Theoretical analysis of field potentials in anisotropic ensembles of neuronal elements

Alteration of Neural Network and Hippocampal Slice Activation through Exosomes Derived from 5XFAD Nasal Lavage Fluid

Exosomes, key mediators of intercellular transmission of pathogenic proteins, such as amyloid-beta and tau, significantly influence the progression and exacerbation of Alzheimer's disease (AD) pathology. Present in a variety of biological fluids, including cerebrospinal fluid, blood, saliva, and nasal lavage fluid (NLF), exosomes underscore their potential as integral mediators of AD pathology. By serving as vehicles for disease-specific molecules, exosomes could unveil valuable insights into disease identification and progression. This study emphasizes the imperative to investigate the impacts of exosomes on neural networks to enhance our comprehension of intracerebral neuronal communication and its implications for neurological disorders like AD. After harvesting exosomes derived from NLF of 5XFAD mice, we utilized a high-density multielectrode array (HD-MEA) system, the novel technology enabling concurrent recordings from thousands of neurons in primary cortical neuron cultures and organotypic hippocampal slices. The ensuing results revealed a surge in neuronal firing rates and disoriented neural connectivity, reflecting the effects provoked by pathological amyloid-beta oligomer treatment. The local field potentials in the exosome-treated hippocampal brain slices also exhibited aberrant rhythmicity, along with an elevated level of current source density. While this research is an initial exploration, it highlights the potential of exosomes in modulating neural networks under AD conditions and endorses the HD-MEA as an efficacious tool for exosome studies.

Cross-population coupling of neural activity based on Gaussian process current source densities

Because local field potentials (LFPs) arise from multiple sources in different spatial locations, they do not easily reveal coordinated activity across neural populations on a trial-to-trial basis. As we show here, however, once disparate source signals are decoupled, their trial-to-trial fluctuations become more accessible, and cross-population correlations become more apparent. To decouple sources we introduce a general framework for estimation of current source densities (CSDs). In this framework, the set of LFPs result from noise being added to the transform of the CSD by a biophysical forward model, while the CSD is considered to be the sum of a zero-mean, stationary, spatiotemporal Gaussian process, having fast and slow components, and a mean function, which is the sum of multiple time-varying functions distributed across space, each varying across trials. We derived biophysical forward models relevant to the data we analyzed. In simulation studies this approach improved identification of source signals compared to existing CSD estimation methods. Using data recorded from primate auditory cortex, we analyzed trial-to-trial fluctuations in both steady-state and task-evoked signals. We found cortical layer-specific phase coupling between two probes and showed that the same analysis applied directly to LFPs did not recover these patterns. We also found task-evoked CSDs to be correlated across probes, at specific cortical depths. Using data from Neuropixels probes in mouse visual areas, we again found evidence for depth-specific phase coupling of primary visual cortex and lateromedial area based on the CSDs.

What we can and what we cannot see with extracellular multielectrodes

Extracellular recording is an accessible technique used in animals and humans to study the brain physiology and pathology. As the number of recording channels and their density grows it is natural to ask how much improvement the additional channels bring in and how we can optimally use the new capabilities for monitoring the brain. Here we show that for any given distribution of electrodes we can establish exactly what information about current sources in the brain can be recovered and what information is strictly unobservable. We demonstrate this in the general setting of previously proposed kernel Current Source Density method and illustrate it with simplified examples as well as using evoked potentials from the barrel cortex obtained with a Neuropixels probe and with compatible model data. We show that with conceptual separation of the estimation space from experimental setup one can recover sources not accessible to standard methods.

Every set of measurements is a window into reality rendering its incomplete or distorted picture. It is often difficult to relate the obtained representation of the world to underlying ground truth. Here we show, for brain electrophysiology, for arbitrary experimental setup (distribution of electrodes), and arbitrary analytical setup (function space of current source densities), that one can identify distributions of current sources which can be recovered precisely, and those which are invisible in the system. This shows what is and what is not observable in the studied system for a given setup, allows to improve the analysis results by modifying analytical setup, and facilitates interpretation of the measured sets of LFP, ECoG and EEG recordings. In particular we show that with conceptual separation of the estimation space from experimental setup one can recover source distributions not accessible to standard methods.

Electroencephalographic Source Reconstruction by the Finite-Element Approximation of the Elliptic Cauchy Problem

OBJECTIVE

This paper develops a novel approach for fast and reliable reconstruction of EEG sources in MRI-based head models.

METHODS

The inverse EEG problem is reduced to the Cauchy problem for an elliptic partial-derivative equation. The problem is transformed into a regularized minimax problem, which is directly approximated in a finite-element space. The resulting numerical method is efficient and easy to program. It eliminates the need to solve forward problems, which can be a tedious task. The method applies to complex anatomical head models, possibly containing holes in surfaces, anisotropic conductivity, and conductivity variations inside each tissue. The method has been verified on a spherical shell model and an MRI-based head.

RESULTS

Numerical experiments indicate high accuracy of localization of brain activations (both cortical potential and current) and rapid execution time.

CONCLUSION

This study demonstrates that the proposed approach is feasible for EEG source analysis and can serve as a rapid and reliable tool for EEG source analysis.

SIGNIFICANCE

The significance of this study is that it develops a fast, accurate, and simple numerical method of EEG source analysis, applicable to almost arbitrary complex head models.

Immediate neurophysiological effects of transcranial electrical stimulation

Noninvasive brain stimulation techniques are used in experimental and clinical fields for their potential effects on brain network dynamics and behavior. Transcranial electrical stimulation (TES), including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), has gained popularity because of its convenience and potential as a chronic therapy. However, a mechanistic understanding of TES has lagged behind its widespread adoption. Here, we review data and modelling on the immediate neurophysiological effects of TES in vitro as well as in vivo in both humans and other animals. While it remains unclear how typical TES protocols affect neural activity, we propose that validated models of current flow should inform study design and artifacts should be carefully excluded during signal recording and analysis. Potential indirect effects of TES (e.g., peripheral stimulation) should be investigated in more detail and further explored in experimental designs. We also consider how novel technologies may stimulate the next generation of TES experiments and devices, thus enhancing validity, specificity, and reproducibility.

Current Source Density Analysis of Electroantennogram Recordings: A Tool for Mapping the Olfactory Response in an Insect Antenna

The set of chemosensory receptors expressed by the olfactory receptor neurons lying in an insect's antennae and maxillary palps define the ability of this insect to perceive the volatile chemicals of its environment. The main two electrophysiological methods of antennal recordings for studying the range of chemicals that activate chemosensory receptors have limitations. Single-sensillum recording (SSR) samples a subset of olfactory receptor neurons and therefore does not reveal the full capacity of an insect to perceive an odor. Electroantennography (EAG), even if less resolutive than SSRs, is sometimes preferred since it samples the activity of a large number of the olfactory receptor neurons. But, at least in flies, the amplitude of the EAG signal is not directly correlated with the degree of sensitivity of the insect to the olfactory compound. Such dual methodology was also used to study mammalian brains, and the current source density (CSD) analysis was developed to bridge the gap between the cellular and the population recordings. This paper details the use of a similar approach adapted to the study of olfactory responses within insects with bulbous antennae. The EAG was recorded at multiple antennal positions and the CSD that generates the EAG potentials were estimated. The method measures the activation of olfactory receptor neurons (ORNs) across the antennae and thus it quantifies the olfactory sensitivity of the insect. It allows a rapid mapping of olfactory responses and thus can be used to guide further SSRs or to determine that two chemicals are detected by independent ORNs. This study further explored biases resulting from a limited number of recording positions or from an approximation of the antennal geometry that should be considered for interpreting the CSD maps. It also shows that the CSD analysis of EAGs is compatible with a gas chromatograph stimulator for analyzing the response to complex odors. Finally, I discuss the origin of the EAG signal in light of the CSD theory.

