R1.1. Nature of arousal

In our view, the LC–NE system is not the only brain system involved in a generalized arousal response (see Pfaff 2006 for a review of arousal pathways in the brain), but its activation is a common theme that runs through all different modes of arousal. For instance, NE inputs to cells in the ventromedial hypothalamus are critical in initiating sexual arousal (Pfaff 2006; of relevance for Mouras’ commentary), whereas noradrenergic input to the amygdala is critical in enhancing memory for emotionally arousing stimuli (see Roozendaal, Luyten, Voogd, & Hermans’ commentary and Section R4.2 on the role of the amygdala).

What is arousal? At the most basic level, we have the contrast between sleep and wakefulness. NE is low during most sleep states (see Becchetti & Amadeo). Then, during wakefulness, physically activity increases NE (Carter et al. 2010). But in addition to these broad-scale changes, the arousal system is also exquisitely sensitive and can adapt rapidly to small changes in the environment or internal goals.

These arousal responses can be detected by measuring pupil dilation. NE system activity increases pupil dilation, as NE released by the LC inhibits pupil constriction (Koss et al. 1984; Wilhelm 2008). Pupils are constricted during sleep, compared with wakefulness (Yoss et al. 1970). During wakefulness, aerobic exercise (Ishigaki et al. 1991) or muscular exertion (Nielsen & Mather 2015; Nielsen et al. 2015) increases pupil dilation. Arousal induced by stimuli or tasks also increases pupil dilation. For example, emotionally arousing scenes (Bradley et al. 2015), sexually arousing stimuli (Bradley et al. 2015), surprise, uncertainty, loud noises, and cognitive effort all increase pupil dilation. Subjective arousal ratings given for emotional images correlate with pupil diameter during viewing (Bradley et al. 2008). These consistencies across different elicitors of arousal provide an important starting point at which to elucidate the underlying mechanisms by which encountering emotionally arousing stimuli modulates cognitive and brain processing. Eldar, Cohen, & Niv review a recent line of work in which they used pupil dilation as a marker of NE activity and found that indices of high NE function are associated with increased selectivity in learning, perception, and memory, consistent with their neural network models in which NE was modeled as global increase in gain. GANE complements and extends this approach by providing hypotheses about how NE implements neural gain.

We agree with Mouras and Kaspar regarding the relevance of sexual arousal and internal sources of arousal (such as from one’s thoughts). Our point of view is that these different types and sources of arousal can be accommodated by the GANE model, as evidence suggests that LC activation is a common theme for all of them.

R1.2. How the heartbeat influences LC activity

The LC is influenced not only by external stimuli and an individual’s own thoughts, but also by interoceptive signals. For instance, distension of the bladder or colon increases LC activity (Elam et al. 1986), whereas an increase in blood pressure decreases LC activity (Elam et al. 1984). LC neurons also exhibit cardiac periodicity. For instance, in cats, LC neurons are most likely to fire 80–180 ms after the peak of the cardiac R-wave (during diastole) and least likely to fire 40 ms before to 60 ms after the R-wave (during systole) (Morilak et al. 1986).

Critchley & Garfinkel have shown that stimuli detection and memory encoding differ during the systole (contraction) and diastole phases of the heartbeat. During systole, participants are better able to detect fear (but not neutral) faces in an attentional blink paradigm and rate them as more intense (Garfinkel et al. 2014). When words are the T2 stimuli in an attentional blink paradigm, later memory for the words depends on both the confidence with which the words were originally detected and at what heartbeat phase the words were detected (Garfinkel et al. 2013). Words detected with high confidence during systole have a memory advantage, whereas words detected with low confidence during systole have a memory disadvantage. Therefore, during systole, highly salient stimuli such as fear faces and clearly detected target words get a boost in processing or later consolidation. But why would this GANE-like pattern occur during systole when the LC neurons are less likely to fire? This surprising aspect of the findings suggests the possibility that LC activity and salient glutamatergic representations may interact best when they are offset slightly in time.

