PubMed Health⌕ Search

Biomedical subjects

P L Nunez

Publications and source records attributed to P L Nunez.

At least 19 recordsLinked to original sources
PubMed2001

Spherical harmonic decomposition applied to spatial-temporal analysis of human high-density electroencephalogram.

We demonstrate an application of spherical harmonic decomposition to the analysis of the human electroencephalogram (EEG). We implement two methods and discuss issues specific to the analysis of hemispherical, irregularly sampled data. Spatial sampling requirements and performance of the methods are quantified using simulated data. The analysis is applied to experimental EEG data, confirming earlier reports of an approximate frequency-wave-number relationship in some bands.

Biophysical Phenomena↗
PubMed2001

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.

Alpha Rhythm↗
PubMed2001

Steady state visually evoked potential (SSVEP) topography in a graded working memory task.

The steady state visually evoked potential (SSVEP) elicited by a diffuse 13-Hz visual flicker was recorded from 64 scalp sites in 30 subjects performing a low and high demand version of an object working memory task. During the perceptual component of the task, the SSVEP amplitude was reduced at left and right parieto-occipital sites. During the hold or memory component of the task, the SSVEP amplitude exhibited a load-dependent increase at frontal and occipito-parietal sites, while the SSVEP latency exhibited a load-dependent reduction at central and left frontal sites. We suggest that SSVEP amplitude changes index cortical information processing modes in that perceptual processes are associated with an SSVEP amplitude reduction, while holding information in active short-term or working memory is associated with an SSVEP amplitude increase. We also discuss changes in SSVEP amplitude and latency in terms of changes in the behavior of cortico-cortico and thalamo-cortico loops that utilize cortical layer I. Such cortico-cortico and thalamo-cortical loops are also proposed to constitute a neurophysiological mechanism for holding information in working memory.

Adult↗
PubMed2000

Toward a quantitative description of large-scale neocortical dynamic function and EEG.

A general conceptual framework for large-scale neocortical dynamics based on data from many laboratories is applied to a variety of experimental designs, spatial scales, and brain states. Partly distinct, but interacting local processes (e.g., neural networks) arise from functional segregation. Global processes arise from functional integration and can facilitate (top down) synchronous activity in remote cell groups that function simultaneously at several different spatial scales. Simultaneous local processes may help drive (bottom up) macroscopic global dynamics observed with electroencephalography (EEG) or magnetoencephalography (MEG). A local/global dynamic theory that is consistent with EEG data and the proposed conceptual framework is outlined. This theory is neutral about properties of neural networks embedded in macroscopic fields, but its global component makes several qualitative and semiquantitative predictions about EEG measures of traveling and standing wave phenomena. A more general "metatheory" suggests what large-scale quantitative theories of neocortical dynamics may be like when more accurate treatment of local and nonlinear effects is achieved. The theory describes the dynamics of excitatory and inhibitory synaptic action fields. EEG and MEG provide large-scale estimates of modulation of these synaptic fields around background levels. Brain states are determined by neuromodulatory control parameters. Purely local states are dominated by local feedback gains and rise and decay times of postsynaptic potentials. Dominant local frequencies vary with brain region. Other states are purely global, with moderate to high coherence over large distances. Multiple global mode frequencies arise from a combination of delays in corticocortical axons and neocortical boundary conditions. Global frequencies are identical in all cortical regions, but most states involve dynamic interactions between local networks and the global system. EEG frequencies may involve a "matching" of local resonant frequencies with one or more of the many, closely spaced global frequencies.

Cerebral Cortex↗
PubMed2000

On the relationship of synaptic activity to macroscopic measurements: does co-registration of EEG with fMRI make sense?

A two-scale theoretical description outlines relationships between brain current sources and the resulting extracranial electric field, recorded as EEG. Finding unknown sources of EEG, the so-called "inverse problem", is discussed in general terms, with emphasis on the fundamental non-uniqueness of inverse solutions. Hemodynamic signatures, measured with fMRI, are expressed as voxel integrals to facilitate comparisons with EEG. Two generally distinct cell groups (1 and 2), generating EEG and fMRI signals respectively, are embedded within the much broader class of synaptic action fields. Cell groups 1 and 2 may or may not overlap in specific experiments. Implications of this incomplete overlap for co-registration studies are considered. Each experimental measure of brain function is generally sensitive to a different kind of source activity and to different spatial and temporal scales. Failure to appreciate such distinctions can exacerbate conflicting views of brain function that emphasize either global integration or functional localization.

Brain↗
PubMed1999

EEG coherency II: experimental comparisons of multiple measures.

