Neural Responses to Ambiguity Involve Domain-general - Am MIT spezialisierte KI-Forschung

Neural Responses to Ambiguity Involve Domain-general
and Domain-specific Emotion Processing Systems

Maital Neta1, William M. Kelley2, and Paul J. Whalen2

Abstrakt

■ Extant research has examined the process of decision making
under uncertainty, specifically in situations of ambiguity. Wie-
immer, much of this work has been conducted in the context of
semantic and low-level visual processing. An open question is
whether ambiguity in social signals (z.B., emotional facial expres-
sionen) is processed similarly or whether a unique set of processors
come on-line to resolve ambiguity in a social context. Our work
has examined ambiguity using surprised facial expressions, als
they have predicted both positive and negative outcomes in the
Vergangenheit. Speziell, whereas some people tended to interpret sur-
prise as negatively valenced, others tended toward a more posi-
tive interpretation. Hier, we examined neural responses to social
ambiguity using faces (surprise) and nonface emotional scenes
(International Affective Picture System). Darüber hinaus, we examined

whether these effects are specific to ambiguity resolution (d.h.,
judgments about the ambiguity) or whether similar effects would
be demonstrated for incidental judgments (z.B., nonvalence judg-
ments about ambiguously valenced stimuli). We found that a dis-
tinct task control (d.h., cingulo-opercular) network was more
active when resolving ambiguity. We also found that activity in
the ventral amygdala was greater to faces and scenes that were
rated explicitly along the dimension of valence, consistent with
findings that the ventral amygdala tracks valence. Taken together,
there is a complex neural architecture that supports decision
making in the presence of ambiguity: (A) a core set of cortical
structures engaged for explicit ambiguity processing across stim-
ulus boundaries and (B) other dedicated circuits for biologically
relevant learning situations involving faces. ■

EINFÜHRUNG

Uncertainty is a prominent feature of our decision pro-
Prozess (Kahneman, Slovic, & Tversky, 1982), as it is ubiqui-
tous in our realistic settings, and poses a major obstacle
to effective decision making (Brunsson, 1985; Corbin,
1980). Although such decision-making processes have
been studied for several decades (Tversky & Kahneman,
1974), we have only recently begun to understand the
neural architecture that allows for performing such a
complex task. A clear understanding of these cognitive
functions requires, Dann, also a clear definition of uncer-
tainty. Whereas some describe this concept as a psycholog-
ical state in which an individual lacks sufficient knowledge
about the outcome(S) of a given choice (see Platt &
Huettel, 2008, für eine Rezension), a more specific kind of uncer-
tainty is derived from ambiguity. In large part, research on
ambiguity has been studied in the realm of linguistic prop-
erties, as ambiguity resolution is a central problem in lan-
guage comprehension (Rodd, Davis, & Johnsrude, 2005;
see MacDonald, Pearlmutter, & Seidenberg, 1994, for a
Rezension). More recently, work in neuroeconomics has com-
pared the effects of risk (levels of probability) and ambigu-
ität (uncertain probabilities) in the context of choice (Erheben,
Snell, Nelson, Rustichini, & Glimcher, 2010; Hsu, Bhatt,
Adolphs, Tranel, & Camerer, 2005).

1Washington University School of Medicine, 2Dartmouth College

Although this work has examined decision-making pro-
cesses in the presence of ambiguity, it remains unclear how
this may differ from the process of resolving ambiguity (d.h.,
making a discrete decision about an ambiguous stimulus,
specifically along the dimension of the ambiguity). In other
Wörter, an incidental judgment in the presence of ambigu-
ity might require participants to judge the gender of faces
that have been morphed along the dimension of race,
whereas an explicit resolution judgment would require par-
ticipants to judge the races of those same faces. Some stud-
ies have revealed that a set of cortical regions collectively
referred to as the cingulo-opercular network (dorsal ACC
[dACC]/medial superior frontal cortex and the bilateral
frontal operculum [FO]/anterior insula [AI]; see Dosenbach
et al., 2006) has been linked to decision making in the pres-
ence of semantic ambiguity (d.h., the selection between
competing alternatives; Thompson-Schill, DʼEsposito,
Aguirre, & Farah, 1997) and when detecting ambiguity in
visual motion (Sterzer, Russ, Preibisch, & Kleinschmidt,
2002). With respect to face processing, one study found
that these regions were more active only when participants
were asked to resolve the ambiguity (d.h., when making
race judgments about faces that are racially ambiguous
[morphed Asian and white faces] and gender judgments
about faces that are gender-ambiguous [morphed male
and female faces; Demos, Wig, Moran, & Kelley, 2004]).
One goal of the current work was to determine whether
certain aspects of the task demands specifically recruit this

Zeitschrift für kognitive Neurowissenschaften 25:4, S. 547–557

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Netzwerk, das ist, when it is recruited by the mere presence
of ambiguity or when specifically making decisions that re-
solve the ambiguity.