Critchley & Garfinkel argue that the GANE notion that LC–NE activity amplifies salience is not sufficient to account for their findings because their cardiac cycle effects sometimes appear to be driven by fear rather than arousal more generally. However, as illustrated in their figure, there was not a significant difference between fear and disgust or happy faces, and the disgust and happy faces showed trends toward enhancement where neutral faces showed a trend toward impairment at diastole. Fear faces are often more salient than happy or disgust faces (Anderson et al. 2003; Mather & Knight 2006); therefore, we think more work is needed before a specific-emotion account must be invoked in place of a salience mechanism such as that provided by GANE.

R1.3. How arousal may amplify the salience of negative stimuli

Kaspar makes the case that negative stimuli may be more likely than positive stimuli to ignite neuronal hot spots because of the evolutionary pressure not to miss potential threats. One challenge is how to test this hypothesis, as negative stimuli, on average, induce more arousal than positive stimuli (Grühn & Scheibe 2008), and so any differences in processing or memory between negative and positive stimuli could be due to different levels of arousal when processing them, rather than to different levels of priority. To try to address this question, we recently ran a study in which we induced arousal independently by having participants squeeze a ball in their hand as hard as they could before they viewed emotional pictures and examined how the resulting increases in arousal influenced memory for the pictures (Nielsen et al. 2015). We were interested in hormonal effects, and all participants were younger female women. Consistent with Kaspar’s predictions, we found that handgrip-induced arousal enhanced memory for the negative, but not the positive pictures. This effect was most pronounced for women with low estrogen and progesterone levels at the time of testing.

Kaspar also suggested that because of declines in the LC–NE system, negative stimuli lose their arousing potential as people age. However, the evidence suggests that the older adults’ positivity effect is not due to a lack of bottom-up salience for negative stimuli. Like younger adults, older adults look first at arousing stimuli regardless of their valence (Knight et al. 2007) and notice arousing or threatening stimuli more quickly than other types of stimuli (Leclerc & Kensinger 2008; Mather & Knight 2006). Bottom-up affective salience should play less of a role in influencing processing for low-arousal pictures, and indeed, the positivity effect appears to be stronger among valenced stimuli low rather than high in arousal (Kensinger 2008). In addition, we found that arousal induced by handgrip selectively benefited memory encoding of negative pictures (compared with positive or neutral pictures) in older women not taking hormone supplements, as well as in younger women with low estrogen and progesterone levels (Nielsen et al., in preparation). The evidence thus suggests that arousing negative pictures have similar bottom-up salience for older and younger adults.

R1.4. Relation between arousal and appraisal theory

On the basis of appraisal theory, Montagrin & Sander raise a question about how arousal and priority interact. They argue that arousal and goal relevance are not independent and stimuli that are relevant for individuals’ goals, needs, and values induce strong arousal and amygdala activity. We agree with them: Given that the LC exhibits phasic activity in response to goal-relevant stimuli (Aston-Jones & Cohen 2005; Aston-Jones et al. 1999), it seems possible that goal-relevant stimuli become arousing. However, the appraisal theory approach they discuss does not detail the neural mechanisms by which arousal induced by goal-relevant stimuli helps people memorize (Montagrin et al. 2013) and prioritize attention to those stimuli (Pool et al. 2015). In contrast, our GANE model can explain their findings of enhanced processing of goal-relevant stimuli: once the amygdala and/or prefrontal regions detect goal-relevant stimuli and recruit the LC (see Sara & Bouret 2012 for discussion of amygdala and prefrontal inputs to LC), NE hot spots will be generated in circuits transmitting goal-relevant information and, in turn, hot spots will enhance memory and perception for those stimuli. Therefore, GANE does not contradict the appraisal model, but instead extends it.

