Relationship between neural and hemodynamic signals during spontaneous activity studied with temporal kernel CCA

Functional magnetic resonance imaging (fMRI) based on the so-called blood oxygen level-dependent (BOLD) contrast is a powerful tool for studying brain function not only locally but also on the large scale. Most studies assume a simple relationship between neural and BOLD activity, in spite of the fact that it is important to elucidate how the “when” and “what” components of neural activity are correlated to the “where” of fMRI data. Here we conducted simultaneous recordings of neural and BOLD signal fluctuations in primary visual (V1) cortex of anesthetized monkeys. We explored the neurovascular relationship during periods of spontaneous activity by using temporal kernel canonical correlation analysis (tkCCA). tkCCA is a multivariate method that can take into account any features in the signals that univariate analysis cannot. The method detects filters in voxel space (for fMRI data) and in frequency–time space (for neural data) that maximize the neurovascular correlation without any assumption of a hemodynamic response function (HRF). Our results showed a positive neurovascular coupling with a lag of 4–5 s and a larger contribution from local field potentials (LFPs) in the γ range than from low-frequency LFPs or spiking activity. The method also detected a higher correlation around the recording site in the concurrent spatial map, even though the pattern covered most of the occipital part of V1. These results are consistent with those of previous studies and represent the first multivariate analysis of intracranial electrophysiology and high-resolution fMRI.     

Testing methodologies for the nonlinear analysis of causal relationships in neurovascular coupling

We investigated the use and implementation of a nonlinear methodology for establishing which changes in neurophysiological signals cause changes in the blood oxygenation level-dependent (BOLD) contrast measured in functional magnetic resonance imaging. Unlike previous analytical approaches, which used linear correlation to establish covariations between neural activity and BOLD, we propose a directed information-theoretic measure, the transfer entropy, which can elucidate even highly nonlinear causal relationships between neural activity and BOLD signal. In this study we investigated the practicality of such an analysis given the limited data samples that can be collected experimentally due to the low temporal resolution of BOLD signals. We implemented several algorithms for the estimation of transfer entropy and we tested their effectiveness using simulated local field potentials (LFPs) and BOLD data constructed to match the main statistical properties of real LFP and BOLD signals measured simultaneously in monkey primary visual cortex. We found that using the advanced methods of entropy estimation implemented and described here, a transfer entropy analysis of neurovascular coupling based on experimentally attainable data sets is feasible.     

On the relationship between the density functional formalism and the potential distribution theory for nonuniform fluids

It is shown that the variational principle for the grand potential of a nonuniform fluid as a functional of the singlet density yields the potential distribution theory for the equilibrium density. We derive the explicit form that the functional takes for a system of hard rods, and propose an approximate one for hard spheres. Attractive interactions are also considered in mean-field approximation. In all cases the pair direct correlation function of the nonuniform system is obtained and the density gradient expansion of the free energy is investigated.     

Evaluating the dynamical coupling between spatiotemporally chaotic signals via an information theory approach

An information-theoretic measure is introduced for evaluating the dynamical coupling of spatiotemporally chaotic signals produced by extended systems. The measure of the one-way coupled map lattices and the one-dimensional, homogeneous, diffusively coupled map lattices is computed with the symbolic analysis method. The numerical results show that the information measure is applicable to determining the dynamical coupling between two directly coupled or indirectly coupled chaotic signals.     

Remote impact analysis by use of propagated acceleration signals,II: Comparison between theory and experiment

The techniques for remote impact analysis developed in Part I [1] are analyzed from an experimental point of view. Comparison is made between the theoretical and experimental Timoshenko transfer functions between the remote acceleration transform and the impact force-time history transform. The inversion process has been applied with success to experimental impacting data; good representations of impact force-time histories have been obtained even in the presence of signal contamination.     

Model architecture for associative memory in a neural network of spiking neurons

A synaptic connectivity model is assembled on a spiking neuron network aiming to build up a dynamic pattern recognition system. The connection architecture includes gap junctions and both inhibitory and excitatory chemical synapses based on Hebb’s hypothesis. The network evolution resulting from external stimulus is sampled in a properly defined frequency space. Neurons’ responses to different current injections are mapped onto a subspace using Principal Component Analysis. Departing from the base attractor, related to a quiescent state, different external stimuli drive the network to different fixed points through specific trajectories in this subspace.     

On the relationship between signal bandwidth and frequency correlation for ocean surface forward scattered signals

The relationship between the bandwidth of a signal and the correlation of that signal with its ocean surface reflected arrival, a quantity we term frequency correlation, has been investigated experimentally and compared with two theories. Decorrelation of wideband surface scattered signals is a direct consequence of time spread. The acoustic measurement utilized a very short pure tone signal, from which time spread has been estimated, and four broadband signals with different bandwidths, for which correlation with the transmitted signal has been measured. An environment-driven model developed by Dahl was used to predict time spread, which agreed favorably with our time spread measurements. The model was also employed in two theories that predict frequency correlation. The first, a theory published by Reeves in 1974, is based upon the ratio of signal temporal resolution to total time spread. This theory compared well with our measurements for 1 kHz bandwidth signals, but is not applicable for signal bandwidths greater than about 2 kHz. The second, a theory developed by Ziomek, models ocean acoustic propagation as transmission through a linear system. This theory agreed well with our frequency correlation measurements for signal bandwidths of 1-22 kHz.     

