Magnetoencephalography and its Achilles' heel

Magnetoencephalography (MEG) has practically unlimited temporal resolution. Fundamental physical reasons, however, restrict the capability of MEG to separate simultaneously active sources. After a brief tutorial introduction into MEG, various aspects of spatial resolution are reviewed with the help of examples. First the estimation of a single current dipole is examined. A consideration of the resolution field shows that the spatial selectivity of the estimated dipole moment is highly dependent on methodological issues. A subsequent consideration of various two-dipole configurations illustrates how the topography of the magnetic field depends on the distance between the two dipoles and their relative orientations. The resolution fields associated with the estimation of the dipole moments reveal a strong interference for closely spaced dipoles. A simple model suggests that the standard deviations of the estimated moments are inversely proportional to the distance of the dipoles. Spatial information provided by techniques like functional magnetic resonance imaging (fMRI) could help to overcome problems resulting from the limited spatial resolution of MEG (multimodal integration). But a straightforward synthesis, according to the principle that fMRI provides the spatial structure of the sources and MEG adds the temporal information, is probably doomed to failure in many situations. A serious dilemma, among other problems, is that the fMRI signal generally represents a temporal integral over several seconds: The knowledge that a certain brain region was active sometime or other is not necessarily helpful for disentangling the MEG activity within a specified short time window. An intriguing fact is that the spatio-temporal pattern of the MEG signals can be considered as a signature of the brain which is suitable for hypothesis testing with high temporal and spatial resolution.     

The Gaussian derivative model for spatial-temporal vision: I. Cortical model

How do we see the motion of objects as well as their shapes? The Gaussian Derivative (GD) spatial model is extended to time to help answer this question. The GD spatio-temporal model requires only two numbers to describe the complete three-dimensional space-time shapes of individual receptive fields in primate visual cortex. These two numbers are the derivative numbers along the respective spatial and temporal principal axes of a given receptive field. Nine transformation parameters allow for a standard geometric association of these intrinsic axes with the extrinsic environment. The GD spatio-temporal model describes in one framework the following properties of primate simple cell fields: motion properties, number of lobes in space-time, spatial orientation. location, and size. A discrete difference-of-offset-Gaussians (DOOG) model provides a plausible physiological mechanism to form GD-like model fields in both space and time. The GD model hypothesizes that receptive fields at the first stage of processing in the visual cortex approximate 'derivative analyzers' that estimate local spatial and temporal derivatives of the intensity profile in the visual environment. The receptive fields as modeled provide operators that can allow later stages of processing in either a biological or machine vision system to estimate the motion as well as the shapes of objects in the environment.     

Visualizing the onset and evolution of an autoantibody response in systemic autoimmunity

The onset of systemic autoimmunity is variable, making it difficult to identify early events. In this study, we show in rheumatoid factor (RF) Ig-transgenic autoimmune-prone mice that the appearance of RF B cells in blood signifies the onset of RF B cell activation in spleen, providing a novel window into the initiation of an autoantibody response. This allowed us to study the early and late phases of spontaneous induction of the B cell autoimmune response. Using this approach we showed that extensive Ab-forming cell generation in spleen, accompanied by somatic hypermutation, occurred despite the lack of an early germinal center response. The onset of the RF response correlated with the levels of IgG2a-containing immune complexes but not total IgG2a. By identifying the time of onset in individual mice, we were able to track progression of disease. We found remissions of RF Ab-forming cell production in some mice, suggesting that at the clonal level, chronic autoantibody responses are dynamic and episodic, much like acute pathogen responses. Surprisingly, there was little accumulation of long-lived plasma cells in bone marrow of mice with long-standing RF responses in spleen. These studies are among the first to define the early events of a spontaneous B cell autoimmune response.     

时空分离Gabor函数模型和感受野的时间特性

本文在我们以前提出的感受野的广义Cabor函数模型基础上,提出了时空可分离感受野数学模型,以此模拟了感受野的各种时间反应性质,并据此推断了两种方向检测感受野模型,模拟了on-off感受野速率谐调曲线.说明Gabor函数也同样很好地反映了感受野的时间性质.     

