The mescaline or strychnine spikes as a tool for physiological and pharmacological studies

The all-or-nothing spikes elicited by antidromic, afferent, or direct electrical stimulation of a cortical area treated with mescaline or strychnine were studied. These potentials are most probably originated in nonsynaptic dentritic membranes and their changes in amplitude and latency can be an index of the excitability of these structures. Several factors are considered as sources of error when measurements of such parameters are made to follow their changes in different experimental conditions. When these sources of error can be eliminated, the frequency, amplitude and latency of those spikes can be taken as an index of the variations in cortical excitability under some physiological conditions. Another use of these giant potentials can be for the study of humoral and pharmacological agents.     

On the transmission of external pressure fluctuations to the cerebrospinal fluid

A theory has been formulated to explain the manner in which external pressure fluctuations are transmitted to the cerebrospinal fluid (CSF). The theory is based upon a three-compartment model which consists of the cerebral ventricles, the basal cisterns and spinal subarachnoid space, and the cortical subarachnoid space. The external pressure disturbance is represented by a Fourier series summed over the frequency ω. The mathematical analysis leads to a time constant τ which depends upon the compliances of the spinal region and sources of external pressure fluctuations, the rate of CSF absorption and the rate of fluid transfer between compartments. For arterial pulsations where ωτ ? 1, the theory is in accord with the experimental observations that (i) the arterial and CSF pulse waves are nearly identical in shape, and (ii) the amplitude of the CSF pulse wave increases with intracranial pressure. Moreover, it predicts that the amplitude of the wave will be larger in the spinal region than in the ventricles. The theory also accounts for the observation of one per minute pulse waves observed in hydrocephalic patients with decreased absorption rates.     

Investigation of the dynamics underlying periodic complexes in the EEG

Periodic complexes (PC), occurring lateralised or diffuse, are relatively rare EEG phenomena which reflect acute severe brain disease. The pathophysiology is still incompletely understood. One hypothesis suggested by the alpha rhythm model of Lopes da Silva is that periodic complexes reflect limit cycle dynamics of cortical networks caused by excessive excitatory feedback. We examined this hypothesis by applying a recently developed technique to EEGs displaying periodic complexes and to periodic complexes generated by the model. The technique, non-linear cross prediction, characterises how well a time series can be predicted, and how much amplitude and time asymmetry is present. Amplitude and time asymmetry are indications of non-linearity. In accordance with the model, most EEG channels with PC showed clear evidence of amplitude and time asymmetry, pointing to non-linear dynamics. However, the non-linear predictability of true PC was substantially lower than that of PC generated by the model. Furthermore, no finite value for the correlation dimension could be obtained for the real EEG data, whereas the model time series had a dimension slighter higher than one, consistent with a limit cycle attractor. Thus we can conclude that PC reflect non-linear dynamics, but a limit cycle attractor is too simple an explanation. The possibility of more complex (high dimensional and spatio-temporal) non-linear dynamics should be investigated. Received: 26 February 1998 / Accepted in revised form: 24 August 1998     

Assessment of Subcortical Source Localization Using Deep Brain Activity Imaging Model with Minimum Norm Operators: A MEG Study

Subcortical structures are involved in many healthy and pathological brain processes. It is crucial for many studies to use magnetoencephalography (MEG) to assess the ability to detect subcortical generators. This study aims to assess the source localization accuracy and to compare the characteristics of three inverse operators in the specific case of subcortical generators. MEG has a low sensitivity to subcortical sources mainly because of their distance from sensors and their complex cyto-architecture. However, we show that using a realistic anatomical and electrophysiological model of deep brain activity (DBA), the sources make measurable contributions to MEG sensors signals. Furthermore, we study the point-spread and cross-talk functions of the wMNE, sLORETA and dSPM inverse operators to characterize distortions in cortical and subcortical regions and to study how noise-normalization methods can improve or bias accuracy. We then run Monte Carlo simulations with neocortical and subcortical activations. In the case of single hippocampus patch activations, the results indicate that MEG can indeed localize the generators in the head and the body of the hippocampus with good accuracy. We then tackle the question of simultaneous cortical and subcortical activations. wMNE can detect hippocampal activations that are embedded in cortical activations that have less than double their amplitude, but it does not completely correct the bias to more superficial sources. dSPM and sLORETA can still detect hippocampal activity above this threshold, but such detection might include the creation of ghost deeper sources. Finally, using the DBA model, we showed that the detection of weak thalamic modulations of ongoing brain activity is possible.     

