GlyT2+ Neurons in the Lateral Cerebellar Nucleus

The deep cerebellar nuclei (DCN) are a major hub in the cerebellar circuitry but the functional classification of their neurons is incomplete. We have previously characterized three cell groups in the lateral cerebellar nucleus: large non-GABAergic neurons and two groups of smaller neurons, one of which express green fluorescence protein (GFP) in a GAD67/GFP mouse line and is therefore GABAergic. However, as a substantial number of glycinergic and glycine/GABA co-expressing neurons have been described in the DCN, this classification needed to be refined by considering glycinergic neurons. To this end we took advantage of a glycine transporter isoform 2 (GlyT2)-eGFP mouse line that allows identification of GlyT2-expressing, presumably glycinergic neurons in living cerebellar slices and compared their electrophysiological properties with previously described DCN neuron populations. We found two electrophysiologically and morphologically distinct sets of GlyT2-expressing neurons in the lateral cerebellar nucleus. One of them showed electrophysiological similarity to the previously characterized GABAergic cell group. The second GlyT2+ cell population, however, differed from all other so far described neuron types in DCN in that the cells (1) are intrinsically silent in slices and only fire action potentials upon depolarizing current injection and (2) have a projecting axon that was often seen to leave the DCN and project in the direction of the cerebellar cortex. Presence of this so far undescribed DCN neuron population in the lateral nucleus suggests a direct inhibitory pathway from the DCN to the cerebellar cortex

The thalamic mGluR1-PLC??4 pathway is critical in sleep architecture

The transition from wakefulness to a nonrapid eye movement (NREM) sleep state at the onset of sleep involves a transition from low-voltage, high-frequency irregular electroencephalography (EEG) waveforms to large-amplitude, low-frequency EEG waveforms accompanying synchronized oscillatory activity in the thalamocortical circuit. The thalamocortical circuit consists of reciprocal connections between the thalamus and cortex. The cortex sends strong excitatory feedback to the thalamus, however the function of which is unclear. In this study, we investigated the role of the thalamic metabotropic glutamate receptor 1 (mGluR1)-phospholipase C ??4 (PLC??4) pathway in sleep control in PLC??4-deficient (PLC??4-/-) mice. The thalamic mGluR1-PLC??4 pathway contains synapses that receive corticothalamic inputs. In PLC??4-/- mice, the transition from wakefulness to the NREM sleep state was stimulated, and the NREM sleep state was stabilized, which resulted in increased NREM sleep. The power density of delta (??) waves increased in parallel with the increased NREM sleep. These sleep phenotypes in PLC??4-/- mice were consistent in TC-restricted PLC??4 knockdown mice. Moreover, in vitro intrathalamic oscillations were greatly enhanced in the PLC??4-/- slices. The results of our study showed that thalamic mGluR1-PLC??4 pathway was critical in controlling sleep architecture.ope

Rebound Discharge in Deep Cerebellar Nuclear Neurons In Vitro

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 primary means of distinguishing between DCN neurons has been according to cell size and transmitter phenotype, but in some cases, differences in the firing properties of DCN cells maintained in vitro have been reported. In particular, it was shown that large diameter cells in the rat DCN exhibit two phenotypes of rebound discharge in vitro that may eventually help define their functional roles in cerebellar output. A transient burst and weak burst phenotype can be distinguished based on the frequency and pattern of rebound discharge immediately following a hyperpolarizing stimulus. Work to date indicates that the difference in excitability arises from at least the degree of activation of T-type Ca2+ current during the immediate phase of rebound firing and Ca2+-dependent K+ channels that underlie afterhyperpolarizations. Both phenotypes can be detected following stimulation of Purkinje cell inhibitory inputs under conditions that preserve resting membrane potential and natural ionic gradients. In this paper, we review the evidence supporting the existence of different rebound phenotypes in DCN cells and the ion channel expression patterns that underlie their generation

Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells

Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus because Purkinje cell inhibition has to be turned into an excitatory output signal, and DCN neurons exhibit complex intrinsic properties. In particular, DCN neurons exhibit a range of rebound spiking properties following hyperpolarizing current injection, raising the question how this could contribute to signal processing in behaving animals. Computer modeling presents an ideal tool to investigate how intrinsic voltage-gated conductances in DCN neurons could generate the heterogeneous firing behavior observed, and what input conditions could result in rebound responses. To enable such an investigation we built a compartmental DCN neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than −70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum