G Model ARTICLE IN PRESS BIOPSY-7253; No of Pages 13 Biological Psychology xxx (2016) xxx–xxx Contents lists available at ScienceDirect Biological Psychology journal homepage: www.elsevier.com/locate/biopsycho Top-down and bottom-up factors in threat-related perception and attention in anxiety Tamara J Sussman, Jingwen Jin, Aprajita Mohanty ∗ Department of Psychology, Stony Brook University, United States a r t i c l e i n f o Article history: Received 14 September 2015 Received in revised form 10 August 2016 Accepted 17 August 2016 Available online xxx Keywords: Top-down Endogenous Threat perception Prestimulus processes Attention Amygdala Anxiety Sensory cortex Prefrontal cortex Perceptual bias Attentional bias a b s t r a c t Anxiety is characterized by the anticipation of aversive future events The importance of prestimulus anticipatory factors, such as goals and expectations, is well-established in both visual perception and attention Nevertheless, the prioritized perception of threatening stimuli in anxiety has been attributed to the automatic processing of these stimuli and the role of prestimulus factors has been neglected The present review will focus on the role of top-down processes that occur before stimulus onset in the perceptual and attentional prioritization of threatening stimuli in anxiety We will review both the cognitive and neuroscience literature, showing how top-down factors, and interactions between top-down and bottom-up factors may contribute to biased perception of threatening stimuli in normal function and anxiety The shift in focus from stimulus-driven to endogenous factors and interactions between top-down and bottom-up factors in the prioritization of threat-related stimuli represents an important conceptual advance In addition, it may yield important clues into the development and maintenance of anxiety, as well as inform novel treatments for anxiety © 2016 Elsevier B.V All rights reserved Introduction Emotional stimuli require rapid adaptive responses, such as avoidance of threat or approach towards a rewarding stimulus To allow for these swift behavioural responses, our perceptual and attentional system prioritizes emotional stimuli over stimuli that are relatively unemotional in nature Spiders, snakes and angry faces are hypothesized to belong to a special class of stimuli that are perceptually prioritized due to their importance for survival (Brosch, Pourtois, & Sander, 2010; New, Cosmides, & Tooby, 2007; Seligman, 1971) Empirical research supporting this view shows that spiders and snakes are detected more rapidly than mushrooms and flowers (Ohman, Flykt, & Esteves, 2001) and angry faces are detected faster than neutral faces (Hansen & Hansen, 1988; Horstmann, 2007) Saccadic eye movements orient more quickly to images of threatening compared to neutral faces and body postures (Bannerman, Milders, de Gelder, & Sahraie, 2009) Threatening ∗ Corresponding author at: Department of Psychology, Stony Brook University, Stony Brook, NY 11794, United States E-mail address: aprajita.mohanty@stonybrook.edu (A Mohanty) stimuli shown rapidly in a stream of images are identified more accurately than neutral stimuli (Anderson, 2005) While positive stimuli may also be associated with similar perceptual benefits, the effects tend to be smaller than those elicited by threatening stimuli (Carretie, Mercado, Tapia, & Hinojosa, 2001; Dijksterhuis & Aarts, 2003; Smith, Cacioppo, Larsen, & Chartrand, 2003; Stefanics, Csukly, Komlosi, Czobor, & Czigler, 2012; Sussman, Weinberg, Szekely, Hajcak, & Mohanty, 2016) The facilitated perception of threatening stimuli has been attributed to bottom-up processing driven by the physical characteristics or evolutionary significance of these stimuli (Bannerman et al., 2009; Ohman et al., 2001) In line with this view, research in affective neuroscience has centered on examining the neural pathways that promote ‘automatic’ perception of emotional stimuli (Fox, 2002; Mendez-Bertolo et al., 2016; Vuilleumier & Pourtois, 2007) It is hypothesized that threatening stimuli are prioritized due to a processing bias (Bar-Haim, Lamy, Pergamin, BakermansKranenburg, & van, 2007; Cisler, Bacon, & Williams, 2009) This processing bias is not measured directly, and instead is inferred from accuracy and reaction time differences between the detection of threatening compared to neutral stimuli Depending on the design of the task, the threat bias is hypothesized to facilitate detec- http://dx.doi.org/10.1016/j.biopsycho.2016.08.006 0301-0511/© 2016 Elsevier B.V All rights reserved Please cite this article in press as: Sussman, T J., et al Top-down and bottom-up factors in threat-related perception and attention in anxiety Biol Psychol (2016), http://dx.doi.org/10.1016/j.biopsycho.2016.08.006 G Model BIOPSY-7253; No of Pages 13 ARTICLE IN PRESS T.J Sussman et al / Biological Psychology xxx (2016) xxx–xxx tion of threatening stimuli in visual search and dot-probe-like tasks or impede performance when threatening stimuli distract from the task at hand (Mathews & MacLeod, 1994; Ohman et al., 2001) Here, we explore the possibility that in addition to processing biases that occur coincident with stimulus presentation, prioritized perception of threatening stimuli in normal function and anxiety may be attributed to prestimulus biases The idea that prestimulus biases impact threat-perception is consistent with research indicating that the process of perception starts prior to an encounter with a stimulus, and with research demonstrating that perception is guided by top-down factors such as goals and expectations (Bacon & Egeth, 1994; Itti & Koch, 2001) For example, both implicit and explicit prestimulus cues improve target perception (Chen & Zelinsky, 2006; Wolfe, Butcher, Lee, & Hyle, 2003) Similarly, in day-to-day life, we often use both implicit and explicit emotional information to guide our perception, for example, while scanning for spiders in an uninhabited room filled with cobwebs These anticipatory search behaviors, aimed at rapidly detecting sources of potential reward or threat, are deployed in a wide range of situations from driving on a highway to navigating social gatherings Prestimulus biases may be of particular importance in anxiety, as dispositional anxiety is associated with overestimation of the likelihood and cost of future negative events (Aue & Okon-Singer, 2015; Grupe & Nitschke, 2013) The importance of top-down processes in anxiety has also been demonstrated by studies showing that threat-related cues impact subsequent perception differently depending on type of anxiety (Sussman, Szekely et al., 2016) In the present review we first discuss the current affective neuroscience literature on exogenous, ‘bottom-up’ factors in understanding perceptual and attentional biases towards threatening stimuli, both in normal function and in anxiety While research has examined the role of top-down factors that are non-emotional in nature (for e.g., searching for matching Gabor patches) and their interaction with bottom-up processing of emotional stimuli (for e.g., task-irrelevant emotional faces in the background), very few studies have examined top-down factors that are themselves emotional in nature (e.g., cues indicating an upcoming threatening face) and their effect on perception Hence, we discuss conceptual and methodological issues in the research literature that arise from an exclusive focus on bottom-up factors in understanding prioritized perception of threatening stimuli We then discuss the importance of endogenous, emotion-related ‘top-down’ factors, such as expectations and prior knowledge regarding threat, in guiding basic human perception We also discuss emerging evidence that underscores the importance of endogenous processing in the perceptual prioritization of threatening stimuli both in normal function and in anxiety Finally, we highlight the importance of shifting the emphasis from stimulus-driven to top-down mechanisms as well as their interaction with bottom-up mechanisms in the study of the perceptual prioritization of threatening stimuli both in normal function and in anxiety (Mohanty & Sussman, 2013) Bottom-up processes influencing the perception of emotional stimuli The human visual system is constantly bombarded with information The limited capacity of this system makes it impossible to process all incoming information (Tsotsos, 1990) As a result, stimuli entering the visual field compete for neural representation (Desimone & Duncan, 1995; Tsotsos, 1997) To deal with this overwhelming excess of information, the visual system biases the competition between stimuli towards preferential representation of the