Demonstrating test-retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response

Growing evidence suggests that loudness dependency of auditory evoked potentials (LDAEP) and resting EEG alpha and theta may be biological markers for predicting response to antidepressants. In spite of this promise, little is known about the joint reliability of these markers, and thus their clinical applicability. New standardized procedures were developed to improve the compatibility of data acquired with different EEG platforms, and used to examine test-retest reliability for the three electrophysiological measures selected for a multisite project-Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). Thirty-nine healthy controls across four clinical research sites were tested in two sessions separated by about 1 week. Resting EEG (eyes-open and eyes-closed conditions) was recorded and LDAEP measured using binaural tones (1000 Hz, 40 ms) at five intensities (60-100 dB SPL). Principal components analysis of current source density waveforms reduced volume conduction and provided reference-free measures of resting EEG alpha and N1 dipole activity to tones from auditory cortex. Low-resolution electromagnetic tomography (LORETA) extracted resting theta current density measures corresponding to rostral anterior cingulate (rACC), which has been implicated in treatment response. There were no significant differences in posterior alpha, N1 dipole, or rACC theta across sessions. Test-retest reliability was .84 for alpha, .87 for N1 dipole, and .70 for theta rACC current density. The demonstration of good-to-excellent reliability for these measures provides a template for future EEG/ERP studies from multiple testing sites, and an important step for evaluating them as biomarkers for predicting treatment response.

From Maxwell's equations to the theory of current-source density analysis

Despite the widespread use of current‐source density (CSD) analysis of extracellular potential recordings in the brain, the physical mechanisms responsible for the generation of the signal are still debated. While the extracellular potential is thought to be exclusively generated by the transmembrane currents, recent studies suggest that extracellular diffusive, advective and displacement currents—traditionally neglected—may also contribute considerably toward extracellular potential recordings. Here, we first justify the application of the electro‐quasistatic approximation of Maxwell's equations to describe the electromagnetic field of physiological origin. Subsequently, we perform spatial averaging of currents in neural tissue to arrive at the notion of the CSD and derive an equation relating it to the extracellular potential. We show that, in general, the extracellular potential is determined by the CSD of membrane currents as well as the gradients of the putative extracellular diffusion current. The diffusion current can contribute significantly to the extracellular potential at frequencies less than a few Hertz; in which case it must be subtracted to obtain correct CSD estimates. We also show that the advective and displacement currents in the extracellular space are negligible for physiological frequencies while, within cellular membrane, displacement current contributes toward the CSD as a capacitive current. Taken together, these findings elucidate the relationship between electric currents and the extracellular potential in brain tissue and form the necessary foundation for the analysis of extracellular recordings.

The Impact of Anisotropy on the Accuracy of Conductivity Imaging: A Quantitative Validation Study

We present a quantitative validation study to assess the accuracy of low-frequency conductivity imaging methods, based on a testing current measured using Current Density Imaging (CDI). We tested the proposed procedure to study the influence of tissue anisotropy on the accuracy of conductivity reconstruction methods, using a finite element model of anisotropic brain tissue. Simulations were carried out for three different levels of tissue anisotropy to compare the results obtained by our recently developed anisotropic conductivity method with those obtained by our well-established conductivity method that assumes isotropic conductivity. The validation results clearly show that the conductivity imaging method which takes into account tissue anisotropy yields significantly superior accuracy.

Dipolar extracellular potentials generated by axonal projections

Extracellular field potentials (EFPs) are an important source of information in neuroscience, but their physiological basis is in many cases still a matter of debate. Axonal sources are typically discounted in modeling and data analysis because their contributions are assumed to be negligible. Here, we established experimentally and theoretically that contributions of axons to EFPs can be significant. Modeling action potentials propagating along axons, we showed that EFPs were prominent in the presence of terminal zones where axons branch and terminate in close succession, as found in many brain regions. Our models predicted a dipolar far field and a polarity reversal at the center of the terminal zone. We confirmed these predictions using EFPs from the barn owl auditory brainstem where we recorded in nucleus laminaris using a multielectrode array. These results demonstrate that axonal terminal zones can produce EFPs with considerable amplitude and spatial reach.

Neurophysiological evidence for the interplay of speech segmentation and word-referent mapping during novel word learning

Learning a new language requires the identification of word units from continuous speech (the speech segmentation problem) and mapping them onto conceptual representation (the word to world mapping problem). Recent behavioral studies have revealed that the statistical properties found within and across modalities can serve as cues for both processes. However, segmentation and mapping have been largely studied separately, and thus it remains unclear whether both processes can be accomplished at the same time and if they share common neurophysiological features. To address this question, we recorded EEG of 20 adult participants during both an audio alone speech segmentation task and an audiovisual word-to-picture association task. The participants were tested for both the implicit detection of online mismatches (structural auditory and visual semantic violations) as well as for the explicit recognition of words and word-to-picture associations. The ERP results from the learning phase revealed a delayed learning-related fronto-central negativity (FN400) in the audiovisual condition compared to the audio alone condition. Interestingly, while online structural auditory violations elicited clear MMN/N200 components in the audio alone condition, visual-semantic violations induced meaning-related N400 modulations in the audiovisual condition. The present results support the idea that speech segmentation and meaning mapping can take place in parallel and act in synergy to enhance novel word learning.

Effects of Ketamine on Resting-State EEG Activity and Their Relationship to Perceptual/Dissociative Symptoms in Healthy Humans

N-methyl-D-aspartate (NMDA) receptor antagonists administered to healthy humans results in schizophrenia-like symptoms, which preclinical research suggests are due to glutamatergically altered brain oscillations. Here, we examined resting-state electroencephalographic activity in 21 healthy volunteers assessed in a placebo-controlled, double-blind, randomized study involving administration of either a saline infusion or a sub-anesthetic dose of ketamine, an NMDA receptor antagonist. Frequency-specific current source density (CSD) was assessed at sensor-level and source-level using eLORETA within regions of interest of a triple network model of schizophrenia (this model posits a dysfunctional switching between large-scale Default Mode and Central Executive networks by the monitor-controlling Salience Network). These CSDs were measured in each session along with subjective symptoms as indexed with the Clinician Administered Dissociative States Scale. Ketamine-induced CSD reductions in slow (delta/theta and alpha) and increases in fast (gamma) frequencies at scalp electrode sites were paralleled by frequency-specific CSD changes in the Default Mode, Central Executive, and Salience networks. Subjective symptoms scores were increased with ketamine and ratings of depersonalization in particular were associated with alpha CSD reductions in general and in specific regions of interest in each of the three networks. These results tentatively support the hypothesis that pathological brain oscillations associated with hypofunctional NMDA receptor activity may contribute to the emergence of the perceptual/dissociate symptoms of schizophrenia.

