Dysfunction of Small-Conductance Ca2+-Activated Potassium (SK) Channels Drives Amygdala Hyperexcitability and Neuropathic Pain Behaviors: Involvement of Epigenetic Mechanisms

Neuroplasticity in the amygdala and its central nucleus (CeA) is linked to pain modulation and pain behaviors, but cellular mechanisms are not well understood. Here, we addressed the role of small-conductance Ca2+-activated potassium (SK) channels in pain-related amygdala plasticity. The facilitatory effects of the intra-CeA application of an SK channel blocker (apamin) on the pain behaviors of control rats were lost in a neuropathic pain model, whereas an SK channel activator (NS309) inhibited pain behaviors in neuropathic rats but not in sham controls, suggesting the loss of the inhibitory behavioral effects of amygdala SK channels. Brain slice electrophysiology found hyperexcitability of CeA neurons in the neuropathic pain condition due to the loss of SK channel-mediated medium afterhyperpolarization (mAHP), which was accompanied by decreased SK2 channel protein and mRNA expression, consistent with a pretranscriptional mechanisms. The underlying mechanisms involved the epigenetic silencing of the SK2 gene due to the increased DNA methylation of the CpG island of the SK2 promoter region and the change in methylated CpG sites in the CeA in neuropathic pain. This study identified the epigenetic dysregulation of SK channels in the amygdala (CeA) as a novel mechanism of neuropathic pain-related plasticity and behavior that could be targeted to control abnormally enhanced amygdala activity and chronic neuropathic pain

Inhibition of microglial activity alters spinal wide dynamic range neuron discharge and reduces microglial Toll-like receptor 4 expression in neuropathic rats

It is believed that neuropathic pain results from aberrant neuronal discharges although some evidence suggests that the activation of glia cells contributes to pain after an injury to the nervous system. This study aimed to evaluate the role of microglial activation on the hyper-responsiveness of wide dynamic range neurons (WDR) and Toll-like receptor 4 (TLR4) expressions in a chronic constriction injury (CCI) model of neuropathic pain in rats. Adult male Wistar rats (230 � 30 g) underwent surgery for induction of CCI neuropathy. Six days after surgery, administration of minocycline (10, 20, and 40 mg/kg, i.p.) was initiated and continued until day 14. After administration of the last dose of minocycline or saline, a behavioral test was conducted, then animals were sacrificed and lumbar segments of the spinal cord were collected for Western blot analysis of TLR4 expression. The electrophysiological properties of WDR neurons were investigated by single unit recordings in separate groups. The findings showed that after CCI, in parallel with thermal hyperalgesia, the expression of TLR4 in the spinal cord and the evoked response of the WDR neurons to electrical, mechanical, and thermal stimulation significantly increased. Post-injury administration of minocycline effectively decreased thermal hyperalgesia, TLR4 expression, and hyperresponsiveness of WDR neurons in CCI rats. The results of this study indicate that post-injury, repeated administration of minocycline attenuated neuropathic pain by suppressing microglia activation and reducing WDR neuron hyperresponsiveness. This study confirms that post-injury modulation of microglial activity is a new strategy for treating neuropathic pain

Visuomotor Cerebellum in Human and Nonhuman Primates

In this paper, we will review the anatomical components of the visuomotor cerebellum in human and, where possible, in non-human primates and discuss their function in relation to those of extracerebellar visuomotor regions with which they are connected. The floccular lobe, the dorsal paraflocculus, the oculomotor vermis, the uvula–nodulus, and the ansiform lobule are more or less independent components of the visuomotor cerebellum that are involved in different corticocerebellar and/or brain stem olivocerebellar loops. The floccular lobe and the oculomotor vermis share different mossy fiber inputs from the brain stem; the dorsal paraflocculus and the ansiform lobule receive corticopontine mossy fibers from postrolandic visual areas and the frontal eye fields, respectively. Of the visuomotor functions of the cerebellum, the vestibulo-ocular reflex is controlled by the floccular lobe; saccadic eye movements are controlled by the oculomotor vermis and ansiform lobule, while control of smooth pursuit involves all these cerebellar visuomotor regions. Functional imaging studies in humans further emphasize cerebellar involvement in visual reflexive eye movements and are discussed

