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Successful decoding of famous faces in the fusiform face area.

Axelrod V, Yovel G - PLoS ONE (2015)

Bottom Line: We found that face-identity could be discriminated above chance level only in the fusiform face area.Our results corroborate the role of the fusiform face area in face recognition.Future studies are needed to further explore the role of the more recently discovered anterior face-selective areas in face recognition.

View Article: PubMed Central - PubMed

Affiliation: School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel.

ABSTRACT
What are the neural mechanisms of face recognition? It is believed that the network of face-selective areas, which spans the occipital, temporal, and frontal cortices, is important in face recognition. A number of previous studies indeed reported that face identity could be discriminated based on patterns of multivoxel activity in the fusiform face area and the anterior temporal lobe. However, given the difficulty in localizing the face-selective area in the anterior temporal lobe, its role in face recognition is still unknown. Furthermore, previous studies limited their analysis to occipito-temporal regions without testing identity decoding in more anterior face-selective regions, such as the amygdala and prefrontal cortex. In the current high-resolution functional Magnetic Resonance Imaging study, we systematically examined the decoding of the identity of famous faces in the temporo-frontal network of face-selective and adjacent non-face-selective regions. A special focus has been put on the face-area in the anterior temporal lobe, which was reliably localized using an optimized scanning protocol. We found that face-identity could be discriminated above chance level only in the fusiform face area. Our results corroborate the role of the fusiform face area in face recognition. Future studies are needed to further explore the role of the more recently discovered anterior face-selective areas in face recognition.

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Individual classification rates of identity discrimination analysis in the right FFA.
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pone.0117126.g004: Individual classification rates of identity discrimination analysis in the right FFA.

Mentions: The functional and anatomical ROIs, defined in the previous step had different sizes. It has been previously shown that classification rate might be influenced by the ROI size [42,48–50]. Therefore, it was important to use the same number of voxels for the ROIs of different regions. For the main discrimination analysis (Fig. 3 and Fig. 4) the ROI comprised of 20 voxels (160 mm3), while they were selected as a contiguous cluster of most selective voxels (e.g., [50–52]). Number of participants per region, average z-score and average MNI coordinate is shown in Table 1. For the discrimination analysis with different ROI size (Fig. 5) the most active voxels with the following size were selected: 10 voxels (80 mm3), 30 voxels (240 mm3), 40 voxels (320 mm3) and 50 voxels (400 mm3). For the control analysis we also conducted discrimination using ROIs of full size, before equalization procedure.


Successful decoding of famous faces in the fusiform face area.

Axelrod V, Yovel G - PLoS ONE (2015)

Individual classification rates of identity discrimination analysis in the right FFA.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4340964&req=5

pone.0117126.g004: Individual classification rates of identity discrimination analysis in the right FFA.
Mentions: The functional and anatomical ROIs, defined in the previous step had different sizes. It has been previously shown that classification rate might be influenced by the ROI size [42,48–50]. Therefore, it was important to use the same number of voxels for the ROIs of different regions. For the main discrimination analysis (Fig. 3 and Fig. 4) the ROI comprised of 20 voxels (160 mm3), while they were selected as a contiguous cluster of most selective voxels (e.g., [50–52]). Number of participants per region, average z-score and average MNI coordinate is shown in Table 1. For the discrimination analysis with different ROI size (Fig. 5) the most active voxels with the following size were selected: 10 voxels (80 mm3), 30 voxels (240 mm3), 40 voxels (320 mm3) and 50 voxels (400 mm3). For the control analysis we also conducted discrimination using ROIs of full size, before equalization procedure.

Bottom Line: We found that face-identity could be discriminated above chance level only in the fusiform face area.Our results corroborate the role of the fusiform face area in face recognition.Future studies are needed to further explore the role of the more recently discovered anterior face-selective areas in face recognition.

View Article: PubMed Central - PubMed

Affiliation: School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel.

ABSTRACT
What are the neural mechanisms of face recognition? It is believed that the network of face-selective areas, which spans the occipital, temporal, and frontal cortices, is important in face recognition. A number of previous studies indeed reported that face identity could be discriminated based on patterns of multivoxel activity in the fusiform face area and the anterior temporal lobe. However, given the difficulty in localizing the face-selective area in the anterior temporal lobe, its role in face recognition is still unknown. Furthermore, previous studies limited their analysis to occipito-temporal regions without testing identity decoding in more anterior face-selective regions, such as the amygdala and prefrontal cortex. In the current high-resolution functional Magnetic Resonance Imaging study, we systematically examined the decoding of the identity of famous faces in the temporo-frontal network of face-selective and adjacent non-face-selective regions. A special focus has been put on the face-area in the anterior temporal lobe, which was reliably localized using an optimized scanning protocol. We found that face-identity could be discriminated above chance level only in the fusiform face area. Our results corroborate the role of the fusiform face area in face recognition. Future studies are needed to further explore the role of the more recently discovered anterior face-selective areas in face recognition.

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