scholarly journals Internally Generated Time in the Rodent Hippocampus is Logarithmically Compressed

2021 ◽  
Author(s):  
Rui Cao ◽  
John H Bladon ◽  
Stephen J Charczynski ◽  
Michael Hasselmo ◽  
Marc Howard
Keyword(s):  
Bayesian Model ◽  
Firing Pattern ◽  
Sensory Input ◽  
Population Level ◽  
Recent Experience ◽  
Logarithmic Scale ◽  
Hierarchical Bayesian Model ◽  
Cell Level ◽  
Quantitative Evidence ◽  
Temporal Representation

The Weber-Fechner law proposes that our perceived sensory input increases with physical input on a logarithmic scale. Hippocampal "time cells" carry a record of recent experience by firing sequentially during a circumscribed period of time after a triggering stimulus. Different cells have "time fields" at different delays up to at least tens of seconds. Past studies suggest that time cells represent a compressed timeline by demonstrating that fewer time cells fire late in the delay and their time fields are wider. This paper asks whether the compression of time cells obeys the Weber-Fechner Law. Time cells were studied with a hierarchical Bayesian model that simultaneously accounts for the firing pattern at the trial level, cell level, and population level. This procedure allows separate estimates of the within-trial receptive field width and the across-trial variability. The analysis at the trial level suggests the time cells represent an internally coherent timeline as a group. Furthermore, even after isolating across-trial variability, time field width increases linearly with delay. Finally, we find that the time cell population is distributed evenly on a logarithmic time scale. Together, these findings provide strong quantitative evidence that the internal neural temporal representation is logarithmically compressed and obeys a neural instantiation of the Weber- Fechner Law.

scholarly journals scMET: Bayesian modeling of DNA methylation heterogeneity at single-cell resolution

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Chantriolnt-Andreas Kapourani ◽  
Ricard Argelaguet ◽  
Guido Sanguinetti ◽  
Catalina A. Vallejos
Keyword(s):  
Single Cell ◽  
Bayesian Modeling ◽  
Bayesian Model ◽  
Regulation Of Gene Expression ◽  
Differential Methylation ◽  
Hierarchical Bayesian Model ◽  
Genomic Features ◽  
Distinct Cell ◽  
Biological Heterogeneity

AbstractHigh-throughput single-cell measurements of DNA methylomes can quantify methylation heterogeneity and uncover its role in gene regulation. However, technical limitations and sparse coverage can preclude this task. scMET is a hierarchical Bayesian model which overcomes sparsity, sharing information across cells and genomic features to robustly quantify genuine biological heterogeneity. scMET can identify highly variable features that drive epigenetic heterogeneity, and perform differential methylation and variability analyses. We illustrate how scMET facilitates the characterization of epigenetically distinct cell populations and how it enables the formulation of novel hypotheses on the epigenetic regulation of gene expression. scMET is available at https://github.com/andreaskapou/scMET.

scholarly journals Additive genetic variance and covariance between relatives in synthetic wheat crosses with variable parental ploidy levels

Genetics ◽  
2021 ◽  
Vol 217 (2) ◽  
Author(s):  
L E Puhl ◽  
J Crossa ◽  
S Munilla ◽  
P Pérez-Rodríguez ◽  
R J C Cantet
Keyword(s):  
Hexaploid Wheat ◽  
Variance Components ◽  
Bayesian Model ◽  
Synthetic Hexaploid Wheat ◽  
Data Sets ◽  
Hierarchical Bayesian Model ◽  
Additive Variance ◽  
Ploidy Levels ◽  
Breeding Values ◽  
Synthetic Hexaploid

Abstract Cultivated bread wheat (Triticum aestivum L.) is an allohexaploid species resulting from the natural hybridization and chromosome doubling of allotetraploid durum wheat (T. turgidum) and a diploid goatgrass Aegilops tauschii Coss (Ae. tauschii). Synthetic hexaploid wheat (SHW) was developed through the interspecific hybridization of Ae. tauschii and T. turgidum, and then crossed to T. aestivum to produce synthetic hexaploid wheat derivatives (SHWDs). Owing to this founding variability, one may infer that the genetic variances of native wild populations vs improved wheat may vary due to their differential origin and evolutionary history. In this study, we partitioned the additive variance of SHW and SHWD with respect to their breed origin by fitting a hierarchical Bayesian model with heterogeneous covariance structure for breeding values to estimate variance components for each breed category, and segregation variance. Two data sets were used to test the proposed hierarchical Bayesian model, one from a multi-year multi-location field trial of SHWD and the other comprising the two species of SHW. For the SHWD, the Bayesian estimates of additive variances of grain yield from each breed category were similar for T. turgidum and Ae. tauschii, but smaller for T. aestivum. Segregation variances between Ae. tauschii—T. aestivum and T. turgidum—T. aestivum populations explained a sizable proportion of the phenotypic variance. Bayesian additive variance components and the Best Linear Unbiased Predictors (BLUPs) estimated by two well-known software programs were similar for multi-breed origin and for the sum of the breeding values by origin for both data sets. Our results support the suitability of models with heterogeneous additive genetic variances to predict breeding values in wheat crosses with variable ploidy levels.

scholarly journals Citizen science via social media revealed conditions of symbiosis between a marine gastropod and an epibiotic alga

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Osamu Kagawa ◽  
◽  
Shota Uchida ◽  
Daishi Yamazaki ◽  
Yumiko Osawa ◽  
...  
Keyword(s):  
Social Media ◽  
Heat Stress ◽  
Environmental Factors ◽  
Citizen Science ◽  
Bayesian Model ◽  
Symbiotic Relationship ◽  
Hierarchical Bayesian Model ◽  
Symbiotic Interaction ◽  
Intertidal Gastropod ◽  
Substrate Size

AbstractEnvironmental factors promote symbiosis, but its mechanism is not yet well understood. The alga Pseudocladophora conchopheria grows only on the shell of an intertidal gastropod Lunella correensis, and these species have a close symbiotic relationship which the alga reduces heat stress of the gastropod. In collaboration with general public, we investigated how environmental conditions alter the symbiotic interaction between the alga and the gastropod. Information about the habitats of each gastropod and images of shells was obtained from the Japanese and Korean coasts via social media. We constructed the hierarchical Bayesian model using the data. The results indicated that the proportion of shell area covered by P. conchopheria increased as the substrate size utilized by the gastropod increased. Meanwhile, temperature did not affect the proportion of P. conchopheria on the shell. These suggested that the alga provides no benefits for the gastropod on small substrates because gastropod can reduce the heat stress by diving into the small sediment. Further, the gastropod’s cost incurred by growing the alga on the shell seems to be low as the algae can grow even in cooler places where no benefits of heat resistance for gastropods. Different environments can yield variable conditions in symbiosis.

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