The Role of the Locus Coeruleus in Risk Assessment during the
Acute Stress Response.
Literature Review
of
Lea K. Hildebrandt
6240917
As part of the research master
Brain and Cognitive Sciences,
Cognitive Neuroscience Track,
University of Amsterdam,
Amsterdam, Netherlands.
Supervisor:
Cade McCall, PhD,
Social Neuroscience Department,
Max Planck Institute for Human Cognitive and Brain Sciences,
Leipzig, Germany.
Co-Assessor:
Dr. Sanne de Wit,
Clinical Psychology Group,
Department of Psychology,
University of Amsterdam,
Amsterdam, Netherlands.
Introduction
Defensive behaviors, such as fight and flight, have long been associated with the response to acute stress. When faced with a dangerous, threatening situation, humans show an immediate activation of the sympathetic nervous system which allows for a quick and efficient behavioral response. Acute stress has been defined as “any threat, either real or perceived, to the homeostasis and well-being of an organism” (Morilak et al., 2005, p. 1215). It is important to note that acute stress, which will be discussed in this review, differs from the daily experience of e.g. work-related stress or potential stress, in that it asks for an immediate action. This stress response is based on observations of animal prey threatened by predators (Cannon, 1929), but it has been suggested that similar defensive behaviors can be found in humans (Blanchard, Hynd, Minke, Minemoto, &
Blanchard, 2001). Interestingly, the variety of possible defensive behaviors has increased and it has been suggested that these behaviors are ordered: flight, fight, and freeze. Thus, the first choice behavior would be to flee, if no escape route is visible fight would result, and if fight is futile, a freezing response, or ‘playing dead’, would occur (Blanchard & Blanchard, 1989). Notably, in order to have adaptive value, this stress response has to occur rapidly.
However, it can be assumed that threats in human’s lives differ from those to animals. Not only the sources of threat (stressors) and their uncertainties and level of threat differ, but also the environment and the human’s abilities to cope with the stressor. Therefore, the range of possible defensive behaviors can be assumed to differ widely. For example, when mugged on the street, running away might be fruitful only if hiding spots are near or the mugged person is faster than the robber. In contrast, fighting would only be beneficial if one is stronger than the robber or when objects that can be used as a weapon are within reach. It can thus be concluded that within the short time period available to prepare a behavioral response, decision processes have to take place. It has been acknowledged by a number of researchers, that the (motor preparation for a) behavioral response is preceded by a first orienting response in which attention is allocated to the threat and environment in order to assess the risks and possibilities for subsequent behavior (e.g. Blanchard, Griebel, Pobbe, & Blanchard, 2011; Lang, Davis, & Ohman, 2000; Pavlov, 1927).
Interestingly, attentional decision-making processes have been linked to this period of the stress response. Two concepts that have been suggested to be involved are attentional scanning of the environment (Blanchard et al., 2011) and, less frequently, a cost-benefit analysis (Lima, 1998) of the situation. These two concepts are also core aspects of the recently proposed adaptive gain theory of decision making (Aston-Jones & Cohen, 2005), which implies that specific norepinephrine (NE) release from the locus coeruleus (LC) leads to two different modes of action: Eploitation and exploration. As long as one behavior is still beneficial, this behavior will be continued (exploitation).
However, if the benefit decreases, the environment would be explored for other, more beneficial behaviors (exploration). Exploitation is therefore associated with selective/focused attention to the task demands, whereas exploration relies on a broad, scanning attention to the environment. In a stressful situation, it seems to be crucial to interrupt any ongoing activities and scan the environment for a possible threat and helpful features of the environment to carry out any defensive action. The aim of this literature review is to shed light on the possible role that exploration/exploitation play in the stress response. For this end, I will first summarize the theories on defensive behaviors in response to stress. Subsequently, I will give an overview of the adaptive gain theory. Eventually, I will point out possible overlaps between these two theories, thereby laying emphasis on locus coeruleus activity.
Defensive behavior in response to acute stress
The original formulation of the stress response, also known as the fight-or-flight response, is accredited to Walter B. Cannon (1929) and describes physiological changes that are associated with preparation for either fleeing from or fighting against the source of threat.
Physiological aspects of the fight-or-flight response
The core aspect of Cannon’s theory is an activation of the sympathetic division of the
autonomic nervous system with a concurrent inhibition of the parasympathetic division. This pattern of activation leads to physiological changes such as an acceleration of the heart rate, increased blood flow to the skeletal muscles and lungs, increased sweating, and the dilation of the pupils, among others. These vascular changes are thought to be related to the allocation of resources away from e.g. digestive processes to organs that enable fast movement (Cannon, 1929). Therefore, the stress response comprises a motor preparation and can thus be seen as a motivational process.
Importantly, Cannon (1929) emphasized the involvement of the adrenal medulla in the sympathetic activation. The adrenal medulla releases epinephrine and norepinephrine; two catecholamines that are associated with arousal, whose release in the organs affects the sympathetic activation.
Consequently, the fast sympathetic-adrenal medulla (SAM) system is involved in the immediate stress response (Krugers, Karst, & Joels, 2012; Starcke & Brand, 2012).
The SAM system is assumed to interact with another, somewhat slower, stress-responsive system, the hypothalamic-pituitary-adrenal (HPA) axis. Involvement of the HPA axis was first proposed by Hans Selye (1955), who also introduced the term stress as it is used today. Simply said, corticotrophin-release factor (CRF) is released by the hypothalamus, which leads to release of adrenocorticotropic hormone (ACTH) in the pituitary gland, which, in turn, triggers cortisol release in the adrenal cortex. Furthermore, negative feedback loops exist between these stages. HPA activation
is associated with sustaining the stress response if necessary and restoring homeostasis (Krugers et al., 2012). It has been suggested that the fast stress response is independent of this second wave of activation. Furthermore, a third, fast part of the stress response was identified: the intracerebral stress response, which denoted the specific brain activation in response to threat (Elling et al., 2011).
Evolutionary aspect of the stress response
Importantly, Cannon strongly emphasized the fast, automatic nature of the fight-or-flight response:
“The most significant feature of these bodily reactions […] is that they are of the nature of
reflexes – they are not willed movements, indeed they are often distressingly beyond the control of the will. The pattern of the reaction, in these as in other reflexes, is deeply
inwrought in the workings of the nervous system, and when the appropriate occasion arises, typical organic responses are evoked through inherent automatisms” (Cannon, 1929, p. 185).
The distinction of human behavior into automatic, reflex-like processes as well as cognitive, controlled processes, denoted as will by Cannon, is in line with Darwin’s (1872) third principle of direct action of the nervous system. This principle states that a strong stimulation would activate certain bodily expressions independently from ‘will’, mainly due to strong nerve connections. This division into a fast, automatic and a somewhat slower controlling process is concordant with theories of the evolution of the human brain and its function. For example, MacLean (1990) proposed that cognition, mainly located in the neocortex, is unique to mammals. In contrast, emotions and
motivations, which are dependent on the limbic system, developed earlier in the course of evolution. The oldest circuit was thought to be the basal ganglia, which supports instinct-driven behavior and can also be found in reptiles.
In line with this evolutionary account, certain reactions of the body, some without obvious function, might “have been developed for quick service in the struggle for existence” (Cannon, 1929, p. 186) and might thus be inherited characteristics from remote ancestors (Cannon, 1929, p. 1). Based on the assumption of phylogenetic association (Crile, 1911), which is similar to Darwin’s (1859) notion of common descent of species, Cannon (1929) assumed that residues of the fight and flight behavior that are found in animals when confronted with a predator can also be found in humans. Indeed, Cannon’s theory of visceral changes is based on observations in humans. However, due to the fact that the term ‘stress’ was not yet used in this context, Cannon associated his observations with fear and anxiety. Nowadays, acute threat is still strongly associated with fear, whereas potential threat is linked to anxiety (e.g. Lang, Davis, & Ohman, 2000). In accordance with Cannon, Darwin (1872) had already proposed that emotions are reflected in facial and bodily expressions in humans,
linking fear to increases in heart rate, breathing, and cold sweat, as well as erection of hair and dilation of pupils (chapter 12). Crile (1911), a surgeon, reported physiological fear reactions in his patients similar to those reported by Cannon (for example acceleration of the heart rate, cold sweat, rise in body temperature, and erection of hair). Crile furthermore associated this fear reaction with perceived danger.
To summarize, the physiological response to a stressor can be found in animals as well as humans and is of adaptive value. This pattern of SAM activation is associated with the preparation for defensive action, namely to either flee from or fight against the threat.
Other defensive behaviors responses
With the growing research interest in defensive behaviors in the last 30 years, it has been suggested that Cannon’s proposition including only fight or flight behavior is oversimplified (Blanchard & Blanchard, 1989; Bracha, Ralston, Matsukawa, Williams, & Bracha, 2004; Rantner, 1967) Blanchard and Blanchard (1989) have subdivided the fight response into a defensive threat and a defensive attack response. Defensive threat is associated with vocal and bodily expressions of threat, such as screaming, whereas defensive attack is the actual aggressive fight against or attack of the stressor. Moreover, they also emphasized that hiding can be seen as a form of escape and thus belongs to the flight response.
Furthermore, it has been observed (Gallup, 1977) that animals often freeze when threatened. During this freezing response, animals abruptly stop to move up to the point of thanatosis (“playing dead”). This behavior can be of adaptive value because it increases the chances to escape from an attack if the predator loses interest or is distracted (Schmidt, Richey, Zvolensky, & Maner, 2008).
Gallup (1977) has found a similar response in humans with post-traumatic stress disorder or victims of rape, which he named tonic immobility (TI). Concerning acute stress situations, Leach (2004) analyzed witness reports from survivors of airplane and ship accidents. One common observation was that some people died because they remained “paralyzed” (p. 4), “behaviorally inactive, […] passive and stiff” (p.3). He associated this (lack of) behavior with a cognitive paralysis, or the inability to ‘think clearly’ (Leach, 2005, p. 135). Schmidt et al. (2008) carried out a controlled experiment in the laboratory where they administered 20% CO2 enriched air to the participants as a threat and subsequently asked the participants to fill in questionnaires. They concluded that, even though the desire to flee was chosen more frequently, 31% of the participants reported mild to great freezing. Marx, Forsyth, Gallup and Lexington (2008) have reviewed the TI response in humans and have suggested that not only extreme fear but also restraint or entrapment is a necessary
Cascade of defensive behaviors
Which of these defensive behaviors is carried out is not arbitrary. In contrast, it has been proposed that these defensive behaviors are hierarchically ordered: flight, fight, and TI(D Caroline Blanchard et al., 2011; Bracha et al., 2004). The most likely defensive response is thus, contrary Cannon’s proposition, flight. Only if no escape route or hiding place can be identified, fight is initiated (Blanchard & Blanchard, 1989). Specifically, Blanchard and Blanchard (1989) suggested that first defensive threat and then defensive attack are considered. Finally, if fight is not an adaptive response (for example, because the stressor is perceived to be invincible), TI would result. However,
Blanchard, Hynd, Minke, Minemoto and Blanchard (2001) proposed that flight is the first choice defensive behavior, followed by hiding. If neither of those is possible, freezing will result up to a certain distance of the stressor (1 m in the rats they studied). If the threat is closer, defensive threat will occur, and with an even smaller distance (0.5 m in rats), defensive attack results. It seems thus that defensive behaviors are organized hierarchically.
Hence, even without a clear order of defensive behaviors, it is clear that a (small) number of different response options exist. Furthermore, the selection of one of these behaviors seems to depend on features of the stressor (distance) as well as the environment (escape route?).
Although the cascade model sheds some light on the order of occurrence or priority of defensive behaviors, it leaves unacknowledged how a certain defensive behavior is selected. It does, however, indicate that certain processes of evaluation have to take place in order to carry out a successful behavioral response. First of all, the location and nature or severity of the threat has to be identified. Second, the environment has to be scanned for possible escape routes, hiding spots, or weapons. Lastly, one’s own strength in relation to the stressor has to be evaluated. The outcome of these attentional processes then needs to be integrated for an utility analysis and a beneficial response has to be chosen.