Laminar Profile and Physiology of the α Rhythm in Primary Visual, Auditory, and Somatosensory Regions of Neocortex

The functional significance of the α rhythm is widely debated. It has been proposed that α reflects sensory inhibition and/or a temporal sampling or "parsing" mechanism. There is also continuing disagreement over the more fundamental questions of which cortical layers generate α rhythms and whether the generation of α is equivalent across sensory systems. To address these latter questions, we analyzed laminar profiles of local field potentials (LFPs) and concomitant multiunit activity (MUA) from macaque V1, S1, and A1 during both spontaneous activity and sensory stimulation. Current source density (CSD) analysis of laminar LFP profiles revealed α current generators in the supragranular, granular, and infragranular layers. MUA phase-locked to local current source/sink configurations confirmed that α rhythms index local neuronal excitability fluctuations. CSD-defined α generators were strongest in the supragranular layers, whereas LFP α power was greatest in the infragranular layers, consistent with some of the previous reports. The discrepancy between LFP and CSD findings appears to be attributable to contamination of the infragranular LFP signal by activity that is volume-conducted from the stronger supragranular α generators. The presence of α generators across cortical depth in V1, S1, and A1 suggests the involvement of α in feedforward as well as feedback processes and is consistent with the view that α rhythms, perhaps in addition to a role in sensory inhibition, may parse sensory input streams in a way that facilitates communication across cortical areas.

SIGNIFICANCE STATEMENT

The α rhythm is thought to reflect sensory inhibition and/or a temporal parsing mechanism. Here, we address two outstanding issues: (1) whether α is a general mechanism across sensory systems and (2) which cortical layers generate α oscillations. Using intracranial recordings from macaque V1, S1, and A1, we show α band activity with a similar spectral and laminar profile in each of these sensory areas. Furthermore, α generators were present in each of the cortical layers, with a strong source in superficial layers. We argue that previous findings, locating α generators exclusively in the deeper layers, were biased because of use of less locally specific local field potential measurements. The laminar distribution of α band activity appears more complex than generally assumed.

Simplest relationship between local field potential and intracellular signals in layered neural tissue

The relationship between the extracellularly measured electric field potential resulting from synaptic activity in an ensemble of neurons and intracellular signals in these neurons is an important but still open question. Based on a model neuron with a cylindrical dendrite and lumped soma, we derive a formula that substantiates a proportionality between the local field potential and the total somatic transmembrane current that emerges from the difference between the somatic and dendritic membrane potentials. The formula is tested by intra- and extracellular recordings of evoked synaptic responses in hippocampal slices. Additionally, the contribution of different membrane currents to the field potential is demonstrated in a two-population mean-field model. Our formalism, which allows for a simple estimation of unknown dendritic currents directly from somatic measurements, provides an interpretation of the local field potential in terms of intracellularly measurable synaptic signals. It is also applicable to the study of cortical activity using two-compartment neuronal population models.

Surface Laplacians (SL) and phase properties of EEG rhythms: Simulated generators in a volume-conduction model

Surface Laplacian (SL) methods offer advantages in spectral analysis owing to the well-known implications of volume conduction. Although recognition of the superiority of SL over reference-dependent measures is widespread, well-reasoned cautions have precluded their universal adoption. Notably, the expected selectivity of SL for superficial rather than deep generators has relegated SL to the role of an add-on to conventional analyses, rather than as an independent area of inquiry, despite empirical findings supporting the consistency and replicability of physiological effects of interest. It has also been reasoned that the contrast-enhancing effects of SL necessarily make it insensitive to broadly distributed generators, including those suspected for oscillatory rhythms such as EEG alpha. These concerns are further exacerbated for phase-sensitive measures (e.g., phase-locking, coherence), where key features of physiological generators have yet to be evaluated. While the neuronal generators of empirically-derived EEG measures cannot be precisely known due to the inverse problem, simple dipole generator configurations can be simulated using a 4-sphere head model and linearly combined. We simulated subdural and deep generators and distributed dipole layers using sine and cosine waveforms, quantified at 67-scalp sites corresponding to those used in previous research. Reference-dependent (nose, average, mastoids reference) EEG and corresponding SL topographies were used to probe signal fidelity in the topography of the measured amplitude spectra, phase and coherence of sinusoidal stimuli at and between "active" recording sites. SL consistently outperformed the conventional EEG measures, indicating that continued reluctance by the research community is unfounded.

Cell type- and activity-dependent extracellular correlates of intracellular spiking

Despite decades of extracellular action potential (EAP) recordings monitoring brain activity, the biophysical origin and inherent variability of these signals remain enigmatic. We performed whole cell patch recordings of excitatory and inhibitory neurons in rat somatosensory cortex slice while positioning a silicon probe in their vicinity to concurrently record intra- and extracellular voltages for spike frequencies under 20 Hz. We characterize biophysical events and properties (intracellular spiking, extracellular resistivity, temporal jitter, etc.) related to EAP recordings at the single-neuron level in a layer-specific manner. Notably, EAP amplitude was found to decay as the inverse of distance between the soma and the recording electrode with similar (but not identical) resistivity across layers. Furthermore, we assessed a number of EAP features and their variability with spike activity: amplitude (but not temporal) features varied substantially (∼ 30-50% compared with mean) and nonmonotonically as a function of spike frequency and spike order. Such EAP variation only partly reflects intracellular somatic spike variability and points to the plethora of processes contributing to the EAP. Also, we show that the shape of the EAP waveform is qualitatively similar to the negative of the temporal derivative to the intracellular somatic voltage, as expected from theory. Finally, we tested to what extent EAPs can impact the lowpass-filtered part of extracellular recordings, the local field potential (LFP), typically associated with synaptic activity. We found that spiking of excitatory neurons can significantly impact the LFP at frequencies as low as 20 Hz. Our results question the common assertion that the LFP acts as proxy for synaptic activity.

Invariance in current dipole moment density across brain structures and species: physiological constraint for neuroimaging

Although anatomical constraints have been shown to be effective for MEG and EEG inverse solutions, there are still no effective physiological constraints. Strength of the current generator is normally described by the moment of an equivalent current dipole Q. This value is quite variable since it depends on size of active tissue. In contrast, the current dipole moment density q, defined as Q per surface area of active cortex, is independent of size of active tissue. Here we studied whether the value of q has a maximum in physiological conditions across brain structures and species. We determined the value due to the primary neuronal current (q primary) alone, correcting for distortions due to measurement conditions and secondary current sources at boundaries separating regions of differing electrical conductivities. The values were in the same range for turtle cerebellum (0.56-1.48 nAm/mm(2)), guinea pig hippocampus (0.30-1.34 nAm/mm(2)), and swine neocortex (0.18-1.63 nAm/mm(2)), rat neocortex (~2.2 nAm/mm(2)), monkey neocortex (~0.40 nAm/mm(2)) and human neocortex (0.16-0.77 nAm/mm(2)). Thus, there appears to be a maximum value across the brain structures and species (1-2 nAm/mm(2)). The empirical values closely matched the theoretical values obtained with our independently validated neural network model (1.6-2.8 nAm/mm(2) for initial spike and 0.7-3.1 nAm/mm(2) for burst), indicating that the apparent invariance is not coincidental. Our model study shows that a single maximum value may exist across a wide range of brain structures and species, varying in neuron density, due to fundamental electrical properties of neurons. The maximum value of q primary may serve as an effective physiological constraint for MEG/EEG inverse solutions.