To date, much of the work examining ambiguity has
been conducted in the context of semantic and low-level
visual processing. An open question is whether ambiguity
in social signals (z.B., emotional facial expressions) Sind
processed in a similar manner or whether a unique set
of processors come on-line to resolve ambiguity in an
emotional context. Zum Beispiel, surprised facial expres-
sions are ambiguous in that they have predicted both
positive and negative outcomes in the past. Tatsächlich, Das
ambiguity can be exploited to demonstrate that people
show individual differences in their propensity to inter-
pret surprised faces as either positive or negative. Im
absence of contextual information that can be used to
disambiguate the valence of this expression, some people
interpret surprised faces negatively, whereas others inter-
pret them positively (Neta & Whalen, 2010; Neta, Norris, &
Whalen, 2009; Kim, Somerville, Johnstone, Alexander, &
Whalen, 2003). The only known reports of neural re-
sponses to ambiguity of surprised faces has shown that
the amygdala is modulated by ambiguity but only in the
absence of a task that requires ambiguity resolution per
se (Kim et al., 2003, 2004). Taken together, the main goal
of this study was to examine ambiguity as it relates to social
Signale, both in face and other nonface emotional stimuli
(d.h., International Affective Picture System [IAPS] scenes)
and to determine how task demands might modulate
responses to ambiguity (explicit valence ratings of ambig-
uously valenced stimuli, as compared with nonvalence
evaluations).

Zu diesem Zweck, we examined behavioral and neural re-
sponses to ambiguous stimuli across two stimulus and
task categories. Speziell, we presented face stimuli
(surprised, angry, and happy expressions) sowie
scenes (ambiguous, clearly negative, and clearly positive)
and asked participants to make either a valence or non-
valence judgment about each one. In both stimulus cate-
gories, the clearly valenced stimuli were included purely
to serve as anchors for behavioral valence ratings of the
ambiguous stimuli. We predicted that there might be a
set of cortical regions that come on-line when effortful
processing of ambiguity is required (d.h., explicit valence
judgments of ambiguously valenced stimuli), whereas the
amygdala may play a dual role, in accordance with ventral
and dorsal subregions tracking valence and arousal, Re-
spectively, that may be critically dependent on the task
demands.

METHODEN

Teilnehmer

Thirty-five healthy participants (right-handed, without
neurological disease, and with normal/corrected vision;
21 Frauen) volunteered. None were aware of the purpose

of the experiment, and they were all compensated for their
participation through monetary payment or course credit.
Written informed consent was obtained from each partici-
pant before the session, and all procedures were approved
by the Dartmouth College Committee for the Protection of
Human Subjects. Three participants were removed because
of technical complications with the stimulus-presenting
computer, and an additional participant was removed be-
cause of nonnormative ratings (z.B., happy expressions were
rated as negative on greater than 40% of trials). Infolge,
the final sample contained 31 Teilnehmer (19 Frauen). Alle
included participants tested within normal limits for de-
pression (Beck Depression Inventory [BDI]; Beck, Station,
& Mendelson, 1961; M = 3.74, SE = .66) and anxiety
(Spielberger, Gorsuch, & Lushene, 1988; State-Trait
Anxiety Inventory: STAIs = 31.06 ± 1.21, STAIt = 34.32 ±
1.43). One additional participant was removed from the
fMRI data analysis because of scanner-related artifact, Also
the final sample for those analyses contained 30 Teilnehmer
(18 Frauen).

Stimuli

For the face task, we used 24 face identities (12 men) Pos-
ing angry, happy, and surprised expressions. We selected
images of 14 Identitäten (7 Frauen, 7 men) from the NimStim
standardized facial expression stimulus set (Tottenham
et al., 2009) Und 20 Identitäten (10 Frauen, 10 men) aus
the averaged Karolinska Directed Emotional Faces data-
base (Lundqvist, Flykt, & Öhman, 1998). Of the 34 indi-
viduals whose images were included in the experiment,
some posed all three expressions, and some posed only
one or two of the expressions, providing us with 48 dis-
crete stimuli. The facial expressions in this stimulus set
have been validated by a separate set of participants who
labeled each expression; only faces correctly labeled more
als 60% of the time were included.

Wichtig, not all of the identities are represented
in each expression condition. Jedoch, the focus of this
study was to assess the ambiguous conditions specifically
(faces and scenes), and the clearly valenced conditions
(z.B., happy and angry expressions) were included only
to serve as anchors that would ground participantsʼ re-
sponses to the ambiguous (z.B., surprised) Reize. Als
solch, we used twice as many face identities in the surprise
condition compared with the angry and happy face con-
ditions, and so, the conditions were never intended to be
matched for identity. Eher, we selected identities within
each expression condition that were labeled the most
accurately in terms of the normative data provided with
the stimulus set, so to ensure that our clearly valenced
faces were the ideal anchors (d.h., the most clearly valenced
stimuli we could present), and the same goal was applied
for the surprised faces.