most relevant stimuli (Desimone & Duncan, 1995) This biasing process is a function of two mechanisms: a bottom-up, sensory driven mechanism that selects stimuli based on their physical salience, and a top-down mechanism with variable selection criteria, which selects stimuli based on expectations, knowledge and goals Unlike top-down mechanisms, bottom-up mechanisms are thought to operate by automatically shifting resources to salient visual stimuli For example, stimuli that create a local discontinuity in the visual environment, such as abrupt occurrence of a new object (Jonides & Yantis, 1998), sudden motion and looming (Abrams & Christ, 2003; Franconeri & Simons, 2003), and luminance contrast changes (Enns, Austen, Di Lollo, Rauschenberger, & Yantis, 2001) are given more priority Similarly, emotional stimuli are considered another class of stimuli that are hypothesized to be processed in a bottom-up manner For example, in visual search arrays, snakes and spiders are detected faster than flowers and mushrooms (Ohman et al., 2001); and angry faces are detected faster and more efficiently than neutral and happy faces (Eastwood, Smilek, & Merikle, 2001; Tipples, Atkinson, & Young, 2002) Threatening faces are also processed earlier and receive more perceptual elaboration compared to other facial expressions (Schupp et al., 2004) Furthermore, saccadic reaction times are faster towards an emotional compared to neutral faces and body postures (Bannerman et al., 2009), as well as towards emotional compared to neutral scenes (Nummenmaa, Hyona, & Calvo, 2009) Similarly, negative words are detected more accurately (Dijksterhuis & Aarts, 2003; Nasrallah, Carmel, & Lavie, 2009) and more quickly (Dijksterhuis & Aarts, 2003) than positive words Attentional probes appearing in the same location as threatening faces are detected faster than probes appearing in the opposite location (Armony & Dolan, 2002; Mogg & Bradley, 1999; Pourtois, Grandjean, Sander, & Vuilleumier, 2004) It is hypothesized that emotional stimuli are prioritized due to their salience, as proposed by appraisal, constructivist and, dimensional theories of emotion (Barrett, 2006; Brosch et al., 2010; Ellsworth & Scherer, 2003; Russell, 2003), or their physical characteristics, as demonstrated by perceptual prioritization of shapes associated with threats (Larson, Aronoff, Sarinopoulos, & Zhu, 2009; Larson, Aronoff, & Stearns, 2007) For example, in one study, participants were asked to detect and rate the valence of a discrepant threatening, happy or neutral schematic face in arrays of otherwise identical faces (Lundqvist & Ohman, 2005) The schematic faces were manipulated such that three, two or one feature(s) of the schematic face conveyed emotion Results showed better visual search performance for more negatively rated faces, even if only one feature conveyed emotion, indicating that the threatening meaning of the face drives improved detection (Lundqvist & Ohman, 2005) On the other hand, researchers have hypothesized that the search advantage of threatening compared to neutral faces may be due to features such as upturned lip corners, open eyes, or frowning that can be discriminated from neutral features (Calvo & Nummenmaa, 2008; Larson et al., 2007) This could be because of the salience of the threat-related features, resulting from their association with the holistic facial expression they come from (e.g., Cave & Batty, 2006), or because of physical differences between features of threatening vs neutral faces regardless of emotional meaning Finally, some researchers have hypothesized that it is the configuration of threatening facial features, such as shape and positioning of the mouth relative to nose and eyes that aids visual search (Calder, Young, Keane, & Dean, 2000; Carey & Diamond, 1977), others have concluded that specific features are responsible for improved detection (Calvo & Nummenmaa, 2008), and some studies have presented results supporting both positions (Lundqvist, Esteves, & Ohman, 2004) Please cite this article in press as: Sussman, T J., et al Top-down and bottom-up factors in threat-related perception and attention in anxiety Biol Psychol (2016), http://dx.doi.org/10.1016/j.biopsycho.2016.08.006 G Model BIOPSY-7253; No of Pages 13 ARTICLE IN PRESS T.J Sussman et al / Biological Psychology xxx (2016) xxx–xxx Neural mechanisms involved in bottom-up threat-perception At the neural level, the bottom-up processing of emotional stimuli is believed to be mediated via the amygdala and its interactions with the visual cortices (Cisler & Koster, 2010; Dolan, 2002; Ohman, 2002, 2005) For example, results from studies using backward masking paradigms suggest that fearful faces activate the amygdala in the absence of conscious awareness (Morris, Ohman, & Dolan, 1998; Whalen et al., 1998) Using an event-related fMRI paradigm in which subjects fixated on a central cue and matched either two fearful or neutral faces or two houses presented eccentrically, Vuilleumier and colleagues examined the hypothesis that emotion and voluntary attention reflect distinct influences that not interact (Vuilleumier, Armony, Driver, & Dolan, 2001; Vuilleumier, Richardson, Armony, Driver, & Dolan, 2004) They found that while activity in the fusiform gyrus (FG), which is known to respond strongly to faces, was modulated by voluntary attention, amygdala responses to fearful faces were not (Vuilleumier et al., 2001) Bottom-up appraisal of emotional stimuli is also associated with greater connectivity between the amygdala and limbic regions, such as the anterior cingulate cortex (Comte et al., 2014) The amygdala is thought to quickly detect relevant stimuli, including threatening stimuli (Cunningham & Brosch, 2012; Sander, Grafman, & Zalla, 2003), via a neural pathway, sometimes referred to as the ‘low road,’ that passes through the superior colliculi and the thalamus, that does not require cortical input (LeDoux, 2000), and carries low-spatial frequency information This theory has been supported by evidence demonstrating that low spatial frequency images of fearful faces produce more amygdala activation than fearful images displayed with high spatial frequency (Vuilleumier, Armony, Driver, & Dolan, 2003) and by evidence that emotional faces can be processed in the absence of awareness in a subject with a lesioned striate visual cortex (de Gelder, Vroomen, Pourtois, & Weiskrantz, 1999) Recent evidence using human intracranial electrophysiological data showed fast amygdala responses, beginning as early as 74-ms after the onset of fearful, but not neutral or happy, facial expressions (MendezBertolo et al., 2016) The latency of fear responses in amygdala was much shorter than their latency in the visual cortices and relied on low spatial frequency information However, this theory has been challenged by a competing model, positing that during the processing of emotional visual stimuli, the amygdala’s primary role is to coordinate cortical function and detect salient stimuli (Pessoa & Adolphs, 2010) This model (discussed in greater detail below) has been supported by evidence demonstrating that emotional faces only produce greater amygdala activity when faces are actively attended to (Pessoa, Kastner, & Ungerleider, 2002), and by evidence that rapid fear detection can rely on high spatial frequency information, suggesting involvement of cortical visual areas (Stein, Seymour, Hebart, & Sterzer, 2014) After the amygdala evaluates incoming information as threatening, it can boost processing in other brain regions, such as the sensory cortices, via re-entrant feedback (Vuilleumier, 2005) Hence, exogenously-driven perceptual prioritization of threatrelated information is hypothesized to involve visual processing modulated by re-entrant feedback signals from the amygdala (Anderson & Phelps, 2001; Davidson, 2002; Ohman et al., 2001; Ohman, 2005; Vuilleumier & Pourtois, 2007) Since the amygdala both receives inputs from all sensory modalities and projects to numerous cortical and subcortical areas, it is well positioned to influence a number of processes and behaviors (Fox, Oler, Tromp, Fudge, & Kalin, 2015; Freese & Amaral, 2009; Holland & Gallagher, 1999) Supporting the theory that this rich connectivity is used during threat perception is evidence that lesions in the human amygdala lead to less activation of the FG when viewing fearful faces compared to healthy controls and participants with hippocampal lesions (Vuilleumier et al., 2004) and also lead to less activation in the inferior temporal cortex, a region crucial for visual recognition, in monkeys (Hadj-Bouziane et al., 2012) Furthermore, greater connectivity between the amygdala