Timing and Tuning for Familiarity of Cortical Responses to Faces

Abstract

Different kinds of known faces activate brain areas to dissimilar degrees. However, the tuning to type of knowledge, and the temporal course of activation, of each area have not been well characterized. Here we measured, with functional magnetic resonance imaging, brain activity elicited by unfamiliar, visually familiar, and personally-familiar faces. We assessed response amplitude and duration using flexible hemodynamic response functions, as well as the tuning to face type, of regions within the face processing system. Core face processing areas (occipital and fusiform face areas) responded to all types of faces with only small differences in amplitude and duration. In contrast, most areas of the extended face processing system (medial orbito-frontal, anterior and posterior cingulate) had weak responses to unfamiliar and visually-familiar faces, but were highly tuned and exhibited prolonged responses to personally-familiar faces. This indicates that the neural processing of different types of familiar faces not only differs in degree, but is probably mediated by qualitatively distinct mechanisms.

Full text

Timing and Tuning for Familiarity of Cortical Responses
to Faces
Maria A. Bobes
1
*, Agustin Lage Castellanos
1
, Ileana Quin
˜ones
2
, Lorna Garcı
´a
2
, Mitchell Valdes-Sosa
1
1Cognitive Neuroscience Dept., Cuban Neurosciences Center, Havana, Cuba, 2Basque Center on Cognition, Brain and Language (BCBL), Donostia, Spain
Abstract
Different kinds of known faces activate brain areas to dissimilar degrees. However, the tuning to type of knowledge, and the
temporal course of activation, of each area have not been well characterized. Here we measured, with functional magnetic
resonance imaging, brain activity elicited by unfamiliar, visually familiar, and personally-familiar faces. We assessed response
amplitude and duration using flexible hemodynamic response functions, as well as the tuning to face type, of regions within
the face processing system. Core face processing areas (occipital and fusiform face areas) responded to all types of faces
with only small differences in amplitude and duration. In contrast, most areas of the extended face processing system
(medial orbito-frontal, anterior and posterior cingulate) had weak responses to unfamiliar and visually-familiar faces, but
were highly tuned and exhibited prolonged responses to personally-familiar faces. This indicates that the neural processing
of different types of familiar faces not only differs in degree, but is probably mediated by qualitatively distinct mechanisms.
Citation: Bobes MA, Lage Castellanos A, Quin
˜ones I, Garcı
´a L, Valdes-Sosa M (2013) Timing and Tuning for Familiarity of Cortical Responses to Faces. PLoS
ONE 8(10): e76100. doi:10.1371/journal.pone.0076100
Editor: Hans P. Op de Beeck, University of Leuven, Belgium
Received April 29, 2013; Accepted August 20, 2013; Published October 9, 2013
Copyright: ß2013 Bobes et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors have no support or funding to report.
Competing Interests: Co-author Mitchell Valdes-Sosa is a PLOS ONE Editorial Board member. This does not alter the authors’ adherence to all the PLOS ONE
policies on sharing data and materials.
* E-mail: antonieta@cneuro.edu.cu
Introduction
All known faces are charged with significance. However, the
face of a slightly known next-block neighbor is not equivalent to
that of a spouse. The former can provoke a flicker of recognition,
whereas the latter induces longer lasting affective states. Different
kinds of known faces differ in the amount and quality of
information that they afford, and probably in the neural systems
that process them. Accordingly, faces that rally different types of
memory will activate cortical areas differentially. These effects
vary according to which areas of the face processing system are
involved. The face processing system is divided in the core face
processing areas – comprised of occipital face area (OFA), fusiform
area (FFA) and posterior superior temporal sulcus (pSTS) – and
the extended face processing system (e.g. posterior cingulate (PC),
temporal cortices, anterior cingulate (AC) and middle orbitofrontal
cortex (mOF)) [1,2].
Several fMRI studies convincingly show a differential involve-
ment of the face-responsive cortical regions in the processing of
distinct types of familiarity. In these studies faces of famous or
personally significant people, and also visually familiar faces served
as stimuli [3,4]. Nevertheless, more information is needed to fully
characterize the role of these brain areas in processing face related
memories. All of the cited studies focus on the comparison of
responses to pairs of face types. Furthermore, only a few studies
have examined responses to more than one type of known face in
the same subjects. Therefore, it is difficult to infer the selectivity of
each area across a range of face-related memories. What is needed
is an activation-profile analysis (see [5]), where the relative strength
of the response to each type of face can be compared in the same
individuals. This is analogous (in the memory domain) to the
tuning curves measured for different values of stimulus parameters.
Tuning for lower order properties of faces (such as viewpoint or
geometrical properties) has been measured for the core face areas
[6] [7], but not for different types of face associated memories.
Tuning for face related properties has not been studied within the
extended face system.