Resolving the dynamics of EEG generators by multichannel recordings

The voltage recorded over the cortex (ECoG) or over the scalp (EEG) is generated by currents derived from many sources called “generators”. Different patterns and amplitudes are observed in aroused, sleepy, epileptic or other brain states. Differences in amplitude are generally attributed to differences in synchrony among generators. The degree of EEG synchrony is measured by the correlation between electrodes placed over different cortical regions. We present a new way to quantitatively assess the degree of synchronization of these generators via multichannel recordings. We illustrate how situations where there are several groups of generators with different inter-group and intra-group synchronies can be analyzed. Finally, we present a way to identify the organization of groups exhibiting topographic organization. Although the model presented here is highly simplified, several methods are based on averaging activity over increasingly larger areas. These types of measurements may be applied as well to EEG and ECoG recordings.     

Mechanical and biochemical modeling of cortical oscillations in spreading cells

Actomyosin-based cortical contractility is a common feature of eukaryotic cells and is involved in cell motility, cell division, and apoptosis. In nonmuscle cells, oscillations in contractility are induced by microtubule depolymerization during cell spreading. We developed an ordinary differential equation model to describe this behavior. The computational model includes 36 parameters. The values for all but two of the model parameters were taken from experimental measurements found in the literature. Using these values, we demonstrate that the model generates oscillatory behavior consistent with current experimental observations. The rhythmic behavior occurs because of the antagonistic effects of calcium-induced contractility and stretch-activated calcium channels. The model makes several experimentally testable predictions: 1), buffering intracellular calcium increases the period and decreases the amplitude of cortical oscillations; 2), increasing the number or activity of stretch activated channels leads to an increase in period and amplitude of cortical oscillations; 3), inhibiting Ca²⁺ pump activity increases the period and amplitude of oscillations; and 4), a threshold exists for the calcium concentration below which oscillations cease.     

Spatio-temporal multiple source localization by wavelet-type decomposition of evoked potentials

Scalp recording of electrical events allows evaluation of human cerebral function, but contributions of the specific brain structures generating the recorded activity are ambiguous. This problem is ill-posed and cannot be solved without auxiliary physiological knowledge about the spatio-temporal characteristics of the generators' activity. In our source localization by model-based wavelet-type decomposition, scalp recorded signals are decomposed into a combination of wavelets, each of which may describe the coherent activity of a population of neurons. We chose the Hermite functions (derived from the Gaussian function to form mono-, bi- and triphasic wave forms) as the mathematical model to describe the temporal pattern of mass neural activity.For each wavelet we solve the inverse problem for two symmetrically positioned and oriented dipoles, one of which attains zero magnitude when a single source is more suitable. We use the wavelet to model the temporal activity pattern of the symmetrical dipoles. By this we reduce the dimension of inverse problem and find a plausible solution. Once the number and the initial parameters of the sources are given, we can apply multiple source localization to correct the solution for generators with overlapping activities.Application of the procedure to subcortical and cortical components of somatosensory evoked potentials demonstrates its feasibility.     

High-throughput transfection of differentiated primary neurons from rat forebrain

Primary neurons in culture are considered to be a highly relevant model in the study of neuronal development and activity. They can be cultivated and differentiated in vitro but are difficult to transfect using conventional methods. To address this problem, a capillary electroporation system called Cellaxess Elektra was developed for efficient and reproducible transfection of primary cortical and hippocampal neurons without significant impact on cell morphology and viability. The cells are transfected in any stage of differentiation and development, directly in cell culture plates. Genetic material is delivered in situ to as many as 384 samples at a time, which enables both high-throughput and high-quality screening for hard-to-transfect primary cells, meaning that gene function can be studied on a genome-wide scale in cells previously inaccessible to genetic manipulation.     

The Opponent Channel Population Code of Sound Location Is an Efficient Representation of Natural Binaural Sounds

In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a “panoramic” code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding.     

Coherence and phase locking in the scalp EEG and between LORETA model sources, and microstates as putative mechanisms of brain temporo-spatial functional organization.

