Ординатура / Офтальмология / Английские материалы / Eye, Retina, and Visual System of the Mouse_Chalupa, Williams_2008

Figure 18.6 Burst and tonic firing in the visual responses of mouse dLGN cells. A, Identifying burst and tonic spikes in extracellularly recorded dLGN cell responses. Criteria based on spike timing, taken from intracellular recordings in vivo (Lu et al., 1992), were used to categorize events: bursts were preceded by >100 ms of silence and consisted of ≥2 spikes separated by interspike intervals (ISIs) of <4 ms. Spikes fired by a single mouse dLGN cell to a sinusoidal grating stimulus are plotted here based on their preceding and following ISIs, and it is clear that the criteria segregate preexisting patterns of spiking behavior. Spikes in box 1 are the first spikes in bursts, those in box 2 are mainly the middle spikes of bursts, and those in box 3 are mainly the last spikes in bursts. All other spikes form part of tonic firing. TF, stimulus temporal

functional similarities to that in other mammals leaves open the possibility for some interesting genetic experiments. What happens to mouse vision, for example, when the calcium channel underlying IT is knocked out in the thalamus (Kim et al., 2001)? At the geniculate level, given the subtle coding differences noted earlier, maybe no drastic effects would be observed, but at the cortical or behavioral level, what would be the consequence of dLGN cells that were always in tonic mode? If the knockout could be more specific—perhaps to TCs or interneurons only—we could start to strip down the functional role of IT even further. And even if there are no visual functional differences between burst and tonic firing, an IT knockout would be the ideal model to show this. Other fun manipulations also spring to mind. How about mutating the HCN channels underlying Ih (e.g., Meuth et al., 2006b) to specifically control rhythmic bursting in an intact preparation? Or producing mutations in any of the modulatory neurotransmitter receptors that

frequency. B, Bursting correlates positively with stimulus detection ability. The receiver operating characteristic (ROC) curves here take responses fired by a single cell to a drifting sinusoidal grating stimulus and, for a given spike count, plot the probability P(hit) of attaining this count during stimulus presentation versus the probability P(false alarm) of attaining this count during an equal period of spontaneous activity. The area under the resulting curve (ROC area) then provides a nonparametric measure of the cell’s ability to distinguish visual from nonvisual stimulation. This ability correlates positively with the burstiness of a mouse dLGN cell: the ROC area increases as the percentage of stimulus cycles with bursts increases. (From Grubb and Thompson, 2005.)

affect TC firing mode? The easiest way to look for causality in the functional role of properties produced by a single molecule may well be to delete that molecule and see what happens. And, for the moment, those experiments are easiest by far in the mouse.

Conclusion

Currently, a good outline of mouse dLGN physiology exists. Neurons in the structure possess all the major intrinsic physiological features of thalamic cells, and knowledge of how these features can be modulated to produce changes in firing rate or firing mode is advancing nicely. We know a great deal about the spatial and temporal features of retinogeniculate input and are able to relate this information (at least indirectly) to the fundamental quantitative visual response properties of mouse dLGN cells. Finally, the features of the two major thalamic firing modes, burst and tonic, and their

possible contributions to visual processing have started to be investigated in the structure.

However, much remains to be uncovered. The areas in which our understanding of geniculate function is far ahead in other species have been highlighted where appropriate in this chapter, but that still leaves a long list of things the physiologist might like to know about the mouse dLGN. Simply in terms of visual response properties, we know nothing about chromatic responses in the mouse dLGN, the responses of mouse dLGN neurons to natural scene stimuli, the effects of contextual influences on mouse dLGN RF properties, the coding possible in populations of mouse dLGN cells, or how any or all of these properties relate to the mouse’s visual behavior. In terms of circuitry, our knowledge of the oscillatory properties of mouse dLGN cells and networks is hugely lacking. It is also difficult to fully understand the functions of the mouse dLGN when we have so little quantitative data on the visual properties of both its retinal input and of its cortical target neurons, and no information at all about physiology in a major provider of thalamic inhibition, the TRN. No nucleus is an island.

