Evaluating the Robustness of Parameter Estimates in Cognitive Models: A Meta-Analytic Review of Multinomial Processing Tree Models Across the Multiverse of Estimation Methods

Researchers have become increasingly aware that data-analysis decisions affect results. Here, we examine this issue systematically for multinomial processing tree (MPT) models, a popular class of cognitive models for categorical data. Specifically, we examine the robustness of MPT model parameter estimates that arise from two important decisions: the level of data aggregation (complete-pooling, no-pooling, or partial-pooling) and the statistical framework (frequentist or Bayesian). These decisions span a multiverse of estimation methods. We synthesized the data from 13,956 participants (164 published data sets) with a meta-analytic strategy and analyzed the magnitude of divergence between estimation methods for the parameters of nine popular MPT models in psychology (e.g., process-dissociation, source monitoring). We further examined moderators as potential sources of divergence. We found that the absolute divergence between estimation methods was small on average (<.04; with MPT parameters ranging between 0 and 1); in some cases, however, divergence amounted to nearly the maximum possible range (.97). Divergence was partly explained by few moderators (e.g., the specific MPT model parameter, uncertainty in parameter estimation), but not by other plausible candidate moderators (e.g., parameter trade-offs, parameter correlations) or their interactions. Partial-pooling methods showed the smallest divergence within and across levels of pooling and thus seem to be an appropriate default method. Using MPT models as an example, we show how transparency and robustness can be increased in the field of cognitive modeling. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

Evaluating the Robustness of Parameter Estimates in Cognitive Models: A Meta-Analytic Review of Multinomial Processing Tree Models Across the Multiverse of Estimation Methods

Researchers have become increasingly aware that data-analysis decisions affect results. Here, we examine this issue systematically for multinomial processing tree (MPT) models, a popular class of cognitive models for categorical data. Specifically, we examine the robustness of MPT model parameter estimates that arise from two important decisions: the level of data aggregation (complete-pooling, no-pooling, or partial-pooling) and the statistical framework (frequentist or Bayesian). These decisions span a multiverse of estimation methods. We synthesized the data from 13,956 participants (164 published data sets) with a meta-analytic strategy and analyzed the magnitude of divergence between estimation methods for the parameters of nine popular MPT models in psychology (e.g., process-dissociation, source monitoring). We further examined moderators as potential sources of divergence. We found that the absolute divergence between estimation methods was small on average (<.04; with MPT parameters ranging between 0 and 1); in some cases, however, divergence amounted to nearly the maximum possible range (.97). Divergence was partly explained by few moderators (e.g., the specific MPT model parameter, uncertainty in parameter estimation), but not by other plausible candidate moderators (e.g., parameter trade-offs, parameter correlations) or their interactions. Partial-pooling methods showed the smallest divergence within and across levels of pooling and thus seem to be an appropriate default method. Using MPT models as an example, we show how transparency and robustness can be increased in the field of cognitive modeling

Inducible Gene Manipulations in Brain Serotonergic Neurons of Transgenic Rats

The serotonergic (5-HT) system has been implicated in various physiological processes and neuropsychiatric disorders, but in many aspects its role in normal and pathologic brain function is still unclear. One reason for this might be the lack of appropriate animal models which can address the complexity of physiological and pathophysiological 5-HT functioning. In this respect, rats offer many advantages over mice as they have been the animal of choice for sophisticated neurophysiological and behavioral studies. However, only recently technologies for the targeted and tissue specific modification of rat genes - a prerequisite for a detailed study of the 5-HT system - have been successfully developed. Here, we describe a rat transgenic system for inducible gene manipulations in 5-HT neurons. We generated a Cre driver line consisting of a tamoxifen-inducible CreERT2 recombinase under the control of mouse Tph2 regulatory sequences. Tissue-specific serotonergic Cre recombinase expression was detected in four transgenic TPH2-CreERT2 rat founder lines. For functional analysis of Cre-mediated recombination, we used a rat Cre reporter line (CAG-loxP.EGFP), in which EGFP is expressed after Cre-mediated removal of a loxP-flanked lacZ STOP cassette. We show an in-depth characterisation of this rat Cre reporter line and demonstrate its applicability for monitoring Cre-mediated recombination in all major neuronal subpopulations of the rat brain. Upon tamoxifen induction, double transgenic TPH2-CreERT2/CAG-loxP.EGFP rats show selective and efficient EGFP expression in 5-HT neurons. Without tamoxifen administration, EGFP is only expressed in few 5-HT neurons which confirms minimal background recombination. This 5-HT neuron specific CreERT2 line allows Cre-mediated, inducible gene deletion or gene overexpression in transgenic rats which provides new opportunities to decipher the complex functions of the mammalian serotonergic system

CHOP Mediates Endoplasmic Reticulum Stress-Induced Apoptosis in Gimap5-Deficient T Cells

Gimap5 (GTPase of the immunity-associated protein 5) has been linked to the regulation of T cell survival, and polymorphisms in the human GIMAP5 gene associate with autoimmune disorders. The BioBreeding diabetes-prone (BBDP) rat has a mutation in the Gimap5 gene that leads to spontaneous apoptosis of peripheral T cells by an unknown mechanism. Because Gimap5 localizes to the endoplasmic reticulum (ER), we hypothesized that absence of functional Gimap5 protein initiates T cell death through disruptions in ER homeostasis. We observed increases in ER stress-associated chaperones in T cells but not thymocytes or B cells from Gimap5−/− BBDP rats. We then discovered that ER stress-induced apoptotic signaling through C/EBP-homologous protein (CHOP) occurs in Gimap5−/− T cells. Knockdown of CHOP by siRNA protected Gimap5−/− T cells from ER stress-induced apoptosis, thereby identifying a role for this cellular pathway in the T cell lymphopenia of the BBDP rat. These findings indicate a direct relationship between Gimap5 and the maintenance of ER homeostasis in the survival of T cells

Histone Modifications in Mouse Pronuclei and Consequences for Embryo Development

International audienceEpigenetic marks, such as DNA methylation and posttranslational modifications of core histones, are the key regulators of gene expression. In the mouse, many of these marks are erased during gamete formation and must be introduced de novo after fertilization. Some of them appear synchronously, but the others are deposited asynchronously and/or remain differently distributed on maternal and paternal chromatin. Although the mechanisms regulating these processes are not entirely understandable, it is commonly accepted that epigenetic reprogramming occurring during the first cell cycle of a mouse embryo is crucial for its further development. This chapter focuses on selected epigenetic modifications, such as DNA methylation, the introduction of histone variants, histones acetylation, phosphorylation, and methylation. Properly depositing these marks on maternal and paternal chromatin is crucial for normal embryonic development. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG