Edited by: Florin Dolcos, University of Illinois at Urbana-Champaign, USA
Reviewed by: Jan Van den Stock, KU Leuven, Belgium; Cosimo Urgesi, University of Udine, Italy; Florin Dolcos, University of Illinois at Urbana-Champaign, USA
*Correspondence: Beatrice de Gelder, Cognitive and Affective Neuroscience Laboratory, Tilburg University, Room P 511, Postbus 90153, 5000 LE Tilburg, Netherlands. e-mail:
This is an open-access article distributed under the terms of the
The amygdala (AMG) has long been viewed as the gateway to sensory processing of emotions and is also known to play an important role at the interface between cognition and emotion. However, the debate continues on whether AMG activation is independent of attentional demands. Recently, researchers started exploring AMG functions using dynamic stimuli rather than the traditional pictures of facial expressions. Our present goal is to review some recent studies using dynamic stimuli to investigate AMG activation and discuss the impact of different viewing conditions, including oddball detection, explicit or implicit recognition, variable cognitive task load, and non-conscious perception. In the second part, we sketch a dynamic dual route perspective of affective perception and discuss the implications for AMG activity. We sketch a dynamic dual route perspective of affective perception. We argue that this allows for multiple AMG involvement in separate networks and at different times in the processing streams. Attention has a different impact on these separate but interacting networks. Route I is engaged in early emotion processing, is partly supported by AMG activity, and is possibly independent of attention, whereas activity related to late emotion processing is influenced by attention. Route II is a cortical-based network that underlies body recognition and action representation. The end result of route I and II is reflexive and voluntary behavior, respectively. We conclude that using dynamic emotion stimuli and a dynamic dual route model of affective perception can provide new insights into the varieties of AMG activation.
The role of the amygdala (AMG) in processing behaviorally salient stimuli is widely documented in many animal and human studies. A variety of affective functions have been attributed to AMG activity including immediate perception of affective stimuli, learning, and conditioning as well as emotional memory (Phelps and LeDoux,
Since the beginning of functional magnetic resonance imaging (fMRI) studies in humans, the AMG has also been the centerpiece of many reports in neurotypical controls (e.g., Morris et al.,
A striking finding is that the AMG exerts some of its functions of paradigmatic cognitive processes such as attention or perception either when the observer is fully aware of the nature and content of the stimulus or, alternatively, in implicit settings. This happens, for example, in settings in which visual awareness is lacking (Whalen et al.,
The overwhelming majority of human fMRI studies that report AMG activation have used pictures of facial expressions. As a consequence, the findings obtained with facial expressions have dominated our view of AMG functions in this past decade. But this relatively limited basis is likely to confine our understanding of the role of the human AMG. New perspectives on human emotional behavior and new technologies have now made possible to present much more realistic and rich pictures to participants in fMRI experiments (e.g., Grosbras et al.,
The theoretical vantage point from which this review proceeds has been formulated by a few authors over the last decades in both animal and human emotion research and has been discussed in different contexts, mostly related to face processing. This theoretical perspective is variedly referred to as a dual route model of affective stimulus perception (LeDoux,
We believe it makes a difference for the understanding of the relation between attention, consciousness, and the AMG whether one adopts a linear or a parallel dual route model of face or body processing. In research from our own lab we have provided evidence for this dynamic dual route perspective while at the same time including in it the notion that both routes are operational in parallel (e.g., de Gelder et al.,
In this brief review we discuss the state of the art concerning the role of the AMG in experiments that instead of using short presentations of static stimuli have presented participants with full naturalistic videos. Using this kind of stimuli can provide us with a more detailed view of the human AMG functions. In the first part we review studies from our lab using dynamic bodily expressions to investigate AMG activation under oddball detection, with either explicit or implicit recognition demands, with variable cognitive task load, and, finally, under conditions of non-conscious perception (see Table
Grèzes et al., |
Oddball detection | Person opening a door in a fearful or neutral manner and scrambles |
Whole brain analysis | Right: 27/–3/–20 | Bodies > scrambles |
Grèzes et al., |
Oddball detection | Person opening a door in a fearful or neutral manner |
Whole brain analysis | Right: –35/0/–14 | –No AMG activation for fearful > neutral in ASD group |
–Weaker connections between the AMG and STS, IFG, and PM in the ASD group. | |||||
Kret et al., |
Oddball detection | Angry, fearful, or neutral facial and bodily expressions | Functional localizer |
Right: 17/–6/–10 | Faces > bodies |
Left: –17/–8/20 | |||||
Kret et al., |
Oddball detection | Angry, fearful, or neutral facial and bodily expressions | Functional localizer |
Right: 17/–6/–10 | Male participants > female participants for faces > bodies contrast |
Left: –17/–8/20 | |||||
Kret et al., |
Oddball detection | Angry, fearful, or neutral facial and bodily expressions | Functional localizer |
Right: 21/–10/–6 | Negative correlation between negative affectivity and threatening faces and bodies > neutral faces and bodies contrast |
Pichon et al., |
Oddball detection | Person opening a door in an angry or neutral manner and scrambles |
Whole brain analysis and sphere | Body > scrambles | –Bodies > scrambles |
Right: 19/–4/–8 | –Anger > neutral | ||||
Left: –33/–1/–17 | |||||
Anger > neutral | |||||
Right: 27/–3/–18 | |||||
Pichon et al., |
Emotion-naming | Person opening a door in an angry, fearful, or neutral manner | Whole brain analysis | Left: –18/–8/10 | –Threatening > neutral |
–Positive correlation between fear recognition and fear > neutral contrast | |||||
Pichon et al., |
