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Effects of Purkinje cell inhibitory synaptic input of transient and weak burst cells. a Comparison of single evoked IPSPs and associated IPSCs of representative transient and weak burst cells from a resting potential of −60 mV. Stimulus intensity was set to 60% of a maximal IPSC. Plots of the mean amplitude and rate of decay of the IPSC for transient (n=10) and weak burst (n=10) cells reveal no significant difference in the single evoked response. b IPSPs are finely graded in amplitude with the intensity of stimulation. Stimulus intensities were normalized to that which evoked a maximum IPSC in each cell and IPSP amplitude to the response at 20% maximum
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Neurons of the deep cerebellar nuclei (DCN) play a critical role in defining the output of cerebellum in the course of encoding Purkinje cell inhibitory inputs. The earliest work performed with in vitro preparations established that DCN cells have the capacity to translate membrane hyperpolarizations into a rebound increase in firing frequency. The...
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... b represent increases beyond baseline tonic firing rates. The absolute membrane potentials at the trough of the AHP and during IPSPs are shown in c could reflect a differential inhibitory influence on transient vs weak burst cells. To test this, we provide some unpublished observations on the IPSPs evoked by stimu- lating Purkinje cell afferents (Fig. 6a). These data reveal no difference in the IPSP or IPSC evoked in transient or weak burst cells in terms of amplitude or duration for a similar stimulus intensity (60% of the intensity required to evoke a maximum IPSC; Fig. 6a). The amplitude of the IPSP is also finely graded with the intensity of stimulation [9,40,77], as confirmed for ...
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... cells. To test this, we provide some unpublished observations on the IPSPs evoked by stimu- lating Purkinje cell afferents (Fig. 6a). These data reveal no difference in the IPSP or IPSC evoked in transient or weak burst cells in terms of amplitude or duration for a similar stimulus intensity (60% of the intensity required to evoke a maximum IPSC; Fig. 6a). The amplitude of the IPSP is also finely graded with the intensity of stimulation [9,40,77], as confirmed for both transient and weak burst cells (Fig. 6b) [16]. The difference in rebound intensity between transient and weak burst cells then does not relate to any obvious difference in the magnitude of the single evoked IPSP. ...
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... in the IPSP or IPSC evoked in transient or weak burst cells in terms of amplitude or duration for a similar stimulus intensity (60% of the intensity required to evoke a maximum IPSC; Fig. 6a). The amplitude of the IPSP is also finely graded with the intensity of stimulation [9,40,77], as confirmed for both transient and weak burst cells (Fig. 6b) [16]. The difference in rebound intensity between transient and weak burst cells then does not relate to any obvious difference in the magnitude of the single evoked IPSP. However, early work reported a difference in the efficacy of single evoked IPSPs compared to a brief train of stimuli in vitro [2,9,13]. We also found that rebound ...
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... in the efficacy of single evoked IPSPs compared to a brief train of stimuli in vitro [2,9,13]. We also found that rebound bursts in transient and weak burst cells are influenced by the number of repetitive stimuli delivered to Purkinje cell inputs, with a more intense rebound burst for 20 as compared to ten stimuli delivered at 100 Hz ( Fig. 6c; as reported in [84]). Thus, for synaptic inhibitory trains initially set to ∼60% of the maximum amplitude IPSC, the rebound frequency of transient burst cells increased from 23±6.7 Hz for ten stimuli to 64±15.9 Hz for 20 stimuli (n=13, p<0.05). For weak burst cells, the increase in rebound frequencies for 10-20 stimuli was 9.4±2.1 to ...
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... transient burst cells increased from 23±6.7 Hz for ten stimuli to 64±15.9 Hz for 20 stimuli (n=13, p<0.05). For weak burst cells, the increase in rebound frequencies for 10-20 stimuli was 9.4±2.1 to 22.8±3.65 Hz (n=12, p<0.05). Note that the increase in firing frequency extends well beyond the early phase and into the late phase of rebound firing (Fig. ...