Risk assessment
Along these lines, a number of researchers have postulated an initial stage of assessment (Blanchard et al., 2011; Bracha et al., 2004; Gray & McNaughton, 2000; Pavlov, 1927). Pavlov (1927) made a distinction between orienting and defense reflexes, and Gray and McNaughton (2000) included freezing into the revised version of his fight-or-flight system. Gray and McNaughton acknowledges that two types of freeze exist, whereby the first occurs “when the animal is awaiting the optimal moment to emit an innate flight response” (2000, p. 96). This period of freezing is thus, in contrast to TI, not associated with a (cognitive) paralysis but rather attention. Due to the fact most predators do not have a good color vision and rely on motion to locate prey (Nesse, 1999), not
moving in this period is adaptive because it increases the chances of not being seen. Bracha et al (2004) have associated this period with “hypervigilance (being on guard, watchful, or hyper-alert)” (p. 448) or to “stop, look, and listen” (p. 448). Similarly, Blanchard and colleagues (2011) have proposed a period of risk assessment (RA), a
“highly adaptive process [that] takes into account important characteristics, such as type and
location (including distance from the subject) of the threat, as well as those (e.g. presence of an escape route or hiding place) of the situation, combining them to predict which specific defense is optimal” (p. 991).
Along these lines, level of ambiguity of the threat has also been related to a RA (Blanchard), whereas a discrete stressor is linked to (a faster execution of) defensive behaviors. Furthermore, they associate RA with disruption of ongoing behavior, choice of a behavioral response, and determining when a threat is no longer present. Thus, it can be assumed that RA plays a major role at the beginning of the stress response but continues to be important throughout.
Predator imminence model
Another, slightly larger scale, model of defensive behavior is the predator imminence model (Fanselow, 1994) , which incorporates how acute the threat is and emphasizes the related increase in arousal. Timberlake and Lukas (1989) have proposed three stages of defensive behavior:
pre-encounter, post-pre-encounter, and circa-strike. Pre-encounter is the stage where one enters a potentially threatening area, post-encounter is associated with the detection of threat, and circa-strike is the stage where contact with the source of threat is inevitable (Fanselow, 1994). A similar distinction can be found in Gray and McNaughton’s (2000) theory, based on Graeff’s (1987) theory. Here, the stages are called potential danger (to approach vs. to avoid), distal danger, and proximal danger. The defensive behaviors described above are those occurring during circa-strike or proximal danger (Fanselow, 1994; Gray & McNaughton, 2000; Lang et al., 2000). However, it can be assumed that RA coincides with the post-encounter phase, in which threat detection is central. Importantly, the sequence through the three stages is related to increases in arousal.
Cardiac defense
Vila and colleagues (2007) proposed a theory that combines the motivational aspect of the stress response – the motor preparation for defensive behaviors – with the attentional aspects of RA. Moreover, being concerned with the cardiac stress response, this theory returns to Cannon’s starting point of visceral activation. To recapitulate, Cannon emphasized activation of the sympathetic nervous system with a concurrent inhibition of the parasympathetic nervous system. In contrast, Vila
et al. (2007) imply a more complex pattern of sympathetic and parasympathetic involvement in the stress response.
In particular, they proposed a theory of cardiac defense based on findings of Bond (1943), a student of Cannon. Bond concluded that the heart rate does not simply increase, as would have been expected based on Cannon’s proposed
sympathetic activation, but that two accelerations of heart rate are divided by a decrease in heart rate back to baseline or even beyond. Vila et al. (2007) have specified this cardiac response to include two periods of heart rate increases, each followed by heart rate decreases (see figure 1). Interestingly, the functional interpretation of these patterns is in
line with the above summarized division into RA and defensive behaviors. Vila and colleagues (2007) suggested that the first in- and decrease of heart rate are associated with attentional processes “aimed at interruption of the ongoing activity and analysis of the potential danger” (p. 178). In contrast, the second in- and decrease is assumed to be related to action preparation of defensive behaviors.
The decelerations of the heart rate provide support for a role of the parasympathetic nervous system in the stress response. Another theory that emphasizes parasympathetic, especially vagal, involvement is the polyvagal theory of Porges (2001). Porges suggested three stages of neural control of the heart rate, which are based on phylogenetic differences between species. The third stage incorporates the unmyelinated, dorsal vagus. Activation of this evolutionary older part of the vagus nerve is, according to Porges (2001), associated with immobilization or freezing. The SAM system is the second stage in the model and also associated with mobilization, like Cannon’s fight or flight responses. Finally, the first and most recently evolved stage comprises the myelinated or ventral vagus, which is assumed to enable inhibition of the SAM system. This stage is proposed to be related to communicative and self-soothing functions. These three stages could coincide with the last 3/4th of Vila et al.’s (2007) cardiac defense model, although the polyvagal theory does not explicitly include a linear order of the stages. In addition, the polyvagal theory could be more applicable to the longer lasting HPA or even to a chronic stress response. Nevertheless, the heart rate decelerations found by Vila and colleagues are likely to be due to vagal influences.
Figure 1. Average second-by-second heart rate response of 15 participants to the first presentation of an intense noise. Taken from Vila et al. (2007)
Summary
To summarize, the currently prevailing opinion in research on defensive behaviors is that any threat is initially succeeded by a period of scanning attention associated with risk assessment and decision making. However, the nature of these attentional and decision-making processes is still unclear. Crucial aspects of this period, occurring simultaneously with an increase in arousal, can thus assumed to be the interruption of ongoing behavior through a re-allocation of attention and the integration of information leading to the choice of a defensive behavior. Therefore, RA seems to involve some sort of cost-benefit or utility analysis: “RA enables the animal to predict, with much greater precision than would otherwise be the case, the likelihood of success of each specific defense that it might make with reference to a particular threat” (Blanchard 2011, p. 992). Interestingly, these attentional processes have been incorporated in the adaptive gain theory by Aston-Jones and Cohen (2005) as crucial parts of the utility analysis necessary for decision-making.
Adaptive Gain Theory
The adaptive gain theory (AGT) is based on the differentiation of behavior into exploitation of ongoing activity and exploration of alternative options. Exploitation can be seen as the safe choice, as it consists of continuation of behavior with a well-known outcome. However, this behavior can be suboptimal, if other options more rewarding options exist. Switching to an alternative behavior with unknown outcome is thus risky but can be beneficial (Cohen, McClure, & Yu, 2007). Exploitation has been linked to focused attention necessary for goal-directed behavior, whereas exploration is associated with broad attention directed at scanning the environment for sources of possible reward (Aston-Jones, Iba, Clayton, Rajkowski, & Cohen, 2007).
