Afferent volleys in limb nerves influencing impulse discharges in cerebellar cortex I. In mossy fibers and granule cells

1971 ◽  
Vol 13 (1) ◽  
pp. 15-35 ◽  
Author(s):  
J. C. Eccles ◽  
D. S. Faber ◽  
J. T. Murphy ◽  
N. H. Sabah ◽  
Helena Táboříková
1987 ◽  
Vol 231 (1263) ◽  
pp. 217-230 ◽  

The previously described direct and relayed projections of periodontal afferents to the cerebellar cortex have been examined in detail by extracellular field-potential analysis. Advantage is taken of the very small temporal dispersion of the afferent volleys to permit identification of the presynaptic spike potential of mossy fibres, the subsequent synaptic potential and the firing of granule cells. Changes in form of the presynaptic potential with depth are compared with published descriptions of presynaptic potentials elsewhere. The negative synaptic potential in the granular layer is shown to have a positive aspect in the molecular layer. Granule-cell firing can, under some conditions, yield a population spike interrupting the synaptic potential wave. Records are presented showing all-or-none complex waves, which appear to be single glomerular potentials not previously described in the mammalian cerebellum. Their distinction from cellular spike potentials is emphasized.


2016 ◽  
Vol 115 (1) ◽  
pp. 255-270 ◽  
Author(s):  
Saeka Tomatsu ◽  
Takahiro Ishikawa ◽  
Yoshiaki Tsunoda ◽  
Jongho Lee ◽  
Donna S. Hoffman ◽  
...  

A region of cerebellar lobules V and VI makes strong loop connections with the primary motor (M1) and premotor (PM) cortical areas and is assumed to play essential roles in limb motor control. To examine its functional role, we compared the activities of its input, intermediate, and output elements, i.e., mossy fibers (MFs), Golgi cells (GoCs), and Purkinje cells (PCs), in three monkeys performing wrist movements in two different forearm postures. The results revealed distinct steps of information processing. First, MF activities displayed temporal and directional properties that were remarkably similar to those of M1/PM neurons, suggesting that MFs relay near copies of outputs from these motor areas. Second, all GoCs had a stereotyped pattern of activity independent of movement direction or forearm posture. Instead, GoC activity resembled an average of all MF activities. Therefore, inhibitory GoCs appear to provide a filtering function that passes only prominently modulated MF inputs to granule cells. Third, PCs displayed highly complex spatiotemporal patterns of activity, with coordinate frames distinct from those of MF inputs and directional tuning that changed abruptly before movement onset. The complexity of PC activities may reflect rapidly changing properties of the peripheral motor apparatus during movement. Overall, the cerebellar cortex appears to transform a representation of outputs from M1/PM into different movement representations in a posture-dependent manner and could work as part of a forward model that predicts the state of the peripheral motor apparatus.


eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Andrei Khilkevich ◽  
Juan Zambrano ◽  
Molly-Marie Richards ◽  
Michael Dean Mauk

Most movements are not unitary, but are comprised of sequences. Although patients with cerebellar pathology display severe deficits in the execution and learning of sequences (Doyon et al., 1997; Shin and Ivry, 2003), most of our understanding of cerebellar mechanisms has come from analyses of single component movements. Eyelid conditioning is a cerebellar-mediated behavior that provides the ability to control and restrict inputs to the cerebellum through stimulation of mossy fibers. We utilized this advantage to test directly how the cerebellum can learn a sequence of inter-connected movement components in rabbits. We show that the feedback signals from one component are sufficient to serve as a cue for the next component in the sequence. In vivo recordings from Purkinje cells demonstrated that all components of the sequence were encoded similarly by cerebellar cortex. These results provide a simple yet general framework for how the cerebellum can use simple associate learning processes to chain together a sequence of appropriately timed responses.


Neuron ◽  
2016 ◽  
Vol 91 (6) ◽  
pp. 1330-1341 ◽  
Author(s):  
Chong Guo ◽  
Laurens Witter ◽  
Stephanie Rudolph ◽  
Hunter L. Elliott ◽  
Katelin A. Ennis ◽  
...  

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