At the same time, it is likely that different types of familiar faces
not only involve distinct neural systems, but also are associated
with different temporal courses of processing. Measurements of the
time course of functional magnetic resonance imaging (fMRI)
hemodynamic-responses to pictures or words (using flexible
hemodynamic response function (HRF) models that can vary in
shape) have revealed significantly longer durations for emotionally
charged than for neutral stimuli [8,9]. The fact that the increased
duration can be measured (despite the poor time resolution of
fMRI) is an indication that the emotional processes involved are
effectively persistent in time. However, the duration of responses
to faces with different types of familiarity (i.e face of acquaintanc-
es/celebrities versus unfamiliar faces) has not been compared to
date, despite their obvious difference in socio-emotional content.
Here we address the two issues introduced above by comparing
the fMRI responses to faces of close personal acquaintances,
artificially learned faces (associated only with visual memories),
and unfamiliar faces, within the same group of subjects. The
temporal course of the hemodynamic responses (estimated with
multi-parameter HRF models), and their tuning for different types
of faces, were measured in regions of interest within both the core
and extended face processing system. We hypothesized that the
tuning would become more specific and response duration would
increase as one progresses along the ventral visual pathway into
frontal areas belonging to the extended face system. To anticipate
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the results, these predictions were partially verified: we found little
tuning and short responses in the core areas, with the most
extreme tuning (i.e. exclusive sensitivity to personally familiar
faces) and the longest responses in the mOF and AC cortex.
Methods and Materials
Participants
Participants were screened to exclude neurological, psychiatric,
and systemic diseases, and then recruited as volunteers. The
sample is comprised of ten right-handed healthy subjects (5 males
and 5 females) that participated in the experiment as non-paid
volunteers. Their ages ranged from 21 to 36 years (mean = 27.9),
all had university degrees. Participants provided written informed
consent to participate in this study, which were documented in
forms signed by participants. The experimental protocols were
approved by the Ethics Committee of The Cuban Neurosciences
Center.
Stimuli
Stimuli consisted of photographs of familiar and unfamiliar
faces, and of houses. Two different sets of familiar faces were
obtained: Acquaintance faces, which were selected among the
family and close friends of each subject (i.e. these were different
across participants); and newly-learned faces, which were previ-
ously unknown faces, learned after exhaustive exposure in the lab
(see below). Although these two types of faces stimuli were both
visually familiar, only the acquaintances possessed social-emotion-
al significance for each participant.
Black and white photographs of the faces in frontal views were
digitally processed (to minimize differences in size, contrast, and
overall luminance) and displayed within a circular border masking
external facial-features, clothes, and the background.
Training for newly-learned faces
Learning took place during six sessions (two sessions per day)
two weeks before the fMRI session. Each session consists of a study
and a test period. In the study period, subjects viewed the set of 15
initially unknown faces (the same in all sessions) on a CRT
monitor in a random order, with the onset and offset times under
the subject’s control. The test period consisted of a familiarity
decision task. The 15 studied (‘‘old’’) faces were presented
interspersed with 15 ‘‘new’’ unfamiliar faces, one at a time in a
random order. The new unfamiliar faces were never repeated.
The subjects verbally classified each face as old or new, and were
provided feedback on the accuracy of the response. The faces in
the training set were thus seen twelve times, after which subjects
reached more than 98% of accuracy. Before the recording session,
subjects viewed once again the learned faces randomly mixed with
new unfamiliar faces.
Image acquisition
A Siemens 1.5T Magnetom Symphony system with a standard
birdcage head coil for signal transmission/reception (Siemens,
Erlangen, Germany) was used to acquire all images. BOLD-
contrast-weighted echoplanar images for functional scans consisted
of 16, interleaved, axial slices of 5 mm thickness (no interslice skip)
that partially covered the brain from about 240 below to about
40 mm above the AC-PC plane. In-plane resolution was
1.7361.73 mm, with the following parameters:
FOV = 5126512 mm; matrix = 1286128; echo time
(TE) = 60 ms; TR = 2 s with no time gap; flip angle = 90 degrees.
The first five volumes of each run were discarded to allow for T1
equilibration effects. Subsequently, a MPRAGE T1-weighted
structural image (16161 mm resolution) was acquired for
coregistration and display of the functional data, with the following
parameters: echo time (TE) = 3930 ms, repetition time
(TR) = 3000 ms, flip angle = 15 degrees, and field of view
(FOV) = 25662566160 mm
3
. This yielded 160 contiguous
1 mm thick slices in a sagittal orientation.
fMRI procedure
Participants were presented with four sets of stimuli: 15 houses,
30 unfamiliar faces, 15 faces of acquaintances, and 15 newly-
learned faces. Within the MRI scanner, the participants viewed
the stimuli in a pseudo-random order, which were presented for
1000 ms, with random inter-stimulus intervals (ISI) varying
between 4000 and 6000 ms. The complete set of stimuli was
repeated in three runs, each time in a different random order,
separated by 1 minute breaks. Different unfamiliar faces were used
in each run. Subjects were required to silently count any familiar
faces. Runs lasted about 7.46 min. Stimuli were rear-projected
onto the center of an opaque screen located at the subject’s feet
and viewed with a mirror fixed to the head coil.
