Physiological origins of evoked magnetic fields and extracellular field potentials produced by guinea-pig CA3 hippocampal slices

L1-norm vs. L2-norm fitting in optimizing focal multi-channel tES stimulation: linear and semidefinite programming vs. weighted least squares

BACKGROUND AND OBJECTIVE

This study focuses on Multi-Channel Transcranial Electrical Stimulation, a non-invasive brain method for stimulating neuronal activity under the influence of low-intensity currents. We introduce a mathematical formulation for finding a current pattern that optimizes an L1-norm fit between a given focal target distribution and volumetric current density inside the brain. L1-norm is well-known to favor well-localized or sparse distributions compared to L2-norm (least-squares) fitted estimates.

METHODS

We present a linear programming approach that performs L1-norm fitting and penalization of the current pattern (L1L1) to control the number of non-zero currents. The optimizer filters a large set of candidate solutions using a two-stage metaheuristic search from a pre-filtered set of candidates.

RESULTS

The numerical simulation results obtained with both 8- and 20-channel electrode montages suggest that our hypothesis on the benefits of L1-norm data fitting is valid. Compared to an L1-norm regularized L2-norm fitting (L1L2) via semidefinite programming and weighted Tikhonov least-squares method (TLS), the L1L1 results were overall preferable for maximizing the focused current density at the target position, and the ratio between focused and nuisance current magnitudes.

CONCLUSIONS

We propose the metaheuristic L1L1 optimization approach as a potential technique to obtain a well-localized stimulus with a controllable magnitude at a given target position. L1L1 finds a current pattern with a steep contrast between the anodal and cathodal electrodes while suppressing the nuisance currents in the brain, hence, providing a potential alternative to modulate the effects of the stimulation, e.g., the sensation experienced by the subject.

Biophysically detailed forward modeling of the neural origin of EEG and MEG signals

Electroencephalography (EEG) and magnetoencephalography (MEG) are among the most important techniques for non-invasively studying cognition and disease in the human brain. These signals are known to originate from cortical neural activity, typically described in terms of current dipoles. While the link between cortical current dipoles and EEG/MEG signals is relatively well understood, surprisingly little is known about the link between different kinds of neural activity and the current dipoles themselves. Detailed biophysical modeling has played an important role in exploring the neural origin of intracranial electric signals, like extracellular spikes and local field potentials. However, this approach has not yet been taken full advantage of in the context of exploring the neural origin of the cortical current dipoles that are causing EEG/MEG signals. Here, we present a method for reducing arbitrary simulated neural activity to single current dipoles. We find that the method is applicable for calculating extracranial signals, but less suited for calculating intracranial electrocorticography (ECoG) signals. We demonstrate that this approach can serve as a powerful tool for investigating the neural origin of EEG/MEG signals. This is done through example studies of the single-neuron EEG contribution, the putative EEG contribution from calcium spikes, and from calculating EEG signals from large-scale neural network simulations. We also demonstrate how the simulated current dipoles can be used directly in combination with detailed head models, allowing for simulated EEG signals with an unprecedented level of biophysical details. In conclusion, this paper presents a framework for biophysically detailed modeling of EEG and MEG signals, which can be used to better our understanding of non-inasively measured neural activity in humans.

Influence of the on-line ELF-EMF stimulation on the electrophysiological properties of the rat hippocampal CA1 neurons in vitro

The extremely low frequency electromagnetic fields (ELF-EMFs) have been shown to have an environmentally negative effect on humans' health; however, its treatment effect is beneficial for patients suffering from neurological disorders. Despite this success, the application of ELF-EMF has exceeded in the understanding of its internal mechanism. Recently, it was found that on-line magnetic stimulation may offer advantages over off-line magnetic exposure and has proven to be effective in activating the prefrontal cortex pyramidal neurons in vitro. Here, we perform computational simulations of the stimulation coils in COMSOL modeling to describe the uniformity of the distribution of the on-line magnetic field. Interestingly, the modeling data and actual measurements showed that the densities of the magnetic flux that was generated by the on-line stimulation coils were similar. The on-line magnetic stimulator induced sodium channel currents as well as field excitatory postsynaptic potentials of the rat hippocampal CA1 neurons and successfully demonstrated its extensive applications to activate neuronal tissue. These findings further raise the possibility that the instrument of on-line magnetic stimulation may be an effective alternative for studies in the field of bioelectromagnetics.

