Integrating Brain and Biomechanical Models—A New Paradigm for Understanding Neuro-muscular Control

To date, realistic models of how the central nervous system governs behavior have been restricted in scope to the brain, brainstem or spinal column, as if these existed as disembodied organs. Further, the model is often exercised in relation to an in vivo physiological experiment with input comprising an impulse, a periodic signal or constant activation, and output as a pattern of neural activity in one or more neural populations. Any link to behavior is inferred only indirectly via these activity patterns. We argue that to discover the principles of operation of neural systems, it is necessary to express their behavior in terms of physical movements of a realistic motor system, and to supply inputs that mimic sensory experience. To do this with confidence, we must connect our brain models to neuro-muscular models and provide relevant visual and proprioceptive feedback signals, thereby closing the loop of the simulation. This paper describes an effort to develop just such an integrated brain and biomechanical system using a number of pre-existing models. It describes a model of the saccadic oculomotor system incorporating a neuromuscular model of the eye and its six extraocular muscles. The position of the eye determines how illumination of a retinotopic input population projects information about the location of a saccade target into the system. A pre-existing saccadic burst generator model was incorporated into the system, which generated motoneuron activity patterns suitable for driving the biomechanical eye. The model was demonstrated to make accurate saccades to a target luminance under a set of environmental constraints. Challenges encountered in the development of this model showed the importance of this integrated modeling approach. Thus, we exposed shortcomings in individual model components which were only apparent when these were supplied with the more plausible inputs available in a closed loop design. Consequently we were able to suggest missing functionality which the system would require to reproduce more realistic behavior. The construction of such closed-loop animal models constitutes a new paradigm of computational neurobehavior and promises a more thoroughgoing approach to our understanding of the brain’s function as a controller for movement and behavior

Inhibitory and facilitatory cueing effects: Competition between exogenous and endogenous mechanisms

Inhibition of return is characterized by delayed responses to previously attended locations when the cue-target onset asynchrony (CTOA) is long enough. However, when cues are predictive of a target's location, faster reaction times to cued as compared to uncued targets are normally observed. In this series of experiments investigating saccadic reaction times, we manipulated the cue predictability to 25% (counterpredictive), 50% (nonpredictive), and 75% (predictive) to investigate the interaction between predictive endogenous facilitatory (FCEs) and inhibitory cueing effects (ICEs). Overall, larger ICEs were seen in the counterpredictive condition than in the nonpredictive condition, and no ICE was found in the predictive condition. Based on the hypothesized additivity of FCEs and ICEs, we reasoned that the null ICEs observed in the predictive condition are the result of two opposing mechanisms balancing each other out, and the large ICEs observed with counterpredictive cueing can be attributed to the combination of endogenous facilitation at uncued locations with inhibition at cued locations. Our findings suggest that the endogenous activity contributed by cue predictability can reduce the overall inhibition observed when the mechanisms occur at the same location, or enhance behavioral inhibition when the mechanisms occur at opposite locations

The computational neurology of active vision

In this thesis, we appeal to recent developments in theoretical neurobiology – namely, active inference – to understand the active visual system and its disorders. Chapter 1 reviews the neurobiology of active vision. This introduces some of the key conceptual themes around attention and inference that recur through subsequent chapters. Chapter 2 provides a technical overview of active inference, and its interpretation in terms of message passing between populations of neurons. Chapter 3 applies the material in Chapter 2 to provide a computational characterisation of the oculomotor system. This deals with two key challenges in active vision: deciding where to look, and working out how to look there. The homology between this message passing and the brain networks solving these inference problems provide a basis for in silico lesion experiments, and an account of the aberrant neural computations that give rise to clinical oculomotor signs (including internuclear ophthalmoplegia). Chapter 4 picks up on the role of uncertainty resolution in deciding where to look, and examines the role of beliefs about the quality (or precision) of data in perceptual inference. We illustrate how abnormal prior beliefs influence inferences about uncertainty and give rise to neuromodulatory changes and visual hallucinatory phenomena (of the sort associated with synucleinopathies). We then demonstrate how synthetic pharmacological perturbations that alter these neuromodulatory systems give rise to the oculomotor changes associated with drugs acting upon these systems. Chapter 5 develops a model of visual neglect, using an oculomotor version of a line cancellation task. We then test a prediction of this model using magnetoencephalography and dynamic causal modelling. Chapter 6 concludes by situating the work in this thesis in the context of computational neurology. This illustrates how the variational principles used here to characterise the active visual system may be generalised to other sensorimotor systems and their disorders