Functional data analysis
Functional data were analyzed using SPM5 and related
toolboxes (Wellcome Department of Imaging Neuroscience;
http://www.fil.ion.ucl.ac.uk/spm). Outlier functional scans and
slices were repaired with the Artifact Repair Toolbox, (Gabrieli
Cognitive NeuroScience Lab; http://cibsr.stanford.edu/tools/
ArtRepair/ArtRepair.htm), after which the images were slice-
Figure 1. Face-related activation found in the voxelwise
analysis. Activation maps indicate regions where the response was
higher for: A) unfamiliar faces than houses. B)acquaintance faces than
unfamiliar faces. C) newly-learned faces than unfamiliar faces. These
activations are shown on an inflated brain, depicting voxels surviving
p,.005 (uncorrected).
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time corrected taking the middle slice as reference (using SPM59s
phase shift interpolation with the unwarp option) and then
realigned to the first image in the session. The anatomical T1
image was coregistered [10] with the whole brain EPI, which in
turn was coregistered with the mean of these limited field-of-view
EPIs. Each participant’s T1 scan was bias corrected, then spatially
normalized to MNI-space and segmented into gray matter (GM),
white matter (WM), and cerebrospinal fluid using the unified
procedure in SPM5 [11]. The parameters for normalization of the
anatomical image were used to transform the functional scans to
MNI space. Normalized images were spatially smoothed using an
8 mm Gaussian kernel. Data were high-pass filtered (64 s cut-off
period).
A massive univariate general linear model (GLM) was applied,
using for each stimulus category a set of design covariates that was
obtained by convolving the canonical hemodynamic response
function, plus time and dispersion derivatives (provided by SPM5),
with delta functions located at stimulus onsets [12]. Also the six
motion-correction parameters were included in the design matrix.
Parameters of the GLM were estimated with a robust regression
using weighted-least-squares, which was corrected for temporal
autocorrelation in the data (Diedrichsen&Shadmehr; http://www.
bangor.ac.uk/,pss412/imaging/robustWLS.html). A t-statistic
was then obtained for each voxel for the contrast of interest in
each subject.
Unfamiliar faces were divided in two subsets for the analysis. A
subset of 15 unfamiliar faces were used for the contrast unfamiliar
faces .houses. This contrast was used as a functional localizer of
face selective areas. A different subset of unfamiliar faces (the
remaining 15 unfamiliar faces) was used to estimate the remaining
contrasts of interest: acquaintances -faces.unfamiliar faces, newly-
learned faces.unfamiliar faces and acquaintances faces.unfa-
miliar faces. The two groups of unfamiliar faces were randomly
selected from the three experimental runs. Consistent effects across
subjects were tested employing the SPM5 random effects model, in
which the contrast images for all the subjects were entered. The
threshold for this analysis was set at p,0.005 (uncorrected).
Region of interest (ROIs): Functional regions of interest were
obtained in different ways for core and extended system areas. For
the core system ROIs were obtained directly from the functional
localizer contrast unfamiliar faces .houses, using a relaxed
threshold of p,0.05 (uncorrected) to obtain larger ROIs. This
contrast evinced activation in bilateral OFA, FFA and right pSTS.
However, this contrast did not uncover extended system areas
since these areas present weak or no response to unfamiliar faces.
The extended system ROIs were obtained starting with
preliminary search regions extracted from a previous study using
a similar paradigm [13]. These regions were located in the
following areas of the AAL atlas [14]: PC, AC, mOF, inferior
frontal pars triangularis (FrI), left insula (Ins), anterior temporal
(AT) and hippocampus. Next, these regions were defined using the
results of a contrast analysis with our experimental data. To avoid
circularity, this contrast analysis was performed with a leave-one-
subject-out procedure (LOSO) [15]. A single subject was
iteratively left out and a second level random effect analysis was
performed for the contrast all faces .houses and the significant
voxels were intersected with the previously defined search regions.
A total of 14 ROIs were obtained: five from the unfamiliar
faces.houses contrast (left and right OFA, left and right FFA, and
right pSTS) and nine from all faces.houses contrast with the
LOSO procedure (left and right PC, left and right AC, left and
right mOF, left and right FrI and left Ins). AT and hippocampus
were not included due to the inconsistency of the response in these
areas (only 7 subjects present activation at the AT area and 5 at
the hippocampus).
Estimation of HRF
The spatially unsmoothed time series in the ROIs were
averaged over voxels obtaining one time series for each ROI
and for each run. To estimate the hemodynamic response the
same design matrix described before was used. The corresponding
coefficients for each column were obtained using linear regression.
After the coefficients were obtained the hemodynamic responses
waveforms were calculated as the linear combination of the three
basic functions scaled by their respective coefficients.
Extraction of HRF parameters: Three parameters were
extracted from the heamodynamic response waveform: height,
latency and width. They were extracted after fitting a Gaussian
function to the obtained HRF. The amplitude was defined as the
maximum of the Gaussian function, and the latency corresponds
Table 1. Clusters of face-selective activations in a Second level random-effects analysis for the localizer contrast (unfamiliar
faces.houses).
cluster p(cor) cluster equiv k voxel p(FDRcor) voxel T voxel p(unc) x y z
0.157 299 1.000 5.63 0.000 38 246 222 Fusiform_R
1.000 4.89 0.000 44 264 214 Occipital_Inf_R
0.618 164 1.000 5.24 0.000 2 258 22 Precuneus_R
1.000 4.44 0.001 24248 22 Cingulum_Post_L
1.000 4.02 0.002 4 248 20 Precuneus_R
1.000 33 1.000 4.49 0.001 242 20 20 Frontal_Inf_Tri_L
0.988 70 1.000 3.96 0.002 240 252 216 Fusiform_L
1.000 3.61 0.003 242 274 212 Occipital_Inf_L
1.000 25 1.000 3.67 0.003 2652 28 Frontal_Med_Orb_L
1.000 7 1.000 3.44 0.004 28 4 16 Caudate_L
table shows 3 local maxima more than 8.0 mm apart.
Height threshold: T = 3.2, p = 0.005 (1.000) {p,0.01 (unc.)}.
Extent threshold: k = 0 voxels p = 1.000 (1.000)).
Degrees of freedom = [1.0, 9.0].
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to the location of this maximum. Accordingly, the width of the
response was defined as the standard deviation of the fitted
Gaussian. The area of the HRF was defined as the area of the
fitted Gaussian, multiplied by the sign of the peak. The height of
each face condition in each ROI was referred to the house
response by subtraction. Repeated measured analysis of variance
(rm ANOVA) were preformed independently over the log
transformation of height, latency and width parameters estimated
for each face stimulus, using two main factors: face category and
ROI. Significant level for planned comparison was set at p,0.05.
When appropriate, the Huynh-Feldt correction [16] was used to
mitigate violations of the sphericity assumptions in the repeated
measures ANOVA (the corresponding epsilon values are report-
ed).
Results
All participants counted the familiar faces (acquaintance and
newly-learned faces) accurately: .95% correct for every subject.
After the fMRI scanning session, subjects were asked to rate the
affective valence of each familiar person using a 5-point likert
scale: 1- ‘‘very unpleasant’’, 2- ‘‘unpleasant’’, 3- ‘‘neutral’’, 4-
‘‘pleasant’’, 5- ‘‘very pleasant’’. The mean ratings reached for faces
of acquaintances were 4.31 (SD = 0.18) – thus dominantly judged
as pleasant – and for newly-learned were 2.81 (SD = 0.25) – near
neutral. The faces of acquaintances were judged more pleasant
than the merely visually familiar newly-learned faces (t = 10.69,
df = 9, p,0.0001).
Voxelwise analysis
In order to localize the brain areas responding to different face
conditions, a second level random effects analysis over three
different contrasts was carried out (Figure 1). Face selective areas
were defined by the contrast of unfamiliar faces.houses for each
subject. (For these comparisons we used a subset of unfamiliar face
not used further for the HRF estimations.) The results of the
random effects model for this contrast are shown in Figure 1A and
Table 1. Two main clusters of activation were found bilaterally,
which correspond to the FFA and OFA. Some other areas, PC,
mOF, and left FrI, also exhibited significant activations (Figure 1A,
Table 1). Brain areas related to face familiarity processing were
located by analyzing the contrasts: acquaintances.unfamiliar
faces and newly-learned.unfamiliar faces (Figure 1B, C). The
Table 2. Clusters of face-selective activations in a Second level random-effects analysis for the localizer contrast (acquaintance
faces.unfamiliar faces).
