No Medium-Term Spinocerebellar Input Plasticity in Deep Cerebellar Nuclear Neurons In Vivo?
The existence of input plasticity in the deep cerebellar nuclear (DCN) cells of the adult cerebellum could have profound implications for our understanding of cerebellar function. Whereas the existence of plastic changes in mossy fiber (mf) synaptic responses in DCN neurons has been demonstrated in juvenile slices, there has so far been no direct demonstration of this form of plasticity in the adult cerebellum in vivo. In the present paper, we recorded from neurons in the anterior interposed nucleus (AIN) and stimulated the spinocerebellar tracts (SCT) directly or via the skin to obtain mf activation and the inferior olive to activate climbing fibers (cfs) in the nonanesthetized, adult, decerebrated cat. We used three different types of protocols that theoretically could be expected to induce plasticity, each of which involved episodically intense afferent activation lasting for 10 min. These were conjunctive mf-cf activation, which effectively induces plasticity in cortical neurons; mf and cf activation in a pattern resembling the protocol for inducing classical conditioning; and conjunctive activation of two excitatory mf inputs. None of these protocols had any statistically significant effect on the evoked responses in the AIN neurons. We conclude that the input plasticity for excitatory mfs in the AIN cells of the adult cerebellum in vivo is likely to be less effective than that of parallel fiber synaptic inputs in cerebellar cortical cells, at least in the timespan of 1 h.
KeywordsPlasticity Deep cerebellar nuclear neurons Mossy fibers Climbing fibers
Plasticity in the neurons of the deep cerebellar nuclei as a substrate for behavioral learning has been debated for a long time, and theoretical predictions and circumstantial evidence have been used to argue that it may be required in some situations of presumed cerebellar-dependent adaptation [7, 24, 25, 29, 34]. Plasticity of deep cerebellar nuclear (DCN) neuron intrinsic excitability  and mossy fiber (mf) inputs [26, 27] have been demonstrated in vitro, but in these cases, only for slice preparations of the juvenile cerebellum. Whereas major changes in the circuitry structure and physiology may be expected to occur during development, cerebellar adaptation works also in adult life and it is important for our understanding of the functioning of the cerebellum to know whether these changes can occur and consequently contribute to adaptation and learning also during adult life. A recent indication that this may be the case was a study where sprouting of mf axons in the DCN was observed after a period of intense training over several days, but this is typically one order of magnitude slower than the timescale on which the cerebellar adaption is believed to work . In any case, it remains to be shown that the effective input to the DCN neurons increases under these conditions.
From a limb control point of view, an important source of information to the neurons of the interpositus nuclei comes from the spinocerebellar and spinoreticulocerebellar systems (SCTs). These are among the few mf systems that have been shown to directly innervate DCN neurons through collaterals of their axons that pass by the nuclei before they form mf synapses in the cortex [3, 19, 20, 21, 22, 23, 33]. These mf systems sample information about ongoing activity in spinal sensorimotor circuits, which may be crucial for our capacity to achieve limb intersegment coordination . Hence, synaptic plasticity in the mf-DCN connections of these systems could theoretically alter the conditions for limb coordination control. A consistent relationship between the location of the cutaneous climbing fiber (cf) receptive field and the distribution of skin areas from which excitatory inputs were evoked in anterior interposed nucleus (AIN) neurons was recently described . This relationship suggests the presence of a cf-dependent plasticity mechanism for regulating the excitatory mf inputs to DCN neurons. Alternatively, the location of the cf receptive field reflects the motor control function of the DCN cell [6, 13], and the synapses of the spinocerebellar tract (SCT) mfs most frequently associated with that specific motor control function could be strengthened through activity-dependent mechanisms, possibly NMDA-receptor dependent , triggered by the degree of correlated pre- and postsynaptic activity.