Synaptic integration fields and associative plasticity of visual cortical cells in vivo

Two major constraints in connectivity decide the spatial extent of visual cortical receptive fields, both during development and adult functioning: 1) feedforward input, extrinsic to visual cortex, is organized in an orderly projection to form a point-to-point mapping of the retina onto the cortical mantle and constitutes the core of the minimal discharge field (MDF) after amplification by local intracortical circuits; and 2) a second type of connectivity consists of long distance horizontal intracortical connections which are thought to favor the binding of local visual operations occurring simultaneously in different parts of the visual field. We review here possible factors, intrinsic to the considered cortical cell, that may control the effectiveness of post-synaptic integration. Their expression during sensory recognition could depend on the spatio-temporal distribution of active inputs onto the target cell dendrite and on their interplay with non-linearities of the membrane properties. On the basis of intracellular recordings in cat area 17, we have observed that peripheral responses (excitatory and inhibitory) could be boosted by coincident postsynaptic depolarization. This effect is lost if the response and the postsynaptic depolarization are mismatched by 1000 ms, suggesting that temporal correlation of central and peripheral responses could regulate in a non-linear manner the gain of center-surround interactions. This temporal selectivity is compatible with up-regulation of composite potentials by the transient voltage-dependent activation of slowly inactivating conductances in visual cortical neurons. A direct consequence of these different considerations is that the receptive field (RF) of neurons in visual pathways should not be considered as a static hardwired window probing the outer environment, but as an active filter which may continuously adapt and be updated as a function of global context and past experience.     

Neural Mechanism of Facilitation System during Physical Fatigue

An enhanced facilitation system caused by motivational input plays an important role in supporting performance during physical fatigue. We tried to clarify the neural mechanisms of the facilitation system during physical fatigue using magnetoencephalography (MEG) and a classical conditioning technique. Twelve right-handed volunteers participated in this study. Participants underwent MEG recording during the imagery of maximum grips of the right hand guided by metronome sounds for 10 min. Thereafter, fatigue-inducing maximum handgrip trials were performed for 10 min; the metronome sounds were started 5 min after the beginning of the handgrip trials. The metronome sounds were used as conditioned stimuli and maximum handgrip trials as unconditioned stimuli. The next day, they were randomly assigned to two groups in a single-blinded, two-crossover fashion to undergo two types of MEG recordings, that is, for the control and motivation sessions, during the imagery of maximum grips of the right hand guided by metronome sounds for 10 min. The alpha-band event-related desynchronizations (ERDs) of the motivation session relative to the control session within the time windows of 500 to 700 and 800 to 900 ms after the onset of handgrip cue sounds were identified in the sensorimotor areas. In addition, the alpha-band ERD within the time window of 400 to 500 ms was identified in the right dorsolateral prefrontal cortex (Brodmann''s area 46). The ERD level in the right dorsolateral prefrontal cortex was positively associated with that in the sensorimotor areas within the time window of 500 to 700 ms. These results suggest that the right dorsolateral prefrontal cortex is involved in the neural substrates of the facilitation system and activates the sensorimotor areas during physical fatigue.     

An in vivo assay of synaptic function mediating human cognition

The contribution of dopamine to working memory has been studied extensively [1-3]. Here, we exploited its well characterized effects [1-3] to validate a novel human in?vivo assay of ongoing synaptic [4, 5] processing. We obtained magnetoencephalographic (MEG) measurements from subjects performing a working memory (WM) task during a within-subject, placebo-controlled, pharmacological (dopaminergic) challenge. By applying dynamic causal modeling (DCM), a Bayesian technique for neuronal system identification [6], to MEG signals from prefrontal cortex, we demonstrate that it is possible to infer synaptic signaling by specific ion channels in behaving humans. Dopamine-induced enhancement of WM performance was accompanied by significant changes in MEG signal power, and?a DCM assay disclosed related changes in synaptic signaling. By estimating the contribution of ionotropic receptors (AMPA, NMDA, and GABA(A)) to the observed spectral response, we demonstrate changes in their function commensurate with the synaptic effects of dopamine. The validity of our model is reinforced by a striking quantitative effect on NMDA and AMPA receptor signaling that predicted behavioral improvement over subjects. Our results provide a proof-of-principle demonstration of a novel framework for inferring, noninvasively, neuromodulatory influences on ion channel signaling via specific ionotropic receptors, providing a window on the hidden synaptic events mediating discrete psychological processes in humans.     