Independent components of neural activity carry information on individual populations

Local field potential (LFP), the low-frequency part of the potential recorded extracellularly in the brain, reflects neural activity at the population level. The interpretation of LFP is complicated because it can mix activity from remote cells, on the order of millimeters from the electrode. To understand better the relation between the recordings and the local activity of cells we used a large-scale network thalamocortical model to compute simultaneous LFP, transmembrane currents, and spiking activity. We used this model to study the information contained in independent components obtained from the reconstructed Current Source Density (CSD), which smooths transmembrane currents, decomposed further with Independent Component Analysis (ICA). We found that the three most robust components matched well the activity of two dominating cell populations: superior pyramidal cells in layer 2/3 (rhythmic spiking) and tufted pyramids from layer 5 (intrinsically bursting). The pyramidal population from layer 2/3 could not be well described as a product of spatial profile and temporal activation, but by a sum of two such products which we recovered in two of the ICA components in our analysis, which correspond to the two first principal components of PCA decomposition of layer 2/3 population activity. At low noise one more cell population could be discerned but it is unlikely that it could be recovered in experiment given typical noise ranges.

Atypical mismatch negativity in response to emotional voices in people with autism spectrum conditions

Autism Spectrum Conditions (ASC) are characterized by heterogeneous impairments of social reciprocity and sensory processing. Voices, similar to faces, convey socially relevant information. Whether voice processing is selectively impaired remains undetermined. This study involved recording mismatch negativity (MMN) while presenting emotionally spoken syllables dada and acoustically matched nonvocal sounds to 20 subjects with ASC and 20 healthy matched controls. The people with ASC exhibited no MMN response to emotional syllables and reduced MMN to nonvocal sounds, indicating general impairments of affective voice and acoustic discrimination. Weaker angry MMN amplitudes were associated with more autistic traits. Receiver operator characteristic analysis revealed that angry MMN amplitudes yielded a value of 0.88 (p<.001). The results suggest that people with ASC may process emotional voices in an atypical fashion already at the automatic stage. This processing abnormality can facilitate diagnosing ASC and enable social deficits in people with ASC to be predicted.

Atypical mismatch negativity to distressful voices associated with conduct disorder symptoms

BACKGROUND

Although a general consensus holds that emotional reactivity in youth with conduct disorder (CD) symptoms arises as one of the main causes of successive aggression, it remains to be determined whether automatic emotional processing is altered in this population.

METHODS

We measured auditory event-related potentials (ERP) in 20 young offenders and 20 controls, screened for DSM-IV criteria of CD and evaluated using the youth version of Hare Psychopathy Checklist (PCL:YV), State-Trait Anxiety Inventory (STAI) and Barrett Impulsiveness Scale (BIS-11). In an oddball design, sadly or fearfully spoken 'deviant' syllables were randomly presented within a train of emotionally neutral 'standard' syllables.

RESULTS

In young offenders meeting with CD criteria, the ERP component mismatch negativity (MMN), presumed to reflect preattentive auditory change detection, was significantly stronger for fearful than sad syllables. No MMN differences for fearful versus sad syllables were observed in controls. Analyses of nonvocal deviants, matched spectrally with the fearful and sad sounds, supported our interpretation that the MMN abnormalities in juvenile offenders were related to the emotional content of sounds, instead of purely acoustic factors. Further, in the young offenders with CD symptoms, strong MMN amplitudes to fearful syllables were associated with high impulsive tendencies (PCL:YV, Factor 2). Higher trait and state anxiety, assessed by STAI, were positively correlated with P3a amplitudes to fearful and sad syllables, respectively. The differences in group-interaction MMN/P3a patterns to emotional syllables and nonvocal sounds could be speculated to suggest that there is a distinct processing route for preattentive processing of species-specific emotional information in human auditory cortices.

CONCLUSIONS

Our results suggest that youths with CD symptoms may process distressful voices in an atypical fashion already at the preattentive level. This auditory processing abnormality correlated with increased impulsivity and anxiety. Our results may help to shed light on the neural mechanisms of aggression.

Generator localization by current source density (CSD): implications of volume conduction and field closure at intracranial and scalp resolutions

The topographic ambiguity and reference-dependency that has plagued EEG/ERP research throughout its history are largely attributable to volume conduction, which may be concisely described by a vector form of Ohm's Law. This biophysical relationship is common to popular algorithms that infer neuronal generators via inverse solutions. It may be further simplified as Poisson's source equation, which identifies underlying current generators from estimates of the second spatial derivative of the field potential (Laplacian transformation). Intracranial current source density (CSD) studies have dissected the "cortical dipole" into intracortical sources and sinks, corresponding to physiologically-meaningful patterns of neuronal activity at a sublaminar resolution, much of which is locally cancelled (i.e., closed field). By virtue of the macroscopic scale of the scalp-recorded EEG, a surface Laplacian reflects the radial projections of these underlying currents, representing a unique, unambiguous measure of neuronal activity at scalp. Although the surface Laplacian requires minimal assumptions compared to complex, model-sensitive inverses, the resulting waveform topographies faithfully summarize and simplify essential constraints that must be placed on putative generators of a scalp potential topography, even if they arise from deep or partially-closed fields. CSD methods thereby provide a global empirical and biophysical context for generator localization, spanning scales from intracortical to scalp recordings.

A neurophysiological deficit in early visual processing in schizophrenia patients with auditory hallucinations

Existing 67-channel event-related potentials, obtained during recognition and working memory paradigms with words or faces, were used to examine early visual processing in schizophrenia patients prone to auditory hallucinations (AH, n = 26) or not (NH, n = 49) and healthy controls (HC, n = 46). Current source density (CSD) transforms revealed distinct, strongly left- (words) or right-lateralized (faces; N170) inferior-temporal N1 sinks (150 ms) in each group. N1 was quantified by temporal PCA of peak-adjusted CSDs. For words and faces in both paradigms, N1 was substantially reduced in AH compared with NH and HC, who did not differ from each other. The difference in N1 between AH and NH was not due to overall symptom severity or performance accuracy, with both groups showing comparable memory deficits. Our findings extend prior reports of reduced auditory N1 in AH, suggesting a broader early perceptual integration deficit that is not limited to the auditory modality.