Materials and Methods
The experimental procedures were approved in advance by the Malmö/Lund Animal Research Ethics Committee (permit number and approval-ID: M32-09 and M05-12). Initial surgery was performed under propofol anesthesia, and all efforts were made to minimize suffering. Our EEG recordings were characterized by a background of periodic 1–4 Hz oscillatory activity, periodically interrupted by large-amplitude 7–14 Hz spindle oscillations lasting for 0.5 s or more. These forms of EEG activities are normally associated with deep stages of sleep. The pattern of EEG activity and the blood pressure remained stable and did not change with noxious stimulation throughout experiments.
Adult cats (N = 14) were prepared as previously described. Briefly, following an initial anesthesia with propofol (Diprivan® Zeneca Ltd., Macclesfield Cheshire, UK), the animals were decerebrated at the intercollicular level and the anesthesia was discontinued. The animals were artificially ventilated and the end-expiratory CO2, blood pressure, and rectal temperature were continuously monitored and maintained within physiological limits. Mounting in a stereotaxic frame, drainage of cerebrospinal fluid, pneumothorax, and clamping the spinal processes of a few cervical and lumbar vertebral bodies served to increase the mechanical stability of the preparation. The dorsal part of the pars intermedia of the left cerebellum was exposed to allow microelectrode access to the AIN. An additional exposure was made of the brainstem/spinal cord junction between the base of the skull and the first cervical vertebra. All exposed areas were covered in paraffin oil to prevent tissue drying.
Recordings and Stimulation
Patch clamp pipettes or metal microelectrodes (tungsten-in-glass microelectrodes, exposed tip 10–20 μm) were advanced to target the AIN as previously described [3, 4]. All neurons included in this study were putative glutamatergic projections neurons, based on the preponderance of short (<25 ms) interspike intervals and intermediate spike-widths . We recorded neurons from both forelimb and hindlimb regions of this nucleus, as identified using the location of the cf receptive field of the afferent Purkinje cells (Fig. 1). This location can be mapped out using electrical stimulation of the skin (0.1 ms pulses of 1.0 mA applied through percutaneous needle electrodes )—if the cfs of the locally afferent Purkinje cells are activated by the stimulation, characteristic local field potentials [6, 8] and postinhibitory rebound responses of the DCN neurons can be recorded . In this way, the location of the cf receptive field can be identified.
In order to stimulate the spinocerebellar and spinoreticulocerebellar tracts, which provide direct mf synaptic inputs to the interpositus nuclei, we placed a tungsten-in-glass microelectrode (exposed tip 50–150 μm) for stimulation laterally at the border between the spinal cord and brainstem. Using this stimulation microelectrode, mf field potentials recorded inside the AIN were routinely evoked at threshold intensities of <20 μA (single stimulus pulse of 0.1 ms duration), suggesting an effective recruitment of directly and synaptically activated (via the lateral reticular nucleus) mf synapses. In addition, we used electrical skin stimulation (pair of percutaneous needle electrodes with 5–10 mm spacing, stimulated at 1 mA shocks with 0.1 ms duration) to recruit another putative pool of spinocerebellar mfs. Cutaneous input is known to activate parts of the spinocerebellar neuron population, and since the other pathway mediating cutaneously activated mf input, the main cuneate nucleus does not terminate in the AIN ; potent excitatory responses evoked from the skin  are likely due to spinocerebellar mfs which should be at least partly non-overlapping with the population of mfs activated from the brain stem. The skin stimulation used was verified to not activate the afferent cfs and evoked a monophasic excitatory response .
In order to activate cfs, a second stimulation electrode was placed in the inferior olive, where low-threshold cf responses (evoked at <10 μA) could be evoked in the pars intermedia of the cerebellar cortex and in the AIN [4, 15].
The combined SCT and skin burst stimulation protocol. The SCT electrode was stimulated with 15 pulses at 200 Hz, and the skin was stimulated 10 times at 333 Hz. With this configuration, the two inputs evoked largely overlapping time windows of excitation. The SCT stimulation intensity was typically 30–70 μA, in a couple of cases 100 μA.
The skin burst and simultaneous, single inferior olive (IO) stimulation protocol. The IO was stimulated once, and a skin burst stimulation of 50 pulses at 333 Hz was started 10 ms in advance in order for the first mf input to arrive at the same time as the cf input (the mf input evoked from the periphery needs at in the order of 10 ms to reach the cerebellar nuclei ).
