Biomedical subjects

Hiromitsu Tabata

Publications and source records attributed to Hiromitsu Tabata.

6 recordsLinked to original sources

PubMed2006

Preparatory gain modulation of visuomotor transmission for smooth pursuit eye movements in monkeys.

It has been reported that the visuomotor processing underlying the initiation of smooth pursuit eye movement is modulated in relation to the recent experience of eye movements: the initial pursuit eye velocity is larger after experiencing repeated pursuits than saccades. To assess which parameters of the previously executed pursuits play an essential role in modulating the gain of visuomotor transmission, we recorded the ocular responses of monkeys to a brief perturbing motion of the tracking target injected before the start of the eye movements. First, we compared the perturbation responses among the blocks in which the duration of executing pursuit was varied. We found that the response amplitude increased with the increase of the pursuit duration and it reached a plateau level at 100-200 ms of the duration. Second, a comparison of the perturbation responses in the blocks in which target velocity was different showed a gradual increase of the response as a function of the required pursuit velocity. Third, when the animals repeatedly performed pursuits, the response amplitude gradually increased with increasing interval between the appearance of the target and the onset of perturbation. On the other hand, such an increase was not observed when the animals repeatedly performed saccades. These results suggest that before initiating eye movements, the pursuit system modulates the gain of visuomotor transmission so as to be closely related to the properties of the repeatedly experienced eye movements and this gain modulation is triggered by the target's appearance.

Animals↗

PubMed2006

The effects of preceding moving stimuli on the initial part of smooth pursuit eye movement.

We examined whether there are any adaptive effects on the pursuit initiation after a prolonged exposure to moving visual stimuli. The eye movements of six human subjects were recorded with the scleral search-coil technique or a Dual Purkinje Image Eye-tracker system. A random-dot image appeared on a CRT monitor and moved coherently in one direction (rightward or leftward) at 10 deg/s for 4 s, while the subject fixated on a stationary target (conditioning stimulus). The screen was blanked for 0.2 s, and then the target stepped to the right or left of the center and moved 10 deg/s leftward or rightward. We measured change in the eye position over the open-loop period of the pursuit initiation. When the pursuit target moved in the same direction as the preceding visual stimulus, a significant reduction in the initial tracking responses (55.9% decrease on average) was found. We then studied in detail the properties of the motion adaptation in pursuit initiation by varying the visual conditions systematically and obtained the following findings. When the subjects tracked the target that moved at 10 deg/s, the pursuit initiation was affected not only by the conditioning stimulus of the same speed as the target, but also by those of different speeds. Further, the conditioning stimulus moving at 10 deg/s affected the pursuit initiation not only when the target moved with the same speed but also when it moved at different speeds (more remarkable for slower speeds). The effect of conditioning stimuli on the pursuit initiation was larger when the duration of the conditioning period was longer. The effect of conditioning stimuli decayed as the duration of the blank period became longer. The findings from the present study are consistent with the properties of neurons in the middle temporal area of monkeys.

Adaptation, Physiological↗

PubMed2005

The visual motion detectors underlying ocular following responses in monkeys.

Psychophysical evidence indicates that visual motion can be sensed by low-level (energy-based) and high-level (feature-based) mechanisms. The present experiments were undertaken to determine which of these mechanisms mediates the initial ocular following response (OFR) that can be elicited at ultra-short latencies by sudden motion of large-field images. We used the methodology of Sheliga, Chen, Fitzgibbon, and Miles (Initial ocular following in humans: A response to first-order motion energy. Vision Research, 2005a), who studied the initial OFRs of humans, to study the initial OFRs of monkeys. Accordingly, we applied horizontal motion to: (1) vertical square-wave gratings lacking the fundamental ("missing fundamental stimulus") and (2) vertical grating patterns consisting of the sum of two sinusoids of frequency 3f and 4f, which created a repeating pattern with beat frequency, f. Both visual stimuli share a critical property: when subject to 1/4-wavelength steps, their overall pattern (feature) shifts in the direction of the steps, whereas their major Fourier component shifts in the reverse direction (because of spatial aliasing). We found that the initial OFRs of monkeys to these stimuli, like those of humans, were always in the opposite direction to the 1/4-wavelength shifts, i.e., in the direction of the major Fourier component, consistent with detection by (low-level) oriented spatio-temporal filters as in the well-known energy model of motion analysis. Our data indicate that the motion detectors mediating the initial OFR have quantitatively similar properties in monkeys and humans, suggesting that monkeys provide a good animal model for the human OFR.

