Search

We recorded evoked magnetic fields while short words were visually presented in different languages with an oddball paradigm. The task was to count how many words were in a target language when most of the words were in another language and there were also non-target deviants in a third language. When native words (Finnish) were targets, they evoked a selection response at the latency of 300-600 ms. However, when the task was to count non-native words among native standards, in addition to the targets, also the non-target foreign words evoked the selection response. These results may reflect differences in the selection process for native versus non-native words brought about by different proficiency levels of the languages.

Objectives: To investigate a possible interaction between sensory processing and transcranial magnetic stimulation (TMS), an experimental set-up permitting multichannel EEG measurements was used. Methods: A somatosensory stimulus was delivered to the right wrist, while single-pulse TMS was applied to the contralateral somatosensory cortex, either concurrent with the somatosensory stimulus or 10 ms after it. A control condition served to mimic the sound of TMS without actually resulting in brain stimulation. Results: An enhancement of the P25 component of the somatosensory-evoked potential (SEP) was consistently observed for TMS concurrent with somatosensory stimulus. The effect was topographically specific to the EEG recording sites below the TMS coil, i.e. above the somatosensory cortex contralateral to the stimulated peripheral nerve. Conclusions: The results can be interpreted (1) as an indication of local interaction between the somatosensory-evoked cortical activity and TMS-evoked activity or (2) as support of a relationship between the background EEG and the evoked potential (EP), this relationship being ‘disrupted’ by TMS. q 2001 Elsevier Science Ireland Ltd. All rights reserved.

We studied event-related desynchronization (ERD) of the 8–13 Hz rhythm (mu rhythm) of the primary somatosensory cortex (SI) caused by contra- and ipsilateral median-nerve stimulation. We used whole-head magnetoencephalography (MEG) and wavelet analysis together with our newly developed color-coded single-trial ERD display. The somatosensory stimuli suppressed mu rhythm at both contra- and ipsilateral SI, but the attenuation was clearly lateralized, being at least 20% stronger contra- than ipsilaterally. Moreover, repeated stimulation significantly reduced mu-rhythm ERD in the ipsilateral but not in the contralateral hemisphere in the course of the experiment. The observed lateralization is in agreement with the classical concept of a dominant role of the contralateral hemisphere in the processing of somatosensory information. The strong ipsilateral ERD in the beginning of the experiment may reflect the presence of non-specific arousal-like activation, which attenuates toward the end of the experiment.

Objective : We have used EEG to measure effects of air- and bone-conducted sound from the coil in transcranial magnetic stimulation (TMS). Methods : Auditory-evoked potentials to TMS were recorded in three different experimental conditions: (1) the coil 2 cm above the head, (2) the coil 2 cm above the head but rigidly connected by a plastic piece to the scalp, (3) the coil pressed against the scalp over the motor cortex. Results : The acoustical click from the TMS coil evoked large auditory potentials, whose amplitude depended critically on the mechanical contact of the coil with the head. Conclusion : Both air- and bone-conducted sounds have to be taken into account in the design and interpretation of TMS experiments.

Objectives: Transcranial magnetic stimulation (TMS) and high-resolution electroencephalography (EEG) were used to study the spreading of cortical activation in 6 healthy volunteers. Methods: Five locations in the left sensorimotor cortex (within 3 cm 2 ) were stimulated magnetically, while EEG was recorded with 60 scalp electrodes. A frameless stereotactic method was applied to determine the anatomic locus of stimulation and to superimpose the results on magnetic resonance images. Scalp potential and cortical current-density distributions were derived from averaged electroencephalographic (EEG) data. Results: The maxima of the ipsilateral activation were detected at the gyrus precentralis, gyrus supramarginalis, and lobulus parietalis superior, depending on the subject. Activation over the contralateral cortex was observed in all subjects, appearing at 22 ^ 2 ms (range 17– 28); the maxima were located at the gyrus precentralis, gyrus frontalis superior, and the lobulus parietalis inferior. Contralateral EEG waveforms showed consistent changes when different sites were stimulated: stimulation of the two most medial points evoked the smallest responses fronto-parietally. Conclusions: With the combination of TMS, EEG, and magnetic resonance imaging, an adequate spatiotemporal resolution may be achieved for tracing the intra- and interhemispheric spread of activation in the cortex caused by a magnetic pulse. q 2002 Elsevier Science Ireland Ltd. All rights reserved.

