Stochastic hybrid model of spontaneous dendritic NMDA spikes

Following recent advances in imaging techniques and methods of dendritic stimulation, active voltage spikes have been observed in thin dendritic branches of excitatory pyramidal neurons, where the majority of synapses occur. The generation of these dendritic spikes involves both Na+ ion channels and M-methyl-D-aspartate receptor (NMDAR) channels. During strong stimulation of a thin dendrite, the resulting high levels of glutamate, the main excitatory neurotransmitter in the central nervous system and an NMDA agonist, modify the current-voltage (I–V) characteristics of an NMDAR so that it behaves like a voltage-gated Na+ channel. Hence, the NMDARs can fire a regenerative dendritic spike, just as Na+ channels support the initiation of an action potential following membrane depolarization. However, the duration of the dendritic spike is of the order 100 ms rather than 1 ms, since it involves slow unbinding of glutamate from NMDARs rather than activation of hyperpolarizing K+ channels. It has been suggested that dendritic NMDA spikes may play an important role in dendritic computations and provide a cellular substrate for short-term memory. In this paper, we consider a stochastic, conductance-based model of dendritic NMDA spikes, in which the noise originates from the stochastic opening and closing of a finite number of Na+ and NMDA receptor ion channels. The resulting model takes the form of a stochastic hybrid system, in which membrane voltage evolves according to a piecewise deterministic dynamics that is coupled to a jump Markov process describing the opening and closing of the ion channels. We formulate the noise-induced initiation and termination of a dendritic spike in terms of a first-passage time problem, under the assumption that glutamate unbinding is negligible, which we then solve using a combination of WKB methods and singular perturbation theory. Using a stochastic phase-plane analysis we then extend our analysis to take proper account of the combined effects of glutamate unbinding and noise on the termination of a spike

Directed intermittent search for a hidden target on a dendritic tree

Motivated by experimental observations of active (motor-driven) intracellular transport in neuronal dendrites, we analyze a stochastic model of directed intermittent search on a tree network. A particle injected from the cell body or soma into the primary branch of the dendritic tree randomly switches between a stationary search phase and a mobile nonsearch phase that is biased in the forward direction. A (synaptic) target is presented somewhere within the tree, which the particle can locate if it is within a certain range and in the searching phase. We approximate the moment generating function using Green’s function methods. The moment generating function is then used to compute the hitting probability and conditional mean first passage time to the target. We show that in contrast to a previously explored finite interval case, there is a range of parameters for which a bidirectional search strategy is more efficient than a unidirectional one in finding the target

Path integrals and large deviations in stochastic hybrid systems

We construct a path-integral representation of solutions to a stochastic hybrid system, consisting of one or more continuous variables evolving according to a piecewise-deterministic dynamics. The differential equations for the continuous variables are coupled to a set of discrete variables that satisfy a continuous-time Markov process, which means that the differential equations are only valid between jumps in the discrete variables. Examples of stochastic hybrid systems arise in biophysical models of stochastic ion channels, motor-driven intracellular transport, gene networks, and stochastic neural networks. We use the path-integral representation to derive a large deviation action principle for a stochastic hybrid system. Minimizing the associated action functional with respect to the set of all trajectories emanating from a metastable state (assuming that such a minimization scheme exists) then determines the most probable paths of escape. Moreover, evaluating the action functional along a most probable path generates the so-called quasipotential used in the calculation of mean first passage times. We illustrate the theory by considering the optimal paths of escape from a metastable state in a bistable neural network

Quasi-steady state reduction of molecular motor-based models of directed intermittent search

We present a quasi-steady state reduction of a linear reaction-hyperbolic master equation describing the directed intermittent search for a hidden target by a motor-driven particle moving on a one-dimensional filament track. The particle is injected at one end of the track and randomly switches between stationary search phases and mobile nonsearch phases that are biased in the anterograde direction. There is a finite possibility that the particle fails to find the target due to an absorbing boundary at the other end of the track. Such a scenario is exemplified by the motor-driven transport of vesicular cargo to synaptic targets located on the axon or dendrites of a neuron. The reduced model is described by a scalar Fokker–Planck (FP) equation, which has an additional inhomogeneous decay term that takes into account absorption by the target. The FP equation is used to compute the probability of finding the hidden target (hitting probability) and the corresponding conditional mean first passage time (MFPT) in terms of the effective drift velocity V, diffusivity D, and target absorption rate λ of the random search. The quasi-steady state reduction determines V, D, and λ in terms of the various biophysical parameters of the underlying motor transport model. We first apply our analysis to a simple 3-state model and show that our quasi-steady state reduction yields results that are in excellent agreement with Monte Carlo simulations of the full system under physiologically reasonable conditions. We then consider a more complex multiple motor model of bidirectional transport, in which opposing motors compete in a “tug-of-war”, and use this to explore how ATP concentration might regulate the delivery of cargo to synaptic targets

