stimulus changed direction. Experiment 3 examined oscillations during pursuit at various head-centred eye eccentricities. No difference was found in the magnitude of activity as a function of eye position during pursuit, suggesting modulations in these rhythms was related to another aspect of the eye movement. Experiment 4 found no specific effects of eye velocity on alpha or beta, but there was a consistent effect of eye speed on beta activity. Additionally, there was no such effect found between alpha and eye speed, suggesting some functional distinction in the role of these rhythms in pursuit behaviour. In Chapter 4, two experiments examined cortical changes during pursuit (Experiment 5) and retinal motion adaptation (Experiment 6), and the subsequent motion aftereffect. Beta suppression in MT+ during oculomotor adaptation was a significant predictor of the motion aftereffect duration, perhaps indicating that beta changes index the efficacy with which the visual motion system is able to recalibrate itself in the presence of a stationary stimulus following adaptation. Taken together, these results suggest a role for beta suppression in MT+ during pursuit, which seems to reflect the processing of extraretinal signals for oculomotor control and the estimation of head-centred motion.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Investigating the cortical oscillatory correlates of smooth pursuit eye movements: a magnetoencephalographic study

Models of motion perception propose that eye movement estimates are integrated into middle temporal cortex (MT+) as a mechanism that disambiguates world motion from retinal motion induced by ego movement. Little is known about the relationship between eye movement signals in this area and cortical oscillations, a phenomenon linked to perceptual and motor processing. Magnetoencephalography was used to examine the significance of oscillations in this area during pursuit. Results from Experiment 1 suggest low-frequency suppression in MT+ reflects eye position during sinusoidal tracking. A control study (Experiment 2) examining activity in response to retinal slip suggests this was not due to pursuit error when the stimulus changed direction. Experiment 3 examined oscillations during pursuit at various head-centred eye eccentricities. No difference was found in the magnitude of activity as a function of eye position during pursuit, suggesting modulations in these rhythms was related to another aspect of the eye movement. Experiment 4 found no specific effects of eye velocity on alpha or beta, but there was a consistent effect of eye speed on beta activity. Additionally, there was no such effect found between alpha and eye speed, suggesting some functional distinction in the role of these rhythms in pursuit behaviour. In Chapter 4, two experiments examined cortical changes during pursuit (Experiment 5) and retinal motion adaptation (Experiment 6), and the subsequent motion aftereffect. Beta suppression in MT+ during oculomotor adaptation was a significant predictor of the motion aftereffect duration, perhaps indicating that beta changes index the efficacy with which the visual motion system is able to recalibrate itself in the presence of a stationary stimulus following adaptation. Taken together, these results suggest a role for beta suppression in MT+ during pursuit, which seems to reflect the processing of extraretinal signals for oculomotor control and the estimation of head-centred motion

Anticipatory eye movements evoked after active following versus passive observation of a predictable motion stimulus.

We used passive and active following of a predictable smooth pursuit stimulus in order to establish if predictive eye movement responses are equivalent under both passive and active conditions. The smooth pursuit stimulus was presented in pairs that were either ‘predictable’ in which both presentations were matched in timing and velocity, or ‘randomized’ in which each presentation in the pair was varied in both timing and velocity. A visual cue signaled the type of response required from the subject; a green cue indicated the subject should follow both the target presentations (Go-Go), a pink cue indicated that the subject should passively observe the 1st target and follow the 2nd target (NoGo-Go), and finally a green cue with a black cross revealed a randomized (Rnd) trial in which the subject should follow both presentations. The results revealed better prediction in the Go-Go trials than in the NoGo-Go trials, as indicated by higher anticipatory velocity and earlier eye movement onset (latency). We conclude that velocity and timing information stored from passive observation of a moving target is diminished when compared to active following of the target. This study has significant consequences for understanding how visuomotor memory is generated, stored and subsequently released from short-term memory

Smooth Pursuit–Related Information Processing in Frontal Eye Field Neurons that Project to the NRTP

The cortical pursuit system begins the process of transforming visual signals into commands for smooth pursuit (SP) eye movements. The frontal eye field (FEF), located in the fundus of arcuate sulcus, is known to play a role in SP and gaze pursuit movements. This role is supported, at least in part, by FEF projections to the rostral nucleus reticularis tegmenti pontis (rNRTP), which in turn projects heavily to the cerebellar vermis. However, the functional characteristics of SP-related FEF neurons that project to rNRTP have never been described. Therefore, we used microelectrical stimulation (ES) to deliver single pulses (50–200 μA, 200-μs duration) in rNRTP to antidromically activate FEF neurons. We estimated the eye or retinal error motion sensitivity (position, velocity, and acceleration) of FEF neurons during SP using multiple linear regression modeling. FEF neurons that projected to rNRTP were most sensitive to eye acceleration. In contrast, FEF neurons not activated following ES of rNRTP were often most sensitive to eye velocity. In similar modeling studies, we found that rNRTP neurons were also biased toward eye acceleration. Therefore, our results suggest that neurons in the FEF–rNRTP pathway carry signals that could play a primary role in initiation of SP

Evidence that smooth pursuit velocity, not eye position, modulates alpha and beta oscillations in human middle temporal cortex

Suppression of 5–25 Hz oscillations have been observed in MT1 during pursuit eye move- ments, suggesting oscillations that play a role in oculomotor control and/or the integration of extrareti- nal signals during pursuit. The amplitude of these rhythms appears to covary with head-centered eye position, but an alternative is that they depend on a velocity signal that lags the movement of the eyes. To investigate, we explored how alpha and beta amplitude changes related to ongoing eye move- ment depended on pursuit at different eccentricities. The results revealed largely identical patterns of modulation in the alpha and beta amplitude, irrespective of the eccentricity at which the pursuit eye movement was performed. The signals we measured therefore do not depend on head-centered posi- tion. A second experiment was designed to investigate whether the alpha and beta oscillations depended on the direction of pursuit, as opposed to just speed. We found no evidence that alpha or beta oscillations depended on direction, but there was a significant effect of eye speed on the magni- tude of the beta suppression. This suggests distinct functional roles for alpha and beta suppression in pursuit behavior