Meeting George Bush versus Meeting Cinderella

The rest of the title of this article by von Cramon and Schubotz is "The Neural Response When Telling Apart What is Real from What is Fictional in the Context of Our Reality." Our ability to distinguish fact from fiction emerges early during our development, and by the age of 5, we not only differentiate reality from fiction but can also distinguish between different fictional worlds. The neural correlates underlying this ability are unknown. The authors obtain fMRI images showing significant difference in brain activity while processing real versus fictional conditions. The graphic is from the paper just to include a pretty picture, I'll spare you the details, because they really don't add all that much to the bottom line:

The processing of real and fictional scenarios activated a common set of regions including medial-temporal lobe structures. When the scenarios involved real people, brain regions associated with episodic memory retrieval and self-referential thinking, the anterior prefrontal cortex and the precuneus/posterior cingulate, were more active. In contrast, areas along the left lateral inferior frontal gyrus (shown in the graphic), associated with semantic memory retrieval, were implicated for scenarios with fictional characters. This implies that there is a fine distinction in the manner in which conceptual information concerning real persons in contrast to fictional characters is represented. In general terms, the findings suggest that fiction relative to reality tends to be represented in more factual terms, whereas our representations of reality relative to fiction are colored by personal subjectivity. What modulates our understanding of the relative difference between reality and fiction seems to be whether such character-type information is coded in self-relevant terms or not.

The authors note their agreement with the statement of William James: "In the relative sense, then, the sense in which we contrast reality with simple unreality, ... reality means simply relation to our emotional and active life

Rapid orienting to positive, as well as negative, emotional stimuli.

Most of the work on how emotions focus our attention has focused on negative stimuli (snakes, angry faces, etc.) Brosch et al. use ERP measurement to note that our attention also can very reliably be captured by positive nurturance stimuli such as baby faces. The results confirm that biological relevance, and not exclusively fear, produces an automatic spatial orienting toward the location of a stimulus. From the paper:

...we recorded event-related potentials from 20 subjects performing a dot-probe task in which the cues were fear-inducing and nurturance-inducing stimuli (i.e., anger faces and baby faces). Highly similar validity modulation was found for the P1 time-locked to target onset, indicating early attentional capture by both positive and negative emotional stimuli. Topographic segmentation analysis and source localization indicate that the same amplification process is involved whether attention orienting is triggered by negative, fear-relevant stimuli or positive, nurturance-relevant stimuli.

Illustration of the experimental sequence. Each trial started with a fixation cross. Then the cue, consisting of two images presented on the left and right sides of the screen, was presented briefly. One of the two pictures was an emotional face, and the other was a neutral face. Following offset of the face pair, the fixation cross was presented randomly for 100, 150, 200, 250, or 300 ms. Afterward, the target, a triangle pointing upward or downward, appeared for 150 ms in the location of one of the previously presented faces. In a valid trial, the triangle was in the location of the emotional image; in an invalid trial, the triangle was in the location of the neutral image. Some participants were required to respond if the triangle pointed upward, and the others were required to respond if the stimulus pointed downward. SOA = stimulus onset asynchrony.

Our facial touch sensitivity - enhanced by viewing a touch.

Studies have shown that observing touch on another person's body activates brain regions involved in tactile perception, even when the observer's body is not directly stimulated. Previous work has shown that in some synaesthetes, this effect induces a sensation of being touched. Serino et al. show in nonsynaesthetes, that

..when observers see a face being touched by hands, rather than a face being merely approached by hands, their detection of subthreshold tactile stimuli on their own faces is enhanced. This effect is specific to observing touch on a body part, and is not found for touch on a nonbodily stimulus, namely, a picture of a house...Thus, observing touch can activate the tactile system, and if perceptual thresholds are manipulated, such activation can result in a behavioral effect in nonsynaesthetes.The effect is maximum if the observed body matches the observer's body.