OBJECTIVE: A concentric spheres model was used in an earlier paper to estimate the effects of volume conduction, reference electrode and spatial filtering on different EEG coherence measures. EEG data are used here to verify theoretical predictions. METHODS: Three EEG data sets were: (1) 64 channel, recorded during 7 alternating periods of resting and mental calculation. (2) 128 channel, for comparison of eyes open versus eyes closed coherence. (3) 128 channel, recorded during deep sleep (stages 3 and 4) and REM. RESULTS: The directions of large scale (lobeal) coherency changes between brain states are relatively independent of coherence measure. However, coherence between specific electrode pairs is sensitive to method and frequency. Average reference and digitally linked mastoids provide reasonable semi-quantitative estimates of large-scale neocortical source coherence. Close bipolar, Laplacian, and dura image methods remove most reference electrode and volume conduction distortion, but may underestimate coherence by spatial filtering. CONCLUSION: Each EEG coherence method has its own potential sources of error and provides coherence estimates for different neural population sizes located in different locations. Thus, studies of coherence and brain state should include several different kinds of estimates to take full advantage of information in recorded signals.

Adolescent↗
PubMed1998

Spatial filtering and neocortical dynamics: estimates of EEG coherence.

The spatial statistics of scalp electroencephalogram (EEG) are usually presented as coherence in individual frequency bands. These coherences result both from correlations among neocortical sources and volume conduction through the tissues of the head. The scalp EEG is spatially low-pass filtered by the poorly conducting skull, introducing artificial correlation between the electrodes. A four concentric spheres (brain, CSF, skull, and scalp) model of the head and stochastic field theory are used here to derive an analytic estimate of the coherence at scalp electrodes due to volume conduction of uncorrelated source activity, predicting that electrodes within 10-12 cm can appear correlated. The surface Laplacian estimate of cortical surface potentials spatially bandpass filters the scalp potentials reducing this artificial coherence due to volume conduction. Examination of EEG data confirms that the coherence estimates from raw scalp potentials and Laplacians are sensitive to different spatial bandwidths and should be used in parallel in studies of neocortical dynamic function.

Algorithms↗
PubMed1997

EEG coherency. I: Statistics, reference electrode, volume conduction, Laplacians, cortical imaging, and interpretation at multiple scales.

Several methodological issues which impact experimental design and physiological interpretations in EEG coherence studies are considered, including reference electrode and volume conduction contributions to erroneous coherence estimates. A new measure, 'reduced coherency', is introduced as the difference between measured coherency and the coherency expected from uncorrelated neocortical sources, based on simulations and analytic-statistical studies with a volume conductor model. The concept of reduced coherency is shown to be in semi-quantitative agreement with experimental EEG data. The impact of volume conduction on statistical confidence intervals for coherence estimates is discussed. Conventional reference, average reference, bipolar, Laplacian, and cortical image coherencies are shown to be partly independent measures of neocortical dynamic function at different spatial scales, due to each method's unique spatial filtering of intracranial source activity.

Action Potentials↗
PubMed1996

Spatial sampling and filtering of EEG with spline laplacians to estimate cortical potentials.

The electroencephalogram (EEG) is recorded by sensors physically separated from the cortex by resistive skull tissue that smooths the potential field recorded at the scalp. This smoothing acts as a low-pass spatial filter that determines the spatial bandwidth, and thus the required spatial sampling density, of the scalp EEG. Although it is better appreciated in the time domain, the Nyquist frequency for adequate discrete sampling is evident in the spatial domain as well. A mathematical model of the low-pass spatial filtering of scalp potentials is developed, using a four concentric spheres (brain, CSF, skull, and scalp) model of the head and plausible estimates of the conductivity of each tissue layer. The surface Laplacian estimate of radial skull current density or cortical surface potential counteracts the low-pass filtering of scalp potentials by shifting the spatial spectrum of the EEG, producing a band-passed spatial signal that emphasizes local current sources. Simulations with the four spheres model and dense sensor arrays demonstrate that progressively more detail about cortical potential distribution is obtained as sampling is increased beyond 128 channels.

Cerebral Cortex↗
PubMed1994

The surface Laplacian, high resolution EEG and controversies.

The surface Laplacian estimate (i.e., current source density) as obtained with spline functions is evaluated in the context of some recent controversies concerning high resolution EEG and source localization. In simulation studies, the spline-Laplacian provides much better estimates of cortical surface potential than is obtained from raw scalp potential, provided dense electrode arrays (e.g., 64 or more electrodes) are used. Spline-Laplacians (which are relatively independent of volume conductor model) provide estimates of cortical potential distribution which are quite similar to those obtained with a cortical imaging algorithm based on a four sphere model.

Algorithms↗
PubMed1994

A theoretical and experimental study of high resolution EEG based on surface Laplacians and cortical imaging.