For the scenes task, we used images from IAPS (Lang,
Bradley, & Cuthbert, 2008) that were previously rated as
either positive, negative, or ambiguous in valence. Ambiguity

548

Zeitschrift für kognitive Neurowissenschaften

Volumen 25, Nummer 4

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was based on discordant valence ratings across participants
(some rated images as positive and others as negative; d.h.,
high standard deviation in valence ratings; Tisch 1). Der
mean (SEM) valence ratings on the normative 9-point scale
(1 = very unpleasant, 9 = very pleasant) war 2.39 (0.08)
for negative pictures, 7.93 (0.07) for positive pictures, Und
5.19 (0.26) for ambiguous pictures (F(2, 10) = 1469.44,
P < .001), such that positive pictures were rated as more positive than ambiguous and negative pictures, and negative pictures were rated as more negative than ambiguous pic- tures (all ps < .001). Importantly, arousal was equated across these three conditions: the mean (SEM) arousal ratings on the normative 9-point scale (1 = low arousal, 9 = high arousal) were 5.36 (0.20) for negative pictures, 4.96 (0.18) for positive pictures, and 4.99 (0.18) for ambiguous pictures (F(2, 10) = 1.56, p = .26; Table 1). In a behavioral pilot, we recruited 20 new participants (11 women). None were aware of the purpose of the ex- periment, and they were all compensated for their par- ticipation through monetary payment or course credit. Written informed consent was obtained from each par- ticipant before the session, and all procedures were approved by Dartmouth College Committee for the Pro- tection of Human Subjects. Each participant viewed 114 scenes and rated each image as positive or negative (consistent with the methods in Experiment 1). Of the 114 scenes, 24 were defined as clearly negative, 24 as clearly positive, and 66 as ambiguous, based on the valence and arousal ratings provided with the stimuli (Table 1). Each image was presented for 1500 msec on a black back- ground, with an intertrial interval of 500 msec, during which a white fixation cross appeared on the screen. As with the face stimuli, 24 images were used, and each par- ticipant viewed 50% ambiguous images and 50% clear valence images (25% clear positive and 25% clear nega- tive). Thus, from the data collected in the pilot, we se- lected 12 clearly negative and 12 clearly positive images and 24 with an ambiguous valence (i.e., chosen because they had the highest standard deviation in valence ratings across participants). Indeed, the standard deviation in rat- ings of ambiguous scenes was significantly greater than the standard deviation in ratings of clearly valenced scenes (t(23) = 19.2, p < .001). Finally, to directly compare the conditions across stimu- lus sets, we ran a Stimulus (IAPS, faces) × Valence (ambig- uous, negative, positive) repeated-measures ANOVA on the normative ratings associated with each stimulus set. For valence ratings, we found a significant main effect of Valence (as expected) but no main effect of Stimulus ( p > .2). For arousal ratings, Jedoch, there was a main
effect of Stimulus (F(1, 11) = 5.66, p = .04), where arousal
ratings were significantly higher for IAPS than faces, welche
is somewhat expected given the nature of the stimuli.

Experiment Design and Parameters

The fMRI paradigm consisted of eight functional runs of
four experimental blocks each: two blocks each of facial
expressions and IAPS stimuli interleaved. Each block began
with a brief (2 Sek) task instruction statement: “valence”
or “gender” (nonvalence) for the face blocks and “valence”
or “social/nonsocial” (d.h., “Does the picture contain a
person?”; nonvalence) for the IAPS blocks. Each block con-
sisted of 24 Bilder, 12 from the ambiguous conditions and
six from each clear valence condition (positive, negative).
All images were presented sequentially for 500 ms, mit
an ISI of 1500 ms, in a randomized fashion for all condi-
tionen. An additional 24 trials were presented randomly
within each block to provide jitter, during which a white
fixation cross appeared on the screen, Und 24 fixation trials
were presented between each block (Figur 1). The order
of the blocks was counterbalanced across participants.
During imaging, participants responded by pressing one
of two buttons with their dominant hand. Darüber hinaus, Die
ratings of surprised faces on the valence task allowed for
the determination of positivity–negativity bias and RT.

Following each scanning session, participants also com-
pleted the following behavioral scales: BDI (Beck et al.,
1961) and the STAIs/STAIt (Spielberger et al., 1988).

Imaging Parameters

Images were acquired on a Philips Achieva 3.0-T scanner
(Philips Medical Systems, Bothell, WA), equipped with a
SENSE birdcage head coil. Anatomical T1-weighted images
were collected using a high-resolution 3-D magnetization-
prepared rapid gradient-echo sequence, mit 160 contig-
uous 1-mm thick sagittal slices (Echozeit = 4.6 ms,
repetition time = 9.8 ms, Sichtfeld = 240 mm, umdrehen
Winkel = 8°, Voxelgröße = 1 × 0.94 × 0.94 mm). Funktional

Tisch 1. Results of Stimulus-matching Procedure for IAPS Scenes

Negative Pictures

Ambiguous Pictures

Positive Pictures

Mean (SEM ) valence

Mean (SEM ) arousal

2.39 (0.08)

5.36 (0.20)

5.19 (0.26)

4.99 (0.18)

7.93 (0.07)

4.96 (0.18)

