Theories separating emotion from cognition are decades, maybe even centuries, old. Classic views of emotion have long proposed that each discrete emotion has dedicated neural circuitry that is activated automatically, without conscious awareness (e.g., Ekman & Cordaro Reference Ekman and Cordaro2011; Izard Reference Izard2007; Panksepp Reference Panksepp2007). More continuous, multicomponent models of emotion that allow for interactions between cognitive and affective systems have received recent attention in the literature (e.g., Coan Reference Coan2010; Cunningham & Zelazo Reference Cunningham, Zelazo, Zelazo, Chandler and Crone2009; Lewis & Douglas Reference Lewis, Douglas, Mascolo and Griffin1998). In his Précis of The Cognitive-Emotional Brain, Pessoa presents a new approach to how cognition and emotion are integrated in the brain that is similar to these newer multicomponent models. His dual competition model outlines a framework for such interactions at the perceptual levels; here, I will discuss the specific aspects of his proposal that address how perception is directly influenced by information with affective or motivational content and how behavioral data might speak to his new model.

According to what Pessoa calls the “standard hypothesis,” the processing of emotionally valenced stimuli occurs rapidly, automatically, and nonconsciously, independent of attention and awareness. In terms of the brain, the processing of these stimuli takes the “low-road,” or a subcortical route. He presents an alternative to the standard hypothesis – the multiple waves model – suggesting that emotional stimuli engage multiple regions of the brain, activating both cortical and noncortical channels. Thus, the processing of emotionally valenced stimuli cannot necessarily be accounted for by one specific mechanism, and there are multiple pathways for the perception of these stimuli.

Pessoa thoroughly evaluates neuroscience research that supports both the standard hypothesis and his new model, but given that the focus of The Cognitive-Emotional Brain (Pessoa Reference Pessoa2013) is indeed on the brain, there is very little discussion of how behavioral work can also speak to these perspectives. There is in fact a large body of work on visual attention to emotional stimuli that researchers use to debate the standard hypothesis versus alternative accounts. Countless studies have reported that both adults and more recently, preschool children, detect negative or threat-relevant stimuli, such as snakes and spiders, more quickly than a variety of neutral stimuli, such as flowers, mushrooms, frogs, and cockroaches (Flykt Reference Flykt2005; Reference Flykt2006; Hayakawa et al. Reference Hayakawa, Kawai and Masataka2011; Lipp Reference Lipp2006; Lipp & Derakshan Reference Lipp and Derakshan2005; Lipp et al. Reference Lipp, Derakshan, Waters and Logies2004; Lipp & Waters Reference Lipp and Waters2007; LoBue Reference LoBue2010; LoBue & DeLoache Reference LoBue and DeLoache2008; Reference LoBue and DeLoache2011; Masataka & Shibasaki Reference Masataka and Shibasaki2012; Öhman et al. Reference Öhman, Flykt and Esteves2001a; Purkis & Lipp Reference Purkis and Lipp2007; Soares et al. Reference Soares, Esteves, Lundqvist and Öhman2012; Tipples et al. Reference Tipples, Young, Quinlan, Broks and Ellis2002b. They also detect threatening or angry faces more quickly than happy, neutral, or even sad faces (Calvo et al. Reference Calvo, Avero and Lundqvist2006; Eastwood et al. Reference Eastwood, Smilek and Merikle2001; Esteves Reference Esteves1999; Fox et al. Reference Fox, Lester, Russo, Bowles, Pichler and Dutton2000; Hansen & Hansen Reference Hansen and Hansen1988; LoBue Reference LoBue2009; Lundqvist & Öhman Reference Lundqvist and Öhman2005; Öhman et al. Reference Öhman, Lundqvist and Esteves2001b; Schubo et al. Reference Schubo, Gendolla, Meinecke and Abele2006; Tipples et al. Reference Tipples, Atkinson and Young2002a; Williams et al. Reference Williams, Moss, Bradshaw and Mattingly2005). Similar findings have been reported with human infants (LoBue & DeLoache Reference LoBue and DeLoache2010; Rakison & Derringer Reference Rakison and Derringer2008) and nonhuman primates (Shibasaki & Kawai Reference Shibasaki and Kawai2009), providing compelling evidence that humans have a perceptual bias for the rapid detection of emotional (and specifically negative or threat-relevant) stimuli.

Consistent with the standard hypothesis, many researchers have explained perceptual biases for threat via automatic, pre-attentive, or nonconscious processes, as opposed to controlled, conscious, or cognitively mediated processes. Evidence for the automaticity account comes from data suggesting that the detection of threat-relevant targets (snakes, spiders, angry faces) does not vary based on the number of distracters present in an array. In other words, whereas the detection of nonthreatening stimuli slows when the number of distracters increases from four to nine, detection of threat-relevant stimuli remains equally efficient regardless of the number of distracters present in a matrix (e.g., Eastwood & Smilek Reference Eastwood and Smilek2005; Fox et al. Reference Fox, Lester, Russo, Bowles, Pichler and Dutton2000; Öhman et al. Reference Öhman, Flykt and Esteves2001a). This suggests that individuals use parallel, or automatic search mechanisms to detect threatening stimuli, and that they use serial, or conscious search strategies to detect nonthreatening stimuli.

