Coding of Tactile Response Properties in the Rat Deep Cerebellar Nuclei

Rowland, Nathan C.; Jaeger, Dieter

doi:10.1152/jn.00285.2005

Cited by 75 publications

(92 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To analyze the exact time point at which the chance of spiking is increased, we adapted a convolution method that reforms spiking patterns into a normalized chance of spiking (modified from ref. 31) by replacing each spike in the raster plots with a 1-ms SD Gaussian distribution and summing the results over trials (for detailed explanation see SI Materials and Methods and Fig. S2).…”

Section: Resultsmentioning

confidence: 99%

Differential olivo-cerebellar cortical control of rebound activity in the cerebellar nuclei

Hoebeek

Witter

Ruigrok

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

136

145

View full text Add to dashboard Cite

The output of the cerebellar cortex is controlled by two main inputs, (i.e., the climbing fiber and mossy fiber-parallel fiber pathway) and activations of these inputs elicit characteristic effects in its Purkinje cells: that is, the so-called complex spikes and simple spikes. Target neurons of the Purkinje cells in the cerebellar nuclei show rebound firing, which has been implicated in the processing and storage of motor coordination signals. Yet, it is not known to what extent these rebound phenomena depend on different modes of Purkinje cell activation. Using extracellular as well as patch-clamp recordings, we show here in both anesthetized and awake rodents that simple and complex spike-like train stimuli to the cerebellar cortex, as well as direct activation of the inferior olive, all result in rebound increases of the firing frequencies of cerebellar nuclei neurons for up to 250 ms, whereas single-pulse stimuli to the cerebellar cortex predominantly elicit well-timed spiking activity without changing the firing frequency of cerebellar nuclei neurons. We conclude that the rebound phenomenon offers a rich and powerful mechanism for cerebellar nuclei neurons, which should allow them to differentially process the climbing fiber and mossy fiber inputs in a physiologically operating cerebellum.olivo-cerebellar loop | rebound firing | Purkinje cell | complex spikes | simple spikes N eurons in the cerebellar nuclei (CN) form the main output of the cerebellum (1). They include GABAergic neurons that provide an inhibitory feedback to the inferior olive (IO) and excitatory neurons that project to various other brainstem nuclei exerting motor control (2-4). In turn, each CN neuron receives a prominent inhibitory GABAergic input from tens of Purkinje cells, a substantial excitatory input from climbing fiber and mossy fiber collaterals, and a modest input from the local interneurons (4-7). Apart from the impact of these inputs, the firing pattern of CN neurons is largely determined by their intrinsic activities (4,(8)(9)(10)(11)(12)(13)(14). Interestingly, following inhibitory current injections or activation of their Purkinje cell input, CN neurons can show a "rebound" depolarization of the membrane potential, accompanied by action-potential firing (8, 11). Even though little is known about the prominence of rebound firing in the awake state, various models on cerebellar function consider this rebound phenomenon in the nuclei as an essential mechanism to process and store relevant information on motor coordination (15-18). The conductances that allow the rebound firing to emerge involve various types of Ca 2+ -channels, the distribution of which probably varies among the different types of neurons in the CN (8,11,14,(19)(20)(21)(22)(23). Regardless of the type of CN neuron, it is tempting to hypothesize that the climbing fibers and parallel fibers, which evoke complex spikes and simple spikes (24-27), respectively, have a differential impact on the generation of rebound activities in the CN neurons.To test this hypothe...

show abstract

Section: Resultsmentioning

confidence: 99%

Differential olivo-cerebellar cortical control of rebound activity in the cerebellar nuclei

Hoebeek

Witter

Ruigrok

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

136

145

View full text Add to dashboard Cite

show abstract

“…DCN neurons respond to brief sensory stimuli with an initial excitation, followed by a sequence of inhibition and rebound excitation (Eccles et al, 1974;Rowland and Jaeger, 2005), which likely reflects the feedforward excitation-inhibition input sequence at the Purkinje cells that inhibit DCN neurons. For the rapidly triggered spikes in Purkinje cells evoked during the brief excitatory phase, the direct readout of PF LTD may be crucial for governing synchronization of Purkinje cells along a folium, which receive shared input via the PF system and thus for determining the resulting pause in DCN spiking.…”