Figure - Visual stimuli used in the tactile confrontation task. In blocked trials, subjects viewed an image of their own face, another person's face, or a house. In each trial, the finger on the bottom left, the finger on the bottom right, or both fingers moved toward the target; in the touch condition, the finger (or fingers) actually touched the target, and in the no-touch condition, the finger (or fingers) reached a position 5 cm away from the target.

Think of when you might have watched a romantic touch in a movie, sitting next to someone you wished would stroke you.....

Your lips in my brain...

The title of the Kriegstein et al. article is: "Simulation of talking faces in the human brain improves auditory speech recognition." It turns out that observing a specific person talking for 2 min improves our subsequent auditory-only speech and speaker recognition for this person. This shows that, in auditory-only speech, the brain exploits previously encoded audiovisual correlations to optimize communication. The authors suggest that this optimization is based on speaker-specific audiovisual internal models, which are used to simulate a talking face. From the author's introduction:

Human face-to-face communication works best when one can watch the speaker's face. This becomes obvious when someone speaks to us in a noisy environment, in which the auditory speech signal is degraded. Visual cues place constraints on what our brain expects to perceive in the auditory channel. These visual constraints improve the recognition rate for audiovisual speech, compared with auditory speech alone. Similarly, speaker identity recognition by voice can be improved by concurrent visual information. Accordingly, audiovisual models of human voice and face perception posit that there are interactions between auditory and visual processing streams

Neurophysiological face processing studies indicate that distinct brain areas are specialized for processing time-varying information [facial movements, superior temporal sulcus (STS), and time-constant information (face identity, fusiform face area (FFA). If speech and speaker recognition are neuroanatomically dissociable, and the improvement by audiovisual learning uses learned dependencies between audition and vision, the STS should underpin the improvement in speech recognition in both controls and prosopagnosics. A similar improvement in speaker recognition should be based on the FFA in controls but not prosopagnosics. Such a neuroanatomical dissociation would imply that visual face processing areas are instrumental for improved auditory-only recognition.

The authors in fact obtained these results when they used functional magnetic resonance imaging (fMRI) to show the response properties of these two areas.

Simple curves can influence whether we see happy or sad faces.

Here is an interesting bit of work from Xu et al. showing that adaptation to simple stimuli (like the shape of a mouth) that are processed early in the visual hierarchy can influence our perception of higher level perceptions (i.e., of faces) that are analyzed at higher levels of the visual hierarchy. Thus adaptation to a concave (sad) cartoon mouth shape makes subsequent perception more likely to report a happy face, and vice versa. Their abstract:

Adaptation is ubiquitous in sensory processing. Although sensory processing is hierarchical, with neurons at higher levels exhibiting greater degrees of tuning complexity and invariance than those at lower levels, few experimental or theoretical studies address how adaptation at one hierarchical level affects processing at others. Nevertheless, this issue is critical for understanding cortical coding and computation. Therefore, we examined whether perception of high-level facial expressions can be affected by adaptation to low-level curves (i.e., the shape of a mouth). After adapting to a concave curve, subjects more frequently perceived faces as happy, and after adapting to a convex curve, subjects more frequently perceived faces as sad. We observed this multilevel aftereffect with both cartoon and real test faces when the adapting curve and the mouths of the test faces had the same location. However, when we placed the adapting curve 0.2° below the test faces, the effect disappeared. Surprisingly, this positional specificity held even when real faces, instead of curves, were the adapting stimuli, suggesting that it is a general property for facial-expression aftereffects. We also studied the converse question of whether face adaptation affects curvature judgments, and found such effects after adapting to a cartoon face, but not a real face. Our results suggest that there is a local component in facial-expression representation, in addition to holistic representations emphasized in previous studies. By showing that adaptation can propagate up the cortical hierarchy, our findings also challenge existing functional accounts of adaptation.

