Experimental Neurobiology最新文献

Anoctamin 2 (ANO2 or TMEM16B), a calcium-activated chloride channel (CaCC), performs diverse roles in neurons throughout the central nervous system. In hippocampal neurons, ANO2 narrows action potential width and reduces postsynaptic depolarization with high sensitivity to Ca²⁺ at relatively fast kinetics. In other brain regions, including the thalamus, ANO2 mediates activity-dependent spike frequency adaptations with low sensitivity to Ca²⁺ at relatively slow kinetics. How this same channel can respond to a wide range of Ca²⁺ levels remains unclear. We hypothesized that splice variants of ANO2 may contribute to its distinct Ca²⁺ sensitivity, and thus its diverse neuronal functions. We identified two ANO2 isoforms expressed in mouse brains and examined their electrophysiological properties: isoform 1 (encoded by splice variants with exons 1a, 2, 4, and 14) was expressed in the hippocampus, while isoform 2 (encoded by splice variants with exons 1a, 2, and 4) was broadly expressed throughout the brain, including in the cortex and thalamus, and had a slower calcium-dependent activation current than isoform 1. Computational modeling revealed that the secondary structure of the first intracellular loop of isoform 1 forms an entrance cavity to the calcium-binding site from the cytosol that is relatively larger than that in isoform 2. This difference provides structural evidence that isoform 2 is involved in accommodating spike frequency, while isoform 1 is involved in shaping the duration of an action potential and decreasing postsynaptic depolarization. Our study highlights the roles and molecular mechanisms of specific ANO2 splice variants in modulating neuronal functions.

A cell-based model of Parkinson's disease (PD) is a well-established in vitro experimental prototype to investigate the disease mechanism and therapeutic approach for a potential anti-PD drug. The SH-SY5Y human neuroblastoma cells and 6-OHDA combo is one of the many neurotoxininduced neuronal cell models employed in numerous neuroscience-related research for discovering neuroprotective drug compounds. Emerging studies have reported a significant correlation between PD and epigenetic alterations, particularly DNA methylation. However, the DNA methylation changes of PD-related CpG sites on the 6-OHDA-induced toxicity on human neuronal cells have not yet been reported. We performed a genome-wide association study (GWAS) using Infinium Epic beadchip array surveying 850000 CpG sites in differentiated human neuroblastoma cells exposed to 6-OHDA. We identified 236 differentially methylated probes (DMPs) or 163 differentially methylated regions (DMRs) in 6-OHDA treated differentiated neuroblastoma cells than the untreated reference group with p<0.01, Δbeta cut-off of 0.1. Among 236 DMPs, hypermethylated DMPs are 110 (47%), whereas 126 (53%) are hypomethylated. Our bioinformatic analysis revealed 3 DMRs that are significantly hypermethylated and associated with neurological disorders, namely AKT1, ITPR1 and GNG7. This preliminary study demonstrates the methylation status of PD-related CpGs in the 6-OHDA-induced toxicity in the differentiated neuroblastoma cells model.

To develop a biomimetic artificial tactile sensing system capable of detecting sustained mechanical touch, we propose a novel biological neuron model (BNM) for slowly adapting type I (SA-I) afferent neurons. The proposed BNM is designed by modifying the Izhikevich model to incorporate long-term spike frequency adaptation. Adjusting the parameters renders the Izhikevich model describing various neuronal firing patterns. We also search for optimal parameter values for the proposed BNM to describe firing patterns of biological SA-I afferent neurons in response to sustained pressure longer than 1-second. We obtain the firing data of SA-I afferent neurons for six different mechanical pressure ranging from 0.1 mN to 300 mN from the ex-vivo experiment on SA-I afferent neurons in rodents. Upon finding the optimal parameters, we generate spike trains using the proposed BNM and compare the resulting spike trains to those of biological SA-I afferent neurons using the spike distance metrics. We verify that the proposed BNM can generate spike trains showing long-term adaptation, which is not achievable by other conventional models. Our new model may offer an essential function to artificial tactile sensing technology to perceive sustained mechanical touch.