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... repetitive stimulus trains also serve to highlight some unique and important aspects of synaptic transmission between Purkinje cells and DCN cells that deserve further investigation. In particular, longer pulse trains reveal a frequency-dependent depression of transmitter release and IPSP amplitude (Fig. 6e) [77,[80][81][82]85]. However, when comparing the relative shift in membrane potential during stimulus trains to the intensity of rebound discharge, it becomes apparent that DCN cells do not respond to repetitive inhibitory inputs in a manner entirely predicted for voltage-dependent postsynaptic channels. Thus, present- ing a higher ...
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... from other studies indicate that for Aizenman et al. [13], we would identify a transient burst-like frequency response following their delivery of a train of IPSPs (∼83 Hz, their Fig. 3a) and a weak burst-like response to a current-evoked hyperpolarization (∼40 Hz, their Fig. 5a). Similarly, the synaptically evoked responses for two cells in Fig. 6a, b of Aizenman and Linden [2] is similar to the pattern of firing in our recordings of transient and weak burst cells shown here in Fig. 5c. The difference would be a shorter burst duration in their results, but this could be due to a lower Ri with microelectrode recordings. Also, as pointed out in their Fig. 6b, tonic ...
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... evoked responses for two cells in Fig. 6a, b of Aizenman and Linden [2] is similar to the pattern of firing in our recordings of transient and weak burst cells shown here in Fig. 5c. The difference would be a shorter burst duration in their results, but this could be due to a lower Ri with microelectrode recordings. Also, as pointed out in their Fig. 6b, tonic hyperpolarization decreases the duration of rebound firing, which is consistent with these differences in that all of our cells were tonically firing from a resting of approx. −60 mV (trough of AHPs) when tested. In Pugh and Raman [61], the rebound bursts evoked following current-evoked hyperpolarizations exhibit frequencies ...
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Citations
... NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-022-30844-0 ARTICLE Cerebellar stimulation produces alternate periods of silence and increased "rebound" activity in CN 91 . Previous evidence demonstrated that this rebound activation is propagated in the forebrain motor network 78 . ...
Chronic Levodopa therapy, the gold-standard treatment for Parkinson’s Disease (PD), leads to the emergence of involuntary movements, called levodopa-induced dyskinesia (LID). Cerebellar stimulation has been shown to decrease LID severity in PD patients. Here, in order to determine how cerebellar stimulation induces LID alleviation, we performed daily short trains of optogenetic stimulations of Purkinje cells (PC) in freely moving LID mice. We demonstrated that these stimulations are sufficient to suppress LID or even prevent their development. This symptomatic relief is accompanied by the normalization of aberrant neuronal discharge in the cerebellar nuclei, the motor cortex and the parafascicular thalamus. Inhibition of the cerebello-parafascicular pathway counteracted the beneficial effects of cerebellar stimulation. Moreover, cerebellar stimulation reversed plasticity in D1 striatal neurons and normalized the overexpression of FosB, a transcription factor causally linked to LID. These findings demonstrate LID alleviation and prevention by daily PC stimulations, which restore the function of a wide motor network, and may be valuable for LID treatment.
... Finally, reduced GM density was found in the left superior parietal lobule. Superior parietal lobule is considered critically important for the manipulation of information in working memory [56,57], but correlation of superior parietal lobule with sensorimotor integration has also been reported [58,59]. Consequently, the left superior parietal lobule involvement may be related to both cognitive and sensorimotor impairment. ...
... Furthermore, an interesting finding is the contribution of cerebellum to the underlying pathological mechanism. It has long been known that the cerebellum has a critical role in motor functions [57,60]. A shift in the understanding of the cerebellum role has been performed during the last two decades, associating it with cerebral networks involved in non-motor networks, including language, spatial, and executive functions [59,61]. ...
Purpose
Brain involvement in X-linked Charcot-Marie-Tooth disease (CMTX) has been previously reported. We studied the brain structural and functional integrity using a multimodal neuroimaging approach in patients with no current central nervous system (CNS) symptoms, in order to further delineate the disease’s phenotype.
