Selective attention modulates high-frequency activity in the face-processing network

Müsch, Kathrin; Hamamé, Carlos M.; Perrone‐Bertolotti, Marcela; Minotti, Lorella; Kahane, Philippe; Engel, Andreas K.; Lachaux, Jean-Philippe; Schneider, Till R.

doi:10.1016/j.cortex.2014.06.006

Cited by 34 publications

(32 citation statements)

References 106 publications

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“…Intracranial recordings are a unique method to assess human neurocognition with high spatial and temporal resolution (Jacobs and Kahana, 2010; Dastjerdi et al, 2013; Parvizi et al, 2013; Musch et al, 2014; Foster et al, 2015; Noy et al, 2015), as shown in previous studies assessing emotions (Ponz et al, 2014; Hesse et al, 2016), cognition (Jensen et al, 2002; Meltzer et al, 2008; Noy et al, 2015), and, more particularly, interoception (Canales-Johnson et al, 2015). In our case, the two patients suffered from pharmacologically intractable epilepsy and were undergoing presurgical evaluation.…”

Section: Methodsmentioning

confidence: 99%

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Attention, in and Out: Scalp-Level and Intracranial EEG Correlates of Interoception and Exteroception

et al. 2017

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Interoception, the monitoring of visceral signals, is often presumed to engage attentional mechanisms specifically devoted to inner bodily sensing. In fact, most standardized interoceptive tasks require directing attention to internal signals. However, most studies in the field have failed to compare attentional modulations between internally- and externally-driven processes, thus probing blind to the specificity of the former. Here we address this issue through a multidimensional approach combining behavioral measures, analyses of event-related potentials and functional connectivity via high-density electroencephalography, and intracranial recordings. In Study 1, 50 healthy volunteers performed a heartbeat detection task as we recorded modulations of the heartbeat-evoked potential (HEP) in three conditions: exteroception, basal interoception (also termed interoceptive accuracy), and post-feedback interoception (sometimes called interoceptive learning). In Study 2, to evaluate whether key interoceptive areas (posterior insula, inferior frontal gyrus, amygdala, and somatosensory cortex) were differentially modulated by externally- and internally-driven processes, we analyzed human intracranial recordings with depth electrodes in these regions. This unique technique provides a very fine grained spatio-temporal resolution compared to other techniques, such as EEG or fMRI. We found that both interoceptive conditions in Study 1 yielded greater HEP amplitudes than the exteroceptive one. In addition, connectivity analysis showed that post-feedback interoception, relative to basal interoception, involved enhanced long-distance connections linking frontal and posterior regions. Moreover, results from Study 2 showed a differentiation between oscillations during basal interoception (broadband: 35–110 Hz) and exteroception (1–35 Hz) in the insula, the amygdala, the somatosensory cortex, and the inferior frontal gyrus. In sum, this work provides convergent evidence for the specificity and dynamics of attentional mechanisms involved in interoception.

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Section: Methodsmentioning

confidence: 99%

“…Time-frequency analysis was performed for basal interoception and exteroception by means of a windowed Fourier transform (window length: 250 ms, step 8 ms, window overlap 97%) (Gross, 2014; Musch et al, 2014). Time-frequency charts were normalized to baseline before the stimulus onset.…”

Section: Methodsmentioning

confidence: 99%

Attention, in and Out: Scalp-Level and Intracranial EEG Correlates of Interoception and Exteroception

et al. 2017

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“…This purely bottom-up driven signal -because face distractors were irrelevant for successful task performanceseems to be short lived, as indicated by the short latency of the gamma-band increase and the absence of a similar effect in long SOA trials. Previous studies also reported enhanced gamma-band power reflecting increased attention Gregoriou et al, 2009;Müsch et al, 2014;Siegel et al, 2008;Worden et al, 2000). Thus, the increased gammaband power to fearful faces presented ipsilaterally to targets may reflect bottom-up attentional orienting to face distractor processing.…”

Section: Neuronal Basis Of the Attentional Bottom-up Bias To Facesmentioning

confidence: 79%

“…Visual attention concurrently enhances gamma-band activity (>30 Hz) and decreases alpha-band activity (8-12 Hz) along the visual pathway Gregoriou et al, 2009;Müsch et al, 2014;Siegel et al, 2008;Worden et al, 2000). Furthermore, gamma-band activity increases during processing of taskirrelevant fearful faces (Luo et al, 2010).…”

Section: Introductionmentioning

confidence: 93%

Gamma-band activity reflects attentional guidance by facial expression

et al. 2017

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“…The low temporal resolution of fMRI makes it difficult to disentangle early bottom-up processing from later top-down and recurrent processing 8 . Some previous intracranial electroencephalography (iEEG) studies have used an explicit expression identification task, making task effects difficult to exclude [18][19][20] . Those that have used an implicit task have shown mixed results regarding whether early fusiform response is sensitive to expression 20,21 .…”

Section: Introductionmentioning

confidence: 99%

Posterior and Mid-Fusiform Contribute to Distinct Stages of Facial Expression Processing

Ghuman

2018

Preprint

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Though the fusiform is well-established as a key node in the face perception network, its role in facial expression processing remains unclear, due to competing models and discrepant findings. To help resolve this debate, we recorded from 17 subjects with intracranial electrodes implanted in face sensitive patches of the fusiform. Multivariate classification analysis showed that facial expression information is represented in fusiform activity, in the same regions that represent identity, though with a smaller effect size. Examination of the spatiotemporal dynamics revealed a functional distinction between posterior and mid-fusiform expression coding, with posterior fusiform showing an early peak of facial expression sensitivity at around 180 ms after subjects viewed a face and mid-fusiform showing a later and extended peak between 230 -460 ms. These results support the hypothesis that the fusiform plays a role in facial expression perception and highlight a qualitative functional distinction between processing in posterior and mid-fusiform, with each contributing to temporally segregated stages of expression perception.

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Selective attention modulates high-frequency activity in the face-processing network

Cited by 34 publications

References 106 publications

Attention, in and Out: Scalp-Level and Intracranial EEG Correlates of Interoception and Exteroception

Attention, in and Out: Scalp-Level and Intracranial EEG Correlates of Interoception and Exteroception

Gamma-band activity reflects attentional guidance by facial expression

Posterior and Mid-Fusiform Contribute to Distinct Stages of Facial Expression Processing

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