However, despite several studies demonstrating evidence for automatic detection of threat, others present evidence against automatic search, either by failing to demonstrate set size effects for threat-relevant stimuli or by reporting detection latencies that are too slow to represent automatic search (for a review, see Becker et al. Reference Becker, Anderson, Mortensen, Neufeld and Neel2011a; Horstmann & Bauland Reference Horstmann and Bauland2006). Other studies demonstrate that the advantage for threat-relevant stimuli may have nothing to do with emotional valence at all and is, instead, driven by low-level features of the targets. Indeed, specific geometric shapes, such as the “V” shaped brow characteristic of angry faces or simple curvilinear figures common to snakes are sufficient in eliciting rapid detection (Larson et al. Reference Larson, Aronoff and Stearns2007; LoBue & DeLoache Reference LoBue and DeLoache2011; LoBue & Larson Reference LoBue and Larson2010. Further, presenting participants with specific features of angry faces in non-face-like configurations maintains the advantage (Coelho et al. Reference Coelho, Cloete and Wallis2011; Horstmann et al. Reference Horstmann, Borgstedt and Heumann2006), and removing or manipulating these important features eliminates it (Becker et al. Reference Becker, Horstmann and Remington2011b).

While the controversy rages on about whether automatic versus controlled search mechanisms drive the rapid perception of emotional stimuli, most researchers acknowledge that both automatic and controlled processes likely play a role in threat detection (e.g, Frischen et al. Reference Frischen, Eastwood and Smilek2008; Wolfe Reference Wolfe1998). Further, research on visual attention to emotional stimuli is usually designed to test the standard hypothesis and does not allow for the study of multiple interacting pathways for rapid detection. This leaves us with the same old dichotomy that Pessoa's theory is aimed at revising – subcortical versus cortical routes, parallel versus serial search, nonconscious versus conscious processing – instead of leaving room for a continuous, more integrated explanation.

Very recent behavioral work that explicitly examines multiple pathways for the rapid detection of emotional stimuli indeed suggests that there is no single factor that effectively drives the phenomenon. In one recent study, for example, researchers attempted to examine the unique and potentially interacting roles of low-level perceptual cues, cognitive factors, and emotional state on rapid visual detection of threat. Across studies, adult participants were asked to detect low-level perceptual features of a commonly studied threat-relevant stimulus – snakes. They were asked to detect simple curvilinear (snake-like) versus equally simple rectilinear shapes in a visual search task in the absence of any threat-relevant cues. In Experiment 2, the same procedure was used, except that threat-relevant or non-threat-relevant labels – calling the simple shapes “snakes” or “caterpillars” – were applied to the curvilinear and rectilinear stimuli in order to examine the added role of cognition (or knowing the identity of a stimulus) in detection. Finally, in Experiment 3, a fearful or neutral emotional induction was administered to participants before they completed the visual detection task with curvilinear and rectilinear targets to examine the role that emotional state might play in rapid detection.

The results were compelling, implicating all three factors. Across all three studies, adults detected simple curvilinear shapes more quickly than simple rectilinear shapes in the absence of any threat-relevant cues, suggesting a perceptual bias for curvilinarity. Further, threat-relevant labels and a fearful emotional induction facilitated detection even further, potentially playing an additive role in rapid detection (LoBue Reference LoBue2014). This study – specifically designed to examine a more continuous hypothesis about the roles of perception, cognition, and emotion on rapid detection – suggests that multiple factors can lead to a bias for emotionally valenced stimuli.

Another recent study using eye-tracking technology further supports this perspective, demonstrating that the advantage for threat-relevant stimuli in visual search tasks cannot be accounted for by either bottom-up or top-down processing biases alone. In the study, researchers replicated a classic threat-detection paradigm with an eye-tracker. Adults were presented with 2 × 2 and 3 × 3 matrices of images and were told to press one button if all of the images were from a single category, and a second button if there was a discrepant image (target) in each matrix. The targets were threat-relevant (snakes and spiders) or non-threat-relevant (flowers and mushrooms) – the same photographs and procedure used in a classic, widely cited study by Öhman et al. (Reference Öhman, Flykt and Esteves2001a). The results replicated previous work, demonstrating that adults detected discrepant snakes and spiders more quickly than discrepant flowers and mushrooms. Most importantly, the fixation data further suggested that a single mechanism was not solely responsible for the results.

There was indeed an advantage for snakes and spiders in perception; participants were faster to first fixate threat-relevant versus non-threat-relevant targets, suggesting (consistent with previous literature) that bottom-up processes lead to an advantage for the threat-relevant stimuli. However, there was also an advantage for snakes and spiders in behavioral responding – participants were faster to decide that discrepant threat-relevant stimuli were present after first fixating them, demonstrating that there is also a top-down advantage for threatening stimuli in detection tasks. Together, this work suggests that a bias for threat-relevant stimuli is driven by an advantage in both bottom-up and top-down processing (LoBue et al. Reference LoBue, Matthews, Harvey and Stark2014).

Together, this behavioral work adds to the body of literature reviewed by Pessoa, suggesting that the processing of emotional stimuli cannot necessarily be accounted for by one specific mechanism and that there are multiple pathways for the perception of emotionally valenced stimuli. As he puts it, “the fate of a biologically relevant stimulus should not be understood in terms of a ‘low road’ versus a ‘high road,’ but in terms of the ‘multiple roads’ that lead to the expression of observed behaviors” (Pessoa Reference Pessoa2013, p. 79). Although some of the newer behavioral work reviewed here supports a more continuous model of emotional perception, most behavioral work to date has sought to support or refute the standard hypothesis and does not necessarily allow for multiple interacting factors in their experimental designs. Ultimately, the consideration of newer, more continuous models of emotional perception might take us further in understanding the development of emotional behavior than traditional views that promote a fundamental separation between affect and cognition.