Gradient estimation in dendritic reinforcement learning

We study synaptic plasticity in a complex neuronal cell model where NMDA-spikes can arise in certain dendritic zones. In the context of reinforcement learning, two kinds of plasticity rules are derived, zone reinforcement (ZR) and cell reinforcement (CR), which both optimize the expected reward by stochastic gradient ascent. For ZR, the synaptic plasticity response to the external reward signal is modulated exclusively by quantities which are local to the NMDA-spike initiation zone in which the synapse is situated. CR, in addition, uses nonlocal feedback from the soma of the cell, provided by mechanisms such as the backpropagating action potential. Simulation results show that, compared to ZR, the use of nonlocal feedback in CR can drastically enhance learning performance. We suggest that the availability of nonlocal feedback for learning is a key advantage of complex neurons over networks of simple point neurons, which have previously been found to be largely equivalent with regard to computational capability.

Deadspace estimation from CO2 versus molar mass measurements in infants

BACKGROUND: Estimation of respiratory deadspace is often based on the CO2 expirogram, however presence of the CO2 sensor increases equipment deadspace, which in turn influences breathing pattern and calculation of lung volume. In addition, it is necessary to correct for the delay between the sensor and flow signals. We propose a new method for estimation of effective deadspace using the molar mass (MM) signal from an ultrasonic flowmeter device, which does not require delay correction. We hypothesize that this estimation is correlated with that calculated from the CO2 signal using the Fowler method. METHODS: Breath-by-breath CO2, MM and flow measurements were made in a group of 77 term-born healthy infants. Fowler deadspace (Vd,Fowler) was calculated after correcting for the flow-dependent delay in the CO2 signal. Deadspace estimated from the MM signal (Vd,MM) was defined as the volume passing through the flowhead between start of expiration and the 10% rise point in MM. RESULTS: Correlation (r = 0.456, P < 0.0001) was found between Vd,MM and Vd,Fowler averaged over all measurements, with a mean difference of -1.4% (95% CI -4.1 to 1.3%). Vd,MM ranged from 6.6 to 11.4 ml between subjects, while Vd,Fowler ranged from 5.9 to 12.0 ml. Mean intra-measurement CV over 5-10 breaths was 7.8 +/- 5.6% for Vd,MM and 7.8 +/- 3.7% for Vd,Fowler. Mean intra-subject CV was 6.0 +/- 4.5% for Vd,MM and 8.3 +/- 5.9% for Vd,Fowler. Correcting for the CO2 signal delay resulted in a 12% difference (P = 0.022) in Vd,Fowler. Vd,MM could be obtained more frequently than Vd,Fowler in infants with CLD, with a high variability. CONCLUSIONS: Use of the MM signal provides a feasible estimate of Fowler deadspace without introducing additional equipment deadspace. The simple calculation without need for delay correction makes individual adjustment for deadspace in FRC measurements possible. This is especially important given the relative large range of deadspace seen in this homogeneous group of infants.

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

Parametric estimation of pulse arrival time: a robust approach to pulse wave velocity

Pulse wave velocity (PWV) is a surrogate of arterial stiffness and represents a non-invasive marker of cardiovascular risk. The non-invasive measurement of PWV requires tracking the arrival time of pressure pulses recorded in vivo, commonly referred to as pulse arrival time (PAT). In the state of the art, PAT is estimated by identifying a characteristic point of the pressure pulse waveform. This paper demonstrates that for ambulatory scenarios, where signal-to-noise ratios are below 10 dB, the performance in terms of repeatability of PAT measurements through characteristic points identification degrades drastically. Hence, we introduce a novel family of PAT estimators based on the parametric modeling of the anacrotic phase of a pressure pulse. In particular, we propose a parametric PAT estimator (TANH) that depicts high correlation with the Complior(R) characteristic point D1 (CC = 0.99), increases noise robustness and reduces by a five-fold factor the number of heartbeats required to obtain reliable PAT measurements.

