scholarly journals Elimination of the error signal in the superior colliculus impairs saccade motor learning

2018 ◽  
Vol 115 (38) ◽  
pp. E8987-E8995 ◽  
Author(s):  
Yoshiko Kojima ◽  
Robijanto Soetedjo

When movements become dysmetric, the resultant motor error induces a plastic change in the cerebellum to correct the movement, i.e., motor adaptation. Current evidence suggests that the error signal to the cerebellum is delivered by complex spikes originating in the inferior olive (IO). To prove a causal link between the IO error signal and motor adaptation, several studies blocked the IO, which, unfortunately, affected not only the adaptation but also the movement itself. We avoided this confound by inactivating the source of an error signal to the IO. Several studies implicate the superior colliculus (SC) as the source of the error signal to the IO for saccade adaptation. When we inactivated the SC, the metrics of the saccade to be adapted were unchanged, but saccade adaptation was impaired. Thus, an intact rostral SC is necessary for saccade adaptation. Our data provide experimental evidence for the cerebellar learning theory that requires an error signal to drive motor adaptation.

1988 ◽  
Vol 72 (3) ◽  
Author(s):  
D.M. Waitzman ◽  
T.P. Ma ◽  
L.M. Optican ◽  
R.H. Wurtz

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniel H. Blustein ◽  
Ahmed W. Shehata ◽  
Erin S. Kuylenstierna ◽  
Kevin B. Englehart ◽  
Jonathon W. Sensinger

AbstractWhen a person makes a movement, a motor error is typically observed that then drives motor planning corrections on subsequent movements. This error correction, quantified as a trial-by-trial adaptation rate, provides insight into how the nervous system is operating, particularly regarding how much confidence a person places in different sources of information such as sensory feedback or motor command reproducibility. Traditional analysis has required carefully controlled laboratory conditions such as the application of perturbations or error clamping, limiting the usefulness of motor analysis in clinical and everyday environments. Here we focus on error adaptation during unperturbed and naturalistic movements. With increasing motor noise, we show that the conventional estimation of trial-by-trial adaptation increases, a counterintuitive finding that is the consequence of systematic bias in the estimate due to noise masking the learner’s intention. We present an analytic solution relying on stochastic signal processing to reduce this effect of noise, producing an estimate of motor adaptation with reduced bias. The result is an improved estimate of trial-by-trial adaptation in a human learner compared to conventional methods. We demonstrate the effectiveness of the new method in analyzing simulated and empirical movement data under different noise conditions.


1998 ◽  
Vol 80 (5) ◽  
pp. 2405-2416 ◽  
Author(s):  
Josh Wallman ◽  
Albert F. Fuchs

Wallman, Josh and Albert F. Fuchs. Saccadic gain modification: visual error drives motor adaptation. J. Neurophysiol. 80: 2405–2416, 1998. The brain maintains the accuracy of saccadic eye movements by adjusting saccadic amplitude relative to the target distance (i.e., saccade gain) on the basis of the performance of recent saccades. If an experimenter surreptitiously moves the target backward during each saccade, thereby causing the eyes to land beyond their targets, saccades undergo a gradual gain reduction. The error signal driving this conventional saccadic gain adaptation could be either visual (the postsaccadic distance of the target from the fovea) or motoric (the direction and size of the corrective saccade that brings the eye onto the back-stepped target). Similarly, the adaptation itself might be a motor adjustment (change in the size of saccade for a given perceived target distance) or a visual remapping (change in the perceived target distance). We studied these possibilities in experiments both with rhesus macaques and with humans. To test whether the error signal is motoric, we used a paradigm devised by Heiner Deubel. The Deubel paradigm differed from the conventional adaptation paradigm in that the backward step that occurred during the saccade was brief, and the target then returned to its original displaced location. This ploy replaced most of the usual backward corrective saccades with forward ones. Nevertheless, saccadic gain gradually decreased over hundreds of trials. Therefore, we conclude that the direction of saccadic gain adaptation is not determined by the direction of corrective saccades. To test whether gain adaptation is a manifestation of a static visual remapping, we decreased the gain of 10° horizontal saccades by conventional adaptation and then tested the gain to targets appearing at retinal locations unused during adaptation. To make the target appear in such “virgin territory,” we had it jump first vertically and then 10° horizontally; both jumps were completed and the target spot extinguished before saccades were made sequentially to the remembered target locations. Conventional adaptation decreased the gain of the second, horizontal saccade even though the target was in a nonadapted retinal location. In contrast, the horizontal component of oblique saccades made directly to the same virgin location showed much less gain decrease, suggesting that the adaptation is specific to saccade direction rather than to target location. Thus visual remapping cannot account for the entire reduction of saccadic gain. We conclude that saccadic gain adaptation involves an error signal that is primarily visual, not motor, but that the adaptation itself is primarily motor, not visual.