Valence scores are based on the normative 9-point scale (1 = very unpleasant, 9 = very pleasant). There was a significant difference between
each condition of pictures (F(2, 10) = 1469.44, P < .001, η2 = .95), such that positive pictures were rated as more positive than ambiguous and negative pictures, and negative pictures were rated as more negative than ambiguous pictures (all ps < .001). Arousal was also based on the normative 9-point scale (1 = low arousal, 9 = high arousal ). Arousal was equated across these three conditions (F(2, 10) = 1.56, p = .26, η2 = .10). Neta, Kelley, and Whalen 549 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 5 / 4 2 5 5 / 4 4 7 / 1 5 9 4 4 7 5 / 0 1 8 7 3 7 o 9 c 0 n 7 _ 9 a / _ j 0 o 0 c 3 n 6 3 _ a p _ d 0 0 b 3 y 6 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 i 2 3 e s / j t f / . u s e r o n 1 7 M a y 2 0 2 1 Figure 1. A depiction of the experimental design. The paradigm consisted of eight runs of four experimental blocks each: two blocks each of facial expressions and IAPS stimuli interleaved. Each block began with a brief (2000 msec) instruction statement: “valence” or “gender” (nonvalence) for the face blocks and “valence” or “social/nonsocial” (nonvalence; i.e., “Does the picture contain a person?”) for the IAPS blocks. Each block consisted of 24 images, 12 from the ambiguous conditions (e.g., surprised faces) and six from each clear valence condition (positive, negative; e.g., happy and angry faces, respectively). All images were presented sequentially for 500 msec, with an ISI of 1500 msec, in a randomized fashion for all conditions. An additional 24 trials were presented randomly within each block to provide jitter, during which a white fixation cross appeared on the screen, and 24 fixation trials were presented between each block. The order of the blocks was counterbalanced across participants. images were acquired using an echo-planar T2*-weighted imaging sequence. Each volume consisted of 36 interleaved 3-mm thick slices, AC–PC aligned, with 0.5-mm interslice gap (echo time = 35 msec, repetition time = 2000 msec, field of view = 240 mm, flip angle = 90°, voxel size = 3 × 3 × 3.5 mm). Despite our focus on the amygdala, we used slices aligned with the AC–PC plane so that we could effec- tively interrogate whole-brain effects of processing am- biguity across stimulus and task categories. fMRI Analysis Processing of fMRI data took place in SPM2 ( Wellcome Department of Cognitive Neurology, London, United Kingdom). First, several preprocessing steps were em- ployed to increase the signal-to-noise ratio before for- mation of statistical images. Slice time correction was employed to correct for acquisition delays within func- tional volumes. Next, realignment corrected for participant head motion within and across runs using rigid body trans- formation. Functional data then underwent unwarping, which corrects for image distortions caused by move- ment by susceptibility interactions (Andersson, Hutton, Ashburner, Turner, & Friston, 2001). Functional data were normalized to the EPI.mnc template, which warped data into Montreal Neurological Institute space. Normalized functional data were then spatially smoothed (6-mm FWHM) using a Gaussian kernel. Next, the general linear model was performed to examine separate task contributions to the fMRI signal. Surprised, angry, and happy expressions as well as ambiguous, neg- ative, and positive IAPS were modeled as separate task regressors, which were convolved with a canonical hemo- dynamic response function. These task regressors were included in a general linear model along with covariates of noninterest (session mean, run regressor, linear trend, and six movement parameters derived from realignment corrections) to compute parameter estimates (images con- taining weighted parameter estimates) for each comparison at each voxel and for each participant. Contrast maps were then entered into a random effects model, which accounts for intersubject variability and allows population-based inferences to be drawn. Param- eter estimates for the ambiguous stimuli (i.e., surprised faces and ambiguously valenced IAPS) were then sub- mitted to a 2 × 2 ANOVA examining the effects of material type (faces vs. IAPS) and task instruction (explicit valence judgments vs. incidental non judgments). Brain regions showing significant main effects in these analyses were ex- tracted as ROIs (threshold: p < .001, as determined by Monte Carlo simulations implemented in AlphaSim within AFNI software [Cox, 1996] correcting for the whole brain). Given the current studyʼs focus on the amygdala, we im- posed a significance threshold of p < .05, corrected for mul- tiple comparisons over the amygdala volume (∼4500 mm3, defined using the Automated Anatomical Labeling atlas; Maldjian, Laurienti, Kraft, & Burdette, 2003) and also deter- mined by Monte Carlo simulations, a strategy we have im- plemented in previous studies (Davis, Johnstone, Mazzulla, Oler, & Whalen, 2010; Kim et al., 2003, 2010; Johnstone, Somerville, Alexander, et al., 2005). ROI ROI analyses were conducted using the MarsBaR tool within SPM2 ( Wellcome Department of Imaging Neuroscience, London, United Kingdom). Spherical regions (6-mm ra- dius) were defined around each of these peak activations, and all significant voxels ( p < .001) were included. Signal intensities for each ROI were then calculated separately for each task comparison (i.e., ambiguously valenced faces and IAPS, for the valence and nonvalence tasks separately) and examined statistically using repeated-measures ANOVA. Then, the BOLD signal (beta weights) from the significantly 550 Journal of Cognitive Neuroscience Volume 25, Number 4 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 5 / 4 2 5 5 / 4 4 7 / 1 5 9 4 4 7 5 / 0 1 8 7 3 7 o 9 c 0 n 7 _ 9 a / _ j 0 o 0 c 3 n 6 3 _ a p _ d 0 0 b 3 y 6 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 i 2 3 e s / j f / . t u s e r o n 1 7 M a y 2 0 2 1 activated voxels was extracted from each ROI for each participant and submitted for off-line testing. RESULTS Behavioral Results Valence Ratings Angry and happy expressions were rated as consistently negative (95.2% of trials) and positive (93.1% of trials), re- spectively. Figure 2A shows that these same participants differed in their tendency to interpret surprised faces negatively versus positively. As a manipulation check of the valence conditions (ambiguously, as compared with clearly valenced stimuli), a Stimulus (IAPS, faces) × Valence (ambiguous, negative, positive) repeated-measures ANOVA Figure 3. RTs (mean ± standard error) are greater when rating the valence of ambiguous stimuli, as compared with an incidental nonvalence rating, and they were also greater for the ambiguous scenes than faces. revealed a significant main effect of Valence (F(2, 29) = 1576.1, p < .001), and pairwise comparisons (LSD cor- rected) revealed that negative stimuli were rated as more negative than ambiguous stimuli, which were rated as more negative than positive stimuli ( ps < .001). Impor- tantly, there was a significant positive correlation in ratings of ambiguous IAPS and faces (r = .50, p = .005; Figure 2B), such that participants who tended to interpret surprised faces as positive also tended to interpret ambiguous IAPS as positive. RT A Stimulus (IAPS, faces) × Task (valence, nonvalence) repeated-measures ANOVA revealed a significant main effect of Stimulus (F(1, 30) = 7.3, p = .011), and pairwise comparisons (LSD corrected) revealed that participants took longer to rate the IAPS, as compared with the face stimuli (Figure 3). A significant main effect of Task (F(1, 30) = 295.3, p < .001) revealed that RTs were longer dur- ing the valence as compared with the nonvalence task. There was no significant Stimulus × Task interaction ( p > .7).