Spatio-temporal visual properties in the ascending tectofugal system

Our study compares the spatio-temporal visual receptive field properties of different subcortical stages of the ascending tectofugal visual system. Extracellular single-cell recordings were performed in the superficial (SCs) and intermediate (SCi) layers of the superior colliculus (SC), the suprageniculate nucleus (Sg) of the posterior thalamus and the caudate nucleus (CN) of halothane-anesthetized cats. Neuronal responses to drifting gratings of various spatial and temporal frequencies were recorded. The neurons of each structure responded optimally to low spatial and high temporal frequencies and displayed narrow spatial and temporal frequency tuning. The detailed statistical analysis revealed that according to its stimulus preferences the SCs has markedly different spatio-temporal properties from the homogeneous group formed by the SCi, Sg and CN. The SCs neurons preferred higher spatial and lower temporal frequencies and had broader spatial tuning than the other structures. In contrast to the SCs the visually active SCi, as well as the Sg and the CN neurons possessed consequently similar spatio-temporal preferences. These data support our hypothesis that the visually active SCi, Sg and CN neurons form a homogeneous neuronal population given a similar spatio-temporal frequency preference and a common function in processing of dynamic visual information.     

Gamma Power Is Phase-Locked to Posterior Alpha Activity

Neuronal oscillations in various frequency bands have been reported in numerous studies in both humans and animals. While it is obvious that these oscillations play an important role in cognitive processing, it remains unclear how oscillations in various frequency bands interact. In this study we have investigated phase to power locking in MEG activity of healthy human subjects at rest with their eyes closed. To examine cross-frequency coupling, we have computed coherence between the time course of the power in a given frequency band and the signal itself within every channel. The time-course of the power was calculated using a sliding tapered time window followed by a Fourier transform. Our findings show that high-frequency gamma power (30–70 Hz) is phase-locked to alpha oscillations (8–13 Hz) in the ongoing MEG signals. The topography of the coupling was similar to the topography of the alpha power and was strongest over occipital areas. Interestingly, gamma activity per se was not evident in the power spectra and only became detectable when studied in relation to the alpha phase. Intracranial data from an epileptic subject confirmed these findings albeit there was slowing in both the alpha and gamma band. A tentative explanation for this phenomenon is that the visual system is inhibited during most of the alpha cycle whereas a burst of gamma activity at a specific alpha phase (e.g. at troughs) reflects a window of excitability.     

Unconsciously Perceived Fear in Peripheral Vision Alerts the Limbic System: A MEG Study

Background

In ecological situations, threatening stimuli often come out from the peripheral vision. Such aggressive messages must trigger rapid attention to the periphery to allow a fast and adapted motor reaction. Several clues converge to hypothesize that peripheral danger presentation can trigger off a fast arousal network potentially independent of the consciousness spot.

Methodology/Principal Findings

In the present MEG study, spatio-temporal dynamics of the neural processing of danger related stimuli were explored as a function of the stimuli position in the visual field. Fearful and neutral faces were briefly presented in the central or peripheral visual field, and were followed by target faces stimuli. An event-related beamformer source analysis model was applied in three time windows following the first face presentations: 80 to 130 ms, 140 to 190 ms, and 210 to 260 ms. The frontal lobe and the right internal temporal lobe part, including the amygdala, reacted as soon as 80 ms of latency to fear occurring in the peripheral vision. For central presentation, fearful faces evoked the classical neuronal activity along the occipito-temporal visual pathway between 140 and 190 ms.

Conclusions

Thus, the high spatio-temporal resolution of MEG allowed disclosing a fast response of a network involving medial temporal and frontal structures in the processing of fear related stimuli occurring unconsciously in the peripheral visual field. Whereas centrally presented stimuli are precisely processed by the ventral occipito-temporal cortex, the related-to-danger stimuli appearing in the peripheral visual field are more efficient to produce a fast automatic alert response possibly conveyed by subcortical structures.     

Simultaneous quantification of cell motility and protein-membrane-association using active contours

We present a new method for the quantification of dynamic changes in fluorescence intensities at the cell membrane of moving cells. It is based on an active contour method for cell-edge detection, which allows tracking of changes in cell shape and position. Fluorescence intensities at specific cortical subregions can be followed in space and time and correlated with cell motility. The translocation of two GFP tagged proteins (CRAC and GRP1) from the cytosol to the membrane in response to stimulation with the chemoattractant cAMP during chemotaxis of Dictyostelium cells and studies of the spatio-temporal dynamics of this process exemplify the method: We show that the translocation can be correlated with motility parameters and that quantitative differences in the rate of association and dissociation from the membrane can be observed for the two PH domain containing proteins. The analysis of periodic CRAC translocation to the leading edge of a cell responding to natural cAMP waves in a mound demonstrates the power of this approach. It is not only capable of tracking the outline of cells within aggregates in front of a noisy background, but furthermore allows the construction of spatio-temporal polar plots, capturing the dynamics of the protein distribution at the cell membrane within the cells' moving co-ordinate system. Compilation of data by means of normalised polar plots is suggested as a future tool, which promises the so-far impossible practicability of extensive statistical studies and automated comparison of complex spatio-temporal protein distribution patterns.     