and sensory regions has been found during threat perception (Lim, Padmala, & Pessoa, 2009; Morris, Friston et al., 1998; Pessoa, Gutierrez, & Ungerleider, 2002) These empirical results support claims of quick and automatic processing of salient stimuli, and provide an amygdala-based mechanism by which threat stimuli could be perceptually prioritized In addition to evidence of an amygdala-driven bottom-up processing of salient stimuli, studies suggest that a ventral network, comprising the temporoparietal junction (TPJ) and the ventral frontal cortex (VFC), helps to reorient attention to salient incoming sensory information outside the current focus of processing (Corbetta & Shulman, 2002) This network is recruited by infrequent or unexpected events that are salient; for e.g., invalidly cued targets in the Posner task or oddballs Studies show that during topdown attentional guidance activity in TPJ is suppressed (Shulman, Astafiev, McAvoy, d’Avossa, & Corbetta, 2007; Shulman et al., 2003; Todd, Fougnie, & Marois, 2005) and in the presence of salient nontargets stimulus activity in TPJ increases (Geng & Mangun, 2011) Hence, the TPJ and VFC function like circuit breakers that shift the focus to salient but task-irrelevant stimuli, even in case of emotional stimuli (Dolcos & McCarthy, 2006) These studies suggest additional bottom-up stimulus-driven mechanisms by which threats could be perceptually prioritized, and demonstrate a possibility of interactions between top-down and bottom-up processes via a brain network that is sensitive to both kinds of processing The influence of anxiety on bottom-up threat-perception While anxiety is typically conceptualized as an anticipatory response to future threatening events, fear is typically thought of as the response to an immediate threat (Davis, Walker, Miles, & Grillon, 2010; Grupe & Nitschke, 2013; LeDoux, 2015) Nevertheless, perceptual processing in anxiety is typically conceptualized as driven by bottom-up processes (Mathews & MacLeod, 1994; Ohman et al., 2001) Empirical studies examining perception of threatening stimuli in anxious individuals, like the studies that examine these phenomena in healthy individuals, tend to utilize tasks that exogenously drive perception and attention through the use of unanticipated or task-irrelevant stimuli Common tasks employed to study this phenomenon present emotional stimuli that ‘pop out’ amongst non-emotional stimuli (Fox et al., 2000; Ohman et al., 2001), are peripheral to fixation (Mogg & Bradley, 1999), appear rapidly in stream of images (Arend & Botella, 2002), or are irrelevant to the task at hand (Williams, Mathews, & MacLeod, 1996) Experimental results suggest that compared to healthy controls, individuals with clinical anxiety (Klumpp & Amir, 2009; Mogg, Millar, & Bradley, 2000; Ohman et al., 2001), dispositional anxiety (Eysenck, Derakshan, Santos, & Calvo, 2007; Mogg & Bradley, 1999; Richards, French, Johnson, Naparstek, & Williams, 1992), and experimentally induced anxiety (Lim & Pessoa, 2008; Robinson, Letkiewicz, Overstreet, Ernst, & Grillon, 2011) detect or orient towards threatening stimuli more quickly Other studies have found no difference in the initial orientation to threat, but have demonstrated that individual differences in anxiety increase dwell time and the time required to disengage from a threatening stimulus (Fox, Russo, Bowles, & Dutton, 2001; Yiend & Mathews, 2001) However, there is some empirical evidence demonstrating that anxiety can both facilitate engagement with threatening stimuli and slow disengagement with threatening stimuli (Koster, Please cite this article in press as: Sussman, T J., et al Top-down and bottom-up factors in threat-related perception and attention in anxiety Biol Psychol (2016), http://dx.doi.org/10.1016/j.biopsycho.2016.08.006 G Model BIOPSY-7253; No of Pages 13 ARTICLE IN PRESS T.J Sussman et al / Biological Psychology xxx (2016) xxx–xxx Verschuere, Crombez, & Van Damme, 2005; Shackman, Maxwell, McMenamin, Greischar, & Davidson, 2011), suggesting that anxiety influences both earlier and later sensory processes involved in threat perception Finally, recent studies of soldiers experiencing acute stressors, such as combat, show that avoidance of threat, rather than a bias towards threats predicts subsequent PTSD symptoms (Wald, Shechner et al., 2011; Wald, et al., 2011) These studies suggest that situationally induced anxiety may influence the relationship between orientation to threat and future anxiety symptoms The well-documented, bidirectional relationship between attentional biases to threat and anxiety (Van Bockstaele et al., 2014) has led to the development of cognitive-bias modification of selective attention (CBM-A), a procedure with demonstrated therapeutic promise, and Attention Bias Modification Treatment (ABMT), a treatment for anxiety Both of these techniques are based on cognitive behavioural models positing that cognitive biases can lead to anxiety disorders, and therefore altering attentional biases could subsequently reduce anxiety symptoms Reviews of both CBM-A and Attention Bias Modification (ABM) have shown these procedures reduce anxiety symptoms and vulnerability to anxiety in adults (MacLeod & Clarke, 2015; MacLeod & Mathews, 2012) and in children (Eldar et al., 2012) Furthermore, meta-analyses of studies examining the impact of CBM and ABMT on anxiety symptoms has demonstrated that these treatments are effective (Hakamata et al., 2010; Hallion & Ruscio, 2011) A meta-analysis of the efficacy of ABMT on clinical anxiety demonstrated that more patients who received this treatment no longer met diagnostic criteria compared to patients in control conditions (Linetzky, Pergamin-Hight, Pine, & Bar-Haim, 2015) Different types of anxiety (e.g dispositional vs situationally induced) can interact, impacting perceptual biases for threatening images For example, anxiety induced by an upcoming examination increased a pre-existing tendency for those higher in dispositional anxiety to respond more rapidly to targets following a threatening stimulus (MacLeod & Mathews, 1988) Similarly, in individuals high in trait-anxiety, a negative mood manipulation led to greater interference from anxiety-related words on an emotional Stroop task (Richards et al., 1992) However, some studies have found a different pattern of interaction For example, while participants high in trait anxiety responded more slowly to threatening words on an emotional Stroop task − indicating that attention had been captured by these threatening distractors − under stress, trait anxiety no longer influenced response times (Mogg, Mathews, Bird, & Macgregor-Morris, 1990) A subsequent study suggests that while transient stressors may wash out differences between high and low anxious individuals, chronic stressors exaggerate the differences in attention attributed to trait anxiety (Mogg, Bradley, & Hallowell, 1994) Therefore, paying attention to the type of stressor at hand could resolve the differences between studies that find that induced anxiety either increases or decreases threat biases Overall, clinical, dispositional and situationally induced anxiety are associated with faster detection of threatening stimuli This perceptual prioritization of threat in anxiety is attributed to attentional capture by the stimulus or automatic processing of threatening stimuli (Ohman et al., 2001; Robinson, Charney, Overstreet, Vytal, & Grillon, 2012; Robinson et al., 2011) Studies that examined brain activity while unanticipated or task-irrelevant stimuli exogenously drive perception and attention demonstrate increased amygdala and visual cortical activity for feared stimuli in anxiety (Lipka, Miltner, & Straube, 2011; Straube, Mentzel, & Miltner, 2005) It is hypothesized that these perceptual enhancements share similarities with exogenous stimulus-driven mechanisms and are mediated via amydalar feedback into visual sensory regions (Pourtois, Schettino, & Vuilleumier, 2013) Other studies have demonstrated that very early sensory processing is boosted in clinically anxious individuals (Knott et al., 1994), and in children higher in dispositional anxiety (Woodward et al., 2001) Threatening stimuli have been shown to activate the amygdala more for anxious than non-anxious subjects, in clinical, dispositional and experimentally induced anxiety (Bishop, Duncan, & Lawrence, 2004; Calder, Ewbank, & Passamonti, 2011; Etkin & Wager, 2007; Etkin et al., 2004; Larson, Ruffalo, Nietert, & Davidson, 2005) However, the amygdala does not work in isolation A recent study demonstrated that under threat of shock, greater functional connectivity between the amygdala and the