Brain electric mechanisms of temporary, functional binding between brain regions are studied using computation of scalp EEG coherence and phase locking, sensitive to time differences of few milliseconds. However, such results if computed from scalp data are ambiguous since electric sources are spatially oriented. Non-ambiguous results can be obtained using calculated time series of strength of intracerebral model sources. This is illustrated applying LORETA modeling to EEG during resting and meditation. During meditation, time series of LORETA model sources revealed a tendency to decreased left-right intracerebral coherence in the delta band, and to increased anterior-posterior intracerebral coherence in the theta band. An alternate conceptualization of functional binding is based on the observation that brain electric activity is discontinuous, i.e., that it occurs in chunks of up to about 100 ms duration that are detectable as quasi-stable scalp field configurations of brain electric activity, called microstates. Their functional significance is illustrated in spontaneous and event-related paradigms, where microstates associated with imagery- versus abstract-type mentation, or while reading positive versus negative emotion words showed clearly different regions of cortical activation in LORETA tomography. These data support the concept that complete brain functions of higher order such as a momentary thought might be incorporated in temporal chunks of processing in the range of tens to about 100 ms as quasi-stable brain states; during these time windows, subprocesses would be accepted as members of the ongoing chunk of processing.     

Giant central N20-P22 with normal area 3b N20-P20: an argument in favour of an area 3a generator of early median nerve cortical SEPs?

Generators of early cortical somatosensory evoked potentials (SEPs) still remain to be precisely localised. This gap in knowledge has often resulted in unclear and contrasting SEPs localisation in patients with focal hemispheric lesions. We recorded SEPs to median nerve stimulation in a patient with right frontal astrocytoma, using a 19-channel recording technique. After stimulation of the left median nerve, N20 amplitude was normal when recorded by the parietal electrode contralateral to the stimulation, while it was abnormally enhanced in traces obtained by the contralateral central electrode. The amplitude of the frontal P20 response was within normal limits. This finding suggests that two dipolar sources, tangential and radial to the scalp surface, respectively, contribute concomitantly to N20 generation. The possible location of the N20 radial source in area 3a is discussed. The P22 potential was also recorded with increased amplitude by the central electrode contralateral to the stimulation, while N30 amplitude was normal in frontal and central traces. We propose that the radial dipolar source of P22 response is independent from both N20 and N30 generators and can be located either in 3a or in area 4. This report illustrates the usefulness of multichannel recordings in diagnosing dysfunction of the sensorimotor cortex in focal cortical lesions.     

A method for the estimation of functional brain connectivity from time-series data

A central issue in cognitive neuroscience is which cortical areas are involved in managing information processing in a cognitive task and to understand their temporal interactions. Since the transfer of information in the form of electrical activity from one cortical region will in turn evoke electrical activity in other regions, the analysis of temporal synchronization provides a tool to understand neuronal information processing between cortical regions. We adopt a method for revealing time-dependent functional connectivity. We apply statistical analyses of phases to recover the information flow and the functional connectivity between cortical regions for high temporal resolution data. We further develop an evaluation method for these techniques based on two kinds of model networks. These networks consist of coupled Rössler attractors or of coupled stochastic Ornstein–Uhlenbeck systems. The implemented time-dependent coupling includes uni- and bi-directional connectivities as well as time delayed feedback. The synchronization dynamics of these networks are analyzed using the mean phase coherence, based on averaging over phase-differences, and the general synchronization index. The latter is based on the Shannon entropy. The combination of these with a parametric time delay forms the basis of a connectivity pattern, which includes the temporal and time lagged dynamics of the synchronization between two sources. We model and discuss potential artifacts. We find that the general phase measures are remarkably stable. They produce highly comparable results for stochastic and periodic systems. Moreover, the methods proves useful for identifying brief periods of phase coupling and delays. Therefore, we propose that the method is useful as a basis for generating potential functional connective models.     

