Search

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.

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.

Several lines of evidence suggest that visual information processing is segregated into the ventral “what” and dorsal “where” pathways. But the question whether information processing in the auditory system is also parceled to spatial and nonspatial domains remains open. In the present study, we performed simultaneous EEG and MEG recordings during auditory location and pitch delayed matching-to-sample tasks to find out whether working memory processing of the auditory stimulus attribute affects the transient components of the evoked potentials. In both tasks, identical blocks of tone stimuli of one of two frequencies were presented in one of two locations; the only difference between the tasks was the instruction to attend either to the frequency or to the location. In the match condition, the N1 latency was shorter and the N1m amplitude larger in the location task compared to the pitch task. Furthermore, the right-hemisphere generator of N1m elicited in the match condition of the location task was situated significantly medially to the N1m generator in the match condition of the pitch task. Latency and amplitude task-related differences in the N1/N1m components as well as the source location differences indicate at least partial segregation of neuronal mechanisms involved in working memory processing of spatial and nonspatial auditory information.

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.

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