生物神经网络系统动力学与功能研究

生物神经系统是由数量极其巨大的神经元相互联结的信息网络系统,在生物体的感觉、认知和运动控制中发挥关键性的作用.首先介绍神经元、大脑和一些生物神经网络的生理结构和理论模型,然后分别介绍其放电活动和网络动态特性的一些重要问题,包括神经元的复杂放电模式、耦合神经元网络系统的同步活动和时空动力学、大脑联合皮层神经微回路的网络结构特征,以及工作记忆和抉择过程的动力学机制等. 最后对今后研究给出一些展望.      

Studying Physiological Synchrony in Couple Therapy through Partial Directed Coherence: Associations with the Therapeutic Alliance and Meaning Construction

In line with the growing recognition of the role of embodiment, affect and implicit processes in psychotherapy, several recent studies examine the role of physiological synchrony in the process and outcome of psychotherapy. This study aims to introduce Partial Directed Coherence (PDC) as a novel approach to calculating psychophysiological synchrony and examine its potential to contribute to our understanding of the therapy process. The study adopts a single-case, mixed-method design and examines physiological synchrony in one-couple therapy in relation to the therapeutic alliance and a narrative analysis of meaning construction in the sessions. Interpersonal Physiological Synchrony (IPS) was calculated, via a windowed approach, through PDC of a Heart Rate Variability-derived physiological index, which was measured in the third and penultimate sessions. Our mixed-method analysis shows that PDC quantified significant moments of IPS within and across the sessions, modeling the characteristics of interpersonal interaction as well as the effects of therapy on the interactional dynamics. The findings of this study point to the complex interplay between explicit and implicit levels of interaction and the potential contribution of including physiological synchrony in the study of interactional processes in psychotherapy.     

Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin--Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τ_syn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τ_syn, suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks.     

Generalized Edwards Transformation and Principle of Permutation Invariance

The relativity of simultaneity is generalized by using the concept of synchronization gauge. The Lorentz transformation is derived without the postulate of the universal limiting speed, and a generalized Edwards transformation is obtained by using the principle of permutation invariance (covariance). It is shown that the existences of the one-way universal limiting speed (in the Lorentz transformation) and the constancy of the two-way average speed of light (in the Edwards transformation) are the necessary consequences of the principle of permutation invariance that is consistent with the postulate of relativity. The connection between the Edward transformation and the general coordinate transformation is discussed, and based on this, we find that the physical meaning of the Edwards parameter, which indicates anisotropy of the speed of light, is a gravitomagnetic potential of the spacetime.     

A note on the onset of synchrony in avian ovulation cycles

Spontaneous oscillator synchrony occurs when populations of interacting oscillators begin cycling together in the absence of environmental forcing. Synchrony has been documented in many physical and biological systems, including oestrus/menstrual cycles in rats and humans. In previous work we showed that Glaucous-winged Gulls (Larus glaucescens) can lay eggs synchronously on an every-other-day schedule, and that synchrony increases with colony density. Here we pose a discrete-time model of avian ovulation to study the dynamics of synchronization. We prove the existence and uniqueness of an equilibrium solution which bifurcates to increasingly synchronous cycles as colony density increases.     

A note on synchronous egg laying in a seabird behaviour model

ABSTRACT

During years when sea surface temperature (SST) is high, gulls in a colony on Protection Island, Washington, USA typically experience low food availability. As SST rises, feeder fish follow plankton to cooler temperatures in deeper water levels. Since gulls are surface-feeding birds, they face a food shortage. A tactic male gulls employ to deal with this food shortage is to cannibalize their neighbours' eggs. Gulls in this colony exhibit an adaptive tactic of every-other-day egg-laying synchrony in response to egg cannibalism, and the level of synchrony increases with colony density. Here we analyze the dynamics of an animal behaviour model for egg laying as a function of colony density. As colony density increases, the equilibrium loses stability in a 2-cycle bifurcation. The 2-cycle becomes increasingly synchronous as the colony density continues to increase. We show that egg-laying synchrony benefits the colony in the presence of cannibalism.     

The phase shift index for marking functional asynchrony in Alzheimer's disease patients using fMRI

Our previous study suggested that the functional magnetic resonance imaging MRI (fMRI) COSLOF Index (CI) could be used as a quantitative biomarker for Alzheimer's disease (AD). The fMRI CI was lowest in the AD group (0.13+/-0.10), followed by the mild cognitive impairment (MCI) group (0.20+/-0.05) and the control group (0.34+/-0.09). The current study continues an investigation into which of the following two factors has a dominant role in determining the CI: the signal-to-noise ratio (SNR) or the phase shift of spontaneous low-frequency (SLF) components. By using a theoretical model for SLF components, we demonstrated that the normalized CI does not depend on the SNR of the SLF components. Further analysis shows that by taking the ratio of the cross-correlation coefficient to the maximum-shifted cross-correlation coefficient, the SNR factor can be canceled. Therefore, the determination of the phase shift index (PSI) method is independent of the SNR, and the PSI provides an accurate measure of the phase shift between SLF components. By applying this PSI method to the control, MCI and AD groups of subjects, experimental results demonstrated that the PSI was highest in the AD group (72.6+/-11.3 degrees ), followed by the MCI group (58.6+/-5.7 degrees ) and, finally, the control group (40.6+/-8.4 degrees ). These results suggest that the larger is the PSI value, the more asynchrony exists between SLF components.     

Pattern synchrony in electrical signals related to earthquake activity

We apply the cross sample entropy method to geoelectrical time series collected from independent channels (North-South and East-West directions) monitored at two sites located in Mexico, to assess the presence of pattern synchrony between the signals, particularly in the proximity of earthquakes. To our best knowledge, this method has not been applied yet for the study of electrical signals related to earthquake activity. Moreover, we introduce the multiscale pattern synchrony analysis by extending the multiscale entropy technique to calculate the cross-entropy between two signals, which represents a novel approach to the study of pattern synchrony. The results obtained suggest that in the vicinity of an earthquake the geoelectrical signals exhibit pattern synchrony that persists for long sequences and through multiple scales, in addition to the presence of correlations in each channel.     

Beyond Dyadic Coupling: The Method of Multivariate Surrogate Synchrony (mv-SUSY)

Measuring interpersonal synchrony is a promising approach to assess the complexity of social interaction, which however has been mostly limited to dyads. In this study, we introduce multivariate Surrogate Synchrony (mv-SUSY) to extend the current set of computational methods. Methods: mv-SUSY was applied to eight datasets consisting of 10 time series each, all with n = 9600 observations. Datasets 1 to 5 consist of simulated time series with the following characteristics: white noise (dataset 1), non-stationarity with linear time trends (dataset 2), autocorrelation (dataset 3), oscillation (dataset 4), and multivariate correlation (dataset 5). Datasets 6 to 8 comprise empirical multivariate movement data of two individuals (datasets 6 and 7) and between members of a group discussion (dataset 8.) Results: As hypothesized, findings of mv-SUSY revealed absence of synchrony in datasets 1 to 4 and presence of synchrony in dataset 5. In the empirical datasets, mv-SUSY indicated significant movement synchrony. These results were predominantly replicated by two well-established dyadic synchrony approaches, Surrogate Synchrony (SUSY) and Surrogate Concordance (SUCO). Conclusions: The study applied and evaluated a novel synchrony approach, mv-SUSY. We demonstrated the feasibility and validity of estimating multivariate nonverbal synchrony within and between individuals by mv-SUSY.