Electrophysiological effects of non-invasive Radio Electric Asymmetric Conveyor (REAC) on thalamocortical neural activities and perturbed experimental conditions

The microwave emitting Radio Electric Asymmetric Conveyor (REAC) is a technology able to interact with biological tissues at low emission intensity (2 mW at the emitter and 2.4 or 5.8 GHz) by inducing radiofrequency generated microcurrents. It shows remarkable biological effects at many scales from gene modulations up to functional global remodeling even in human subjects. Previous REAC experiments by functional Magnetic Resonance Imaging (fMRI) on healthy human subjects have shown deep modulations of cortical BOLD signals. In this paper we studied the effects of REAC application on spontaneous and evoked neuronal activities simultaneously recorded by microelectrode matrices from the somatosensory thalamo-cortical axis in control and chronic pain experimental animal models. We analyzed the spontaneous spiking activity and the Local Field Potentials (LFPs) before and after REAC applied with a different protocol. The single neuron spiking activities, the neuronal responses to peripheral light mechanical stimuli, the population discharge synchronies as well as the correlations and the network dynamic connectivity characteristics have been analyzed. Modulations of the neuronal frequency associated with changes of functional correlations and significant LFP temporal realignments have been diffusely observed. Analyses by topological methods have shown changes in functional connectivity with significant modifications of the network features.

Modeling the effect of dendritic input location on MEG and EEG source dipoles

The cerebral sources of magneto- and electroencephalography (MEG, EEG) signals can be represented by current dipoles. We used computational modeling of realistically shaped passive-membrane dendritic trees of pyramidal cells from the human cerebral cortex to examine how the spatial distribution of the synaptic inputs affects the current dipole. The magnitude of the total dipole moment vector was found to be proportional to the vertical location of the synaptic input. The dipole moment had opposite directions for inputs above and below a reversal point located near the soma. Inclusion of shunting-type inhibition either suppressed or enhanced the current dipole, depending on whether the excitatory and inhibitory synapses were on the same or opposite side of the reversal point. Relating the properties of the macroscopic current dipoles to dendritic current distributions can help to provide means for interpreting MEG and EEG data in terms of synaptic connection patterns within cortical areas.

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.

Correlates of a single cortical action potential in the epidural EEG

To identify the correlates of a single cortical action potential in surface EEG, we recorded simultaneously epidural EEG and single-unit activity in the primary somatosensory cortex of awake macaque monkeys. By averaging over EEG segments coincident with more than hundred thousand single spikes, we found short-lived (≈ 0.5 ms) triphasic EEG deflections dominated by high-frequency components > 800 Hz. The peak-to-peak amplitude of the grand-averaged spike correlate was 80 nV, which matched theoretical predictions, while single-neuron amplitudes ranged from 12 to 966 nV. Combining these estimates with post-stimulus-time histograms of single-unit responses to median-nerve stimulation allowed us to predict the shape of the evoked epidural EEG response and to estimate the number of contributing neurons. These findings establish spiking activity of cortical neurons as a primary building block of high-frequency epidural EEG, which thus can serve as a quantitative macroscopic marker of neuronal spikes.

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Cortical spikes are coincident with short-lived (~ 0.5 ms) EEG deflections.

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Cortical spikes produce ~  80 nV epidural EEG deflections at a distance of ~ 5 mm.

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EEG potentials due to spikes are dominated by high-frequency (> 800 Hz) components.

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High-frequency (> 800 Hz) EEG is a genuine macroscopic marker of spiking activity.

Discrimination of cortical laminae using MEG

Typically MEG source reconstruction is used to estimate the distribution of current flow on a single anatomically derived cortical surface model. In this study we use two such models representing superficial and deep cortical laminae. We establish how well we can discriminate between these two different cortical layer models based on the same MEG data in the presence of different levels of co-registration noise, Signal-to-Noise Ratio (SNR) and cortical patch size. We demonstrate that it is possible to make a distinction between superficial and deep cortical laminae for levels of co-registration noise of less than 2 mm translation and 2° rotation at SNR > 11 dB. We also show that an incorrect estimate of cortical patch size will tend to bias layer estimates. We then use a 3D printed head-cast (Troebinger et al., 2014) to achieve comparable levels of co-registration noise, in an auditory evoked response paradigm, and show that it is possible to discriminate between these cortical layer models in real data.

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We evaluate necessary recording precision to distinguish superficial/deep laminae.

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For coregistration error of < 2 mm/2° we can distinguish between these laminar models.

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Incorrect assumptions about cortical patch size bias these layer estimates.

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Initial results suggest that the auditory M100 derives from deep cortical layers.

Variability of magnetoencephalographic sensor sensitivity measures as a function of age, brain volume and cortical area

OBJECTIVE

To assess the feasibility and appropriateness of magnetoencephalography (MEG) for both adult and pediatric studies, as well as for the developmental comparison of these factors across a wide range of ages.