Interhemispheric phase synchrony and amplitude correlation of beta oscillations were studied with MEG in a resting condition. The left and right hemisphere beta oscillations exhibited phase-locking with a phase-lag near zero degrees. The index of synchronization was strongest when these oscillations had large amplitude. Functionally, we interpret the phase synchrony on the basis of bilaterality of movement organization. A positive interhemispheric correlation was also found for the amplitude of spontaneous beta oscillations over long time intervals (> 1 s). The low-frequency correlation of spontaneous rhythmic activity may be the source of the low-frequency correlations of the hemodynamic responses in homologous areas that have been reported previously and have been interpreted as functional connectivity between these areas.

The motor cortex of 10 healthy subjects was stimulated by transcranial magnetic stimulation (TMS) before and after ethanol challenge (0.8 g/kg resulting in blood concentration of 0.77 +/- 0.14 ml/liter). The electrical brain activity resulting from the brief electromagnetic pulse was recorded with high-resolution electroencephalography (EEG) and located using inversion algorithms. Focal magnetic pulses to the left motor cortex were delivered with a figure-of-eight coil at the random interstimulus interval of 1.5-2.5 s. The stimulation intensity was adjusted to the motor threshold of abductor digiti minimi. Two conditions before and after ethanol ingestion (30 min) were applied: (1) real TMS, with the coil pressed against the scalp; and (2) control condition, with the coil separated from the scalp by a 2-cm-thick piece of plastic. A separate EMG control recording of one subject during TMS was made with two bipolar platinum needle electrodes inserted to the left temporal muscle. In each condition, 120 pulses were delivered. The EEG was recorded from 60 scalp electrodes. A peak in the EEG signals was observed at 43 ms after the TMS pulse in the real-TMS condition but not in the control condition or in the control scalp EMG. Potential maps before and after ethanol ingestion were significantly different from each other (P = 0.01), but no differences were found in the control condition. Ethanol changed the TMS-evoked potentials over right frontal and left parietal areas, the underlying effect appearing to be largest in the right prefrontal area. Our findings suggest that ethanol may have changed the functional connectivity between prefrontal and motor cortices. This new noninvasive method provides direct evidence about the modulation of cortical connectivity after ethanol challenge.

Objectives: Brain responses to auditory and visual stimuli have been previously shown to depend on the level of spontaneous brain activity in the 8‐13 Hz range. Our aim was to determine whether somatosensory evoked responses are influenced by ongoing rhythmic activity in the 8‐13 Hz frequency range originating in the sensorimotor cortex (mu rhythm). Methods: We used a whole-head 122 channel magnetoencephalography (MEG) system to record somatosensory evoked fields (SEFs) in response to median nerve stimulation in 11 subjects. Spontaneous oscillations in the 8‐13 Hz band over the contralateral sensorimotor cortex were evaluated in 3 different pre-stimulus time intervals using wavelet analysis. Results: The N20m SEF deflection did not depend on pre-stimulus activity, while the amplitude of the P35m deflection, and to a lesser extent that of the P60m deflection, showed a small positive correlation with the amplitude of the pre-stimulus mu rhythm. Although the amplitude of the mu rhythm varied by a factor of 2.3‐5, the maximum variations in P35m and P60m amplitude were only 21 and 12%, respectively. The latencies of the peaks were not affected by the strength of the pre-stimulus mu rhythm. Conclusions: It appears that the first excitatory cortical response (N20m) is independent of the oscillatory state (8‐13 Hz frequency range) of the sensorimotor cortex. Later parts of the response (P35m and P60m) are also relatively stable compared with the large variations in mu rhythm. q 2000 Elsevier Science Ireland Ltd. All rights reserved.