2002 ◽  
Vol 87 (2) ◽  
pp. 679-695 ◽  
Author(s):  
Robijanto Soetedjo ◽  
Chris R. S. Kaneko ◽  
Albert F. Fuchs

There is general agreement that saccades are guided to their targets by means of a motor error signal, which is produced by a local feedback circuit that calculates the difference between desired saccadic amplitude and an internal copy of actual saccadic amplitude. Although the superior colliculus (SC) is thought to provide the desired saccadic amplitude signal, it is unclear whether the SC resides in the feedback loop. To test this possibility, we injected muscimol into the brain stem region containing omnipause neurons (OPNs) to slow saccades and then determined whether the firing of neurons at different sites in the SC was altered. In 14 experiments, we produced saccadic slowing while simultaneously recording the activity of a single SC neuron. Eleven of the 14 neurons were saccade-related burst neurons (SRBNs), which discharged their most vigorous burst for saccades with an optimal amplitude and direction (optimal vector). The optimal directions for the 11 SRBNs ranged from nearly horizontal to nearly vertical, with optimal amplitudes between 4 and 17°. Although muscimol injections into the OPN region produced little change in the optimal vector, they did increase mean saccade duration by 25 to 192.8% and decrease mean saccade peak velocity by 20.5 to 69.8%. For optimal vector saccades, both the acceleration and deceleration phases increased in duration. However, during 10 of 14 experiments, the duration of deceleration increased as fast as or faster than that of acceleration as saccade duration increased, indicating that most of the increase in duration occurred during the deceleration phase. SRBNs in the SC changed their burst duration and firing rate concomitantly with changes in saccadic duration and velocity, respectively. All SRBNs showed a robust increase in burst duration as saccadic duration increased. Five of 11 SRBNs also exhibited a decrease in burst peak firing rate as saccadic velocity decreased. On average across the neurons, the number of spikes in the burst was constant. There was no consistent change in the discharge of the three SC neurons that did not exhibit bursts with saccades. Our data show that the SC receives feedback from downstream saccade-related neurons about the ongoing saccades. However, the changes in SC firing produced in our study do not suggest that the feedback is involved with producing motor error. Instead, the feedback seems to be involved with regulating the duration of the discharge of SRBNs so that the desired saccadic amplitude signal remains present throughout the saccade.


2020 ◽  
Vol 124 (6) ◽  
pp. 2022-2051 ◽  
Author(s):  
Reza Shadmehr

The cerebellum resembles a feedforward, three-layer network of neurons in which the “hidden layer” consists of Purkinje cells (P-cells) and the output layer consists of deep cerebellar nucleus (DCN) neurons. In this analogy, the output of each DCN neuron is a prediction that is compared with the actual observation, resulting in an error signal that originates in the inferior olive. Efficient learning requires that the error signal reach the DCN neurons, as well as the P-cells that project onto them. However, this basic rule of learning is violated in the cerebellum: the olivary projections to the DCN are weak, particularly in adulthood. Instead, an extraordinarily strong signal is sent from the olive to the P-cells, producing complex spikes. Curiously, P-cells are grouped into small populations that converge onto single DCN neurons. Why are the P-cells organized in this way, and what is the membership criterion of each population? Here, I apply elementary mathematics from machine learning and consider the fact that P-cells that form a population exhibit a special property: they can synchronize their complex spikes, which in turn suppress activity of DCN neuron they project to. Thus complex spikes cannot only act as a teaching signal for a P-cell, but through complex spike synchrony, a P-cell population may act as a surrogate teacher for the DCN neuron that produced the erroneous output. It appears that grouping of P-cells into small populations that share a preference for error satisfies a critical requirement of efficient learning: providing error information to the output layer neuron (DCN) that was responsible for the error, as well as the hidden layer neurons (P-cells) that contributed to it. This population coding may account for several remarkable features of behavior during learning, including multiple timescales, protection from erasure, and spontaneous recovery of memory.


1998 ◽  
Vol 79 (6) ◽  
pp. 3060-3076 ◽  
Author(s):  
Martin Paré ◽  
Daniel Guitton

Paré, Martin and Daniel Guitton. Brain stem omnipause neurons and the control of combined eye-head gaze saccades in the alert cat. J. Neurophysiol. 79: 3060–3076, 1998. When the head is unrestrained, rapid displacements of the visual axis—gaze shifts (eye-re-space)—are made by coordinated movements of the eyes (eye-re-head) and head (head-re-space). To address the problem of the neural control of gaze shifts, we studied and contrasted the discharges of omnipause neurons (OPNs) during a variety of combined eye-head gaze shifts and head-fixed eye saccades executed by alert cats. OPNs discharged tonically during intersaccadic intervals and at a reduced level during slow perisaccadic gaze movements sometimes accompanying saccades. Their activity ceased for the duration of the saccadic gaze shifts the animal executed, either by head-fixed eye saccades alone or by combined eye-head movements. This was true for all types of gaze shifts studied: active movements to visual targets; passive movements induced by whole-body rotation or by head rotation about stationary body; and electrically evoked movements by stimulation of the caudal part of the superior colliculus (SC), a central structure for gaze control. For combined eye-head gaze shifts, the OPN pause was therefore not correlated to the eye-in-head trajectory. For instance, in active gaze movements, the end of the pause was better correlated with the gaze end than with either the eye saccade end or the time of eye counterrotation. The hypothesis that cat OPNs participate in controlling gaze shifts is supported by these results, and also by the observation that the movements of both the eyes and the head were transiently interrupted by stimulation of OPNs during gaze shifts. However, we found that the OPN pause could be dissociated from the gaze-motor-error signal producing the gaze shift. First, OPNs resumed discharging when perturbation of head motion briefly interrupted a gaze shift before its intended amplitude was attained. Second, stimulation of caudal SC sites in head-free cat elicited large head-free gaze shifts consistent with the creation of a large gaze-motor-error signal. However, stimulation of the same sites in head-fixed cat produced small “goal-directed” eye saccades, and OPNs paused only for the duration of the latter; neither a pause nor an eye movement occurred when the same stimulation was applied with the eyes at the goal location. We conclude that OPNs can be controlled by neither a simple eye control system nor an absolute gaze control system. Our data cannot be accounted for by existing models describing the control of combined eye-head gaze shifts and therefore put new constraints on future models, which will have to incorporate all the various signals that act synergistically to control gaze shifts.