Statistical thermodynamic formalism in the solution of information theory problems

This is the first of several papers dealing with the application of statistical thermodynamic methodology to the solution of coding and communication theory problems. Emphasis is placed on the various ensemble techniques of statistical mechanics, the words or samples of a message taking the place of molecules in the prototype physical system. Analogs of temperature, internal energy, pressure, chemical potential, volume, entropy, etc., are developed. The isomorphism with thermodynamics is complete and these quantities transform (for example, by partial differentiation) in exactly the same way as the prototype physical quantities. The methods are nicely applicable to coding cases involving sources with memory, in which case, correlation can be discussed in terms of analog coupling energies between signals or words so that the store of many-body-problem techniques can be used. In addition, the manipulative freedom stemming from the possibility of choosing from a multiplicity of ensembles constrained by intensive parameters proves a distinct advantage. A concrete example dealing with the choice of a compact code for a nonextended source with memory is presented. The compact code is derived, and some discussion is given concerning the breadth of its power spectrum. In a following paper, its autocorrelation function within the framework of pulse code modulation is derived and transformed by Wiener theory so that the power spectrum is directly exhibited (along with the spectra for several other cases).Research supported under AFOSR Grant No. 70-1877. The present work is contribution No. 2643 of the Department of Chemistry, University of California-Los Angeles.     

Coupling of neural activity and fMRI-BOLD in the motion area MT

The fMRI-BOLD contrast is widely used to study the neural basis of sensory perception and cognition. This signal, however, reflects neural activity only indirectly, and the detailed mechanisms of neurovascular coupling and the neurophysiological correlates of the BOLD signal remain debated. Here we investigate the coupling of BOLD and electrophysiological signals in the motion area MT of the macaque monkey by simultaneously recording both signals. Our results demonstrate that a prominent neuronal response property of area MT, so-called motion opponency, can be used to induce dissociations of BOLD and neuronal firing. During the presentation of a stimulus optimally driving the local neurons, both field potentials [local field potentials (LFPs)] and spiking activity [multi-unit activity (MUA)] correlated with the BOLD signal. When introducing the motion opponency stimulus, however, correlations of MUA with BOLD were much reduced, and LFPs were a much better predictor of the BOLD signal than MUA. In addition, for a subset of recording sites we found positive BOLD and LFP responses in the presence of decreases in MUA, regardless of the stimulus used. Together, these results demonstrate that correlations between BOLD and MUA are dependent on the particular site and stimulus paradigm, and foster the notion that the fMRI-BOLD signal reflects local dendrosomatic processing and synaptic activity rather than principal neuron spiking responses.     

The relationship between BOLD signal and autonomic nervous system functions: implications for processing of "physiological noise"

Functional magnetic resonance imaging (fMRI) research has revealed not only important aspects of the neural basis of cognitive and perceptual functions, but also important information on the relation between high-level brain functions and physiology. One of the central outstanding questions, given the features of the blood oxygenation level-dependent (BOLD) signal, is whether and how autonomic nervous system (ANS) functions are related to changes in brain states as measured in the human brain. A straightforward way to address this question has been to acquire external measurements of ANS activity such as cardiac and respiratory data, and examine their relation to the BOLD signal. In this article, we describe two conceptual approaches to the treatment of ANS measures in the context of BOLD fMRI analysis. On the one hand, several research lines have treated ANS activity measures as noise, considering them as nothing but a confounding factor that reduces the power of fMRI analysis or its validity. Work in this line has developed powerful methods to remove ANS effects from the BOLD signal. On the other hand, a different line of work has made important progress in showing that ANS functions such as cardiac pulsation, heart rate variability and breathing rate could be considered as a theoretically meaningful component of the signal that is useful for understanding brain function. Work within this latter framework suggests that caution should be exercised when employing procedures to remove correlations between BOLD data and physiological measures. We discuss these two positions and the reasoning underlying them. Thereafter, we draw on the reviewed literature in presenting practical guidelines for treatment of ANS data, which are based on the premise that ANS data should be considered as theoretically meaningful information. This holds particularly when studying cortical systems involved in regulation, monitoring and/or generation of ANS activity, such as those involved in decision making, conflict resolution and the experience of emotion.     

Finite-state neural networks. A step toward the simulation of very large systems

Neural networks composed of neurons withQ _N states and synapses withQ states are studied analytically and numerically. Analytically it is shown that these finite-state networks are much more efficient at information storage than networks with continuous synapses. In order to take the utmost advantage of networks with finite-state elements, a multineuron and multisynapse coding scheme is introduced which allows the simulation of networks having 1.0×10⁹ couplings at a speed of 7.1×10⁹ coupling evaluations per second on asingle processor of the Cray-YMP. A local learning algorithm is also introduced which allows for the efficient training of large networks with finite-state elements.     