Locus coeruleus and AGT
Interestingly, Aston-Jones and colleagues (e.g. Aston-Jones, Rajkowski, & Cohen, 1999; Rajkowski, Kubiak, & Aston-Jones, 1994; Usher, Cohen, Servan-Schreiber, Rajkowski, & Aston-Jones, 1999) have associated exploitation and exploration with different patterns of activity of the locus coeruleus (LC). The LC is a structure in the brainstem in which the major part of the brain’s norepinephrine (NE) is released (Maeda, 2000). NE is strongly associated with arousal, which is assumed to have a modulating effect on efferent structures. This means that NE is not in itself
excitatory or inhibitory but augments evoked responses in target structures. In addition, it is linked to decreasing spontaneous, stimulus-unrelated activity of neurons in these structures. Consequently, this led to the proposition that NE mediates a decrease of the signal-to-noise ratio in target structures (Aston-Jones et al., 2007).
LC activity is therefore traditionally thought of as being correlated with arousal. However, in recent years, Aston-Jones and his colleagues, who have greatly studied LC activity, differentiated between tonic and phasic activity of the LC (e.g. Rajkowski et al., 1994). Initially it was suggested that tonic LC activity is related to arousal, based on the finding that spontaneous LC activity is higher during wakefulness than sleep. At the same time, it was observed that LC cells fire phasically in response to both unconditioned (e.g. noise) and conditioned (targets in a task) stimuli (Rajkowski et al., 1994). Similarly, phasic activity was found “in response to conspicuous environmental stimuli of many modalities” (Aston-Jones et al., 1999, p. 1310). Foote, Aston-Jones and Bloom (1980) found that presentation of a novel stimulus lead to phasic activity in the monkey LC associated with
interruption of ongoing behavior and orientation towards that stimulus. Aston-Jones et al. (1999) had monkeys carry out a visual discrimination task while measuring single cell LC activity. They found that phasic activity immediately followed target stimuli and occurred more often in periods of good task performance. Notably, phasic activity did not occur after non-target distractors and reversal of stimulus meaning did not affect the results, which implies that it is related to the meaning, e.g. the salience, and not the features of the stimuli. Tonic activity, in contrast, is increased in periods of worse performance, measured by more false alarms. Interestingly, Aston-Jones and colleagues found phasic activity only at moderate levels of tonic activity (see figure 2). This is in line with the Yerkes-Dodson Law (Yerkes & Yerkes-Dodson, 1908), which states
that performance of a difficult task is optimal at a medium level of arousal but is impaired at both high and low levels of arousal (Aston-Jones et al., 1999). Therefore, it can be said that phasic activity is related to both a stimulus-driven orienting response as well as top-down control of vigilance, or sustained, focused, selective attention (Berridge & Waterhouse, 2003). Tonic activity, in contrast, is
related to overall arousal, behavioral flexibility and scanning attentiveness. The latter interpretation is also reflected in a higher occurrence of scanning eye movements during tonic activity (Aston-Jones et al., 1999).
Based on these results, Aston-Jones and Cohen (2005) suggested that the role of the LC is to optimize task performance, summarized in the adaptive gain theory. Tonic activity of the LC would be visible when utility of an ongoing behavior wanes, which results in disengagement with the task and searching for alternatives. Phasic activity, in contrast, would be associated with an optimization of the performance of the ongoing behavior. Therefore, LC activity might be driven by input from cost- and reward-signaling regions, such as the anterior cingulated cortex, the ventromedial prefrontal
Figure 2. Yerkes-Dodson relationship between tonic and phasic LC activity in relationship to attention and performance. Taken from Aston-Jones et al. (1999).
cortex, and the orbitofrontal cortex (Aston-Jones et al., 2007; Cohen et al., 2007). Based on the conclusion of Yu and Dayan (2005) that NE signals unexpected uncertainty, Cohen (2007) suggested that unexpected lack of reward might signal the benefit of exploration.
In line with the relationship between tonic activity and task disengagement are findings from Devauges and Sara (1990). They found that administration of Idazoxan, a drug that increases LC (tonic) firing, resulted in a faster acquisition of a new rule, i.e. facilitated the attentional shift to novel stimuli. Similar results were found by Lapiz and Morilak (2006), who showed that enhancement of tonic NE transmission to the medial prefrontal cortex (mPFC) improved performance on an attentional set-shifting task. This improvement affected specifically extradimensional set-shifting (EDS). EDS denotes a shift of response rules to a different category: One has to ignore former target stimuli and attend to formerly irrelevant stimuli (Birrel & Brown, 2000).
Moreover, Clayton, Rajkowski, Cohen and Aston-Jones (2004) found that phasic LC activity is linked more closely to the behavioral response than to the stimulus onset, which they concluded to support that LC activity is driven by decision processes and not directly by sensory features of the stimulation. Furthermore, no phasic LC activity could be found in the case of errors of omission or unrelated motor actions, which, in addition to sensory processes, also excludes motor processes as a source for phasic activity (Aston-Jones et al., 2007).
Stress and attention
Selective, or focused, attention denotes the filtering of relevant stimuli only, thus ignoring irrelevant information. It has often been proposed that stress precludes the ability for exerting focused attention (e.g. Elling et al., 2011). It has been concluded that stressed individuals are more easily distractible, i.e. susceptible to exerting exogenous attention to salient stimuli rather than endogenous, goal-driven attention (Elling et al., 2011). Thus, these findings could indicate a decrease of phasic and an increase of tonic LC activity. However, others have proposed that selective
attention improves under conditions of stress (Chajut & Algom, 2003). It has to be noted, however, that these findings are often based on experiments that used one (sometimes rather chronic or less severe) stressor and measured attention towards a second task. Attention towards a stressor and/or attention to possible escape routes have not been studied in detail.
Interestingly, in line with Vila et al.’s (2007) model of cardiac defense, Ramírez et al. (2010) found that the in- and decreases in heart rate in response to stress, especially the later ones, were enhanced when attention was externally directed instead of internally. This could be interpreted as stimulus-driven, environmentally directed vs. top-down attention, which might be related to tonic and phasic LC activity.
LC activity in stress
When faced with acute stress, processes such as explorative scanning the environment and/or exploitative focused attention to the threat and the planning of defensive actions are crucial. Furthermore, threatening events can be seen as salient, unconditioned stimuli with a high
unexpected uncertainty. Therefore, the differential LC activation could play an important role in the RA phase of the stress response. It could be assumed that both tonic and phasic activity are
important to regulate RA, but the specific roles of both activity patterns in stress are unclear. Due to the fact that novel, unconditioned stimuli elicit phasic activation (Foote et al., 1980), its activity could be associated with the orienting response. Furthermore, a high level of focused attention might be necessary when trying to survive a life-threatening situation. In contrast, tonic activity is associated with scanning attention directed toward the environment (Aston-Jones et al., 1999), unexpected uncertainty within a task (Dayan & Yu, 2006), and behavioral flexibility (Aston-Jones et al., 1999), which can all be assumed to be important factors of evaluation of the environment and generating behavioral response options during RA.
