Limitations in the rapid extraction of evoked potentials using parametric modeling.

The rapid extraction of variations in evoked potentials (EPs) is of great clinical importance. Parametric modeling using autoregression with an exogenous input (ARX) and robust evoked potential estimator (REPE) are commonly used methods for extracting EPs over the conventional moving time average. However, a systematic study of the efficacy of these methods, using known synthetic EPs, has not been performed. Therefore, the current study evaluates the restrictions of these methods in the presence of known and systematic variations in EP component latency and signal-to-noise ratios (SNR). In the context of rapid extraction, variations of wave V of the auditory brainstem in response to stimulus intensity were considered. While the REPE methods were better able to recover the simulated model of the EP, morphology and the latency of the ARX-estimated EPs was a closer match to the actual EP than than that of the REPE-estimated EPs. We, therefore, concluded that ARX rapid extraction would perform better with regards to the rapid tracking of latency variations. By tracking simulated and empirically induced latency variations, we conclude that rapid EP extraction using ARX modeling is only capable of extracting latency variations of an EP in relatively high SNRs and, therefore, should be used with caution in low-noise environments. In particular, it is not a suitable method for the rapid extraction of early EP components such as the auditory brainstem potential.

Modeling electrocortical activity through improved local approximations of integral neural field equations.

Neural field models of firing rate activity typically take the form of integral equations with space-dependent axonal delays. Under natural assumptions on the synaptic connectivity we show how one can derive an equivalent partial differential equation (PDE) model that properly treats the axonal delay terms of the integral formulation. Our analysis avoids the so-called long-wavelength approximation that has previously been used to formulate PDE models for neural activity in two spatial dimensions. Direct numerical simulations of this PDE model show instabilities of the homogeneous steady state that are in full agreement with a Turing instability analysis of the original integral model. We discuss the benefits of such a local model and its usefulness in modeling electrocortical activity. In particular, we are able to treat "patchy" connections, whereby a homogeneous and isotropic system is modulated in a spatially periodic fashion. In this case the emergence of a "lattice-directed" traveling wave predicted by a linear instability analysis is confirmed by the numerical simulation of an appropriate set of coupled PDEs.

Understanding the transition to seizure by modeling the epileptiform activity of general anesthetic agents.

A central difficulty in modeling epileptogenesis using biologically plausible computational and mathematical models is not the production of activity characteristic of a seizure, but rather producing it in response to specific and quantifiable physiologic change or pathologic abnormality. This is particularly problematic when it is considered that the pathophysiological genesis of most epilepsies is largely unknown. However, several volatile general anesthetic agents, whose principle targets of action are quantifiably well characterized, are also known to be proconvulsant. The authors describe recent approaches to theoretically describing the electroencephalographic effects of volatile general anesthetic agents that may be able to provide important insights into the physiologic mechanisms that underpin seizure initiation.

Modeling the effects of anesthesia on the electroencephalogram.

Changes to the electroencephalogram (EEG) observed during general anesthesia are modeled with a physiological mean field theory of electrocortical activity. To this end a parametrization of the postsynaptic impulse response is introduced which takes into account pharmacological effects of anesthetic agents on neuronal ligand-gated ionic channels. Parameter sets for this improved theory are then identified which respect known anatomical constraints and predict mean firing rates and power spectra typically encountered in human subjects. Through parallelized simulations of the eight nonlinear, two-dimensional partial differential equations on a grid representing an entire human cortex, it is demonstrated that linear approximations are sufficient for the prediction of a range of quantitative EEG variables. More than 70,000 plausible parameter sets are finally selected and subjected to a simulated induction with the stereotypical inhaled general anesthetic isoflurane. Thereby 86 parameter sets are identified that exhibit a strong "biphasic" rise in total power, a feature often observed in experiments. A sensitivity study suggests that this "biphasic" behavior is distinguishable even at low agent concentrations. Finally, our results are briefly compared with previous work by other groups and an outlook on future fits to experimental data is provided.

Evidence for synergistic modulation of early information processing by nicotinic and muscarinic receptors in humans.