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Questionnaire Data

As noted in the Methods section, we administered per-
sonality and trait measure scales to document that these
participants fell within a healthy psychiatric range on cer-
tain measures (d.h., depression, anxiety) across all partici-
Hose. Results indicated that all scores for depression
(BDI) and anxiety (STAI) were within normal limits.

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Figur 2. Individual differences in rating valence of surprised expressions
and ambiguous scenes. (A) Consistent with previous work, angry faces
are rated consistently negative, happy faces are consistently positive,
and surprised ratings vary from negative to positive, revealing individual
differences in how people interpret the valence of these expressions.
(B) There was a significant positive correlation between ratings for
ambiguous faces and scenes. Individuals who tended to rate surprised
faces as positive also tended to rate the ambiguous IAPS scenes as positive.

fMRI Results

A voxelwise whole-brain 2 × 2 repeated-measures ANOVA
on the ambiguous trials with the factors of Stimulus (IAPS,
faces) and Task (valence, nonvalence) revealed brain re-
gions showing a main effect of Stimulus, a main effect of

Neta, Kelley, and Whalen

551

38.92

Left medial superior frontal gyrus

Brain Regions Preferentially Sensitive to Task

Task, and an interaction between Stimulus and Task in re-
sponse to ambiguity (Tisch 2). To explore the directionality
of each effect, regions identified in the statistical F maps
were examined further using ROI analyses. It should be
noted that when RTs were regressed out, none of the re-
ported effects changed.

Tisch 2. Brain Regions Identified as Responding to Ambiguous
Stimuli

Region

Main Effect of Stimulus (Faces vs. Scenes)

−33 −39 −21

364.66

Left fusiform gyrus

33 −36 −21

201.71 Right fusiform gyrus

37.0

Right ACC

23.78

Left ACC

32.61

Left dACC

28.14 Right inferior frontal gyrus

−6

−3 −42

−6

−36

−51

27.70

Left superior frontal gyrus

18 −30

26.70

Left superior temporal gyrus

−57 −3 −21

34.26

Left middle temporal gyrus

54 −6 −27

38.48 Right inferior temporal gyrus

−27 −90

−39 −84

36 −84

97.35

Left superior occipital gyrus

170.36

Left middle occipital gyrus

124.58 Right middle occipital gyrus

Main Effect of Task ( Valence vs. Nonvalence)