R2.1. Perspectives on physiological mechanisms of priority

Larkum & Phillips describe a novel physiological mechanism by which contextual information modulates pyramidal cell activity. Neocortical pyramidal cell bodies have an apical trunk that ascends to a dendritic branching pattern called an apical tuft, which resides in a different cortical layer than the cell body and the basal dendrites around it. The long distance of the apical tuft from the cell body sets it up to serve a modulatory role in driving cell activity (Phillips 2015). Apical amplification could, for example, provide top-down priority selection of a quiet bottom-up auditory input to cortical output circuits. In their figure, Larkum & Phillips illustrate the interaction between GANE and apical amplification priority, providing an experimentally testable physiological model. Houghton argues that, computationally, the mossy cell hilar circuit in hippocampus would set priority for hippocampal processing and suggests heavy hilar NE innervation is consistent with GANE amplification of that mechanism. Becchetti & Amadeo make the interesting point that conscious (and, thus, prioritized) oneiric processing occurs during rapid eye movement (REM) sleep, likely supported by high acetylcholine modulation. But with active suppression of LC–NE during REM, there is little or no memory of those priority events, also consistent with GANE.

R4.1. NE-only model

Strange & Galarza-Vallejo propose that the glutamate aspect of the model is not necessary; they describe a simpler model in which priority is coded by phasic NE release in the brain. They work through an example from research on the emotional oddball – 1 (E-1) effect, in which emotional oddballs (words or pictures) impair memory for the immediately preceding item on the list if that item was low priority for the participant, but enhance it if that item was high priority (e.g., Sakaki et al. 2014a). A problem with their NE-only model is that it is not clear how phasic NE release can selectively “tag” the E-1 item and not other items. Perhaps in the simple setup they describe, in which one word or object appears at a time in the list, phasic NE release could mark activated neural networks via a temporal tagging process. However, they do not consider findings that when multiple items are shown simultaneously, whether and how much memory for them is enhanced or impaired by a subsequent emotional item depends on their priority. For example, in an experiment in which a scene was shown either alone or with an object superimposed (Fig. R1A), if the image was followed by an emotional sound, there was impaired memory for the scene later, but only if it had been made lower priority by being in the background (Fig. R1B) (Ponzio & Mather 2014). Likewise, in another study in which participants saw four items at the same time that were then followed by a tone that was conditioned to predict either a shock (CS+) or no shock (CS−), having a subsequent arousing tone affected later memory for the simultaneously shown items differently depending on the relative priority of the items (Lee et al. 2015). The model Strange and Galarza-Vallejo propose does not explain how phasic LC activation could have different effects on items shown at the same time. In our view, this is the main contribution of GANE: by positing a mechanism for local cortical modulation of NE, it provides the only explanation to date of how arousal can have simultaneous differential effects on items based on their priority.

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Fig. R1

(A) Arousing negative sounds were heard after seeing a background scene either alone or superimposed with a foreground object. (B) The arousing sounds impaired memory for the scene only when it was seen behind the object and, therefore, was somewhat suppressed by that competitor (Ponzio & Mather 2014).

R7.1. Prediction errors

Prediction is a central feature of efficient cognitive processing. As described by Ferreira-Santos, GANE fits well with “predictive coding” frameworks of cognition: sudden mismatches between predicted and actual sensory and affective inputs represent an important form of conflict and competition that can elicit arousal and LC activity. Supporting this view, pupil dilation has been linked to the occurrence of prediction errors (Braem et al. 2015; Preuschoff et al. 2011). Furthermore, in monkeys, phasic LC activity ceases to signal the occurrence of reward once the reward follows a specific action predictably (Sara & Segal 1991). Other research also indicates that affect enhances prediction error responses (Vogel et al. 2015) and that prediction errors are a fundamental component of generating interceptive feelings (Barrett & Simmons 2015).

R7.2. Uncertainty

As pointed out by Nassar, Bruckner, & Eppinger, as well as by Bouret, it is important to consider the purpose of having one level of arousal modulate cognitive processing differently than another level. When is it useful for cognitive processing to remain focused on previously salient information? And when will it be advantageous to be open to new prioritized information? Nassar and colleagues argue that during times of uncertainty, it is especially important not simply to focus on current prioritized cues, but to amplify incoming prioritized sensory information (Yu & Dayan 2005). They review findings that pupil diameter is larger during periods of uncertainty than when expectations are reliable. Thus, tonically higher levels of NE should decrease the threshold for new salient stimuli to ignite hot spots. They suggest that older adults’ deficits in learning under conditions of uncertainty may be linked to age-related declines in LC function.