Here are some examples of face stimuli used in the studies, in which subjects were experiments as well as naive subjects:


Figure - Examples of the face stimuli used in this study. a, Cartoon faces used in experiment 1, generated with our anti-aliasing program. The mouth curvature varied from concave to convex to produce sad to happy expressions. b, Ekman faces used in experiment 2. The first (sad) and last (happy) images were taken from the Ekman PoFA database, and the intermediate ones were generated with MorphMan 4.0. c, MMI faces used in experiments 3 and 4. The first (sad), middle (neutral), and last (happy) images were taken from the MMI face database, and the other images were generated with MorphMan 4.0.

Differing perception of facial expressions in the East and West

Nagourney describes a study in the March issue of The Journal of Personality and Social Psychology reinforcing previous work showing that Westerners are more likely to see emotions as individual feelings while East Asians see them as inseparable from the feelings of the group. Many researchers have suggested that East Asians take a more holistic view of the world. Here is the abstract of the Masuda et al. article:

Two studies tested the hypothesis that in judging people's emotions from their facial expressions, Japanese, more than Westerners, incorporate information from the social context. In Study 1, participants viewed cartoons depicting a happy, sad, angry, or neutral person surrounded by other people expressing the same emotion as the central person or a different one. The surrounding people's emotions influenced Japanese but not Westerners' perceptions of the central person. These differences reflect differences in attention, as indicated by eye-tracking data (Study 2): Japanese looked at the surrounding people more than did Westerners. Previous findings on East-West differences in contextual sensitivity generalize to social contexts, suggesting that Westerners see emotions as individual feelings, whereas Japanese see them as inseparable from the feelings of the group.

Brain imaging of our parental instinct

A group of collaborators reports in PLOS ONE a specific and rapid neural signature for our parental instinct:

Darwin originally pointed out that there is something about infants which prompts adults to respond to and care for them, in order to increase individual fitness, i.e. reproductive success, via increased survivorship of one's own offspring. Lorenz proposed that it is the specific structure of the infant face that serves to elicit these parental responses, but the biological basis for this remains elusive. Here, we investigated whether adults show specific brain responses to unfamiliar infant faces compared to adult faces, where the infant and adult faces had been carefully matched across the two groups for emotional valence and arousal, as well as size and luminosity. The faces also matched closely in terms of attractiveness. Using magnetoencephalography (MEG) in adults, we found that highly specific brain activity occurred within a seventh of a second in response to unfamiliar infant faces but not to adult faces. This activity occurred in the medial orbitofrontal cortex (mOFC), an area implicated in reward behaviour, suggesting for the first time a neural basis for this vital evolutionary process. We found a peak in activity first in mOFC and then in the right fusiform face area (FFA)....These findings provide evidence in humans of a potential brain basis for the “innate releasing mechanisms” described by Lorenz for affection and nurturing of young infants.


The group analysis reveals a significant peak in the medial orbitofrontal cortex in the 10–30 Hz band in the 0–250 ms (first two columns), 100–350 ms (third column) and 200–450 ms (fourth column) windows when participants viewed infant (upper row) and not when they viewed adult faces (lower row). The fifth column shows the integrated map over the three time windows...In order to see the extent of the spread of activity over the fusiform cortices elicited by faces, the group activity is superimposed on a ventral view of the human brain (with the cerebellum removed).

100% accuracy in automatic face detection.

A problem with the automatic face recognition systems being tested in some airport security screening systems is that none can cope with the kind of image variability encountered in the real world. Jenkins and Burton have used a simple averaging technique to increase the accuracy of an industry standard face-recognition algorithm from 54% to 100%. They averaged the images from 20 different photographs for each of 25 male celebrities who were also in a large public online database of 31,077 photographs of famous faces, comprising an average of nine different photos for each of 3628 celebrities - these images were highly variable in their quality and covered a wide range of lighting conditions, facial expressions, poses, and age. Using the FaceVACS (Cognitec Systems GmbH, Dresden, Germany)industry standard face-recognition system that has been widely adopted, they fed this database their averaged images for each of 25 male celebrities who were also in the online database (excluding photos that were both in their sample and in the database). With the averaged images, the database returned the correct identification 100% of the time. When individual photographs were presented to the database the correct identification was returned only ~50% of the time. From their text:

