How sensorimotor interaction shapes and supports young children's gestural communication around science

Research has demonstrated that gesture produced during conversation can provide insights into scientific thinking and can aid scientific communication in adults and school-aged children. However, to date, there has been a limited exploration into the role of gesture in supporting young children’s science communication, and how this is underpinned and shaped by their sensorimotor experiences. This study examines, identifies and conceptualises ways in which children spontaneously used gesture during their interaction-orientated discourse and how this mapped to their action experiences at a water table. Findings show how gestural communication in children under 5 years of age can convey different levels of complexity related to science thinking

Computational modeling and analysis of hippocampal-prefrontal information coding during a spatial decision-making task

We introduce a computational model describing rat behavior and the interactions of neural populations processing spatial and mnemonic information during a maze-based, decision-making task. The model integrates sensory input and implements working memory to inform decisions at a choice point, reproducing rat behavioral data and predicting the occurrence of turn- and memory-dependent activity in neuronal networks subserving task performance. We tested these model predictions using a new software toolbox (Maze Query Language, MQL) to analyse activity of medial prefrontal cortical (mPFC) and dorsal hippocampal (dCA1) neurons recorded from six adult rats during task performance. The firing rates of dCA1 neurons discriminated context (i.e., the direction of the previous turn), whilst a subset of mPFC neurons was selective for current turn direction or context, with some conjunctively encoding both. mPFC turn-selective neurons displayed a ramping of activity on approach to the decision turn and turn-selectivity in mPFC was significantly reduced during error trials. These analyses complement data from neurophysiological recordings in non-human primates indicating that firing rates of cortical neurons correlate with integration of sensory evidence used to inform decision-making

Data-Driven Subgroups in Depression Derived from Directed Functional Connectivity Paths at Rest

Depressed patients show abnormalities in brain connectivity at rest, including hyperconnectivity within the default mode network (DMN). However, there is well-known heterogeneity in the clinical presentation of depression that is overlooked when averaging connectivity data. We used data-driven parsing of neural connectivity to reveal subgroups among 80 depressed patients completing resting state fMRI. Directed functional connectivity paths (eg, region A influences region B) within a depression-relevant network were characterized using Group Iterative Multiple Model Estimation, a method shown to accurately recover the direction and presence of connectivity paths in individual participants. Individuals were clustered using community detection on neural connectivity estimates. Subgroups were compared on network features and on clinical and biological/demographic characteristics that influence depression prognosis. Two subgroups emerged. Subgroup A, containing 71% of the patients, showed a typical pattern of connectivity across DMN nodes, as previously reported in depressed patients on average. Subgroup B exhibited an atypical connectivity profile lacking DMN connectivity, with increased dorsal anterior cingulate-driven connectivity paths. Subgroup B members had an over-representation of females (87% of Subgroup B vs 65% of Subgroup A; χ2=3.89, p=0.049), comorbid anxiety diagnoses (42.9% of Subgroup B vs 17.5% of Subgroup A; χ2=5.34, p=.02), and highly recurrent depression (63.2% of Subgroup B vs 31.8% of Subgroup A; χ2=5.38, p=.02). Neural connectivity-based categorization revealed an atypical pattern of connectivity in a depressed patient subset that would be overlooked in group comparisons of depressed and healthy participants, and tracks with clinically relevant phenotypes including anxious depression and episodic recurrence. Data-driven parsing suggests heterogeneous substrates of depression; ideally, future work building on these findings will inform personalized treatment

Approvimating Sums of Infinite Series

The Euler-Maclaurin summation formula is frequently used to efficiently estimate sums of infinite series of the form $\sum_{j=1}^{\infty}f(j)$. The purpose of this article is to describe a modification of this numerical technique designed to simplify and reduce the computational effort required to obtain an acceptable estimate of the sum. The modified formula is obtained by replacing $f\left( x\right)$ with an easily constructed polynomial like interpolating function $a\left( x\right)$ designed to simplify the calculation of the integral and derivatives associated with Euler-Maclaurin. This approach provides a more tractable algorithm which can be written as a matrix equation. Examples are provided to demonstrate that the accuracy of the new algorithm compares favorably with that of the traditional formula. The paper concludes with a brief discussion of a method for approximating the error incurred when replacing the exact value of the sum of the original series with the estimate