The amplitude and timing of the BOLD signal reflects the relationship between local field potential power at different frequencies

There is growing evidence that several components of the mass neural activity contributing to the local field potential (LFP) can be partly separated by decomposing the LFP into nonoverlapping frequency bands. Although the blood oxygen level-dependent (BOLD) signal has been found to correlate preferentially with specific frequency bands of the LFP, it is still unclear whether the BOLD signal relates to the activity expressed by each LFP band independently of the others or if, instead, it also reflects specific relationships among different bands. We investigated these issues by recording, simultaneously and with high spatiotemporal resolution, BOLD signal and LFP during spontaneous activity in early visual cortices of anesthetized monkeys (Macaca mulatta). We used information theory to characterize the statistical dependency between BOLD and LFP. We found that the alpha (8-12 Hz), beta (18-30 Hz), and gamma (40-100 Hz) LFP bands were informative about the BOLD signal. In agreement with previous studies, gamma was the most informative band. Both increases and decreases in BOLD signal reliably followed increases and decreases in gamma power. However, both alpha and beta power signals carried information about BOLD that was largely complementary to that carried by gamma power. In particular, the relationship between alpha and gamma power was reflected in the amplitude of the BOLD signal, while the relationship between beta and gamma bands was reflected in the latency of BOLD with respect to significant changes in gamma power. These results lay the basis for identifying contributions of different neural pathways to cortical processing using fMRI.

How local is the local field potential?

Local field potentials (LFPs) are of growing importance in neurophysiological investigations. LFPs supplement action potential recordings by indexing activity relevant to EEG, magnetoencephalographic, and hemodynamic (fMRI) signals. Recent reports suggest that LFPs reflect activity within very small domains of several hundred micrometers. We examined this conclusion by comparing LFP, current source density (CSD), and multiunit activity (MUA) signals in macaque auditory cortex. Estimated by frequency tuning bandwidths, these signals' "listening areas" differ systematically with an order of MUA < CSD < LFP. Computational analyses confirm that observed LFPs receive local contributions. Direct measurements indicate passive spread of LFPs to sites more than a centimeter from their origins. These findings appear to be independent of the frequency content of the LFP. Our results challenge the idea that LFP recordings typically integrate over extremely circumscribed local domains. Rather, LFPs appear as a mixture of local potentials with "volume conducted" potentials from distant sites.

On the estimation of population-specific synaptic currents from laminar multielectrode recordings

Multielectrode array recordings of extracellular electrical field potentials along the depth axis of the cerebral cortex are gaining popularity as an approach for investigating the activity of cortical neuronal circuits. The low-frequency band of extracellular potential, i.e., the local field potential (LFP), is assumed to reflect synaptic activity and can be used to extract the laminar current source density (CSD) profile. However, physiological interpretation of the CSD profile is uncertain because it does not disambiguate synaptic inputs from passive return currents and does not identify population-specific contributions to the signal. These limitations prevent interpretation of the CSD in terms of synaptic functional connectivity in the columnar microcircuit. Here we present a novel anatomically informed model for decomposing the LFP signal into population-specific contributions and for estimating the corresponding activated synaptic projections. This involves a linear forward model, which predicts the population-specific laminar LFP in response to synaptic inputs applied at different positions along each population and a linear inverse model, which reconstructs laminar profiles of synaptic inputs from laminar LFP data based on the forward model. Assuming spatially smooth synaptic inputs within individual populations, the model decomposes the columnar LFP into population-specific contributions and estimates the corresponding laminar profiles of synaptic input as a function of time. It should be noted that constant synaptic currents at all positions along a neuronal population cannot be reconstructed, as this does not result in a change in extracellular potential. However, constraining the solution using a priori knowledge of the spatial distribution of synaptic connectivity provides the further advantage of estimating the strength of active synaptic projections from the columnar LFP profile thus fully specifying synaptic inputs.

Inverse current source density method in two dimensions: inferring neural activation from multielectrode recordings

The recent development of large multielectrode recording arrays has made it affordable for an increasing number of laboratories to record from multiple brain regions simultaneously. The development of analytical tools for array data, however, lags behind these technological advances in hardware. In this paper, we present a method based on forward modeling for estimating current source density from electrophysiological signals recorded on a two-dimensional grid using multi-electrode rectangular arrays. This new method, which we call two-dimensional inverse Current Source Density (iCSD 2D), is based upon and extends our previous one- and three-dimensional techniques. We test several variants of our method, both on surrogate data generated from a collection of Gaussian sources, and on model data from a population of layer 5 neocortical pyramidal neurons. We also apply the method to experimental data from the rat subiculum. The main advantages of the proposed method are the explicit specification of its assumptions, the possibility to include system-specific information as it becomes available, the ability to estimate CSD at the grid boundaries, and lower reconstruction errors when compared to the traditional approach. These features make iCSD 2D a substantial improvement over the approaches used so far and a powerful new tool for the analysis of multielectrode array data. We also provide a free GUI-based MATLAB toolbox to analyze and visualize our test data as well as user datasets.

Current source density measures of electroencephalographic alpha predict antidepressant treatment response

BACKGROUND

Despite recent success in pharmacologic treatment of depression, the inability to predict individual treatment response remains a liability. This study replicates and extends findings relating pretreatment electroencephalographic (EEG) alpha to treatment outcomes for serotonergic medications.

METHODS

Resting EEG (eyes-open and eyes-closed) was recorded from a 67-electrode montage in 41 unmedicated depressed patients and 41 healthy control subjects. Patients were tested before receiving antidepressants including a serotonergic mode of action (selective serotonin reuptake inhibitor [SSRI], serotonin and norepinephrine reuptake inhibitor, or SSRI plus norepinephrine and dopamine reuptake inhibitor). EEG was quantified by frequency principal components analysis of spectra derived from reference-free current source density (CSD) waveforms, which sharpens and simplifies EEG topographies, disentangles them from artifact, and yields measures that more closely represent underlying neuronal current generators.

RESULTS

Patients who did not respond to treatment had significantly less alpha CSD compared with responders or healthy control subjects, localizable to well-defined posterior generators. The alpha difference between responders and nonresponders was greater for eyes-closed than eyes-open conditions and was present across alpha subbands. A classification criterion based on the median alpha for healthy control subjects showed good positive predictive value (93.3) and specificity (92.3). There was no evidence of differential value for predicting response to an SSRI alone or dual treatment targeting serotonergic plus other monoamine neurotransmitters.

CONCLUSIONS

Findings confirm the value of EEG alpha amplitude as a viable predictor of antidepressant response and suggest that personalized treatments for depression may be identified using simple electrophysiologic CSD measures.

Intracellular and current source density analysis of pretectal input to the optic tectum of the frog

OBJECTIVE

Electrophysiological examination of the ipsilateral pretectotectal projection has proved that pretectal cells elicit strong suppressive responses to the ipsilateral tectum. However, the neural mechanisms underlying the contralateral pretectotectal prejection are still obscure. The present study aimed to examine the synaptic nature of pretectal nuclei and contralateral tectal cells, and to demonstrate the spatiotemporal pattern of neuronal activity in the 2 main brain structures.

METHODS

Intracellular recording and current source density (CSD) analysis were used to test the complexity of neuronal mechanism of pretectotectal information transfer.

RESULTS

The pretectal stimulation elicited only one type of response on the contralateral tectum, the inhibitory postsynaptic potential (IPSP). The majority of contra-induced IPSPs were assumed to be polysynaptically driven. In the CSD analysis, only one sink with short latency was observed in each profile. The ipsilateral projection produced a prominent monosynaptic sink in layer 8 of tectum. Recipient neurons were located in layers 6 and 7 of tectum. The result confirmed former findings from ipsilateral intracellular recordings.