We demonstrated this improvement with a commercially available algorithm and an online face database over which we had no control. We suggest that image averaging enhances performance by stabilizing the face image. With standard photographs, the match tends to be dominated by aspects of the image that are not diagnostic of identity (e.g., lighting and pose). Averaging together multiple photographs of the same person dilutes these transients while preserving aspects of the image that are consistent across photos. The resulting images capture the visual essence of an individual's face and elevate machine performance to the standard of familiar face recognition in humans. It would be technically straightforward to incorporate an average image into identification documents. Doing so would greatly reduce the incidence of face-recognition errors and raise the prospect of a viable automatic face-recognition infrastructure.


Example photographs of Bill Clinton and their average (right). [Image 1, photo by Marc Nozell (www.flickr.com/photos/marcn/534512066); image 2, photo by Roger Goun (www.flickr.com/photos/sskennel/829574139); image 20, photo by Nelson Pavlosky (www.flickr.com/photos/skyfaller/26752190). All photos were used under a Creative Commons license.] Different pictures of a single face can vary enormously, making automatic recognition difficult. Averaging together multiple photos of the same face stabilizes the image, improving performance dramatically.

Face perception after no experience of faces

This work really nails down the fact that face processing is a special perceptual process and is organized as such at birth, as contrasted with having its origin in a more general-purpose perceptual system that becomes specialized after frequent visual experiences. Sugita has studied face perception in monkeys reared with no exposure to faces. Here is his abstract, and one figure from the paper:

Infant monkeys were reared with no exposure to any faces for 6–24 months. Before being allowed to see a face, the monkeys showed a preference for human and monkey faces in photographs, and they discriminated human faces as well as monkey faces. After the deprivation period, the monkeys were exposed first to either human or monkey faces for a month. Soon after, the monkeys selectively discriminated the exposed species of face and showed a marked difficulty in regaining the ability to discriminate the other nonexposed species of face. These results indicate the existence of an experience-independent ability for face processing as well as an apparent sensitive period during which a broad but flexible face prototype develops into a concrete one for efficient processing of familiar faces.

Figure: An infant monkey and her living circumstance. An infant monkey and a caregiver with (A) and without (B) a facemask. Both photos were taken after the face-deprivation period. (C) Toys placed in the monkey's home cage. (D) Decorations provided around the home cage.

Nature versus Nurture in Ventral Visual Cortex

Polk et al. do functional magnetic resonance imaging of monozygotic and dizygotic twins to show that genetics play a significant role in determining the cortical response to faces and places, more so than to orthographic stimuli (chairs or pseudowords). Here is their abstract, a paragraph from their concluding section and one figure from the paper.

Using functional magnetic resonance imaging, we estimated neural activity in twins to study genetic influences on the cortical response to categories of visual stimuli (faces, places, and pseudowords) that are known to elicit distinct patterns of activity in ventral visual cortex. The neural activity patterns in monozygotic twins were significantly more similar than in dizygotic twins for the face and place stimuli, but there was no effect of zygosity for pseudowords (or chairs, a control category). These results demonstrate that genetics play a significant role in determining the cortical response to faces and places, but play a significantly smaller role (if any) in the response to orthographic stimuli.