Combining sources in stable isotope mixing models: alternative methods

Stable isotope mixing models are often used to quantify source contributions to a mixture. Examples include pollution source identification; trophic web studies; analysis of water sources for soils, plants; or water bodies, and many others. A common problem is having too many sources to allow a unique solution. We discuss two alternative procedures for addressing this problem. One option is a priori to combine sources with similar signatures so the number of sources is small enough to provide a unique solution. Aggregation should be considered only when isotopic signatures of clustered sources are not significantly different, and sources are related so the combined source group has some functional significance. For example, in a food web analysis, lumping several species within a trophic guild allows more interpretable results than lumping disparate food sources, even if they have similar isotopic signatures. One result of combining mixing model sources is increased uncertainty of the combined end-member isotopic signatures and consequently the source contribution estimates; this effect can be quantified using the IsoError model (). As an alternative to lumping sources before a mixing analysis, the IsoSource mixing model () can be used to find all feasible solutions of source contributions consistent with isotopic mass balance. While ranges of feasible contributions for each individual source can often be quite broad, contributions from functionally related groups of sources can be summed a posteriori, producing a range of solutions for the aggregate source that may be considerably narrower. A paleohuman dietary analysis example illustrates this method, which involves a terrestrial meat food source, a combination of three terrestrial plant foods, and a combination of three marine foods. In this case, a posteriori aggregation of sources allowed strong conclusions about temporal shifts in marine versus terrestrial diets that would not have otherwise been discerned.     

利用稳定氢氧同位素定量区分白刺水分来源的方法比较

水是影响植物分布的重要生态因子之一,对植物水源的研究有助于在全球变化背景下了解植物的时空分布格局.根据同位素质量守恒,利用稳定氢氧同位素可以确定植物水分来源,相关的方法也不断改进.利用三源线性混合模型、多源线性混合模型、吸水深度模型以及动态模型分别对格尔木白刺(Nitraria Tangutorum)的水分来源进行了对比研究,发现格尔木白刺主要吸收利用50-100 cm处的土壤水及地下水.在研究方法上,各模型都有自己的应用范围和局限:三源线性混合模型一般只能在植物吸收的水分来源不超过3个的情况下运行;多源线性混合模型弥补了三源线性混合模型的不足,可以同时比较多种来源水各自对白刺的贡献率及贡献范围;吸水深度模型弥补了混合模型中不能计算白刺对土壤水的平均吸水深度的缺陷;动态模型则会为未来降水格局变化对植物的时空分布的影响研究起很大作用.针对不同的适用范围,模型的选择及综合应用会更广泛.但是,该技术还存在一些不足,需要结合测定土水势,富氘水的示踪等方法来弥补.     

A corticothalamic circuit model for sound identification in complex scenes

The identification of the sound sources present in the environment is essential for the survival of many animals. However, these sounds are not presented in isolation, as natural scenes consist of a superposition of sounds originating from multiple sources. The identification of a source under these circumstances is a complex computational problem that is readily solved by most animals. We present a model of the thalamocortical circuit that performs level-invariant recognition of auditory objects in complex auditory scenes. The circuit identifies the objects present from a large dictionary of possible elements and operates reliably for real sound signals with multiple concurrently active sources. The key model assumption is that the activities of some cortical neurons encode the difference between the observed signal and an internal estimate. Reanalysis of awake auditory cortex recordings revealed neurons with patterns of activity corresponding to such an error signal.     

Stimulus Phase Locking of Cortical Oscillation for Auditory Stream Segregation in Rats

The phase of cortical oscillations contains rich information and is valuable for encoding sound stimuli. Here we hypothesized that oscillatory phase modulation, instead of amplitude modulation, is a neural correlate of auditory streaming. Our behavioral evaluation provided compelling evidences for the first time that rats are able to organize auditory stream. Local field potentials (LFPs) were investigated in the cortical layer IV or deeper in the primary auditory cortex of anesthetized rats. In response to ABA- sequences with different inter-tone intervals and frequency differences, neurometric functions were characterized with phase locking as well as the band-specific amplitude evoked by test tones. Our results demonstrated that under large frequency differences and short inter-tone intervals, the neurometric function based on stimulus phase locking in higher frequency bands, particularly the gamma band, could better describe van Noorden’s perceptual boundary than the LFP amplitude. Furthermore, the gamma-band neurometric function showed a build-up-like effect within around 3 seconds from sequence onset. These findings suggest that phase locking and amplitude have different roles in neural computation, and support our hypothesis that temporal modulation of cortical oscillations should be considered to be neurophysiological mechanisms of auditory streaming, in addition to forward suppression, tonotopic separation, and multi-second adaptation.     