dorsolateral prefrontal cortex (DLPFC) predicted faster threat detection, and was positively associated with trait anxiety (Robinson et al., 2012) Other studies have found that individuals with anxiety disorders had less functional connectivity between the amygdala and the DLPFC compared to healthy controls while resting or viewing threatening faces (Birn et al., 2014; Prater, Hosanagar, Klumpp, Angstadt, & Phan, 2013) Furthermore, in one study, the connectivity between DLPFC and amygdala correlated negatively with measures of social anxiety (Prater et al., 2013) Together, these studies suggest that different kinds of anxiety influence the relationship between the amygdala and the frontal cortex in distinct ways While the literature describing the impact of anxiety on perception consistently demonstrates a bias for threatening stimuli, precisely when this bias comes into play remains unclear Since one of the core features of anxiety is a tendency to make inaccurate predictions regarding the likelihood and costs of future negative events (Grupe & Nitschke, 2013), the effect of anxiety on threat perception may start before stimulus presentation and may involve top-down factors such as goals, expectations and prior knowledge Therefore, to gain a complete understanding of how anxiety impacts threat detection, it is necessary to examine the impact of top-down processing on threat perception in anxiety Conceptual and methodological issues regarding research on bottom-up factors effecting perception Overall, studies of psychological and neural mechanisms involved in perception of emotional stimuli have reinforced the view that emotional salience-related, bottom-up effects are involuntary and not under the control of attention (Vuilleumier & Driver, 2007) However, this research raises methodological issues First, the majority of studies examining the influence of emotional stimuli on attention have used tasks in which emotional stimuli appear unexpectedly, such as modifications of a peripheral or exogenous cuing task (Armony & Dolan, 2002; Holmes, Green, & Vuilleumier, 2005; Keil, Moratti, Sabatinelli, Bradley, & Lang, 2005; Mogg & Bradley, 1999; Mogg, McNamara et al., 2000; Stormark & Hugdahl, 1996, 1997) The dot probe paradigm is a very commonly used task in which both a threatening and neutral stimulus are presented simultaneously and peripherally, and one of them is followed by an attentional probe (Holmes et al., 2005; Mogg & Bradley, 1999; Mogg, McNamara et al., 2000) A facilitated response to probes that appear at the same location of threat information (valid trial), in comparison with responses to probes at the opposite location of threat information (invalid trial), is interpreted as vigilance for threat Secondly, bottom-up processing of emotional stimuli has been shown to interact with top-down factors such as goals and taskrelevance While bottom-up processing of emotional stimuli is adaptive when they are relevant to our well-being, it is equally adaptive to ignore these stimuli and stay task-focused when they pose no danger Hence, adaptive behavior requires constant interaction between top-down goals and bottom-up processing Studies using paradigms in which emotional stimuli are task-irrelevant Please cite this article in press as: Sussman, T J., et al Top-down and bottom-up factors in threat-related perception and attention in anxiety Biol Psychol (2016), http://dx.doi.org/10.1016/j.biopsycho.2016.08.006 G Model BIOPSY-7253; No of Pages 13 ARTICLE IN PRESS T.J Sussman et al / Biological Psychology xxx (2016) xxx–xxx hypothesize that emotional stimuli distract from the task at hand because they are processed automatically, leading to impaired taskrelevant performance For example, task-irrelevant emotional faces slow reaction times (Vuilleumier et al., 2001) and decrease accuracy (McHugo, Olatunji, & Zald, 2013) The presentation of emotional stimuli exogenously or as distractors in experimental paradigms has contributed to the view that emotional stimuli are processed involuntarily in a bottom-up manner and are immune to the effect attention or cognitive control However, studies also show that strong as it may be, bottom-up processing of an emotional stimulus is also susceptible to top-down control For example, happy and threatening facial expressions have been shown to capture attention when they are the target of search but not when they are in opposition to task goals (Hahn & Gronlund, 2007; Williams, Moss, Bradshaw, & Mattingley, 2005) This indicates that in addition to stimulus characteristics, top-down goals guide the efficiency of emotional facial expression search Similarly, reward and punishment can modulate bottomup capture of attention (Engelmann & Pessoa, 2007) and distractor inhibition (Della Libera & Chelazzi, 2006) For more detailed coverage on the interaction between top-down goals and bottom-up processing of emotional stimuli we would refer readers to more comprehensive reviews on this topic by Aue, Chauvigne, Bristle, Okon-Singer, & Guex, 2016; Pessoa, 2009; Pessoa & Ungerleider, 2005 and Pessoa et al., 2002; Pessoa, Gutierrez et al., 2002 Neural evidence also indicates that bottom-up subcortical processing of emotional stimuli is susceptible to top-down control For example, amygdala and its influence on the visual cortex, is impacted by top-down factors like task-context and attentional control (Pessoa & Adolphs, 2010; Pessoa, 2008) Amygdala response is modulated via top-down input from prefrontal brain regions during emotional conflict (Etkin, Egner, Peraza, Kandel, & Hirsch, 2006) and reappraisal (Ochsner, Bunge, Gross, & Gabrieli, 2002; Ochsner et al., 2004; Phan, Wager, Taylor, & Liberzon, 2004); for a review see (Ochsner & Gross, 2005) While some studies have argued that amygdala response to threatening stimuli is independent of voluntary attention (e.g Vuilleumier et al., 2001), these studies tend to use tasks in which threatening stimuli are presented in an unexpected manner, and have not examined the contributions top-down factors, such as those implemented via projections from the prefrontal cortex to the amygdala Hence, Pessoa and Adolphs (2010) propose an alternative model, which underlines the numerous connections between the prefrontal cortex, the visual cortex, the amygdala and other subcortical structures, and posits that the amygdala is primarily involved in the coordination of cortical processing rather than just the detection of threat The interaction between bottom-up emotional processing and top-down factors also plays an important role in anxiety as outlined by the attentional control theory (Eysenck et al., 2007) This theory posits that trait anxiety increases the attention given to threatening stimuli and impairs attentional control In other words, trait anxiety impairs top-down guidance of attention and boosts bottom-up processes related to threat detection More specifically, according to attentional control theory, trait anxiety impairs the efficiency with which non-threatening stimuli are processed, rather than always impacting performance This is consistent with studies that found that accuracy (Calvo, Eysenck, Ramos, & Jimenez, 1994; Ikeda, Iwanaga, & Seiwa, 1996; Markham & Darke, 1991) or reaction time was not negatively impacted by anxiety (Bishop et al., 2004; Compton et al., 2003; Whalen et al., 1998) Attentional control theory also posits that the impact of trait anxiety on performance is exacerbated as demands on the executive control increase (Ashcraft & Kirk, 2001; Eysenck, 1985) Finally, in addition to evidence indicating that emotional bottom-up factors constantly interact with top-down factors, research increasingly shows that top-down factors play a vital role in perception (Barrett & Simmons, 2015; Summerfield & de Lange, 2014) Perceptual decision-making is heavily influenced by factors that occur prior to physical encounter with the stimulus, such as, expectations regarding what is contextually relevant or likely This is exemplified by faster and more accurate recognition of objects that occur in familiar contexts (Bar, 2004; Brattico, Naatanen, & Tervaniemi, 2002; Enns & Lleras, 2008), hence, a loaf of bread is identified more accurately than a drum in the kitchen (Palmer, 1975) More recently, research is showing that emotional top-down factors can also influence perception (e.g., Sussman et al., 2016; Sussman, Szekely et al., 2016) In the brain, top-down factors such as expectation, context, attention, and learning have been shown to influence amygdala activity The amygdala is one of the most highly connected regions of the brain and shows connectivity consistent with that of a ‘hub’ region (Barbas, 