The skin burst and delayed single IO stimulation protocol. A skin burst stimulation of 50 pulses at 333 Hz and at the time point of the last stimulation pulse, a single-pulse IO stimulation was applied.
For all three protocols, the bursts were repeated at 0.33 Hz for 10 min, i.e., for a total of 200 repetitions.
We quantified the responses obtained from a single-pulse stimulation, either to the SCT or to the skin, before and after a burst stimulation protocol. For the protocols involving skin bursts and the simultaneous or delayed IO stimulation, respectively, the responses were quantified using peristimulus histograms of raw spike time data (5 ms bin width). For the display and analysis of the combined skin burst and SCT stimulation protocol, we used a kernel density estimation (KDE) plot, i.e., each spike was replaced by a Gaussian distribution with standard deviation of 0.5 ms. The averaged sum of all Gaussian distributions transforms a discrete spiking pattern into a continuous function describing the spiking probability on a continuous time scale. The standard deviation of the kernels was set so that the total spiking probability function was smooth across neurons. This was done as the responses to the SCT stimulation were brief, which reduced the total number of spikes and made the responses more sensitive to chance distributions of single spikes. The KDE helped in reducing this problem. See Hoebeek et al.  for a more comprehensive discussion on KDE.
In all cases, the response was quantified as the mean firing frequency during the time window of the response, with the firing frequencies being obtained either from the KDE plots or the peristimulus histograms. To smooth the signal used in the analysis, the peristimulus histograms were filtered with a moving average of width 15 ms. The response onset was counted from the first occurrence of at least two consecutive bins with an activity that exceeded the baseline activity by at least two standard deviations. The end of the response was defined as the bin where the activity decreased to the threshold. For each cell, the time window for the response was initially calculated individually for every peristimulus histogram (i.e., control and all the post-protocol time points). Then the median start and end points of the responses were used to define the response time window for the cell, in which the response was quantified. The response was quantified as the mean net activity during the defined time window. For responses evoked by SCT, the responses obtained were typically evoked between 1.5 to 4.0 ms after the onset of the stimulation. The KDE in itself did not allow a rigorous setting of the time limits, but histograms of the raw data provided a support for the chosen time limits in a similar fashion as above. For responses evoked by the skin, the quantified data was typically evoked within a response latency time window of 10–30 ms after the onset of the skin stimulation.
Subsequently, the relative response for each set of single-pulse stimulations was compared to the relative response before onset of the burst protocol and the change in response from each cell was analyzed in separate consecutive time spans of 10 min (time points). The null hypothesis that there was no net change in the response was tested using Wilcoxon signed-rank test. The signed-rank test was computed for each time point by comparing the total number of cells with the number of cells with a positive response. The probability for the outcome is calculated, assuming there is a 50% probability for each cell having a positive change in response.
Effects of Combined SCT Burst and Skin Burst Stimulation Protocol
Number of cells with positive changes in response amplitude versus the total number of cells shown, respectively, for each stimulation protocol and each time point. If there is no systematic potentiation or depression, on average, there should be as many cells with positive as with negative changes in response amplitude
Number of cells with positive response change
Total number of cells
Wilcoxon signed-rank test
Combined SCT and skin burst protocol
Skin burst and simultaneous single IO stimulation protocol
Skin burst and delayed single IO stimulation protocol
Effect of the Skin Burst and Simultaneous, Single IO Stimulation Protocol
Effect of the Skin Burst and Delayed Single IO Stimulation Protocol
In the present study, we tested whether the efficacy of mf input to DCN neurons could be altered using any out of the three different types of stimulation protocols in the adult cerebellum in vivo. Essentially, no effects were obtained over the first 10–90 min following the termination of any of the stimulation protocols. This is in contrast to the dramatic effects obtained in the neurons of the cerebellar cortex over a similar time span using related stimulation protocols [11, 12, 14, 16]. We conclude that at least in terms of efficacy and speed of induction, plasticity in the mf-DCN neuron synapse appears to be much less effective than in the parallel fiber synapses in the cortex. The potential consequences for our understanding of the function of the cerebellum in learning and adaptation are discussed.