Filling of a Poisson trap by a population of random intermittent searchers

We extend the continuum theory of random intermittent search processes to the case of N independent searchers looking to deliver cargo to a single hidden target located somewhere on a semi-infinite track. Each searcher randomly switches between a stationary state and either a leftward or rightward constant velocity state. We assume that all of the particles start at one end of the track and realize sample trajectories independently generated from the same underlying stochastic process. The hidden target is treated as a partially absorbing trap in which a particle can only detect the target and deliver its cargo if it is stationary and within range of the target; the particle is removed from the system after delivering its cargo. As a further generalization of previous models, we assume that up to n successive particles can find the target and deliver its cargo. Assuming that the rate of target detection scales as 1 / N , we show that there exists a well-defined mean-field limit N → ∞ , in which the stochastic model reduces to a deterministic system of linear reaction-hyperbolic equations for the concentrations of particles in each of the internal states. These equations decouple from the stochastic process associated with filling the target with cargo. The latter can be modeled as a Poisson process in which the time-dependent rate of filling λ ( t ) depends on the concentration of stationary particles within the target domain. Hence, we refer to the target as a Poisson trap. We analyze the efficiency of filling the Poisson trap with n particles in terms of the waiting time density f n ( t ) . The latter is determined by the integrated Poisson rate μ ( t ) = ∫ t 0 λ ( s ) d s , which in turn depends on the solution to the reaction-hyperbolic equations. We obtain an approximate solution for the particle concentrations by reducing the system of reaction-hyperbolic equations to a scalar advection-diffusion equation using a quasisteady-state analysis. We compare our analytical results for the mean-field model with Monte Carlo simulations for finite N . We thus determine how the mean first passage time (MFPT) for filling the target depends on N and n

Anxiety Detection Leveraging Mobile Passive Sensing

Anxiety disorders are the most common class of psychiatric problems affecting both children and adults. However, tools to effectively monitor and manage anxiety are lacking, and comparatively limited research has been applied to addressing the unique challenges around anxiety. Leveraging passive and unobtrusive data collection from smartphones could be a viable alternative to classical methods, allowing for real-time mental health surveillance and disease management. This paper presents eWellness, an experimental mobile application designed to track a full-suite of sensor and user-log data off an individual's device in a continuous and passive manner. We report on an initial pilot study tracking ten people over the course of a month that showed a nearly 76% success rate at predicting daily anxiety and depression levels based solely on the passively monitored features

Increasing condom use in heterosexual men: development of a theory-based interactive digital intervention

Increasing condom use to prevent sexually transmitted infections is a key public health goal. Interventions are more likely to be effective if they are theory- and evidence-based. The Behaviour Change Wheel (BCW) provides a framework for intervention development. To provide an example of how the BCW was used to develop an intervention to increase condom use in heterosexual men (the MenSS website), the steps of the BCW intervention development process were followed, incorporating evidence from the research literature and views of experts and the target population. Capability (e.g. knowledge) and motivation (e.g. beliefs about pleasure) were identified as important targets of the intervention. We devised ways to address each intervention target, including selecting interactive features and behaviour change techniques. The BCW provides a useful framework for integrating sources of evidence to inform intervention content and deciding which influences on behaviour to target

The RAPID-CTCA trial (Rapid Assessment of Potential Ischaemic Heart Disease with CTCA) - a multicentre parallel-group randomised trial to compare early computerised tomography coronary angiography versus standard care in patients presenting with suspected or confirmed acute coronary syndrome: study protocol for a randomised controlled trial.

