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: In the P50 gating or conditioning-testing (C-T) paradigm, the P50 response, a small positive midlatency ( approximately 50 ms after stimulus onset) component of the human auditory evoked potential (AEP), is reduced towards the second click (S2) as compared to the response to the first click (S1). This phenomenon is called sensory gating. The putative function of sensory gating is thought to protect subjects from being flooded by irrelevant stimuli. Comparative studies have been done in rats in order to elucidate the underlying neural substrate of sensory gating. However, for a direct comparison of rat and human AEP components, it is imperative for both components to show similar characteristics. The amount of sensory gating in humans is dependent on repetitive stimulation and the interstimulus interval (ISI). In the present study effects of repetitive stimulation (Experiment 1) and various ISIs (Experiment 2) were determined on rat AEP components. The results demonstrate that gating is not limited to a restricted cortical area or a single midlatency component and that repetitive stimulation and ISI affect gating of several rat AEP components. Components such as the vertex P17 and N22 show a decrease in gating within several S1-S2 presentations, mainly due to a decrease in amplitude to S1 (Experiment 1). Gating for vertex components (such as the P17, N22 and N50) is ISI dependent (Experiment 2), but there is no interval in the 200-600 ms range at which optimal gating occurs. The ISI effects on gating are due to an increase of the amplitude to S2. The results have implications for the discussion about the rat homologue of the human P50.Biological Psychology 03/2001; 55(3):195-213. · 3.40 Impact Factor
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ABSTRACT: We studied the effect of different sound intensities on the auditory evoked gamma-band response (GBR). Previous studies observed oscillatory gamma activity in the auditory cortex of animals and humans. For the visual modality, it has been demonstrated that the GBR can be modulated by top-down (attention, memory) as well as bottom-up factors (stimulus properties). Therefore, we expected to find a sound intensity modulation for the auditory GBR. 21 healthy participants without hearing deficits were investigated in a forced-choice discrimination task. Sinusoidal tones were presented at three systematically varied sound intensities (30, 45, 60 dB hearing level). The results of the auditory evoked potentials were predominantly consistent with previous studies. Furthermore, we observed an augmentation of the evoked GBR with increasing sound intensity. The analysis indicated that this intensity difference in the GBR amplitude most likely arises from increased phase-locking. The results demonstrate a distinct dependency between sound intensity and gamma-band oscillations. Future experiments that investigate the relationship between auditory evoked GBRs and higher cognitive processes should therefore select stimuli with an adequate sound intensity and control this variable to avoid confounding effects. In addition, it seems that gamma-band activity is more sensitive to exogenous stimulus parameters than evoked potentials.International Journal of Psychophysiology 09/2007; 65(2):152-61. · 2.04 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