1995; Stephan et al., 2000; Swanson, 2003; Young, Scannell, Burns, & Blakemore, 1994) indicating that it is well situated to influence processing in other regions In summary, while much has been learned regarding the bottom-up factors involved in the perceptual prioritization of emotional stimuli, increasing evidence is showing that 1) studies examining attentional and perceptual biases for emotional stimuli have largely utilized paradigms that capitalize on the use of bottom-up processes, 2) bottom-up perception and related neural mechanisms are sensitive to top-down influence, 3) top-down factors play a critical role in human visual perception Together, these lines of evidence underscore the importance of examining the role of top-down prestimulus biases in the prirotized perception of threatening stimuli Top-down guidance of perception In contrast to bottom-up processes, top-down processes are endogenous and driven by contexts or goals According to the top-down perspective, visual perception involves a process of hypothesis testing in which predictive perceptual models are proposed based on prior knowledge and incoming sensory information is compared to these predicted models (Gregory, 1968; Summerfield et al., 2006) Therefore, past knowledge and experience create expectations of what is relevant or likely, helping facilitate the speed and accuracy of subsequent perceptual judgments This expectation takes the form of predictive neural representations that may be based on perceptual templates that consist of important discriminating features (Neisser, 2014) used to aid stimulus recognition These predictive representations are implemented via two important top-down mechanisms: 1) by an attention-related prioritization of stimulus processing based on the relevance of the stimulus to goals and 2) by an expectation-related interpretation of stimulus based on the likelihood of encountering an anticipated stimulus (Summerfield & de Lange, 2014; Summerfield et al., 2006) The function of top-down attention is to allocate cognitive resources based on the relevance or salience of a stimulus given the current context Common manipulations of attention by top-down processes include spatial attention, feature-based attention, and object-based attention (Kanwisher & Wojciulik, 2000) For example, prior knowledge of the target stimulus location enhances the detection of stimuli at the attended location (Carrasco, Ling, & Read, 2004; Posner, Snyder, & Davidson, 1980), even when attention is ‘covert’ (i.e in the absence of saccades to attended locations) Similarly, top-down spatial biasing towards the location reduces the distracting effects of salient stimuli at other locations (Theeuwes, 1991; Yantis & Jonides, 1984) In contrast to attention, the effect of expectation is often studied by manipulating the likelihood of the occurrence of a stimulus Studies have robustly demonstrated that responses to visual stimuli are facilitated by the conditional Please cite this article in press as: Sussman, T J., et al Top-down and bottom-up factors in threat-related perception and attention in anxiety Biol Psychol (2016), http://dx.doi.org/10.1016/j.biopsycho.2016.08.006 G Model BIOPSY-7253; No of Pages 13 ARTICLE IN PRESS T.J Sussman et al / Biological Psychology xxx (2016) xxx–xxx probability of occurrence in a given context Objects are recognized more quickly in a context in which they are likely to be found (Gold & Shadlen, 2007; Heekeren, Marrett, & Ungerleider, 2008) Research also demonstrates that objects in familiar or predictable contexts are recognized faster and more accurately than objects seen in unpredictable contexts (Bar, 2004; Brattico et al., 2002; Enns & Lleras, 2008); for example, a loaf of bread is identified more accurately than a drum in the kitchen (Palmer, 1975) Additionally, humans integrate and weigh prior knowledge about likelihood and uncertainty in combination with current sensory information in perceptual decision-making following Bayes’ theorem (Bach & Dolan, 2012) In contrast, unexpected visual objects in a complex scene are often detected more slowly and with more errors (Biederman, Mezzanotte, & Rabinowitz, 1982) Top-down guidance of perception by emotional cues While threatening stimuli can take us by surprise, we often detect these stimuli within contexts or following cues that indicate an upcoming threat Implicit and explicit environmental cues direct us to stimuli that are relevant or likely given the context, subsequently improving perception For example, a context such as a dense forest path in Colorado can create expectations of seeing a bear, or an overt cue, such as a sign warning that a floor was recently washed, encourages us to look for slippery spots, resulting in faster detection of the expected stimulus Emotional and motivational top-down factors (e.g searching for threat or anticipating reward) have been shown to influence target detection When emotional stimuli are task-relevant, in other words, when they are prioritized both by top-down and bottom-up processes, detection of these stimuli are improved For example, happy and threatening facial expressions are prioritized when they are the target of search, but not when they are in opposition to task goals, (Hahn & Gronlund, 2007; Williams et al., 2005) Furthermore, cues indicating an upcoming threat-related perceptual decision improve the sensitivity and speed of subsequent perceptual decisions (Sussman et al., 2016; Sussman, Szekely et al., 2016), specifically in case of subsequent fearful faces (Sussman, et al., 2016) These studies indicate that, in addition to stimulus characteristics, emotion-related top-down goals guide the efficiency of facial expression search, and can improve target detection Top-down processes could improve threat perception by guiding attention to a spatial location, or to a specific feature For example, on a visual search task, cues correctly predicting the spatial location and threat value of faces improved reaction time; performance improved both when spatial cues were accurate and when cues accurately predicted an angry face, demonstrating that endogenous processes related to both spatial and feature-based attention can enhance threat detection (Mohanty, Egner, Monti, & Mesulam, 2009) Additionally, on a cued word identification task, emotional words were more accurately identified than neutral words, while emotional distractors had no impact on performance, suggesting that when directed to looking for a specific emotional stimulus via cues, perceptual processing of that emotional stimulus is enhanced (Zeelenberg, Wagenmakers, & Rotteveel, 2006) The arousal-biased competition theory suggests a mechanism by which top-down processes may perceptually prioritize emotional stimuli It posits that emotional cues increase arousal, biasing selective attention toward perception of the stimuli relevant to the goal at hand (Mather & Sutherland, 2011) Brain mechanisms of top-down guidance of perception After sensory information hits the retina it is processed in hierarchically organized regions with increasing level of abstractness and complexity before a percept is formed (Deco & Rolls, 2004; Tanaka, 1996) Downstream (higher order) brain regions feed information back to upstream (lower order) regions, influencing how information is processed These feedback projections outnumber the feedforward projections in most stages of the hierarchy, and therefore are likely to have a major influence on the processing of incoming information (Angelucci et al., 2002) Since attention and expectation are two top-down influences that may play a crucial role in perceptual biases towards threatening stimuli, this review will focus on these two factors Top-down modulation of perception impacts most known stages of visual information processing, even in brain regions that process basic visual information, such as V1 (Li, Piech, & Gilbert, 2006; Motter, 1993; Roelfsema, Lamme, & Spekreijse, 1998) In fact, top-down modulation has been found to occur even before the sensory information reaches the cortex in the subcortical region of lateral geniculate nucleus (McAlonan, Cavanaugh, & Wurtz, 2008; O’Connor, Fukui, Pinsk, & Kastner, 2002); for review see (Gilbert & Li, 2013) Top-down modulation is more obvious in extrastriate areas (V2/V3 and V4) (McAdams & Maunsell, 1999; Nienborg & Cumming, 2009), and in the medial (Womelsdorf, Anton-Erxleben, & Treue, 2008) and ventral visual streams (Chelazzi, Miller, Duncan, & Desimone, 1993) The effect of attention and expectation on visual cortical activity prior to stimulus onset has been demonstrated in multiple human studies (Esterman & Yantis, 