Dendritic excitation–inhibition balance shapes cerebellar output during motor behaviour

Feedforward excitatory and inhibitory circuits regulate cerebellar output, but how these circuits interact to shape the somatodendritic excitability of Purkinje cells during motor behaviour remains unresolved. Here we perform dendritic and somatic patch-clamp recordings in vivo combined with optogenetic silencing of interneurons to investigate how dendritic excitation and inhibition generates bidirectional (that is, increased or decreased) Purkinje cell output during self-paced locomotion. We find that granule cells generate a sustained depolarization of Purkinje cell dendrites during movement, which is counterbalanced by variable levels of feedforward inhibition from local interneurons. Subtle differences in the dendritic excitation–inhibition balance generate robust, bidirectional changes in simple spike (SSp) output. Disrupting this balance by selectively silencing molecular layer interneurons results in unidirectional firing rate changes, increased SSp regularity and disrupted locomotor behaviour. Our findings provide a mechanistic understanding of how feedforward excitatory and inhibitory circuits shape Purkinje cell output during motor behaviour

Spontaneous Activity Does Not Predict Morphological Type in Cerebellar Interneurons

The effort to determine morphological and anatomically defined neuronal characteristics from extracellularly recorded physiological signatures has been attempted with varying success in different brain areas. Recent studies have attempted such classification of cerebellar interneurons (CINs) based on statistical measures of spontaneous activity. Previously, such efforts in different brain areas have used supervised clustering methods based on standard parameterizations of spontaneous interspike interval (ISI) histograms. We worried that this might bias researchers toward positive identification results and decided to take a different approach. We recorded CINs from anesthetized cats. We used unsupervised clustering methods applied to a nonparametric representation of the ISI histograms to identify groups of CINs with similar spontaneous activity and then asked how these groups map onto different cell types. Our approach was a fuzzy C-means clustering algorithm applied to the Kullbach-Leibler distances between ISI histograms. We found that there is, in fact, a natural clustering of the spontaneous activity of CINs into six groups but that there was no relationship between this clustering and the standard morphologically defined cell types. These results proved robust when generalization was tested to completely new datasets, including datasets recorded under different anesthesia conditions and in different laboratories and different species (rats). Our results suggest the importance of an unsupervised approach in categorizing neurons according to their extracellular activity. Indeed, a reexamination of such categorization efforts throughout the brain may be necessary. One important open question is that of functional differences of our six spontaneously defined clusters during actual behavior

Spontaneous Activity Does Not Predict Morphological Type in Cerebellar Interneurons

The effort to determine morphological and anatomically defined neuronal characteristics from extracellularly recorded physiological signatures has been attempted with varying success in different brain areas. Recent studies have attempted such classification of cerebellar interneurons (CINs) based on statistical measures of spontaneous activity. Previously, such efforts in different brain areas have used supervised clustering methods based on standard parameterizations of spontaneous interspike interval (ISI) histograms. We worried that this might bias researchers toward positive identification results and decided to take a different approach. We recorded CINs from anesthetized cats. We used unsupervised clustering methods applied to a nonparametric representation of the ISI histograms to identify groups of CINs with similar spontaneous activity and then asked how these groups map onto different cell types. Our approach was a fuzzy C-means clustering algorithm applied to the Kullbach-Leibler distances between ISI histograms. We found that there is, in fact, a natural clustering of the spontaneous activity of CINs into six groups but that there was no relationship between this clustering and the standard morphologically defined cell types. These results proved robust when generalization was tested to completely new datasets, including datasets recorded under different anesthesia conditions and in different laboratories and different species (rats). Our results suggest the importance of an unsupervised approach in categorizing neurons according to their extracellular activity. Indeed, a reexamination of such categorization efforts throughout the brain may be necessary. One important open question is that of functional differences of our six spontaneously defined clusters during actual behavior