Generally, tonic LC activity has been strongly linked to the stress response by signaling arousal (Bremner, Krystal, Southwick, & Charney, 1996). NE is crucially involved in the SAM activation and interacts with HPA axis activity (Herman & Cullinan, 1997; Radley, Williams, & Sawchenko, 2008). It is assumed that tonic NE release facilitates a behavioral response to stress (Morilak et al., 2005). Valentino and Bockstaele (2009) suggested that the LC is active in parallel to the HPA axis, and moreover, corticotropin-releasing factor (CRF), which is released by the hypothalamus during stress, have been found to cause LC activity (Jedema & Grace, 2004; Valentino & Foote, 1988). In particular, Valentino and Bockstaele (2009) proposed that tonic activity increases and phasic activity decreases as a result of CRF, which “would promote heightened arousal and scanning attention” (p. 6)
necessary for “sampling of alternate behaviors in the environment” (p. 6). The CRF-related increase in tonic activity is similar to the one found in response to stressors (Valentino & Bockstaele, 2009). Devilbiss and Waterhouse (2011) found similar increases of tonic and decreases of phasic activity in stress. This decrease of the signal-to-noise ratio was associated with impairments in sensory
processing/gating. Snyder, Wang, Han, McFadden and Valentino (2012) injected CRF directly into the rat-LC and found that aspects of attentional set-shifting, such as EDS and reversal learning, were improved. The effect of CRF is opposed by those of glutamate and opiods: Glutamate is associated with increases in phasic LC activity (Valentino & Bockstaele, 2009), whereas opiods have been shown to decrease tonic activity (Curtis, Leiser, Snyder, & Valentino, 2012). This could be an adaptive mechanism to control CRF-LC influences on cognition.
In contrast to this tonic enhancement during stress, Morilak (2005) suggested that phasic activation is triggered by the salience of a stressor and also noted that this phasic activation is correlated with the duration of peripheral physiology of the stress response (Jacobs et al., 1991), whereas tonic activity has little effect.
Short overview LC neurocircuitry
Afferent CRF innervations of the LC include the central nucleus (CN) of the amygdala and the paraventricular nucleus (PVN) of the hypothalamus, among others (Cook, 2004; Joëls & Baram, 2009). The PVN is the first stage of the HPA axis (Herman & Cullinan, 1997), and the CRF release in the LC could initiate an initial faster response to stress (the “third wave”) than the HPA axis allows. The CN has been strongly associated with fear circuits, especially with fear conditioning (Ledoux, 2000). The CN of the amygdala seems to signal the severity or valence of a stimulus and is thus important in mediating fear (Kalin). Furthermore, the CN mediates autonomic (via the lateral
hypothalamic area) and behavioral (via the periaqueductal gray, PAG) correlates of (conditioned) fear (LeDoux, Iwata, Cicchetti, & Reis, 1988). In the predator imminence model by Gray and McNaughton (2000), amygdala activation is incorporated in the post-encounter phase, which could indicate an involvement in detection of the threat or risk assessment (Fanselow, 1994).
In contrast, direct and indirect influences of LC activity on both CN and PNV have been proposed. LC projects to the basolateral amygdala, which in turn signals back to the CN (Joëls & Baram, 2009). LC tonic activity has been shown to activate the PVN, therefore modulating the HPA responses to acute stressors (Radley et al., 2008). Interestingly, the latter relationship was mediated by inhibition of the dorsal medial prefrontal cortex (mPFCd). Thus, according to Radley et al. (2008), mPFCd has an inhibitory effect on the PVN, which, in turn, is inhibited by LC activity. Speaking for an important involvement of the mPFCd in stress, these results together with findings of Lapiz and Morilak (Lapiz & Morilak, 2006), who proposed that NE transmission to mPFC enhances EDS, provide support for a possible involvement of the LC in moderating attentional processes during stress.
Even though the LC projects to a great variety of cortical and subcortical structures, an involvement of high tonic LC activity in the stress response seems compelling. This activity is triggered by CRF innervations of structures that are at the core of fear processing and the stress response. Projections from the LC to the medial prefrontal enable the scanning attention and behavioral flexibility associated with tonic LC activity.
A role for phasic activity?
Even though evidence points toward a decrease in phasic activity during the stress response, Morilak et al. (2005) have suggested that it might also play a role. Indeed, the first perception of a threatening stimulus could be seen as a novel and salient stimulus, which has been associated with both phasic activity. It could be the case that both phasic and tonic modes are part of the stress response. Particularly, the stimulation of a stressor, such as a loud, unexpected noise, could first elicit a phasic LC response, which would be succeeded – and inhibited – by an increasing, CRF-driven arousal, or tonic activity.
Alternatively, accounting for the slow response profile studied by Morilak et al. (2005), a later period of phasic attention could possibly occur which would succeed response selection and be linked to initiation of the defensive behavior. This last proposed activity is based on (Aston-Jones & Cohen, 2005) findings that phasic activity occurs after the decision is made and is linked to a behavioral response. This would also be in line with the AGT, assuming that phasic activity signals high utility of a chosen defensive behavior. However, a late phasic activity would likely depend on glutamate and opiods to counter tonic activity and would thus most likely occur during coping, or re-establishing homeostasis. Therefore, it can be assumed that during preparation of defensive
behaviors, high tonic LC activity excludes the involvement of phasic activity.
However, further investigations could shed more light on this topic. First of all, recently, the periaqueductalgray (PAG) has been strongly associated with the implementation of defensive behaviors (Mobbs et al., 2007). What is more, Mobbs et al. (2007) showed that activity shifts from ventromedial prefrontal cortex to PAG with increasing proximity of the threat (from post-encounter to circa-strike stages). Thus, this could possibly not only denote distance, but also the shift from RA to defensive behavior. Even though studies linking the LC to the PAG are sparse, LC innervations to the PAG exist (Sullivan, Coplan, Kent, & Gorman, 1999) and microinjections of NE into the PAG lead to anxiolytic-like effects (Pelosi et al., 2009). It would thus be fruitful to further investigate direct and indirect effects of the LC-NE system on PAG as a possible linking circuit between RA and defensive behaviors.