Dependence of Visual Cell Properties on Intracortical Synapses Among Hypercolumns: Analysis by a Computer Model

The role of intracortical synapses in affecting the property of visual cells is investigated by means of an original mathematical model of cortical circuitry in V1. The model represents a compromise between computational simplicity and physiological reliability. The model incorporates four different inputs into a cortical cell: thalamic input from the lateral geniculate nucleus, according to an even Gabor function; short-range inhibition confined within the hypercolumn; a long-range excitation, which emphasizes the properties of the input; and a long-range inhibition. In the model we assume that all cells receive a similar thalamic input, which differs simply according to its position in the retina and orientation preference. Simulations were performed, with different parameter values, to assess the main characteristics of cell response (i.e., the width and locations of subregions in the receptive field (RF), orientation tuning curve, and response to drifting and counterphase gratings) as a function of the strength and extension of intracortical excitatory synapses. Results suggest that, if intracortical excitation is confined within the hypercolumn, the cells exhibit the same properties as simple cells, both with regards to the width and shape of the RF, orientation tuning curve, and response to drifting and counterphase gratings. By contrast, if excitatory synapses extend beyond the hypercolumn with sufficient strength, the cells exhibit the typical characteristics of complex cells. A progressive shift from complex to simple cells can be realized with a monotonic variation in parameters. Simulations are also performed with a hierarchical model, to suggest possible experiments able to discriminate the present recurrent mechanism from the classical hierarchical one. Results support the assumptions of previous simpler models (Chance et al., 1999) and may help to understand and assess the role of intracortical synapses in rigorous quantitative terms.     

Birth, growth and death as structuring operators in bacterial population dynamics

A new model is presented that describes microbial population dynamics that emerge from complex interactions among birth, growth and death as oriented, discrete events. Specifically, birth and death act as structuring operators for individual organisms within the population, which become synchronised as age clusters (called cell generations that are structured in age classes) that are born at the same time and die in concert; a pattern very consistent with recent experimental data that show bacterial group death correlates with temporal population dynamics in chemostats operating at carrying capacity. Although the model only assumes “natural death” (i.e., no death from predation or antimicrobial exposure), it indicates that short-term non-linear dynamic behaviour can exist in a bacterial population growing under longer term pseudo-steady-state conditions (a confined dynamic equilibrium). After summarizing traditional assumptions about bacterial aging, simulations of batch, continuous-flow, and bioreactors with recycle are used to show how population dynamics vary as function of hydraulic retention time, microbial kinetics, substrate level, and other factors that cause differential changes in the distribution of living and dead cells within the system. In summary, we show that population structures induced by birth and death (as discrete and delayed events) intrinsically create a non-linear dynamic system, implying that a true steady state can never exist in growing bacterial populations. This conclusion is discussed within the context of process stability in biotechnology.     

脑磁源的定位研究

在脑电脑磁研究中,常将大脑视为一电磁系统,利用准静态近似下的麦克斯韦方程,可以发现代表脑神经元活动的原在电流密度与脑外磁场之间呈线性关系。在高斯哭喊杨存在的情况下,采用极大似然估计理论,讨论了一种基于脑磁场时域－罕注解磁源定位问题的一般方法。球对称导体模型下的模拟计算表明,这一方法是有效的。对于考虑真实头模型下的磁源定位问题求解磁源定位,提出了一种联合使用脑磁脑电数据的近似方法。     

A linear spatio-temporal model of the light-to-bipolar cell system and its response characteristics to moving bars

A linear spatio-temporal model for the visual pathway from receptor to bipolar cell is presented. This model is based on histological and electrophysiological data obtained from previously published work. The model incorporates the salient linear spatio-temporal dynamic characteristics of the light-to-bipolar cell system, and aims at furthering our understanding of the integrated spatio-temporal response characteristics of this system. This model is used to examine the way spatial and temporal dynamic characteristics combine to form the response of a single bipolar and of a combination of two bipolars to a moving bar stimulus. A unimodal speed sensitivity curve is identified than can be used to postulate speed detection schemes based on simple thresholding operations. The dependence of this speed sensitivity curve on specific temporal and spatial parameters of the receptive field is studied, giving rise to some simple speed discrimination schemata.Dr. Curlander is currently with the Jet Propulsion Laboratory of the California Institute of Technology, Pasadena, CA91109, USA     

