Principles for transformation of scalp EEG from potential field into source distribution.

Tracings representing simultaneously recorded values of EEG potentials from different positions on the scalp surface describe how the instantaneous potential field over the scalp surface changes with time. Each instantaneous distribution of potential can be seen as resulting from spatial integration of primary components into the potential field. These components may be derived by means of the reverse procedure: subjecting the data from the potential field to spatial differentiation as provided by the Laplacian source operator. The result is a "deblurred," i.e., a more differentiated, distribution of source components hypothetically associated with the generators of the potential field. The Laplacian source operator can be implemented as a linear combination of the instantaneous potential values, either by means of very simple electronic circuitry or in a computer. The linear combination is a standard operation in matrix algebra and is widely applied in signal processing. The formalism of matrix algebra simplifies a precise evaluation of the method in relation to conventional derivation techniques and provides further methods for analysis of the EEG data.     

Spatiotemporal analysis of brain electrical fields

Psychological studies with reaction time methodology show that there is meaningful variability in the performance of cognitive operations when responses are measured in milliseconds. Temporal precision is also required to reveal the rapid neurophysiological events in cortical networks. Sampling the brain's electrical activity at the scalp surface characterizes regional brain function with millisecond temporal resolution. The problem with electroencephalographic (EEG) data is localizing the areas of the cortex that generate the observed scalp fields. Although the eventual goal will be to specify the neural generators of the EEG, we propose that an important first step for functional studies is to examine accurate, time-dynamic maps of the brain's electrical fields at the head surface. Given an adequate spatial sampling of the surface potentials, accurate electrical studies require measures that are independent of the location of the reference sensor. The 2D Laplacian of the potential field may be used to define the local features of the scalp current flow. Because the electrical fields are dynamic, brain mapping with electrical data requires animations rather than static images. © 1994 Wiley-Liss, Inc.     

Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

OBJECTIVE: Definition of appropriate frequency bands and choice of recording reference limit the interpretability of quantitative EEG, which may be further compromised by distorted topographies or inverted hemispheric asymmetries when employing conventional (non-linear) power spectra. In contrast, fPCA factors conform to the spectral structure of empirical data, and a surface Laplacian (2-dimensional CSD) simplifies topographies by minimizing volume-conducted activity. Conciseness and interpretability of EEG and CSD fPCA solutions were compared for three common scaling methods. METHODS: Resting EEG and CSD (30 channels, nose reference, eyes open/closed) from 51 healthy and 93 clinically-depressed adults were simplified as power, log power, and amplitude spectra, and summarized using unrestricted, Varimax-rotated, covariance-based fPCA. RESULTS: Multiple alpha factors were separable from artifact and reproducible across subgroups. Power spectra produced numerous, sharply-defined factors emphasizing low frequencies. Log power spectra produced fewer, broader factors emphasizing high frequencies. Solutions for amplitude spectra showed optimal intermediate tuning, particularly when derived from CSD rather than EEG spectra. These solutions were topographically distinct, detecting multiple posterior alpha generators but excluding the dorsal surface of the frontal lobes. Instead a low alpha/theta factor showed a secondary topography along the frontal midline. CONCLUSIONS: CSD amplitude spectrum fPCA solutions provide simpler, reference-independent measures that more directly reflect neuronal activity. SIGNIFICANCE: A new quantitative EEG approach affording spectral components is developed that closely parallels the concept of an ERP component in the temporal domain.     

EEG and MEG coherence: measures of functional connectivity at distinct spatial scales of neocortical dynamics

We contrasted coherence estimates obtained with EEG, Laplacian, and MEG measures of synaptic activity using simulations with head models and simultaneous recordings of EEG and MEG. EEG coherence is often used to assess functional connectivity in human cortex. However, moderate to large EEG coherence can also arise simply by the volume conduction of current through the tissues of the head. We estimated this effect using simulated brain sources and a model of head tissues (cerebrospinal fluid (CSF), skull, and scalp) derived from MRI. We found that volume conduction can elevate EEG coherence at all frequencies for moderately separated (<10 cm) electrodes; a smaller levation is observed with widely separated (>20 cm) electrodes. This volume conduction effect was readily observed in experimental EEG at high frequencies (40-50 Hz). Cortical sources generating spontaneous EEG in this band are apparently uncorrelated. In contrast, lower frequency EEG coherence appears to result from a mixture of volume conduction effects and genuine source coherence. Surface Laplacian EEG methods minimize the effect of volume conduction on coherence estimates by emphasizing sources at smaller spatial scales than unprocessed potentials (EEG). MEG coherence estimates are inflated at all frequencies by the field spread across the large distance between sources and sensors. This effect is most apparent at sensors separated by less than 15 cm in tangential directions along a surface passing through the sensors. In comparison to long-range (>20 cm) volume conduction effects in EEG, widely spaced MEG sensors show smaller field-spread effects, which is a potentially significant advantage. However, MEG coherence estimates reflect fewer sources at a smaller scale than EEG coherence and may only partially overlap EEG coherence. EEG, Laplacian, and MEG coherence emphasize different spatial scales and orientations of sources.     

