Ten subjects performed a time production task, in which they were instructed to press a button four seconds after the presentation of an auditory stimulus. Two seconds after the button press they received either auditory or visual feedback on the temporal accuracy of their response. In such a paradigm negative slow brain potentials can be recorded preceding the response (Movement Preceding Negativity, MPN) as well as preceding the feedback stimulus (Stimulus Preceding Negativity, SPN). Spatiotemporal dipole modelling is used to gain insight in the possible generators of MPN and SPN. From the models it follows that the MPN can be described by one contralateral radial dipole and a bilateral pair of tangential dipoles. All three dipoles are located near central electrode positions, so the generators of the MPN probably reside within the motor cortex. The SPN is modelled by a bilateral frontotemporal pair of dipoles, hypothetically representing activation of the Insulae Reili. The insular cortex is involved in the processing of affective-motivational input, such as carried by the feedback in the present paradigm. However, processing of the information content of the feedback stimulus might by itself also activate the frontal cortex. Both the response and the feedback stimulus are followed by a positive peak, which can be described by the same deep posterior dipole. Both peaks probably represent a P3, which is related to context updating.

Many researchers have used off-line techniques for the automatic detection of electromyogram (EMG) onset. However, very little is known about the accuracy of these methods. In the present study, five such methods are evaluated and their accuracy is reported. Five subjects were asked to produce fast (ballistic) and slow (ramp) contractions with thumb and index finger of the right hand in a simple reaction time task. EMG was recorded from the first dorsal interosseus muscle, and onsets were visually determined in the raw EMG. These onsets were compared with the onsets produced by the automated methods on the rectified and low-pass filtered EMG. Four of the automated methods produced very reliable estimates of the visually determined onsets, at least when additional constraints upon the initial estimates were made. Studies using automated methods for EMG onset detection should report findings about their accuracy.

In previous EEG experiments we have presented a time estimation task to our subjects, who had to press a button with either the left or right index finger 3 s after an auditory warning stimulus (WS). Two seconds later a visual Knowledge of Results (KR) stimulus was presented on a screen in front, informing them about whether the movement had been made in the correct time window (a vertical line), whether it was too early (a minus sign) or too late (a plus sign). The potential distribution underlying the anticipatory attention for the KR stimulus suggested a right hemisphere network in which the prefrontal cortex, the insula Reili and the parietal cortex were involved. In the present positron emission tomography (PET) activation study we aimed to further localize the exact positions of these regions, using the same paradigm. Two conditions were compared in which the WS had to be followed by a button press with the left index finger. In experimental condition A, subjects received true information about their performance, while in condition B false information was given, utilizing the same stimuli, but randomly, thus without any relation to the actual performance. In both conditions identical stimuli were presented and identical movements were made. Therefore we applied statistical parameter mapping (SPM) for comparison of condition A with B in order to identify regional increases in perfusion related to the anticipation and use of the KR. We found in line with our predictions a right hemisphere activation of (1) BA45, (2) the junction of the posterior insula with the temporal transverse gyrus and (3) the posterior part of the parietal cortex. This activation pattern was accompanied by a better performance due to KR. A second, though not predicted, effect was the increase in correct responses during the last two sessions compared to the first two sessions, independent of KR. This learning effect was accompanied by an activation of BA46 and the supplementary motor area (SMA), again in the right hemisphere. Summarizing, two different prefrontal areas in the right hemisphere were activated: a more ventral area, related to the use of external stimuli providing feedback about a past performance, in order to produce movements in time, and another mid-dorsal one, related to temporal programming on the basis of internal cues.

Methods like dipole source localization require an exact specification of the co-ordinates of electrode positions. Different values for the co-ordinates of F3, F4, P3 and P4 are encountered in literature. This is due to the unexpected complexity of the calculations involved and aggravated by an inaccurate but widely used control procedure for the placement of these electrodes. We present a table of co-ordinates for the 10-20 system together with a method for determining the co-ordinates of mid-way positions within the 10-20 system. The consequence of using erroneous co-ordinates on the accuracy of dipole source localization is discussed.

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A major problem in the study of brain potentials is the occurrence of ocular artefacts in electro-encephalograms. OAs can be monitored by placing electrodes near the eyes and recording electro-oculograms. In the paper, two OA correction methods based on simulations are compared; the Jervis method and the vandenBerg method. In most simulations, the residual (the difference between the original EEG and the EEG after correction) is smaller in amplitude and variance for the vandenBerg method than for the Jervis method. When eye movements and blinks are given different factors, the blinks are not removed completely. For both methods, the residual of the blinks increases with the differences between the model parameters for the blinks and for eye movements. The occurrence of a slow negative wave greatly disturbs the estimated parameters and thus the residuals of the Jervis method. For the vandenBerg method, there is only a very small effect. The conclusion from correcting a recorded data set, which does not contain a slow negative wave, is that, for these data, there is no evidence that one method is better than the other.