A competitive integration model of exogenous and endogenous eye movements

We present a model of the eye movement system in which the programming of an eye movement is the result of the competitive integration of information in the superior colliculi (SC). This brain area receives input from occipital cortex, the frontal eye fields, and the dorsolateral prefrontal cortex, on the basis of which it computes the location of the next saccadic target. Two critical assumptions in the model are that cortical inputs are not only excitatory, but can also inhibit saccades to specific locations, and that the SC continue to influence the trajectory of a saccade while it is being executed. With these assumptions, we account for many neurophysiological and behavioral findings from eye movement research. Interactions within the saccade map are shown to account for effects of distractors on saccadic reaction time (SRT) and saccade trajectory, including the global effect and oculomotor capture. In addition, the model accounts for express saccades, the gap effect, saccadic reaction times for antisaccades, and recorded responses from neurons in the SC and frontal eye fields in these tasks. © The Author(s) 2010

Generative Models for Active Vision

The active visual system comprises the visual cortices, cerebral attention networks, and oculomotor system. While fascinating in its own right, it is also an important model for sensorimotor networks in general. A prominent approach to studying this system is active inference—which assumes the brain makes use of an internal (generative) model to predict proprioceptive and visual input. This approach treats action as ensuring sensations conform to predictions (i.e., by moving the eyes) and posits that visual percepts are the consequence of updating predictions to conform to sensations. Under active inference, the challenge is to identify the form of the generative model that makes these predictions—and thus directs behavior. In this paper, we provide an overview of the generative models that the brain must employ to engage in active vision. This means specifying the processes that explain retinal cell activity and proprioceptive information from oculomotor muscle fibers. In addition to the mechanics of the eyes and retina, these processes include our choices about where to move our eyes. These decisions rest upon beliefs about salient locations, or the potential for information gain and belief-updating. A key theme of this paper is the relationship between “looking” and “seeing” under the brain's implicit generative model of the visual world

Perceptions as Hypotheses: Saccades as Experiments

If perception corresponds to hypothesis testing (Gregory, 1980); then visual searches might be construed as experiments that generate sensory data. In this work, we explore the idea that saccadic eye movements are optimal experiments, in which data are gathered to test hypotheses or beliefs about how those data are caused. This provides a plausible model of visual search that can be motivated from the basic principles of self-organized behavior: namely, the imperative to minimize the entropy of hidden states of the world and their sensory consequences. This imperative is met if agents sample hidden states of the world efficiently. This efficient sampling of salient information can be derived in a fairly straightforward way, using approximate Bayesian inference and variational free-energy minimization. Simulations of the resulting active inference scheme reproduce sequential eye movements that are reminiscent of empirically observed saccades and provide some counterintuitive insights into the way that sensory evidence is accumulated or assimilated into beliefs about the world

System Level Assessment of Motor Control through Patterned Microstimulation in the Superior Colliculus

We are immersed in an environment full of sensory information, and without much thought or effort we can produce orienting responses to appropriately react to different stimuli. This seemingly simple and reflexive behavior is accomplished by a very complicated set of neural operations, in which motor systems in the brain must control behavior based on populations of sensory information. The oculomotor or saccadic system is particularly well studied in this regard. Within a visual environment consisting of many potential stimuli, we control our gaze with rapid eye movements, or saccades, in order to foveate visual targets of interest. A key sub-cortical structure involved in this process is the superior colliculus (SC). The SC is a structure in the midbrain which receives visual input and in turn projects to lower-level areas in the brainstem that produce saccades. Interestingly, microstimulation of the SC produces eye movements that match the metrics and kinematics of naturally-evoked saccades. As a result, we explore the role of the SC in saccadic motor control by manually introducing distributions of activity through neural stimulation. Systematic manipulation of microstimulation patterns were used to characterize how ensemble activity in the SC is decoded to generate eye movements. Specifically, we focused on three different facets of saccadic motor control. In the first study, we examine the effective influence of microstimulation parameters on behavior to reveal characteristics of the neural mechanisms underlying saccade generation. In the second study, we experimentally verify the predictions of computational algorithms that are used to describe neural mechanisms for saccade generation. And in the third study, we assess where neural mechanisms for decoding occur within the oculomotor network in order to establish the order of operations necessary for saccade generation. The experiments assess different aspects of saccadic motor control, which collectively, reveal properties and mechanisms that contribute to the comprehensive understanding of signal processing in the oculomotor system