Figure legend: Patterns of estimated neural activity when viewing the four stimulus categories (axial slice). Functional activation maps were computed for the four contrasts of interest (faces, houses, pseudowords, and chairs relative to the phase-scrambled control condition), and the similarity measures (r) between these functional maps were computed for each twin pair. (Click on figure to enlarge)

The results of this study demonstrate that genetics play a significant role in determining the cortical response to faces and places. Of course, these findings do not imply that experience plays no role in determining the observed activity. To take just one example, genes that affect social behavior could potentially lead some people to look at faces and places more than other people, and the resulting difference in experience could lead to changes in the neural circuitry (we thank one of the anonymous reviewers for this example). The results simply demonstrate that genetics do play a crucial role. The results also show that genetics play a significantly smaller role in determining the cortical response to visually presented orthographic stimuli. Overall, the findings are consistent with the view that the cortical substrates of face recognition and place recognition are partially innately specified, but that the cortical response to orthographic stimuli is more dependent on experience. Face and place recognition are older than reading on an evolutionary scale, they are shared with other species, and they provide a clearer adaptive advantage. It is therefore plausible that evolution would shape the cortical response to faces and places, but not orthographic stimuli.

Subliminal Smells Can Guide Social Preferences

Here is the abstract of an interesting article by Li et al. in Psychological Science, followed by a figure showing the experimental paradigm:

It is widely accepted that unconscious processes can modulate judgments and behavior, but do such influences affect one's daily interactions with other people? Given that olfactory information has relatively direct access to cortical and subcortical emotional circuits, we tested whether the affective content of subliminal odors alters social preferences. Participants rated the likeability of neutral faces after smelling pleasant, neutral, or unpleasant odors delivered below detection thresholds. Odor affect significantly shifted likeability ratings only for those participants lacking conscious awareness of the smells, as verified by chance-level trial-by-trial performance on an odor-detection task. Across participants, the magnitude of this priming effect decreased as sensitivity for odor detection increased. In contrast, heart rate responses tracked odor valence independently of odor awareness. These results indicate that social preferences are subject to influences from odors that escape awareness, whereas the availability of conscious odor information may disrupt such effects.

Figure - The experimental paradigm. First, participant specific odor detection thresholds were determined using an ascending-staircase procedure. Then, participants completed an odor-detection and likeability judgment task. In this example, the detection threshold was at dilution 20, so dilution 22 was used in the main task. In that task, participants sniffed a bottle, indicated whether or not it contained an odor, viewed a face stimulus, and finally rated the likeability of the face. For a subset of the participants, heart rate was recorded.

The Other-Race Effect -Perceptual Narrowing develops during infancy

We are more susceptible to recognition errors when a target face is from an unfamiliar racial group, rather than our own racial group. This is referred to as the "other race effect." An interesting study from Kelly et al. looks at the development of this effect in human infants under one year of age:

Experience plays a crucial role in the development of face processing. In the study reported here, we investigated how faces observed within the visual environment affect the development of the face-processing system during the 1st year of life. We assessed 3-, 6-, and 9-month-old Caucasian infants' ability to discriminate faces within their own racial group and within three other-race groups (African, Middle Eastern, and Chinese). The 3-month-old infants demonstrated recognition in all conditions, the 6-month-old infants were able to recognize Caucasian and Chinese faces only, and the 9-month-old infants' recognition was restricted to own-race faces. The pattern of preferences indicates that the other-race effect is emerging by 6 months of age and is present at 9 months of age. The findings suggest that facial input from the infant's visual environment is crucial for shaping the face-processing system early in infancy, resulting in differential recognition accuracy for faces of different races in adulthood.

Figure - Sample stimuli from the Chinese male and Middle Eastern female conditions. The habituation face is shown at the top of each triad. The test faces (novel and familiar) are shown underneath.

The stimuli were 24 color images of male and female adult faces (age range = 23–27 years) from four different ethnic groups (African, Asian, Middle Eastern, and Caucasian). All faces had dark hair and dark eyes so that the infants would be unable to demonstrate recognition on the basis of these features. The images were photos of students. The Africans were members of the African and Caribbean Society at the University of Sheffield; the Asians were Han Chinese students from Zhejiang Sci-Tech University, Hangzhou, China; the Middle Easterners were members of the Pakistan Society at the University of Sheffield; and the Caucasians were psychology students at the University of Sheffield.

Predicting election outcomes in 100 milliseconds!