Quantification of tyrosine hydroxylase (TH)-positive neurons is essential for the preclinical study of Parkinson's disease (PD). However, manual analysis of immunohistochemical (IHC) images is labor-intensive and has less reproducibility due to the lack of objectivity. Therefore, several automated methods of IHC image analysis have been proposed, although they have limitations of low accuracy and difficulties in practical use. Here, we developed a convolutional neural network-based machine learning algorithm for TH+ cell counting. The developed analytical tool showed higher accuracy than the conventional methods and could be used under diverse experimental conditions of image staining intensity, brightness, and contrast. Our automated cell detection algorithm is available for free and has an intelligible graphical user interface for cell counting to assist practical applications. Overall, we expect that the proposed TH+ cell counting tool will promote preclinical PD research by saving time and enabling objective analysis of IHC images.

Stroke destroys neurons and their connections leading to focal neurological deficits. Although limited, many patients exhibit a certain degree of spontaneous functional recovery. Structural remodeling of the intracortical axonal connections is implicated in the reorganization of cortical motor representation maps, which is considered to be an underlying mechanism of the improvement in motor function. Therefore, an accurate assessment of intracortical axonal plasticity would be necessary to develop strategies to facilitate functional recovery following a stroke. The present study developed a machine learning-assisted image analysis tool based on multi-voxel pattern analysis in fMRI imaging. Intracortical axons originating from the rostral forelimb area (RFA) were anterogradely traced using biotinylated dextran amine (BDA) following a photothrombotic stroke in the mouse motor cortex. BDA-traced axons were visualized in tangentially sectioned cortical tissues, digitally marked, and converted to pixelated axon density maps. Application of the machine learning algorithm enabled sensitive comparison of the quantitative differences and the precise spatial mapping of the post-stroke axonal reorganization even in the regions with dense axonal projections. Using this method, we observed a substantial extent of the axonal sprouting from the RFA to the premotor cortex and the peri-infarct region caudal to the RFA. Therefore, the machine learningassisted quantitative axonal mapping developed in this study can be utilized to discover intracortical axonal plasticity that may mediate functional restoration following stroke.

Subdiaphragmatic vagotomy (SDV) is known to produce analgesic effect in various pain conditions including not only visceral pain but also somatic pain. We aimed to determine brain mechanisms by which SDV induces analgesic effect in somatic pain condition by using formalin-induced acute inflammatory pain model. We identified brain regions that mediate SDV-induced analgesic effect on acute inflammatory pain by analyzing c-Fos expression in the whole brain. We found that c-Fos expression was specifically increased in the anterior insular cortex (aIC) among subregions of the insular cortex in acute inflammatory pain, which was reversed by SDV. These results were not mimicked in female mice, indicating sexual-dimorphism in SDV-induced analgesia. SDV decreased c-Fos expressions more preferentially in glutamatergic neurons rather than GABAergic neurons in the aIC, and pharmacological activation of glutamatergic neurons with NMDA in the aIC inhibited SDV-induced analgesic effect. Furthermore, chemogenetic activation of glutamatergic neurons in the aIC reversed SDV-induced analgesia. Taken together, our results suggest that the decrease in the neuronal activity of glutamatergic neurons in the aIC mediates SDV-induced analgesic effect, potentially serving as an important therapeutic target to treat inflammatory pain.

The FK506 binding protein 5 (FKBP5) is a co-chaperone that regulates the activity of the glucocorticoid receptor (GR) and has been reported to mediate stress resilience. This study aimed to determine the effects of Fkbp5 deletion on acute stress-induced recognition memory impairment and hippocampal GR signaling. Wild-type and Fkbp5-knockout mice were subjected to acute uncontrollable stress induced by restraint and electrical tail shock. First, we assessed the cognitive status of mice using a novel object recognition task. Next, we measured plasma corticosterone, GR levels, and the levels of GR phosphorylation at serine 211 in the hippocampus. Wild-type mice exhibited stress-induced memory impairments, whereas Fkbp5-knockout mice did not. Plasma corticosterone and GR levels did not differ between the non-stressed wild-type and Fkbp5-knockout mice, but the levels of phosphorylated GR were lower in Fkbp5-knockout mice than in wild-type mice. Wild-type and Fkbp5-knockout mice showed increased nuclear GR levels following stress, indicating GR translocation. However, cytosolic phosphorylated GR levels were lower in the hippocampi of Fkbp5-knockout mice following stress than in those of wild-type mice. These results suggest that FKBP5 deficiency increases resilience to acute stress by altering GR signaling.