Impairments in early information processing are a hallmark feature of diverse neuropsychiatric disorders including schizophrenia and Alzheimer's disease (AD). Several lines of evidence implicate a dysfunction of the cholinergic system in these disorders, particularly in AD where there is known degeneration in major cholinergic pathways. Inspection time (IT), a measure of early visual information processing speed, has been shown to be sensitive to cholinergic manipulation. The current study employed the IT task to (1) examine the independent roles of nicotinic and muscarinic receptors in modulating information processing and (2) investigate the interaction of nicotinic and muscarinic receptor systems in modulating information processing. Twelve healthy participants completed a randomized, double-blind, placebo-controlled study under four drug conditions; (1) placebo, (2) mecamylamine (15 mg; oral), (3) scopolamine (0.4 mg, s.c.), (4) mecamylamine (15 mg) + scopolamine (0.4 mg). IT measures were examined at baseline and 2.5 h post drug administration. Selective blockade of nicotinic receptors with mecamylamine did not significantly impair IT, whereas selective blockade of muscarinic receptors with scopolamine produced a significant but small impairment in IT. Combined blockade of both receptor types with scopolamine and mecamylamine produced a large impairment in IT performance. The results indicate that both nicotinic and muscarinic receptors are involved in modulating IT, and that the two systems may function synergistically to modulate early visual information processing. These findings suggest that functional abnormalities in both nicotinic and muscarinic systems may underlie deficits in early visual information processing seen in disorders such as Alzheimer's disease and schizophrenia.

Alpha rhythm emerges from large-scale networks of realistically coupled multicompartmental model cortical neurons.

Conical pyramidal and stellate neurons were simulated using the GENESIS simulation package. Model neurons were leaky integrate-and-fire and consisted of from four to nine passive compartments. Neurophysiological measurements, based on single-cell recordings and patch-clamp experiments, provided estimations for the simulation of cortical neurons: transmitter-activated conductances, passive membrane time constants and axonal delays. Network connectivity was generated using a previously described probabilistic scheme based on known cortical histology, in which the probability of connections forming between one neuron and another fell off monotonically with increasing inter-cellular separation. Simulations of up to 6400 cortical neurons, approaching the scale of an individual cortical column, confirmed previous findings with smaller networks. Limit-cycle behaviour emerged in the network, in the frequency in the range of the mammalian alpha and beta rhythms (8-20 Hz). Contrary to expectation, near-linear relationships were found between the mean soma membrane potential and and neuronal firing probability. Some of the implications for cortical information processing, in particular the dynamical interactions between the neuronal and larger scales, are discussed.

Theoretical electroencephalogram stationary spectrum for a white-noise-driven cortex: evidence for a general anesthetic-induced phase transition.

We present a model for the dynamics of a cerebral cortex in which inputs to neuronal assemblies are treated as random Gaussian fluctuations about a mean value. We incorporate the effect of general anesthetic agents on the cortex as a modulation of the inhibitory neurotransmitter rate constant. Stochastic differential equations are derived for the state variable h(e), the average excitatory soma potential, coherent fluctuations of which are believed to be the source of scalp-measured electroencephalogram (EEG) signals. Using this stochastic approach we derive a stationary (long-time limit) fluctuation spectrum for h(e). The model predicts that there will be three distinct stationary (equilibrium) regimes for cortical activity. In region I ("coma"), corresponding to a strong inhibitory anesthetic effect, h(e) is single valued, large, and negative, so that neuronal firing rates are suppressed. In region II for a zero or small anesthetic effect, h(e) can take on three values, two of which are stable; we label the stable solutions as "active" (enhanced firing) and "quiescent" (suppressed firing). For region III, corresponding to negative anesthetic (i.e., analeptic) effect, h(e) again becomes single valued, but is now small and negative, resulting in strongly elevated firing rates ("seizure"). If we identify region II as associated with the conscious state of the cortex, then the model predicts that there will be a rapid transit between the active-conscious and comatose unconscious states at a critical value of anesthetic concentration, suggesting the existence of phase transitions in the cortex. The low-frequency spectral power in the h(e) signal should increase strongly during the initial stage of anesthesia induction, before collapsing to much lower values after the transition into comatose-unconsciousness. These qualitative predictions are consistent with clinical measurements by Bührer et al. [Anaesthesiology 77, 226 (1992)], MacIver et al. [ibid. 84, 1411 (1996)], and Kuizenga et al. [Br. J. Anaesthesia 80, 725 (1998)]. This strong increase in EEG spectral power in the vicinity of the critical point is similar to the divergences observed during thermodynamic phase transitions. We show that the divergence in low-frequency power in our model is a natural consequence of the existence of turning points in the trajectory of stationary states for the cortex.