METHODS

For 45 subjects with ages from 1 to 24years (infants, toddlers, school-age children and young adults), lead fields (LFs) of MEG sensors are computed using anatomically realistic boundary element models (BEMs) and individually-reconstructed cortical surfaces. Novel metrics are introduced to quantify MEG sensor focality.

RESULTS

The variability of MEG focality is graphed as a function of brain volume and cortical area. Statistically significant differences in total cerebral volume, cortical area, MEG global sensitivity and LF focality are found between age groups.

CONCLUSIONS

Because MEG focality and sensitivity differ substantially across the age groups studied, the cortical LF maps explored here can provide important insights for the examination and interpretation of MEG signals from early childhood to young adulthood.

SIGNIFICANCE

This is the first study to (1) investigate the relationship between MEG cortical LFs and brain volume as well as cortical area across development, and (2) compare LFs between subjects with different head sizes using detailed cortical reconstructions.

Pitfalls in the dipolar model for the neocortical EEG sources

For about six decades, primary current sources of the electroencephalogram (EEG) have been assumed dipolar in nature. In this study, we used electrophysiological recordings from anesthetized Wistar rats undergoing repeated whisker deflections to revise the biophysical foundations of the EEG dipolar model. In a first experiment, we performed three-dimensional recordings of extracellular potentials from a large portion of the barrel field to estimate intracortical multipolar moments generated either by single spiking neurons (i.e., pyramidal cells, PC; spiny stellate cells, SS) or by populations of them while experiencing synchronized postsynaptic potentials. As expected, backpropagating spikes along PC dendrites caused dipolar field components larger in the direction perpendicular to the cortical surface (49.7 ± 22.0 nA·mm). In agreement with the fact that SS cells have “close-field” configurations, their dipolar moment at any direction was negligible. Surprisingly, monopolar field components were detectable both at the level of single units (i.e., −11.7 ± 3.4 nA for PC) and at the mesoscopic level of mixed neuronal populations receiving extended synaptic inputs within either a cortical column (−0.44 ± 0.20 μA) or a 2.5-m3-voxel volume (−3.32 ± 1.20 μA). To evaluate the relationship between the macroscopically defined EEG equivalent dipole and the mesoscopic intracortical multipolar moments, we performed concurrent recordings of high-resolution skull EEG and laminar local field potentials. From this second experiment, we estimated the time-varying EEG equivalent dipole for the entire barrel field using either a multiple dipole fitting or a distributed type of EEG inverse solution. We demonstrated that mesoscopic multipolar components are altogether absorbed by any equivalent dipole in both types of inverse solutions. We conclude that the primary current sources of the EEG in the neocortex of rodents are not precisely represented by a single equivalent dipole and that the existence of monopolar components must be also considered at the mesoscopic level.

High-frequency neural activity and human cognition: past, present and possible future of intracranial EEG research

Human intracranial EEG (iEEG) recordings are primarily performed in epileptic patients for presurgical mapping. When patients perform cognitive tasks, iEEG signals reveal high-frequency neural activities (HFAs, between around 40 Hz and 150 Hz) with exquisite anatomical, functional and temporal specificity. Such HFAs were originally interpreted in the context of perceptual or motor binding, in line with animal studies on gamma-band ('40 Hz') neural synchronization. Today, our understanding of HFA has evolved into a more general index of cortical processing: task-induced HFA reveals, with excellent spatial and time resolution, the participation of local neural ensembles in the task-at-hand, and perhaps the neural communication mechanisms allowing them to do so. This review promotes the claim that studying HFA with iEEG provides insights into the neural bases of cognition that cannot be derived as easily from other approaches, such as fMRI. We provide a series of examples supporting that claim, drawn from studies on memory, language and default-mode networks, and successful attempts of real-time functional mapping. These examples are followed by several guidelines for HFA research, intended for new groups interested by this approach. Overall, iEEG research on HFA should play an increasing role in cognitive neuroscience in humans, because it can be explicitly linked to basic research in animals. We conclude by discussing the future evolution of this field, which might expand that role even further, for instance through the use of multi-scale electrodes and the fusion of iEEG with MEG and fMRI.