The potential benefits of obtaining this information are huge. With the advent of more and more sophisticated techniques for controlling gene expression in a spatially and temporally regulated manner (Lewandowski, 2001; Aronoff and Petersen, 2006), the mouse dLGN offers a good model of both visual processing and thalamic function in which we can investigate the effects of single molecules on physiological phenomena. The hope is that in the near future, studies of wild-type and mutant mouse dLGN physiology will lead us closer to an understanding of what the visual thalamus actually does.

acknowledgments I thank Murray Sherman and Ian Thompson for their helpful comments.

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When animals orient to objects of particular interest in their immediate environment, combined movements of the eyes, head, trunk, and limbs are induced. If movements of the head, trunk, and limbs are then restrained, isolated eye movement can be investigated as a component of such orienting movements. It is under this condition of restraint that saccadic eye movements are studied in cats, monkeys, and humans (Sparks, 1999).

In general, saccadic eye movement is a rapid shift of eye position to capture an object in the visual environment. Studying saccadic eye movements as a way to understand the neural mechanisms underlying control of accurate movements has several advantages. First, the muscular mechanics of the oculomotor control system are relatively simple when compared with limb movement controllers. Therefore, quantification of movements is relatively easy; the parameter to calculate is the angle of eyeball direction. Second, electrical stimulation of part of the underlying neural circuits can mimic naturally evoked movements. Finally, much is now known about the properties of identified neuronal elements of the related circuits. The neuronal circuitries underlying the generation of saccades have been intensively studied, especially in cats and monkeys (Wurtz and Goldberg, 1989; Moschovakis et al., 1996; Scudder et al., 2002; Sparks, 2002). Moreover, numerous theoretical models have been proposed to explain the saccadic system (Girard and Berthoz, 2005).

Several kinds of studies have been pursued in mice to investigate slow eye movements such as the vestibular-ocular reflex (VOR) and optokinetic responses and their adaptive control mechanism (De Zeeuw et al., 1998; Katoh et al., 1998; Blazquez et al., 2004; Stahl, 2004). In contrast to these slow eye movement systems and, despite some previous reports (Mitchiner et al., 1976; Balkema et al., 1984; GrusserCornehls and Bohm, 1988), quantitative and systematic analyses of saccades have not been carried out in mice. The mouse is an ideal experimental model animal in which to study the molecular mechanism of saccade control. However, saccades have not been thought to be important in mice, because mice have a poor fovea and are lateral-eyed, and they are thought to use mainly head movements for orientation.

We have recently developed a PC-based high-speed video-oculography system to perform online analysis of eye movements of mice with high temporal resolution. Using this system, we are able to investigate the ocular component of orienting movements that are saccade-like rapid eye movements (SLREMs), and we have conducted quantitative and systematic analyses of SLREMs in head-fixed mice (Sakatani and Isa, 2004, 2007). Our results suggest that mice have neural circuits for the generation of REMs that share common mechanisms with those in other animal species. Because the behavioral meaning of REMs in mice under natural conditions is still unclear, we use the term SLREM rather than saccade in this chapter, emphasizing our focus on the kinematics of these eye movements.

Saccades are controlled by large-scale neural networks distributed widely over many brain areas, including the brainstem, basal ganglia, frontal and parietal cortex, and cerebellum, and these circuits have not been studied in mice or rats. Among the various components of these networks, the superior colliculus (SC) is presumed to be a pivotal brainstem structure for determination of saccade vectors. We have recently found that electrical stimulation of the SC induce SLREMs in mice.

In addition, over the past decade considerable progress was made in understanding signal processing in local circuits of the mammalian SC by applying whole-cell patch-clamp recording and intracellular labeling techniques in the rodent slice preparation (for reviews, see Isa, 2002; Isa et al., 2003; Helms et al., 2004; Isa and Sparks, 2006).

In this chapter, we introduce recent research conducted by our group on the neural system for the control of orienting movements in rodents and discuss structure-function relationships of the related neural circuits, mainly focusing on the SC.

Saccade-like rapid eye movements in mice

Measurement of Rapid Eye Movements Although the existence of SLREMs has been reported in mice (Mitchiner et al., 1976; Balkema et al., 1984; Grusser-Cornehls and Bohm, 1988), no previous work has focused on quantitative

measurements of REMs in this species except for the fast phase of the VOR (Stahl, 2004). It is difficult to measure REMs stably and continuously in such small animals. Our recent development of a PC-based high-speed videooculography technique enabled us to perform online analysis of spontaneously evoked SLREMs in mice in a quantitative manner (Sakatani and Isa, 2004).

