The Mechanisms of Locus Coeruleus-Norepinephrine System in Attention

XING Lianzi, CHEN Yujie, MIAO Chengguo, ZHANG Yang
(Department of Psychology, Soochow University, Suzhou 215100, China)

Abstract: The locus coeruleus-norepinephrine (LC-NE) system is a critical neuromodulatory system in the brain that plays an essential role in attentional regulation. This article provides a systematic review of the mechanisms by which the LC-NE system contributes to attention, including: 1) the firing patterns and activity dynamics of LC-NE neurons during attentional processes; 2) behavioral and neurophysiological indicators that reliably reflect LC-NE activity; 3) the role of LC-NE in the three attentional subsystems—alerting, orienting, and executive control; and 4) the associations between LC-NE function and various attention-related disorders. Future studies should integrate techniques such as pupillometry, event-related potentials, intracranial electroencephalography, high-resolution neuroimaging, and neuromodulation. Combining these high spatiotemporal resolution tracking methods with causal intervention approaches can further elucidate the dynamic regulatory mechanisms of the LC-NE system in attentional processing, thereby providing a theoretical basis for interventions in attentional disorders.

Keywords: LC-NE, attention, alerting, orienting, executive control

Classification Number: B482

Attention, as a core cognitive mechanism for information selection and processing (Posner, 1980), has long been a focal point in cognitive science research. It determines not only how individuals effectively filter and allocate limited cognitive resources in their environment but also directly influences the efficiency of goal-directed behavior. Neurotransmitter systems are believed to play crucial roles in cognitive functions such as attention, alertness, and cognitive control (Aston-Jones & Cohen, 2005; Boyle et al., 2024; Ghosh & Maunsell, 2024; Pajkossy et al., 2018). Among these, the locus coeruleus-norepinephrine system (LC-NE), with its extensive neural projection network and norepinephrine (NE) release mechanisms, serves as a hub in the dynamic regulation of brain functional states and is considered one of the core neuromodulatory systems (Berridge et al., 2012; Dahl et al., 2022; Maness et al., 2022; Poe et al., 2020; Thiele & Bellgrove, 2018; Usher et al., 1999; Verguts & Notebaert, 2009).

Consistent evidence from rodents, non-human primates, and humans demonstrates that the LC-NE system plays a key role in attentional regulation (Aston-Jones & Cohen, 2005; Bari et al., 2020; Bouret & Sara, 2005; Dahl et al., 2020; Ghosh & Maunsell, 2024; Janitzky et al., 2015; McBurney-Lin et al., 2019; McGaughy et al., 2008; Unsworth & Robison, 2017). It is important to note that attention is not a unitary psychological process but rather comprises multiple interconnected yet functionally distinct subsystems. Classic attention theories posit that attention can be divided into three main subsystems: alerting, orienting, and executive control (Fan et al., 2002; Petersen & Posner, 2012). Although these subsystems exhibit relative independence in terms of function and neural basis (Fan et al., 2005), some studies have found interactions among them (MacLeod et al., 2010). While numerous studies have revealed that the LC-NE system is broadly involved in regulating each attentional subsystem (Bari et al., 2020; Bast et al., 2018; Gabay, Pertzov, et al., 2011; Geva et al., 2013; Ghosh & Maunsell, 2024; Grueschow et al., 2020, 2022; Unsworth & Robison, 2017), consensus on its specific mechanisms in attentional regulation has not yet been reached. In particular, how tonic and phasic firing patterns of locus coeruleus (LC) neurons function within different subsystems and their interrelationships remain lacking systematic elaboration. Meanwhile, existing theories also show certain divergences. For example, the "adaptive gain theory" emphasizes that LC achieves a balance between alertness and exploration through gain modulation, whereas the "network reset" theory highlights its triggering role in attentional shifting. Although each perspective has supporting evidence, they have not yet been integrated within a unified framework. Furthermore, generalizing findings from animal studies to human cognition and clinical applications still faces multiple challenges, such as cross-species differences, limited imaging resolution, and insufficient causal evidence. These challenges not only limit our in-depth understanding of the regulatory mechanisms of the LC-NE system in attentional processing but also constrain its potential application in interventions for attention-related disorders. Therefore, this article aims to comprehensively review the neurophysiological mechanisms of the LC-NE system in attentional regulation, summarize behavioral and neurophysiological indicators used to index LC-NE activity, and systematically examine the system's specific roles in different attentional subsystems and its potential impact on various attentional disorders, thereby providing a theoretical framework and methodological reference for future research.