Subthreshold somatic voltage in neocortical pyramidal cells can control whether spikes propagate from the axonal plexus to axon terminals: a model study

There is suggestive evidence that pyramidal cell axons in neocortex may be coupled by gap junctions into an "axonal plexus" capable of generating very fast oscillations (VFOs) with frequencies exceeding 80 Hz. It is not obvious, however, how a pyramidal cell in such a network could control its output when action potentials are free to propagate from the axons of other pyramidal cells into its own axon. We address this problem by means of simulations based on three-dimensional reconstructions of pyramidal cells from rat somatosensory cortex. We show that somatic depolarization enables propagation via gap junctions into the initial segment and main axon, while somatic hyperpolarization disables it. We show further that somatic voltage cannot effectively control action potential propagation through gap junctions on minor collaterals; action potentials may therefore propagate freely from such collaterals regardless of somatic voltage. In previous work, VFOs are all but abolished during the hyperpolarization phase of slow oscillations induced by anesthesia in vivo. This finding constrains the density of gap junctions on collaterals in our model and suggests that axonal sprouting due to cortical lesions may result in abnormally high gap junction density on collaterals, leading in turn to excessive VFO activity and hence to epilepsy via kindling.

Source cancellation profiles of electroencephalography and magnetoencephalography

Recorded electric potentials and magnetic fields due to cortical electrical activity have spatial spread even if their underlying brain sources are focal. Consequently, as a result of source cancellation, loss in signal amplitude and reduction in the effective signal-to-noise ratio can be expected when distributed sources are active simultaneously. Here we investigate the cancellation effects of EEG and MEG through the use of an anatomically correct forward model based on structural MRI acquired from 7 healthy adults. A boundary element model (BEM) with four compartments (brain, cerebrospinal fluid, skull and scalp) and highly accurate cortical meshes (~300,000 vertices) were generated. Distributed source activations were simulated using contiguous patches of active dipoles. To investigate cancellation effects in both EEG and MEG, quantitative indices were defined (source enhancement, cortical orientation disparity) and computed for varying values of the patch radius as well as for automatically parcellated gyri and sulci. Results were calculated for each cortical location, averaged over all subjects using a probabilistic atlas, and quantitatively compared between MEG and EEG. As expected, MEG sensors were found to be maximally sensitive to signals due to sources tangential to the scalp, and minimally sensitive to radial sources. Compared to EEG, however, MEG was found to be much more sensitive to signals generated antero-medially, notably in the anterior cingulate gyrus. Given that sources of activation cancel each other according to the orientation disparity of the cortex, this study provides useful methods and results for quantifying the effect of source orientation disparity upon source cancellation.

Can magnetoencephalography track the afferent information flow along white matter thalamo-cortical fibers?

White matter thalamo-cortical fibers allow the communication of distant brain regions by carrying neuronal signals. Mapping non-invasively the information flow within white matter fibers is regarded so far as impossible. We investigated here whether information flow propagating along thalamo-cortical fibers can be detected using magnetoencephalography (MEG). Somatosensory evoked fields (SEFs) were recorded from healthy subjects and a patient with a unilateral, prenatally acquired, white matter lesion, which had induced the development of an abnormal trajectory of thalamo-cortical fibers. Equivalent current dipole (ECD) was used to model sources of SEFs. ECD at ~15 ms after stimulus onset was located within or close to the contralateral thalamus at the proximity of a hemodynamic response detected during a similar fMRI experiment. At the M20 peak latency, ECD was localized within the hand area of the contralateral primary somatosensory cortex (Brodmann area 3b (BA3b)). In healthy subjects, ECD changed dynamically position from thalamus to BA3b following a curved path, which was partially overlapping the thalamo-cortical fibers reconstructed by tractography. In the patient, ECD followed a similar path only in the intact hemisphere. In the affected hemisphere, the dipole trajectory circumnavigated the extended lesion on its way to the preserved primary somatosensory cortex--similar to the trajectory findings. Evidence from different methodological approaches converges on the conclusion that MEG can track the afferent information flow along thalamo-cortical fibers and in contrast to the traditional view can localize under presuppositions deep thalamic sources.

Modulus and direction of the neural current vector identify distinct functional connectivity modes between human MT+ areas

Reconstruction of neural current sources from magnetoencephalography (MEG) data provides two independent estimates of the instantaneous current modulus and its direction. Here, we explore how different information on the modulus and direction affects the inter-hemisphere connectivity of the human medial temporal complex (hMT+). Connectivity was quantified by mutual information values of paired time series of current moduli or directions, with the joint probability distribution estimated with an optimized Gaussian kernel. These time series were obtained from tomographic analysis of single-trial MEG responses to a visual motion stimulus. With a high-contrast stimulus, connectivity measures based on the modulus were relatively strong in the prestimulus period, continuing until 100 ms after stimulus onset. The strongest modulus connectivity was produced with a long lag (19 ms) of the right hMT+ after the left hMT+. On the other hand, connectivity measures based on direction were relatively strong after 100 ms, with a short delay of less than 6 ms. These results suggest that nonspecific and probably indirect communication between the homologous areas is turned, by the stimulus arrival, into more precise and direct communication through the corpus callosum. The orientation of the estimated current vector for the strong connectivity can be explained by the curvature of the active cortical sheet. The temporal patterns of modulus and directional connectivity were different at low contrast, but similar to those at high contrast. We conclude that the modulus and direction indicate distinct functional connectivity modes.

