Statistical mechanics of neocortical interactions: EEG dispersion relations

Quantum Calcium-Ion Interactions with EEG

Background: Previous papers have developed a statistical mechanics of neocortical interactions (SMNI) fit to short-term memory and EEG data. Adaptive Simulated Annealing (ASA) has been developed to perform fits to such nonlinear stochastic systems. An N-dimensional path-integral algorithm for quantum systems, qPATHINT, has been developed from classical PATHINT. Both fold short-time propagators (distributions or wave functions) over long times. Previous papers applied qPATHINT to two systems, in neocortical interactions and financial options. Objective: In this paper the quantum path-integral for Calcium ions is used to derive a closed-form analytic solution at arbitrary time that is used to calculate interactions with classical-physics SMNI interactions among scales. Using fits of this SMNI model to EEG data, including these effects, will help determine if this is a reasonable approach. Method: Methods of mathematical-physics for optimization and for path integrals in classical and quantum spaces are used for this project. Studies using supercomputer resources tested various dimensions for their scaling limits. In this paper the quantum path-integral is used to derive a closed-form analytic solution at arbitrary time that is used to calculate interactions with classical-physics SMNI interactions among scales. Results: The mathematical-physics and computer parts of the study are successful, in that there is modest improvement of cost/objective functions used to fit EEG data using these models. Conclusions: This project points to directions for more detailed calculations using more EEG data and qPATHINT at each time slice to propagate quantum calcium waves, synchronized with PATHINT propagation of classical SMNI.

Statistical mechanics of neocortical interactions: Large-scale EEG influences on molecular processes

Calculations further support the premise that large-scale synchronous firings of neurons may affect molecular processes. The context is scalp electroencephalography (EEG) during short-term memory (STM) tasks. The mechanism considered is Π=p+qA (SI units) coupling, where p is the momenta of free Ca(2+) waves, q the charge of Ca(2+) in units of the electron charge, and A the magnetic vector potential of current I from neuronal minicolumnar firings considered as wires, giving rise to EEG. Data has processed using multiple graphs to identify sections of data to which spline-Laplacian transformations are applied, to fit the statistical mechanics of neocortical interactions (SMNI) model to EEG data, sensitive to synaptic interactions subject to modification by Ca(2+) waves.

Neocortical dynamics at multiple scales: EEG standing waves, statistical mechanics, and physical analogs

The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model.

Spatial-temporal structures of human alpha rhythms: theory, microcurrent sources, multiscale measurements, and global binding of local networks

A theoretical framework supporting experimental measures of dynamic properties of human EEG is proposed with emphasis on distinct alpha rhythms. Robust relationships between measured dynamics and cognitive or behavioral conditions are reviewed, and proposed physiological bases for EEG at cellular levels are considered. Classical EEG data are interpreted in the context of a conceptual framework that distinguishes between locally and globally dominated dynamic processes, as estimated with coherence or other measures of phase synchronization. Macroscopic (scalp) potentials generated by cortical current sources are described at three spatial scales, taking advantage of the columnar structure of neocortex. New EEG data demonstrate that both globally coherent and locally dominated behavior can occur within the alpha band, depending on narrow band frequency, spatial measurement scale, and brain state. Quasi-stable alpha phase structures consistent with global standing waves are observed. At the same time, alpha and theta phase locking between cortical regions during mental calculations is demonstrated, consistent with neural network formation. The brain-binding problem is considered in the context of EEG dynamic behavior that generally exhibits both of these local and global aspects. But specific experimental designs and data analysis methods may severely bias physiological interpretations in either local or global directions.

Implications of recording strategy for estimates of neocortical dynamics with electroencephalography

Neocortical dynamics evidently involves very complex, nonlinear processes including top-down and bottom-up interactions across spatial scales. The dynamics may also be strongly influenced by global (periodic) boundary conditions. The primary experimental measure of human neocortical dynamics at short time scales ( approximately few ms) is the scalp electroencephalogram (EEG). It is shown that different recording and data analysis strategies are sensitive to different parts of the spatial spectrum. Thus experimental measures of system dynamics (e.g., correlation dimension estimates) can generally be expected to depend on experimental method. These ideas are illustrated in two ways: a large scale, quasilinear theory of neocortical dynamics in which standing wave phenomenon occur with predicted frequencies in the general range of EEG, and a relatively simple nonlinear physical system consisting of a linear string with attached nonlinear springs. The string/springs system is integrated numerically to illustrate transitions from periodic to chaotic behavior as mesoscopic nonlinear influences dominate macroscopic linear effects. The implications of these results for new theories of neocortical dynamics, experimental estimates of dynamic properties, and cognitive EEG studies are considered.

Radial coherence, wave velocity and damping of electrocortical waves

Mean squared coherence was calculated as a function of frequency (1-32 Hz) and electrode separation (1-8 mm) from 64-channel extradural arrays on occipito-parietal association cortex of cats. A 2-parameter theoretical function was then fitted to sets of pooled estimates. The theoretical function described coherences between recording sites of small separation for linear, non-dispersive, dissipative waves moving on an infinite homogeneous plane medium, and driven by spatio-temporally noisy inputs. Residuals of fit were then plotted as a function of frequency and distance, and were found to show no systematic trends with frequency, but an irregular and generally increasing relation to distance. This was the result predicted for linear non-dispersive waves on a surface actually folded, and with significant additional wave action generated between electrodes. Further recordings of coherence from more widely separated electrodes indicated that boundary conditions were absorbing or remote, rather than closed or reentrant. The phase velocity for electrocortical waves obtained from autoregression estimates of temporal damping and parameters of fit to coherence, was found in the range 0.1-0.29 m/sec, and appeared independent of the direction of electrode alignment. This compares with the velocity of 0.33 m/sec for alpha waves earlier found by Lopes da Silva and Storm van Leeuwen.

Generation of human EEG by a combination of long and short range neocortical interactions

A theory of neocortical interactions is developed involving both local delays (PSP rise and decay times) and global delays due to finite velocity of action potentials in corticocortical fibers. The theory is based on plausible assumptions regarding input/output relations in neocortical columns and realistic neural parameters. The simultaneous existence of short wavelength waves propagating away from multiple epicenters and long wavelength standing waves due to global boundary conditions is predicted. Both phenomena appear to have dominant oscillation frequencies in the general range of observed EEG phenomena in humans. A mechanism by which removal of diffuse input from the reticular formation may cause an abrupt drop in EEG frequency (as in the transition from the awake to sleeping state) is postulated.