R8.1. Varied effects of adrenoceptors

As highlighted in several commentaries, the GANE model does not incorporate all known adrenoreceptor functions. These omissions include the role of postsynaptic α₂-receptors that play important roles in the PFC (see commentaries by Abdallah, Averill, Krystal, Southwick, & Arnsten and Todd, Ehlers, & Anderson) and that also occur in other areas of neocortex (Venkatesan et al. 1996). Navarra & Waterhouse and Gaucher & Edeline point out that α₁-adrenoreceptors have more varied actions, including synergism with β-adrenoreceptor effects, potentiation of effects on their own, and astrocytic action. In particular, they highlight that the role of α₁-adrenoreceptor in sensory cortex may be facilitatory: when activated, these receptors appear to potentiate postsynaptic excitatory responses and can boost subthreshold inputs (for a review, see Berridge & Waterhouse 2003). Furthermore, global astrocytic calcium waves are initiated via LC–NE activation of astrocytic α₁-adrenoreceptors (Ding et al. 2013), consistent with a model in which LC–NE global effects recruit both α₁- and α₂-adrenoreceptors.

R8.2. Suppressive effects of NE in sensory regions

Gaucher & Edeline emphasize the suppressive actions of exogenous NE on processing in auditory cortex as being inconsistent with GANE. But their finding that a small population of auditory neurons encoding natural stimuli are enhanced by NE (Gaucher & Edeline 2015) and contribute to discrimination is similar to newer findings in olfactory cortex that LC–NE modulation is essential for difficult natural odor discrimination and increases the stability of small distributed odor representations (Shakhawat et al. 2015), as predicted by GANE.

R8.3. Differential effects of adrenergic receptors in prefrontal and posterior cortex

Abdallah, Averill, Krystal, Southwick, & Arnsten highlight the differences between the actions of NE on classic sensory synapses in subcortical and posterior sensory regions and newly evolved circuits in layer 3 of the dorsolateral PFC (DLPFC). On the basis of animal and human research, they suggest hot spot effects are most likely to occur in sensory and limbic (e.g., amygdala, hippocampus) synapses where β-adrenoreceptors promote glutamate responses and long-term potentiation. In the PFC, in contrast to “classic” sensory areas, β-adrenoreceptor activation has been found to impair rather than enhance postsynaptic function via increased cAMP signaling (Arnsten et al. 2015; Ramos & Arnsten 2007). Like β-adrenoreceptors, α₁- and α₂-adrenoreceptors also appear to have contrasting influence on neuronal activity in the PFC versus sensory cortices. Although α₁-receptors enhance sensory neuron firing, they tend to impair PFC function and working memory (Ramos & Arnsten 2007). On the other hand, whereas α₂-receptors enhance inhibitory signals and suppress noisy activity in the posterior cortex, their activation strengthens dorsolateral PFC functional network connectivity and promotes working memory (Arnsten et al. 2012).

These inverted rules of adrenoreceptor function in the PFC have important implications for how GANE influences cognitive processing during sudden arousal. Although an arousal-induced surge of NE may disrupt working memory representations in the DLPFC (e.g., current event models), it should also transiently enhance the throughput of strong glutamatergic signals in the hippocampus (Brown et al. 2005). Therefore, DLPFC impairments may facilitate reorientation during arousal to information that has bottom-up salience and is associated with hot spots of high activity in sensory regions but not in PFC.