Unitary inhibitory field potentials in the CA3 region of rat hippocampus

Glickfeld and colleagues (2009) suggested that single hippocampal interneurones generate field potentials at monosynaptic latencies. We pursued this observation in simultaneous intracellular and multiple extracellular records from the CA3 region of rat hippocampal slices. We confirmed that interneurones evoked field potentials at monosynaptic latencies. Pyramidal cells initiated disynaptic inhibitory field potentials, but did not initiate detectable monosynaptic excitatory fields. We confirmed that inhibitory fields were GABAergic in nature and showed they were suppressed at low external Cl(-), suggesting they originate at postsynaptic sites. Field potentials generated by a single interneuron were detected at multiple sites over distances of more than 800 mum along the stratum pyramidale of the CA3 region. We used arrays of extracellular electrodes to examine amplitude distributions of spontaneous inhibitory fields recorded at sites orthogonal to or along the CA3 stratum pyramidale. Cluster analysis of spatially distributed inhibitory field events let us separate events generated by interneurones terminating on distinct zones of somato-dendritic axis. Events generated at dendritic sites had similar amplitudes but occurred less frequently and had somewhat slower kinetics than perisomatic events generated near the stratum pyramidale. In records from multiple sites in the CA3 stratum pyramidale, we distinguished inhibitory fields that seemed to be initiated by interneurones with spatially distinct axonal arborisations.

A method for the estimation of functional brain connectivity from time-series data

A central issue in cognitive neuroscience is which cortical areas are involved in managing information processing in a cognitive task and to understand their temporal interactions. Since the transfer of information in the form of electrical activity from one cortical region will in turn evoke electrical activity in other regions, the analysis of temporal synchronization provides a tool to understand neuronal information processing between cortical regions. We adopt a method for revealing time-dependent functional connectivity. We apply statistical analyses of phases to recover the information flow and the functional connectivity between cortical regions for high temporal resolution data. We further develop an evaluation method for these techniques based on two kinds of model networks. These networks consist of coupled Rössler attractors or of coupled stochastic Ornstein-Uhlenbeck systems. The implemented time-dependent coupling includes uni- and bi-directional connectivities as well as time delayed feedback. The synchronization dynamics of these networks are analyzed using the mean phase coherence, based on averaging over phase-differences, and the general synchronization index. The latter is based on the Shannon entropy. The combination of these with a parametric time delay forms the basis of a connectivity pattern, which includes the temporal and time lagged dynamics of the synchronization between two sources. We model and discuss potential artifacts. We find that the general phase measures are remarkably stable. They produce highly comparable results for stochastic and periodic systems. Moreover, the methods proves useful for identifying brief periods of phase coupling and delays. Therefore, we propose that the method is useful as a basis for generating potential functional connective models.

Fetal neurological assessment using noninvasive magnetoencephalography

SQUID Array for Reproductive Assessment is a unique magnetoencephalography device designed for the noninvasive recording of fetal brain activity. In this article, we provide a general overview of the technology and its potential application to fetal medicine. A large number of studies that have been conducted and published describing this device since it was brought into operation are referenced throughout the article.

Intracranial microprobe for evaluating neuro-hemodynamic coupling in unanesthetized human neocortex

Measurement of the blood-oxygen-level dependent (BOLD) response with fMRI has revolutionized cognitive neuroscience and is increasingly important in clinical care. The BOLD response reflects changes in deoxy-hemoglobin concentration, blood volume, and blood flow. These hemodynamic changes ultimately result from neuronal firing and synaptic activity, but the linkage between these domains is complex, poorly understood, and may differ across species, cortical areas, diseases, and cognitive states. We describe here a technique that can measure neural and hemodynamic changes simultaneously from cortical microdomains in waking humans. We utilize a "laminar optode," a linear array of microelectrodes for electrophysiological measures paired with a micro-optical device for hemodynamic measurements. Optical measurements include laser Doppler to estimate cerebral blood flow as well as point spectroscopy to estimate oxy- and deoxy-hemoglobin concentrations. The microelectrode array records local field potential gradients (PG) and multi-unit activity (MUA) at 24 locations spanning the cortical depth, permitting estimation of population trans-membrane current flows (Current Source Density, CSD) and population cell firing in each cortical lamina. Comparison of the laminar CSD/MUA profile with the origins and terminations of cortical circuits allows activity in specific neuronal circuits to be inferred and then directly compared to hemodynamics. Access is obtained in epileptic patients during diagnostic evaluation for surgical therapy. Validation tests with relatively well-understood manipulations (EKG, breath-holding, cortical electrical stimulation) demonstrate the expected responses. This device can provide a new and robust means for obtaining detailed, quantitative data for defining neurovascular coupling in awake humans.

