Sequential changes of auditory processing during target detection: motor responding versus mental counting.
ABSTRACT Brain potentials evoked to non-targets in an auditory target detection task changed in amplitude, duration, polarity, and scalp topography as a function of position in the stimulus sequence relative to the target. (1) A negative prestimulus readiness like-potential, or RP, the poststimulus N100, and a late slow wave to non-targets immediately after the target were reduced in amplitude compared to non-targets immediately before the target. The amplitudes of these potentials after the target then increased in size as a linear function of the number of non-targets in the sequence. (2) The amplitudes of the positive components, P50 and P200, were larger to non-targets immediately after the target than to non-targets immediately before the targets. P50 amplitude then decreased to subsequent non-targets in the sequence in a linear manner; P200 amplitude was reduced equivalently to all subsequent non-targets. (3) The duration of the P200 component could extend into the time domain when the P300 to targets would occur. The P200 component to non-targets was therefore designated 'P200/300'. The duration of the P200/300 component was shorter to non-targets immediately after the target than to non-targets immediately before the targets. P200/300 duration then extended in a linear manner to subsequent non-targets in the sequence and approached the peak latency of the P300 evoked by targets. (4) The anterior/posterior scalp distribution of P50 and the polarity of the late slow wave to non-targets changed as a function of non-target position in the sequence. The subject's response to the targets (button press or mental count) influenced these sequential effects. Linear trends for sequence were present in the press but not the count conditions for the amplitude of the RP, N100, and P300; linear trends for P50, P200/300 duration, and the late slow wave were found in both the press and count conditions. Reaction time was speeded as a function of the number of preceding targets. These dynamic changes in the processing of auditory signals were attributed to an interaction of attention and the subjective expectancies for both the appearance of a target stimulus and the requirement to make a motor response.
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ABSTRACT: Increases in the target-to-target interval (TTI) systematically enhance the amplitude of the target P300 ERP component. Research examining changes in nontarget P300 related to nontarget-to-nontarget interval (NNI) or sequential probability manipulations has produced inconsistent results, with some studies reporting no enhancement in nontarget P300 and others finding response profiles analogous to TTI effects. Our aim was to clarify these differences. All participants completed a specially designed auditory equiprobable Go/NoGo task with manipulations of TTI and NNI while their EEG activity was recorded. P300 amplitudes were extracted using temporal PCA with Varimax rotation. P3b to targets and nontargets increased systematically as respective TTIs/NNIs increased, but this change did not differ between stimulus types. The Slow Wave did not show any effect of interval, but was more positive to targets than nontargets when interval was collapsed. P3b findings show that matching-stimulus interval effects are not restricted to targets, but discrepancies relative to previous research suggest that NNI effects in P3b may depend on additional processing of nontarget stimuli.International journal of psychophysiology: official journal of the International Organization of Psychophysiology 06/2014; · 3.05 Impact Factor
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ABSTRACT: Previous research has shown that as the stimulus-to-matching-stimulus interval (including the target-to-target interval, TTI, and nontarget-to-nontarget interval, NNI) increases, the amplitude of the P300 ERP component increases systematically. Here, we extended previous P300 research and explored TTI and NNI effects on the various ERP components elicited in an auditory equiprobable Go/NoGo task. We also examined whether a similar mechanism was underpinning interval effects in early ERP components (e.g., N1). Thirty participants completed a specially-designed variable-ISI equiprobable task whilst their EEG activity was recorded. Component amplitudes were extracted using temporal PCA with unrestricted Varimax rotation. As expected, N1, P2, and P3b amplitudes increased as TTI and NNI increased, however, Processing Negativity (PN) and Slow Wave (SW) did not show the same systematic change with interval increments. To determine the origin of interval effects in sequential processing, a multiple regression analysis was conducted on each ERP component including stimulus type, interval, and all preceding components as predictors. These analyses showed that matching-stimulus interval predicted N1, P3b, and weakly predicted P2, but not PN or SW; SW was determined by P3b only. These results suggest that N1, P3b, and to some extent, P2, are affected by a similar temporal mechanism. However, the dissimilar pattern of results obtained for sequential ERP components indicates that matching-stimulus intervals are not affecting all aspects of stimulus processing. This argues against a global mechanism, such as a pathway-specific refractory effect, and suggests that stimulus processing is occurring in parallel pathways, some of which are not affected by temporal manipulations of matching-stimulus interval.International journal of psychophysiology: official journal of the International Organization of Psychophysiology 07/2014; · 3.05 Impact Factor
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ABSTRACT: In the present study, we investigated how the electrical activity in the sensorimotor cortex contributes to improved cognitive processing capabilities and how SMR (sensorimotor rhythm, 12-15Hz) neurofeedback training modulates it. Previous evidence indicates that higher levels of SMR activity reduce sensorimotor interference and thereby promote cognitive processing. Participants were randomly assigned to two groups, one experimental (N=10) group receiving SMR neurofeedback training, in which they learned to voluntarily increase SMR, and one control group (N=10) receiving sham feedback. Multiple cognitive functions and electrophysiological correlates of cognitive processing were assessed before and after 10 neurofeedback training sessions. The experimental group but not the control group showed linear increases in SMR power over training runs, which was associated with behavioural improvements in memory and attentional performance. Additionally, increasing SMR led to a more salient stimulus processing as indicated by increased N1 and P3 event-related potential amplitudes after the training as compared to the pre-test. Finally, functional brain connectivity between motor areas and visual processing areas was reduced after SMR training indicating reduced sensorimotor interference. These results indicate that SMR neurofeedback improves stimulus processing capabilities and consequently leads to improvements in cognitive performance. The present findings contribute to a better understanding of the mechanisms underlying SMR neurofeedback training and cognitive processing and implicate that SMR neurofeedback might be an effective cognitive training tool.Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology 04/2014; · 3.12 Impact Factor