Another example of a quick judgment turning out to be more accurate than a considered one... Ballew and Todorov showed study participants transient pictures of the winner and runner-up for recent United States gubernatorial elections. Rapid, unreflective judgments of competence based solely on facial appearance (of candidates participants did not recognize) predicted the actual outcomes of gubernatorial elections. Instructions to deliberate and make a good judgment led to less accurate predictions of the election outcomes. Here is their abstract :

Here we show that rapid judgments of competence based solely on the facial appearance of candidates predicted the outcomes of gubernatorial elections, the most important elections in the United States next to the presidential elections. In all experiments, participants were presented with the faces of the winner and the runner-up and asked to decide who is more competent. To ensure that competence judgments were based solely on facial appearance and not on prior person knowledge, judgments for races in which the participant recognized any of the faces were excluded from all analyses. Predictions were as accurate after a 100-ms exposure to the faces of the winner and the runner-up as exposure after 250 ms and unlimited time exposure. Asking participants to deliberate and make a good judgment dramatically increased the response times and reduced the predictive accuracy of judgments relative to both judgments made after 250 ms of exposure to the faces and judgments made within a response deadline of 2 s. Finally, competence judgments collected before the elections in 2006 predicted 68.6% of the gubernatorial races and 72.4% of the Senate races. These effects were independent of the incumbency status of the candidates. The findings suggest that rapid, unreflective judgments of competence from faces can affect voting decisions.

Figure - An example of an experimental trial in the 250-ms presentation condition. Participants decided who was more competent.

Brain changes after rehabilitation of congenital prosopagnosia

Another article on faces...Degutis et al. show MRI changes correlating with a recovery of enhanced amplitude of the N170 ERP (electroencephalogram event related potential)component in response to faces compared to objects after training of a subject with congenital prosopagnosia (face blindness).

We used functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) to measure neural changes associated with training configural processing in congenital prosopagnosia, a condition in which face identification abilities are not properly developed in the absence of brain injury or visual problems. We designed a task that required discriminating faces by their spatial configuration and, after extensive training, prosopagnosic MZ significantly improved at face identification. Event-related potential results revealed that although the N170 was not selective for faces before training, its selectivity after training was normal. fMRI demonstrated increased functional connectivity between ventral occipital temporal face-selective regions (right occipital face area and right fusiform face area) that accompanied improvement in face recognition. Several other regions showed fMRI activity changes with training; the majority of these regions increased connectivity with face-selective regions. Together, the neural mechanisms associated with face recognition improvements involved strengthening early face-selective mechanisms and increased coordination between face-selective and nonselective regions, particularly in the right hemisphere.

It's in the Eyes!

Another curious bit on our brain's specialization for recognizing faces, noting the central role of the eyes. The abstract and a figure:

Unlike most other objects that are processed analytically, faces are processed configurally. This configural processing is reflected early in visual processing following face inversion and contrast reversal, as an increase in the N170 amplitude, a scalp-recorded event-related potential. Here, we show that these face-specific effects are mediated by the eye region. That is, they occurred only when the eyes were present, but not when eyes were removed from the face. The N170 recorded to inverted and negative faces likely reflects the processing of the eyes. We propose a neural model of face processing in which face- and eye-selective neurons situated in the superior temporal sulcus region of the human brain respond differently to the face configuration and to the eyes depending on the face context. This dynamic response modulation accounts for the N170 variations reported in the literature. The eyes may be central to what makes faces so special.

Figure - Simplified neural model of early face processing. Three sources are simultaneously active around 170 msec poststimulus onset. One source in the superior temporal sulcus (STS) region with a radial orientation generates the ERP N170 component. The combination of tangential sources in the fusiform gyrus (FG) and middle occipital gyrus (MOG) generates the MEG M170. The dynamic response modulation of eye- and face-selective neurons within the STS accounts for inversion and CR effects on the face N170 amplitude and for the other existing ERP data on the N170. The + signs represent the amount of activation of the neurons. The absence of + signs signifies that the neurons are not responding.