2010; Peelen, FeiFei, & Kastner, 2009; Stokes, Thompson, Nobre, & Duncan, 2009; Summerfield et al., 2006) For example, using a cued face/house discrimination task, one study demonstrated increase of bloodoxygen-level dependent (BOLD) signal in object-category-specific visual cortical areas during expectation (Esterman & Yantis, 2010) Anticipation increases prestimulus neuronal activity in sensory and decision-related neurons (Kastner, Pinsk, De Weerd, Desimone, & Ungerleider, 1999; Ress, Backus, & Heeger, 2000; Summerfield & de Lange, 2014) For example, studies show that neurons in the inferior temporal lobe that encode the expected stimulus show increased activation following a predictive cue (Erickson & Desimone, 1999) Similarly, neurons in medial temporal lobe (sensitive to object motion) are activated prior to a predicted motion stimulus (Albright, 2012; K Sakai & Miyashita, 1991) Prestimulus BOLD signal in extrastriate visual cortex is associated with subsequent decisions regarding whether subjects report seeing the Rubin’s vase illusion as a face or a vase (Hesselmann, Kell, Eger, & Kleinschmidt, 2008), and face-related cues elicit increased BOLD signal in fusiform face area (FFA) prior to face stimulus onset (Bar et al., 2001; Esterman & Yantis, 2010; Puri, Wojciulik, & Ranganath, 2009) In a random dot classification task, BOLD signal in motion sensitive visual cortex prior to stimulus onset predicts the subject’s response (Hesselmann, Kell, & Kleinschmidt, 2008) Another study examining the prestimulus oscillatory activity over motor cortex found that both endogenous expectation (without explicit cue) and expectation induced by explicit cues biases the starting point of decision-related activity before the accumulation of sensory evidence (de Lange, Rahnev, Donner, & Lau, 2013) Studies examining the ensemble activity patterns of BOLD signal have shown that top-down attention to a target activates targetspecific representations in shape-sensitive visual areas (Peelen et al., 2009), and brain regions involved in olfactory perception (Zelano, Mohanty, & Gottfried, 2011), indicating a preparatory bias favoring the attended stimulus over competing ones Increased prestimulus activity may reflect increased attention prior to stimulus onset, thereby improving subsequent detection (Hesselmann, Sadaghiani, Friston, & Kleinschmidt, 2010) Alternatively, according to sequential sampling models of perceptual decision-making, like the drift diffusion model (Ratcliff & Smith, 2004; Ratcliff, 1978), increases in prestimulus activity may reflect a bias or shift in the starting point for evidence accumulation towards a specific decision boundary, or may reflect a change in the rate of Please cite this article in press as: Sussman, T J., et al Top-down and bottom-up factors in threat-related perception and attention in anxiety Biol Psychol (2016), http://dx.doi.org/10.1016/j.biopsycho.2016.08.006 G Model BIOPSY-7253; No of Pages 13 ARTICLE IN PRESS T.J Sussman et al / Biological Psychology xxx (2016) xxx–xxx evidence accumulation (Summerfield & de Lange, 2014) Behaviorally, studies have shown that a predicted stimulus is associated with faster reaction time, higher accuracy, and higher perceptual sensitivity compared to unpredicted stimuli (Bar, 2004; Geisler, 2008; Polat & Sagi, 1994) In addition to sensory areas, top-down modulation of visual processing involves prefrontal and parietal areas For example, top-down biasing of attention in space involves a network of frontoparietal regions that include the intra-parietal sulcus in the posterior parietal cortex (PPC) and the frontal eye fields (FEF), the anterior cingulate cortex and supplementary motor area (ACC/SMA), and the thalamus and superior colliculus (Corbetta & Shulman, 2002; Gitelman et al., 1999; Kastner, De Weerd, Desimone, & Ungerleider, 1998; Kastner et al., 1999; Mesulam, 1981, 1999; Reynolds, Chelazzi, & Desimone, 1999) This spatial attention network is hypothesized to form an integrated search template combining the spatial coordinates and the relevance of the anticipated stimulus to bias visual neurons in preparation for the search process (Egner, 2008; Gottlieb, 2007; Thompson & Bichot, 2005) Brain regions involved with assessing the motivational value of a stimulus include neurons in the inferior parietal lobule and the intra-parietal sulcus (Bushnell, Goldberg, & Robinson, 1981; Mountcastle, Lynch, Georgopoulos, Sakata, & Acuna, 1975; Sugrue, Corrado, & Newsome, 2004) and limbic regions such as amygdala (Pessoa et al., 2002; Pessoa, Gutierrez et al., 2002; Vuilleumier & Driver, 2007) However, whether these regions communicate is unclear The cingulate gyrus may be a conduit for information on motivational salience used by the spatial attention network (Mesulam, Van Hoesen, Pandya, & Geschwind, 1977), as the limbic parts of the cingulate gyrus send projections to frontoparietal regions and posterior cingulate neurons signal reward outcomes associated with eye movements (McCoy, Crowley, Haghighian, Dean, & Platt, 2003) and preferences guiding visual orienting (McCoy & Platt, 2005) Brain mechanisms of top-down guidance of perception by emotional cues While most studies have focused on the brain mechanisms of bottom-up perception of emotional stimuli, newer evidence is beginning to uncover the brain circuitry that is involved in top-down guidance by emotional information In one study, endogenous guidance of attention was manipulated by predictive cues offering both probabilistic information related to the location of a subsequently presented stimulus, and information regarding the emotional salience of that stimulus (Mohanty et al., 2009) Spatially valid cues enhanced target detection In addition, cues accurately predicting angry face targets were associated with faster responses than uninformative cues, indicating an endogenous mediation of improved target detection, driven by emotional cues Functional imaging showed that prior to the stimulus presentation, spatially informative cues activated the frontoparietal spatial attention network including the intra-parietal sulcus and FEF, as well as FG Cues predicting angry faces also activated brain regions associated with emotional processing, including limbic areas, such as the amygdala Additive effects of spatial and emotional cueing were identified in the intra-parietal sulcus, FEF and FG indicating that cues activate regions involved in directing spatial attention prior to arrival of the threat are activated in preparation These regions also had increased connectivity with the amygdala following angry face cues This study demonstrates that prestimulus threat-related cues elicit amygdala input to the spatial attention network and inferotemporal visual areas, thereby facilitating threat detection Separate from the effects of attention, expectations regarding upcoming targets can enhance their perception (Summerfield & Egner, 2009) According to the ‘predictive coding’ theory, rather than passively absorbing sensory input, the brain actively predicts what is coming, generating a prestimulus template against which observed sensory information is matched (Summerfield et al., 2006; Zelano et al., 2011) In an fMRI study in which human subjects decided whether visual objects were faces or not, predictive neural representations related to faces were reported in medial prefrontal cortex (mPFC; Summerfield et al., 2006) Interestingly, perceptual decisions about faces were associated with an increase in top-down connectivity from the mPFC to face-sensitive visual cortices, including FFA, consistent with the idea that the prefrontal cortex codes for the predicted representations and sends top-down signals that guide the sensory regions in collecting relevant evidence to make the perceptual decision Using multivariate pattern (MVP) analyses of prestimulus ensemble patterns, another study showed that target-specific ensemble patterns emerge prior to encountering the target stimulus in the orbitofrontal cortex (OFC) and in sensory cortices Furthermore, these prestimulus patterns reliably predict subsequent behavioural performance (Zelano et al., 2011) In a study that examined the impact of threat compared to neutral prestimulus cues on brain activity and subsequent performance, threat cues increased both cue- and stimulus-related brain activation and improved subsequent stimulus detection (Sussman et al., 2016) More specifically, threat cues resulted in a larger late positive potential (LPP) and in increased superior temporal sulcus (STS) activity, both of which are measures of emotional face processing In addition, threat cues specifically increased amygdala activity for subsequently