Current Source Density Profiles of Optical Recording Maps: a New Approach to the Analysis of Spatio-temporal Neural Activity Patterns

Spatio-temporal spreading of activity in the CA1 region of the rat hippocampal slice was studied by two experimental approaches. At identical locations in the tissue we measured both the extracellular field potential distribution with microelectrode recordings and the intracellular potential distribution by optical recording, using voltage-sensitive fluorescent dyes. Current source density analysis (CSD) was applied to the extracellular field potential distributions (eCSD) to enhance the spatial resolution. In order to obtain an analogous improvement for the optical recordings, we developed a new CSD transformation, which calculates the locations of the transmembrane current generators from the intracellular potential distributions (iCSD). Compared to the underlying fluorescence maps, the new iCSD profiles exhibit a considerable improvement in spatial resolution. Results can be directly interpreted in terms of physiological membrane processes, such as postsynaptic potentials and action potentials. The iCSD profiles show a surprisingly good correspondence with the classical eCSD profiles both qualitatively and quantitatively, the only difference being that cell body activity is reduced in amplitude. Thus, this new optical CSD analysis paves the way for a quantitative interpretation, rather than the hitherto predominantly qualitative interpretation of spatio-temporal activity profiles from optical recording measurements.     

Laminar cortical interactions during epileptic spikes studied with principal component analysis and physiological modeling

The direct cortical responses (DCR) to electrical stimulation and electrically evoked interictal penicillin spikes (EIIS) were studied in the same rats using current source-density (CSD) analysis to directly compare regions of neuronal depolarization and hyperpolarization in neocortex. Principal component analysis (PCA) was further used to evaluate patterns of covariance in the CSD that were characteristic of interactions between pyramidal cell populations with spatially and temporally distinct transmembrane currents. A physical model was applied to the physiological interpretation of PCA results and the optimal model parameters used to estimate neuronal generators of recorded laminar field potentials. The data suggested that the DCR and EIIS were produced by the same neuronal circuit which could be represented by two anatomically distinct populations of pyramidal cells. The first of these populations was situated in the upper and middle layers (supragranular pyramidal neurons) and formed a dipolar CSD pattern that reversed polarity in layers II and III. The second deeper population (infragranular pyramidal neurons) extended throughout most of the cortical thickness and formed a dipolar CSD pattern that reversed polarity in layer V. We propose that excitatory intracortical connections of supragranular pyramidal cells may pathologically synchronize depolarization within the epileptic focus. In this way, supragranular pyramidal cells may provide a trigger mechanism for interictal spikes in neocortex.     

Principal components analysis of Laplacian waveforms as a generic method for identifying ERP generator patterns: I. Evaluation with auditory oddball tasks.