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.

Methods for Determining Frequency- and Region-Dependent Relationships Between Estimated LFPs and BOLD Responses in Humans

The relationship between electrophysiological and functional magnetic resonance imaging (fMRI) signals remains poorly understood. To date, studies have required invasive methods and have been limited to single functional regions and thus cannot account for possible variations across brain regions. Here we present a method that uses fMRI data and singe-trial electroencephalography (EEG) analyses to assess the spatial and spectral dependencies between the blood-oxygenation-level-dependent (BOLD) responses and the noninvasively estimated local field potentials (eLFPs) over a wide range of frequencies (0–256 Hz) throughout the entire brain volume. This method was applied in a study where human subjects completed separate fMRI and EEG sessions while performing a passive visual task. Intracranial LFPs were estimated from the scalp-recorded data using the ELECTRA source model. We compared statistical images from BOLD signals with statistical images of each frequency of the eLFPs. In agreement with previous studies in animals, we found a significant correspondence between LFP and BOLD statistical images in the gamma band (44–78 Hz) within primary visual cortices. In addition, significant correspondence was observed at low frequencies (<14 Hz) and also at very high frequencies (>100 Hz). Effects within extrastriate visual areas showed a different correspondence that not only included those frequency ranges observed in primary cortices but also additional frequencies. Results therefore suggest that the relationship between electrophysiological and hemodynamic signals thus might vary both as a function of frequency and anatomical region.

Neural correlates of tactile detection: a combined magnetoencephalography and biophysically based computational modeling study

Previous reports conflict as to the role of primary somatosensory neocortex (SI) in tactile detection. We addressed this question in normal human subjects using whole-head magnetoencephalography (MEG) recording. We found that the evoked signal (0-175 ms) showed a prominent equivalent current dipole that localized to the anterior bank of the postcentral gyrus, area 3b of SI. The magnitude and timing of peaks in the SI waveform were stimulus amplitude dependent and predicted perception beginning at approximately 70 ms after stimulus. To make a direct and principled connection between the SI waveform and underlying neural dynamics, we developed a biophysically realistic computational SI model that contained excitatory and inhibitory neurons in supragranular and infragranular layers. The SI evoked response was successfully reproduced from the intracellular currents in pyramidal neurons driven by a sequence of lamina-specific excitatory input, consisting of output from the granular layer (approximately 25 ms), exogenous input to the supragranular layers (approximately 70 ms), and a second wave of granular output (approximately 135 ms). The model also predicted that SI correlates of perception reflect stronger and shorter-latency supragranular and late granular drive during perceived trials. These findings strongly support the view that signatures of tactile detection are present in human SI and are mediated by local neural dynamics induced by lamina-specific synaptic drive. Furthermore, our model provides a biophysically realistic solution to the MEG signal and can predict the electrophysiological correlates of human perception.

Modelling the magnetic signature of neuronal tissue

Neuronal communication in the brain involves electrochemical currents, which produce magnetic fields. Stimulus-evoked brain responses lead to changes in these fields and can be studied using magneto- and electro-encephalography (MEG/EEG). In this paper we model the spatiotemporal distribution of the magnetic field of a physiologically idealized but anatomically realistic neuron to assess the possibility of using magnetic resonance imaging (MRI) for directly mapping the neuronal currents in the human brain. Our results show that the magnetic field several centimeters from the centre of the neuron is well approximated by a dipole source, but the field close to the neuron is not, a finding particularly important for understanding the possible contrast mechanism underlying the use of MRI to detect and locate these currents. We discuss the importance of the spatiotemporal characteristics of the magnetic field in cortical tissue for evaluating and optimizing an experiment based on this mechanism and establish an upper bound for the expected MRI signal change due to stimulus-induced cortical response. Our simulations show that the expected change of the signal magnitude is 1.6% and its phase shift is 1 degrees . An unexpected finding of this work is that the cortical orientation with respect to the external magnetic field has little effect on the predicted MRI contrast. This encouraging result shows that magnetic resonance contrast directly based on the neuronal currents present in the cortex is theoretically a feasible imaging technique. MRI contrast generation based on neuronal currents depends on the dendritic architecture and we obtained high-resolution optical images of cortical tissue to discuss the spatial structure of the magnetic field in grey matter.

