Stimulus-Dependent State Transition between Synchronized Oscillation and Randomly Repetitive Burst in a Model Cerebellar Granular Layer

Information processing of the cerebellar granular layer composed of granule and Golgi cells is regarded as an important first step toward the cerebellar computation. Our previous theoretical studies have shown that granule cells can exhibit random alternation between burst and silent modes, which provides a basis of population representation of the passage-of-time (POT) from the onset of external input stimuli. On the other hand, another computational study has reported that granule cells can exhibit synchronized oscillation of activity, as consistent with observed oscillation in local field potential recorded from the granular layer while animals keep still. Here we have a question of whether an identical network model can explain these distinct dynamics. In the present study, we carried out computer simulations based on a spiking network model of the granular layer varying two parameters: the strength of a current injected to granule cells and the concentration of Mg2+ which controls the conductance of NMDA channels assumed on the Golgi cell dendrites. The simulations showed that cells in the granular layer can switch activity states between synchronized oscillation and random burst-silent alternation depending on the two parameters. For higher Mg2+ concentration and a weaker injected current, granule and Golgi cells elicited spikes synchronously (synchronized oscillation state). In contrast, for lower Mg2+ concentration and a stronger injected current, those cells showed the random burst-silent alternation (POT-representing state). It is suggested that NMDA channels on the Golgi cell dendrites play an important role for determining how the granular layer works in response to external input

Tumor size before image-guided brachytherapy is an important factor of local control after radiotherapy for cervical squamous cell carcinoma: analysis in cases using central shielding

We analyzed the local control (LC) of cervical squamous cell carcinoma treated by computed tomography (CT)-based image-guided brachytherapy (IGBT) using central shielding (CS). We also examined the value of tumor diameter before brachytherapy (BT) as a factor of LC. In total, 97 patients were analyzed between April 2016 and March 2020. Whole-pelvic (WP) radiotherapy (RT) with CS was performed, and the total pelvic sidewall dose was 50 or 50.4 Gy; IGBT was delivered in 3-4 fractions. The total dose was calculated as the biologically equivalent dose in 2 Gy fractions, and distribution was modified manually by graphical optimization. The median follow-up period was 31.8 months (6.3-63.2 months). The 1- and 2-year LC rates were 89% and 87%, respectively. The hazard ratio was 10.11 (95% confidence interval: 1.48-68.99) for local recurrence in those with a horizontal tumor diameter >= 4 cm compared to those with = 4 cm, different treatment strategies such as employing interstitial-BT for dose escalation may be necessary

Slitrk2 deficiency causes hyperactivity with altered vestibular function and serotonergic dysregulation

SLITRK2 encodes a transmembrane protein that modulates neurite outgrowth and synaptic activities and is implicated in bipolar disorder. Here, we addressed its physiological roles in mice. In the brain, the Slitrk2 protein was strongly detected in the hippocampus, vestibulocerebellum, and precerebellar nuclei—the vestibular-cerebellar-brainstem neural network including pontine gray and tegmental reticular nucleus. Slitrk2 knockout (KO) mice exhibited increased locomotor activity in novel environments, antidepressant-like behaviors, enhanced vestibular function, and increased plasticity at mossy fiber–CA3 synapses with reduced sensitivity to serotonin. A serotonin metabolite was increased in the hippocampus and amygdala, and serotonergic neurons in the raphe nuclei were decreased in Slitrk2 KO mice. When KO mice were treated with methylphenidate, lithium, or fluoxetine, the mood stabilizer lithium showed a genotype-dependent effect. Taken together, Slitrk2 deficiency causes aberrant neural network activity, synaptic integrity, vestibular function, and serotonergic function, providing molecular-neurophysiological insight into the brain dysregulation in bipolar disorders

A Computational Mechanism for Unified Gain and Timing Control in the Cerebellum

Precise gain and timing control is the goal of cerebellar motor learning. Because the basic neural circuitry of the cerebellum is homogeneous throughout the cerebellar cortex, a single computational mechanism may be used for simultaneous gain and timing control. Although many computational models of the cerebellum have been proposed for either gain or timing control, few models have aimed to unify them. In this paper, we hypothesize that gain and timing control can be unified by learning of the complete waveform of the desired movement profile instructed by climbing fiber signals. To justify our hypothesis, we adopted a large-scale spiking network model of the cerebellum, which was originally developed for cerebellar timing mechanisms to explain the experimental data of Pavlovian delay eyeblink conditioning, to the gain adaptation of optokinetic response (OKR) eye movements. By conducting large-scale computer simulations, we could reproduce some features of OKR adaptation, such as the learning-related change of simple spike firing of model Purkinje cells and vestibular nuclear neurons, simulated gain increase, and frequency-dependent gain increase. These results suggest that the cerebellum may use a single computational mechanism to control gain and timing simultaneously

Cerebellar Globular Cells Receive Monoaminergic Excitation and Monosynaptic Inhibition from Purkinje Cells

