A re-examination of the time constant of the oculomotor neural integrator in human

Optimisation of an exemplar oculomotor model using multi-objective genetic algorithms executed on a GPU-CPU combination

BACKGROUND

Parameter optimisation is a critical step in the construction of computational biology models. In eye movement research, computational models are increasingly important to understanding the mechanistic basis of normal and abnormal behaviour. In this study, we considered an existing neurobiological model of fast eye movements (saccades), capable of generating realistic simulations of: (i) normal horizontal saccades; and (ii) infantile nystagmus - pathological ocular oscillations that can be subdivided into different waveform classes. By developing appropriate fitness functions, we optimised the model to existing experimental saccade and nystagmus data, using a well-established multi-objective genetic algorithm. This algorithm required the model to be numerically integrated for very large numbers of parameter combinations. To address this computational bottleneck, we implemented a master-slave parallelisation, in which the model integrations were distributed across the compute units of a GPU, under the control of a CPU.

RESULTS

While previous nystagmus fitting has been based on reproducing qualitative waveform characteristics, our optimisation protocol enabled us to perform the first direct fits of a model to experimental recordings. The fits to normal eye movements showed that although saccades of different amplitudes can be accurately simulated by individual parameter sets, a single set capable of fitting all amplitudes simultaneously cannot be determined. The fits to nystagmus oscillations systematically identified the parameter regimes in which the model can reproduce a number of canonical nystagmus waveforms to a high accuracy, whilst also identifying some waveforms that the model cannot simulate. Using a GPU to perform the model integrations yielded a speedup of around 20 compared to a high-end CPU.

CONCLUSIONS

The results of both optimisation problems enabled us to quantify the predictive capacity of the model, suggesting specific modifications that could expand its repertoire of simulated behaviours. In addition, the optimal parameter distributions we obtained were consistent with previous computational studies that had proposed the saccadic braking signal to be the origin of the instability preceding the development of infantile nystagmus oscillations. Finally, the master-slave parallelisation method we developed to accelerate the optimisation process can be readily adapted to fit other highly parametrised computational biology models to experimental data.

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.

Intersaccadic drift velocity is sensitive to short-term hypobaric hypoxia

Hypoxia, defined as decreased availability of oxygen in the body's tissues, can lead to dyspnea, rapid pulse, syncope, visual dysfunction, mental disturbances such as delirium or euphoria, and even death. It is considered to be one of the most serious hazards during flight. Thus, early and objective detection of the physiological effects of hypoxia is critical to prevent catastrophes in civil and military aviation. The few studies that have addressed the effects of hypoxia on objective oculomotor metrics have had inconsistent results, however. Thus, the question of whether hypoxia modulates eye movement behavior remains open. Here we examined the effects of short-term hypobaric hypoxia on the velocity of saccadic eye movements and intersaccadic drift of Spanish Air Force pilots and flight engineers, compared with a control group that did not experience hypoxia. Saccadic velocity decreased with time-on-duty in both groups, in correlation with subjective fatigue. Intersaccadic drift velocity increased in the hypoxia group only, suggesting that acute hypoxia diminishes eye stability, independently of fatigue. Our results suggest that intersaccadic drift velocity could serve as a biomarker of acute hypoxia. These findings may also contribute to our understanding of the relationship between hypoxia episodes and central nervous system impairments.