Methods
Seventeen CMTX patients with no current CNS symptoms and 24 matched healthy controls underwent brain magnetic resonance imaging (MRI). Structural integrity was evaluated performing Gray matter analysis with voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) of diffusion tensor imaging (DTI). Functional integrity was evaluated with resting-state functional MRI (rs-fMRI).
Results
Decreased gray matter density was detected in CMTX patients compared to healthy controls in bilateral hippocampus, left thalamus, left postcentral gyrus, left superior parietal lobule, left cerebellum crus I and II, and vermis VI. DTI analysis showed increased fractional anisotropy and radial diffusivity in the right anterior insula and increased axial diffusivity in right cerebellum crus I in CMTX patients. rs-fMRI revealed decreased spontaneous neural activity on left precentral gyrus in patients compared to healthy controls.
Conclusion
Advanced magnetic resonance (MR) neuroimaging techniques in CMTX patients revealed structural and functional involvement of multiple motor and extra-motor brain areas. MR neuroimaging techniques have the potential to delineate the CNS phenotype of a peripheral neuropathy like CMTX.
... Varying between 100 and 200 ms long, these pauses relate well with an underlying 5-10 Hz cerebellar cortex rhythmicity (Alviña et al., 2008), and they complement the pacemaker regularity of Purkinje cell firing, which have an important role in the coordinated circuitry (Walter et al., 2006). Besides, the 4-12 Hz rhythmicity also fits well with a recovery time constant of the channels CaV3.1 in those same neurons around 100 ms (Iftinca et al., 2006;De Schutter and Steuber, 2009;Tadayonnejad et al., 2010). Importantly as well, mutant mice that are without the calcium-sensitive BK channels in their Purkinje cells show Correlation between the firing rate and the RI, for the units with a RI > 0 (red dots). ...
Oscillations in the granule cell layer (GCL) of the cerebellar cortex have been related to behavior and could facilitate communication with the cerebral cortex. These local field potential (LFP) oscillations, strong at 4-12 Hz in the rodent cerebellar cortex during awake immobility, should also be an indicator of an underlying influence on the patterns of the cerebellar cortex neuronal firing during rest. To address this hypothesis, cerebellar cortex LFPs and simultaneous single-neuron activity were collected during LFP oscillatory periods in the GCL of awake resting rats. During these oscillatory episodes, different types of units across the GCL and Purkinje cell layers showed variable phase-relation with the oscillatory cycles. Overall, 74% of the Golgi cell firing and 54% of the Purkinje cell simple spike (SS) firing were phase-locked with the oscillations, displaying a clear phase relationship. Despite this tendency, fewer Golgi cells (50%) and Purkinje cell's SSs (25%) showed an oscillatory firing pattern. Oscillatory phase-locked spikes for the Golgi and Purkinje cells occurred towards the peak of the LFP cycle. GCL LFP oscillations had a strong capacity to predict the timing of Golgi cell spiking activity, indicating a strong influence of this oscillatory phenomenon over the GCL. Phase-locking was not as prominent for the Purkinje cell SS firing, indicating a weaker influence over the Purkinje cell layer, yet a similar phase relation. Overall, synaptic activity underlying GCL LFP oscillations likely exert an influence on neuronal population firing patterns in the cerebellar cortex in the awake resting state and could have a preparatory neural network shaping capacity serving as a neural baseline for upcoming cerebellar operations.
... To explain the excitation of DNCs [specifically, deep cerebellar nuclei (dCN) cells], two physiological mechanisms have been proposed. One mechanism is the recruitment of a post-inhibitory rebound excitation (Aizenman and Linden, 1999;Hoebeek et al., 2010;Tadayonnejad et al., 2010;Witter et al., 2013). Another mechanism is the suppression of PCs that facilitates dCN cells by a release from tonic inhibition from PCs, a mechanism known as disinhibition (Albus, 1971;Miyashita and Nagao, 1984;Nagao, 1992;Shinoda et al., 1992;Medina and Mauk, 2000). ...
