Quantifying neural efficiency and neural capacity across the brain during a working memory task using a quadratic model of neural-cognitive relationships

Task-based functional magnetic resonance imaging (MRI) neuroimaging for the study of cognitive neuroscience provides insight into how the brain responds to increasing cognitive demands. Theoretical models of neural-cognitive relationships define neural efficiency and neural capacity as two parameters to describe the rate of gain of brain activity and the upper limits of the increases, respectively. Although qualitatively well described, there are limited discussions and demonstrations of estimating these parameters from data. The current work presents a method using a quadratic equation model of cognitive demands. The methods were applied to 21 healthy young adults while engaging in four levels of the verbal n-back working memory task (0, 1, 2 and 3-back). Measures of the area under the curve captured both linear and curvilinear responses to quantify the locations and amounts of task-related increases in brain activity. In addition, we calculated voxel-wise maps of neural efficiency and neural capacity. Results showed increases in brain activation in regions typically involved in working memory. The relationships between increasing cognitive demands and brain activity also differed across the brain within and between individuals, as indicated by differential neural efficiency and neural capacity values. This approach provides tools for evaluating current theories about the relationships between brain activity and cognition. Neural efficiency and neural capacity provide physiological measures of brain activity, which will help evaluate how age, disease and intervention processes affect brain activity. Finally, all presented methods are readily applicable using standard current software packages for neuroimaging.

[Optimal design of neural modulation strategy of vestibular prosthesis]

Objective:To reveal the response characteristics of semicircular canal neurons（SCN） in the nonlinear perceptual interval, and to establish and screen out the precise SCN information coding model and function expression, which lays a foundation for the optimization and improvement of neuromodulation strategy of multichannel vestibular prosthesis. Method:The perceptual electrophysiological information data of the SCNs during the rotational stimulation was recorded in the nonlinear perceptual interval. The nonlinear least-squares algorithm was used to fit the electrophysiological information data to establish the linear-nonlinear models. The Akaike information criterion was used to calculate the goodness of fit of each model to determine the optimal expression function. Result:In the frequency experiment, the accurate information coding model of more than 85% of SCNs is a quadratic polynomial, and the frequency has no significant effect on the linear-nonlinear selection of the SCNs information coding model（P>0.05）. In the amplitude experiment, the accurate information coding model of more than 83.33% of SCNs is quadratic polynomial when the maximum angular velocity is>80 deg/s, and the amplitude has a significant effect on the linear-nonlinear selection of the SCNs information coding model（P=0.038）. Conclusion:The information coding models of SCN population in the nonlinear perceptual interval have two expressions, linear and nonlinear function, which is closely related to angular velocity. The quadratic polynomial function is more accurate and more advantageous and it can be used to design the precise neuromodulation strategy of multichannel vestibular prosthesis.

A WSN Layer-Cluster Key Management Scheme Based on Quadratic Polynomial and Lagrange Interpolation Polynomial

Since current key management schemes are mainly designed for static and planar networks, they are not very suitable for the layer-cluster wireless sensor networks (WSNs), a WSN layer-cluster key management scheme based on quadratic polynomial and Lagrange interpolation polynomial is proposed, in which the main idea of this scheme along the research line of broadcast identity authentication, session key, group key, network key and personal key. Specifically, authentication key can be established on the basis of Fourier series for identity authentication; session key is established by a multiple asymmetric quadratic polynomial, in which session key information is encrypted by the authentication key to ensure the security of intermediate interactive information; based on the former two keys, group key is established on the basis of Lagrange interpolation polynomial, in which the nodes of the cluster are not directly involved; the generation and management of network key is similar to the group key, in which the establishment idea is to regard the BS and all cluster heads as a group; the generation and management of personal key is also similar to the group key, the difference is that the personal key can be obtained by cluster nodes through getting the Lagrange interpolation polynomial coefficients based on their own random key information. It is analyzed that the proposed layer-cluster key management scheme can guarantee the identity of network nodes firstly through forward authentication and reverse authentication, and session key, group key and network key will guarantee the independence of the keys’ management and avoids the problem of single point failure compared with LEAP protocol, and personal key will guarantee the privacy of network.

The optimum valine: lysine ratios on performance and carcass traits of male broilers based on different regression approaches

Three different regression approaches were applied to determine the optimal digestible (d.) and analyzed Val:Lys ratios for broiler performance and carcass yield. One-day-old male Cobb 500 broilers (n = 960) were assigned to 1 of 8 diets, with 6 pens/diet and 20 birds/pen, for 42 days. The negative control consisted of the basal diet with a d.Val:d.Lys ratio of 0.63 and with 93% of the required d.Lys. The positive control consisted of the basal diet with a d.Val:d.Lys of 0.80, with no reduction in d.Lys content. The other (test) diets contained a range of d.Val:d.Lys ratios, all with 93% of the required d.Lys. Data on feed intake (FI), body weight gain (BWG), and feed conversion ratio (FCR) were submitted to regression analysis, applying quadratic polynomial (QP), exponential asymptotic (EA), and linear response plateau (LRP) models. Since Val did not affect carcass or breast meat yield, no regression was performed. Digestible and analyzed Val:Lys ratios were similar based on the regression models. The intercept between the QP and LRP models was used to determine the optimum Val:Lys ratio. Overall, the ideal d.Val:d.Lys ratio will vary according to the main goal of poultry production, i.e., BWG or FCR. For BWG, the ideal ratio was found to be 0.78 (0 to 12 d), 0.73 (0 to 28 d), and 0.76 (0 to 35 or 0 to 42 d). For FCR, the optimum d.Val:d.Lys was found to be 0.80 (0 to 12 d), 0.75 (0 to 28 d), and 0.78 (0 to 35 or 0 to 42 d). The optimum analyzed Val:Lys ratio was slightly higher. For instance, for BWG the optimum ratio was 0.80 (0 to 12 d), 0.76 (0 to 28 d), and 0.79 (0 to 35 or 0 to 42 d). For FCR, the optimum Val:Lys was 0.81 (0 to 12 d), 0.79 (0 to 28 d), and 0.81 (0 to 35 or 0 to 42 d). Valine did not affect carcass or breast meat yield.

Generalized Two-dimensional Correlation Analysis for Unimodal Waveforms Modeled by Quadratic Polynomials

We describe further potential of generalized 2D correlation analysis, aiming to realize the automation of the sequential order determination of signal variations. By modeling unimodal waveforms using quadratic functions, we can analytically express 2D correlation functions to yield an index to determine the sequential order. Based on the obtained results, we find an exception for determining the sequential order of signal variations. To resolve the exception, we suggest an extended way of interpreting the sequential order of signal intensity changes.