OBJECTIVE: To evaluate the effectiveness and comparability of PCA-based simplifications of ERP waveforms versus their reference-free Laplacian transformations for separating task- and response-related ERP generator patterns during auditory oddball tasks. METHODS: Nose-referenced ERPs (31 sites total) were recorded from 66 right-handed adults during oddball tasks using syllables or tones. Response mode (left press, right press, silent count) and task was varied within subjects. Spherical spline current source density (CSD) waveforms were computed to sharpen ERP scalp topographies and eliminate volume-conducted contributions. ERP and CSD data were submitted to separate covariance-based, unrestricted temporal PCAs (Varimax) to disentangle temporally and spatially overlapping ERP and CSD components. RESULTS: Corresponding ERP and CSD factors were unambiguously related to known ERP components. For example, the dipolar organization of a central N1 was evident from factorized anterior sinks and posterior sources encompassing the Sylvian fissure. Factors associated with N2 were characterized by asymmetric frontolateral (tonal: frontotemporal R > L) and parietotemporal (phonetic: parietotemporal L > R) sinks for targets. A single ERP factor summarized parietal P3 activity, along with an anterior negativity. In contrast, two CSD factors peaking at 360 and 560 ms distinguished a parietal P3 source with an anterior sink from a centroparietal P3 source with a sharply localized Fz sink. A smaller parietal but larger left temporal P3 source was found for silent count compared to button press. Left or right press produced opposite, region-specific asymmetries originating from central sites, modulating the N2/P3 complex. CONCLUSIONS: CSD transformation is shown to be a valuable preprocessing step for PCA of ERP data, providing a unique, physiologically meaningful solution to the ubiquitous reference problem. By reducing ERP redundancy and producing sharper, simpler topographies, and without losing or distorting any effects of interest, the CSD-PCA solution replicated and extended previous task- and response-related findings. SIGNIFICANCE: Eliminating ambiguities of the recording reference, the combined CSD-PCA approach systematically bridges between montage-dependent scalp potentials and distinct, anatomically-relevant current generators, and shows promise as a comprehensive, generic strategy for ERP analysis.     

Principal components analysis of Laplacian waveforms as a generic method for identifying ERP generator patterns: II. Adequacy of low-density estimates.

OBJECTIVE: To evaluate the comparability of high- and low-density surface Laplacian estimates for determining ERP generator patterns of group data derived from a typical ERP sample size and paradigm. METHODS: High-density ERP data (129 sites) recorded from 17 adults during tonal and phonetic oddball tasks were converted to a 10-20-system EEG montage (31 sites) using spherical spline interpolations. Current source density (CSD) waveforms were computed from the high- and low-density, but otherwise identical, ERPs, and correlated at corresponding locations. CSD data were submitted to separate covariance-based, unrestricted temporal PCAs (Varimax of covariance loadings) to identify and effectively summarize temporally and spatially overlapping CSD components. Solutions were compared by correlating factor loadings and scores, and by plotting ANOVA F statistics derived from corresponding high- and low-resolution factor scores using representative sites. RESULTS: High- and low-density CSD waveforms, PCA solutions, and F statistics were remarkably similar, yielding correlations of .9 < or = r < or = .999 between waveforms, loadings, and scores for almost all comparisons at low-density locations except for low-signal CSD waveforms at occipital sites. Each of the first 10 high-density factors corresponded precisely to one factor of the first 10 low-density factors, with each 10-factor set accounting for the meaningful CSD variance (> 91.6%). CONCLUSIONS: Low-density surface Laplacian estimates were shown to be accurate approximations of high-density CSDs at these locations, which adequately and quite sufficiently summarized group data. Moreover, reasonable approximations of many high-density scalp locations were obtained for group data from interpolations of low-density data. If group findings are the primary objective, as typical for cognitive ERP research, low-resolution CSD topographies may be as efficient, given the effective spatial smoothing when averaging across subjects and/or conditions. SIGNIFICANCE: Conservative recommendations for restricting surface Laplacians to high-density recordings may not be appropriate for all ERP research applications, and should be re-evaluated considering objective, costs and benefits.     

Origins of the somatic N20 and high-frequency oscillations evoked by trigeminal stimulation in the piglets.

OBJECTIVE: In humans, the somatic evoked potentials (SEPs) and magnetic fields (SEFs) elicited by peripheral nerve stimulation contain high-frequency oscillations (HFOs) around 600 Hz superimposed on the initial cortical response N20. Responses elicited by snout stimulation in the swine also contain similar HFOs during the rising phase of the porcine N20. This study examined the generators of the N20 and HFOs in the swine. METHODS: We recorded intracortical SEPs and multi-unit activities in the sulcal area of the primary somatosensory cortex (SI) simultaneously with SEFs. The laminar profiles of the potential and current-source-density (CSD) were analyzed. RESULTS: The CSD analysis revealed that the N20 was produced by two dipolar generators, both directed toward the cortical surface. After the arrival of the initial thalamocortical volley in layer IV, the sink of the first generator shifted toward shallower layers II-III with a velocity of 0.109+/-0.038 m/s (mean+/-SD). The sink of the second generator moved to layer V. The initial thalamocortical axonal component of the HFO was produced by repolarizing current with the sink in layer IV. The CSD laminar profile of the postsynaptic component was very similar to the profile of intracortical N20. The current sink within each cycle of HFO propagated upward with a velocity of 0.633+/-0.189 m/s, indicating backpropagation. CONCLUSIONS: We propose that the N20 is generated by two sets of excitatory neurons which also produce the HFOs. Although the loci of synaptic inputs are unknown, these neurons appear to fire initially in the soma and produce backpropagating spikes toward distal apical dendrites. SIGNIFICANCE: These conclusions relate the N20 to the HFO and provide a new explanation of how the current underlying the N20 is invariantly directed toward superficial layers across species.     

