Spatio-temporal dynamics of face perception

Muukkonen, Ilkka; Ölander, Kaisu; Numminen, Jussi; Salmela, Viljami

doi:10.1016/j.neuroimage.2020.116531

Cited by 41 publications

(24 citation statements)

References 55 publications

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“…Indeed, we observed that the centrality of these nodes is larger for faces than for non-face stimuli from the initial stages of processing, in contrast with classical ERP studies, suggesting that facesensitive neural activity arises only in the N170 component. In this study, the analysis of the cortical activity in terms of event-related network changes reveals an earlier primacy of face over non-face stimuli, in line with a very recent study which, combining EEG and fMRI, showed that the coding of facial expressions from occipital to the ventral temporal cortex starts in this time frame (Muukkonen et al, 2020). Furthermore, this result supports another recent study showing that face-sensitive neural activity can be detected already in the P1 component (Tanaka, 2018).…”

Section: Discussionsupporting

confidence: 89%

Event‐related network changes unfold the dynamics of cortical integration during face processing

Maffei

Sessa

2021

Psychophysiology

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Face perception arises from a collective activation of brain regions in the occipital, parietal and temporal cortices. Despite the wide acknowledgment that these regions act in an intertwined network, the network behavior itself is poorly understood. Here we present a study in which time‐varying connectivity estimated from EEG activity elicited by facial expressions presentation was characterized using graph‐theoretical measures of node centrality and global network topology. Results revealed that face perception results from a dynamic reshaping of the network architecture, characterized by the emergence of hubs located in the occipital and temporal regions of the scalp. The importance of these nodes can be observed from the early stages of visual processing and reaches a climax in the same time‐window in which the face‐sensitive N170 is observed. Furthermore, using Granger causality, we found that the time‐evolving centrality of these nodes is associated with ERP amplitude, providing a direct link between the network state and local neural response. Additionally, investigating global network topology by means of small‐worldness and modularity, we found that face processing requires a functional network with a strong small‐world organization that maximizes integration, at the cost of segregated subdivisions. Interestingly, we found that this architecture is not static, but instead, it is implemented by the network from stimulus onset to ~200 ms. Altogether, this study reveals the event‐related changes underlying face processing at the network level, suggesting that a distributed processing mechanism operates through dynamically weighting the contribution of the cortical regions involved.

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Section: Discussionsupporting

confidence: 89%

Event‐related network changes unfold the dynamics of cortical integration during face processing

Maffei

Sessa

2021

Psychophysiology

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“…Indeed, we observed that the centrality of these nodes is larger for faces than for non-face stimuli from the initial stages of processing, in contrast with classical ERP studies suggesting that face-sensitive neural activity arises only in the N170 component. In this study, the analysis of the cortical activity in terms of event-related network changes reveals an earlier primacy of face over non-face stimuli, in line with a very recent study which, combining EEG and fMRI, showed that the coding of facial expressions from occipital to the ventral temporal cortex starts in this time frame (Muukkonen, Ölander, Numminen, & Salmela, 2020). Furthermore, this result supports another recent study showing that face-sensitive neural activity can be detected already in the P1 component (Tanaka, 2018).…”

Section: Discussionsupporting

confidence: 89%

Event-related network changes unfold the dynamics of cortical integration during face processing

Maffei

Sessa

2020

Preprint

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AbstractFace perception arises from a collective activation of brain regions in the occipital, parietal and temporal cortices. Despite wide acknowledgement that these regions act in an intertwined network, the network behavior itself is poorly understood. Here we present a study in which time-varying connectivity estimated from EEG activity elicited by facial expressions presentation was characterized using graph-theoretical measures of node centrality and global network topology. Results revealed that face perception results from a dynamic reshaping of the network architecture, characterized by the emergence of hubs located in the occipital and temporal regions of the scalp. The importance of these nodes can be observed from early stages of visual processing and reaches a climax in the same time-window in which the face-sensitive N170 is observed. Furthermore, using Granger causality, we found that the time-evolving centrality of these nodes is predictive of ERP amplitude, providing a direct link between the network state and local neural response.Additionally, investigating global network topology by means of small-worldness and modularity, we found that face processing requires a functional network with a strong small-world organization that maximizes integration, at the cost of segregated modular subdivisions. Interestingly, we found that this architecture is not static, but instead it is dynamically implemented by the network from stimulus onset to ∼200 msec. Altogether, this study shows that recognizing facial expressions relies on a distributed information processing mechanism that dynamically weights the contribution of the cortical regions involved.

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“…This representation correspondence persisted, with some interruptions, until 750 ms. Such early-onset representations have previously been found in recent EEG/MEG studies for face identity (Dima et al, 2018;Nemrodov et al, 2018Nemrodov et al, , 2016Vida et al, 2017) as well as for facial expressions (Muukkonen et al, 2020). Our study is the first one to report that invariant aspects of face identity are initially detectable in the right parietal cortex.…”

Section: Discussionsupporting

confidence: 82%

“…Thus, the data of 20 participants (10 male) with a mean age of 22.05 years (SD = 2.26) was analyzed. This sample size was based on previous studies employing the representational-similarity-based fusion of M/EEG and fMRI (Cichy et al, 2014;Muukkonen et al, 2020), but was slightly increased to enhance statistical power. All participants had normal or corrected-to-normal eyesight.…”

Section: Methodsmentioning

confidence: 99%

“…By relating multivariate similarity spaces obtained from EEG and fMRI via RSA, we were able to combine the superior temporal resolution of EEG with the precise spatial resolution of fMRI. This cutting-edge analysis method, that has only been used in a hand-full of studies so far, has brought significant advances in understanding the processing of objects (Cichy et al, 2016(Cichy et al, , 2014Cichy and Pantazis, 2017;Hebart et al, 2018), biological motion (Chang et al, 2021) as well as emotions present in voices (Giordano et al, 2021) or faces (Muukkonen et al,2020;Bayer et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Prolonged and distributed processing of facial identity in the human brain

Stecher

Muukkonen

Salmela

et al. 2021

Preprint

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The recognition of facial identity is essential for social interactions. Despite extensive prior fMRI and EEG/MEG research on the neural representations of familiar faces, we know little about the spatio-temporal dynamics of face identity information. Therefore, we applied a novel multimodal approach, by fusioning the neuronal responses recorded in an fMRI and an EEG experiment. We analyzed the neural responses to naturally varying famous faces and traced how face identity emerges over time in different areas of the brain. We found that image invariant face identity information prevails over an extended time period (from 150 to 810 ms after stimulus onset) in the representational geometry of a broadly distributed network of parietal, temporal, and frontal areas with overlapping temporal profiles. These results challenge the current hierarchical models of face perception and suggest instead concerted and parallel activation of multiple nodes in the brain's identity coding network while processing information of familiar faces.

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Spatio-temporal dynamics of face perception

Cited by 41 publications

References 55 publications

Event‐related network changes unfold the dynamics of cortical integration during face processing

Event‐related network changes unfold the dynamics of cortical integration during face processing

Event-related network changes unfold the dynamics of cortical integration during face processing

Prolonged and distributed processing of facial identity in the human brain

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