Evoked potentials to auditory movement sensation in duplex perception

Laufer, Ilan; Pratt, Hillel

doi:10.1016/s1388-2457(03)00083-x

Cited by 38 publications

(18 citation statements)

References 61 publications

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“…This slight discrepancy in location of the onset response may be due to the low spatial resolution of the method. However, in earlier studies using noise bursts and speech sounds, N 100 was located to primary auditory cortex (e.g., Laufer and Pratt, 2003b;Sinai and Pratt, 2003). This indicates that the source estimation method and the number of electrodes used provide valid results, and the discrepancy between onset response and change response source locations reflects a real difference.…”

Section: Discussionmentioning

confidence: 86%

“…The SnPM method estimates the probability distribution by using a randomization procedure, corrects for multiple comparisons and has the highest possible statistical power (Nichols and Holmes, 2002). The SnPM method in the context of ERP source estimation was validated in our previous studies by comparing its results with more conventional ANOVA results (Laufer and Pratt, 2003b;Sinai and Pratt, 2003).…”

Section: Erp Functional Imagingmentioning

confidence: 99%

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Auditory-evoked potentials to frequency increase and decrease of high- and low-frequency tones

Pratt

Starr

Michalewski

et al. 2009

Clinical Neurophysiology

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a b s t r a c tObjective: To define cortical brain responses to large and small frequency changes (increase and decrease) of high-and low-frequency tones. Methods: Event-Related Potentials (ERPs) were recorded in response to a 10% or a 50% frequency increase from 250 or 4000 Hz tones that were approximately 3 s in duration and presented at 500-ms intervals. Frequency increase was followed after 1 s by a decrease back to base frequency. Frequency changes occurred at least 1 s before or after tone onset or offset, respectively. Subjects were not attending to the stimuli. Latency, amplitude and source current density estimates of ERPs were compared across frequency changes. Results: All frequency changes evoked components P 50 , N 100 , and P 200 . N 100 and P 200 had double peaks at bilateral and right temporal sites, respectively. These components were followed by a slow negativity (SN). The constituents of N 100 were predominantly localized to temporo-parietal auditory areas. The potentials and their intracranial distributions were affected by both base frequency (larger potentials to low frequency) and direction of change (larger potentials to increase than decrease), as well as by change magnitude (larger potentials to larger change). The differences between frequency increase and decrease depended on base frequency (smaller difference to high frequency) and were localized to frontal areas. Conclusions: Brain activity varies according to frequency change direction and magnitude as well as base frequency. Significance: The effects of base frequency and direction of change may reflect brain networks involved in more complex processing such as speech that are differentially sensitive to frequency modulations of high (consonant discrimination) and low (vowels and prosody) frequencies.

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Section: Discussionmentioning

confidence: 86%

Section: Erp Functional Imagingmentioning

confidence: 99%

Auditory-evoked potentials to frequency increase and decrease of high- and low-frequency tones

Pratt

Starr

Michalewski

et al. 2009

Clinical Neurophysiology

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show abstract

Section: Methodsmentioning

confidence: 99%

Cortical evoked potentials to an auditory illusion: Binaural beats

Pratt

Starr

Michalewski

et al. 2009

Clinical Neurophysiology

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“…The SnPM method estimates the probability distribution of the data set being analyzed by using a randomization procedure, corrects for multiple comparisons and has the highest possible statistical power (Nichols and Holmes, 2002). The SnPM method in the context of ERP source estimation was validated in our earlier studies by comparing its results with more conventional ANOVA results (Laufer and Pratt, 2003;Sinai and Pratt, 2003). Specifically, in this study we used the 'pseudo-t' statistic which reduced noise in the data by averaging over adjacent voxels (Nichols and Holmes, 2002).…”

Section: Erp Functional Imagingmentioning

confidence: 99%