The locust olfactory system as a case study for modeling dynamics of neurobiological networks: from discrete time neurons to continuous time neurons

Both chaotic and periodic activities are observed in networks of the central nervous systems. We choose the locust olfactory system as a good case study to analyze the relationships between networks' structure and the types of dynamics involved in coding mechanisms. In our modeling approach, we first build a fully connected recurrent network of synchronously updated McCulloch and Pitts neurons (MC-P type). In order to measure the use of the temporal dimension in the complex spatio-temporal patterns produced by the networks, we have defined an index the Normalized Euclidian Distance NED. We find that for appropriate parameters of input and connectivity, when adding some strong connections to the initial random synaptic matrices, it was easy to get the emergence of both robust oscillations and distributed synchrony in the spatiotemporal patterns. Then, in order to validate the MC-P model as a tool for analysis for network properties, we examine the dynamic behavior of networks of continuous time model neuron (Izhikevitch Integrate and Fire model -IFI-), implementing the same network characteristics. In both models, similarly to biological PN, the activity of excitatory neurons are phase-locked to different cycles of oscillations which remind the ones of the local field potential (LFP), and nevertheless exhibit dynamic behavior complex enough to be the basis of spatio-temporal codes.     

The visual cortex produces gamma band echo in response to broadband visual flicker

The aim of this study is to uncover the network dynamics of the human visual cortex by driving it with a broadband random visual flicker. We here applied a broadband flicker (1–720 Hz) while measuring the MEG and then estimated the temporal response function (TRF) between the visual input and the MEG response. This TRF revealed an early response in the 40–60 Hz gamma range as well as in the 8–12 Hz alpha band. While the gamma band response is novel, the latter has been termed the alpha band perceptual echo. The gamma echo preceded the alpha perceptual echo. The dominant frequency of the gamma echo was subject-specific thereby reflecting the individual dynamical properties of the early visual cortex. To understand the neuronal mechanisms generating the gamma echo, we implemented a pyramidal-interneuron gamma (PING) model that produces gamma oscillations in the presence of constant input currents. Applying a broadband input current mimicking the visual stimulation allowed us to estimate TRF between the input current and the population response (akin to the local field potentials). The TRF revealed a gamma echo that was similar to the one we observed in the MEG data. Our results suggest that the visual gamma echo can be explained by the dynamics of the PING model even in the absence of sustained gamma oscillations.     

Flexibility of spatial averaging in visual perception

The classical receptive field (RF) concept-the idea that a visual neuron responds to fixed parts and properties of a stimulus-has been challenged by a series of recent physiological results. Here, we extend these findings to human vision, demonstrating that the extent of spatial averaging in contrast perception is also flexible, depending strongly on stimulus contrast and uniformity. At low contrast, spatial averaging is greatest (about 11 min of arc) within uniform regions such as edges, as expected if the relevant neurons have orientation-selective RFs. At high contrast, spatial averaging is minimal. These results can be understood if the visual system is balancing a trade-off between noise reduction, which favours large areas of averaging, and detail preservation, which favours minimal averaging. Two distinct populations of neurons with hard-wired RFs could account for our results, as could the more intriguing possibility of dynamic, contrast-dependent RFs.     

A linear model for symmetric receptive fields: implications for classification tests with flashed and moving images

The purpose of this study was to explore the effects of spatial and temporal properties on the expected responses of visual neurons that have linear receptive fields (RFs), particularly those having a mirror symmetric distribution of spatial subregions. Receptive fields that are symmetric in at least one spatial dimension occur in neurons of the retina, the lateral geniculate nucleus (LGN), and the visual cortex of mammals. Responses to flashing bars, moving bars, and moving edges were studied for different configurations of an analog RF model in which spatial and temporal aspects were varied independently. Responses of the model at intermediate stimulus speeds were found to agree with responses in the literature for X and Y units of the LGN and often for simple units of the visual cortex. In particular, having separated regions of response to light and dark edges, an identifying property of simple cells, was found to be a linear consequence of RF regions responding inversely to stimuli of opposite polarity. Model differences from responses of cortical complex units show that a linear model cannot mimic their responses, and imply that complex units employ major nonlinearities in coding image polarity (light vs dark), which signifies a nonlinearity in coding intensity. Because sudden flux changes inherent in flashing bars test mainly temporal RF properties, and slowly moving edges test mainly spatial properties, these two tests form a useful minimal set with which to describe and classify RFs. The usefulness of this set derives both from its sensitivity to spatial and temporal variables, and from the correlation between the linearity of a cell's processing of stimulus intensity and its RF classification.