It could of course be argued that the data set was limited and that other results would have been obtained with more data. While this is always true for any data, visual inspection of the time course of net changes in post-protocol response amplitude in all cells revealed no trend in the data in either direction, again in contrast to data from the cerebellar cortex (see above). On basis of the absence of any trend, we could hence not defend extending the data acquisition in these very time consuming and difficult experiments. At the same time, the scientific community has repeatedly realized that it is important that also negative findings are published [17, 18], even though it can be argued that they are less conclusive.
First, it is important to point out that these findings do not imply that mf-interpositus plasticity does not exist in the adult cerebellum. It is of course possible that other protocols that we did not try would have been more effective. Perhaps a more likely possibility is that more long-term protocols and longer duration AIN cell recordings could have provided a different answer. In experiments of classically conditioned eyeblink responses, for example, effects in the Purkinje cell responses start to emerge at the same time scale as we were looking at here but they evolve substantially for hours after . It should also be noted that we used much shorter intertrial intervals than in the latter paper, so comparisons cannot be made directly. The structural changes observed in mf collaterals to the DCN after repeated training protocols  was obtained only after several days of training, but it was not possible for us to follow single neurons for a comparable amount of time. In comparison with mf synaptic plasticity in juvenile slices [26, 27], however, the time scales were comparable but the results were very different. Notably, apart from age differences there was also a striking difference between the protocols: an important component in the slice work was the presence of a 20–25-mV hyperpolarization of the DCN neuron during the stimulation of the mf synapses, which lasted for at least 150 ms in order to initiate a postinhibitory rebound . In the in vivo setting, such a hyperpolarization would appear to translate to a simultaneous activation of all of the afferent Purkinje cells to firing rates of 200–300 Hz for the duration of the period of inhibition , which appears to be a completely unlikely scenario in the adult cerebellum. This does not necessarily exclude that the fundamental plasticity mechanism described in the slice [26, 27] applies in vivo, but may suggest that the mechanism could operate on a much slower time course in the adult cerebellum in vivo, where these extreme cases of concerted Purkinje cell activity may not appear.
An interesting aspect is the contrast to the effects observed in cerebellar cortical neurons using similar protocols and, in at least one case, comparable recording times [14, 16]. This suggests that there is likely to be a difference between the interpositus cells and the cortical neurons at least in their propensity for plasticity of excitatory inputs. From a functional point of view, this may make sense. The limb areas of the AIN are an integral part of a motor command loop, which via direct connections to rubrospinal and thalamocortical neurons innervating the motor cortex can strongly influence the activity of spinal premotor interneurons . These interneurons are probably very important for the synergy selection, i.e., which muscles are to be activated at what time during the execution of a complex, well-trained movement . Since some of these interneurons provide feedback to the cerebellum, directly or via the lateral reticular nucleus, and since this feedback is the information that is provided by the spinocerebellar mf-DCN synapses, this synaptic linkage can be important for associating and linking specific synergy patterns into compound movements. As they are one of the fundaments of the core motor command loop, it may be important to let them become stabilized after development when basic movement patterns/synergy patterns have been acquired. Fine-tuning of the drive of these synergy patterns during specific phases/contexts of a movement can be achieved via the cerebellar cortex and its inhibitory control of the AIN neurons. This fine-tuning can be minor adaptations required by changes in muscle strength over time or context-dependent factors, for example, which do not require a change in the fundamental movement patterns. Such adaptations must be allowed to occur more rapidly and could be primarily brought about by alterations in the cortical network—this would be an explanation for the different propensities for input plasticity in the cortex as compared to the AIN neurons.
The authors wish to express their gratitude to Tommy Schyman, statistician at Region Skåne, for answering the methodological questions about the statistical analysis. This study was supported by grants from NINDS/NIH (R01 NS040863), The Hand Embodied (THE) (an Integrated Project funded by the EU under FP7, project no. 248587), and the Swedish Research Council (VR Medicine). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
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