Simulation of electrocortical waves.

We report simulations of the electrocorticogram of the cat and human, based on estimates of fibre range, fibre density, axonal and dendritic delays, and cortical synaptic density. The long-range cortical connections of real cortex were simplified to couplings of symmetric density, decreasing in density with range, on a closed (toroidal) surface. Non-specific cortical activation was modelled as a diffuse global input and specific sensory input as a localised white noise input. Spectral properties of output included peak densities at the frequencies of the major cerebral rhythms, a '1/f' spectral envelope and 'shift to the right' with increasing total power as non-specific activation increased. Steady-state travelling waves with a velocity of 5-7 m/s (human) and < 1 m/s (cat) were produced. Frequency/wavenumber analysis revealed an additional class of activity with wavenumbers independent of temporal frequency. All these findings accord qualitatively and quantitatively with existing physiological results. Global resonant modes were not prominent, but the simulations obey a restricted case of the analytical results of Nunez (1994). Wave/pulse relations resemble the findings of Freeman (1975).

Computer simulation of electrocortical activity at millimetric scale.

We report a simulation of electrocortical wave activity at millimetric scale, during the "desynchronised" state. Asymmetric sigmoid pulse/wave relations, short-range excitatory/inhibitory interactions and long-range excitatory couplings of pools of cortical cells were modelled. Frequency/wave number analysis of cat electrocorticogram was compared with the results of simulation. Local standing waves, with wave numbers from about 0.25/mm to 3.3/mm independent of temporal frequency, appeared in real and simulated ECoG. These arise from interactions of excitatory and inhibitory cells and reciprocal excitation of pyramidal cells. The simulation also exhibits long wave length activity consistent with that of the real ECoG. Serial relay of excitation gives rise to travelling waves with a velocity of about 0.6 m/sec, which approximates earlier experimental estimates based on coherence. Interaction of the local and travelling waves results in group waves with high phase velocities (32 m/sec at 5 Hz, to 0.6 m/sec at 50 Hz). Such group waves have not yet been experimentally identified and would be readily confused with effects of volume conduction. However, the frequency response characteristics of the simulation, along with the group waves, may account for experimental findings of action potential correlation with local field potentials at 40-50 Hz and long-range synchronisation of action potentials.

Localization of a nonintercalative DNA binding antitumour drug in mitochondria: relationship to multidrug resistance.

The bis-(n-butyl) quaternary salt of N,N'-bis-(6-quinolyl)terephthalamide (QBQ), a fluorescent antitumour compound in the phthalanilide series which is thought to bind to the minor groove of the DNA double helix, has been investigated with respect to its in vitro activity and subcellular localization. Cultured MCF-7 human breast carcinoma cells concentrated QBQ in mitochondria by a time-dependent process which was inhibited by the ionophore valinomycin, suggesting a possible mode of antitumour action of QBQ through mitochondrial poisoning. Growth of cultured P388 murine leukaemia cells was inhibited 50% in the presence of 0.52 microM QBQ and multidrug-resistant P388 sublines developed for resistance to actinomycin D, vincristine, Adriamycin and the phthalanilide NSC 38280 were cross-resistant to the drug. Cross-resistance was reduced in all lines by the presence of 11 microM verapamil, suggesting that a transport resistance mechanism operates on QBQ. The actinomycin D-resistant P388 cell line was found to be cross-resistant to the aromatic cations rhodamine 123, which binds to proteins, and ethidium and pyronin Y, which bind intercalatively to DNA. Thus mitochondrion-specific drugs with different macromolecular binding properties all appear to be excluded by multidrug-resistant cells.