CONCLUSION

These results suggest the following neuronal circuit: afferents from the pretectal nuclei broadly inhibit both tectal neuron, and since no second sink occurs in tectal layers, the pretectotectal excitatory afferents probably do not extend over the whole tectum, but are within limited state. The results of intracellular recording and CSD analysis further provide evidence of how pretectal afferent activity flows within the tectal laminae.

Field potential signature of distinct multicellular activity patterns in the mouse hippocampus

Cognitive functions go along with complex patterns of distributed activity in neuronal networks, thereby forming assemblies of selected neurons. To support memory processes, such assemblies have to be stabilized and reactivated in a highly reproducible way. The rodent hippocampus provides a well studied model system for network mechanisms underlying spatial memory formation. Assemblies of place-encoding cells are repeatedly activated during sleep-associated network states called sharp wave-ripple complexes (SPW-Rs). Behavioral studies suggest that at any time the hippocampus harbors a limited number of different assemblies that are transiently stabilized for memory consolidation. We hypothesized that the corresponding field potentials (sharp wave-ripple complexes) contain a specific signature of the underlying neuronal activity patterns. Hence, they should fall into a limited number of different waveforms. Application of unbiased sorting algorithms to sharp wave-ripple complexes in mouse hippocampal slices did indeed reveal the reliable recurrence of defined waveforms that were robust over prolonged recording periods. Single-unit discharges tended to fire selectively with certain SPW-R classes and were coupled above chance level. Thus, field SPW-Rs of different waveforms are directly related to the underlying multicellular activity patterns that recur with high fidelity. This direct relationship between the coordinated activity of distinct groups of neurons and macroscopic electrographic signals may be important for cognition-related physiological studies in humans and behaving animals.

Endogenous electric fields may guide neocortical network activity

Local field potentials and the underlying endogenous electric fields (EFs) are traditionally considered to be epiphenomena of structured neuronal network activity. Recently, however, externally applied EFs have been shown to modulate pharmacologically evoked network activity in rodent hippocampus. In contrast, very little is known about the role of endogenous EFs during physiological activity states in neocortex. Here, we used the neocortical slow oscillation in vitro as a model system to show that weak sinusoidal and naturalistic EFs enhance and entrain physiological neocortical network activity with an amplitude threshold within the range of in vivo endogenous field strengths. Modulation of network activity by positive and negative feedback fields based on the network activity in real-time provide direct evidence for a feedback loop between neuronal activity and endogenous EF. This significant susceptibility of active networks to EFs that only cause small changes in membrane potential in individual neurons suggests that endogenous EFs could guide neocortical network activity.

The effect of spatially inhomogeneous extracellular electric fields on neurons

The cooperative action of neurons and glia generates electrical fields, but their effect on individual neurons via ephaptic interactions is mostly unknown. Here, we analyze the impact of spatially inhomogeneous electric fields on the membrane potential, the induced membrane field, and the induced current source density of one-dimensional cables as well as morphologically realistic neurons and discuss how the features of the extracellular field affect these quantities. We show through simulations that endogenous fields, associated with hippocampal theta and sharp waves, can greatly affect spike timing. These findings imply that local electric fields, generated by the cooperative action of brain cells, can influence the timing of neural activity.

Novelty P3 reductions in depression: characterization using principal components analysis (PCA) of current source density (CSD) waveforms

We previously reported a novelty P3 reduction in depressed patients compared to healthy controls (n=20 per group) in a novelty oddball task using a 31-channel montage. In an independent replication and extension using a 67-channel montage (n=49 per group), reference-free current source density (CSD) waveforms were simplified and quantified by a temporal, covariance-based principal components analysis (PCA) (unrestricted Varimax rotation), yielding factor solutions consistent with other oddball tasks. A factor with a loadings peak at 343 ms summarized the target P3b source as well as a secondary midline frontocentral source for novels and targets. An earlier novelty vertex source (NVS) at 241 ms was present for novels, but not targets, and was reduced in patients. Compatible CSD-PCA findings were also confirmed for the original low-density sample. Results are consistent with a reduced novelty response in clinical depression, involving the early phase of the frontocentral novelty P3.

Classification of cortical microcircuits based on micro-electrode-array data from slices of rat barrel cortex

The bewildering complexity of cortical microcircuits at the single cell level gives rise to surprisingly robust emergent activity patterns at the level of laminar and columnar local field potentials (LFPs) in response to targeted local stimuli. Here we report the results of our multivariate data-analytic approach based on simultaneous multi-site recordings using micro-electrode-array chips for investigation of the microcircuitry of rat somatosensory (barrel) cortex. We find high repeatability of stimulus-induced responses, and typical spatial distributions of LFP responses to stimuli in supragranular, granular, and infragranular layers, where the last form a particularly distinct class. Population spikes appear to travel with about 33 cm/s from granular to infragranular layers. Responses within barrel related columns have different profiles than those in neighbouring columns to the left or interchangeably to the right. Variations between slices occur, but can be minimized by strictly obeying controlled experimental protocols. Cluster analysis on normalized recordings indicates specific spatial distributions of time series reflecting the location of sources and sinks independent of the stimulus layer. Although the precise correspondences between single cell activity and LFPs are still far from clear, a sophisticated neuroinformatics approach in combination with multi-site LFP recordings in the standardized slice preparation is suitable for comparing normal conditions to genetically or pharmacologically altered situations based on real cortical microcircuitry.

The relationship between magnetic and electrophysiological responses to complex tactile stimuli

BACKGROUND

Magnetoencephalography (MEG) has become an increasingly popular technique for non-invasively characterizing neuromagnetic field changes in the brain at a high temporal resolution. To examine the reliability of the MEG signal, we compared magnetic and electrophysiological responses to complex natural stimuli from the same animals. We examined changes in neuromagnetic fields, local field potentials (LFP) and multi-unit activity (MUA) in macaque monkey primary somatosensory cortex that were induced by varying the rate of mechanical stimulation. Stimuli were applied to the fingertips with three inter-stimulus intervals (ISIs): 0.33s, 1s and 2s.

RESULTS

Signal intensity was inversely related to the rate of stimulation, but to different degrees for each measurement method. The decrease in response at higher stimulation rates was significantly greater for MUA than LFP and MEG data, while no significant difference was observed between LFP and MEG recordings. Furthermore, response latency was the shortest for MUA and the longest for MEG data.

CONCLUSION

The MEG signal is an accurate representation of electrophysiological responses to complex natural stimuli. Further, the intensity and latency of the MEG signal were better correlated with the LFP than MUA data suggesting that the MEG signal reflects primarily synaptic currents rather than spiking activity. These differences in latency could be attributed to differences in the extent of spatial summation and/or differential laminar sensitivity.