cluster p(cor) cluster equiv k voxel p(FDRcor) voxel T voxel p(unc) x y z
0.961 83 0.136 9.71 0.000 60 0 218 Temporal_Mid_R
0.000 1756 0.136 7.74 0.000 0 42 8 Cingulum_Ant_L
0.136 6.20 0.000 6 56 16 Frontal_Sup_Medial_R
0.181 4.55 0.001 22 26 16 Cingulum_Ant_L
0.356 206 0.136 6.05 0.000 52 266 20 Temporal_Mid_R
0.208 3.92 0.002 62 254 12 Temporal_Mid_R
0.944 89 0.136 6.01 0.000 244 22 2 Frontal_Inf_Tri_L
0.615 154 0.136 5.92 0.000 28240 16 Cingulum_Post_L
0.205 4.06 0.001 8 238 18 Cingulum_Post_R
0.998 50 0.136 5.91 0.000 38 28 218 Frontal_Inf_Orb_R
0.841 114 0.207 3.98 0.002 14 26 22 Caudate_R
1.000 22 0.144 5.37 0.000 32 6 220 Temporal_Pole_Sup_R
0.905 100 0.154 5.01 0.000 32 228 220 Fusiform_R
0.220 3.13 0.006 32 238 218 Fusiform_R
0.993 62 0.195 4.25 0.001 2 220 4 Thalamus_R
0.913 98 0.156 4.85 0.000 34 212 220 Hippocampus_R
0.992 63 0.205 4.08 0.001 254 12 22 Frontal_Inf_Oper_L
0.214 3.35 0.004 248 4 22 Precentral_L
1.000 4 0.208 3.79 0.002 60 214 224 Temporal_Inf_R
1.000 33 0.208 3.70 0.002 252 32 8 Frontal_Inf_Tri_L
0.998 52 0.208 3.62 0.003 242 258 16 Temporal_Mid_L
1.000 36 0.208 3.61 0.003 214 6 14 Caudate_L
1.000 10 0.213 3.48 0.003 30 240 22 ParaHippocampal_R
0.999 43 0.214 3.34 0.004 2 262 20 Calcarine_R
1.000 2 0.216 3.26 0.005 234 240 24 ParaHippocampal_L
1.000 7 0.219 3.21 0.005 260 218 210 Temporal_Mid_L
table shows 3 local maxima more than 8.0 mm apart.
Height threshold: T = 3.2, p = 0.005 (1.000) {p,0.005 (unc.)}.
Extent threshold: k = 0 voxels, p = 1.000 (1.000).
Degrees of freedom = [1.0, 9.0].
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responses to faces of acquaintances were larger than the responses
to unfamiliar faces in several regions, including AC, mOF, PC, left
FrI, left and right pSTS, right anterior FFA, and the right
parahippocampus (Figure 1B). Smaller clusters also appeared in
other regions (Table 2). However, the cortical response to newly-
learned faces was more limited, evoking larger BOLD responses
than unfamiliar faces only in PC, left middle temporal, right
hippocampus and the left FrI (Figure 1C, Table 3).
ROI-based analysis
The mean HRFs for each ROI are shown in Figure 2A. Within
the ROIs belonging to the core system (OFA, FFA and pSTS), the
HRF responses observed for all face conditions showed the typical
positive ongoing pattern, except for the newly-learned response in
pSTS, which were negative. These responses had a width of
approximately 10 s. In all the extended system ROIs (Figure 2B),
HRFs for faces of acquaintances were visibly larger than for
unfamiliar and newly-learned faces. Also, in these ROIs the HRFs
for faces of acquaintances were longer in duration than those
related to other face conditions, more clearly so in the right mOF
and right AC, where the HRF had a width of almost 15 s. The
responses to newly-learned and unfamiliar faces seemed to be of
low amplitude but still were larger than the response to houses in
all ROIs (except right AC), although responses to newly-learned
faces were somewhat larger in PC and Ins.
The average height for each face condition across ROIs is
displayed in Figure 3A. The corresponding rm-ANOVA (3 face
conditions614 ROIs) showed highly significant effects of Face
condition (F(2,18) = 30.4, p,0.000002, H-F epsilon = 0.997,
p,0.000002), and ROI (F(13,117) = 4.44, H-F epsilon = 0.26,
p,0.008), and a significant interaction between these two factors
(F(26,234) = 2, p,0.005, H-F epsilon = 0.5, p,0.03). Planned
comparisons showed that this interaction was driven by the much
larger responses to faces of acquaintances than to unfamiliar faces
in the extended system (collapsing across ROIs of the extended
system, F(1,9) = 55.24. p,0.00004), with a much smaller differ-
ence in the core ROIs (F(1,9) = 10.25.p,0.01) (see Figure S1 in
File S1). The contrast for the interaction between lumped core vs.
lumped extended ROIs on one hand, and faces of acquaintances
vs. unfamiliar faces on the other, was significant (F(1,9) = 7.34,
p,0.02). However the corresponding interactions involving
acquaintances vs. newly-learned (F(1,9) = 1.63, n.s.) and unfamiliar
vs. newly-learned (F(1,9) = 1.39, n.s.) were not significant. (See
Table S1 in File S1 for other planned comparisons results).
Table 3. Clusters of face-selective activations in a Second level random-effects analysis for the contrast newly-learned
faces.unfamiliar faces).
cluster p(cor) cluster equiv k voxel p(FDRcor) voxel T voxel p(unc) x y z
0.290 247 0.616 5.86 0.000 28238 18 Cingulum_Post_L
0.026 484 0.616 4.31 0.001 216 10 10 Caudate_L
0.616 3.58 0.003 218 0 24 Pallidum_L
1.000 14 0.616 4.68 0.001 256 252 14 Temporal_Mid_L
0.944 95 0.616 4.02 0.002 16 8 8 Caudate_R
0.956 90 0.616 3.93 0.002 12 22 18 Caudate_R
0.616 3.24 0.005 18 2 22 Caudate_R
1.000 41 0.616 3.86 0.002 30 2626 Putamen_R
1.000 16 0.616 3.83 0.002 34 212 218 Hippocampus_R
1.000 27 0.616 3.31 0.005 248 38 18 Frontal_Inf_Tri_L
table shows 3 local maxima more than 8.0 mm apart.