Mechanisms of seizure propagation in a cortical model

We consider a mathematical model of mesoscopic human cortical ictal electrical activity. We compare the model results with ictal electrocortical data recorded from three human subjects and show how the two agree. We determine that, in the model system, seizures result from increased connectivity between excitatory and inhibitory cell populations, or from decreased connectivity within either excitatory or inhibitory cell populations. We compare the model results with the disinhibition and 4-AP models of epilepsy and suggest how the model may guide the development of new anticonvulsant therapies.

Magnetoencephalography in Neurosurgery

OBJECTIVE:

To present applications of magnetoencephalography (MEG) in studies of neurosurgical patients.

METHODS:

MEG maps magnetic fields generated by electric currents in the brain, and allows the localization of brain areas producing evoked sensory responses and spontaneous electromagnetic activity. The identified sources can be integrated with other imaging modalities, e.g., with magnetic resonance imaging scans of individual patients with brain tumors or intractable epilepsy, or with other types of brain imaging data.

RESULTS:

MEG measurements using modern whole-scalp instruments assist in tailoring individual therapies for neurosurgical patients by producing maps of functionally irretrievable cortical areas and by identifying cortical sources of interictal and ictal epileptiform activity. The excellent time resolution of MEG enables tracking of complex spaciotemporal source patterns, helping, for example, with the separation of the epileptic pacemaker from propagated activity. The combination of noninvasive mapping of subcortical pathways by magnetic resonance imaging diffusion tensor imaging with MEG source localization will, in the near future, provide even more accurate navigational tools for preoperative planning. Other possible future applications of MEG include the noninvasive estimation of language lateralization and the follow-up of brain plasticity elicited by central or peripheral neural lesions or during the treatment of chronic pain.

CONCLUSION:

MEG is a mature technique suitable for producing preoperative “road maps” of eloquent cortical areas and for localizing epileptiform activity.

Contributions of principal neocortical neurons to magnetoencephalography and electroencephalography signals

A realistically shaped three-dimensional single-neuron model was constructed for each of four principal cell types in the neocortex in order to infer their contributions to magnetoencephalography (MEG) and electroencephalography (EEG) signals. For each cell, the soma was stimulated and the resulting intracellular current was used to compute the current dipole Q for the whole cell or separately for the apical and basal dendrites. The magnitude of Q is proportional to the magnetic field and electrical potential far from the neuron. A train of spikes and depolarization shift in an intracellular burst discharge were seen as spikes and an envelope in Q for the layer V and layer II/III pyramidal cells. The stellate cells lacked the envelope. As expected, the pyramidal cells produced a stronger Q than the stellate cells. The spikes produced by the layer V pyramidal cells (n = 4) varied between -0.78 and 2.97 pA m with the majority of the cells showing a current toward the pia (defined as positive). The basal dendrites, however, produced considerable spike currents. The magnitude and direction of dipole moment are in agreement with the distribution of the dendrites. The spikes in Q for the layer V pyramidal cells were produced by the transient sodium conductance and potassium conductance of delayed rectifier type; the conductances distributed along the dendrites were capable of generating spike propagation, which was seen in Q as the tail of a triphasic wave lasting several milliseconds. The envelope was similar in magnitude (-0.41 to -0.90 pA m) across the four layer V pyramidal cells. The spike and envelope for the layer II/III pyramidal cell were 0.47 and -0.29 pA m, respectively; these values agreed well with empirical and theoretical estimates for guinea pig CA3 pyramidal cells. Spikes were stronger for the layer IV spiny stellate (0.27 pA m) than the layer III aspiny stellate cell (0.06 pA m) along their best orientations. The spikes may thus be stronger than has been previously thought. The Q for a population of stellate cells may be weaker than a linear sum of their individual Q values due to their variable dendritic geometry. The burst discharge by pyramidal cells may be detectable with MEG and EEG when 10 000-50 000 cells are synchronously active.

Widely distributed magnetoencephalography spikes related to the planning and execution of human saccades

With sufficiently fast data sampling, ubiquitous sharp transients appear in magnetoencephalography (MEG) data. Initially, no known collective neuronal activity could explain MEG signal generation well above 100 Hz, so it was assumed that these transients were entirely composed of background electronic noise that could be eliminated by filtering and averaging. Recent studies at the cellular level provided evidence for synchronous synaptic input to dendrites and volleys of near-simultaneous action potentials. MEG studies have also identified high-frequency oscillations well above 200 Hz after averaging large number of somatosensory evoked responses. In this study, we searched for evidence of high-frequency neuronal activity in the raw MEG signal using the highest sampling rate available with our hardware. Two human subjects participated in three experiments using visual cues to define planning, preparation, and execution or inhibition of saccades. Tomographic analysis identified "MEG spikes" that were widely distributed across the cortex, cerebellum, and brainstem during cue presentations and saccades. Here we demonstrate how these MEG spikes can be recorded and localized in real time and show that task demands influence their properties. The MEG spikes were organized into feedforward and corollary discharge sequences that could, when combined with the slower activity-linked processing in discrete brain areas over long periods, lasting hundreds of milliseconds. Preparation for impending saccade began as soon as relevant information became available. Cues providing partial information initiated competing motor programs for as yet undecided future actions that were maintained until cues with new information resolved the uncertainty.

