Current Source Density Data Research Articles

Exploring the maximum duration of the contingent negative variation

While the contingent negative variation (CNV) has been the subject of extensive research over the last fifty years, the maximum duration during which such cortical negativity can be maintained has, to the best of our knowledge, never been systematically explored. Participants were presented with the classic S1–S2 paradigm task, where a warning stimulus (S1) acts as a cue for the appearance of an imperative stimulus (S2). A fast motor response was required upon S2 arrival. Inter-stimulus intervals (ISIs) of 2.5, 5, 7.5 and 10 s duration were presented in blocked fashion. Data was analysed using both EEG referenced to linked mastoids and the current source density (CSD) technique, which maximizes the cortical origin of the measured voltage. Mean late CNV (lCNV) amplitude was found to be significantly higher for fast reaction time (RT) trials when CSD data was split according to the median into ‘fast’ and ‘slow’ RT halves. Post-hoc comparisons showed that this RT effect was particularly strong for the 10 s condition. This may be explained by the lack of an lCNV component and thus of cortical negativity prior to S2 in the 10 s condition. Our results suggest that intervals of a duration between 7.5 and 10 s represent the upper boundary during which the lCNV component can be elicited.

Hemifield-dependent N1 and event-related theta/delta oscillations: An unbiased comparison of surface Laplacian and common EEG reference choices

Surface Laplacian methodology has been used to reduce the impact of volume conduction and arbitrary choice of EEG recording reference for the analysis of surface potentials. However, the empirical implications of employing these different transformations to the same EEG data remain obscure. This study directly compared the statistical effects of four commonly-used (nose, linked mastoids, average) or recommended (reference electrode standardization technique [REST]) references and their spherical spline current source density (CSD) transformation for a large data set stemming from a well-understood experimental manipulation. ERPs (72 sites) recorded from 130 individuals during a visual half-field paradigm with highly-controlled emotional stimuli were characterized by mid-parietooccipital N1 (125ms peak latency) and event-related synchronization (ERS) of theta/delta (160ms), which were most robust over the contralateral hemisphere. All five data transformations were rescaled to the same covariance and submitted to a single temporal or time-frequency PCA (Varimax) to yield simplified estimates of N1 or theta/delta ERS. Unbiased nonparametric permutation tests revealed that these hemifield-dependent asymmetries were by far most focal and prominent for CSD data, despite all transformations showing maximum effects at mid-parietooccipital sites. Employing smaller subsamples (signal-to-noise) or window-based ERP/ERS amplitudes did not affect these comparisons. Furthermore, correlations between N1 and theta/delta ERS at these sites were strongest for CSD and weakest for nose-referenced data. Contrary to the common notion that the spatial high pass filter properties of a surface Laplacian reduce important contributions of neuronal generators to the EEG signal, the present findings demonstrate that instead volume conduction inherent in surface potentials weakens the representation of neuronal activation patterns at scalp that directly reflect regional brain activity.

Clinical Implications of Quantitative Electroencephalography and Current Source Density in Patients with Alzheimer’s Disease

This study examined whether quantitative electroencephalography (qEEG) and current source density (CSD) can be used to evaluate symptom severity in Alzheimer's disease (AD) patients. Thirty AD patients (13 mild and 17 moderate severity) and 30 normal control (NC) subjects were recruited. The Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet and the Global Deterioration Scale were measured. qEEG and CSD data were analyzed in five frequency bands: delta (1-3Hz), theta (4-7Hz), alpha (8-12Hz), beta (13-25Hz), and gamma (30-50Hz). Compared with the NC subjects, the moderate AD patients had significantly increased theta and decreased beta power. Compared with the mild AD patients, the moderate AD patients had significantly decreased beta power. In the AD patients, the theta power was significantly correlated with a poor performance for global cognition; however, beta power was positively correlated with a good performance for global cognition, attention, memory, visuospatial function, and executive function. The CSD of the theta band in the superior temporal gyrus, transverse temporal gyrus, insula, postcentral gyrus, cuneus, and lingual gyrus was significantly different between NC subjects and moderate AD patients and between mild and moderate AD patients. The theta CSD of these regions was significantly correlated with a poor performance for global cognition, memory, visuospatial function, execution, and language. The results suggest that qEEG and the CSD of the theta and beta bands are useful biological markers in AD patients.

ANATOMICALLY-CONSTRAINED EFFECTIVE CONNECTIVITY AMONG LAYERS IN A CORTICAL COLUMN MODELED AND ESTIMATED FROM LOCAL FIELD POTENTIALS

We propose a neural mass model for anatomically-constrained effective connectivity among neuronal populations residing in four layers (L2/3, L4, L5 and L6) within a cortical column. Eight neuronal populations in a given column--an excitatory population and an inhibitory population per layer--are assumed to be coupled via effective connections of unknown strengths that need to be estimated. The effective connections are constrained to anatomical connections that have been shown to exist in previous anatomical studies. The neural input to a cortical column is directed into the two populations in L4. The anatomically-constrained effective connectivity is captured by a system of 16 stochastic differential equations. Solving these equations yields the average postsynaptic potentials and transmembrane currents generated in each population. The current source density (CSD) responses in each layer, which serve as the model observations, are equated in the model to the sum of all currents generated within that layer. The model is implemented in a continuous-discrete state-space framework, and the innovation method is used for estimating the model parameters from CSD data. To this end, local field potential (LFP) responses to forepaw stimulation were recorded in rat area S1 using multi-channel linear probes. LFPs were converted to CSD signals, which were averaged within each layer, yielding one CSD response per layer. To estimate the effective strengths of connections between all cortical layers, the model was fitted to these CSD signals. The results show that the pattern of effective interactions is strongly influenced by the pattern of strengths of the anatomical connections; however, these two patterns are not identical. The estimated anatomically-constrained effective connectivity matrix and the anatomical connectivity matrix shared five of their six strongest connections, although rankings according to connection strength differed. The strongest effective connections were from excitatory neurons in layer 4 to excitatory neurons in layer 2/3. Our study shows the feasibility of estimating anatomically-constrained effective connectivity within a cortical column, and indicates that there is a strong influence of anatomical connectivity on effective connectivity between cortical layers.

A Dynamic Causal Model of the Coupling Between Pulse Stimulation and Neural Activity

We present a dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies. Neural responses were measured in terms of local field potentials. These were converted into current source density (CSD) data, and the time series of the CSD sink was extracted to provide a time series response train. The model structure consists of three layers (approximating the responses from the brain stem to the thalamus and then the barrel cortex), and the latter two layers contain nonlinearly coupled modules of linear second-order dynamic systems. The interaction of these modules forms a nonlinear regulatory system that determines the temporal structure of the neural response amplitude for the thalamic and cortical layers. The model is based on the measured population dynamics of neurons rather than the dynamics of a single neuron and was evaluated against CSD data from experiments with varying stimulation frequency (1-40 Hz), random pulse trains, and awake and anesthetized animals. The model parameters obtained by optimization for different physiological conditions (anesthetized or awake) were significantly different. Following Friston, Mechelli, Turner, and Price (2000), this work is part of a formal mathematical system currently being developed (Zheng et al., 2005) that links stimulation to the blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal through neural activity and hemodynamic variables. The importance of the model described here is that it can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity.

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≤ r≤.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.

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.