−30

−54

−30

24 −9

21 −3

69.82 Medial superior frontal cortex

35.09 Right dACC

47.56 Right FO

46.84

Left insula

34.42 Right inferior frontal gyrus

43.33

Left inferior frontal gyrus

24.26

Left middle frontal gyrus

15.07 Right superior frontal gyrus

48 −42

−12 −78

12 −75

18.51 Right middle temporal gyrus

18.42

Left cuneus

18.76 Right cuneus

Stimulus × Task Interaction

−30 −63

−39 −54

−6

21.78

Left middle occipital gyrus

17.61

Left inferior parietal lobule

16.89

Left medial frontal gyrus

Brain Regions Preferentially Sensitive to Stimulus

The main effect of Stimulus revealed activations in inferior
temporal cortex, with a peak on the bilateral medial fusiform
gyrus (X, j, z: left = −33, −39, −21; right = 33, −36, −21;
main effects of Stimulus, links: F(1, 29) = 191.0, P < .001; right: F(1, 29) = 126.3, p < .001). ROI analyses revealed that activity here was greater for the IAPS stimuli than the face stimuli (Figure 4). Many of the other regions that showed a main effect of Stimulus (Table 2) revealed a similar pattern (i.e., greater activity for IAPS than faces), with the exception of the right ACC (x, y, z = 3, 36, 6; main effects of stimulus: F(1, 29) = 45.8, p < .001) and the right inferior fron- tal gyrus (x, y, z = 57, 12, 24; main effects of Stimulus: F(1, 29) = 14.7, p = .001), which showed greater activity for the faces than the IAPS stimuli. Of these regions, only the latter one also showed a main effect of Task (F(1, 29) = 11.6, p = .002), with a preferential response to the valence, as compared with the nonvalence task. None of these regions showed a significant interaction ( p > .1).

The main effect of Task revealed activity in the bilateral AI/FO
(left = −31, 21, −3; right = 36, 21, −3; main effects of task,
links: F(1, 29) = 38.9, P < .001; right: F(1, 29) = 49.1, p < .001) as well as in the dACC (x, y, z = 0, 18, 48; main effect of Task: F(1, 29) = 49.8, p < .001; Figure 5A). ROI analyses in all of the regions that showed a main effect of Task (Table 2) revealed that activity here was greater for the explicit valence judgment task than the nonvalence (gender and social) task for both categories (faces and scenes, respectively). More- over, the left AI/FO and the left inferior frontal gyrus also showed a main effect of Stimulus (F(1, 29) = 12.5, p = .001; F(1, 29) = 15.6, p < .001; respectively), with a prefer- ential response to the IAPS than face stimuli. Several of these regions, including the dACC, showed a significant inter- action of Stimulus and Task (F(1, 29) = 5.4, p = .03), where there was a preferential response to the IAPS, but only during the nonvalence task. Finally, with a lower significance threshold (see fMRI Analysis), we found a region of ventral amygdala (x, y, z = −12, −3, −21) also showed a main effect of Task. An ROI analysis was used to examine Stimulus (IAPS, faces) × Task (valence, nonvalence) effects. We confirmed this main effect of Task (F(1, 29) = 10.6, p = .003), but no other main effects or interactions were significant ( ps >
.2). Like the other regions showing a main effect of Task,
there was greater activity here for the valence task as com-
pared with the nonvalence task (Figure 5B).1

Brain Regions Exhibiting an Interaction of
Stimulus and Task

Three distributed cortical regions demonstrated a cross-
over interaction, including the left middle occipital gyrus

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Zeitschrift für kognitive Neurowissenschaften

