NONLINEAR INTERDEPENDENCE IN NEURAL SYSTEMS: MOTIVATION,THEORY, AND RELEVANCE

In this article, we motivate models of medium to large-scale neural activity that place an emphasis on the modular nature of neocortical organization and discuss the occurrence of nonlinear interdependence in such models. On the basis of their functional, anatomical, and physiological properties, it is argued that cortical columns may be treated as the basic dynamical modules of cortical systems. Coupling between these columns is introduced to represent sparse long-range cortical connectivity. Thus, neocortical activity can be modeled as an array of weakly coupled dynamical subsystems. The behavior of such systems is represented by dynamical attractors, which may be fixed point, limit cycle, or chaotic in nature. If all the subsystems are perfectly identical, then the state of identical chaotic synchronization is a possible attractor for the array. Following the introduction of parameter variation across the array, such a state is not possible, although two other important nonlinear interdependences--generalized and phase synchronized--are possible. We suggest that an understanding of nonlinear interdependence may assist advances in models of neural activity and neuroscience time series analysis.     

Finite element contact analysis as a critical technique in dental biomechanics: A review

PurposeNonlinear finite element contact analysis is used to mathematically estimate stress and strain in a time- and status-dependent mechanical model. However, the benefits and limitations of this method have not been thoroughly examined.Study selectionThe current review summarizes the utility of contact analysis in characterizing individual stressors: (1) tooth-to-tooth contact, (2) restorative interface, and (3) bone–implant integration.ResultsOpposing tooth contact, friction, and sliding phenomena were simulated to estimate stress distribution and assess the failure risk for tooth enamel, composite, and ceramic restorations. Mechanical tests such as the flexural tests were simulated with the contact analysis to determine the rationale underlying experimental findings. The tooth–restoration complex was modeled with interface contact elements that simulate imperfect bonding, and the normal and tangential stresses were calculated to predict failure progression. Previous studies have used a friction coefficient to represent osseointegration adjacent to dental implants, but the relationship between interface friction and the bone quality is unknown. An understanding of the local stress and strain may better predict loss of osseointegration, however, the effective stress as a critical contributor to bone degradation and formation has not been established.ConclusionsContact analysis provides numerous benefits for dental and oral health sciences, however, a fundamental understanding and improved methodology are necessary.     

A note on hyper ellipse method for classifying biological and medical data

The classification of biological and medical datasets is essential to humanity. This study proposes a hyper ellipse method based on mixed integer nonlinear program for classifying datasets. A linearization technique with a number of piecewise line segments is used to treat nonlinear constraints, which aims to obtain an approximate optimal solution. Numerical examples are presented to demonstrate the efficacy of the proposed method.     

丁酸氯维地平静脉注射乳剂在大鼠体内的药动学研究

目的研究两种丁酸氯维地平制剂在大鼠体内的药动学特点。方法将24只大鼠随机均分为4组,分别静脉滴注低、中、高剂量的丁酸氯维地平受试制剂及参比制剂,采用HPLC法测定全血中的丁酸氯维地平,计算药动学参数,评价其在大鼠体内的药动学特点。结果丁酸氯维地平低、中、高剂量受试制剂和参比制剂在大鼠血浆中的主要药动学参数为:Cmax分别为46.16±10.65、82.99±9.34、177.80±38.32、80.31±3.04 ng·m L-1;AUC0-t分别为2.309±0.628、4.221±0.988、9.339±1.759、3.968±0.411 min·μg·m L-1;t1/2分别为12.20±4.65、16.74±6.93、15.13±4.81、18.34±4.43 min。结论丁酸氯维地平受试制剂和参比制剂在大鼠体内药动学参数差异无统计学意义,受试制剂在0.36~3.24 mg·kg-1剂量范围内呈非线性动力学特征。     

One- and Two-Stage Arrhenius Models for Pharmaceutical Shelf Life Prediction

One of the most challenging aspects of the pharmaceutical development is the demonstration and estimation of chemical stability. It is imperative that pharmaceutical products be stable for two or more years. Long-term stability studies are required to support such shelf life claim at registration. However, during drug development to facilitate formulation and dosage form selection, an accelerated stability study with stressed storage condition is preferred to quickly obtain a good prediction of shelf life under ambient storage conditions. Such a prediction typically uses Arrhenius equation that describes relationship between degradation rate and temperature (and humidity). Existing methods usually rely on the assumption of normality of the errors. In addition, shelf life projection is usually based on confidence band of a regression line. However, the coverage probability of a method is often overlooked or under-reported. In this paper, we introduce two nonparametric bootstrap procedures for shelf life estimation based on accelerated stability testing, and compare them with a one-stage nonlinear Arrhenius prediction model. Our simulation results demonstrate that one-stage nonlinear Arrhenius method has significant lower coverage than nominal levels. Our bootstrap method gave better coverage and led to a shelf life prediction closer to that based on long-term stability data.     