Processing stages underlying word recognition in the anteroventral temporal lobe

The anteroventral temporal lobe integrates visual, lexical, semantic and mnestic aspects of word processing, through its reciprocal connections with the ventral visual stream, language areas, and the hippocampal formation. We used linear microelectrode arrays to probe population synaptic currents and neuronal firing in different cortical layers of the anteroventral temporal lobe, during semantic judgments with implicit priming and overt word recognition. Since different extrinsic and associative inputs preferentially target different cortical layers, this method can help reveal the sequence and nature of local processing stages at a higher resolution than was previously possible. The initial response in inferotemporal and perirhinal cortices is a brief current sink beginning at approximately 120 ms and peaking at approximately 170 ms. Localization of this initial sink to middle layers suggests that it represents feedforward input from lower visual areas, and simultaneously increased firing implies that it represents excitatory synaptic currents. Until approximately 800 ms, the main focus of transmembrane current sinks alternates between middle and superficial layers, with the superficial focus becoming increasingly dominant after approximately 550 ms. Since superficial layers are the target of local and feedback associative inputs, this suggests an alternation in predominant synaptic input between feedforward and feedback modes. Word repetition does not affect the initial perirhinal and inferotemporal middle layer sink but does decrease later activity. Entorhinal activity begins later (approximately 200 ms), with greater apparent excitatory post-synaptic currents and multiunit activity in neocortically projecting than hippocampal-projecting layers. In contrast to perirhinal and entorhinal responses, entorhinal responses are larger to repeated words during memory retrieval. These results identify a sequence of physiological activation, beginning with a sharp activation from lower level visual areas carrying specific information to middle layers. This is followed by feedback and associative interactions involving upper cortical layers, which are abbreviated to repeated words. Following bottom-up and associative stages, top-down recollective processes may be driven by entorhinal cortex. Word processing involves a systematic sequence of fast feedforward information transfer from visual areas to anteroventral temporal cortex followed by prolonged interactions of this feedforward information with local associations and feedback mnestic information from the medial temporal lobe.

Modification of the synaptic glutamate turnover in the hippocampal tissue exposed to low-frequency, pulsed magnetic fields

The influence of pulsed magnetic fields (PMF) on the release and uptake of glutamate was investigated. While the release was examined using hippocampal slices, synaptosomes were chosen to characterize the uptake process. (3)H-D-aspartate was used as a marker of glutamergic transmission. The pulsed magnetic fields (9-15 mT) applied according to the pattern which induced epileptic discharges in hippocampus amplified and attenuated the release and uptake of glutamate, respectively. However, the magnetic fields which induced an increase in neuronal excitability without concomitant seizures amplified both processes. These results confirm our previous reports and indicate that the glutamergic synapses are the target of magnetic fields action.

Contribution of ionic currents to magnetoencephalography (MEG) and electroencephalography (EEG) signals generated by guinea-pig CA3 slices

A mathematical model was used to analyse the contributions of different types of ionic currents in the pyramidal cells of longitudinal CA3 slices to the magnetic fields and field potentials generated by this preparation. Murakami et al. recently showed that a model based on the work of Traub et al. provides a quantitatively accurate account of the basic features of three types of empirical data (magnetic fields outside the slice, extracellular field potentials within the slice and intracellular potentials within the pyramidal neurons) elicited by stimulations of the soma and apical dendrites. This model was used in the present study to compute the net current dipole moment (Q) due to each of the different voltage- and ligand-gated channels in the cells in the presence of fast GABAA inhibition. These values of Q are proportional to the magnetic field and electrical potential far away from the slice. The intrinsic conductances were found to be more important than the synaptic conductances in determining the shape and magnitude of Q. Among the intrinsic conductances, the sodium (gNa) and delayed-rectifier potassium (gK(DR)) channels were found to produce sharp spikes. The high-threshold calcium channel (gCa) and C-type potassium channel (gK(C)) primarily determined the overall current waveforms. The roles of gCa and gK(C) were independent of small perturbations in these channel densities in the apical and basal dendrites. A combination of gNa, gK(DR), gCa, and gK(C) accounted for most of the evoked responses, except for later slow components, which were primarily due to synaptic channels.