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Traditional approaches to EEG modelling use the methods of classical physics to reconstruct scalp potentials in terms of explicit physical models of cortical neuron ensembles. The principal difficulty is that the multiplicity of cellular processes with an intricate array of deterministic and random factors prevents creation of consistent biophysical parameter sets. An original, empirically-testable solution has been recently achieved in our previous studies by a radical departure from the deterministic equations of classical physics to the probabilistic reasoning of quantum mechanics. This crucial step relocates elementary bioelectric sources of EEG signals from the cellular to the molecular level where positively and negatively ions are considered as elementary sources of electricity. The rationale is that despite dramatic differences in cellular machineries, statistical factors governed by the rules of central limit theorem produce EEG waveforms as a statistical aggregate of the synchronized activity of multiple closely-located microscale sources. Using the formalism of nonhomogeneous birth-and-death processes (BDP) the quantum models of microscale events are deduced and linked to the dynamics of macroscale EEG waveforms. This study expands these methods with new features for comprehensive analysis of event related potentials directly from single trials, i.e. the EEG segments which are closely related in timing to cognitive events. We derive a universal model of the components of single trial ERPs both in frequency and time domains. This, for the first time, enables us to quantify all significant cognitive components in single trial ERPs, providing an alternative to the traditional method of averaging. Given P300 as an important objective marker of psychiatric disorders, a methodology which reliably discloses the component compositions of this potential, may have specific diagnostic importance. In this study, reliable identification of the P3a and P3b components from an auditory oddball paradigm provided a means of differentiating borderline personality disorder from schizophrenia.

The probabilistic formalism of quantum mechanics is used to quantitatively link the electroencephalogram (EEG) with the underlying microscale activity of cortical neurons. Previous approaches applied methods of classic physics to reconstruct the EEG in terms of explicit physical models of cortical neurons and the volume conductor. However, the multiplicity of cellular processes with extremely intricate mixtures of deterministic and random factors prevented the creation of consistent biophysical parameter sets. To avoid the uncertainty surrounding the physical attributes of the neuronal ensembles, we undertake here a radical departure from deterministic equations of classical physics to the probabilistic reasoning of quantum mechanics. The crucial step is the relocation of the elementary bioelectric sources from cellular to molecular level. Using a novel method of time-frequency analysis with adaptive segmentation for digital processing of empirical EEG and single trial event related potentials (ERPs), we found universal “building blocks” of these cortical processes both in the frequency and time domains. This result is qualified as a phenomenon known in statistical physics and quantum mechanics as universality. Therationale is that despite dramatic differences in the cellular machineries, the statistical factors governed by the central limit theorem produce the EEG waveform as a statistical aggregate of the synchronized activities of large ensembles of closely located cortical neurons. Using these theoretical and empirical findings the probabilistic laws that control the microscale machinery generating the EEG are deduced.

Eyeblink electromyogram (EMG) is a noninvasive and reliable tool for evaluating information processing at different levels of the central nervous system.The recently developed method of fragmentary decompositioncreates the model of a single trial eyeblink EMG as the series of consecutive, partly overlapping components, with the generic mass potential being the basis element. Here we express this model in terms of underlying cellular processes. To our knowledge, this is the first study where the dynamics of a mass potential at global scale is deduced from a stochastic particle model of the ion movements at microscopic scale. We consider generation of the eyeblink EMG as a stimulus- induced creation of an extracellular dipole by the movements of ions at the microscopic scale. These processes are described in terms of an equivalent circuit which is composed of novel circuit elements named sourceoid, sinkoid, and dipoloid. The corresponding equations are formulated in terms of nonhomogeneous birth-and-death processes. The theory brings together the deterministic and stochastic factors underlying the genesis of eyeblink EMG with the minimum number of free parameters. No matter how complex are the particle systems, just a few global scale parameters accumulate essential aspects of microscale activities which appear as significant variables at the global scale. Numerical experiments revealed that the mass effect of multiple elementary dipoles is expected to settle down into a behavior that qualitatively remains unchanged at different levels of a volume conductor. We summarize these findings as the principle of the conservation of the mass potential distributions.

Objective: To test the hypothesis that borderline personality disorder is a manifestation of a particularly right hemispheric disturbance, involving deficient higher order inhibition, and to consider the therapeutic implications of the findings. Methods: A cohort of 17 medication free borderline patients were compared with 17 age and sex matched controls by means of a study of p3a, which reflects the activity of one of the two main generators of the P300 (P3) of the event-related-potential. P3b reflects the output of the other generator. P3a, an aspect of the attentional system, depends upon prefrontally connected neurocircuitry. P3b is underpinned by a particularly parietally connected neural system. Using an oddball paradigm, P3a was extracted from the responses to targets using a novel single trial analysis. Results: In borderline patients, over homologous electrode sites, p3a amplitudes, but not latencies, were significantly larger in the right hemisphere compared with the left. The differences were most marked fronto-centrally. No such difference was shown in the control subjects. P3a at right hemisphere sites was significantly larger in borderline compared with control patients. There was no significant difference between the groups for the left hemisphere sites. Conclusions: The abnormally large amplitudes of P3a at right hemisphere sites in borderline patients together with the failure of habituation of P3a, are consistent with deficient inhibitory activity. Discussion of the findings suggest that they may reflect impeded maturation of the fronto-medial processing systems which, it is argued, may be a consequence of the typical early environment of those with the borderline condition. This suggestion leads to a consideration of optimal therapeutic behaviour in this condition, in particular for ‘matching’ or ‘analogical’ responsiveness.