Genome-wide association study of receptive language ability of 12 year olds

Purpose: We have previously shown that individual differences in measures of receptive language ability at age 12 are highly heritable. The current study attempted to identify some of the genes responsible for the heritability of receptive language ability using a genome-wide association (GWA) approach. Method: We administered four internet-based measures of receptive language (vocabulary, semantics, syntax, and pragmatics) to a sample of 2329 12-year-olds for whom DNA and genome-wide genotyping were available. Nearly 700,000 single-nucleotide polymorphisms (SNPs) and one million imputed SNPs were included in a GWA analysis of receptive language composite scores. Results: No SNP associations met the demanding criterion of genome-wide significance that corrects for multiple testing across the genome (p < 5 ×10-8). The strongest SNP association did not replicate in an additional sample of 2639 12-year-olds. Conclusion: These results indicate that individual differences in receptive language ability in the general population do not reflect common genetic variants that account for >3% of the phenotypic variance. The search for genetic variants associated with language skill will require larger samples and additional methods to identify and functionally characterize the full spectrum of risk variants

Controlled Diffusion of Photoswitchable Receptors by Binding Anti-electrostatic Hydrogen-Bonded Phosphate Oligomers

Dihydrogen phosphate anions are found to spontaneously associate into anti-electrostatic oligomers via hydrogen bonding interactions at millimolar concentrations in DMSO. Diffusion NMR measurements supported formation of these oligomers, which can be bound by photoswitchable anion receptors to form large bridged assemblies of approximately three times the volume of the unbound receptor. Photoisomerization of the oligomer-bound receptor causes a decrease in diffusion coefficient of up to 16%, corresponding to a 70% increase in effective volume. This new approach to external control of diffusion opens prospects in controlling molecular transport using light

EvoL: The new Padova T-SPH parallel code for cosmological simulations - I. Basic code: gravity and hydrodynamics

We present EvoL, the new release of the Padova N-body code for cosmological simulations of galaxy formation and evolution. In this paper, the basic Tree + SPH code is presented and analysed, together with an overview on the software architectures. EvoL is a flexible parallel Fortran95 code, specifically designed for simulations of cosmological structure formation on cluster, galactic and sub-galactic scales. EvoL is a fully Lagrangian self-adaptive code, based on the classical Oct-tree and on the Smoothed Particle Hydrodynamics algorithm. It includes special features such as adaptive softening lengths with correcting extra-terms, and modern formulations of SPH and artificial viscosity. It is designed to be run in parallel on multiple CPUs to optimize the performance and save computational time. We describe the code in detail, and present the results of a number of standard hydrodynamical tests.Comment: 33 pages, 49 figures, accepted on A&

Parsing Heterogeneity in the Brain Connectivity of Depressed and Healthy Adults During Positive Mood

There is well-known heterogeneity in affective mechanisms in depression that may extend to positive affect. We used data-driven parsing of neural connectivity to reveal subgroups present across depressed and healthy individuals during positive processing, informing targets for mechanistic intervention

Spatial Effects and GWA Mapping of Root Colonization Assessed in the Interaction Between the Rice Diversity Panel 1 and an Arbuscular Mycorrhizal Fungus

The majority of the research reported here is an output of EU project “EURoot” (FP7-KBBE-2011-5 Grant Agreement No. 289300) project. RS’s contribution was funded by FACCE-JPI NET project “GreenRice” (Sustainable and environmental friendly rice cultivation systems in Europe) and was funded by the BBSRC award BB/M018415/1.Peer reviewedPublisher PD