Association of cortical spreading depression and seizures in patients with medically intractable epilepsy

ObjectiveMonitoring of the ultra-low frequency potentials, particularly cortical spreading depression (CSD), is excluded in epilepsy monitoring due to technical barriers imposed by the scalp ultra-low frequency electroencephalogram (EEG). As a result, clinical studies of CSD have been limited to invasive EEG. Therefore, the occurrence of CSD and its interaction with epileptiform field potentials (EFP) require investigation in epilepsy monitoring.MethodsUsing a novel AC/DC-EEG approach, the occurrence of DC potentials in patients with intractable epilepsy presenting different symptoms of aura was investigated during long-term video-EEG monitoring.ResultsVarious forms of slow potentials, including simultaneous negative direct current (DC) potentials and prolonged EFP, propagated negative DC potentials, and non-propagated single negative DC potentials were recorded from the scalp of the epileptic patients. The propagated and single negative DC potentials preceded the prolonged EFP with a time lag and seizure appeared at the final shoulder of some instances of the propagated negative DC potentials. The slow potential deflections had a high amplitude and prolonged duration and propagated slowly through the brain. The high-frequency EEG was suppressed in the vicinity of the negative DC potential propagations.ConclusionsThe study is the first to report the recording of the propagated and single negative DC potentials with EFP at the scalp of patients with intractable epilepsy. The negative DC potentials preceded the prolonged EFP and may trigger seizures. The propagated and single negative DC potentials may be considered as CSD.SignificanceRecordings of CSD may serve as diagnostic and prognostic monitoring tools in epilepsy.     

Classification of motor imagery by means of cortical current density estimation and Von Neumann entropy

The goal of the present study is to employ the source imaging methods such as cortical current density estimation for the classification of left- and right-hand motor imagery tasks, which may be used for brain-computer interface (BCI) applications. The scalp recorded EEG was first preprocessed by surface Laplacian filtering, time-frequency filtering, noise normalization and independent component analysis. Then the cortical imaging technique was used to solve the EEG inverse problem. Cortical current density distributions of left and right trials were classified from each other by exploiting the concept of Von Neumann entropy. The proposed method was tested on three human subjects (180 trials each) and a maximum accuracy of 91.5% and an average accuracy of 88% were obtained. The present results confirm the hypothesis that source analysis methods may improve accuracy for classification of motor imagery tasks. The present promising results using source analysis for classification of motor imagery enhances our ability of performing source analysis from single trial EEG data recorded on the scalp, and may have applications to improved BCI systems.     

Current source density estimation and interpolation based on the spherical harmonic Fourier expansion

A method for the spatial analysis of EEG and EP data, based on the spherical harmonic Fourier expansion (SHE) of scalp potential measurements, is described. This model provides efficient and accurate formulas for: (1) the computation of the surface Laplacian and (2) the interpolation of electrical potentials, current source densities, test statistics and other derived variables. Physiologically based simulation experiments show that the SHE method gives better estimates of the surface Laplacian than the commonly used finite difference method. Cross-validation studies for the objective comparison of different interpolation methods demonstrate the superiority of the SHE over the commonly used methods based on the weighted (inverse distance) average of the nearest three and four neighbor values.     