Emotion-naming and color-naming | Person opening a door in an angry, fearful, or neutral manner | Whole brain analysis | Right: 29/–7/–17 | –Threatening > neutral in emotion-naming |
Left: –33/–5/–15 | –Deactivation in the color-naming task | ||||
Pouga et al., |
Oddball detection | Person opening a door in a fearful or neutral manner |
Whole brain analysis | Right: 17/–8/–17 | –Fear > neutral |
Left: –28/–3/–19 | –Negative correlation between difficulty identifying emotions and fear > neutral contrast | ||||
Sinke et al., |
Emotion-naming and color-naming | Teasing or threatening social interaction and scrambles | Anatomically defined for individual subjects | Right AMG: 18 ± 2.4/–5 ± 3.6/–16 ± 1.7 | –Deactivation in both the emotion-naming and color-naming task |
–Less deactivation for threatening social interactions regardless of task condition | |||||
Sinke et al., |
Easy or hard color-naming with focus on aggressor or passive victim | Threatening social interaction between an aggressor and passive victim | Group mask | Left AMG: –19/–7/–13 | –Deactivation in both the easy and hard color-naming task |
–Less deactivation when focus on aggressor, especially in easy color-naming task | |||||
Van den Stock et al., |
Oddball detection | Person opening a door in an angry or neutral manner | Anatomically defined | Right: 19/–2/–5 | –Anger > neutral only for non-conscious perception |
Left: 22/–7/–6 |
The review will highlight the complex way in which emotional stimuli are processed in the brain and the interplay between emotion and cognition. Specifically, we will focus on the interaction between emotion and attention, as the latter can be considered a typical cognitive function. In fact, a central role of attention is to modulate sensory processing, for example, by increasing the firing rate in primary sensory areas or by enhancing behavioral performance. In recent years, such functions have also been reported during the processing of emotional stimuli and have been related to the activity of the AMG. Thus, converging evidence is pointing to the AMG as a central hub in the dynamic interplay between emotion and cognition and makes the study of the functional and anatomical properties of this structure a paradigmatic case for the study of emotion–cognition interaction.
Experiments using oddball detection provide valuable insight when affective processing for new classes of stimuli are investigated and they have the extra advantage of allowing a closer comparison with animal data that rarely use complex evaluative tasks. Our first study with video clips used a passive viewing paradigm requiring participants simply to detect the oddball stimuli presented upside-down (Grèzes et al.,
Pichon et al. (
Another paper by Kret et al. (
Personality factors or psychiatric disorders may also influence AMG activity. Kret et al. (
To further investigate AMG activation under different task conditions, Pichon et al. (
The results obtained in the comparison between emotion-naming (explicit) and color-naming (implicit) conditions allow us to enter the debate on the role of attention in AMG activation. In the literature there is a longstanding debate if implicit or pre-attentive processing of emotional stimuli triggers AMG activation. Two contradictory lines of research are described (for a review see Pessoa,
Using dynamic stimuli we can provide additional information in the debate on automaticity of the AMG response to threatening social information. In contrast to the observation of AMG activation to both angry and fearful social actions in the explicit recognition task (Pichon et al.,
These results show a complex pattern. The disengagement of the AMG (as suggested by deactivation) under implicit conditions (Sinke et al.,
The interaction between emotion and attention and the role of the AMG in this interaction is far from settled, as documented by the fMRI findings reported above. Moreover, the interpretation of these findings is complicated by several factors. First, fMRI measures emotion processing across a relatively long time-window. So, it is possible that initial encoding of emotions in the AMG is relatively independent from attention, but that top-down attention modulation is involved at later stages. A critical point for future research is therefore to “isolate” AMG activity in the earliest processing stages, which are more likely to occur in an automatic, pre-attentive, rather than controlled, resource-dependent fashion (Garrido et al.,
The studies we commented upon so far all compared two different tasks with different cognitive/attentional load to assess their influence on AMG activity. Yet this does not allow an assessment of task load
The goal of the next study (Sinke et al.,
Recently, Shafer and colleagues provided for the first time evidence that supported both the view of Pessoa (
An important source of evidence concerning the role of the AMG in emotion processing comes from studies on patients with cortical blindness following destruction of the visual cortex. In fact, the lesion renders the patients clinically blind for the stimuli presented in the affected portion of the visual field (scotoma) and produces a pathological segregation between the major cortical route to the AMG, which is damaged, and the intact subcortical visual pathway, providing a unique experimental opportunity (Weiskrantz,
A recent behavioral/fMRI study in a patient (GY) with unilateral cortical blindness provides additional information on the effect of visual awareness on AMG activation (Van den Stock et al.,
Three findings are of relevance for the current review and the proposed dual route perspective of affective perception. First, cortical activation to non-conscious perception was restricted to the right FG, motor and somatosensory regions. Second, subcortical network activity was not found in the intact hemisphere associated with conscious perception of emotional actions. Third, cortical activation for conscious perception was observed in the prefrontal cortex (PFC), STS, precuneus and intraparietal sulcus (IPS). The results suggest that two separate neural systems underlie conscious and non-conscious perception. On the one hand, a geniculo-striate system underlies conscious perception and is mostly cortical based, while on the other hand, non-conscious perception seems based on the extrageniculo-striate and subcortical pathway including the AMG. However, several questions remain. Do these neural systems interact during the processing of emotional stimuli and what is the role of the AMG in both pathways?