Modulating emotional appraisal by false physiological feedback.

Grey et al. examine how emotional appraisal is influenced by physiological feedback. Their observations make me wonder whether trying the opposite trick, giving false feedback that suggests less autonomic arousal, could chill out reactions to an emotional stimulus... Their main points:

James and Lange proposed that emotions are the perception of physiological reactions. Two-level theories of emotion extend this model to suggest that cognitive interpretations of physiological changes shape self-reported emotions. Correspondingly false physiological feedback of evoked or tonic bodily responses can alter emotional attributions. Moreover, anxiety states are proposed to arise from detection of mismatch between actual and anticipated states of physiological arousal. However, the neural underpinnings of these phenomena previously have not been examined.

We undertook a functional brain imaging (fMRI) experiment to investigate how both primary and second-order levels of physiological (viscerosensory) representation impact on the processing of external emotional cues. Twelve participants were scanned while judging face stimuli during both exercise and non-exercise conditions in the context of true and false auditory feedback of tonic heart rate. We observed that the perceived emotional intensity/salience of neutral faces was enhanced by false feedback of increased heart rate. Regional changes in neural activity corresponding to this behavioural interaction were observed within included right anterior insula, bilateral mid insula, and amygdala. In addition, right anterior insula activity was enhanced during by asynchronous relative to synchronous cardiac feedback even with no change in perceived or actual heart rate suggesting this region serves as a comparator to detect physiological mismatches. Finally, BOLD activity within right anterior insula and amygdala predicted the corresponding changes in perceived intensity ratings at both a group and an individual level.

Our findings identify the neural substrates supporting behavioural effects of false physiological feedback, and highlight mechanisms that underlie subjective anxiety states, including the importance of the right anterior insula in guiding second-order “cognitive” representations of bodily arousal state.

Where the brain understands animate agents..

Wheatley et al offer an interesting study in a recent issue of Psychological Science (vol 18, pg 469, 2007, PDF here). Here is the abstract and two figures:

How people understand the actions of animate agents has been vigorously debated. This debate has centered on two hypotheses focused on anatomically distinct neural substrates: The mirror-system hypothesis proposes that the understanding of others is achieved via action simulation, and the social-network hypothesis proposes that such understanding is achieved via the integration of critical biological properties (e.g., faces, affect). In this study, we assessed the areas of the brain that were engaged when people interpreted and imagined moving shapes as animate or inanimate. Although observing and imagining the moving shapes engaged the mirror system, only activation of the social network was modulated by animacy.

Lateral and medial views of the social network (top, highlighted in yellow) and mirror system (bottom, highlighted in blue). The social network includes areas associated with biological motion (superior temporal sulcus, labeled "1"), biological form (lateral fusiform gyrus, labeled "6"), mentalizing (medial prefrontal cortex and posterior cingulate, labeled "3" and "4," respectively), and affective processing (insula and amygdala, labeled "2" and "5," respectively). The mirror system consists of the inferior parietal cortex (labeled "7") and the ventral-premotor/inferior-frontal cortex (labeled "8").


Experimental results. The brain slices in (a) depict areas of the social network that were more active when moving shapes were inferred (red) or imagined (orange) as animate than when they were inferred or imagined as inanimate. Yellow areas were more active for both animate inference and imagery ("conjunction"). The graph in (b) displays the average hemodynamic responses within the conjunction areas as a function of animacy (animate, inanimate) and condition (motion, imagery). (Results are not shown for the posterior insula, although this was also a conjunction area.) The illustration in (c) shows areas of the mirror system that were more active when subjects watched and made inferences about the moving shapes (purple) and when they imagined (dark blue) the moving shapes relative to when they viewed the backgrounds alone; light-blue areas were more active during both the motion and imagery conditions ("conjunction") than in the background condition. The graph in (d) shows the average hemodynamic responses of the conjunction mirror areas as a function of animacy and condition. For purposes of illustration, all group data are presented on the N27 (AFNI software) brain. Error bars represent standard errors. STS = superior temporal sulcus; PFC = prefrontal cortex.