Cortical source analysis of resting state EEG data in children with attention deficit hyperactivity disorder

ObjectiveThis study investigated age-dependent and subtype-related alterations in electroencephalography (EEG) power spectra and current source densities (CSD) in children with attention deficit and hyperactivity disorder (ADHD).MethodsWe performed spectral and cortical source (exact low-resolution electromagnetic tomography, eLORETA) analyses using resting state EEG recordings from 40 children (8–16 years) with combined and inattentive subtypes of ADHD and 41 age-matched healthy controls (HC). Group differences in EEG spectra and CSD were investigated at each scalp location, voxel and cortical region in delta, theta, alpha and beta bands. We also explored associations between topographic changes in EEG power and CSD and age.ResultsCompared to healthy controls, combined ADHD subtype was characterized with significantly increased diffuse theta/beta power ratios (TBR) with a widespread decrease in beta CSD. Inattentive ADHD subtype presented increased TBR in all brain regions except in posterior areas with a global increase in theta source power. In both ADHD and HC, older age groups showed significantly lower delta source power and TBR and higher alpha and beta source power than younger age groups. Compared to HC, ADHD was characterized with increases in theta fronto-central and temporal source power with increasing age.ConclusionsOur results confirm that TBR can be used as a neurophysiological biomarker to differentiate ADHD from healthy children at both the source and sensor levels.SignificanceOur findings emphasize the importance of performing the source imaging analysis in order to better characterize age-related changes in resting-state EEG activity in ADHD and controls.     

Inhibitory processes in the flash evoked potential of the monkey.

Flash visual evoked potentials (VEP) and concurrent multiple unit activity (MUA) were recorded from closely spaced intracortical sites in unanesthetized monkeys before and after intracortical injection of the GABAA antagonist bicuculline. Laminar VEP profiles were subjected to current source density (CSD) analysis to localize the transmembrane current flows contributing to the generation of the field potentials. Before bicuculline, the first large VEP component, N40, was generated principally within the parvocellular thalamorecipient sublamina 4Cb. After bicuculline injection, the current sinks associated with N40 spread throughout lamina 4, consistent with a release of intracortical inhibition mediated by GABA. A subsequent component, P65, believed to represent recurrent inhibitory activity within 4Cb, was greatly diminished in size after bicuculline injection. The laminar pattern of current sources and sinks coincident with this component was more complicated after bicuculline, reflecting the summation of current flows associated with disinhibited lamina 4 activity. Bicuculline also altered the responses of neuronal elements in laminae 3 and 5, evidenced by large increases in MUA in these laminae that began approximately 50 msec after stimulation. Finally, bicuculline diminished the degree of intracortical ocular dominance, implicating GABAergic mechanisms in the maintenance and refinement of ocular input segregation within cortical columns.     

Multiple source analysis of interictal spikes: goals, requirements, and clinical value.

When evaluating interictal spikes using dipole source analysis it is important to account for multiple sources and the overlapping background EEG. Analyses of spike peaks may be modeling only propagated sources. Careful filtering of averaged spike data and multiple source analysis can provide useful information about the onset of epileptiform activity. A forward high-pass filter can help to enhance the initial spike activity during onset over the propagated activity. These points are illustrated with examples of a temporal, a parietal, and a frontal averaged spike. Multiple source analysis was applied using a genetic algorithm and a sequential strategy, in one case including a model of background alpha activity. Multiple source analysis could model sources describing the onset activity that were distinct in location and orientation from the propagated activity. In all cases, the prominent peak on the scalp was dominated by the contribution of propagated sources. Clinical interpretation benefits from an approach that combines the temporal evolution of EEG scalp topography and multiple source activities with the information from localization and orientation of equivalent dipole sources to identify the cortical generators underlying the earliest phase of interictal spikes.     

A ring-shaped distribution of dipoles as a source model of induced gamma-band activity.

As opposed to slow waves, spontaneous and stimulus-induced oscillations in the gamma-band show no polarity reversal in cortical depth, which cannot be explained by the classical equivalent current dipole model usually proposed as a model of pyramidal cell synaptic activity. Here we propose a ring-shaped distribution of dipoles as a source model for these fast oscillations. This distribution generates a field potential that does not reverse through cortical depth. Such a geometry could correspond to horizontally oriented dendritic fields. Moreover, this distribution generates a potential field, but no, or weak, magnetic field on the scalp surface, which corresponds to the observation that visually-induced gamma-band oscillations are detectable in EEG data, but not in simultaneously recorded MEG data.     