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(X, j, z = −30, −63, 33; interaction: F(1, 29) = 16.0, p =
.001), the left inferior parietal lobule (X, j, z = −39, −54,
48; interaction: F(1, 29) = 17.8, P < .001), and the left medial frontal gyrus (x, y, z = −6, 51, 21; F(1, 29) = 11.3, p = .002; Figure 6). DISCUSSION The neural architecture for responding to ambiguity relies, in part, on cognitive control processing that is recruited when participants make a judgment that requires the res- olution of ambiguity. We found that activity in regions l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 5 / 4 2 5 5 / 4 4 7 / 1 5 9 4 4 7 5 / 0 1 8 7 3 7 o 9 c 0 n 7 _ 9 a / _ j 0 o 0 c 3 n 6 3 _ a p _ d 0 0 b 3 y 6 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 i 2 3 e s / j t . f / u s e r o n 1 7 M a y 2 0 2 1 Figure 5. Brain regions active for the main effect of task. (A) Three task control regions, comprising the cingulo-opercular network, showed greater activity during the valence task, as compared with the nonvalence task (gender judgment for face stimuli, social judgment for IAPS scenes). (B) A region of ventral amygdala showed greater activity to ambiguous stimuli during the valence task. Neta, Kelley, and Whalen 553 Figure 6. Brain regions exhibiting an interaction of stimulus and task include (A) left medial frontal gyrus, (B) left inferior parietal lobule, and (C) left middle occipital gyrus. D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 5 / 4 2 5 5 / 4 4 7 / 1 5 9 4 4 7 5 / 0 1 8 7 3 7 o 9 c 0 n 7 _ 9 a / _ j 0 o 0 c 3 n 6 3 _ a p _ d 0 0 b 3 y 6 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 i 2 3 e s / j t / f . u s e r o n 1 7 M a y 2 0 2 1 comprising a task control network (i.e., cingulo-opercular network) provides a central part of this architecture, as it also has been shown to play a crucial role in processing ambiguity in other domains (i.e., linguistic, low-level per- ception). This domain-general processing is consistent with our behavioral results that demonstrated that individ- ual differences in the bias to resolve ambiguity positively or negatively were correlated across the stimulus boundaries (i.e., the same participants who showed a positive bias when resolving ambiguity of facial expressions showed a similar positive bias when resolving ambiguity in scenes). Finally, we found that activity in the ventral amygdala was greater to faces and scenes that were rated explicitly along the dimension of valence, consistent with findings that the ventral amygdala tracks valence (Whalen et al., 2009; Kim et al., 2003). Here, we discuss the implications of these findings, specifically in the context of task control and specific emotion processing systems. The Function of the Cingulo-opercular Network A meta-analysis of 10 different tasks showed that three cortical regions, comprising the cingulo-opercular net- work (dACC and the bilateral AI/FO), showed three dis- tinct types of task-control signals: (1) signals tied to the start of a task, which are likely related to the instantia- tion of task parameters; (2) activity sustained at a con- stant level across the task period, which likely reflects maintenance of those parameters; and (3) error-related activity, which is likely related to performance feed- back (Dosenbach et al., 2006). Thus, this network has been referred to as a “core” task set system (Dosenbach et al., 2006, 2007), which is thought to be involved in controlling task performance through the stable main- tenance of task parameters, as well as making and moni- toring choices in accordance with those parameters (see Dosenbach, Fair, Cohen, Schlaggar, & Petersen, 2008, for a review). Aside from these higher-order cognitive functions, there are widely replicated findings implicating the dACC in conflict monitoring (Botvinick, Braver, Barch, Carter, & Cohen, 2001; Miller & Cohen, 2001). Moreover, the AI shows transient responses related to electrodermal arousal (Critchley, Elliott, Mathias, & Dolan, 2000), empathy (Singer et al., 2004), the generation of subjective feelings and integration of sensory inputs (see Medford & Critchley, 2010, for a review), and other socioemotional processing (Chang, Smith, Dufwenberg, & Sanfey, 2011; Sanfey, Rilling, Aronson, Nystrom, & Cohen, 2003; Lane, Fink, Chua, & Dolan, 1997). This region is also shown, via resting state functional connectivity (see Dosenbach et al., 2007; Fox, Corbetta, Snyder, Vincent, & Raichle, 2006; Fox et al., 2005) to coactivate with the dACC as part of a network that is nonspecifically involved in general goal-directed cognition (Chang, Yarkoni, Khaw, & Sanfey, 2012; Yarkoni, Poldrack, Nichols, Van Essen, & Wager, 2011; Dosenbach et al., 2006). Thus, task-related manipulations (e.g., con- flict monitoring) that drive activity in one of these regions (dACC) is likely to also affect activation in the others (bilateral AI), providing further evidence that these regions comprise a network or system that is implicated in many instances requiring attentional resources or task control (see also Nee, Wager, & Jonides, 2007; Duncan & Owen, 2000, for meta-analyses of cognitive control paradigms). 554 Journal of Cognitive Neuroscience Volume 25, Number 4 As such, although the dACC and AI are independently implicated in specific processes (e.g., conflict monitoring, generating subjective feelings), the specific role of these regions likely lies in the domain of general task control. In other words, many different task demands are likely to require an ability to sustain attention, monitor task parameters, and modulate arousal (Nelson et al., 2010; Dosenbach et al., 2006), but this does not indicate that the specific role for these regions is to, for example, gen- erate subjective feelings. A Role for the Cingulo-opercular Network in Ambiguity We found increased activity in this network in response to surprised faces and ambiguous IAPS, but only when mak- ing judgments that require the resolution of ambiguity. This network has been shown to respond to ambiguity in semantic (Thompson-Schill et al., 1997), visual mo- tion (Sterzer et al., 2002), and face processing (Demos et al., 2004) paradigms. This is consistent with the notion that these regions are recruited during tasks where a stimulus–response mapping needs to be made concern- ing the ambiguous stimulus. In other words, ambiguity is defined here as something that can be interpreted in more than one way and, in turn, requires a selection between competing alternatives. Research in neuroeconomics has demonstrated a link between the AI and ambiguity in deci- sion making, particularly in situations that require behav- ioral flexibility that is dependent on contextual analysis (Huettel, Stowe, Gordon, Warner, & Platt, 