Automatic Computation of Left Ventricular Volume Changes Over a Cardiac Cycle from Echocardiography Images by Nonlinear Dimensionality Reduction

Curve of left ventricular (LV) volume changes throughout the cardiac cycle is a fundamental parameter for clinical evaluation of various cardiovascular diseases. Currently, this evaluation is often performed manually which is tedious and time consuming and suffers from significant interobserver and intraobserver variability. This paper introduces a new automatic method, based on nonlinear dimensionality reduction (NLDR) for extracting the curve of the LV volume changes over a cardiac cycle from two-dimensional (2-D) echocardiography images. Isometric feature mapping (Isomap) is one of the most popular NLDR algorithms. In this study, a modified version of Isomap algorithm, where image to image distance metric is computed using nonrigid registration, is applied on 2-D echocardiography images of one cycle of heart. Using this approach, the nonlinear information of these images is embedded in a 2-D manifold and each image is characterized by a symbol on the constructed manifold. This new representation visualizes the relationship between these images based on LV volume changes and allows extracting the curve of the LV volume changes automatically. Our method in comparison to the traditional segmentation algorithms does not need any LV myocardial segmentation and tracking, particularly difficult in the echocardiography images. Moreover, a large data set under various diseases for training is not required. The results obtained by our method are quantitatively evaluated to those obtained manually by the highly experienced echocardiographer on ten healthy volunteers and six patients which depict the usefulness of the presented method.     

A new algorithm developed based on a mixture of spectral and nonlinear techniques for the analysis of heart rate variability

In this paper, an algorithm based on a joint use of spectral and nonlinear techniques for heart rate variability (HRV) analysis is proposed. First, the measured RR data are passed into a trimmed moving average (TMA)-based filtering system to generate a lower frequency (LF) time series and a higher frequency (HF) one that approximately reflect the sympathetic and vagal activities, respectively. Since the Lyapunov exponent can be used to characterize the level of chaos in complex physiological systems, the largest Lyapunov exponents corresponding to the complex sympathetic and vagal systems are then estimated from the LF and HF time series, respectively, using an existing algorithm. Numerical results of a postural maneuver experiment indicate that both characteristic exponents or their combinations might serve as a set of innovative and robust indicators for HRV analysis, even under the contamination of sparse impulses due to aberrant beats in the RR data.     

Evaluation of the effects of nonlinear frequency compression on speech recognition and sound quality for adults with mild to moderate hearing loss

Objective: While potentially improving audibility for listeners with considerable high frequency hearing loss, the effects of implementing nonlinear frequency compression (NFC) for listeners with moderate high frequency hearing loss are unclear. The purpose of this study was to investigate the effects of activating NFC for listeners who are not traditionally considered candidates for this technology. Design: Participants wore study hearing aids with NFC activated for a 3–4 week trial period. After the trial period, they were tested with NFC and with conventional processing on measures of consonant discrimination threshold in quiet, consonant recognition in quiet, sentence recognition in noise, and acceptableness of sound quality of speech and music. Study sample: Seventeen adult listeners with symmetrical, mild to moderate sensorineural hearing loss participated. Better ear, high frequency pure-tone averages (4, 6, and 8 kHz) were 60 dB HL or better. Results: Activating NFC resulted in lower (better) thresholds for discrimination of /s/, whose spectral center was 9 kHz. There were no other significant effects of NFC compared to conventional processing. Conclusion: These data suggest that the benefits, and detriments, of activating NFC may be limited for this population.     

Local and distant cortical responses to single pulse intracranial stimulation in the human brain are differentially modulated by specific stimulation parameters

BackgroundElectrical neuromodulation via direct electrical stimulation (DES) is an increasingly common therapy for a wide variety of neuropsychiatric diseases. Unfortunately, therapeutic efficacy is inconsistent, likely due to our limited understanding of the relationship between the massive stimulation parameter space and brain tissue responses.ObjectiveTo better understand how different parameters induce varied neural responses, we systematically examined single pulse-induced cortico-cortico evoked potentials (CCEP) as a function of stimulation amplitude, duration, brain region, and whether grey or white matter was stimulated.MethodsWe measured voltage peak amplitudes and area under the curve (AUC) of intracranially recorded stimulation responses as a function of distance from the stimulation site, pulse width, current injected, location relative to grey and white matter, and brain region stimulated (N = 52, n = 719 stimulation sites).ResultsIncreasing stimulation pulse width increased responses near the stimulation location. Increasing stimulation amplitude (current) increased both evoked amplitudes and AUC nonlinearly. Locally (<15 mm), stimulation at the boundary between grey and white matter induced larger responses. In contrast, for distant sites (>15 mm), white matter stimulation consistently produced larger responses than stimulation in or near grey matter. The stimulation location-response curves followed different trends for cingulate, lateral frontal, and lateral temporal cortical stimulation.ConclusionThese results demonstrate that a stronger local response may require stimulation in the grey-white boundary while stimulation in the white matter could be needed for network activation. Thus, stimulation parameters tailored for a specific anatomical-functional outcome may be key to advancing neuromodulatory therapy.