Height threshold: T = 3.2, p = 0.005 (1.000) {p,0.005 (unc.)}.
Extent threshold: k = 0 voxels, p = 1.000 (1.000).
Degrees of freedom = [1.0, 9.0].
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Figure 2. Mean HRFs average across subjects for different face
conditions in the selected ROIs. Error bars denote the standard
error of the mean.
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The mean HRF widths for face condition against ROIs are
displayed in Figure 3B. The corresponding rm-ANOVA (3 face
conditions614 ROIs) for width evinced a significant effect of Face
condition (F(2,18) = 6.2, p,0.0089, H-F epsilon = 1 p,0.0089),
but not for ROI (F(1,9) = 0.62, n.s.). The interaction between these
two factors was also significant (F(26,234) = 1.69, p,0.02, H-F
epsilon = 0.8, p,0.03). The contrast for the interaction between
lumped core vs. lumped extended ROIs on one hand, and the
three face conditions on the other, was significant (F(2,18) = 5.02,
p,0.018). The interactions of ROI type (core vs. extended) and
the faces of acquaintances vs. unfamiliar (F(1,9) = 9.58, p,0.01),
and of ROI type with faces of acquaintances vs. newly-learned
faces (F(1,9) = 6.24, p,0.034), were significant, whereas the same
interaction with newly-learned vs. unfamiliar was not
(F(1,9) = 0.41, n.s.). Within the lumped core ROIs, significant
differences for width between pairs of face conditions were absent
(all F(1,9),1.63), whereas in the lumped extended system ROIs,
the difference in width for both acquaintances vs. unfamiliar
(F(1,9) = 17.9, p,0.0023) and acquaintances vs. newly-learned
(F(1,9) = 24.8, p,0.0008) were highly significant. However, the
contrast for newly-learned vs. unfamiliar was not (F(1,9) = 0.003,
n.s.). (See Figure S2, and Table S2 in File S1 for other planned
comparisons results.).
In order to view the tuning for face types more clearly, we
defined an activation profile in each ROI as a unitary norm vector
whose components corresponded to the area of the HRFs for each
Figure 3. Bar graphs showing the parameters extracted from the estimated HRFs, for all face condition and all ROIs A) Height B)
Width. Error bars correspond to the standard error. The results from the two-way interaction rm ANOVA between face condition and ROI are shown
(significant differences between the conditions are indicated: * p,0.05, ** p,0.01, ***p,0.001).
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of the three face conditions (Figure 4). Therefore in these profiles,
amplitude and duration measures were combined. As shown in the
figure, these ROIs are grouped into two distinct clusters within the
tuning space. One group of ROIs was comprised by the OFAs and
FFAs, which exhibited little face type selectivity. The other group
included the mOFs, ACs, PCs and FrI, characterized by large
responses to faces of acquaintances and little response to other
types of faces. Two ROIs do not fit into these clusters: the left
insula, which responded to both faces of acquaintance and newly-
learned faces; and the right pSTS, which responded to both
familiar and unfamiliar faces, with negative response to newly-
learned faces.
Discussion
The amplitude and duration of BOLD responses to unfamiliar,
visually-familiar, and personally-familiar faces were measured in
several ROIs within the face processing system. Responses to
unfamiliar faces were present in all core areas (OFA, FFA and
pSTS), which also responded to visually and personally familiar
faces. Only small differences in response amplitude and duration
across face types were found in these ROIs. In contrast, most areas
of the extended system (e.g. mOF) responded very weakly to
unfamiliar and visually-familiar faces, but exhibited large and
prolonged reactions to personally-familiar faces.
Before discussing the ROI data in more detail, we examine the
consistency of our different voxelwise analyses with previously
reported work. When faces were compared to non-face objects,
both the FFA and the OFA were activated bilaterally as described
in many studies [17]. Additionally, in the newly-learned.unfa-
miliar face contrast, we replicated the reported activations for PC,
right hippocampus and left FrI [18], but not for OFA or FFA [19].
For the acquaintance.unfamiliar face contrast we also replicated
the reported activations in pSTS, AC, PC, Ins, and mOF [20] but
not in amygdala and middle temporal gyrus as reported in other
studies [21]. Thus our voxelwise analyses were largely consistent
with previous work.
Our results evinced two distinct patterns of tuning-to-familiar-
ity, which mainly correspond to the core and the extended face
ROIs respectively. Core areas responded strongly to all face
categories, with weak face-category selectivity. In the right OFA
and FFA the response was equivalent in amplitude across face
type, whereas in the left OFA and FFA a small advantage was
present for personally-familiar. Previous work is inconsistent about
the effect of face familiarity on core system responses. In FFA,
larger activations (relative to unfamiliar) have been reported for
famous [20], personally familiar faces [22], and newly-learned
faces [19]. However, decreased activations [18], and null effects
have been also reported [23].