BACKGROUND: Emergency department attendances with chest pain requiring assessment for acute coronary syndrome (ACS) are a major global health issue. Standard assessment includes history, examination, electrocardiogram (ECG) and serial troponin testing. Computerised tomography coronary angiography (CTCA) enables additional anatomical assessment of patients for coronary artery disease (CAD) but has only been studied in very low-risk patients. This trial aims to investigate the effect of early CTCA upon interventions, event rates and health care costs in patients with suspected/confirmed ACS who are at intermediate risk. METHODS/DESIGN: Participants will be recruited in about 35 tertiary and district general hospitals in the UK. Patients ≥18 years old with symptoms with suspected/confirmed ACS with at least one of the following will be included: (1) ECG abnormalities, e.g. ST-segment depression >0.5 mm; (2) history of ischaemic heart disease; (3) troponin elevation above the 99(th) centile of the normal reference range or increase in high-sensitivity troponin meeting European Society of Cardiology criteria for 'rule-in' of myocardial infarction (MI). The early use of ≥64-slice CTCA as part of routine assessment will be compared to standard care. The primary endpoint will be 1-year all-cause death or recurrent type 1 or type 4b MI at 1 year, measured as the time to such event. A number of secondary clinical, process and safety endpoints will be collected and analysed. Cost effectiveness will be estimated in terms of the lifetime incremental cost per quality-adjusted life year gained. We plan to recruit 2424 (2500 with ~3% drop-out) evaluable patients (1212 per arm) to have 90% power to detect a 20% versus 15% difference in 1-year death or recurrent type 1 MI or type 4b MI, two-sided p < 0.05. Analysis will be on an intention-to-treat basis. The relationship between intervention and the primary outcome will be analysed using Cox proportional hazard regression adjusted for study site (used to stratify the randomisation), age, baseline Global Registry of Acute Coronary Events score, previous CAD and baseline troponin level. The results will be expressed as a hazard ratio with the corresponding 95% confidence intervals and p value. DISCUSSION: The Rapid Assessment of Potential Ischaemic Heart Disease with CTCA (RAPID-CTCA) trial will recruit 2500 participants across about 35 hospital sites. It will be the first study to investigate the role of CTCA in the early assessment of patients with suspected or confirmed ACS who are at intermediate risk and including patients who have raised troponin measurements during initial assessment. TRIAL REGISTRATION: ISRCTN19102565 . Registered on 3 October 2014. ClinicalTrials.gov: NCT02284191

Overweight and lifestyle behaviors of low socioeconomic elementary school children in Buenos Aires

<p>Abstract</p> <p>Background</p> <p>There is growing interest in understanding the role that lifestyle behaviors play in relation to children's weight status. The objective of the study was to determine the association between children s BMI and dietary practices and maternal BMI.</p> <p>Methods</p> <p>330 students (168M) aged 8.9 + 2 y from 4 suburban Buenos Aires elementary schools, and their mothers aged 36.2 + 7 y were examined between April and September 2007. Mothers were asked about their children s lifestyle. Data included parental education levels socioeconomic status, mothers and children s BMI, and Tanner stage.</p> <p>Results</p> <p>All families were in the low socio-economic class. 79% of parents had an elementary education or less. 61 (18.5%) of children were obese (OB) (BMI>95%ile per CDC norms), and 53 (16.1%) overweight (OW) (BMI>85<95%ile). 103 (31.2%) of mothers were OB (BMI>30 kg/m2), and102 (30.9%) OW (BMI>25<30). 63% the children were pre-pubertal. 40% had a TV set in their bedroom. 13% of the children skipped breakfast and only 38% watched TV ≤2 hours daily, as recommended. Multiple logistic regression analysis showed a positive association between children s OW/OB and drinking sweetened beverages (OR = 1.24; 95% CI, 1.02–1.52), TV viewing (OR = 1.30; 95% CI,1.05–1.62), and maternal BMI (OR: 1.07; 95% CI,1.02–1.12), and a negative association with eating breakfast (OR = 0.43; 95% CI, 0.19–0.97) adjusted for fruit and vegetables consumption, milk consumption, maternal educational level and socioeconomic class.</p> <p>Conclusion</p> <p>Our results suggest that TV viewing, drinking sweet beverages, skipping breakfast, and maternal BMI are important predictive variables for childhood OW/OB.</p