Intracranial measurement of current densities induced by transcranial magnetic stimulation in the human brain

Transcranial magnetic stimulation (TMS) is a non-invasive technique that uses the principle of electromagnetic induction to generate currents in the brain via pulsed magnetic fields. The magnitude of such induced currents is unknown. In this study we measured the TMS induced current densities in a patient with implanted depth electrodes for epilepsy monitoring. A maximum current density of 12 microA/cm2 was recorded at a depth of 1 cm from scalp surface with the optimum stimulation orientation used in the experiment and an intensity of 7% of the maximal stimulator output. During TMS we recorded relative current variations under different stimulating coil orientations and at different points in the subject's brain. The results were in accordance with current theoretical models. The induced currents decayed with distance form the coil and varied with alterations in coil orientations. These results provide novel insight into the physical and neurophysiological processes of TMS

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

We demonstrate an application of spherical harmonic decomposition to analysis of the human electroencephalogram (EEG). We implement two methods and discuss issues specific to analysis of hemispherical, irregularly sampled data. Performance of the methods and spatial sampling requirements are quantified using simulated data. The analysis is applied to experimental EEG data, confirming earlier reports of an approximate frequency-wavenumber relationship in some bands.Comment: 12 pages, 8 figures, submitted to Phys. Rev. E, uses APS RevTeX style

Effects of dipole position, orientation and noise on the accuracy of EEG source localization

BACKGROUND: The electroencephalogram (EEG) reflects the electrical activity in the brain on the surface of scalp. A major challenge in this field is the localization of sources in the brain responsible for eliciting the EEG signal measured at the scalp. In order to estimate the location of these sources, one must correctly model the sources, i.e., dipoles, as well as the volume conductor in which the resulting currents flow. In this study, we investigate the effects of dipole depth and orientation on source localization with varying sets of simulated random noise in 4 realistic head models. METHODS: Dipole simulations were performed using realistic head models and using the boundary element method (BEM). In all, 92 dipole locations placed in temporal and parietal regions of the head with varying depth and orientation were investigated along with 6 different levels of simulated random noise. Localization errors due to dipole depth, orientation and noise were investigated. RESULTS: The results indicate that there are no significant differences in localization error due tangential and radial dipoles. With high levels of simulated Gaussian noise, localization errors are depth-dependant. For low levels of added noise, errors are similar for both deep and superficial sources. CONCLUSION: It was found that if the signal-to-noise ratio is above a certain threshold, localization errors in realistic head models are, on average the same for deep and superficial sources. As the noise increases, localization errors increase, particularly for deep sources

Sensitivity of MEG and EEG to Source Orientation

An important difference between magnetoencephalography (MEG) and electroencephalography (EEG) is that MEG is insensitive to radially oriented sources. We quantified computationally the dependency of MEG and EEG on the source orientation using a forward model with realistic tissue boundaries. Similar to the simpler case of a spherical head model, in which MEG cannot see radial sources at all, for most cortical locations there was a source orientation to which MEG was insensitive. The median value for the ratio of the signal magnitude for the source orientation of the lowest and the highest sensitivity was 0.06 for MEG and 0.63 for EEG. The difference in the sensitivity to the source orientation is expected to contribute to systematic differences in the signal-to-noise ratio between MEG and EEG.National Institutes of Health (U.S.) (Grant NS057500)National Institutes of Health (U.S.) (Grant NS037462)National Institutes of Health (U.S.) (Grant HD040712)National Center for Research Resources (U.S.) (P41RR14075)Mind Research Networ

MEG in the macaque monkey and human: distinguishing cortical fields in space and time.

Magnetoencephalography (MEG) is an increasingly popular non-invasive tool used to record, on a millisecond timescale, the magnetic field changes generated by cortical neural activity. MEG has the advantage, over fMRI for example, that it is a direct measure of neural activity. In the current investigation we used MEG to measure cortical responses to tactile and auditory stimuli in the macaque monkey. We had two aims. First, we sought to determine whether MEG, a technique that may have low spatial accuracy, could be used to distinguish the location and organization of sensory cortical fields in macaque monkeys, a species with a relatively small brain compared to that of the human. Second, we wanted to examine the temporal dynamics of cortical responses in the macaque monkey relative to the human. We recorded MEG data from anesthetized monkeys and, for comparison, from awake humans that were presented with simple tactile and auditory stimuli. Neural source reconstruction of MEG data showed that primary somatosensory and auditory cortex could be differentiated and, further, that separate representations of the digit and lip within somatosensory cortex could be identified in macaque monkeys as well as humans. We compared the latencies of activity from monkey and human data for the three stimulation types and proposed a correspondence between the neural responses of the two species. We thus demonstrate the feasibility of using MEG in the macaque monkey and provide a non-human primate model for examining the relationship between external evoked magnetic fields and their underlying neural sources

Somatosensory System Deficits in Schizophrenia Revealed by MEG during a Median-Nerve Oddball Task

Although impairments related to somatosensory perception are common in schizophrenia, they have rarely been examined in functional imaging studies. In the present study, magnetoencephalography (MEG) was used to identify neural networks that support attention to somatosensory stimuli in healthy adults and abnormalities in these networks in patient with schizophrenia. A median-nerve oddball task was used to probe attention to somatosensory stimuli, and an advanced, high-resolution MEG source-imaging method was applied to assess activity throughout the brain. In nineteen healthy subjects, attention-related activation was seen in a sensorimotor network involving primary somatosensory (S1), secondary somatosensory (S2), primary motor (M1), pre-motor (PMA), and paracentral lobule (PCL) areas. A frontal–parietal–temporal “attention network”, containing dorsal- and ventral–lateral prefrontal cortex (DLPFC and VLPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), superior parietal lobule (SPL), inferior parietal lobule (IPL)/supramarginal gyrus (SMG), and temporal lobe areas, was also activated. Seventeen individuals with schizophrenia showed early attention-related hyperactivations in S1 and M1 but hypo-activation in S1, S2, M1, and PMA at later latency in the sensorimotor network. Within this attention network, hypoactivation was found in SPL, DLPFC, orbitofrontal cortex, and the dorsal aspect of ACC. Hyperactivation was seen in SMG/IPL, frontal pole, and the ventral aspect of ACC in patients. These findings link attention-related somatosensory deficits to dysfunction in both sensorimotor and frontal–parietal–temporal networks in schizophrenia