2006), although ambiguous decisions (multiple possible outcomes with unknown probabilities) are made more quickly than risky decisions (multiple possible outcomes with known prob- abilities). In other words, as in our own data showing that these regions were still active during explicit valence judg- ments even when RT was regressed out, activity in this network seems to be unrelated to time on task (see also Neta, Schlaggar, & Petersen, under revision, but see Grinband et al., 2011). Recent work on perceptual recognition found that ac- tivity in the AI/FO region remained near baseline until the moment of recognition, suggesting a relation to the mo- ment of the decision itself (Ploran et al., 2007). Similarly, the dACC was shown to learn from experiences by mon- itoring and integrating outcomes (Behrens, Woolrich, Walton, & Rushworth, 2007), playing a crucial role in the update (late) period of such decision making, not during the initial computation of uncertainty (see Singer, Critchley, & Preuschoff, 2009, for a review). These find- ings suggest that these regions may not be involved in the process of deciding how to resolve ambiguous stim- uli, but rather, they are crucial at the point during which ambiguity is resolved per se. Taken together, these data support the notion that activity in the cingulo-opercular network is not simply related to task difficulty, and we propose that this activity is most readily observed in tasks that (1) require a decision relevant to the ambiguity (i.e., valence) and (2) require resolution rather than simple detection or perception of ambiguity. Future work can investigate how these transient responses to ambiguity relate to the transient error-related activity identified in the same regions (Neta et al., under revision). Limitations We note several limitations in interpreting the present find- ings. First, the IAPS stimuli were significantly more arous- ing than the face stimuli. As noted in the Methods section, this is somewhat expected given the nature of these stim- ulus categories, where the IAPS scenes carry much more information than individual facial expressions. Given this effect, the brain regions that were found to show a main effect of stimulus may be, at least in part, modulated by this difference in arousal. However, we focus here predomi- nantly on the main effects of task, which is not impacted by these arousal effects. Second, although we compared two stimulus categories, one of individual facial expressions and another that rep- resents nonface emotional stimuli (IAPS scenes), we note that approximately half of our scenes contained (at least part of ) faces and human forms. As such, the present data showing similar neural responses to ambiguity between these two stimulus sets might still require a social element, and the present result can be mostly cautiously summa- rized by saying that this network was similarly involved in processing ambiguity to directly presented faces and other faces within more complex social scenes. Finally, based on previous work showing that a region of the dorsal amygdala tracks surprised faces during passive viewing (Kim et al., 2003), we predicted that this region would show greater activity to stimuli with an ambiguous, as compared with clear valence, and that this effect might be modulated by task demands. Indeed, this would fit well with nonhuman animal work implicating the amygdala in associative orienting, meaning that it functions to alert other brain areas in instances of uncertainty when there is a greater amount to learn (Gallagher, Graham, & Holland, 1990; Kapp, Frysinger, Gallagher, & Haselton, 1979). However, we did not find a region of dorsal amyg- dala in the omnibus ANOVA in the current study. It could be that our task manipulation did not allow for the sen- sitivity to pick up on the amygdala response to ambiguity in the implicit nonvalence task (as our previous work has demonstrated such an effect only for passive viewing). In- deed, meta-analyses have demonstrated that amygdala re- sponses to emotional stimuli can be diminished during an active task, as compared with passive viewing (Costafreda, Brammer, David, & Fu, 2008). Future work might help to disentangle these effects by directly comparing passive viewing to responses during both explicit and implicit evaluations of ambiguous stimuli. Neta, Kelley, and Whalen 555 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 5 / 4 2 5 5 / 4 4 7 / 1 5 9 4 4 7 5 / 0 1 8 7 3 7 o 9 c 0 n 7 _ 9 a / _ j 0 o 0 c 3 n 6 3 _ a p _ d 0 0 b 3 y 6 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 i 2 3 e s / j f . t / u s e r o n 1 7 M a y 2 0 2 1 Conclusions The brain regions that were recruited while making a valence judgment about ambiguously valenced stimuli (i.e., the cingulo-opercular network, ventral amygdala) were active for both the ambiguous faces (surprised expressions) and scenes. Moreover, the bias with which people resolve ambiguity is consistent across these categories of stimuli. Thus, the neural and behavioral responses required when resolving ambiguity transcends stimulus boundaries and is better defined by an uncertainty in stimulus–response mapping that is created when people are required to make a selection between competing alternatives. At a weaker threshold, a targeted analysis of the amygdala based on previous data showed that the dorsal amygdala showed the highest response to surprised faces, but only during the nonvalence task. Together, these data suggest that, although some of the domain-general processes that come on-line in the “face” of ambiguity are similar across many categories of ambiguity (faces and scenes in the present work; semantic, visual motion, and economic decision- making ambiguity in previous work), there may be other dedicated circuits for some social and emotional ambiguity and, specifically, for biologically relevant learning situations involving faces. Acknowledgments We thank J. V. Haxby for advice on experimental design and com- ments on the manuscript as well as S. E. Petersen and D. D. Wagner for fruitful discussions about results. We also thank G. Wolford for statistical advising and comments on the manu- script, C. J. Norris for advice on experimental design, and A. L. Palmer and S. V. Fogelson for discussion about methods. Finally, we thank R. A. Loucks for assistance in recruitment of participants and help with data collection and survey data entry. This work was supported by NIMH 080716. Reprint requests should be sent to Maital Neta, Department of Neurology, Washington University School of Medicine, Room 2220, 4525 Scott Ave., St. Louis, MO 63110, or via e-mail: maital@npg. wustl.edu, maital@dartmouth.edu. Note 1. 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