In a distinct pattern, all regions of the extended system clearly
responded more to faces of acquaintances than to either unfamiliar
faces or newly-learned faces, with the largest effects in mOF, AC,
and PC. In fact, in these ROIs there was little response to the latter
types of faces. This extreme tuning for faces of acquaintances is
Figure 4. Activation profile in the tuning space. Each ROI is represented in the unitary sphere as a normalized three dimensional vector
composed by the response to each face condition. The areas of the estimated HRF were used to describe the intensity of the response to each face
condition. The core system ROIs are shown in red, while the extended system ROIs are in blue. The red vector is the mean profile of four ROIs of the
core system (bilateral OFA and FFA). The blue vector is the mean profile of the extended system ROIs.
doi:10.1371/journal.pone.0076100.g004
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PLOS ONE | www.plosone.org 7 October 2013 | Volume 8 | Issue 10 | e76100

roughly consistent with, but cannot be clearly measured, in the
traditional voxelwise contrasts presented here and reported
previously. In the case of mOF, our results are more noteworthy
given the difficulty of measuring the BOLD signal in this region
due to susceptibility artifacts (which may explain why some studies
did not find the effect in this region, e.g. [22]). Note that mere
visual familiarity did not activate these extended system areas.
A few ROIs did not fit neatly into the two categories described
above. Responses to newly-learned and personally familiar faces
did not differ in amplitude in the Insula. The right pSTS exhibited
negative responses to newly-learned faces (but still larger than the
response to houses which we used as reference). Negative
responses to newly-learned faces have been previously found in
the intra-parietal sulcus [24], and in the amygdala [3], and could
be related to inhibition that segregates these minimally familiar
stimuli from those containing social information deserving further
processing. Similar negative responses, have been also found for
neutral pictures [8] and words [9] intermingled with emotional
stimuli.
We also analyzed the duration of face-related activity in each
ROI. This parameter has been ignored up to now in studies of face
familiarity. The duration of the responses did not vary across face
type in the core areas. However, in the extended system the
responses to faces of acquaintances were apparently longer than
those for the other types of face, and were also longer than in the
core system. Both results suggest that personally-familiar faces are
associated with prolonged neural processing. This different
temporal dynamic should depend on both the information content
offered by each kind of face and the position of the studied region
within the visual hierarchy. Note that the core areas are conceived
to be involved in a fast, feed-forward, and relatively automatic
analysis of the visual cues afforded by faces [2], whereas the
extended system includes areas involved in processes potentially
prolonged in time (e.g. rumination and long lasting emotions in the
mOF). However, we are cautious about this conclusion for several
reasons. Responses to newly-learned and unfamiliar faces were
very small in the extended system ROIs, entailing less reliable
estimations of width. Furthermore, between-ROI differences in
HRF width could be due to confounding factors such as regional
differences in neurovascular coupling [25]. In this context, the
results from the right PC are of special significance since its
responses to all faces were large and statistically reliable. Since
HRF width was still larger there for personally familiar faces
despite invariant neurovascular coupling, longer neural processing
seems a likely explanation for the effect.
To recapitulate, both amplitude tuning and HRF duration
indicate a sharp dichotomy in the response pattern in the ROIs we
studied here. The two measures were combined for the activation
profile plot shown in Figure 4. The data could in principle be
uniformly distributed over the whole sphere of possible functional
profiles, with different clusters gradually blending into each other.
However, the profiles were clustered into two clearly disjoint
groups. Type I areas responded to all faces more or less
equivalently, whereas type II areas were extremely tuned,
presenting enhanced and prolonged responses only to faces of
acquaintances. Importantly, type II areas were not responding to
visual familiarity.
Type II profiles could be related to the retrieval of different
types of memory, including two main candidates: on one hand
semantic and episodic declarative memories, and on the other
emotional associations. We cannot differentiate the relative
contribution of these candidates in this study, although several
lines of evidence suggest that emotional associations could be
important. Emotional associations are unavoidable after close
personal contact with other people. Accordingly, the subjects in
the present study rated faces of acquaintances as very pleasant but
newly-learned faces as neutral. We have reported that skin
conductance responses (SCR) are larger for faces of acquaintances
than for both unfamiliar faces and newly-learned faces [26].
Congruently, increased HRF duration has been described for
affective pictures [8] or emotional words [9] relative to neutral
stimuli in the frontal superior medial/AC and PC. In these studies
the intensity of the emotional experience was directly related to
HRF amplitude and duration [8].
The presence of type II profiles in the mOF is especially
interesting and fits with a body of previously reported data.
Lesions to the mOF abolish the enhanced SCRs for familiar faces
[27]. This area exhibits a significant correlation between BOLD
and SCR amplitudes [28]. Furthermore, the mOF is thought to
play a role in representing the reward value of stimuli [29].