Section: Functional Implicationsmentioning

confidence: 99%

Linking Synaptic Plasticity and Spike Output at Excitatory and Inhibitory Synapses onto Cerebellar Purkinje Cells

Mittmann¹,

Häusser²

2007

J. Neurosci.

View full text Add to dashboard Cite

Understanding the relationship between synaptic plasticity and neuronal output is essential if we are to understand how plasticity is encoded in neural circuits. In the cerebellar cortex, motor learning is thought to be implemented by long-term depression (LTD) of excitatory parallel fiber (PF) to Purkinje cell synapses triggered by climbing fiber (CF) input. However, theories of motor learning generally neglect the contribution of plasticity of inhibitory inputs to Purkinje cells. Here we describe how CF-induced plasticity of both excitatory and inhibitory inputs is reflected in Purkinje cell spike output. We show that coactivation of the CF with PF input and interneuron input leads not only to LTD of PF synapses but also to comparable, "balanced" LTD of evoked inhibitory inputs. These two forms of plasticity have opposite effects on the spike output of Purkinje cells, with the number and timing of spikes sensitively reflecting the degree of plasticity. We used dynamic clamp to evaluate plasticity-induced changes in spike responses to sequences of excitation and feedforward inhibition of varied relative and absolute amplitude. Balanced LTD of both excitatory and inhibitory components decreased the net spike output of Purkinje cells only for inputs with small inhibitory components, whereas for inputs with a larger proportion of feedforward inhibition CF-triggered LTD resulted in an increase in the net spike output. Thus, the net effect of CF-triggered plasticity on Purkinje cell output depends on the balance of excitation and feedforward inhibition and can paradoxically increase cerebellar output, contrary to current theories of cerebellar motor learning.

show abstract

“…Until recently, however, whether the strength of this information is reflected in the firing rate of DCN neurons has been less clear. Rowland and Jaeger (2005) showed with recordings from DCN neurons in vivo that as a population, these neurons show increased response amplitudes as the intensity of the stimulus (air puff) is increased. They also showed that the intensity of the stimulus was encoded in the activity of cerebellar granule cells.…”

Section: Purkinje Cells Provide Dcn Neurons With Information Regardinmentioning

confidence: 99%

The Linear Computational Algorithm of Cerebellar Purkinje Cells

Walter¹,

Khodakhah²

2006

J. Neurosci.

View full text Add to dashboard Cite

The orchestration of simple motor tasks by the cerebellum results in coordinated movement and the maintenance of balance. The cerebellum integrates sensory and cortical information to generate the signals required for the coordinated execution of simple motor tasks. These signals originate in the firing rate of Purkinje cells, each of which integrates sensory and cortical information conveyed by granule cell synaptic inputs. Given the importance of the granule cell input-Purkinje cell output function for cerebellar computation, this algorithm was determined. Using several stimulation paradigms, including those that mimicked patterns of granule cell activity similar to those observed in vivo, we quantified the poststimulus maximum firing rate and number of extra spikes in response to granule cell synaptic input. Both of these parameters linearly encoded the strength of synaptic input when inhibitory synaptic transmission was blocked. This linear algorithm was independent of the location or temporal pattern of synaptic input. With inhibitory synaptic transmission intact, the maximum firing rate, but not the number of extra spikes, encoded the strength of granule cell synaptic input. Furthermore, the maximum firing rate of Purkinje cells linearly encoded the strength of synaptic input whether or not the activation of granule cells resulted in a pause in Purkinje cell firing. On the basis of the data presented, we propose that Purkinje cells encode the strength of granule cell synaptic input in their maximum firing rate with a linear algorithm.

show abstract

Coding of Tactile Response Properties in the Rat Deep Cerebellar Nuclei

Cited by 75 publications

References 75 publications

Differential olivo-cerebellar cortical control of rebound activity in the cerebellar nuclei

Differential olivo-cerebellar cortical control of rebound activity in the cerebellar nuclei

Linking Synaptic Plasticity and Spike Output at Excitatory and Inhibitory Synapses onto Cerebellar Purkinje Cells

The Linear Computational Algorithm of Cerebellar Purkinje Cells

Contact Info

Product

Resources

About