Chapter 24 - Model of optokinetic responses involving two different visual motion processing pathways

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Abstract

To understand visual motion processing underlying the optokinetic response (OKR), we developed a biomimetic model that reproduces the findings from behavioral experiments. We recorded OKRs induced by drifting gratings with different spatiotemporal frequencies from humans and non-human primates. The characteristics of the initial open-loop responses and the closed-loop eye velocity gains were analyzed using a model developed in this study. The model consists of two pathways with different dynamics. One mediates the transient response (transient pathway) and the other the sustained response (sustained pathway). Each pathway has a different spatiotemporal frequency dependence. Assuming there are different visual sensitivities for these pathways, one tuned to lower spatial and higher temporal frequencies on the retina and the other tuned to stimulus velocity, we successfully reproduced the course of OKRs. Our results suggest that two different neural circuitries/populations contribute to visual processing in the different stages of OKRs.

Introduction

The optokinetic response (OKR) is a reflexive eye movement induced by motion of a wide visual field (Collewijn, 1991). When observers are exposed to sustained visual motion, an alternating pattern of slow and fast eye movements emerges (slow and quick phases), called optokinetic nystagmus (OKN). In primates, slow-phase eye velocity of the OKN in response to a velocity step is thought to be composed of two components: a rapid rise and a slower rise component (Cohen et al., 1977). Anatomical and physiological studies have revealed that the monkey OKR is mediated by cortical and subcortical pathways (Fuchs and Mustari, 1993). It has been suggested that the cortical pathway contributes primarily to the former component, whereas the subcortical pathway is related more to the latter (Fuchs and Mustari, 1993; Takemura et al., 2007).

The OKR in humans is strongly dependent on visual features of moving images. The spatial frequency and speed of motion stimuli affect the slow-phase velocity gain of OKN (Van Die and Collewijn, 1986). The ocular following response (OFR) to sudden motion of a large visual field, which is closely related to the initial OKR, is also sensitive to spatial and temporal frequencies (Gellman et al., 1990; Miles et al., 1986; Miura et al., 2006, Miura et al., 2009, Miura et al., 2014; Sheliga et al., 2005). These dependences seem to reflect a mixture of characteristics of cortical and subcortical visual processing. The pretectum and the accessory optic system, to which directionally selective ganglion cells of the retina project (Yonehara et al., 2008), are closely related to OKN (Mustari and Fuchs, 1990; Simpson, 1984). The cortical MT (middle temporal) and MST (medial superior temporal) areas are important in visual motion processing and critically involved in smooth eye movement systems (Dursteler and Wurtz, 1988; Ilg, 2008; Kawano et al., 1994; Takemura et al., 2007). However, it is still unclear how spatiotemporal frequency dependences of OKRs are formed over the entire course of the responses.

The purpose of this study is to elaborate our understanding of sensory processing for OKRs. We describe visual dependences of OKRs in terms of spatiotemporal frequency characteristics in two different phases of the responses, i.e., at the initial development and at the later closed-loop stage. To interpret the observed data within a consistent framework during the course of the OKR, we developed a biomimetic model that involves a dual pathway of different dynamics (transient and sustained), each pathway with spatiotemporal frequency characteristics of its own. We herein show that the model can simulate visual dependences of OKRs successfully when these two pathways have different sensitivities to the spatiotemporal frequency of the visual stimulus on the retina, suggesting that two different neural circuitries/populations contribute to visual processing at different stages of OKRs.

Section snippets

Subjects and eye movement recording

Eye movements were recorded in three human subjects (25–42 years old) and two Japanese monkeys (Macaca fuscata, 6–8 kg) using an electromagnetic induction technique (Fuchs and Robinson, 1966). Voltage signals encoding the horizontal and vertical eye positions were recorded at 1 kHz. The human experiments were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki. All experimental procedures were approved by the Kyoto University Graduate School and

Spatiotemporal frequency dependence of OKRs

Drifting sinusoidal gratings elicited OKRs, generally with nystagmus profiles (Fig. 1A and B). The response began with a smooth movement (slow phase) that was interrupted by a fast movement (quick phase). Then, slow and quick phases alternated. The slow-phase eye velocity increased as time progressed and reached a steady state by 0.6 s after motion onset in this example. In the following, we focus on eye movements during slow phases.

The slow-phase eye velocity depended on the spatiotemporal

Discussion

The OFR depends strongly on the spatial and temporal frequencies of the visual stimuli; the optimal spatial frequency is ~ 0.25 c/d and the optimal temporal frequency > 10 Hz (Gellman et al., 1990; Miles et al., 1986; Miura et al., 2009, Miura et al., 2014; Sheliga et al., 2005). In this chapter, the initial OKR showed similar characteristics, although the optimal spatial frequency for humans was a little lower on average. Van Die and Collewijn (1986) demonstrated that the closed-loop gain

Acknowledgment

This work was supported by JSPS KAKENHI (15K06709 and 16H03297).

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