Second, if an alternating pattern between phasic and tonic activity exists, it might be
interesting to examine a possible relationship with the model of cardiac defense summarized above. Interestingly, studies on vagus nerve stimulation have resulted in an association of vagal and LC activity. The effect of vagus nerve stimulation of reducing seizures in epilepsy is reduced if the LC is lesioned (Krahl, Clark, Smith, & Browning, 1998). Furthermore, transection of the vagus nerve in rats has been shown to directly decrease tonic discharge rates in the LC, whereas phasic activity was not
affected (Borsody & Weiss, 2005). This effect was moreover attributed to the dorsal trunk of the vagus. The dorsal vagus is the evolutionary oldest part of the polyvagal theory, and is linked to immobilization (Porges, 2001). Thus, increasing influence of the dorsal vagus on slowing the heart rate would increase tonic LC discharge. This conclusion might point towards a continuous increase in arousal, even when the heart rate decreases, but it might also account for an underlying mechanism for temporarily decreasing tonic activity (enabling phasic activity and related attentional processes) if vagal influence is diminished by the SAM.
Finally, to further investigate the relationship between the stress response and AGT, it would be fruitful to focus on the involvement of brain regions suggested to play a role in AGT during the stress response. These regions are mainly the orbitofrontal cortex (OFC) and the anterior cingulate cortex (ACC), which are thought of as signaling rewards and costs and project to the LC to influence phasic and tonic activity (Aston-Jones & Cohen, 2005). Cost-benefit analysis can be assumed to play a central role in the selection of a defensive behavior, and therefore the OFC and the ACC could be involved by biasing LC activity in addition to the CRF influence. Alternatively, CRF-induced LC activity could simply simulate the influence of OFC/ACC to switch to LC tonic mode, which would enable adaptive exploration. This direct hypothalamic effect might also allow for faster LC activation than the activation via the frontal cortex. Along these same lines, it would be interesting to incorporate the LC-NE system with the function of the dopamine system, which signals reward, during stress.
Similarly, accounting for dual-process models of decision-making (e.g. Kahneman, 2003) might shed some more lights on circuits involved in automatic responses, such as stress. Dual-process models differentiate between cognitive and automatic routes to decision-making. Clearly, the hard-wired stress response is an automatic process, but, as was pointed out in this review, increasingly complex environments and threats (compared to those of animals) might ask for
increasingly complex computations. Likewise, a focus on habit formation and conditioning could shed light on implications for the daily life. Besides innate associations between a certain stressor and a defensive behavior, habit formation and conditioning are two processes that are considered automatic. It can be assumed that especially habit formation is the foundation for more complex, intuitive behavior. For example, paramedics learn certain sequences of actions so that when they encounter a stressful situation such as an accident they can depend on certain cues and
automatically carry out the order of actions.
Conclusion
The LC-NE system is involved in the acute stress response, mainly by increasing arousal by its tonic mode of activation. The LC is activated by CRF, a neuropeptide centrally involved in the stress
response. Due to the wide-spread projections of the LC throughout the brain, it is difficult to clearly define its role in the stress response. However, the mPFCd is a promising structure of involvement. According to the AGT, different patterns of activity of the LC signal utility of a certain behavior, which would have adaptive value during RA and selection of defensive behaviors. Tonic activity of the LC can be found during stress, supporting attentional scanning of the environment and behavioral flexibility. However, involvement of phasic activity in the stress response, which is related to
orienting to salient stimuli and assumed to be important in signaling high utility of a behavior, has yet to be clearly determined.
References
Aston-Jones, G, Rajkowski, J., & Cohen, J. (1999). Role of locus coeruleus in attention and behavioral flexibility. Biological psychiatry, 46(9), 1309–20. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/10560036
Aston-Jones, Gary, & Cohen, J. D. (2005). An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annual review of neuroscience, 28(May), 403–50. doi:10.1146/annurev.neuro.28.061604.135709
Aston-Jones, Gary, Iba, M., Clayton, E., Rajkowski, J., & Cohen, J. (2007). The locus coeruleus and regulation of behavioral flexibility and attention : clinical implications, 196–235.
Berridge, C. W., & Waterhouse, B. D. (2003). The locus coeruleus-noradrenergic system: modulation of behavioral state and state-dependent cognitive processes. Brain Research Reviews, 42(1), 33–84. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12668290
Birrel, J., & Brown, V. (2000). Medial frontal cortex mediates perceptual attentional set shifting in the rat. Journal of Neuroscience, 20, 4320–4324.
Blanchard, D C, Hynd, a L., Minke, K. a, Minemoto, T., & Blanchard, R. J. (2001). Human defensive behaviors to threat scenarios show parallels to fear- and anxiety-related defense patterns of non-human mammals. Neuroscience and biobehavioral reviews, 25(7-8), 761–70. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11801300
Blanchard, D Caroline, Griebel, G., Pobbe, R., & Blanchard, R. J. (2011). Risk assessment as an evolved threat detection and analysis process. Neuroscience and biobehavioral reviews, 35(4), 991–8. doi:10.1016/j.neubiorev.2010.10.016
Blanchard, R. J., & Blanchard, D. C. (1989). Attack and defense in rodents as ethoexperimental models for the study of emotion. Progress in neuro-psychopharmacology & biological
psychiatry, 13 Suppl, S3–14. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/2694228
Bond, D. D. (1943). Sympathetic and vagal interaction in emotional responses of the heart rate.
Borsody, M. K., & Weiss, J. M. (2005). The subdiaphragmatic vagus nerves mediate activation of locus coeruleus neurons by peripherally administered microbial substances. Neuroscience, 131(1), 235–45. doi:10.1016/j.neuroscience.2004.09.061
Bracha, H. S., Ralston, T. C., Matsukawa, J. M., Williams, A. E., & Bracha, A. S. (2004). Does “fight or flight” need updating? Psychosomatics, 45(5), 448–9. doi:10.1176/appi.psy.45.5.448
Bremner, J. D., Krystal, J. H., Southwick, S. M., & Charney, D. S. (1996, May). Noradrenergic mechanisms in stress and anxiety: I. Preclinical studies. Synapse (New York, N.Y.). doi:10.1002/(SICI)1098-2396(199605)23:1<39::AID-SYN5>3.0.CO;2-I
Cannon, W. B. (1929). Bodily Changes in Pain, Hunger, Fear, and Rage. New York: Appleton-Century-Crofts.