presented threatening vs neutral faces Furthermore, brain activity, as measured by the LPP and STS activity, predicted subsequent improvement in the speed and precision of perceptual decisions about threatening faces These results demonstrate how top-down processing elicited by prestimulus threat-related cues can enhance subsequent perceptual decision-making It has also been hypothesized that this enhancement may be due to arousal-induced release of norepinephrine into the locus coeruleus leading to increased levels of glutamate and norepinephrine at the site of the goal-relevant representation, thereby enhancing the representation of the goal-relevant stimulus (Mather, Clewett, Sakaki, & Harley, 2015) Overall, while the neural mechanisms involved in prestimulus threat-related biases are relatively unexplored, emerging evidence indicates that top-down factors may impact threat perception both by changes in prestimulus activity in sensory regions as well as prestimulus biasing via templates instantiated in higher order regions (including PPC, FEF, and other prefrontal regions) and interactions of these regions with limbic and sensory regions 10 Top-down guidance of the perception by emotional cues in anxiety Top-down processes may also play a crucial role in the development and maintenance of perceptual biases in anxiety disorders Anticipation of negative future events is one of the cardinal features of anxiety For example, people with anxiety tend to overestimate both the likelihood of negative events occurring and the cost of these negative events (Grupe & Nitschke, 2013) Thus, a person with clinical anxiety or spider-related fear standing in a room with cobwebs might have higher expectation of spiders being present and overestimate their dangerousness compared to a non-anxious person in the same room As a result of this overestimation, anxious individuals will scan the environment for spiders and will detect them faster if present Researchers have proposed that focusing on the anticipatory phase in anxiety may be an effective strategy Please cite this article in press as: Sussman, T J., et al Top-down and bottom-up factors in threat-related perception and attention in anxiety Biol Psychol (2016), http://dx.doi.org/10.1016/j.biopsycho.2016.08.006 G Model BIOPSY-7253; No of Pages 13 ARTICLE IN PRESS T.J Sussman et al / Biological Psychology xxx (2016) xxx–xxx to determine psychological and neurobiological factors involved in anxiety development and maintenance (Davis et al., 2010) According to the ‘uncertainty and anticipation model of anxiety,’ anxiety influences several cognitive processes, two of which relate directly to threat perception (Grupe & Nitschke, 2013) First, hypervigilance, or increased attention to threatening information even before a stimulus is presented can lead to both faster detection of threatening stimuli and a misinterpretation of neutral stimuli For example, anxiety caused by the threat of shock leads to faster detection of negative stimuli (Robinson et al., 2011), interpretation of neutral faces as being negative in socially anxious individuals (Yoon & Zinbarg, 2008) and interpretation of ambiguous interoceptive experiences as being negative in people high in anxiety sensitivity (Richards, Austin, & Alvarenga, 2001) Second, inflated estimates of threat probability and the costs of threats can lead to improved performance (Paulus & Yu, 2012), via overweighting of low probability events (Mukherjee, 2010) Recent evidence provides direct support for the view that anxiety can improve perception by influencing top-down processes such as top-down attention This research shows improvement in perceptual sensitivity due to prior threat-related information is dependent on individual differences in trait anxiety and current levels of induced anxiety (Sussman, Szekely et al., 2016) In this study, two groups of participants varying in levels of trait anxiety (dispositional anxiety) identified degraded emotional and neutral stimuli in a cued two-alternative forced-choice perceptual task One group completed the perceptual tasks in the presence of the threat of shock (high situationally induced anxiety), while the other group completed the same task in the absence of threat of shock (low situationally induced anxiety) Individual differences in trait anxiety moderated gains in perceptual sensitivity following the threat cue, such that higher trait anxiety was associated with larger gains in perceptual sensitivity in the presence of shock (Sussman, Szekely et al., 2016) but worse perceptual sensitivity in the absence of shock Overall, results from this study demonstrated that distinct types of anxiety (dispositional and induced) interact with each other in influencing how prior threat-related information is used in a top-down manner to guide perception (Sussman, Szekely et al., 2016) Prestimulus threat-related information can influence perception by effecting attention or expectation, both of which are hypothesized to involve different psychological and neural mechanisms (Summerfield & de Lange, 2014) The cues in the aforementioned Sussman, Szekely et al (2016) indicated what to look for (threatening or neutral faces) but the cues did not provide information regarding the likelihood of targets Aue and colleagues (2013, 2016) manipulated the probability or likelihood of upcoming targets to examine whether threat expectancy (inflated estimates of threat probability) impacts detection of a spider or birds in individuals with or without spider fear (Aue et al., 2016; Aue, Guex, Chauvigne & Okon-Singer, 2013) In two studies, they manipulated expectancy via a prestimulus cue telling participants there was a 90% or 50% likelihood of seeing a spider or a bird Cues indicating the likelihood of spiders did not have a significant impact on the speed of spider detection for individuals with or without spider fear However, prestimulus cues regarding the likelihood of seeing a bird on the subsequent trial lead to observable differences in reaction time, error rates, pupil diameter and heart rate for both groups of subjects (Aue et al., 2016; Aue, Guex, Chauvigne & Okon-Singer, 2013) These studies indicate that top-down manipulation of expectancies does not impact detection of threatening stimuli the way it affects detection of non-threatening stimuli Taken together, the Sussman et al (2016, 2016) and Aue et al (2013, 2016) studies indicate that anxiety is associated with differential utilization of attention but not probability-related information regarding upcoming threatening stimuli Making use of prior threat related information requires the maintenance of task-relevant representations online in working memory to match against incoming stimuli (Sreenivasan, Sambhara, & Jha, 2011) Because emotional representations are maintained with greater vividness (Bywaters, Andrade, & Turpin, 2004), they may tax working memory resources more than neutral internal representations Therefore, tasks that require the maintenance of threat-related information, or that encourage the unnecessary entry of threat-related information into working memory may result in deficits for individuals high in trait anxiety (Stout, Shackman, & Larson, 2013; Sussman, Szekely et al., 2016) Trait anxiety is thought to particularly impact the efficiency on tasks involving the inhibition function (supporting empirical research includes Calvo & Eysenck, 1996; Fox, 2002; Yiend & Mathews, 2001), the shifting function (Eysenck et al., 2007; Gopher, Armony, & Greenshpan, 2000), and, to a certain extent, the updating function (Duff & Logie, 2001) Neurally, anxiety is associated with reduced recruitment of regions involved in top-down control For example, predictive representations of upcoming target stimuli are maintained in prefrontal regions of the brain, specifically, the dorsal and ventral medial prefrontal cortex (DMPFC & VMPFC; Summerfield et al., 2006) Studies show that anxiety is associated with poorer recruitment of DMPFC (Shin et al., 2005) and dorsolateral prefrontal cortex (DLPFC; Bishop, 2009), possibly contributing to an impaired ability to maintain and deploy threat-related perceptual templates in the service of threat perception In line with this, low trait anxious individuals have been found to benefit from cues preceding a visual search task, whereas individuals high in trait anxiety are not able to use these cues as effectively (Berggren & Derakshan, 2013) In a recent study, decreased perceptual sensitivity in high trait anxiety was observed for threatening but not neutral cues (Sussman, Szekely et al., 2016) Since the adverse impact of anxiety on performance becomes greater with increasing