Evidence based check-up: the general medical point of view

Check-up is a frequent motivation for patients to see their general practitioner. The challenge lies in the choice of screening tools to accomplish an efficient, individual and age-adapted approach. In this article we review evidence-based screening methods, whose efficacy has been demonstrated by randomized clinical trials, as well as their application in clinical practice. While cardiovascular check-up has a high grade of evidence for nearly all patients, counselling to lifestyle change except for smoking cessation has been proved with lower evidence. In contrast, relatively new is the fact that ultrasound to screen for an abdominal aortic aneurysm is useful among men smokers or past smokers between 65 and 75 years old.

Non-invasive and non-occlusive blood pressure estimation via a chest sensor

The clinical demand for a device to monitor Blood Pressure (BP) in ambulatory scenarios with minimal use of inflation cuffs is increasing. Based on the so-called Pulse Wave Velocity (PWV) principle, this paper introduces and evaluates a novel concept of BP monitor that can be fully integrated within a chest sensor. After a preliminary calibration, the sensor provides non-occlusive beat-by-beat estimations of Mean Arterial Pressure (MAP) by measuring the Pulse Transit Time (PTT) of arterial pressure pulses travelling from the ascending aorta towards the subcutaneous vasculature of the chest. In a cohort of 15 healthy male subjects, a total of 462 simultaneous readings consisting of reference MAP and chest PTT were acquired. Each subject was recorded at three different days: D, D+3 and D+14. Overall, the implemented protocol induced MAP values to range from 80 ± 6 mmHg in baseline, to 107 ± 9 mmHg during isometric handgrip maneuvers. Agreement between reference and chest-sensor MAP values was tested by using intraclass correlation coefficient (ICC = 0.78) and Bland-Altman analysis (mean error = 0.7 mmHg, standard deviation = 5.1 mmHg). The cumulative percentage of MAP values provided by the chest sensor falling within a range of ±5 mmHg compared to reference MAP readings was of 70%, within ±10 mmHg was of 91%, and within ±15mmHg was of 98%. These results point at the fact that the chest sensor complies with the British Hypertension Society (BHS) requirements of Grade A BP monitors, when applied to MAP readings. Grade A performance was maintained even two weeks after having performed the initial subject-dependent calibration. In conclusion, this paper introduces a sensor and a calibration strategy to perform MAP measurements at the chest. The encouraging performance of the presented technique paves the way towards an ambulatory-compliant, continuous and non-occlusive BP monitoring system.

Efficient estimation of the total number of acini in adult rat lung

Pulmonary airways are subdivided into conducting and gas-exchanging airways. An acinus is defined as the small tree of gas-exchanging airways, which is fed by the most distal purely conducting airway. Until now a dissector of five consecutive sections or airway casts were used to count acini. We developed a faster method to estimate the number of acini in young adult rats. Right middle lung lobes were critical point dried or paraffin embedded after heavy metal staining and imaged by X-ray micro-CT or synchrotron radiation-based X-rays tomographic microscopy. The entrances of the acini were counted in three-dimensional (3D) stacks of images by scrolling through them and using morphological criteria (airway wall thickness and appearance of alveoli). Segmentation stopper were placed at the acinar entrances for 3D visualizations of the conducting airways. We observed that acinar airways start at various generations and that one transitional bronchiole may serve more than one acinus. A mean of 5612 (±547) acini per lung and a mean airspace volume of 0.907 (±0.108) μL per acinus were estimated. In 60-day-old rats neither the number of acini nor the mean acinar volume did correlate with the body weight or the lung volume.

New Algorithms for M-Estimation of Multivariate Scatter and Location

We present new algorithms for M-estimators of multivariate scatter and location and for symmetrized M-estimators of multivariate scatter. The new algorithms are considerably faster than currently used fixed-point and related algorithms. The main idea is to utilize a second order Taylor expansion of the target functional and to devise a partial Newton-Raphson procedure. In connection with symmetrized M-estimators we work with incomplete U-statistics to accelerate our procedures initially.