It is often assumed that sensorimotor coordination is a feature of the sensorimotor areas of the neocortex only. The purpose of the present study was to examine how this phenomenon is reflected in the auditory cortex of man. Ten subjects were engaged in a stimulus-reaction paradigm, in which each of two acoustical tones was associated to either of two motor reactions. Magnetic fields recorded with a 122-channel magnetometer were modelled by current dipoles. The spatial coordinates as well as the amplitudes of the dipoles were analyzed from 90 to 110 ms after stimulus onset using discriminant analysis. The results suggest that the dipole trajectory in the auditory cortex of the right hemisphere and amplitudes of the dipoles in the auditory cortex of the left hemisphere already 90-110 ms after the beginning of the stimulus could be affected not only by physical features of the stimulus, but also by the motor task required as a reaction.

Introduction The brain spontaneously generates complex patterns of oscillatory activity whose dynamic signature is poorly understood. Identifying hidden structures in the electrophysiological time series could yield important insights into the function and mechanisms of large-scale neuronal interactions. Self-organized criticality (SOC) provides a general theoretical framework of how complex systems can evolve to a non-equilibrium state characterized by power-law scaling behavior [l]. This statistical property of the critical state stems from a non-linear process creating transient spatio-temporal correlations at wide scales and lends the system susceptible to change. We explore the possibility that the dynamical fingerprint of criticality in a family of complex systems is shared by oscillations in the human brain. Methods Spontaneous electrical brain activity from 8 normal subjects (aged 20-30 years, 1 female) was recorded using a whole-scalp magnetometer with 122 planar gradiometers. The subjects were seated in a magnetically shielded room and instructed to relax with eyes either open or closed in two separate 20-minute recording sessions. The measurements were replicated in 4 subjects, giving 12 data sets for each condition. The time-varying signal amplitude of narrow frequency bands was estimated by means of wavelet analysis. We focussed the analysis on the 8-13 Hz frequency range due to the high signal-to-noise ratio of the alpha rhythm. Results Wavelet transformation of the time series revealed amplitude fluctuations on wide time scales (Fig. 1). To detect power-law temporal correlations, characteristic for scale-invariant systems far from equilibrium, we employed the detrended fluctuation analysis [2]. The outcome was a remarkably invariant and persistent scaling behavior across subjects and conditions (Fig. 2), indicating a lack of ‘typical’ time scales for the duration and recurrence of oscillations. Least-squares fits in double logarithmic coordinates yielded self-similarity parameters

Transcranial magnetic stimulation (TMS) can be used to excite the human cortex noninvasively. TMS also activates scalp muscles and sensory receptors; additionally, the loud sound from the stimulating coil activates auditory pathways. These side effects complicate the interpretation of the results of TMS studies. For control experiments, the authors have designed a coil that can produce both real and sham stimulation without moving the coil. The sham TMS is similar to the real TMS, except for the different relative direction of the currents in the two loops of the figure of eight coil. While the real TMS elicited activation of hand muscles, sham TMS had no such effect; however, the auditory-evoked potentials were similar.

The human brain spontaneously generates neural oscillations with a large variability in frequency, amplitude, duration, and recurrence. Little, however, is known about the long-term spatiotemporal structure of the complex patterns of ongoing activity. A central unresolved issue is whether fluctuations in oscillatory activity reflect a memory of the dynamics of the system for more than a few seconds.We investigated the temporal correlations of network oscillations in the normal human brain at time scales ranging from a few seconds to several minutes. Ongoing activity during eyes-open and eyes-closed conditions was recorded with simultaneous magnetoencephalography and electroencephalography. Here we show that amplitude fluctuations of 10 and 20 Hz oscillations are correlated over thousands of oscillation cycles. Our analyses also indicated that these amplitude fluctuations obey power-law scaling behavior. The scaling exponents were highly invariant across subjects. We propose that the large variability, the long-range correlations, and the power-law scaling behavior of spontaneous oscillations find a unifying explanation within the theory of self-organized criticality, which offers a general mechanism for the emergence of correlations and complex dynamics in stochastic multiunit systems. The demonstrated scaling laws pose novel quantitative constraints on computational models of network oscillations. We argue that critical-state dynamics of spontaneous oscillations may lend neural networks capable of quick reorganization during processing demands.