Face perception by distributed cortical networks.

Continuing to pass along material from talks given at the recent ASSC meeting, here is the abstract and some figures from an interesting bit of work on face perception (PDF here).

Face perception elicits activation within a distributed cortical network in the human brain. The network includes visual (‘‘core’’) regions, as well as limbic and prefrontal (‘‘extended’’) regions, which process invariant facial features and changeable aspects of faces, respectively. We used functional Magnetic Resonance Imaging and Dynamic Causal Modeling to investigate effective connectivity and functional organization between and within the core and the extended systems. We predicted a ventral rather than dorsal connection between the core and the extended systems during face viewing and tested whether valence and fame would alter functional coupling within the network. We found that the core system is hierarchically organized in a predominantly feedforward fashion, and that the fusiform gyrus (FG) exerts the
dominant influence on the extended system. Moreover, emotional faces increased the coupling between the FG and the amygdala, whereas famous faces increased the coupling between the FG and the orbitofrontal cortex. Our results demonstrate content-specific dynamic alterations in the functional coupling between visuallimbic and visual-prefrontal face-responsive pathways.

Face perception elicits activation within a distributed cortical network. Axial sections, taken from a representative subject, illustrate activation within the core (IOG-inferior occipital gyrus, FG-fusiform gyrus, STS - superior temporal sulcus) and extended (AMG-amygdala, IFG-inferior frontal gyrus, OFC-orbitofrontal cortex) systems. Coordinates are in the Talaraich space. L 5 left, R 5 right.


(click to enlarge) Alterations in effective connectivity within the core and the extended systems induced by all faces, emotional faces, and famous faces. Black connections indicate significant regional effects, red connections indicate significant bilinear effects, and dotted lines indicate non-significant effects.

Role of the amygdala in visual awareness.

There have been several reports that subliminal stimuli (such as flashing a picture of an angry face for 33 msec) can activate the amygdala even though the subject is unaware of the stimulus. Pessoa presented work at the recent ASSC meeting using more rigorous criteria for behavioral performance that suggests, to the contrary, that visibility or attention is required for the expression of the effect of valence on early visual processing (even as early as the 'automatic' parallel processing in V1.) A PDF of a recent Pessoa et al. article is here, and PDF of commentary on this work by Duncan and Barrett here). This work:

...shows that amygdala responses depend on visual awareness. Under conditions in which subjects were not aware of fearful faces flashed for 33 ms, no differential activation was observed in the amygdala. On the other hand, differential activation was observed for 67 ms fearful targets that the subjects could reliably detect. When trials were divided into hits, misses, correct rejects, and false alarms, we show that target visibility is an important factor in determining amygdala responses to fearful faces. Taken together, our results further challenge the view that amygdala responses occur automatically.

Duncan and Barrett, in their commentary, suggest

...that the amygdala is acting to increase neural activity in the fusiform gyrus, thereby increasing the likelihood that visual representations that have affective value reach awareness. The psychological consequence is that a person’s momentary affective state might help to select the contents of conscious experience.

Visual awareness is associated with amygdala activation. In the Pessoa et al. study, participants viewed backwardly masked images of faces that depicted fear, presented for either 33 ms or 67 ms. All participants showed greater amygdala activation when viewing fearful faces that were presented for 67 ms, compared with faces that depicted neutral expressions. (a) Pessoa et al. found an increase in amygdala activation (as well as fusiform gyrus activation, which is not shown in the figure) only among those participants who showed objective awareness of 33 ms presentations of faces that depicted fear. (b) Participants who did not show objective awareness did not have significant increases in amygdala activation. Given the excitatory projections from the amygdala to the ventral visual stream, this finding suggests that the amygdala enhances visual awareness for objectives with affective value.

Genuine vs. Fake smiles, can you tell the difference?

This neat test from the BBC, based on Paul Ekman's work.