Two different methods to improve the spatial resolution of EEG are discussed: the surface Laplacian (e.g., current source density) and cortical imaging (e.g., spatial deconvolution). The former methods tend to be independent of head volume conductor model, whereas the latter methods are more model-dependent. Computer simulation of scalp potentials due to either a few isolated sources or 4200 distributed cortical sources and studies of actual EEG data both indicate that the two methods provide similar estimates of cortical potential distribution. Typical correlation coefficients between either spline-Laplacian or cortical image and simulated (calculated) cortical potential are in the 0.8-0.95 range, depending partly on CSF thickness. By contrast, correlation coefficients between simulated scalp and cortical potential are in the 0.4-0.5 range, suggesting that high resolution methods provide much better estimates of cortical potential than is obtained with conventional EEG. The two methods are also applied to steady-state visually evoked potentials and spontaneous EEG. Correlation coefficients obtained from real EEG data are in the same general ranges as correlations obtained from simulations. The new high resolution methods can provide a dramatic increase in the information content of EEG and appear to have widespread application in both clinical and cognitive studies.

Brain↗
PubMed1993

Comparison of high resolution EEG methods having different theoretical bases.

Mathematically simulated data is used to obtain direct comparisons of the accuracies of spline/Laplacian and cortical imaging algorithms in predicting cortical potential. Even though the two approaches have quite different theoretical bases, the two methods provide nearly identical estimates of cortical activity at scales greater than about 2 or 3 cm when 64 electrodes are used.

Brain↗
PubMed1993

High-resolution EEG using spline generated surface Laplacians on spherical and ellipsoidal surfaces.

Spline generated surface Laplacians are introduced as an effective method for estimating neocortical source activity at moderate scales. The method appears to be robust to the unavoidable perturbations of measured potentials and errors of head geometry and resistivity that are certain to occur in clinical or research settings. In particular, we have derived the surface Laplacian for general ellipsoidal surfaces in terms of the spline function. The spline-Laplacian accurately estimates isolated dipoles or distributed sources, is insensitive to subcortical sources and to sources which originate outside the boundaries of the electrode array, and acts as a bandpass spatial filter whose characteristics appear to provide a good match to the volume conduction of intracranial sources through human heads. As a result, spatial resolution is improved over that obtained with conventional EEG by at least a factor of three. This improvement, whether obtained with spline-Laplacian or model-dependent methods, is likely to have a significant impact on both medical and cognitive studies involving EEG.

Action Potentials↗
PubMed1991

Quantitative representation of the upper surface of the human head.

A three dimensional digitizer was used to locate 62 positions on an electrode cap placed on the heads of nine subjects. Nonlinear regression methods were used to obtain the best fit sphere, ellipsoid, and perturbed ellipsoid. RMS errors varied from approximately 1 cm to 2 mm, depending on subject and surface chosen. The spherical coordinates of the standard 10/20 electrodes on best fit spheres were obtained. A method to estimate ellipsoid axes using only three standard EEG head dimensions with an ordinary tape measure is derived from the data. The results have at least two potential applications: the forward/inverse problem in EEG and MEG, and the estimation of surface Laplacians from EEG data.

Electrodes↗
PubMed1991

A visual study of surface potentials and Laplacians due to distributed neocortical sources: computer simulations and evoked potentials.

A "picture book" of surface potentials, Laplacians, and magnetic fields due to distributed, neocortical sources is presented. The mathematically simulated data is based on 4200 current sources at the macrocolumn scale. Estimated scalp surface maps are based on the three-concentic spheres model of the head. Emphasis is placed on the effects of sampling with a limited number of electrodes, the choice of reference electrode, and the use of the spline Laplacian to improve spatial resolution. The spline Laplacian is applied to median and ulnar nerve somatosensory evoked potentials and to auditory evoked potentials including P300. Substantial improvement in spatial resolution over conventional methods is obtained. The implementation of practical high resolution EEG systems based on the spline Laplacian is considered.

Algorithms↗
PubMed1991

Finite-element model of the human head: scalp potentials due to dipole sources.

Three-dimensional finite-element models provide a method to study the relationship between human scalp potentials and neural current sources inside the brain. A new formulation of dipole-like current sources is developed here. Finite-element analyses based on this formulation are carried out for both a three-concentric-spheres model and a human-head model. Differences in calculated scalp potentials between these two models are studied in the context of the forward and inverse problems in EEG. The effects of the eye orbit structure on surface potential distribution are also studied.

Action Potentials↗
PubMed1991

The spline-Laplacian in clinical neurophysiology: a method to improve EEG spatial resolution.

An important goal of EEG research is to obtain practical methods to improve the spatial resolution of scalp-recorded potentials, i.e., to make surface data more accurately represent local underlying brain sources. This goal may be somewhat different from that of "localizing brain activity with EEG," since the latter approach often involves prior assumptions about the nature of sources. In this paper, we demonstrate that spline-Laplacian, a relatively new approach that can yield dramatic improvement in spatial resolution when average electrode spacing is less than about 3 cm. This approach is mostly independent of assumptions about sources and models of the head. The demonstration involves computer simulations, evoked potentials, normal spontaneous EEG, and epileptic spikes.

Arousal↗