Search

IntroductionPain that arises spontaneously is considered more clinically relevant than pain evoked by external stimuli. However, measuring spontaneous pain in animal models in preclinical studies is challenging due to methodological limitations. To address this issue, recently we developed a deep learning (DL) model to assess spontaneous pain using cellular calcium signals of the primary somatosensory cortex (S1) in awake head-fixed mice. However, DL operate like a “black box”, where their decision-making process is not transparent and is difficult to understand, which is especially evident when our DL model classifies different states of pain based on cellular calcium signals. In this study, we introduce a novel machine learning (ML) model that utilizes features that were manually extracted from S1 calcium signals, including the dynamic changes in calcium levels and the cell-to-cell activity correlations.MethodWe focused on observing neural activity patterns in the primary somatosensory cortex (S1) of mice using two-photon calcium imaging after injecting a calcium indicator (GCaMP6s) into the S1 cortex neurons. We extracted features related to the ratio of up and down-regulated cells in calcium activity and the correlation level of activity between cells as input data for the ML model. The ML model was validated using a Leave-One-Subject-Out Cross-Validation approach to distinguish between non-pain, pain, and drug-induced analgesic states.Results and discussionThe ML model was designed to classify data into three distinct categories: non-pain, pain, and drug-induced analgesic states. Its versatility was demonstrated by successfully classifying different states across various pain models, including inflammatory and neuropathic pain, as well as confirming its utility in identifying the analgesic effects of drugs like ketoprofen, morphine, and the efficacy of magnolin, a candidate analgesic compound. In conclusion, our ML model surpasses the limitations of previous DL approaches by leveraging manually extracted features. This not only clarifies the decision-making process of the ML model but also yields insights into neuronal activity patterns associated with pain, facilitating preclinical studies of analgesics with higher potential for clinical translation.

Abstract Histone modifications are a key mechanism underlying the epigenetic regulation of gene expression, which is critically involved in the consolidation of multiple forms of memory. However, the roles of histone modifications in cerebellum-dependent motor learning and memory are not well understood. To test whether changes in histone methylation are involved in cerebellar learning, we used heterozygous Kdm3b knockout (Kdm3b +/−) mice, which show reduced lysine 9 on histone 3 (H3K9) demethylase activity. H3K9 di-methylation is significantly increased selectively in the granule cell layer of the cerebellum of Kdm3b +/− mice. In the cerebellum-dependent optokinetic response (OKR) learning, Kdm3b +/− mice show deficits in memory consolidation, whereas they are normal in basal oculomotor performance and OKR acquisition. In addition, RNA-seq analyses revealed that the expression levels of several plasticity-related genes were altered in the mutant cerebellum. Our study suggests that active regulation of histone methylation is critical for the consolidation of cerebellar motor memory.

Abstract Alzheimer’s disease (AD) is a neurodegenerative disorder associated with deficits in cognition and synaptic plasticity. While accumulation of amyloid β (Aβ) and hyper-phosphorylation of tau are parts of the etiology, AD can be caused by a large number of different genetic mutations and other unknown factors. Considering such a heterogeneous nature of AD, it would be desirable to develop treatment strategies that can improve memory irrespective of the individual causes. Reducing the phosphorylation of eukaryotic translation initiation factor 2α (eIF2α) was shown to enhance long-term memory and synaptic plasticity in naïve mice. Moreover, hyper-phosphorylation of eIF2α is observed in the brains of postmortem AD patients. Therefore, regulating eIF2α phosphorylation can be a plausible candidate for restoring memory in AD by targeting memory-enhancing mechanism. In this study, we examined whether PKR inhibition can rescue synaptic and learning deficits in two different AD mouse models; 5XFAD transgenic and Aβ1–42-injected mice. We found that the acute treatment of PKR inhibitor (PKRi) can restore the deficits in long-term memory and long-term potentiation (LTP) in both mouse models without affecting the Aβ load in the hippocampus. Our results prove the principle that targeting memory enhancing mechanisms can be a valid candidate for developing AD treatment.

Neuropathic pain is an intractable chronic pain, caused by damage to the somatosensory nervous system. To date, treatment for neuropathic pain has limited effects. For the development of efficient therapeutic methods, it is essential to fully understand the pathological mechanisms of neuropathic pain. Besides abnormal sensitization in the periphery and spinal cord, accumulating evidence suggests that neural plasticity in the brain is also critical for the development and maintenance of this pain. Recent technological advances in the measurement and manipulation of neuronal activity allow us to understand maladaptive plastic changes in the brain during neuropathic pain more precisely and modulate brain activity to reverse pain states at the preclinical and clinical levels. In this review paper, we discuss the current understanding of pathological neural plasticity in the four pain-related brain areas: the primary somatosensory cortex, the anterior cingulate cortex, the periaqueductal gray, and the basal ganglia. We also discuss potential treatments for neuropathic pain based on the modulation of neural plasticity in these brain areas.

MicroRNAs (miRNAs) are small, noncoding RNAs that posttranscriptionally regulate gene expression in many tissues. Although a number of brain-enriched miRNAs have been identified, only a few specific miRNAs have been revealed as critical regulators of synaptic plasticity, learning, and memory. miR-9-5p/3p are brain-enriched miRNAs known to regulate development and their changes have been implicated in several neurological disorders, yet their role in mature neurons in mice is largely unknown. Here, we report that inhibition of miR-9-3p, but not miR-9-5p, impaired hippocampal long-term potentiation (LTP) without affecting basal synaptic transmission. Moreover, inhibition of miR-9-3p in the hippocampus resulted in learning and memory deficits. Furthermore, miR-9-3p inhibition increased the expression of the LTP-related genes Dmd and SAP97, the expression levels of which are negatively correlated with LTP. These results suggest that miR-9-3p-mediated gene regulation plays important roles in synaptic plasticity and hippocampus-dependent memory. [ABSTRACT FROM AUTHOR]