Chajut, E., & Algom, D. (2003). Selective attention improves under stress: Implications for theories of social cognition. Journal of Personality and Social Psychology, 85(2), 231–248.
doi:10.1037/0022-3514.85.2.231
Clayton, E. C., Rajkowski, J., Cohen, J. D., & Aston-Jones, G. (2004). Phasic activation of monkey locus ceruleus neurons by simple decisions in a forced-choice task. The Journal of neuroscience : the
official journal of the Society for Neuroscience, 24(44), 9914–20.
doi:10.1523/JNEUROSCI.2446-04.2004
Cohen, J. D., McClure, S. M., & Yu, A. J. (2007). Should I stay or should I go? How the human brain manages the trade-off between exploitation and exploration. Philosophical transactions of the
Royal Society of London. Series B, Biological sciences, 362(1481), 933–42.
doi:10.1098/rstb.2007.2098
Cook, C. J. (2004). Stress induces CRF release in the paraventricular nucleus, and both CRF and GABA release in the amygdala. Physiology & behavior, 82(4), 751–62.
doi:10.1016/j.physbeh.2004.06.013
Crile, G. W. (1911). Phylogenetic association in relation to the emotions. Proceedings of the American
Philosophical Society, 51(204), 76–90.
Curtis, A. L., Leiser, S. C., Snyder, K., & Valentino, R. J. (2012). Predator stress engages corticotropin-releasing factor and opioid systems to alter the operating mode of locus coeruleus
norepinephrine neurons. Neuropharmacology, 62(4), 1737–45. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22210331
Darwin, C. (1859). On the Origin of Species by Means of Natural Selection, or the Preservation of
Favoured Races in the Struggle for Life. London: John Murray.
Darwin, C. (1872). The Expression of the Emotions in Man and Animals. London: John Murray. Dayan, P., & Yu, A. J. (2006). Phasic norepinephrine: a neural interrupt signal for unexpected events.
Network: Computation in Neural Systems, 17(4), 335–50. doi:10.1080/09548980601004024
Devauges, V., & Sara, S. J. (1990). Activation of the noradrenergic system facilitates an attentional shift in the rat. Behavioural brain research, 39(1), 19–28. Retrieved from
Devilbiss, D. M., & Waterhouse, B. D. (2011). Phasic and tonic patterns of locus coeruleus output differentially modulate sensory network function in the awake rat. Journal of neurophysiology,
105(1), 69–87. doi:10.1152/jn.00445.2010
Elling, L., Steinberg, C., Bröckelmann, A.-K., Dobel, C., Bölte, J., & Junghofer, M. (2011). Acute stress alters auditory selective attention in humans independent of HPA: a study of evoked potentials.
PloS one, 6(4), e18009. doi:10.1371/journal.pone.0018009
Fanselow, M. S. (1994). Neural organization of the defensive behavior system responsible for fear.
Psychonomic Bulletin & Review, 1(4), 429–438. doi:10.3758/BF03210947
Foote, S. L., Aston-Jones, G., & Bloom, F. E. (1980). Impulse activity of locus coeruleus neurons in awake rats and monkeys is a function of sensory stimulation and arousal Neurobiology :
Proceedings of the National Academy of Sciences, 77, 3033–3037.
Gallup, G. G. (1977). Tonic immobility: The role of fear and predation. Psychological Record, 27, 41– 61.
Graeff, F. G. (1987). The anti-aversive action of druges. In T. Thompson, P. B. Dew, & J. Barrett (Eds.),
Advances in behavioural pharmacalogy. Hillsdale, NJ: Lawrence Erlbaum Associates Inc.
Gray, J. A., & McNaughton, N. (2000). The Neuropsychology of Anxiety: An Enquiry into the Functions
of the Septo-Hippocampal System, Second Edition (2nd ed.). Oxford: Oxford University Press.
Herman, J. P., & Cullinan, W. E. (1997). Neurocircuitry of stress: central control of the hypothalamo-pituitary-adrenocortical axis. Trends in neurosciences, 20(2), 78–84. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/9023876
Jacobs, B. L., Abercrombie, E. D., Fornal, C. A., Levine, E. S., Morilak, D. A., & Stafford, I. L. (1991). Single-unit and physiological analyses of brain norepinephrine function in behaving animanls.
Progression in Brain Research, 88, 159–165.
Jedema, H. P., & Grace, A. a. (2004). Corticotropin-releasing hormone directly activates
noradrenergic neurons of the locus ceruleus recorded in vitro. The Journal of neuroscience : the
official journal of the Society for Neuroscience, 24(43), 9703–13.
doi:10.1523/JNEUROSCI.2830-04.2004
Joëls, M., & Baram, T. Z. (2009). The neuro-symphony of stress. Nature reviews. Neuroscience, 10(6), 459–66. doi:10.1038/nrn2632
Kahneman, D. (2003). A perspective on judgment and choice: mapping bounded rationality. The
American psychologist, 58(9), 697–720. doi:10.1037/0003-066X.58.9.697
Krahl, S. E., Clark, K. B., Smith, D. C., & Browning, R. a. (1998). Locus coeruleus lesions suppress the seizure-attenuating effects of vagus nerve stimulation. Epilepsia, 39(7), 709–14. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9670898
Krugers, H. J., Karst, H., & Joels, M. (2012). Interactions between noradrenaline and corticosteroids in the brain: from electrical activity to cognitive performance. Frontiers in cellular neuroscience,
Lang, P. J., Davis, M., & Ohman, A. (2000). Fear and anxiety: animal models and human cognitive psychophysiology. Journal of affective disorders, 61(3), 137–59. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/11163418
Lapiz, M. D. S., & Morilak, D. a. (2006). Noradrenergic modulation of cognitive function in rat medial prefrontal cortex as measured by attentional set shifting capability. Neuroscience, 137(3), 1039– 49. doi:10.1016/j.neuroscience.2005.09.031
LeDoux, J. E., Iwata, J., Cicchetti, P., & Reis, D. J. (1988). Different projections of the central amygdaloid nucleus mediate autonomic and behavioral correlates of conditioned fear. The
Journal of neuroscience : the official journal of the Society for Neuroscience, 8(7), 2517–29.
Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/2854842
Leach, J. (2004). Why people “freeze” in an emergency: temporal and cognitive constraints on survival responses. Aviation, space, and environmental medicine, 75(6), 539–42. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/15198281
Leach, J. (2005). Cognitive paralysis in an emergency: the role of the supervisory attentional system.
Aviation, space, and environmental medicine, 76(2), 134–6. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/15742830
Ledoux, J. E. (2000). Emotion circuits in the brain. Annual Review Neuroscience, 23, 155–184.