Neuronal mechanisms of cortical alpha oscillations in awake-behaving macaques

Field potential oscillations at approximately 10 Hz (alpha rhythm) are widely noted in the visual cortices, but their physiological mechanisms and significance are poorly understood. In vitro studies have implicated pyramidal neurons in both infragranular and supragranular layers as pacemakers. The generality of these observations for the intact brain in the behaving subject is unknown. We analyzed laminar profiles of spontaneous local field potentials and multiunit activity (MUA) recorded with linear array multielectrodes from visual areas V2, V4, and inferotemporal (IT) cortex of two macaque monkeys during performance of a sensory discrimination task. Current source density (CSD) analysis was combined with CSD-MUA coherence to identify intracortical alpha current generators and their potential for alpha pacemaking. The role of each alpha current generator was further delineated by Granger causality analyses. In V2 and V4, alpha current generators were found in all layers, with the infragranular generator acting as primary local pacemaking generator. In contrast, in IT, alpha current generators were found only in supragranular and infragranular layers, with the supragranular generator acting as primary local pacemaking generator. The amplitude of alpha activity in V2 and V4 was negatively correlated with behavioral performance, whereas the opposite was true in IT. The alpha rhythm in IT thus appears to differ from that in the lower-order cortices, both in terms of its underlying physiological mechanism and its behavioral correlates. This work may help to reconcile some of the diverse findings and conclusions on the functional significance of alpha band oscillations in the visual system.

Diffusion in brain extracellular space

Diffusion in the extracellular space (ECS) of the brain is constrained by the volume fraction and the tortuosity and a modified diffusion equation represents the transport behavior of many molecules in the brain. Deviations from the equation reveal loss of molecules across the blood-brain barrier, through cellular uptake, binding, or other mechanisms. Early diffusion measurements used radiolabeled sucrose and other tracers. Presently, the real-time iontophoresis (RTI) method is employed for small ions and the integrative optical imaging (IOI) method for fluorescent macromolecules, including dextrans or proteins. Theoretical models and simulations of the ECS have explored the influence of ECS geometry, effects of dead-space microdomains, extracellular matrix, and interaction of macromolecules with ECS channels. Extensive experimental studies with the RTI method employing the cation tetramethylammonium (TMA) in normal brain tissue show that the volume fraction of the ECS typically is approximately 20% and the tortuosity is approximately 1.6 (i.e., free diffusion coefficient of TMA is reduced by 2.6), although there are regional variations. These parameters change during development and aging. Diffusion properties have been characterized in several interventions, including brain stimulation, osmotic challenge, and knockout of extracellular matrix components. Measurements have also been made during ischemia, in models of Alzheimer's and Parkinson's diseases, and in human gliomas. Overall, these studies improve our conception of ECS structure and the roles of glia and extracellular matrix in modulating the ECS microenvironment. Knowledge of ECS diffusion properties is valuable in contexts ranging from understanding extrasynaptic volume transmission to the development of paradigms for drug delivery to the brain.

Coupling between neuronal firing rate, gamma LFP, and BOLD fMRI is related to interneuronal correlations

BACKGROUND

To what extent is activity of individual neurons coupled to the local field potential (LFP) and to blood-oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI)? This issue is of high significance for understanding brain function and for relating animal studies to fMRI, yet it is still under debate.

RESULTS

Here we report data from simultaneous recordings of isolated unit activity and LFP by using multiple electrodes in the human auditory cortex. We found a wide range of coupling levels between the activity of individual neurons and gamma LFP. However, this large variability could be predominantly explained (r = 0.66) by the degree of firing-rate correlations between neighboring neurons. Importantly, this phenomenon occurred during both sensory stimulation and spontaneous activity. Concerning the coupling of neuronal activity to BOLD fMRI, we found that gamma LFP was well coupled to BOLD measured across different individuals (r = 0.62). By contrast, the coupling of single units to BOLD was highly variable and, again, tightly related to interneuronal-firing-rate correlations (r = 0.70).

CONCLUSIONS

Our results offer a resolution to a central controversy regarding the coupling between neurons, LFP, and BOLD signals by demonstrating, for the first time, that the coupling of single units to the other measures is variable yet it is tightly related to the degree of interneuronal correlations in the human auditory cortex.

Contrasting roles of neural firing rate and local field potentials in human memory

Recording the activity of neurons is a mainstay of animal memory research, while human recordings are generally limited to the activity of large ensembles of cells. The relationship between ensemble activity and neural firing rate during declarative memory processes, however, remains unclear. We recorded neurons and local field potentials (LFPs) simultaneously from the same sites in the human hippocampus and entorhinal cortex (ERC) in patients with implanted intracranial electrodes during a virtual taxi-driver task that also included a memory retrieval component. Neurons increased their firing rate in response to specific passengers or landmarks both during navigation and retrieval. Although we did not find item specificity in the broadband LFP, both theta- and gamma-band LFPs increased power to specific items on a small but significant percent of channels. These responses, however, did not correlate with item-specific neural responses. To contrast item-specific responses with process-specific responses during memory, we compared neural and LFP responses during encoding (navigation) and retrieval (associative and item-specific recognition). A subset of neurons also altered firing rates nonspecifically while subjects viewed items during encoding. Interestingly, LFPs in the hippocampus and ERC increased in power nonspecifically while subjects viewed items during retrieval, more often during associative than item-recognition. Furthermore, we found no correlation between neural firing rate and broadband, theta-band, and gamma-band LFPs during process-specific responses. Our findings suggest that neuronal firing and ensemble activity can be dissociated during encoding, item-maintenance, and retrieval in the human hippocampal area, likely relating to functional properties unique to this region.

Reference-independent ERP old/new effects of auditory and visual word recognition memory: Joint extraction of stimulus- and response-locked neuronal generator patterns

To clarify polarity, topography, and time course of recognition memory ERP old/new effects during matched visual and auditory continuous word recognition tasks, unrestricted temporal PCA jointly analyzed stimulus- and response-locked, reference-free current source densities (31-channel, N=40). Randomization tests provided unbiased statistics for complete factor topographies. Old/new left parietal source effects were complemented by lateral frontocentral sink effects in both modalities, overlapping modality-specific P3 sources 160 ms preresponse. A mid-frontal sink 45 ms postresponse terminated the frontoparietal generator pattern, showed old/new effects consistent with bilateral activation of anterior cingulate and SMA, and preceded similar activity extending posteriorly along the longitudinal fissure. These methods separated old/new stimulus source (preresponse) and response sink (postresponse) effects from motor and modality-specific ERPs.