This review surveys physiological, behavioral, and morphological evidence converging to the view of the cerebro-cerebellum as loci of internal forward models. The cerebro-cerebellum, the phylogenetically newest expansion in the cerebellum, receives convergent inputs from cortical, subcortical, and spinal sources, and is thought to perform the predictive computation for both motor control, motor learning, and cognitive functions. This predictive computation is known as an internal forward model. First, we elucidate the theoretical foundations of an internal forward model and its role in motor control and motor learning within the framework of the optimal feedback control model. Then, we discuss a neural mechanism that generates various patterns of outputs from the cerebro-cerebellum. Three lines of supporting evidence for the internal-forward-model hypothesis are presented in detail. First, we provide physiological evidence that the cerebellar outputs (activities of dentate nucleus cells) are predictive for the cerebellar inputs [activities of mossy fibers (MFs)]. Second, we provide behavioral evidence that a component of movement kinematics is predictive for target motion in control subjects but lags behind a target motion in patients with cerebellar ataxia. Third, we provide morphological evidence that the cerebellar cortex and the dentate nucleus receive separate MF projections, a prerequisite for optimal estimation. Finally, we speculate that the predictive computation in the cerebro-cerebellum could be deployed to not only motor control but also to non-motor, cognitive functions. This review concludes that the predictive computation of the internal forward model is the unifying algorithmic principle for understanding diverse functions played by the cerebro-cerebellum.
... CN neurons have been subdivided into six subgroups, of which five are present in the medial nucleus: glutamatergic, GABAergic nucleo-olivary and glycinergic projection neurons, and local GABAergic and/or glycinergic cells (Czubayko et al., 2001;Uusisaari et al., 2007;Alviña et al., 2008;Knöpfel, 2008, 2011;Bagnall et al., 2009;Tadayonnejad et al., 2010;Zheng and Raman, 2010;Blenkinsop and Lang, 2011;Bengtsson and Jörntell, 2014;Husson et al., 2014;Ankri et al., 2015;Najac and Raman, 2015;Canto et al., 2016;Yarden-Rabinowitz and Yarom, 2017). Specific intrinsic biophysical properties (e.g., spike width, afterhyperpolarization shape and duration, firing rate) for at least 4 different CN neurons subtypes have been described using intracellular recordings (Uusisaari et al., 2007;Knöpfel, 2008, 2011;Bagnall et al., 2009;Ankri et al., 2015;Najac and Raman, 2015;Canto et al., 2016;Yarden-Rabinowitz and Yarom, 2017). ...
... CN neurons integrate excitatory inputs from mossy and climbing fibers, and inhibitory inputs from PCs and local interneurons. It was recently demonstrated that excitatory afferents are responsible for half of the action potentials in CN cells (Yarden-Rabinowitz and Yarom, 2017); the other half is intrinsically elicited since CN neurons are spontaneously active (Thach, 1968;Aizenman and Linden, 1999;Raman et al., 2000;Alviña et al., 2009;Sangrey and Jaeger, 2010;Tadayonnejad et al., 2010;Zheng and Raman, 2010;Boehme et al., 2011;Engbers et al., 2013). Although the existence of a PC inhibitory control of CN cells is generally accepted (Ito et al., 1970;Ito, 1984;Gauck and Jaeger, 2000;Czubayko et al., 2001;Telgkamp and Raman, 2002;Pedroarena and Schwarz, 2003;Rowland and Jaeger, 2005;Blenkinsop and Lang, 2011;Person and Raman, 2011;Chaumont et al., 2013), the question of whether this inhibition gradually decreases CN neurons mean firing rate (rate code), delimits a temporal window for neuron discharge (temporal code), or both is still debated (De Zeeuw et al., 2008. ...