Lima, L. (1998). Stress and Decision Making under the Risk of Predation : Recent Developments from Behavioral , Reproductive , and Ecological Perspectives. Advances in the Study of Behavior, 27, 215–290.
MacLean, P. D. (1990). The Triune Brain in Evolution: Role in Paleocerebral Functions. New York: Plenum.
Maeda, T. (2000). The locus coeruleus: history. Journal of chemical neuroanatomy, 18, 57–64. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10708919
Marx, B. P., Forsyth, J. P., Gallup, G. G., & Lexington, J. M. (2008). Tonic Immobility as an Evolved Predator Defense :, 74–90.
Mobbs, D., Petrovic, P., Marchant, J. L., Hassabis, D., Weiskopf, N., Seymour, B., Dolan, R. J., et al. (2007). When fear is near: threat imminence elicits prefrontal-periaqueductal gray shifts in humans. Science, 317(5841), 1079–83. doi:10.1126/science.1144298
Morilak, D. a, Barrera, G., Echevarria, D. J., Garcia, A. S., Hernandez, A., Ma, S., & Petre, C. O. (2005). Role of brain norepinephrine in the behavioral response to stress. Progress in
neuro-psychopharmacology & biological psychiatry, 29(8), 1214–24. doi:10.1016/j.pnpbp.2005.08.007
Nesse, R. M. (1999). Proximate and evolutionary studiesof anxiety, stress and depression: Synergy at the interfact. Neuroscience and Biobehavioral Reviews, 23, 895–903.
Pavlov, I. (1927). Conditioned Reflexes. Oxford: Oxford University Press.
Pelosi, G. G., Resstel, L. L. B. M., Soares, V. P., Zangrossi, H., Guimarães, F. S., & Corrêa, F. M. a. (2009). Anxiolytic-like effect of noradrenaline microinjection into the dorsal periaqueductal gray of rats. Behavioural pharmacology, 20(3), 252–9. doi:10.1097/FBP.0b013e32832c7098
Porges, S. W. (2001). The polyvagal theory: phylogenetic substrates of a social nervous system.
International journal of psychophysiology : official journal of the International Organization of Psychophysiology, 42(2), 123–46. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/11587772
Radley, J. J., Williams, B., & Sawchenko, P. E. (2008). Noradrenergic innervation of the dorsal medial prefrontal cortex modulates hypothalamo-pituitary-adrenal responses to acute emotional stress. The Journal of neuroscience : the official journal of the Society for Neuroscience, 28(22), 5806–16. doi:10.1523/JNEUROSCI.0552-08.2008
Rajkowski, J., Kubiak, P., & Aston-Jones, G. (1994). Locus coeruleus activity in monkey: phasic and tonic changes are associated with altered vigilance. Brain research bulletin, 35(5-6), 607–16. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/7859118
Ramírez, I., Guerra, P., Muñoz, M. A., Perakakis, P., Anllo-Vento, L., & Vila, J. (2010). The dynamics of cardiac defense: from attention to action. Psychophysiology, 47(5), 879–87. doi:10.1111/j.1469-8986.2010.01008.x
Rantner, S. C. (1967). Comparative aspects of hypnosis. In J. E. Gordon (Ed.), Handbook of Clinical and
Experimental Hypnosis. New York: MacMillan.
Schmidt, N. B., Richey, J. A., Zvolensky, M. J., & Maner, J. K. (2008). Exploring human freeze responses to a threat stressor. Journal of behavior therapy and experimental psychiatry, 39(3), 292–304. doi:10.1016/j.jbtep.2007.08.002
Selye, H. (1955). Stress and disease. Science (New York, N.Y.), 122, 625–31. Retrieved from
http://apps.webofknowledge.com/full_record.do?product=UA&search_mode=Refine&qid=2&S ID=W18MAg@@1OE2lKfJ6eJ&page=1&doc=5
Snyder, K., Wang, W.-W., Han, R., McFadden, K., & Valentino, R. J. (2012). Corticotropin-releasing factor in the norepinephrine nucleus, locus coeruleus, facilitates behavioral flexibility.
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 37(2), 520–30. doi:10.1038/npp.2011.218
Starcke, K., & Brand, M. (2012). Decision making under stress: a selective review. Neuroscience and
biobehavioral reviews, 36(4), 1228–48. doi:10.1016/j.neubiorev.2012.02.003
Sullivan, G. M., Coplan, J. D., Kent, J. M., & Gorman, J. M. (1999). The noradrenergic system in pathological anxiety: a focus on panic with relevance to generalized anxiety and phobias.
Biological Psychiatry, 46(9), 1205–1218. doi:10.1016/S0006-3223(99)00246-2
Timberlake, W., & Lucas, G. A. (1989). Behavior systems and learning: From misbehavior to general principles. In S. B. Klein & R. R. Mowrer (Eds.), Contemporary learning theories: Instrumental
conditions theory and the impact of biological constraints on learning (pp. 237–275). Hillsdale,
NJ: Erlbaum.
Usher, M., Cohen, J. D., Servan-Schreiber, D., Rajkowski, J., & Aston-Jones, G. (1999). The role of locus coeruleus in the regulation of cognitive performance. Science (New York, N.Y.), 283(5401), 549– 54. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9915705
Valentino, R J, & Foote, S. L. (1988). Corticotropin-releasing hormone increases tonic but not sensory-evoked activity of noradrenergic locus coeruleus neurons in unanesthetized rats. The Journal of
neuroscience : the official journal of the Society for Neuroscience, 8(3), 1016–25. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/3258021
Valentino, Rita J, & Bockstaele, E. V. (2009). Convergen regulation of locus coeruleus activity as an adaptive response to stress. European Journal of Pharmacology, 583, 194–203.
Vila, J., Guerra, P., Muñoz, M. A., Vico, C., Viedma-del Jesús, M. I., Delgado, L. C., Perakakis, P., et al. (2007). Cardiac defense: from attention to action. International journal of psychophysiology :
official journal of the International Organization of Psychophysiology, 66(3), 169–82.
doi:10.1016/j.ijpsycho.2007.07.004
Yerkes, R. M., & Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habit-formation. Journal of Comparative Neurology and Psychology, 18, 459–482.
Yu, A. J., & Dayan, P. (2005). Uncertainty, neuromodulation, and attention. Neuron, 46(4), 681–92. doi:10.1016/j.neuron.2005.04.026