Current source density analysis of contra- and ipsilateral isthmotectal connections of the frog

The nucleus isthmi (NI) of the frog receives input from the ipsilateral optic tectum and projects back to both optic tecta. After ablation of NI, frogs display no visually elicited prey-catching or threat avoidance behavior. Neural mechanisms that underlie the loss of such important behavior have not been solved. Electrophysiological examination of the contralateral isthmotectal projection has proved that it contributes to binocular vision. On the other hand, there are very few physiological investigations of the ipsilateral isthmotectal projection. In this study, current source density (CSD) analysis was applied to contra- and ipsilateral isthmotectal projections. The contralateral projection produced monosynaptic sinks in superficial layers and in layer 8. The results confirmed former findings obtained by single unit recordings. The ipsilateral projection elicited a prominent monosynaptic sink in layer 8. Recipient neurons were located in layers 6–7. These results, combined with those from the former intracellular study, led to the following neuronal circuit. Afferents from the ipsilateral NI inhibit non-efferent pear shaped neurons in the superficial layers, and strongly excite large ganglionic neurons projecting to the descending motor regions. Thus feedback to the output neurons strengthens the visually elicited responses.

fMRI MODELS OF DENDRITIC AND ASTROCYTIC NETWORKS

In order to elucidate the relationships between hierarchical structures within the neocortical neuropil and the information carried by an ensemble of neurons encompassing a single voxel, it is essential to predict through volume conductor modeling LFPs representing average extracellular potentials, which are expressed in terms of interstitial potentials of individual cells in networks of gap-junctionally connected astrocytes and synaptically connected neurons. These relationships have been provided and can then be used to investigate how the underlying neuronal population activity can be inferred from the measurement of the BOLD signal through electrovascular coupling mechanisms across the blood-brain barrier. The importance of both synaptic and extrasynaptic transmission as the basis of electrophysiological indices triggering vascular responses between dendritic and astrocytic networks, and sequential configurations of firing patterns in composite neural networks is emphasized. The purpose of this review is to show how fMRI data may be used to draw conclusions about the information transmitted by individual neurons in populations generating the BOLD signal.

Current-source density estimation based on inversion of electrostatic forward solution: Effects of finite extent of neuronal activity and conductivity discontinuities

A new method for estimation of current-source density (CSD) from local field potentials is presented. This inverse CSD (iCSD) method is based on explicit inversion of the electrostatic forward solution and can be applied to data from multielectrode arrays with various geometries. Here, the method is applied to linear-array (laminar) electrode data. Three iCSD methods are considered: the CSD is assumed to have cylindrical symmetry and be (i) localized in infinitely thin discs, (ii) step-wise constant or (iii) continuous and smoothly varying (using cubic splines) in the vertical direction. For spatially confined CSD distributions the standard CSD method, involving a discrete double derivative, is seen in model calculations to give significant estimation errors when the lateral source dimension is comparable to the size of a cortical column (less than approximately 1 mm). Further, discontinuities in the extracellular conductivity are seen to potentially give sizable errors for even wider source distributions. The iCSD methods are seen to give excellent estimates when the correct lateral source dimension and spatial distribution of conductivity are incorporated. To illustrate the application to real data, iCSD estimates of stimulus-evoked responses measured with laminar electrodes in the rat somatosensory (barrel) cortex are compared to estimates from the standard CSD method.

ERP/CSD indices of impaired verbal working memory subprocesses in schizophrenia

To disentangle subprocesses of verbal working memory deficits in schizophrenia, long EEG epochs (>10 s) were recorded from 13 patients and 17 healthy adults during a visual word serial position test. ERP generator patterns were summarized by temporal PCA from reference-free current source density (CSD) waveforms to sharpen 31-channel topographies. Patients showed poorer performance and reduced left inferior parietotemporal P3 source. Build-up of mid-frontal negative slow wave (SW) in controls during item encoding, integration, and active maintenance was absent in patients, whereas a sustained mid-frontal SW sink during the retention interval was comparable across groups. Mid-frontal SW sinks (encoding and retention periods) and posterior SW sinks and sources (encoding only) were related to performance in controls only. Data suggest disturbed processes in a frontal-parietotemporal network in schizophrenia, affecting encoding and early item storage.

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.

Intracellular and current source density analyses of somatosensory input to the optic tectum of the frog

This is the first report of current source density (CSD) and intracellular analyses of non-optic processing in the frog optic tectum. Sciatic nerve stimulation was used to test for somatosensory input to the optic tectum. To demonstrate the distribution of somatosensory input, field potentials were recorded from the whole surface of both tecta. Two components were observed. An early component was found in the whole area, but a late component was detected only in medial and caudal regions of the contralateral tectum. The effect of different stimulus intensity suggested that the optic tectum receives mainly the tactile sensation with fast conducting, low threshold level afferents from the sciatic nerve. The result of CSD analysis suggests that somatosensory afferents terminate on the tectal neurons with vertically expanding dendrites at the medial site of the contralateral optic tectum where the late component was found. Intracellular recordings demonstrated postsynaptic potentials in the middle and deeper layers, which is consistent with results from mammalian superior colliculus in earlier studies. Additional stimulation of the optic tract demonstrated that some somatosensory neurons had bimodal responses. The responses of those in the middle layers appeared to participate in avoidance behavior, based upon previous CSD analysis of the tectum using optic tract stimulation. All somatosensory responses elicited in these neurons were IPSPs. The findings imply that the somatosensory input to the optic tectum gives a suppressive effect on avoidance behavior. A somatosensory effect on prey-catching behavior could not be found in the present small number of intracellular data.

An Oscillatory Hierarchy Controlling Neuronal Excitability and Stimulus Processing in the Auditory Cortex

EEG oscillations are hypothesized to reflect cyclical variations in the neuronal excitability, with particular frequency bands reflecting differing spatial scales of brain operation. However, despite decades of clinical and scientific investigation, there is no unifying theory of EEG organization, and the role of ongoing activity in sensory processing remains controversial. This study analyzed laminar profiles of synaptic activity [current source density CSD] and multiunit activity (MUA), both spontaneous and stimulus-driven, in primary auditory cortex of awake macaque monkeys. Our results reveal that the EEG is hierarchically organized; delta (1–4 Hz) phase modulates theta (4–10 Hz) amplitude, and theta phase modulates gamma (30–50 Hz) amplitude. This oscillatory hierarchy controls baseline excitability and thus stimulus-related responses in a neuronal ensemble. We propose that the hierarchical organization of ambient oscillatory activity allows auditory cortex to structure its temporal activity pattern so as to optimize the processing of rhythmic inputs.

Reading vascular changes in brain imaging: is dendritic calcium the key?

A key goal in functional neuroimaging is to use signals that are related to local changes in metabolism and blood flow to track the neuronal correlates of mental activity. Recent findings indicate that the dendritic processing of excitatory synaptic inputs correlates more closely than the generation of spikes with brain imaging signals. The correlation is often nonlinear and context-sensitive, and cannot be generalized for every condition or brain region. The vascular signals are mainly produced by increases in intracellular calcium in neurons and possibly astrocytes, which activate important enzymes that produce vasodilators to generate increments in flow and the positive blood oxygen level dependent signal. Our understanding of the cellular mechanisms of functional imaging signals places constraints on the interpretation of the data.

Emergence of oscillations and spatio-temporal coherence states in a continuum-model of excitatory and inhibitory neurons

A neural field model of the reaction-diffusion type for the emergence of oscillatory phenomena in visual cortices is proposed. To investigate the joint spatio-temporal oscillatory dynamics in a continuous distribution of excitatory and inhibitory neurons, the coupling among oscillators is modelled as a diffusion process, combined with non-linear point interactions. The model exhibits cooperative activation properties in both time and space, by reacting to volleys of activations at multiple cortical sites with ordered spatio-temporal oscillatory states, similar to those found in the physiological experiments on slow-wave field potentials. The possible use of the resulting spatial distributions of coherent states, as a flexible medium to establish feature association, is discussed.