Transmission of temporally correlated spike trains through synapses with short-term depression

Short-term synaptic depression, caused by depletion of releasable neurotransmitter, modulates the strength of neuronal connections in a history-dependent manner. Quantifying the statistics of synaptic transmission requires stochastic models that link probabilistic neurotransmitter release with presynaptic spike-train statistics. Common approaches are to model the presynaptic spike train as either regular or a memory-less Poisson process: few analytical results are available that describe depressing synapses when the afferent spike train has more complex, temporally correlated statistics such as bursts. Here we present a series of analytical results—from vesicle release-site occupancy statistics, via neurotransmitter release, to the post-synaptic voltage mean and variance—for depressing synapses driven by correlated presynaptic spike trains. The class of presynaptic drive considered is that fully characterised by the inter-spike-interval distribution and encompasses a broad range of models used for neuronal circuit and network analyses, such as integrate-and-fire models with a complete post-spike reset and receiving sufficiently short-time correlated drive. We further demonstrate that the derived post-synaptic voltage mean and variance allow for a simple and accurate approximation of the firing rate of the post-synaptic neuron, using the exponential integrate-and-fire model as an example. These results extend the level of biological detail included in models of synaptic transmission and will allow for the incorporation of more complex and physiologically relevant firing patterns into future studies of neuronal networks

Bayesian Inference of Synaptic Quantal Parameters from Correlated Vesicle Release

Synaptic transmission is both history-dependent and stochastic, resulting in varying responses to presentations of the same presynaptic stimulus. This complicates attempts to infer synaptic parameters and has led to the proposal of a number of different strategies for their quantification. Recently Bayesian approaches have been applied to make more efficient use of the data collected in paired intracellular recordings. Methods have been developed that either provide a complete model of the distribution of amplitudes for isolated responses or approximate the amplitude distributions of a train of post-synaptic potentials, with correct short-term synaptic dynamics but neglecting correlations. In both cases the methods provided significantly improved inference of model parameters as compared to existing mean-variance fitting approaches. However, for synapses with high release probability, low vesicle number or relatively low restock rate and for data in which only one or few repeats of the same pattern are available, correlations between serial events can allow for the extraction of significantly more information from experiment: a more complete Bayesian approach would take this into account also. This has not been possible previously because of the technical difficulty in calculating the likelihood of amplitudes seen in correlated post-synaptic potential trains; however, recent theoretical advances have now rendered the likelihood calculation tractable for a broad class of synaptic dynamics models. Here we present a compact mathematical form for the likelihood in terms of a matrix product and demonstrate how marginals of the posterior provide information on covariance of parameter distributions. The associated computer code for Bayesian parameter inference for a variety of models of synaptic dynamics is provided in the supplementary material allowing for quantal and dynamical parameters to be readily inferred from experimental data sets

Learning spatio-temporal patterns with Neural Cellular Automata

Neural Cellular Automata (NCA) are a powerful combination of machine learning and mechanistic modelling. We train NCA to learn complex dynamics from time series of images and PDE trajectories. Our method is designed to identify underlying local rules that govern large scale dynamic emergent behaviours. Previous work on NCA focuses on learning rules that give stationary emergent structures. We extend NCA to capture both transient and stable structures within the same system, as well as learning rules that capture the dynamics of Turing pattern formation in nonlinear Partial Differential Equations (PDEs). We demonstrate that NCA can generalise very well beyond their PDE training data, we show how to constrain NCA to respect given symmetries, and we explore the effects of associated hyperparameters on model performance and stability. Being able to learn arbitrary dynamics gives NCA great potential as a data driven modelling framework, especially for modelling biological pattern formation.Comment: For videos referenced in appendix, see: https://github.com/AlexDR1998/NCA/tree/main/Video

Characterization of an electron conduit between bacteria and the extracellular environment

A number of species of Gram-negative bacteria can use insoluble minerals of Fe(III) and Mn(IV) as extracellular respiratory electron acceptors. In some species of Shewanella, deca-heme electron transfer proteins lie at the extracellular face of the outer membrane (OM), where they can interact with insoluble substrates. To reduce extracellular substrates, these redox proteins must be charged by the inner membrane/periplasmic electron transfer system. Here, we present a spectro-potentiometric characterization of a trans-OM icosa-heme complex, MtrCAB, and demonstrate its capacity to move electrons across a lipid bilayer after incorporation into proteoliposomes. We also show that a stable MtrAB subcomplex can assemble in the absence of MtrC; an MtrBC subcomplex is not assembled in the absence of MtrA; and MtrA is only associated to the membrane in cells when MtrB is present. We propose a model for the modular organization of the MtrCAB complex in which MtrC is an extracellular element that mediates electron transfer to extracellular substrates and MtrB is a trans-OM spanning ß-barrel protein that serves as a sheath, within which MtrA and MtrC exchange electrons. We have identified the MtrAB module in a range of bacterial phyla, suggesting that it is widely used in electron exchange with the extracellular environment

