摘要
跳視的準確與否，和傳送到運動神經元之刺激訊號強度有關。如果在跳視的神經傳導路徑中，有某些神經元產生病變或退化，跳視將會失去其準確度。近來已有許多神經生理及神經解剖的研究資料陸續被提出，除了可以解釋跳視產生的神經生理機制外，也有助於跳視系統的模擬。
對於利用目前已發展的跳視模型來模擬人類跳視的過程中，一般會遭遇兩個問題。第一，幾乎所有的模型都是根據所量測知猴子數據所建立的，而猴子的跳視要比人類快許多。而調整模型某些參數可以有效地降低速度，產生較慢的跳視。第二，目前跳視模型的效率皆經由評估主序列之動態關係為基礎，並未考慮到其它參數（例如，加速時間和曲斜率）。腦幹模型乃是基於猴子外展神經核的生理資料所建構的模型，目前雖然已被應用在模擬人類警覺程度及猴子小腦病變的跳視軌跡上，但其所產生的速度軌跡之加速時間太短。而利用最小變異理論所發展出的模型加速時間則太長。
在本論文中，我們嘗試利用靈長類的小腦模型模擬人類的跳視軌跡。經由調整腦幹之相關參數及齒狀核動眼區（FOR）之輸出訊號，小腦模型可以有效產生加速時間和實驗數據非常一致之跳視軌跡。本研究發現整合齒狀核動眼區和腦幹之小腦模型可以有效地產生與現有的跳視軌跡非常一致的跳視軌跡。另外我們證明小腦在跳視加速相與減速相的時間調控扮演非常重要的角色。

Abstract

To attain saccadic accuracy, it requires that the control signals sent to the motor neurons have to be the right size to bring the fovea to the target. Accuracy will be lost if the neurons responsible for the generation of saccades are degenerated or disordered. Recently, neurophysiological and neuroanatomical data have been proposed to explain the mechanism of saccade generation, which are also helpful in modeling saccadic system.
There are two problems encountered for the existing models in generating accurate human saccades. Firstly, most models were built based on the data recorded from monkeys that were known to generate faster saccades than the human, several parameters have to be adjusted to fit slower saccades for the latter. Secondly, efficiency of the existing models was judged by the main sequence relations only, while other parameters such as acceleration time and skewness are not considered at all. For example, the brain stem model, which was constructed based on the primate abducean neurons and has been used extensively in simulating saccades with bluntness of vigilance state and lesioned cerebellum, generates velocity profiles with the acceleration time is too short, while it is too long for the model developed based on the minimum variance theory.
In this thesis, we intended to simulate human saccades by tuning the parameters based on the cerebellar model that were built according to the primate data. By tuning the parameters of the brain stem and the signals from the fastigial ocular region (FOR), the cerebellar model is able to generate velocity profile that the acceleration time is in agreement with the experiment. It is concluded that the cerebellar model, which integrates the FORs and the brain stem, can efficiently generate velocity profiles agreed with the recorded profiles. Also the cerebellum plays an important role in chronically regulating the time course of acceleration and deceleration phases of saccades.

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