Congruently, the attractiveness or trustworthiness of faces is
related to mOF activation [30]. Prolonged neural responses to
emotional (compared with neutral) facial expressions have been
found in the mOF with intracranial single unit recordings [31].
Therefore, the type II profile found in mOF is consistent with what
is known about its role in the processing of emotional information.
On the other hand, the role of declarative memories in
generating type II profiles cannot be excluded. A large store of
semantic and episodic memories are also available for personal
acquaintances. Anterior and medial temporal lobe structures have
been implicated in the processing of declarative knowledge.
Enhanced and prolonged neuronal unit activity to recognized-
as compared to unrecognized-familiar faces has been found in
medial temporal structures with intracranial recordings [32]. At
least two approaches are available to dissect the roles of declarative
memories and emotional associations in generating type II profiles.
Firstly, one could broaden the profile analysis by including
responses to artificially learned faces selectively associated to either
declarative or affective information. Artificial learning of face
affective information has been reported [33], and was related to
increased activations in AC. Artificial learning of face related
semantics has also been reported, coupled to increased activation
of anterior temporal areas [34]. Thus, inclusion of these artificial
stimuli in activation profiles, as well as measurement of the
durations of the corresponding activations is necessary.
In an alternate approach, one can study activation profiles/
temporal dynamics of different types of faces in brain damaged
patients with dissociations of declarative and affective knowledge.
This has been done for prosopagnosia, where the ability to overtly
recognize faces is lost [35]. In some cases of this disorder,
emotional memories are available for previously familiar faces as
evinced by larger SCRs for familiar- than for unfamiliar-faces
[36]. Interestingly, these cases can exhibit larger fMRI responses
for personally-familiar than for unfamiliar faces in the extended
system (e.g. PC and mOF) [13]. Face activation profiles must also
be studied in the reverse dissociation (impaired emotional
association and intact declarative knowledge for faces, e.g.
Capgras syndrome [37]).
Some limitations of this study must be addressed. One problem
is the low power due to the small number of subjects. Performing
similar experiments with a larger number of subjects is necessary.
Another problem, as pointed out by [38], is the potential
difference between memories for faces artificially learned in the
laboratory and those learned naturally in daily life. Therefore, use
of this type of artificial stimuli should be complemented with that
of real-life stimuli for which the amount of different kinds of
knowledge can be gauged. This brings us to another limitation.
We only included faces of close friends and family in the
Timing and Tuning of Responses to Face Familiarity
PLOS ONE | www.plosone.org 8 October 2013 | Volume 8 | Issue 10 | e76100

personally-familiar category. Consequently, all of these faces were
rated as agreeable by all subjects. Artificially learned faces
associated with different affective properties activate dissimilar
brain regions [33]. In future studies of activation profiles,
personally familiar faces of different valence (e.g. agreeable vs.
disagreeable) should be included.
In conclusion, our results indicate that the neural processing of
different types of familiar faces not only differs in degree, but is
probably mediated by qualitatively distinct mechanisms. Several
areas in the extended face system were virtually activated only by
faces of personal acquaintances. These activations were longer
lasting than those produced by mere visual familiarity. The short
and spatially restricted response to visual familiarity is consistent
with activity in a feed forward circuit [39]. On the other hand, the
prolonged and spatially disseminated response to personal
familiarity suggests a network incorporating multiple feed-forward
routes operating in parallel, and very likely feedback circuitry [40].
To elucidate these candidate mechanisms, the activation profiles
and temporal dynamics of face sensitive areas must be further
studied.
Supporting Information
File S1 Figure S1. Bar graphs showing the median of the height
parameter of the core system ROIs(left and right OFA, left and
right FFA, and right pSTS) and the extended ROIs (left and right
PC, left and right AC, left and right mOF, left and right FrI and
left Ins. Error bars corresponded to the standard error. Figure S2.
Bar graphs showing the median of the width parameter of the core
system ROIs(left and right OFA, left and right FFA, and right
pSTS) and the extended ROIs (left and right PC, left and right
AC, left and right mOF, left and right FrI and left Ins. Error bars
corresponded to the standard error. Table S1. Results of the
planned comparison in the rm-ANOVA over height values. Two
factors: Face condition (3 levels) and ROI (14 levels). Table S2.
Results of the planned comparison in the rm-ANOVA over width
values. Two factors: Face condition (3 levels) and ROI (14 levels).
(DOC)
Acknowledgments
Special thanks are extended to the Center of Medical and Surgical
Research in Havana for its help in imaging the subjects, and the Cuban
Human Brain Mapping Project for providing neuroinformatics support.
Also thanks to Joe Michel Lopez and Rogney Marin for their technical
assistance and to all the subjects participating in the study.
Author Contributions
Conceived and designed the experiments: MAB. Performed the experi-
ments: IQ LG. Analyzed the data: ALC MVS MAB. Contributed
reagents/materials/analysis tools: ALC. Wrote the paper: MAB ALC
MVS.
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