Inhibitory interneurons in the cerebellar granular layer are more heterogeneous than traditionally depicted. In contrast to Golgi cells, which are ubiquitously distributed in the granular layer, small fusiform Lugaro cells and globular cells are located underneath the Purkinje cell layer and small in number. Globular cells have not been characterized physiologically. Here, using cerebellar slices obtained from a strain of gene-manipulated mice expressing GFP specifically in GABAergic neurons, we morphologically identified globular cells, and compared their synaptic activity and monoaminergic influence of their electrical activity with those of small Golgi cells and small fusiform Lugaro cells. Globular cells were characterized by prominent IPSCs together with monosynaptic inputs from the axon collaterals of Purkinje cells, whereas small Golgi cells or small fusiform Lugaro cells displayed fewer and smaller spontaneous IPSCs. Globular cells were silent at rest and fired spike discharges in response to application of either serotonin (5-HT) or noradrenaline. The two monoamines also facilitated small Golgi cell firing, but only 5-HT elicited firing in small fusiform Lugaro cells. Furthermore, globular cells likely received excitatory monosynaptic inputs through mossy fibers. Because globular cells project their axons long in the transversal direction, the neuronal circuit that includes interplay between Purkinje cells and globular cells could regulate Purkinje cell activity in different microzones under the influence of monoamines and mossy fiber inputs, suggesting that globular cells likely play a unique modulatory role in cerebellar motor control

The 3rd DBCLS BioHackathon: improving life science data integration with Semantic Web technologies.

BACKGROUND: BioHackathon 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and accessibility of life science research data on the Web by bringing together representatives from public databases, analytical tool providers, and cyber-infrastructure researchers to jointly tackle important challenges in the area of in silico biological research. RESULTS: The theme of BioHackathon 2010 was the 'Semantic Web', and all attendees gathered with the shared goal of producing Semantic Web data from their respective resources, and/or consuming or interacting those data using their tools and interfaces. We discussed on topics including guidelines for designing semantic data and interoperability of resources. We consequently developed tools and clients for analysis and visualization. CONCLUSION: We provide a meeting report from BioHackathon 2010, in which we describe the discussions, decisions, and breakthroughs made as we moved towards compliance with Semantic Web technologies - from source provider, through middleware, to the end-consumer.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.

X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution

Dynamics of the granule cells in response to sinusoidally oscillating MF signals at 0.5 Hz.

<p>(A) Top panel, spike patterns of 1,000 out of 102,400 granule cells during a cycle of MF signal oscillation (2.0 s = 0.5 Hz). Black dots indicate spike discharges. At the beginning and end of a cycle where the firing rate of MFs is low, granule cells elicit spikes uniformly at random. At the middle of a cycle where the firing rate of MFs is high, spike patterns exhibit a variety of temporal profiles. Bottom panel, the ratio of active granule cells, which plots the number of active granule cells in each 10 ms bin divided by the total number of granule cells ( = 102,400). (B) Spike patterns of 5 representative granule cells across 100 cycles of MF signal oscillation. Black dots and grey lines in each panel show spike discharges in each cycle and the averaged spike density histogram, respectively. The granular layer modeled as a random recurrent network generates a variety of discharge patterns of granule cells, which can be used to produce a sequence of active granule-cell populations. (C) Similarity index <i>S</i>(Δ<i>t</i>) defined by Eq. (7) for the spike patterns shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033319#pone-0033319-g002" target="_blank">Figure 2A</a>. The index monotonically decreases from 1 at Δ<i>t</i> = 0 to 0.58 as Δ<i>t</i> increases, suggesting that the active granule-cell population gradually changes into another, uncorrelated population over time. Therefore, a non-recurrent sequence of active granule-cell populations is generated. (D) Reproducibility index <i>R</i>(<i>t</i>) defined by Eq. (9) for 10 pairs of spike patterns for all granule cells across two successive cycles of MF signal oscillation. The reproducibility increases towards 0.9 at the beginning of a cycle, and then linearly decreases towards 0.8, suggesting that the spike patterns of granule cells are highly reproducible across cycles.</p

Simulation of OKR adaptation.

<p>(A and B) Learning-induced change of the firing of (A) a Purkinje cell and (B) a VN neuron at the 1st, 100th, 200th, and 300th cycles of MF signal oscillation (black to gray, respectively). The Purkinje cell increases the modulation from 3 to 24 spikes/s by decreasing the minimum firing frequency from 83 to 27 spikes/s. The maximal firing frequency changes modelately (from 89 to 75 spikes/s). The VN neuron increases the modulation from 21 to 33 spikes/s by increasing the maximal firing frequency from 63 to 121 spikes/s. The minimal firing frequency changes from 22 to 41 spikes/s. (C) Gain change with respect to the number of cycles. Gain ratio was defined by the modulation of a VN neuron at each 10 cycles divided by the modulation at the 1^st cycle. The gain ratio gradually increases and converges to 1.57 by 300 cycles. (D) The distribution of synaptic weights between active granule cells and Purkinje cells after 300 cycles of MF signal oscillation. The synaptic weights of active granule cells at the beginning and end of a cycle are uniformly distributed between 0.15 and 1, whereas these around the middle of a cycle are narrowly distributed between 0.15 and 0.5. Thus, the temporal change is reversely correlated with the waveform of the CF signal as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0033319#pone-0033319-g001" target="_blank">Figure 1B</a>. (E and F) Modulation of a VN neuron by 300 cycles of MF signal oscillation with different peak firing rates of (E) MFs at 25, 30, 35 and 40 spikes/s while setting that of CFs at 3 spikes/s, and (F) CFs at 2, 3, 4 and 5 spikes/s while setting that of MFs at 30 spikes/s (black to gray). In both cases, the modulation increases as their peak firing rates increase.</p

Summary of exponential functions.

<p>All units are in millisecond. Abbreviations: GR, granule cell; GO, Golgi cell; PKJ, Purkinje cell; BS, basket cell; VN, vestibular nuclear neuron; IO, inferior olivary neuron.</p