ECG frequency analysis is complicated by the fact that ECG signals are non-stationary, that is, their activity patterns change slowly or intermittently as a result of variations in a number of physiological and physical influences. Previous applications of spectral methods to the ECG analysis have identified power spectrum of the intervals between heart beats, characteristic frequencies of which belong to low frequency ranges. Here we introduce a new approach, based on the recently developed SBF algorithm of numerical Fourier transform spectroscopy, which can evaluate frequency transfer functions from electrical transients induced by the heart activity. Using this approach, we found that ECG compo- nents, induced by a heart contraction are consistent with the transient behavior of a classical underdamped harmonic oscil- lator. Identification of this model using the Bode diagram, allows us to characterize heart contractions by the novel pa- rameters: natural frequency and damping ratio of heart contraction. Characteristic natural frequency of a healthy heart is in the frequency range between 13 and 20 Hz.

The quantified analysis of the electroencephalogram (qEEG) has enabled the extraction of additional psychophysiological information from the raw EEG, but in turn has introduced a number of distortions. This study compared Dynamic Spectral Analysis (DSA), a novel and mathematically stringent technique for the evaluation of qEEG activity with conventional power spectral analysis in subjects with both first episode and chronic schizophrenia and matched controls. Advantages of the technique in the automated processing of data, rejection of artefact, avoidance of artefact introduced by the mathematical trans-formation of the data and the identification of irregular low frequency artefactual activity "pi" are discussed in detail. Using this method, the study has confirmed past observations of increased slow wave activity in schizophrenia, and identified a decrease in peak frequency in the alpha band in the subjects with chronic schizophrenia. The two clinical groups differed in mean peak frequency in the delta band with the first episode schizophrenia subjects having a raised mean peak frequency and the subjects with chronic schizophrenia having a lowered mean peak frequency. The results suggest continued change in the EEG with illness chronicity in schizophrenia. These changes were most evident in the frequency domain emphasizing the importance of routine measurement of mean band frequencies in qEEG studies.

Abstract A recently developed method of fragmentary decomposition (FD) of nonstationary physiological signals was extended to eyeblink EMG measurement to quantify all significant stimulus-induced components and identify their parameters. FD provides a representation of single-trial eyeblink EMG as a nonstationary signal with the generic mass potential (GMP) being the universal functional element. The current study uses this model-based signal-processing methodology to identify distinct stimulus-induced components of eyeblink EMG and to extract additional psychophysiological information from the eyeblink signal. Analysis of the single-trial eyeblink EMG records from 10 normal subjects showed that GMP is an adequate functional element of which an eyeblink EMG response is composed. In particular, both spontaneous and stimulus-induced single components of eyeblink EMG are produced by functionally similar mechanisms. However, we found that about 54% of GMPs are combined into complex patterns that respond differently to various experimental conditions. To typify characteristic patterns of eyeblink EMG component composition, we defined two fundamental categories of components: Complex components (CC), comprised of multiple subcomponents (GMPs), versus monolithic components (MC), involving a single GMP. Given the nonstationary character of eyeblink EMG, the stimulus-related appearance of some specific component patterns, such as MCs and CCs, is in essence a probabilistic problem. To characterize the probabilistic structure of eyeblink EMG, we introduce the stimulus dependent probability diagram (SDPD), which shows the probability of appearance of defined component patterns of EMG activity at different times after the stimulus presentation. SDPD analysis shows that the stimulus elicits strong though short-term (phasic) effects on monolithic components and moderate but long-lasting (tonic) effects on complex components.

This paper presents a new method for the identification of individual event related potential (ERP) components in both frequency and time domains. Using the similar basis function (SBF) algorithm the method provides a time to frequency transform, representing a frequency domain equivalent of the component waveform. Notable features of the SBF algorithm are that it allows for unevenly spaced sampled functions in both the time and frequency domains, and estimates of spectral densities are obtained by numerical computation of finite Fourier integrals. Application of this method to ERP data from 20 normal subjects demonstrated a similar shape of component amplitude frequency characteristics for traditional late component waveforms (N1, P2, N2 and P3). On this basis, a low-frequency band was found where the component amplitude frequency characteristic was described by a Gaussian function, while the component phase frequency characteristic was a linear function of frequency. These relationships are interpreted as frequency domain equivalents of the component. Transformed to the time domain, they provided an analytical description of the ERP as the sum of positive- and negative-going monopolar waves. The study points to similar mechanisms underlying these component waveforms, and analytically defines dynamic properties for the components both in the frequency and time domains.