R8.4. Relative timing of arousal and prioritization process

The key distinction outlined in the previous section between the effects of NE in sensory cortices and limbic regions versus the PFC agrees well with the timing hypotheses proposed by Warren, Murphy, & Nieuwenhuis. In their commentary, Warren and colleagues present evidence that the relative strength of bottom-up and top-down (cognitive control) priority inputs changes rapidly within a single trial. Whereas bottom-up salience dominates the competition for mental resources early on, cognitive control processes take longer to develop and overcome the initial dominance of perceptual salience. Warren et al. suggest that this time-variant model of salience determines whether phasic arousal enhances or impairs task-relevant (but not perceptually salient) information.

Indeed, the GANE model predicts that arousal-induced NE release will bias competition in favor of whatever information has the highest priority at that moment. Experiencing arousal while a representation is highly active should strengthen that representation regardless of whether top-down goals or bottom-up salience prioritized the representation, because the representation was activated before moderate to high levels of NE could disrupt goal-directed processing in the PFC (Ramos & Arnsten 2007). In contrast, the source of priority may matter more when experiencing arousal before a stimulus is perceived. Although prestimulus arousal should amplify the effects of bottom-up salience, it may diminish the effects of top-down priority if, as outlined in the previous section, working memory processes that help maintain and implement processing goals are impaired by the arousal (Ramos & Arnsten 2007).

Data from our lab provide clear evidence that prestimulus arousal enhances the impact of bottom-up salience (Lee et al. 2013; Sutherland & Mather 2011; 2015), whereas poststimulus arousal enhances the impact of top-down prioritization (Lee et al. 2015; Sakaki et al. 2014a; 2014b). Whether arousal enhances priority for the other two combinations remains to be seen. We have not yet tested scenarios in which something perceptually salient is followed by something arousing, but GANE would predict that as long as the representation associated with that perceptually salient item were still strongly active when arousal increased, it would benefit further from the arousal. In contrast, as outlined above, the situation in which arousal occurs before top-down prioritization occurs could show the reverse effect; insofar as arousal disrupts the ability of the PFC to prioritize an otherwise nonsalient stimulus, arousal should diminish the impact of top-down priority because the goal-relevant representation is not highly activated. Consistent with this, we have found that playing an emotional sound before a brief display of letters makes it harder for participants to selectively report the letters in the high point value color (Sutherland et al., under review). Given the impairing effects of high NE on DLPFC, for a prestimulus arousal to enhance processing of a goal-relevant item, the goal prioritization process would need to be relatively independent of the PFC, perhaps because it is automatic or habitual.

R8.5. Inverted-U relationship between LC firing and cognitive selectivity

Aston-Jones and Cohen (2005) proposed an inverted-U model of tonic NE function, in which low tonic LC activity promotes being inattentive and nonalert, moderate LC activity promotes being focused, and high tonic LC activity promotes distractibility. In their commentary, Navarra & Waterhouse ask where along the inverted-U function the glutamate–NE interactions proposed in GANE would operate. Their question is in part inspired by data from Devilbiss and Waterhouse (2000), who simultaneously administered glutamate and NE into in vitro rat barrel field cortex slices. They found that some cells showed a monotonic suppression of the excitatory postsynaptic response to glutamate, as NE increased. Other cells showed an inverse U shape, in which there were increasing glutamate-evoked discharges as NE increased to 5 nA, but then decreasing glutamate-evoked discharges as NE tonic levels were further increased (10–30 nA). These findings suggest that tonic levels of NE modulate postsynaptic responses to glutamatergic input, which is quite interesting. In particular, it seems that high tonic levels of NE would quiet activity in neurons exhibiting this postsynaptic NE suppression, which could contribute to the general decrease in neural noise seen under arousal (one interesting side note is that they found that, unlike in layers II/III, NE-induced facilitation of glutamate-evoked responses was the predominant response in layer V, which may be connected to the apical amplification ideas of Larkum & Phillips). However, the in vitro preparation of the study eliminated the LC from the equation and so did not provide the opportunity to observe the glutamate-evoked local release of NE proposed in GANE. As outlined in Table R2, more research is needed measuring in vivo interactions of glutamate and NE, as the GANE hot spot mechanism involves interactions between the LC and distant cortical representations.