Omega-3 DHA and Sleep in UK Children: Results From the DOLAB Study

Results from the DHA-Oxford-Learning-and-Behaviour study (DOLAB) on the benefits of DHA supplementation for childrens' sleep. See also the article: Fatty acids and sleep in UK children: subjective and pilot objective sleep results from the DOLAB study – a randomized controlled trial. (http://onlinelibrary.wiley.com/enhanced/doi/10.1111/jsr.12135/

Blood Omega-3 Concentrations are Associated With Reading, Working Memory and Behaviour in Healthy Children Aged 7-9 Years

Epidemiological results from the DHA-Oxford-Learning-and-Behaviour study (DOLAB). Presented at the International Society for the Study of Fatty Acids and Lipids (ISSFAL) conference 2012 in Vancouver

4,5,6,7-Tetra­bromo-1,1,3-trimethyl-3-(2,3,4,5-tetra­bromo­phen­yl)indane

The title compound (OctaInd), C18H12Br8, is a commercial brominated flame retardant (BFR). In the mol­ecule, the five-membered ring has a slight envelope conformation, with a deviation of 0.317 (9) Å for the flap C atom from four essentially planar C atoms. The dihedral angle between the two benzene rings is 74.00 (16) Å

Correction to: Improved X-ray baggage screening sensitivity with 'targetless' search training.

Funder: Defence and Security Accelerator; doi: http://dx.doi.org/10.13039/100012339Abstract: When searching for a known target, mental representations of target features, or templates, guide attention towards matching objects and facilitate recognition. When only distractor features are known, distractor templates allow irrelevant objects to be recognised and attention to be shifted away. This is particularly true in X-ray baggage search, a challenging real-world visual search task with implications for public safety, where targets may be unknown, difficult to predict and concealed by an adversary, but distractors are typically benign and easier to identify. In the present study, we draw on basic principles of distractor suppression and rejection to investigate a counterintuitive ‘targetless’ approach to training baggage search. In a simulated X-ray baggage search task, we observed significant benefits to target detection sensitivity (d′) for targetless relative to target-based training, but no effects of performance-contingent rewards or the inclusion of superordinate semantic categories during training. The benefits of targetless search training were most apparent for stimuli involving less spatial overlap (occlusion), which likely represents the difficulty and greater individual variation involved in searching more visually complex images. Together, these results demonstrate the effectiveness of a counterintuitive targetless approach to training target detection in X-ray baggage search, based on basic principles of distractor suppression and rejection, with potential for use as a real-world training tool

Constraints on the perturbed mutual motion in Didymos due to impact-induced deformation of its primary after the DART impact

Binary near-Earth asteroid (65803) Didymos is the target of the proposed NASA Double Asteroid Redirection Test (DART), part of the Asteroid Impact & Deflection Assessment (AIDA) mission concept. In this mission, the DART spacecraft is planned to impact the secondary body of Didymos, perturbing mutual dynamics of the system. The primary body is currently rotating at a spin period close to the spin barrier of asteroids, and materials ejected from the secondary due to the DART impact are likely to reach the primary. These conditions may cause the primary to reshape, due to landslides, or internal deformation, changing the permanent gravity field. Here, we propose that if shape deformation of the primary occurs, the mutual orbit of the system would be perturbed due to a change in the gravity field. We use a numerical simulation technique based on the full two-body problem to investigate the shape effect on the mutual dynamics in Didymos after the DART impact. The results show that under constant volume, shape deformation induces strong perturbation in the mutual motion. We find that the deformation process always causes the orbital period of the system to become shorter. If surface layers with a thickness greater than ~0.4 m on the poles of the primary move down to the equatorial region due to the DART impact, a change in the orbital period of the system and in the spin period of the primary will be detected by ground-based measurement.Comment: 8 pages, 7 figures, 2 tables, accepted for publication in MNRA

Using Eye Movements to Understand how Security Screeners Search for Threats in X-Ray Baggage.

There has been an increasing drive to understand failures in searches for weapons and explosives in X-ray baggage screening. Tracking eye movements during the search has produced new insights into the guidance of attention during the search, and the identification of targets once they are fixated. Here, we review the eye-movement literature that has emerged on this front over the last fifteen years, including a discussion of the problems that real-world searchers face when trying to detect targets that could do serious harm to people and infrastructure