In this final part we aim to recast some of the inconsistencies concerning the role of the AMG in relation to emotion and attention within the vantage point of a dynamic dual route perspective. Ultimately, a better understanding of the respective role of the different AMG subnuclei is needed.
Traditional face processing models view perception as starting with face categorization. Once this is successfully completed, it is followed by one or more successive stages of decoding the various face attributes like identity, emotion, gender, etc. In the framework of currently known brain areas that play a role in face processing this translates as initial categorization in occipitotemporal cortex (OFA) and STS, followed by fusiform face area (FFA), then extraction of the emotional valence following connections between FFA and AMG. Alternatively, we suggested that there may be separate processing routes already in the early stages, and this view is gaining momentum from new findings (e.g., de Gelder et al.,
In the area of body research a very similar picture dominates and perception is also viewed as following the ventral pathway. Researchers interested in neural representations of bodies and body parts have discovered two brain areas central to neurofunctional body representation, initially the extrastriate body area (EBA) and later the fusiform body area (FBA; Urgesi et al.,
Variants of these roles are that EBA and OFA, respectively, code the stimulus part while only at the stage of FBA and FFA the whole stimulus is encoded (for a critique of this view see de Gelder et al.,
Indeed, Vuilleumier (
Route II lies parallel to route I and plays a role in body recognition (EBA, FBA, STS), action recognition (e.g., the fronto-parietal system), and attention. It is suggested that attention by means of activity of the fronto-parietal attentional network and the basal forebrain has a bidirectional relation with this route. The end result of route II is voluntary action (fronto-motor regions), although a shortcut exists in route I to trigger more reflexive action.
The findings that feed this debate on the relationship between AMG activity and attention may be best addressed in the context of a dynamic dual route model. In fact, while AMG is part of both routes, only route II appears modulated by attention and task constraints and has a direct impact on AMG activation.
Current methods in human affective neuroscience appear particularly limited to provide information about time course. Speed of processing is an important aspect of dual route claims. Initial evidence is coming from studies using the high temporal resolution of MEG. For example, activity in the Pulv (10–20 ms) and Amg (20–30 ms) is found for conscious perception of fearful expressions using MEG (Luo et al.,
However, in many fMRI studies subcortical activity during conscious emotion perception is often not observed. One explanation is that cortical feedback during conscious emotion perception might reflect inhibitory modulation over the subcortical SC-Pulv-Amg pathway (Tamietto and de Gelder,
But independently of these methodological limitations and initial findings it is important to avoid theoretical misconception about the timing issue. It is in evolutionary terms more important which neural pathway supports quicker behavioral output (i.e., access to visuomotor integration and action) and not which brain area starts firing first in response to visual stimulation. Thus assuming a direct linear relationship between the latency of a neural response and the latency of a behavioral response is misleading. For example, speed of spontaneous expressive actions is faster for non-conscious emotion perception (Tamietto et al.,
In this review we considered the AMG as one homogenous structure, but this is certainly not the case. While an extensive discussion of the AMG subnuclei and the possible role of these structures are beyond the scope of this review, we will highlight several relevant aspects of the AMG anatomy and discuss these in terms of future research.
A widely accepted division of the human AMG is in terms of 3 main subnuclei, namely the basolateral (BLA), central-medial amygdala (CMA), and superficial amygdala (SFA; Heimer et al.,
We have reviewed studies using dynamic bodily expressions and a variety of experimental setups to investigate the role of the AMG in emotion processing and the influence of attention on AMG activation. Taken together, we argue that in the dual route model of affective perception AMG activation can be observed in separate networks and at different time points. Both early and late emotion processing is partly supported by the AMG; however, only late AMG activation is influenced by attention.
With sophisticated paradigms and a wide variety of different stimuli (static or dynamic, emotional or non-emotional, facial or bodily expressions or social interactions) and the ever-expanding neuroscience toolbox one can only hope that after decades of research the question what AMG activity indicates will finally be answered.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
This work was supported by the project TANGO. The project TANGO acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under FET-Open grant number: 249858.
The Supplementary Material for this article can be found online at