Dipole modeling of epileptic spikes can be accurate or misleading

PURPOSE: We investigated the accuracy and potential for serious error when representing cortical generators of epileptic spikes with the common single-dipole model. Spike generators were realistically simulated with cortical areas of different extents. METHODS: The source was simulated by using a patch that comprised small triangles on the cortical surface, each triangle having an elementary dipole generator with a moment corresponding to real intracerebral fields of spikes. The source-patch covered various clinically important parts of the temporal and frontal lobes, with an area ranging from 6 to 120 cm2. The scalp field was computed for each source-patch by using a realistic head model and was fitted by the single-dipole model to determine the best-fit dipole and the intracerebral distribution of residual variance (RV). Dipole modeling also was performed for the simulated scalp field with additional real EEG background. RESULTS: The RV after fitting a dipole to the scalp field without noise was at most 1.34%. Scalp spikes arising from sources of 6 cm2 were of small amplitude, and the dipoles estimated for these spikes were inconsistent. Extension of the source area was associated with increase of scalp potential amplitude, only very small increase of RV, and increased consistency of the estimated dipoles. When the source was very large, the dipoles clustered at very misleading locations. CONCLUSIONS: Pitfalls in dipole source localization are caused by the procedure of fitting the simplistic dipole model to real cortical sources with spatial extent and complex configuration.     

Comparison of data transformation procedures to enhance topographical accuracy in time-series analysis of the human EEG.

We describe a methodology to apply current source density (CSD) and minimum norm (MN) estimation as pre-processing tools for time-series analysis of single trial EEG data. The performance of these methods is compared for the case of wavelet time-frequency analysis of simulated gamma-band activity. A reasonable comparison of CSD and MN on the single trial level requires regularization such that the corresponding transformed data sets have similar signal-to-noise ratios (SNRs). For region-of-interest approaches, it should be possible to optimize the SNR for single estimates rather than for the whole distributed solution. An effective implementation of the MN method is described. Simulated data sets were created by modulating the strengths of a radial and a tangential test dipole with wavelets in the frequency range of the gamma band, superimposed with simulated spatially uncorrelated noise. The MN and CSD transformed data sets as well as the average reference (AR) representation were subjected to wavelet frequency-domain analysis, and power spectra were mapped for relevant frequency bands. For both CSD and MN, the influence of noise can be sufficiently suppressed by regularization to yield meaningful information, but only MN represents both radial and tangential dipole sources appropriately as single peaks. Therefore, when relating wavelet power spectrum topographies to their neuronal generators, MN should be preferred.     

Dynamic imaging of coherent sources

Electric source imaging allows localization of sources in the brain underlying frequency-associated EEG patterns detected on the scalp EEG. New algorithms have substantially improved the localization power of the EEG. Dynamic imaging of coherent sources (DICS) is one of these solutions. This algorithm uses a spatial filter to map power and coherence estimates of oscillatory brain activity. In this focus article, we explain the DICS method and summarize studies representing the ability of DICS to detect cortical and subcortical electric sources and neuronal networks associated with absence seizures, photoparoxysmal responses and hypsarrhythmia. By applying renormalized partial directed coherence (RPDC), the information flow between 2 sources can be described, which contributes to a better understanding of networks underlying different forms of epilepsy.     

BIOPHYSICAL MODELING OF TONIC CORTICAL ELECTRICAL ACTIVITY IN ATTENTION DEFICIT HYPERACTIVITY DISORDER

Psychophysiological theories characterize Attention Deficit Hyperactivity Disorder (ADHD) in terms of cortical hypoarousal and a lack of inhibition of irrelevant sensory input, drawing on evidence of abnormal electroencephalographic (EEG) delta–theta activity. To investigate the mechanisms underlying this disorder a biophysical model of the cortex was used to fit and replicate the EEGs from 54 ADHD adolescents and their control subjects. The EEG abnormalities in ADHD were accounted for by the model's neurophysiological parameters as follows: (i) dendritic response times were increased, (ii) intrathalamic activity involving the thalamic reticular nucleus (TRN) was increased, consistent with enhanced delta–theta activity, and (iii) intracortical activity was increased, consistent with slow wave (<1 Hz) abnormalities. The longer dendritic response time is consistent with the increase in the activity of inhibitory cells types, particularly in the TRN, and therefore reduced arousal. The increase in intracortical activity may also reflect an increase in background activity or cortical noise within neocortical circuits. In terms of neurochemistry, these findings may be accounted for by disturbances in the cholinergic and/or noradrenergic systems. To the knowledge of the authors, this is the first study to use a detailed biophysical model of the brain to elucidate the neurophysiological mechanisms underlying tonic abnormalities in ADHD.