The cerebellum drives motor coordination and sequencing of actions at the millisecond timescale through adaptive control of cerebellar nuclear output. Cerebellar nuclei integrate high-frequency information from both the cerebellar cortex and the two main excitatory inputs of the cerebellum, the mossy fibers and the climbing fiber collaterals. However, how nuclear cells process rate and timing of inputs carried by these inputs is still debated. Here, we investigate the influence of the cerebellar cortical output, the Purkinje cells, on identified cerebellar nuclei neurons in vivo in male mice. Using transgenic mice expressing Channelrhodopsin2 specifically in Purkinje cells and tetrode recordings in the medial nucleus we identified two main groups of neurons based on the waveform of their action potentials. These two groups of neurons coincide with glutamatergic and GABAergic neurons identified by optotagging after Chrimson expression in VGlut2-cre and GAD-cre mice, respectively. The glutamatergic-like neurons fire at high rate and respond to both rate and timing of Purkinje cell population inputs, whereas GABAergic-like neurons only respond to the mean population firing rate of Purkinje cells at high frequencies. Moreover, synchronous activation of Purkinje cells can entrain the glutamatergic-like, but not the GABAergic-like, cells over a wide range of frequencies. Our results suggest that the downstream effect of synchronous and rhythmic Purkinje cell discharges depends on the type of cerebellar nuclei neurons targeted.SIGNIFICANCE STATEMENTMotor coordination and skilled movements are driven by the permanent discharge of neurons from the cerebellar nuclei that communicate cerebellar computation to other brain areas. Here, we set out to study how specific subtypes of cerebellar nuclear neurons of the medial nucleus are controlled by Purkinje cells, the sole output of the cerebellar cortex. We could isolate different subtypes of nuclear cell that differentially encode Purkinje cell inhibition. Purkinje cell stimulation entrain glutamatergic projection cells at their firing frequency whereas GABAergic neurons are only inhibited. These differential coding strategies may favor temporal precision of cerebellar excitatory outputs associated with specific features of movement control, while setting the global level of cerebellar activity through inhibition via rate coding mechanisms.
... Large DCNs usually respond to hyperpolarizing stimulus with an increase in firing rate above baseline after the stimulus end, so called rebound response e.g. 32,33,34 , and GABAergic DCNs also respond to hyperpolarizing inputs with rebound responses 28 . DTX induced changes in the maximum rebound frequency but we observed increases as well as decreases (max rebound frequency, Figs 2C right plots, see methods) The possible causes of the variability in this or other type of responses will be discussed later. ...
The Kv1 voltage-gated potassium channels (kv1.1-1.8) display characteristic low-threshold activation ranges which is inherent to their role in controlling diverse aspects of neuronal function, such as the action potential (AP) threshold and waveform, and thereby influence neuronal excitability or synaptic transmission. Kv1 channels are highly expressed in the cerebellar cortex and nuclei and mutations of human Kv1 genes are associated to episodic forms of ataxia (EAT-1). Besides the well-established role of Kv1 channels in regulating the basket-Purkinje cells inhibitory synapses of cerebellar cortex, cerebellar Kv1 channels regulate the principal deep cerebellar nuclear neurons activity (DCNs). DCNs however, include as well a heterogeneous population of GABAergic cells that project locally, to the inferior-olive or recurrently to the cerebellar cortex, but whether their function is controlled by Kv1 channels remains unclear. Here, using cerebellar slices from the GAD67-GFP line mice to identify putative GABAergic-DCNs and specific Kv1 channel blockers (dendrotoxins-alpha/I/K (DTXs)) we provide evidence that putative GABAergic-DCNs spontaneous and evoked activity is controlled by Kv1 currents. DTXs shifted in GABAergic-DCNs the voltage threshold of spontaneous APs in the hyperpolarizing direction, increased GABAergic-DCNs spontaneous firing rate and decreased the ability to fire repetitively action potentials at high frequency. Moreover, in spontaneously silent putative nucleo-cortical DCNs, DTXs application induced depolarization and tonic firing. These results strongly suggest that Kv1 channels regulate GABAergic-DCNs activity and thereby can control previously unrecognized aspects of cerebellar function.