2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Afsheen Khan ◽  
Sally A. McFadden ◽  
Mark Harwood ◽  
Josh Wallman

When saccadic eye movements consistently fail to land on their intended target, saccade accuracy is maintained by gradually adapting the movement size of successive saccades. The proposed error signal for saccade adaptation has been based on the distance between where the eye lands and the visual target (retinal error). We studied whether the error signal could alternatively be based on the distance between the predicted and actual locus of attention after the saccade. Unlike conventional adaptation experiments that surreptitiously displace the target once a saccade is initiated towards it, we instead attempted to draw attention away from the target by briefly presenting salient distractor images on one side of the target after the saccade. To test whether less salient, more predictable distractors would induce less adaptation, we separately used fixed random noise distractors. We found that both visual attention distractors were able to induce a small degree of downward saccade adaptation but significantly more to the more salient distractors. As in conventional adaptation experiments, upward adaptation was less effective and salient distractors did not significantly increase amplitudes. We conclude that the locus of attention after the saccade can act as an error signal for saccade adaptation.


1995 ◽  
Vol 73 (4) ◽  
pp. 1724-1728 ◽  
Author(s):  
A. A. Kustov ◽  
D. L. Robinson

1. Models of the saccadic system propose that there is an integration of the pulse signal, and there is good evidence that the integrator is reset gradually (Nichols and Sparks 1994, 1995). Other studies of the superior collicular contribution to the saccadic system have proposed a sensory, not motor, nature for its signal. 2. To test experimentally the resetting of the integrator and the nature of the collicular signal, we electrically stimulated the superior colliculus during periods of fixation and during the course of visually guided saccades. Trains of stimuli which were presented during periods of fixation evoked saccades with fixed vectors. Identical stimulation at the beginning of a visually guided saccade evoked saccades whose direction was rotated and amplitude extended from the fixed vector. The direction of the rotation was opposite that of the visually guided saccade, and the magnitude of this rotation could be as large as 80 degrees. 3. Stimulation which was applied at progressively later times during the visually guided saccade, evoked saccades with progressively smaller rotations and progressively less elongations. The time period during which saccades were modified persisted beyond the end of the visually guided saccade, when the eyes were stationary. Thus, we confirm the previous findings (Nichols and Sparks 1994, 1995; Robinson, 1972), that the end of the saccade is not a period of quiescence within the oculomotor pathways. 4. Our results confirm that the resetting of the integration of the saccade signal is gradual rather than abrupt. Furthermore, these data suggest that the superior colliculus signals a motor error.


PLoS Biology ◽  
2021 ◽  
Vol 19 (9) ◽  
pp. e3001400
Author(s):  
Akshay Markanday ◽  
Junya Inoue ◽  
Peter W. Dicke ◽  
Peter Thier

Purkinje cell (PC) discharge, the only output of cerebellar cortex, involves 2 types of action potentials, high-frequency simple spikes (SSs) and low-frequency complex spikes (CSs). While there is consensus that SSs convey information needed to optimize movement kinematics, the function of CSs, determined by the PC’s climbing fiber input, remains controversial. While initially thought to be specialized in reporting information on motor error for the subsequent amendment of behavior, CSs seem to contribute to other aspects of motor behavior as well. When faced with the bewildering diversity of findings and views unraveled by highly specific tasks, one may wonder if there is just one true function with all the other attributions wrong? Or is the diversity of findings a reflection of distinct pools of PCs, each processing specific streams of information conveyed by climbing fibers? With these questions in mind, we recorded CSs from the monkey oculomotor vermis deploying a repetitive saccade task that entailed sizable motor errors as well as small amplitude saccades, correcting them. We demonstrate that, in addition to carrying error-related information, CSs carry information on the metrics of both primary and small corrective saccades in a time-specific manner, with changes in CS firing probability coupled with changes in CS duration. Furthermore, we also found CS activity that seemed to predict the upcoming events. Hence PCs receive a multiplexed climbing fiber input that merges complementary streams of information on the behavior, separable by the recipient PC because they are staggered in time.


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