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Oscillatory brain activity during multisensory attention reflects activation, disinhibition, and cognitive control

View Article: PubMed Central - PubMed

ABSTRACT

In this study, we used a novel multisensory attention paradigm to investigate attention-modulated cortical oscillations over a wide range of frequencies using magnetencephalography in healthy human participants. By employing a task that required the evaluation of the congruence of audio-visual stimuli, we promoted the formation of widespread cortical networks including early sensory cortices as well as regions associated with cognitive control. We found that attention led to increased high-frequency gamma-band activity and decreased lower frequency theta-, alpha-, and beta-band activity in early sensory cortex areas. Moreover, alpha-band coherence decreased in visual cortex. Frontal cortex was found to exert attentional control through increased low-frequency phase synchronisation. Crossmodal congruence modulated beta-band coherence in mid-cingulate and superior temporal cortex. Together, these results offer an integrative view on the concurrence of oscillations at different frequencies during multisensory attention.

No MeSH data available.


Related in: MedlinePlus

Grand mean time-frequency representations of spectral power corresponding to the stimulus onset time window (left) and the change onset window (right) for posterior sensor sites (inset at the upper left).The frequency range was split such that higher frequencies are illustrated in the upper two panels while the lower frequencies are shown below. Oscillatory power was calculated across conditions relative to the pre-cue baseline. Colors represent percentage signal change with respect to pre-cue baseline activity.
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f2: Grand mean time-frequency representations of spectral power corresponding to the stimulus onset time window (left) and the change onset window (right) for posterior sensor sites (inset at the upper left).The frequency range was split such that higher frequencies are illustrated in the upper two panels while the lower frequencies are shown below. Oscillatory power was calculated across conditions relative to the pre-cue baseline. Colors represent percentage signal change with respect to pre-cue baseline activity.

Mentions: We selected frequency bands based on visual inspection of the grand average time-frequency representations as follows: 2.5–5 Hz delta/theta, 7.5–10 Hz alpha, 15–25 Hz beta, 60–80 Hz gamma. Figure 2 depicts spectral power averaged across posterior sensors with respect to the stimulus onset time window as well as the change time window. The low frequency band in the delta/theta range was defined based on time-frequency representations from frontal sensors not shown here (but see the topographical distributions spectral power in Fig. 3). For briefness we refer to this low frequency range as theta in the following (for a critical discussion of the common delta/theta distinction, see Lega et al.18). For statistical comparisons in source space we averaged power across all time bins in each time window separately. We restricted the stimulus onset and the change onset time windows to 0–500 ms to capture primarily activity associated with early stimulus processing and to avoid potential overlap with the respective subsequent intensity change. (Depending on the jitter interval, the change onset could follow the stimulus offset after 450 ms, and the second intensity change could follow the offset of the first change also after 450 ms).


Oscillatory brain activity during multisensory attention reflects activation, disinhibition, and cognitive control
Grand mean time-frequency representations of spectral power corresponding to the stimulus onset time window (left) and the change onset window (right) for posterior sensor sites (inset at the upper left).The frequency range was split such that higher frequencies are illustrated in the upper two panels while the lower frequencies are shown below. Oscillatory power was calculated across conditions relative to the pre-cue baseline. Colors represent percentage signal change with respect to pre-cue baseline activity.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5015072&req=5

f2: Grand mean time-frequency representations of spectral power corresponding to the stimulus onset time window (left) and the change onset window (right) for posterior sensor sites (inset at the upper left).The frequency range was split such that higher frequencies are illustrated in the upper two panels while the lower frequencies are shown below. Oscillatory power was calculated across conditions relative to the pre-cue baseline. Colors represent percentage signal change with respect to pre-cue baseline activity.
Mentions: We selected frequency bands based on visual inspection of the grand average time-frequency representations as follows: 2.5–5 Hz delta/theta, 7.5–10 Hz alpha, 15–25 Hz beta, 60–80 Hz gamma. Figure 2 depicts spectral power averaged across posterior sensors with respect to the stimulus onset time window as well as the change time window. The low frequency band in the delta/theta range was defined based on time-frequency representations from frontal sensors not shown here (but see the topographical distributions spectral power in Fig. 3). For briefness we refer to this low frequency range as theta in the following (for a critical discussion of the common delta/theta distinction, see Lega et al.18). For statistical comparisons in source space we averaged power across all time bins in each time window separately. We restricted the stimulus onset and the change onset time windows to 0–500 ms to capture primarily activity associated with early stimulus processing and to avoid potential overlap with the respective subsequent intensity change. (Depending on the jitter interval, the change onset could follow the stimulus offset after 450 ms, and the second intensity change could follow the offset of the first change also after 450 ms).

View Article: PubMed Central - PubMed

ABSTRACT

In this study, we used a novel multisensory attention paradigm to investigate attention-modulated cortical oscillations over a wide range of frequencies using magnetencephalography in healthy human participants. By employing a task that required the evaluation of the congruence of audio-visual stimuli, we promoted the formation of widespread cortical networks including early sensory cortices as well as regions associated with cognitive control. We found that attention led to increased high-frequency gamma-band activity and decreased lower frequency theta-, alpha-, and beta-band activity in early sensory cortex areas. Moreover, alpha-band coherence decreased in visual cortex. Frontal cortex was found to exert attentional control through increased low-frequency phase synchronisation. Crossmodal congruence modulated beta-band coherence in mid-cingulate and superior temporal cortex. Together, these results offer an integrative view on the concurrence of oscillations at different frequencies during multisensory attention.

No MeSH data available.


Related in: MedlinePlus