... CACNA1G encodes one of the T-type voltage-gated calcium channels, Ca V 3.1, which is widely expressed in the brain, especially in neurons in the thalamus, hippocampus, and inferior olivary nucleus (ION), as well as cerebellar PCs (Ernst et al., 2009;Talley et al., 1999). Ca V 3.1 plays an important role in regulating calcium entry and membrane potential (Zamponi et al., 2015), including rebound burst firing of neurons in the thalamus (Kim et al., 2001) and cerebellar nuclei (Perez-Reyes and Lory, 2006;Tadayonnejad et al., 2010). Accordingly, Ca V 3.1 variants are associated with various disorders, including idiopathic generalized epilepsy (Singh et al., 2007), autism spectrum disorder (Strom et al., 2010), and more recently SCA42 and childhood-onset cerebellar atrophy (Chemin et al., 2018). ...
Spinocerebellar ataxia 42 (SCA42) is a neurodegenerative disorder recently shown to be caused by c.5144G > A (p.Arg1715His) mutation in CACNA1G, which encodes the T-type voltage-gated calcium channel CaV3.1. Here, we describe a large Japanese family with SCA42. Postmortem pathological examination revealed severe cerebellar degeneration with prominent Purkinje cell loss without ubiquitin accumulation in an SCA42 patient. To determine whether this mutation causes ataxic symptoms and neurodegeneration, we generated knock-in mice harboring c.5168G > A (p.Arg1723His) mutation in Cacna1g, corresponding to the mutation identified in the SCA42 family. Both heterozygous and homozygous mutants developed an ataxic phenotype from the age of 11–20 weeks and showed Purkinje cell loss at 50 weeks old. Degenerative change of Purkinje cells and atrophic thinning of the molecular layer were conspicuous in homozygous knock-in mice. Electrophysiological analysis of Purkinje cells using acute cerebellar slices from young mice showed that the point mutation altered the voltage dependence of CaV3.1 channel activation and reduced the rebound action potentials after hyperpolarization, although it did not significantly affect the basic properties of synaptic transmission onto Purkinje cells. Finally, we revealed that the resonance of membrane potential of neurons in the inferior olivary nucleus was decreased in knock-in mice, which indicates that p.Arg1723His CaV3.1 mutation affects climbing fiber signaling to Purkinje cells. Altogether, our study shows not only that a point mutation in CACNA1G causes an ataxic phenotype and Purkinje cell degeneration in a mouse model, but also that the electrophysiological abnormalities at an early stage of SCA42 precede Purkinje cell loss.
... These studies were largely aimed at addressing an open question in the cerebellar field: does cerebellar nuclear rebound depolarization constitute a meaningful coding mechanism in the cerebellum? In vitro, it was shown that upon hyperpolarizing input, cerebellar nuclear neurons are capable of showing strong post-inhibitory spike responses exceeding baseline firing frequency [105,106], that could last for hundreds of milliseconds, even when excitatory transmission was blocked [107][108][109][110][111]. Rebound depolarization seems to be mediated in part by T-type calcium channels [106,112,113], hyperpolarization-gated cyclic nucleotide channels [113], and persistent sodium channels [114]; Steuber et al. as well as concurrent mGlur1 activation [66]. ...
The eyeblink conditioning paradigm captures an elementary form of associative learning in a neural circuitry that is understood to an extraordinary degree. Cerebellar cortical Purkinje cell simple spike suppression is widely regarded as the main process underlying conditioned responses (CRs), leading to disinhibition of neurons in the cerebellar nuclei that innervate eyelid muscles downstream. However, recent work highlights the addition of a conditioned Purkinje cell complex spike response, which at the level of the interposed nucleus seems to translate to a transient spike suppression that can be followed by a rapid spike facilitation. Here, we review the characteristics of these responses at the cerebellar cortical and nuclear level, and discuss possible origins and functions.
