Good practice for conducting and reporting MEG research

Groß, Joachim; Baillet, Sylvain; Barnes, Gareth R.; Henson, Richard N.; Hillebrand, Arjan; Jensen, Ole; Jerbi, Karim; Litvak, Vladimir; Maess, Burkhard; Oostenveld, Robert; Parkkonen, Lauri; Taylor, Jason R.; Wassenhove, Virginie van; Wibral, Michael; Schoffelen, Jan‐Mathijs

doi:10.1016/j.neuroimage.2012.10.001

Cited by 659 publications

(570 citation statements)

References 128 publications

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“…The inverse solver used to localize the sources was then applied on the averaged normed evoked data. The normalization procedure was done to alleviate source cancellation when averaging sources within a label of interest, and across subjects (Gross et al, 2013). The comparisons of evoked responses between conditions were computed using a non-parametric permutation test.…”

Section: Event-related Fields and Source Reconstructionmentioning

confidence: 99%

Encoding of event timing in the phase of neural oscillations

2014

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a b s t r a c t a r t i c l e i n f oTime perception is a critical component of conscious experience. To be in synchrony with the environment, the brain must deal not only with differences in the speed of light and sound but also with its computational and neural transmission delays. Here, we asked whether the brain could actively compensate for temporal delays by changing its processing time. Specifically, can changes in neural timing or in the phase of neural oscillation index perceived timing? For this, a lag-adaptation paradigm was used to manipulate participants' perceived audiovisual (AV) simultaneity of events while they were recorded with magnetoencephalography (MEG). Desynchronized AV stimuli were presented rhythmically to elicit a robust 1 Hz frequency-tagging of auditory and visual cortical responses. As participants' perception of AV simultaneity shifted, systematic changes in the phase of entrained neural oscillations were observed. This suggests that neural entrainment is not a passive response and that the entrained neural oscillation shifts in time. Crucially, our results indicate that shifts in neural timing in auditory cortices linearly map participants' perceived AV simultaneity. To our knowledge, these results provide the first mechanistic evidence for active neural compensation in the encoding of sensory event timing in support of the emergence of time awareness.

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Section: Event-related Fields and Source Reconstructionmentioning

confidence: 99%

Encoding of event timing in the phase of neural oscillations

2014

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“…There was no overlap between the selected epochs. Visual inspection was preferred over automatic approaches, since these may introduce complex new artifacts or biases [8].…”

Section: Eeg Recordingsmentioning

confidence: 99%

Increased power of resting-state gamma oscillations in autism spectrum disorder detected by routine electroencephalography

Diessen

Senders

Jansen

et al. 2014

Eur Arch Psychiatry Clin Neurosci

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Experimental studies suggest that increased resting-state power of gamma oscillations is associated with autism spectrum disorder (ASD). To extend the clinical applicability of this finding, we retrospectively investigated routine electroencephalography (EEG) recordings of 19 patients with ASD and 19 age-and gender-matched controls. Relative resting-state condition gamma spectral power was variable, but on average significantly increased in children with ASD. This effect remained when excluding electrodes associated with myogenic gamma activity. These findings further indicate that increased resting-state gamma activity characterizes a subset of ASD and may also be detected by routine EEG as a clinically accessible and well-tolerated investigation.

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“…However, despite these disadvantages, subtractive baseline correction may be Manuscript in preparation [v1.1.3;Fri Jan 13 12:31:19 2017;#324bb4c] the natural choice for some researchers because it is the standard approach in EEG research (e.g. Gross et al, 2013;Woodman, 2010).…”

Section: Of 25mentioning

confidence: 99%

Safe and sensible baseline correction of pupil-size data

Mathôt

Fabius

Heusden

et al. 2017

Preprint

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Measurement of pupil size (pupillometry) has recently gained renewed interest from psychologists, but there is little agreement on how pupil-size data is best analyzed. Here we focus on one aspect of pupillometric analyses: baseline correction, that is, analyzing changes in pupil size relative to a baseline period. Baseline correction is useful in experiments that investigate the effect of some experimental manipulation on pupil size. In such experiments, baseline correction improves statistical power by taking into account random fluctuations in pupil size over time. However, we show that baseline correction can also distort data if unrealistically small pupil sizes are recorded during the baseline period, which can easily occur due to eye blinks, data loss, or other distortions. Divisive baseline correction (corrected pupil size = pupil size / baseline) is affected more strongly by such distortions than subtractive baseline correction (corrected pupil size = pupil size - baseline). We make four recommendations for safe and sensible baseline correction of pupil-size data: 1) use subtractive baseline correction; 2) visually compare your corrected and uncorrected data; 3) be wary of pupil-size effects that emerge faster than the latency of the pupillary response allows (within ±220 ms after the manipulation that induces the effect); and 4) remove trials on which baseline pupil size is unrealistically small (indicative of blinks and other distortions).

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Good practice for conducting and reporting MEG research

Cited by 659 publications

References 128 publications

Encoding of event timing in the phase of neural oscillations

Encoding of event timing in the phase of neural oscillations

Increased power of resting-state gamma oscillations in autism spectrum disorder detected by routine electroencephalography

Safe and sensible baseline correction of pupil-size data

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