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

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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.

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Clusters with significant changes in source coherence were found for the congruence effect in the beta-band (upper row), as well as for the attention effect in the alpha-band (middle row) and theta-band (bottom row).Each significant coherence cluster is illustrated with colors indicating the number of connections of a given location to other locations within the cluster (see methods for details). For the bar plots on the right hand side of the figure coherence and imaginary part of coherency were calculated between all voxels constituting a significant cluster. Bars represent average coherence or average imaginary part of coherency, respectively. Error bars denote standard errors, and asterisks indicate significant differences. Since all condition differences of average imaginary part of coherency are significant, it is unlikely that the source cluster coherence results are compromised by volume conduction. Abbreviations: Coh – coherence, ImCoh – imaginary part of coherency, Co – congruent, In – incongruent, At – attended, Un – unattended.
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f5: Clusters with significant changes in source coherence were found for the congruence effect in the beta-band (upper row), as well as for the attention effect in the alpha-band (middle row) and theta-band (bottom row).Each significant coherence cluster is illustrated with colors indicating the number of connections of a given location to other locations within the cluster (see methods for details). For the bar plots on the right hand side of the figure coherence and imaginary part of coherency were calculated between all voxels constituting a significant cluster. Bars represent average coherence or average imaginary part of coherency, respectively. Error bars denote standard errors, and asterisks indicate significant differences. Since all condition differences of average imaginary part of coherency are significant, it is unlikely that the source cluster coherence results are compromised by volume conduction. Abbreviations: Coh – coherence, ImCoh – imaginary part of coherency, Co – congruent, In – incongruent, At – attended, Un – unattended.

Mentions: In the analysis of source coherence, three significant clusters were identified in the time window corresponding to the first intensity change (Fig. 5). These clusters represent regions in which the experimental conditions modulated coherence in a specific frequency range. Crossmodal congruence modulated coherence in the beta-band. Attention was associated with two clusters in the alpha- and theta-band respectively. No significant clusters were found for the interaction between attention and congruence. The clustering approach resulted in a pooling of frequencies slightly different from the frequency bands predefined for the analysis of spectral power. The beta-band cluster arose in a narrow 30-32 Hz range in regions including left medial parietal cortex as well as right superior and middle temporal gyrus. These regions exhibited stronger coherence for the incongruent condition compared to the congruent condition in the beta-band. One of the two clusters associated with changes in attention concentrated coherence between 8–12 Hz in widespread posterior regions in occipital, parietal and temporal cortex. Within this cluster, coherence decreased for the attended condition compared to the unattended condition. Moreover, the allocation of attention was found to increase theta-band coherence in a cluster comprising bilateral inferior frontal and precentral gyrus, left middle temporal gyrus, and right medial frontal cortex. These clusters, identified with coherence analysis, could not be explained by volume conduction effects (see bar plots on the right hand side of Fig. 5). Average imaginary part of coherency, which reflects non-zero phase-lag synchronisation and is therefore not influenced by volume conduction, was significantly different between conditions within the clusters (beta congruence effect: t18 = −2.70, p = 0.015; alpha attention effect: t18 = −4.10, p < 0.001; theta attention effect: t18 = 3.62, p = 0.002). These effects mirror the significant differences found for coherence (beta congruence effect: t18 = −8.56, p < 0.001; alpha attention effect: t18 = −9.00, p < 0.001; theta attention effect: t18 = 8.75, p < 0.001). This strongly suggests that volume conduction did not contaminate the significant coherence cluster results.


Oscillatory brain activity during multisensory attention reflects activation, disinhibition, and cognitive control
Clusters with significant changes in source coherence were found for the congruence effect in the beta-band (upper row), as well as for the attention effect in the alpha-band (middle row) and theta-band (bottom row).Each significant coherence cluster is illustrated with colors indicating the number of connections of a given location to other locations within the cluster (see methods for details). For the bar plots on the right hand side of the figure coherence and imaginary part of coherency were calculated between all voxels constituting a significant cluster. Bars represent average coherence or average imaginary part of coherency, respectively. Error bars denote standard errors, and asterisks indicate significant differences. Since all condition differences of average imaginary part of coherency are significant, it is unlikely that the source cluster coherence results are compromised by volume conduction. Abbreviations: Coh – coherence, ImCoh – imaginary part of coherency, Co – congruent, In – incongruent, At – attended, Un – unattended.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f5: Clusters with significant changes in source coherence were found for the congruence effect in the beta-band (upper row), as well as for the attention effect in the alpha-band (middle row) and theta-band (bottom row).Each significant coherence cluster is illustrated with colors indicating the number of connections of a given location to other locations within the cluster (see methods for details). For the bar plots on the right hand side of the figure coherence and imaginary part of coherency were calculated between all voxels constituting a significant cluster. Bars represent average coherence or average imaginary part of coherency, respectively. Error bars denote standard errors, and asterisks indicate significant differences. Since all condition differences of average imaginary part of coherency are significant, it is unlikely that the source cluster coherence results are compromised by volume conduction. Abbreviations: Coh – coherence, ImCoh – imaginary part of coherency, Co – congruent, In – incongruent, At – attended, Un – unattended.
Mentions: In the analysis of source coherence, three significant clusters were identified in the time window corresponding to the first intensity change (Fig. 5). These clusters represent regions in which the experimental conditions modulated coherence in a specific frequency range. Crossmodal congruence modulated coherence in the beta-band. Attention was associated with two clusters in the alpha- and theta-band respectively. No significant clusters were found for the interaction between attention and congruence. The clustering approach resulted in a pooling of frequencies slightly different from the frequency bands predefined for the analysis of spectral power. The beta-band cluster arose in a narrow 30-32 Hz range in regions including left medial parietal cortex as well as right superior and middle temporal gyrus. These regions exhibited stronger coherence for the incongruent condition compared to the congruent condition in the beta-band. One of the two clusters associated with changes in attention concentrated coherence between 8–12 Hz in widespread posterior regions in occipital, parietal and temporal cortex. Within this cluster, coherence decreased for the attended condition compared to the unattended condition. Moreover, the allocation of attention was found to increase theta-band coherence in a cluster comprising bilateral inferior frontal and precentral gyrus, left middle temporal gyrus, and right medial frontal cortex. These clusters, identified with coherence analysis, could not be explained by volume conduction effects (see bar plots on the right hand side of Fig. 5). Average imaginary part of coherency, which reflects non-zero phase-lag synchronisation and is therefore not influenced by volume conduction, was significantly different between conditions within the clusters (beta congruence effect: t18 = −2.70, p = 0.015; alpha attention effect: t18 = −4.10, p < 0.001; theta attention effect: t18 = 3.62, p = 0.002). These effects mirror the significant differences found for coherence (beta congruence effect: t18 = −8.56, p < 0.001; alpha attention effect: t18 = −9.00, p < 0.001; theta attention effect: t18 = 8.75, p < 0.001). This strongly suggests that volume conduction did not contaminate the significant coherence cluster results.

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