Figure 19.1 shows schematically the procedures used to measure eye movements in mice. Movements of the right eye are monitored with a high-speed CCD camera (CS3720, Toshiba TELI Corp., Tokyo) at a sampling rate of 240 frames/s placed at an angle of 60° laterally from the body axis and 30° down from the horizontal plane (figure 19.1A). The awake animal is placed in a stereotaxic apparatus with the body loosely restrained on a soft rubber sheet, so that the legs hang in the air, not touching anything else. The animal’s head is fixed painlessly to the platform with a brass rod attached to a manipulator (figure 19.1B).

Captured images of the eyes are processed online using custom software that detects the center of the pupil by fitting a circular function to the pupil boundary and tracks the eye position online (figure 19.1C). Subsequently, pupillary displacement in the two-dimensional video plane is geometrically converted to angular rotation of the eyeball by estimating its rotation center based on the anatomical eyeball model (figure 19.1D). Detailed procedures can be found in the original publication by Sakatani and Isa (2004).

Spontaneous SLREMs in Mice Eye movement trajectories were successfully recorded and analyzed in C57BL/ 6JjmsSlc mice in a quantitative manner using the highspeed video-oculography technique (figure 19.1E). Naturally evoked, spontaneous SLREMs were observed in a dimly lit (<100 lux), sound-attenuated box (figure 19.1F). Arrowheads in the figure indicate the occurrence of SLREMs.

Figure 19.1 Spontaneously evoked saccade-like rapid eye movements (SLREMs). A, Top-view (top) and back-view (bottom) diagrams of the video coordinate system. The optical axis of the camera is shown as a white arrow. The movements of the right eye were monitored with a high-speed (240 frames/s) video camera. A CCD camera (shaded box) was set at an angle of 60° right with regard to the body axis and 30° down against the horizontal plane. B, A mouse was loosely restrained with a rubber sheet and the head was fixed with a brass rod and a pedestal. C, Image processing software detected a boundary of the pupil (dotted circle in bottom panel) and its

center ( ) online from a captured frame image (top panel). Angular eye positions were then calculated based on an anatomical eyeball model (Sakatani and Isa, 2004). D, Anatomy of the eyeball in the mouse. The effective rotation radius (Reffective) is calculated from the pupil radius (Rpupil: obtained from a video image) and lens radius (Rlens: 1.25 mm). The radius is 1.6 mm and δ is 0.1 mm in this model. E, Eye trajectories in the x-y plane. Each number represents the corresponding SLREM shown in F. F, Horizontal (top) and vertical (bottom) eye positions. SLREMs were observed at the time indicated by arrowheads (top).

Male C57BL/6jmsSlc mice (n = 7) spontaneously made SLREMs at a nearly constant rate under the recording condition. On average, spontaneous SLREMs in all animals in the head-fixed condition occurred at a frequency of 7.5 ± 4.7/min (n = 7) with a median amplitude of 14.3 ± 2.1°, mainly in the horizontal direction (88%; −45 +45° and +135 +225° in polar coordinates). The observed maximal eye deviation from the central position ranged from 66.7° to 99.6° in the horizontal plane and from 39.8° to 59.8° in the vertical plane. The observed maximum oculomotor range in the horizontal direction in the mouse is relatively wider than in the cat (50°: Guitton et al., 1980) or rabbit (30°: Collewijn, 1970) and is close to the oculomotor range in humans (110°: Guitton and Volle, 1987).

The eye often returned toward the central position by a centripetal saccade or drifted back slowly toward the center of the orbit after the SLREM. Thus, SLREMs usually occurred from the center of the orbit.

To investigate the effect of auditory and visual stimuli on triggering SLREMs, an attempt was made to check the ability of these stimuli to induce SLREMs. Although mice responded with SLREMs when presented with a novel stimulus (sound or light), they tended to become habituated to these stimuli quickly, and then they became almost unresponsive to these sound or visual stimuli.

The kinematics of SLREM can be defined on the basis of velocity-amplitude characteristics (Bahill et al., 1975). Figure 19.2A shows velocity profiles of SLREMs with four different amplitudes in a single animal.