An investigation of the relationship between BOLD and perfusion signal changes during epileptic generalised spike wave activity

In pathological conditions interpretation of functional magnetic resonance imaging (fMRI) results can be difficult. This is due to a reliance on the assumed coupling between neuronal activity and changes in cerebral blood flow (CBF) and oxygenation. We wanted to investigate the coupling between blood oxygen level dependant contrast (BOLD) and CBF time courses in epilepsy patients with generalised spike wave activity (GSW) to better understand the underlying mechanisms behind the EEG-fMRI signal changes observed, especially in regions of negative BOLD response (NBR). Four patients with frequent GSW were scanned with simultaneous electroencephalographic (EEG)-fMRI with BOLD and arterial spin labeling (ASL) sequences. We examined the relationship between simultaneous CBF and BOLD measurements by looking at the correlation of the two signals in terms of percentage signal change on a voxel-by-voxel basis. This method is not reliant on coincident activation. BOLD and CBF were positively correlated in patients with epilepsy during background EEG activity and GSW. The subject average value of the Delta CBF/Delta BOLD slope lay between +19 and +36 and also showed spatial variation which could indicate areas with altered vascular response. There was not a significant difference between Delta CBF/Delta BOLD during GSW, suggesting that neurovascular coupling to BOLD signal is generally maintained between states and, in particular, within areas of NBR.     

On the far field in the Lorenz-Mie theory and T-matrix formulation

The far field within the context of the Lorenz-Mie theory and the T-matrix formulation is usually expressed on the basis of the asymptotic properties of vector spherical waves. The radiation condition is taken into account by employing proper vector spherical functions as the expansion basis of the scattered field. The asymptotic behavior of the Hankel function is obtained from differential equations. The asymptotic far field can also be obtained from the Kirchhoff surface integral equation, in which the radiation condition has been implemented when it is derived from the Maxwell equations. This note is to present an explicit establishment of the relationship between the asymptotic far field and the near field in the Lorenz-Mie theory and the T-matrix formulation through the Kirchhoff surface integral.     

导体椭球的面电荷密度和曲率的关系

通过求解拉普拉斯方程,得到导体椭球的电势分布情况,进一步分析了导体表面的面电荷密度和曲率的关系,得到面电荷密度不是和曲率成正比,而是和曲率的1/3次方成正比的.     

偏置模式波前传感器光强信息提取及输出信号对比分析

 在小像差近似下,对偏置模式波前传感器进行了理论分析,明确了该传感器的适用条件,对比分析了3种信息提取方式和3种传感器信号输出方式的优劣。针对Zernike像差模式,数值模拟研究了传感器对单阶和多阶模式的响应特性。结果表明,畸变波前中与偏置模式相同或相关的模式之间有响应,但传感器对各阶Zernike模式的响应灵敏度不同,而且不相关模式的存在对传感器输出信号和灵敏度均有影响。     

Application of information theory to the design of line-scan and sensor-array imaging systems

Information theory is used to assess the performance of line-scan and sensor-array imaging systems as a function of their spatial response, sensitivity, and sampling and quantization intervals. Computational results for the statistical properties of random radiance fields provide general guidelines for optimizing the information efficiency of image data acquisition, processing and reconstruction systems.     

偏置模式波前传感器光强信息提取及输出信号对比分析

在小像差近似下,对偏置模式波前传感器进行了理论分析,明确了该传感器的适用条件,对比分析了3种信息提取方式和3种传感器信号输出方式的优劣。针对Zernike像差模式,数值模拟研究了传感器对单阶和多阶模式的响应特性。结果表明,畸变波前中与偏置模式相同或相关的模式之间有响应,但传感器对各阶Zernike模式的响应灵敏度不同,而且不相关模式的存在对传感器输出信号和灵敏度均有影响。     

运用神经网络推算音乐厅满场混响时间

混响时间是厅堂音质评价中的一个重要客观参量。本文提出了运用神经网络由空场混响时间推算满场混响时间的新方法。与其它方法比较,该方法有相当的预测精度。在此基础上,本文进一步分析了音乐厅中座椅类型和座椅数量对满场混响时间的影响,并对满场条件下座椅的吸声增量进行了讨论。     

On the use of the derivative of electroglottographic signals for characterization of nonpathological phonation

Electroglottography is a common method for providing noninvasive measurements of glottal activity. The derivative of the electroglottographic signal, however, has not attracted much attention, although it yields reliable indicators of glottal closing instants. The purpose of this paper is to provide a guide to the usefulness of this signal. The main features that are to be found in this signal are presented on the basis of an extensive analysis of a database of items sung by 18 trained singers. Glottal opening and closing instants are related to peaks in the signal; the latter can be used to measure glottal parameters such as fundamental frequency and open quotient. In some cases, peaks are doubled or imprecise, which points to special (but by no means uncommon) glottal configurations. A correlation-based algorithm for the automatic measurement of fundamental frequency and open quotient using the derivative of electroglottographic signals is proposed. It is compared to three other electroglottographic-based methods with regard to the measurement of open quotient in inverse-filtered derived glottal flow. It is shown that agreement with the glottal-flow measurements is much better than most threshold-based measurements in the case of sustained sounds.