task demands on the central executive (Eysenck et al., 2007), it is possible that maintenance of a perceptual set for threatening stimuli which might be more complex may be more demanding than maintaining a perceptual set for neutral stimuli Few studies have examined neural mechanisms of threat related guidance of attention or expectation in anxiety However, examination of neural activity at rest or prior to stimulus onset in anxiety provides clues into potential neural mechanisms Neuroimaging studies have demonstrated that the amygdala is more active for people with anxiety disorders compared to healthy controls (Furmark et al., 2002; Sakai et al., 2005; Semple et al., 2000), and for people with a short variant of the 5-HT transported gene compared to individuals homozygous for the long variant (Canli et al., 2006), when at rest Anticipatory amygdala and anterior cingulate cortex activity prior to treatment predicted treatment outcome weeks later (Nitschke et al., 2009) In one experiment, subjects with social phobia were asked to imagine giving a public speech Individuals with social phobia had hyperactivity in limbic and paralimbic regions compared to healthy controls (Lorberbaum et al., 2004) While anticipating giving a public speech, socially anxious individuals also showed increased limbic activation and decreased striatal activation (Boehme et al., 2014), as well as reduced functional connectivity between cortical regions involved in emotion regulation and limbic regions (Cremers et al., 2015) Furthermore, symptom severity was found to correlate with changes in activation and connectivity (Boehme et al., 2014; Cremers et al., 2015) Overall, these studies show greater limbic activity prior to stimulus onset in anxiety suggesting that anxiety may impact threat perception by changes in prestimulus activity in limbic regions, possibly leading individuals with anxiety to interpret cues regarding salience and the likelihood of upcoming threatening stimuli differently than individuals without anxiety Enhanced perceptual Please cite this article in press as: Sussman, T J., et al Top-down and bottom-up factors in threat-related perception and attention in anxiety Biol Psychol (2016), http://dx.doi.org/10.1016/j.biopsycho.2016.08.006 G Model BIOPSY-7253; No of Pages 13 ARTICLE IN PRESS T.J Sussman et al / Biological Psychology xxx (2016) xxx–xxx sensitivity in threatening contexts, or following threat-related cues may also be due to enhanced sensory-perceptual functions, which have been observed in both high trait anxiety and induced anxiety (Robinson, Vytal, Cornwell, & Grillon, 2013) Results from one study demonstrate that the threat of shock changes neural processing to a sensory-vigilance mode that prioritizes threatening stimuli (Arnsten, 2009; Shackman et al., 2011) Finally, models of decisionmaking suggest a few mechanisms that could drive the perceptual prioritization of threatening images in anxiety by biasing decisions towards a threaten response (Sussman, Szekely et al., 2016) Overall, the role of top-down factors in threat perception in anxiety is not well understood While greater activity in threat-sensitive limbic and sensory brain regions at rest and during anticipatory periods in anxiety suggests a possible mechanism by which threat perception could be prioritized in anxiety, the impact of anxiety on top-down attention or expectation of threat is not yet known Some empirical evidence supports enhancements in perceptual sensitivity due to prior threat-related information; however, these perceptual benefits depend on the type of anxiety In dispositional anxiety, impairment of top-down mechanisms may make utilization and maintenance of top-down threat-related information harder; whereas this information may be more effectively utilized in case of clinical and situationally induced anxiety 11 Conclusion The perceptual prioritization of threatening stimuli, often described as a bias for these stimuli, in dispositional, clinical and induced anxiety has been observed as faster detection of threatrelated stimuli (Lim & Pessoa, 2008; Mogg & Bradley, 1999; Mogg et al., 2000; Ohman et al., 2001; Robinson et al., 2011), or greater activation in fear-sensitive brain regions (Bishop et al., 2004; Etkin et al., 2004; Larson et al., 2005) This perceptual advantage has generally been studied as a bottom-up phenomenon driven by the physical characteristics of the threatening stimulus Because bottom-up processes were thought to drive the prioritized perception of threat, experiments designed to study a bias for threatening stimuli have often relied on tasks that only tested the effects of exogenous factors However, top-down processes, such as prior knowledge, expectations and goals, influence perception (Brosch et al., 2010; Pessoa & Adolphs, 2010) Furthermore, these endogenous factors are of particular importance in anxiety, which is characterized by exaggerated and inaccurate estimates of the probability and costs of future negative events (Grupe & Nitschke, 2013) Therefore, examining the impact of top-down factors on threat perception in anxiety is a crucial step towards shedding light on how basic processes of cognition, such as perception, may shape the development and maintenance of anxiety and related disorders Future studies should focus on examining the differential impact of threat-related top-down and bottom-up mechanisms (e.g., cues guiding one to look for threatening faces and threatening faces themselves) on perception and attention Distinguishing the impact of prestimulus attention from the impact of prestimulus expectation of seeing a salient target could provide more fine-grained detail about how top-down factors influence perception in normal function and in anxiety Examination of neural and computational models would help elucidate the mechanisms implementing specific top-down and bottom-up factors involved in the perceptual prioritization of emotional stimuli For example, future studies could compare pre- and post-stimulus neural representations of emotional vs neutral stimuli in visual and prefrontal regions of the brain, allowing us to determine how each contributes to perceptual prioritization of threat in anxiety The use of computational models would allow us to examine the specific mechanisms that contribute to the perceptual prioritization Furthermore, the impact of other types of top-down processes on threat perception should be examined For example, since we typically can infer what kinds of threats and rewards are more relevant or likely depending on the context we currently inhabit, exploring the impact of context on threat perception will allow for more ecologically valid examination of how emotional stimuli are perceptually prioritized Some work has been conducted in this vein A recent study demonstrated that negative contexts evoked by recalling a real-life threat (the Boston Marathon Bombings) led to an increased false alarm rate on a shooting task (Wormwood, Lynn, Feldman Barrett, & Quigley, 2016) This study demonstrates that by studying the impact of context, we can add considerably to our understanding of how threats are perceptually prioritized, and how neutral stimuli may be misperceived as threatening in dayto-day life The interaction of situational contexts (such as the one described above), and internal contexts, such as anxiety, or other moods should also be explored to gain a more complete understanding of how top-down factors impact perception While some research has been done in this area, many questions remain One study demonstrated that a fearful mood, induced via film clip, could speed reaction times over and above the impact of low-level visual information (LoBue, 2014) However, little is known about how positive moods impact threat perception, or about how situational and internal contexts interact in their impact on threat-perception Future research should also aim to better isolate the impact of top-down from bottom-up factors on threat perception, as results could advance our understanding of how these factors interact to perceptually prioritize emotional stimuli Drawing these distinctions is especially crucial when studying the influence of anxiety on perception, as anxiety is associated with inaccurate estimates of the likelihood and costs of future negative events (Grupe & Nitschke, 2013) Elucidating how individual differences in anxiety impact the interaction between top-down and bottom-up factors, both in terms of behavioural performance and neural processing, could provide clues about how basic perceptual processes are associated with clinical symptoms 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