The peak velocity of the SLREM relative to its amplitude increased in mice in a way similar to that seen in other mammals, such as humans, monkeys, and cats. Even though there is a similar tendency among these mammals, mice exhibited some unique characteristics. The peak velocity did not saturate, at least in the range of observation (2–50°). The velocity profile of SLREMs with different amplitudes exhibited a characteristic appearance. Figure 19.2B shows an example of the relationship between amplitude and peak velocity in a single animal. This relationship exhibited a nearly linear correlation (correlation coefficient 0.92 in the nasal direction and 0.92 in the temporal direction) and could be well fitted by linear regression. The peak velocity increased almost linearly with a slope of 52.2 deg/s-deg in the nasal direction and 34.7 deg/s-deg in the temporal direction. The amplitude and peak velocity of SLREMs were found to be linearly correlated in all seven animals tested (correlation coefficient 0.91 ± 0.03 in the nasal direction and 0.85 ± 0.07 in the temporal direction), with a mean slope of 51.3 ± 3.9 deg/s-deg in the nasal direction and 31.7 ± 3.2 deg/s-deg in the temporal direction. These values are much higher than those recorded in other mammals, such as human: 20 deg/s-deg (Boghen et al., 1974), monkey: 40 deg/s-deg (Fuchs, 1967), cat: 10 deg/s-deg (Evinger and Fuchs, 1978),

rabbit: 13 deg/s-deg (Collewijn, 1970), and rat: 20–40 deg/ s-deg (Fuller, 1985; Hikosaka and Sakamoto, 1987).

These results suggest that the mouse may have neural circuits for the generation of REM that share some common properties with those in cats, monkeys, and humans. However, there might also be some different properties related to the control of SLREM duration, which should be a subject of future studies.

The difference between the nasal and temporal directions was significant (Tukey’s test: P < 0.01). In humans, the kinematics of centrifugal saccadic eye movements differ from those of centripetal saccades (Pelisson and Prablanc, 1988). In a recent study on the VOR in mice, Stahl (2004) also noted that abducting fast phases of nystagmus tended to be slower than adducting fast phase.

Electrically Induced SLREMs in Mice The SC is comprised of several layers. The dorsal three layers—the stratum zonale (SZ), the stratum griseum superficiale (SGS), and the stratum opticum (SO)—are designated the superficial layers and receive visual input either directly from the retina or indirectly from the visual cortex. The next two layers, the stratum griseum intermediale (SGI) and the stratum album intermediale (SAI), ventral to the superficial layers are designated intermediate layers, and the ventralmost two layers, the stratum griseum profundum (SGP) and the stratum album profundum (SAP), are designated deep layers. The intermediate and deep layers send descending outputs to the brainstem reticular formation and spinal cord. In monkeys, it is well known that a population of neurons in the intermediate and deep layers exhibits high-frequency burst discharges starting about 20 ms prior to contraversive saccades (Schiller and Stryker, 1972; Wurtz and Goldberg, 1972) and that repetitive electrical stimulation of these layers evokes saccades (Robinson, 1972). To clarify whether the SC controls SLREM in mice, we tested the effects of repetitive electrical stimulation of the SC in awake, headfixed mice.

Electrical stimulation of the intermediate layer of the SC can induce eye movements closely resembling spontaneously evoked SLREMs in awake, head-fixed mice (figure 19.3). As shown in figure 19.3A, SLREMs were induced above a certain threshold stimulus intensity (biphasic current, 333 Hz, 180 ms duration, 0.1 ms negative and 0.1 ms positive pulse duration, 20 μA in this case) of stimulation. Increasing the stimulus current beyond the threshold shortened latencies of the induced SLREMs from 96 ms to 42 ms (from the onset of stimulation), whereas the amplitude of the eye movements remained constant at higher stimulus intensities. The average latency was 59.8 ± 22.3 ms, and the latency was never shorter than 16.7 ms. As exemplified in figure 19.3B, the threshold stimulus intensity to induce the SLREM was systematically examined at different depths in the SC. Threshold current

Figure 19.2 Peak velocity versus amplitude relationships of spontaneously evoked and electrically induced SLREMs. A, Examples of velocity profiles of spontaneously evoked SLREMs of different size and velocity. Each velocity trace is aligned with the onset of SLREM determined by a velocity threshold above 100 deg/s. The amplitude of spontaneous SLREMs is 9.7°, 20.8°, 29.2°, and 39.5° (top to bottom). The peak velocity is 2,222, 1,685, 1,284, and 851 deg/s, respectively. B, Example of the peak velocity versus amplitude plot in a single animal. Solid line indicates the linear regression line. C, Velocity profile of electrically induced SLREMs. The

intensities were lower in the intermediate and deep layers. The threshold was often lower than 10 μA in these layers. This suggests that the cell bodies or axons of projection neurons responsible for induction of SLREMs are located in the intermediate and deep layers of the SC in mice as in other species.