Animals↗

PubMed2005

A model of smooth pursuit in primates based on learning the target dynamics.

While the predictive nature of the primate smooth pursuit system has been evident through several behavioural and neurophysiological experiments, few models have attempted to explain these results comprehensively. The model we propose in this paper in line with previous models employing optimal control theory; however, we hypothesize two new issues: (1) the medical superior temporal (MST) area in the cerebral cortex implements a recurrent neural network (RNN) in order to predict the current or future target velocity, and (2) a forward model of the target motion is acquired by on-line learning. We use stimulation studies to demonstrate how our new model supports these hypotheses.

Animals↗

PubMed2005

Anticipatory gain modulation in preparation for smooth pursuit eye movements.

We studied the effect of the probability of required tracking on the gain of visuomotor transmission for pursuit initiation in monkeys. We recorded the ocular responses to a brief movement (perturbation) of a target located at an eccentric position from the central fixation spot. As soon as the central fixation spot went off, the animal was required to make a saccade to the target if it remained stationary or to track if it moved. The probability of an upcoming ramp motion of the target (horizontal, 20 degrees /sec), requiring pursuit, was varied (target motion probability [TMP] = 0, 0.25, 0.5, 0.75, and 1, which was fixed in a block). We found that the magnitude of the response to the perturbation increased gradually as the TMP increased. The initial pursuit response and the perturbation response showed very similar dependence on the TMP, suggesting that the response to the perturbation could be used as an index of the gain of visuomotor transmission for pursuit initiation. We also found that the changes in the ocular responses after the TMP was changed from one probability to another occurred rapidly (decay constant of only a few trials). These results suggest that the gain of visuomotor transmission in preparing for pursuit is rapidly modulated in accordance with the anticipated future need for pursuit.

Animals↗

PubMed2002

Computational study on monkey VOR adaptation and smooth pursuit based on the parallel control-pathway theory.

Much controversy remains about the site of learning and memory for vestibuloocular reflex (VOR) adaptation in spite of numerous previous studies. One possible explanation for VOR adaptation is the flocculus hypothesis, which assumes that this adaptation is caused by synaptic plasticity in the cerebellar cortex. Another hypothesis is the model proposed by Lisberger that assumes that the learning that occurs in both the cerebellar cortex and the vestibular nucleus is necessary for VOR adaptation. Lisberger's model is characterized by a strong positive feedback loop carrying eye velocity information from the vestibular nucleus to the cerebellar cortex. This structure contributes to the maintenance of a smooth pursuit driving command with zero retinal slip during the steady-state phase of smooth pursuit with gain 1 or during the target blink condition. Here, we propose an alternative hypothesis that suggests that the pursuit driving command is maintained in the medial superior temporal (MST) area based on MST firing data during target blink and during ocular following blank, and as a consequence, we assume a much smaller gain for the positive feedback from the vestibular nucleus to the cerebellar cortex. This hypothesis is equivalent to assuming that there are two parallel neural pathways for controlling VOR and smooth pursuit: a main pathway of the semicircular canals to the vestibular nucleus for VOR, and a main pathway of the MST-dorsolateral pontine nuclei (DLPN)-flocculus/ventral paraflocculus to the vestibular nucleus for smooth pursuit. First, we theoretically demonstrate that this parallel control-pathway theory can reproduce the various firing patterns of horizontal gaze velocity Purkinje cells in the flocculus/ventral paraflocculus dependent on VOR in the dark, smooth pursuit, and VOR cancellation as reported in Miles et al. at least equally as well as the gaze velocity theory, which is the basic framework of Lisberger's model. Second, computer simulations based on our hypothesis can stably reproduce neural firing data as well as behavioral data obtained in smooth pursuit, VOR cancellation, and VOR adaptation, even if only plasticity in the cerebellar cortex is assumed. Furthermore, our computer simulation model can reproduce VOR adaptation automatically based on a heterosynaptic interaction model between parallel fiber inputs and climbing fiber inputs. Our results indicate that different assumptions about the site of pursuit driving command maintenance computationally lead to different conclusions about where the learning for VOR adaptation occurs. Finally, we propose behavioral and physiological experiments capable of discriminating between these two possibilities for the site of pursuit driving command maintenance and hence for the sites of learning and memory for VOR adaptation.

Adaptation, Physiological↗