Climbing fiber afferent modulation during a visually guided, multi-joint arm movement in the monkey

Wang, Jianjun; Kim, Jong H.; Ebner, Timothy J.

doi:10.1016/0006-8993(87)90331-3

Cited by 88 publications

(21 citation statements)

References 19 publications

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“…When the primary motor cortex functions as a feedback controller, it derives motor error signals, and passes them to the inverse model via the inferior olive. This inverse-model-based control explains well the above-mentioned experimental observations by Mano et al (1986) and Wang et al (1987). These model-based control systems will be considered later in comparison with the model systems postulated above for VOR, OKR, and saccade.…”

Section: Hand Reach and Cursor Trackingsupporting

confidence: 88%

“…In this visually guided wrist tracking, Purkinje cells in the cerebellar hemisphere (lobules IV–VI) exhibited complex spikes related to movements, presumably reflecting motor errors. In another experiment by Wang et al (1987), a monkey moved a manipulandum, the position of which is represented by a cursor on the screen. The monkey was trained to move the cursor from the start box to the target box, and the target box could be repositioned during movement.…”

Section: Hand Reach and Cursor Trackingmentioning

confidence: 99%

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Error detection and representation in the olivo-cerebellar system

Ito¹

2013

Front. Neural Circuits

233

211

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Complex spikes generated in a cerebellar Purkinje cell via a climbing fiber have been assumed to encode errors in the performance of neuronal circuits involving Purkinje cells. To reexamine this notion in this review, I analyzed structures of motor control systems involving the cerebellum. A dichotomy was found between the two types of error: sensory and motor errors play roles in the feedforward and feedback control conditions, respectively. To substantiate this dichotomy, here in this article I reviewed recent data on neuronal connections and signal contents of climbing fibers in the vestibuloocular reflex (VOR), optokinetic eye movement response, saccade, hand reaching, cursor tracking, as well as some other cases of motor control. In our studies, various sources of sensory and motor errors were located in the neuronal pathways leading to the inferior olive. We noted that during the course of evolution, control system structures involving the cerebellum changed rather radically from the prototype seen in the flocculonodular lobe and vermis to that applicable to the cerebellar hemisphere. Nevertheless, the dichotomy between sensory and motor errors is maintained.

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Section: Hand Reach and Cursor Trackingsupporting

confidence: 88%

Section: Hand Reach and Cursor Trackingmentioning

confidence: 99%

Error detection and representation in the olivo-cerebellar system

Ito¹

2013

Front. Neural Circuits

233

211

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“…The reasons for using the target change paradigm are two-fold. First, it was found that complex spike activity is high when the target is changed (Wang et al 1987). Second, by placing the second target to the left or right of the first target, we can manipulate the sign of the trajectory error and hence the sign of the motor-command error.…”

Section: Critical Experimental Testmentioning

confidence: 99%

“…Each region is further subdivided into longitudinal microzones 200 ~m wide and more than 50 mm long (Andersson and Oscarsson 1978;Oscarsson 1980). Several research groups provided data which suggest that different regions of the cerebellum play important roles in the learning of different motor behaviors, such as arm movement (Gilbert and Thach 1977;Gellman et al 1985;Wang et al 1987), locomotion (Udo et al 1980;Matsukawa and Udo 1985), posture control (Nashner 1981), and classical conditioning of eye-blink responses (Thompson 1987).…”

Section: Introductionmentioning

confidence: 99%

A computational model of four regions of the cerebellum based on feedback-error learning

1992

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We propose a computationally coherent model of cerebellar motor learning based on the feedback-error-learning scheme. We assume that climbing fiber responses represent motor-command errors generated by some of the premotor networks such as the feedback controllers at the spinal-, brain stem- and cerebral levels. Thus, in our model, climbing fiber responses are considered to convey motor errors in the motor-command coordinates rather than in the sensory coordinates. Based on the long-term depression in Purkinje cells each corticonuclear microcomplex in different regions of the cerebellum learns to execute predictive and coordinative control of different types of movements. Ultimately, it acquires an inverse model of a specific controlled object and complements crude control by the premotor networks. This general model is developed in detail as a specific neural circuit model for the lateral hemisphere. A new experiment is suggested to elucidate the coordinate frame in which climbing fiber responses are represented.

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“…Complex spike discharge is associated with errors during eye movements (Barmack and Simpson, 1980; Graf et al, 1988; Kobayashi et al, 1998; Medina and Lisberger, 2008; Soetedjo and Fuchs, 2006). During arm movements, complex spikes modulate with perturbations (Gilbert and Thach, 1977; Wang et al, 1987), adaptation to visuomotor transformations (Ojakangas and Ebner, 1994), and end point errors (Kitazawa et al, 1998). Whether Purkinje cell simple spike discharge encodes errors has received less attention.…”

Section: Introductionmentioning

confidence: 99%

Predictive and Feedback Performance Errors Are Signaled in the Simple Spike Discharge of Individual Purkinje Cells

2012

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The cerebellum has been implicated in processing motor errors required for online control of movement and motor learning. The dominant view is that Purkinje cell complex spike discharge signals motor errors. This study investigated whether errors are encoded in the simple spike discharge of Purkinje cells in monkeys trained to manually track a pseudo-randomly moving target. Four task error signals were evaluated based on cursor movement relative to target movement. Linear regression analyses based on firing residuals ensured that the modulation with a specific error parameter was independent of the other error parameters and kinematics. The results demonstrate that simple spike firing in lobules IV–VI is significantly correlated with position, distance and directional errors. Independent of the error signals, the same Purkinje cells encode kinematics. The strongest error modulation occurs at feedback timing. However, in 72% of cells at least one of the R2 temporal profiles resulting from regressing firing with individual errors exhibit two peak R2 values. For these bimodal profiles, the first peak is at a negative τ (lead) and a second peak at a positive τ (lag), implying that Purkinje cells encode both prediction and feedback about an error. For the majority of the bimodal profiles, the signs of the regression coefficients or preferred directions reverse at the times of the peaks. The sign reversal results in opposing simple spike modulation for the predictive and feedback components. Dual error representations may provide the signals needed to generate sensory prediction errors used to update a forward internal model.

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Climbing fiber afferent modulation during a visually guided, multi-joint arm movement in the monkey

Cited by 88 publications

References 19 publications

Error detection and representation in the olivo-cerebellar system

Error detection and representation in the olivo-cerebellar system

A computational model of four regions of the cerebellum based on feedback-error learning

Predictive and Feedback Performance Errors Are Signaled in the Simple Spike Discharge of Individual Purkinje Cells

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