Based on the vesicle hypothesis, the modes of elementary quantum-vesicle interactions have been formulated in terms of probabilities of induced and spontaneous interstate quanta transitions and generalized within the framework of the previously developed theory of the double barrier synapse. Among the three allowed states for a quantum, the transition state is a novel formulation for the fraction of immediately available quanta governed by both vesicle and presynaptic membranes. The parameters of the model were determined by fitting solutions to the experimental curves representing effects of single pulse and short train activation on transmitter release at the frog neuromuscular junction. Qualitative differences in particle physics of transmitter release found under low quantal outputs on one hand and normal transmission on the other allowed the formulation of the uncertainty hypothesis and the quantum condition of synaptic homeostasis.

A “vicious circle” hypothesis is put forward for the common kind of somatization which forms the basis of the DSM's “somatization disorder.” Two compounding mechanisms are seen to be operative: (1) a failure of higher order inhibitory systems involved in the “medial pain system”; (2) amplification of stimulus intensity produced by the effect of attention. Attentional failure is produced not only by social factors but also by failure of sensory intensity modulation consequent upon (1). The argument focuses on data from borderline patients inwhomthe unusual prominence of pain may be due, at least in part, to incompetence of the “medial pain system.” This is reflected in enlarged P3a components of the event-related potential suggesting diminished inhibitory function involving prefrontal connections. Two studies are briefly presented in summary form suggesting that somatization may be ameliorated by a form of therapy which focuses on “inner” material as a means of overcoming “stimulus entrapment.”

Fragmentary decomposition (FD) is a recently developed method of non-stationary electrophysiological signal analysis addressed to mass potentials, such as electromyogram (EMG), event-related potential (ERP), evoked potential, electroencephalogram (EEG), electroretinogram, etc. Being supported by the generally accepted physiological notion that a peak is a functionally meaningful component of a mass potential, FD provides a way to avoid averaging and, instead, quantifies the component composition of complex electrophysiological signals directly from single-trials. The major computational procedures of FD include adaptive segmentation, the frequency domain component identification, and creation of the signal model as a linear aggregation of multiple components, with the generic mass potential (GMP) being the universal component template. This paper presents an improved, high-resolution FD technique which allows the resolution of overlapping sub-components and supports each identified component by an individual model. On the basis of this methodological innovation, we define two fundamental categories of multi-peak component waveforms: complex components (CC), comprised of multiple sub-components (GMPs), versus monolithic components (MC), involving a single GMP. We show that quantification of MCs and CCs from single-trial eyeblink EMG and single-trial ERP provides a more comprehensive analysis of these signals. Given single-trial eyeblink EMG, we find that the stimulus elicits strong though short-term (phasic) effects on MCs and moderate but long-lasting (tonic) effects on CCs. A new realm of single-trial ERP quantification is possible in that the MC appears as a marker of a single cognitive variable whereas the CC appears as a marker of a series of functionally related cognitive variables. The engagement of the brain in a specific cognitive task is accompanied by an increase of CCs in single-trial ERPs, which is especially informative with respect to the P3 cognitive potential. New methodology provides evidence for the three basic types of single-trial P3 sub-components: monolithic P3a, monolithic P3b, and a complex component, P3ab, which includes both P3a and P3b as sub-components.

It is now estimated that up to one-half of attention deficit hyperactivity disorder (ADHD) children continue to manifest symptoms in adulthood. A striking discrepancy between juvenile and adult populations is the increasing proportion of females with an ADHD diagnosis. To shed light on the psychophysiological mechanisms underlying adult ADHD, electroencephalography (EEG) and electrodermal index of arousal (skin conductance level or SCL) measures were employed under conditions of eyes-closed resting activity. Quantitative EEG (QEEG) and SCL were measured simultaneously and continuously (2 min) in 35 ADHD adults (21 males, 14 females) and their age- and sex-matched controls. As a group ADHD adults were found to have EEG and SCL deviations consistent with previous adolescent and juvenile studies. However, adult males (but not females) with ADHD showed increased EEG theta activity. By contrast, adult females (but not males) with ADHD were autonomically hypo-aroused (decreased SCL). These results suggest that distinct mechanisms may underpin adult ADHD in males and females.

Via the parameter optimization method, well documented in the literature, data on the facilitated release of acetylcholine from the preganglionic nerve terminals during short trains of impulses have been quantitatively generalized within the framework of the previously developed theory of the double barrier synapse. This allowed unique transformation of the set of discrete measurements of facilitated transmitter release into continuous dependencies of facilitation on time and frequency and, subsequently, into the resonant curves having very readily interpreted computational meaning. Thus direct evidence is produced that an overall effect of facilitory action of presynaptic stimulation does indeed reflect resonant properties of the terminal in a form of the previously predicted synaptic resonance phenomenon.