Complex Spike Activity in the Oculomotor Vermis of the Cerebellum: A Vectorial Error Signal for Saccade Motor Learning?

Soetedjo, Robijanto; Kojima, Yoshiyuki; Fuchs, Albert F.

doi:10.1152/jn.90526.2008

Cited by 111 publications

(137 citation statements)

References 41 publications

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“…However, these findings do not necessarily indicate that the learning signal is purely visual. For example, as speculated in a recent study (Soetedjo et al, 2008), the "quasi-visual" cells in the deeper layers of the SC (Mays and Sparks, 1980;Sparks and Hartwich-Young, 1989), which exhibit apparent visual response Figure 10. a, Relationship between the direction of the endpoint shift (ordinate) and that of the optimal vector for SC stimulation site (abscissa) for 32 experiments, shown separately for left SC and right SC stimulation.…”

Section: Nature Of a Learning Signal And Its Transmission Pathway To mentioning

confidence: 68%

“…This tecto-olivo-cerebellar pathway has been postulated to transmit a learning signal in modeling studies (Dean et al, 1994;Fujita, 2005) but its function remains to be defined. Recent recording studies have provided strong support for the olivary relay of learning signals (Soetedjo and Fuchs, 2006;Soetedjo et al, 2008). Climbing fiber responses of Purkinje cells in the oculomotor vermis carry error information during saccade adaptation.…”

Section: Nature Of a Learning Signal And Its Transmission Pathway To mentioning

confidence: 99%

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Learning Signals from the Superior Colliculus for Adaptation of Saccadic Eye Movements in the Monkey

Kaku¹,

Yoshida²,

Iwamoto³

2009

J. Neurosci.

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Vital to motor learning is information about movement error. Using this information, the brain creates neural learning signals that instruct a plasticity mechanism to produce appropriate behavioral learning. Little is known, however, about brain structures that generate learning signals for voluntary movements. Here we show that signals from the superior colliculus (SC) can drive learning in saccadic eye movements in the monkey. Electrical stimulation of the SC deeper layers, subthreshold for evoking saccades, was applied immediately (ϳ60 ms) after the end of horizontal saccades in one or both directions. The target disappeared during saccades and remained invisible for 1 s to eliminate effects of postsaccadic visual information. Repetitive pairing of saccades with SC stimulation produced a marked, two-dimensional shift in movement endpoint relative to the target location. The elicited endpoint shift took a gradual, approximately exponential course over several hundred saccades as in visually induced saccade adaptation. The shift in movement endpoint remained nearly unchanged after stimulation was discontinued, indicating involvement of neuronal plasticity. When both rightward and leftward saccades were paired with stimulation, their endpoints shifted in similar directions. The endpoint shift was directed contralaterally to the stimulated SC. The direction and size of the endpoint shift depended on the stimulation site in the SC. We propose that the SC, a brainstem structure long known to be crucial for saccade execution, is involved in motor learning and sends signals that dictate the direction of adaptive shift in saccade endpoint.

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Section: Nature Of a Learning Signal And Its Transmission Pathway To mentioning

confidence: 68%

Section: Nature Of a Learning Signal And Its Transmission Pathway To mentioning

confidence: 99%

Learning Signals from the Superior Colliculus for Adaptation of Saccadic Eye Movements in the Monkey

Kaku¹,

Yoshida²,

Iwamoto³

2009

J. Neurosci.

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“…5. Reanalysis of data from Soetedjo et al (2008). This plot is a summary of n ϭ 18 Purkinje cells in the cerebellum showing the probability of a complex spike in response to errors of various sizes.…”

Section: Discussionmentioning

confidence: 99%

“…Complex spikes (CSs) that are generated by climbing fiber inputs onto Purkinje cells of the cerebellum are considered to be the biological representation of an error signal (Kitazawa et al 1998). However, when the probability of a CS was measured in response to various error sizes, the probability was high for small errors but decreased for larger errors (Soetedjo et al 2008). This result is inconsistent with the idea that CSs encode an error, and instead indicates that error size may play a role in plasticity of Purkinje cells.…”

mentioning

confidence: 99%

Sensitivity to prediction error in reach adaptation

Marko¹,

Haith²,

Harran³

et al. 2012

Journal of Neurophysiology

127

128

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It has been proposed that the brain predicts the sensory consequences of a movement and compares it to the actual sensory feedback. When the two differ, an error signal is formed, driving adaptation. How does an error in one trial alter performance in the subsequent trial? Here we show that the sensitivity to error is not constant but declines as a function of error magnitude. That is, one learns relatively less from large errors compared with small errors. We performed an experiment in which humans made reaching movements and randomly experienced an error in both their visual and proprioceptive feedback. Proprioceptive errors were created with force fields, and visual errors were formed by perturbing the cursor trajectory to create a visual error that was smaller, the same size, or larger than the proprioceptive error. We measured single-trial adaptation and calculated sensitivity to error, i.e., the ratio of the trial-to-trial change in motor commands to error size. We found that for both sensory modalities sensitivity decreased with increasing error size. A reanalysis of a number of previously published psychophysical results also exhibited this feature. Finally, we asked how the brain might encode sensitivity to error. We reanalyzed previously published probabilities of cerebellar complex spikes (CSs) and found that this probability declined with increasing error size. From this we posit that a CS may be representative of the sensitivity to error, and not error itself, a hypothesis that may explain conflicting reports about CSs and their relationship to error.

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“…A similar if rarer behavior can be seen in the superior colliculus (Walker et al, 1995). In the cerebellum, Soetedjo et al (2008) showed that complex spikes in the vermis encode the direction of the visual error between 100 and 150 ms after saccade end.…”

Section: Temporal Dynamics Of the Sensorimotor Integrationmentioning

confidence: 71%

Optimal and Suboptimal Use of Postsaccadic Vision in Sequences of Saccades

Morel

Baraduc

2011

Journal of Neuroscience

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Saccades are imprecise, due to sensory and motor noise. To avoid an accumulation of errors during sequences of saccades, a prediction derived from the efference copy can be combined with the reafferent visual feedback to adjust the following eye movement. By varying the information quantity of the visual feedback, we investigated how the reliability of the visual information affects the postsaccadic update in humans. Two elements of the visual scene were manipulated, the saccade target or the background, presented either together or in isolation. We determined the weight of the postsaccadic visual information by measuring the effect of intrasaccadic visual shifts on the following saccade. We confirmed that the weight of visual information evolves with information quantity as predicted for a statistically optimal system. In particular, we found that the visual background alone can guide the postsaccadic update, and that information from target and background are optimally combined. Moreover, these visual weights are adjusted dynamically and on a trial-to-trial basis to the level of visual noise determined by target eccentricity and reaction time. In contrast, we uncovered a dissociation between the visual signals used to update the next planned saccade (main saccade) and those used to generate an involuntary corrective saccade. The latter was exclusively based on visual information about the target, and discarded all information about the background: a suboptimal use of visual evidence.

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Complex Spike Activity in the Oculomotor Vermis of the Cerebellum: A Vectorial Error Signal for Saccade Motor Learning?

Cited by 111 publications

References 41 publications

Learning Signals from the Superior Colliculus for Adaptation of Saccadic Eye Movements in the Monkey

Learning Signals from the Superior Colliculus for Adaptation of Saccadic Eye Movements in the Monkey

Sensitivity to prediction error in reach adaptation

Optimal and Suboptimal Use of Postsaccadic Vision in Sequences of Saccades

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