Complex regional pain syndrome (CRPS) is a chronic neuropathic pain disorder. Pain catastrophizing, characterized by magnification, rumination, and helplessness, increases perceived pain intensity and mental distress in CRPS patients. As functional connectivity patterns in CRPS remain largely unknown, we aimed to investigate functional connectivity alterations in CRPS patients and their association with pain catastrophizing using a whole-brain analysis approach. Twenty-one patients with CRPS and 49 healthy controls were included in the study for clinical assessment and resting-state functional magnetic resonance imaging. Between-group differences in whole-brain functional connectivity were examined through a Network-based Statistics analysis. Associations between altered functional connectivity and the extent of pain catastrophizing were also assessed in CRPS patients. Relative to healthy controls, CRPS patients showed higher levels of functional connectivity in the bilateral somatosensory subnetworks (components 1~2), but lower functional connectivity within the prefronto-posterior cingulate (component 3), prefrontal (component 4), prefronto-parietal (component 5), and thalamo-anterior cingulate (component 6) subnetworks (p<0.05, family-wise error corrected). Higher levels of functional connectivity in components 1~2 (β=0.45, p=0.04) and lower levels of functional connectivity in components 3~6 (β=-0.49, p=0.047) were significantly correlated with higher levels of pain catastrophizing in CRPS patients. Higher functional connectivity in the somatosensory subnetworks implicating exaggerated pain perception and lower functional connectivity in the prefronto-parieto-cingulo-thalamic subnetworks indicating impaired cognitive-affective pain processing may underlie pain catastrophizing in CRPS.

Connectome, the complete wiring diagram of the nervous system of an organism, is the biological substrate of the mind. While biological neural networks are crucial to the understanding of neural computation mechanisms, recent artificial neural networks (ANNs) have been developed independently from the study of real neural networks. Computational scientists are searching for various ANN architectures to improve machine learning since the architectures are associated with the accuracy of ANNs. A recent study used the hermaphrodite Caenorhabditis elegans (C. elegans) connectome for image classification tasks, where the edge directions were changed to construct a directed acyclic graph (DAG). In this study, we used the whole-animal connectomes of C. elegans hermaphrodite and male to construct a DAG that preserves the chief information flow in the connectomes and trained them for image classification of MNIST and fashion-MNIST datasets. The connectome-inspired neural networks exhibited over 99.5% and 92.6% of accuracy for MNIST and fashion-MNIST datasets, respectively, which increased from the previous study. Together, we conclude that realistic biological neural networks provide the basis of a plausible ANN architecture. This study suggests that biological networks can provide new inspiration to improve artificial intelligences (AIs).

Ca²⁺+ transients can be observed in the distal dendrites of Purkinje cells (PCs) despite their lack of action potential backpropagation. These Ca²⁺+ events in distal dendrites require specific patterns of PC firing, such as complex spikes (CS) or simple spikes (SS) of burst mode. Unlike CS, which can act directly on voltage-gated calcium channels in the dendrites through climbing fiber inputs, the condition that can produce the Ca²⁺+ events in distal dendrites with burst mode SS is poorly understood. Here, we propose the interspike interval threshold (ISIT) for Ca²⁺+ transients in the distal dendrites of PC. We found that to induce the Ca²⁺+ transients in distal dendrites the frequency of spike firing of PC should reach 250 Hz (3 ms ISI). Metabotropic glutamate receptor 1 (mGluR1) activation significantly relieved the ISIT and established cellular conditions in which spike firing with 50 Hz (19 ms ISI) could induce Ca²⁺+ transients in the distal dendrites. In contrast, blocking T-type Ca²⁺+ channels or depleting the endoplasmic reticulum Ca²⁺+ store resulted in a stricter condition in which spike firing with 333 Hz (2 ms ISI) was required. Our findings demonstrate that the PC has strict ISIT for dendritic Ca²⁺+ transients, and this ISIT can be relieved by mGluR1 activation. This strict restriction of ISIT could contribute to the reduction of the signal-to-noise ratio in terms of collecting information by preventing excessive dendritic Ca²⁺+ transients through the spontaneous activity of PC.