Controlling the uncontrolled: Are there incidental experimenter effects on physiologic responding?

The degree to which experimenters shape participant behavior has long been of interest in experimental social science research. Here, we extend this question to the domain of peripheral psychophysiology, where experimenters often have direct, physical contact with participants, yet researchers do not consistently test for their influence. We describe analytic tools for examining experimenter effects in peripheral physiology. Using these tools, we investigate nine data sets totaling 1,341 participants and 160 experimenters across different roles (e.g., lead research assistants, evaluators, confederates) to demonstrate how researchers can test for experimenter effects in participant autonomic nervous system activity during baseline recordings and reactivity to study tasks. Our results showed (a) little to no significant variance in participants' physiological reactivity due to their experimenters, and (b) little to no evidence that three characteristics of experimenters that are well known to shape interpersonal interactions-status (using five studies with 682 total participants), gender (using two studies with 359 total participants), and race (in two studies with 554 total participants)-influenced participants' physiology. We highlight several reasons that experimenter effects in physiological data are still cause for concern, including the fact that experimenters in these studies were already restricted on a number of characteristics (e.g., age, education). We present recommendations for examining and reducing experimenter effects in physiological data and discuss implications for replication

Stochastic Blockmodeling for the Analysis of Big Data

The aim of this paper is to consider the stochastic blockmodel to obtain clusters of units as regards patterns of similar relations; moreover we want to analyze the relations between clusters. Blockmodeling is a technique usually applied in social network analysis focusing on the relations between \u201cactors\u201d i.e. units. In our time people and devices constantly generate data. The network is generating location and other data that keeps services running and ready to use in every moment. This rapid development in the availability and access to data has induced the need for better analysis techniques to understand the various phenomena. Blockmodeling techniques and Clustering algorithms, can be used for this aim. In this paper application regards the Web

Chemical genetic identification of CDKL5 substrates reveals its role in neuronal microtubule dynamics.

Loss-of-function mutations in CDKL5 kinase cause severe neurodevelopmental delay and early-onset seizures. Identification of CDKL5 substrates is key to understanding its function. Using chemical genetics, we found that CDKL5 phosphorylates three microtubule-associated proteins: MAP1S, EB2 and ARHGEF2, and determined the phosphorylation sites. Substrate phosphorylations are greatly reduced in CDKL5 knockout mice, verifying these as physiological substrates. In CDKL5 knockout mouse neurons, dendritic microtubules have longer EB3-labelled plus-end growth duration and these altered dynamics are rescued by reduction of MAP1S levels through shRNA expression, indicating that CDKL5 regulates microtubule dynamics via phosphorylation of MAP1S. We show that phosphorylation by CDKL5 is required for MAP1S dissociation from microtubules. Additionally, anterograde cargo trafficking is compromised in CDKL5 knockout mouse dendrites. Finally, EB2 phosphorylation is reduced in patient-derived human neurons. Our results reveal a novel activity-dependent molecular pathway in dendritic microtubule regulation and suggest a pathological mechanism which may contribute to CDKL5 deficiency disorder

Collison effects in the nonlinear Raman response of liquid carbon disulfide

The contributions of induced-multipole and electron overlap effects to the third-order Raman response were studied. A model was constructed on the polarizability of carbon disulfide dimers using polarizabilities from accurate time-dependent density functional theory calculations. The model was used to calculate the third-order time-domain Raman response of liquid carbon disulfide

The population and reproductive biology of Pseudochromis Queenslandica at One Tree Island, Great Barrier Reef

The human brain has the extraordinary capability to transform cluttered sensory input into distinct object representations. For example, it is able to rapidly and seemingly without effort detect object categories in complex natural scenes. Surprisingly, category tuning is not sufficient to achieve conscious recognition of objects. What neural process beyond category extraction might elevate neural representations to the level where objects are consciously perceived? Here we show that visible and invisible faces produce similar category-selective responses in the ventral visual cortex. The pattern of neural activity evoked by visible faces could be used to decode the presence of invisible faces and vice versa. However, only visible faces caused extensive response enhancements and changes in neural oscillatory synchronization, as well as increased functional connectivity between higher and lower visual areas. We conclude that conscious face perception is more tightly linked to neural processes of sustained information integration and binding than to processes accommodating face category tuning

Many-body effects in the stimulated Raman response of binary mixtures:A comparison between theory and experiment

The subpicosecond dynamics of binary mixtures of carbon disulfide and alkane have been studied using third-order time-resolved Raman techniques. Both the anisotropic and the isotropic responses were investigated. These depend differently on many-body contributions to the first-order susceptibility and probe different modes in the liquid. The anisotropic response is dominated by single molecule effects, whereas the isotropic response is completely determined by many-body contributions since the single molecule response vanishes. To interpret the experimental results, molecular dynamics simulations were performed on model mixtures. The effect of dilution on the subpicosecond response cannot be explained by many-body effects in the first-order susceptibility alone. Aggregation due to permanent quadrupole moments on the carbon disulfide molecules and density changes upon dilution are also inadequate explanations for the observed effect. Apparently the character of the many-body dynamics itself is modified by the change of the molecular force fields, when carbon disulfide molecules are replaced by alkanes.<br/

Topological network alignment uncovers biological function and phylogeny

Sequence comparison and alignment has had an enormous impact on our understanding of evolution, biology, and disease. Comparison and alignment of biological networks will likely have a similar impact. Existing network alignments use information external to the networks, such as sequence, because no good algorithm for purely topological alignment has yet been devised. In this paper, we present a novel algorithm based solely on network topology, that can be used to align any two networks. We apply it to biological networks to produce by far the most complete topological alignments of biological networks to date. We demonstrate that both species phylogeny and detailed biological function of individual proteins can be extracted from our alignments. Topology-based alignments have the potential to provide a completely new, independent source of phylogenetic information. Our alignment of the protein-protein interaction networks of two very different species--yeast and human--indicate that even distant species share a surprising amount of network topology with each other, suggesting broad similarities in internal cellular wiring across all life on Earth.Comment: Algorithm explained in more details. Additional analysis adde

A Relational Event Approach to Modeling Behavioral Dynamics

This chapter provides an introduction to the analysis of relational event data (i.e., actions, interactions, or other events involving multiple actors that occur over time) within the R/statnet platform. We begin by reviewing the basics of relational event modeling, with an emphasis on models with piecewise constant hazards. We then discuss estimation for dyadic and more general relational event models using the relevent package, with an emphasis on hands-on applications of the methods and interpretation of results. Statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling, simulation, and analysis of relational data. Statnet packages are contributed by a team of volunteer developers, and are made freely available under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing platform that supports R (including Windows, Linux, and Mac).