... To explain the excitation of DNCs or more generally the deep cerebellar nuclear (dCN) cells without effective excitatory drive, there are two proposed mechanisms. First, some researchers proposed recruitment of a post-inhibitory rebound excitation [16][17][18][19]. They observed a short burst of dCN cells after current-induced strong hyperpolarization or synchronous activation of a large number of PCs. ...
Background:
In order to optimize outcomes of novel therapies for cerebellar ataxias (CAs), it is desirable to start these therapies while declined functions are restorable: i.e. while the so-called cerebellar reserve remains.
Objective:
In this mini-review, we tried to define and discuss the cerebellar reserve from physiological and morphological points of view.
Method:
The cerebellar neuron circuitry is designed to generate spatiotemporally organized outputs, regardless of the region. Therefore, the cerebellar reserve may be defined as a mechanism to restore its proper input-output organization of the cerebellar neuron circuitry, when it is damaged. Then, the following four components are essential for recruitment of the cerebellar reserve: operational local neuron circuitry; proper combination of mossy fiber inputs to be integrated; climbing fiber inputs to instruct favorable reorganization of the integration; deep cerebellar nuclei to generate reorganized outputs.
Results:
We discussed three topics related to these resources, 1) principles of generating organized cerebellar outputs, 2) redundant mossy fiber inputs to the cerebellum, 3) plasticity of the cerebellar neuron circuitry.
Conclusion:
To make most of the cerebellar reserve, it is desirable to start any intervention as early as possible when the cerebellar cell loss is minimal or even negligible. Therefore, an ideal future therapy for degenerative cerebellar diseases should start before consuming the cerebellar reserve at all. In the mean time, our real challenge is to establish a reliable method to identify decrease in the cerebellar reserve as early as possible.
... Consequently, one fundamental question is what generates action potentials (APs) in these neurons. One proposed mechanism is the 'rebound' response, an increase in firing frequency following the release from PN inhibition (Ito et al. 1970;Llinás & Mühlethaler, 1988;Aizenman & Linden, 1999;Hoebeek et al. 2010;Tadayonnejad et al. 2010;Witter et al. 2013). The reliability of this mechanism has been questioned in in vivo studies (Bengtsson et al. 2011). ...
Key points:
Cerebellar nuclei (CN) neurons can be classified into four groups according to their action potential (AP) waveform, corresponding to four types of neurons previously characterized. Half of the APs are generated by excitatory events, suggesting that excitatory inputs play a key role in generating CN outputs. Analysis of post-synaptic potentials reveals that the probability of excitatory inputs generating an AP is 0.1. The input from climbing fibre collaterals is characterized by a pair of synaptic potentials with a distinct interpair interval of 4.5 ms. The probability of climbing fibre collaterals initiating an AP in CN neurons is 0.15.
Abstract:
It is commonly agreed that the main function of the cerebellar system is to provide well-timed signals used for the execution of motor commands or prediction of sensory inputs. This function is manifested as a temporal sequence of spiking that should be expressed in the cerebellar nuclei (CN) projection neurons. Whether spiking activity is generated by excitation or release from inhibition is still a hotly debated issue. In an attempt to resolve this debate, we recorded intracellularly from CN neurons in anaesthetized mice and performed an analysis of synaptic activity that yielded a number of important observations. First, we demonstrate that CN neurons can be classified into four groups. Second, shape-index plots of the excitatory events suggest that they are distributed over the entire dendritic tree. Third, the rise time of excitatory events is linearly related to amplitude, suggesting that all excitatory events contribute equally to the generation of action potentials (APs). Fourth, we identified a temporal pattern of spontaneous excitatory events that represent climbing fibre inputs and confirm the results by direct stimulation and analysis on harmaline-evoked activity. Finally, we demonstrate that the probability of excitatory inputs generating an AP is 0.1 yet half of the APs are generated by excitatory events. Moreover, the probability of a presumably spontaneous climbing fibre input generating an AP is higher, reaching a mean population value of 0.15. In view of these results, the mode of synaptic integration at the level of the CN should be re-considered.