Ultradian Rhythms in Arousal-The Problem of Masking

Studies utilizing widely different experimental techniques provided evidence that there are spontaneous ultradian cycles in arousal during the waking state. These comprised of cyclic fluctuations between increased and decreased sleep propensity with a periodicity of about 1.5 hr. Being of relatively low amplitude, these cycles are vulnerable to masking effects by a variety of experimental conditions. Masking can be exerted by varying the tonic level of arousal, by coexisting slow ultradian components which are particularly prominent during the second half of the day, or by some specific experimental conditions. Furthermore, increased sleepiness was shown to enhance the slow ultradian components and suppress the 1.5-hr cycles in EEG indices of arousal on the one hand, and to emphasize the 1.5-hr cycles in motor activity and reaction time performance on the other hand. Much more attention should be paid to the problem of masking of ultradian cycles in arousal. Recognizing the sources and reasons for masking will ad vance our knowledge of the characteristics of these cycles and their function.     

Wavelet decomposition of transmitted ultrasound wave through a 1-D muscle-bone system

In the attempt for using ultrasound as a diagnostic device for osteoporosis, several authors have described the result of the in vitro experiment in which ultrasound is passed through a cancellous bone specimen placed in a water tank. However, in the in vivo setting, a patient's cancellous bone is surrounded by cortical and muscle layers. This paper considers in the one-dimensional case (1) what effect the cortical bone segments surrounding the cancellous segment would have on the received signal and (2) what the received signal would be when a source and receiver are placed on opposite sides of a structure consisting of a cancellous segment surrounded by cortical and muscle layers. Mathematically this is accomplished by representing the received signal as a sum of wavelets which go through different reflection-transmission histories at the muscle-cortical bone and cortical-cancellous bone interfaces. The muscle and cortical bone are modeled as elastic materials and the cancellous bone as a poroelastic material described by the Biot-Johnson-Koplik-Dashen model. The approach presented here permits the assessment of which possible paths of transmission and reflection through the cortical-cancellous or muscle-cortical-cancellous complex will result in significant contributions to the received waveform. This piece of information can be useful for solving the inverse problem of non-destructive assessment of material properties of bone. Our methodology can be generalized to three-dimensional parallelly layered structure by first applying Fourier transform in the directions perpendicular to the transverse direction.     

A mathematical model for the dynamics of large membrane deformations of isolated fibroblasts

In this paper we develop and extend a previous model of cell deformations, initially proposed to describe the dynamical behaviour of round-shaped cells such as keratinocytes or leukocytes, in order to take into account cell pseudopodial dynamics with large amplitude membrane deformations such as those observed in fibroblasts. Beyond the simulation (from a quantitative, parametrized model) of the experimentally observed oscillatory cell deformations, a final goal of this work is to underline that a set of common assumptions regarding intracellular actin dynamics and associated cell membrane local motion allows us to describe a wide variety of cell morphologies and protrusive activity. The model proposed describes cell membrane deformations as a consequence of the endogenous cortical actin dynamics where the driving force for large-amplitude cell protrusion is provided by the coupling between F-actin polymerization and contractility of the cortical actomyosin network. Cell membrane movements then result of two competing forces acting on the membrane, namely an intracellular hydrostatic protrusive force counterbalanced by a retraction force exerted by the actin filaments of the cell cortex. Protrusion and retraction forces are moreover modulated by an additional membrane curvature stress. As a first approximation, we start by considering a heterogeneous but stationary distribution of actin along the cell periphery in order to evaluate the possible morphologies that an individual cell might adopt. Then non-stationary actin distributions are considered. The simulated dynamic behaviour of this cytomechanical model not only reproduces the small amplitude rotating waves of deformations of round-shaped cells such as keratinocytes [as proposed in the original model of Alt and Tranquillo (1995, J. Biol. Syst. 3, 905–916)] but is furthermore in very good agreement with the protrusive activity of cells such as fibroblasts, where large amplitude contracting/retracting pseudopods are more or less periodically extended in opposite directions. In addition, the biophysical and biochemical processes taken into account by the cytomechanical model are characterized by well-defined parameters which (for the majority) can be discussed with regard to experimental data obtained in various experimental situations.