We examined the motor representation of various rostrocaudal and mediolateral locations in the SC (figure 19.3C and D) at the depth of the intermediate layer. The trajectories of eye movements evoked at different sites in a single mouse SC are shown in figure 19.3D. Since the left SC was stimu-

amplitude of the SLREM is 6°, 9°, 21°, and 29° (top to bottom). Note that the velocity curve has a nearly bell-shaped profile. A second peak observed for 21° movements reflects overshoot. D, Relationship between the peak velocity and amplitude of the electrically induced SLREM. The entire data set pooled across 31 sites in 7 animals is plotted in the nasal direction (top, n = 106) and temporal direction (bottom, n = 121) separately. Each data point represents the value of peak velocity in an individual stimulation trial. A linear regression line is superimposed (solid line).

lated and movements of the right eye were recorded, an ipsiversive SLREM means movement in the nasal direction, while a contraversive movement means temporal movement in this figure. From most stimulation sites in the SC, SLREMs were evoked in the contraversive (temporal) direction. The amplitude of evoked REMs became larger when more caudal sites were stimulated and smaller at more rostral sites, showing a similar motor representation pattern to that in other mammals. These results suggest that mice are equipped with saccade generator circuits downstream of the SC. On the other hand, nasal (ipsiversive) SLREMs could be induced

Figure 19.3 SLREMs induced by stimulation of the superior colliculus (SC). A, Eye position traces of an electrically induced REM in response to different current intensities of SC stimulation. The threshold current (T) to evoke the eye movements was 20 μA at the site of electrical stimulation (b). Stimulation was applied at 333 Hz for 180 ms duration as indicated by the thick black line along the time axis (individual pulse width was 0.2 ms). Top to bottom, 0.5 × T, 1.0 × T, 1.5 × T, and 2.0 × T, respectively. B, Threshold current intensities to induce SLREMs at various points in the SC in a single animal are presented on a coronal section. The threshold current intensities are represented by the size of the symbol. dSC, deeper layers of the SC; SAI, stratum album intermediale; SGI,

from the rostromedial portion (stimulation sites 3 and 6). In this region, the visual representation of the superficial layer is the same as that of the visual field with the opposite SC (Dräger and Hubel, 1975). Therefore, this region represents the ipsilateral visual field. Thus, in mice, the SC on one side likely controls both contraversive and ipsiversive SLREMs, in agreement with the overlying retinotopic map in the superficial layer (Dräger and Hubel, 1975).

The velocity profile of the electrically induced SLREMs had a somewhat bell-shaped curve, which was reported as a

stratum griseum intermediale; SGP, stratum griseum profundum; SGS, stratum griseum superficiale; SO, stratum opticum; sSC, superficial layers of the SC; SZ, stratum zonale. C, Schematic drawing of the experimental arrangement (top) and dorsal view of the left SC, showing the stimulation sites (bottom). Circled numbers indicate penetrations of the stimulation electrode plotted on the dorsal view of the left SC. D, Examples of eye movements evoked at different sites in a mouse SC. The stimulation sites are indicated with numbers corresponding to those in C. Open circles indicate terminal points of the movements. Dotted lines indicate the horizontal and vertical midline determined arbitrarily as shown in C.

typical feature of SLREMs in other mammals (see Wurtz and Goldberg, 1989) (see figure 19.2C). Larger eye movements often tended to overshoot, resulting in the second peak of the velocity profile (see figure 19.2C). For SLREMs with larger amplitude, the peak velocity was higher than that associated with smaller SLREMs. This relationship was clearly demonstrated in the pooled data from a single animal (nine tracks) in figure 19.2D. Also, the peak velocities of SLREMs differed depending on the direction of the SLREM. The relationship between the peak velocity and