Contribution of the Primate Frontal Cortex to Eye Movements and Neuronal Activity in the Superior Colliculus

Humans and non-human primates must precisely align the eyes on an object to view it with high visual acuity. An important role of the oculomotor system is to generate accurate eye movements, such as saccades, toward a target. Given that each eye has only six muscles that rotate the eye in three degrees of freedom, this relatively simple volitional movement has allowed researchers to well-characterize the brain areas involved in their generation. In particular, the midbrain Superior Colliculus (SC), is recognized as having a primary role in the generation of visually-guided saccades via the integration of sensory and cognitive information. One important source of sensory and cognitive information to the SC is the Frontal Eye Fields (FEF). The role of the FEF and SC in visually-guided saccades has been well-studied using anatomical and functional techniques, but only a handful of studies have investigated how these areas work together to produce saccades. While it is assumed that the FEF exerts its influence on saccade generation though the SC, it remains unknown what happens in the SC when the FEF is suddenly inactivated. To test this prediction, I use the combined approach of FEF cryogenic inactivation and SC neuronal recordings, although it also provides a valuable opportunity to understand how FEF inputs to the SC govern saccade preparation. Nonetheless, it was first necessary to characterize the eye movement deficits following FEF inactivation, as it was unknown how a large and reversible FEF inactivation would influence saccade behaviour, or whether cortical areas influence fixational eye movements (e.g. microsaccades). Four major results emerged from this thesis. First, FEF inactivation delayed saccade reaction times (SRT) in both directions. Second, FEF inactivation impaired microsaccade generation and also selectively reduced microsaccades following peripheral cues. Third, FEF inactivation decreased visual, cognitive, and saccade-related activity in the ipsilesional SC. Fourth, the delayed onset of saccade-related SC activity best explained SRT increases during FEF inactivation, implicating one mechanism for how FEF inputs govern saccade preparation. Together, these results provide new insights into the FEF\u27s role in saccade and microsaccade behaviour, and how the oculomotor system commits to a saccade

Capture of fixation by rotational flow; a deterministic hypothesis regarding scaling and stochasticity in fixational eye movements.

Visual scan paths exhibit complex, stochastic dynamics. Even during visual fixation, the eye is in constant motion. Fixational drift and tremor are thought to reflect fluctuations in the persistent neural activity of neural integrators in the oculomotor brainstem, which integrate sequences of transient saccadic velocity signals into a short term memory of eye position. Despite intensive research and much progress, the precise mechanisms by which oculomotor posture is maintained remain elusive. Drift exhibits a stochastic statistical profile which has been modeled using random walk formalisms. Tremor is widely dismissed as noise. Here we focus on the dynamical profile of fixational tremor, and argue that tremor may be a signal which usefully reflects the workings of oculomotor postural control. We identify signatures reminiscent of a certain flavor of transient neurodynamics; toric traveling waves which rotate around a central phase singularity. Spiral waves play an organizational role in dynamical systems at many scales throughout nature, though their potential functional role in brain activity remains a matter of educated speculation. Spiral waves have a repertoire of functionally interesting dynamical properties, including persistence, which suggest that they could in theory contribute to persistent neural activity in the oculomotor postural control system. Whilst speculative, the singularity hypothesis of oculomotor postural control implies testable predictions, and could provide the beginnings of an integrated dynamical framework for eye movements across scales