1.1 LC-NE System and Attention-Related Neurophysiological Characteristics

The LC is a unique NE nucleus in vertebrates, located deep in the dorsal brainstem, and serves as the primary center for NE synthesis and release in the brain (Manger & Eschenko, 2021; Poe et al., 2020). LC neurons influence multiple key cortical and subcortical structures through extensive axonal projections (Berridge & Waterhouse, 2003; Ma et al., 2023; McBurney-Lin et al., 2019; Poe et al., 2020; Sara & Bouret, 2012), including the prefrontal cortex (PFC), anterior cingulate cortex (ACC), parietal cortex, thalamus, and amygdala (Berridge & Waterhouse, 2003; Poe et al., 2020). These brain regions are closely associated with critical processes such as attention maintenance and orienting (Bang et al., 2023; Katsuki & Constantinidis, 2012; Petersen & Posner, 2012; Sarrias-Arrabal et al., 2023), collectively forming the core anatomical basis for LC-NE system regulation of attentional processing.

During attentional regulation, the LC dynamically modulates neural activity in target brain areas by releasing NE and activating different receptor types, thereby playing a central role in maintaining selective attention, regulating arousal levels, and enabling flexible allocation of attentional resources. NE receptors primarily include three types: high-affinity α₂ receptors (more sensitive to NE, activated at relatively low NE levels), which mainly participate in inhibitory regulation by reducing neuronal background noise to enhance signal-to-noise ratio; and lower-affinity α₁ and β receptors (requiring higher NE concentrations for activation), which are typically associated with excitatory effects (Atzori et al., 2016; Zhang et al., 2023). In brain regions involved in attention regulation such as the PFC, different NE concentrations can selectively activate different receptor types: moderate NE levels preferentially activate high-affinity α₂ receptors, enhancing neuronal firing and thereby improving working memory performance and executive function (Arnsten, 2009; Ramos & Arnsten, 2007); whereas under high-stress or high-arousal states, elevated NE levels activate low-affinity α₁ and β receptors, inhibiting PFC neuronal discharge and impairing its function, ultimately leading to declines in attention and executive function (Arnsten, 2009; Ramos & Arnsten, 2007). In addition to receptor-mediated excitatory and inhibitory effects, NE can also modulate neuronal plasticity by enhancing synaptic transmission efficacy and reducing spontaneous firing frequency, thereby improving the response flexibility of neural networks (Berridge & Waterhouse, 2003; Woodward et al., 1979). In summary, the unique anatomical projections, receptor characteristics, and neuromodulatory mechanisms of the LC-NE system collectively constitute the physiological basis for its attention regulation.

1.2 LC-NE System Firing Patterns and Attention Regulation

LC neuronal firing activity manifests primarily in two modes: tonic and phasic patterns. The tonic mode reflects baseline activity and is mainly associated with overall alertness levels, task engagement, and behavioral flexibility; the phasic mode represents brief, high-frequency discharges in response to target stimuli or unexpected events and is considered a key neural mechanism for attentional focusing and selection (Unsworth & Robison, 2017). Electrophysiological studies in non-human primates have revealed significant functional distinctions between these two firing patterns in cognitive-behavioral regulation (Rajkowski et al., 1994).

The phasic pattern typically occurs when individuals encounter unexpected, salient, or task-relevant stimuli, exhibiting high temporal specificity. Brief, high-frequency neural discharges can enhance prioritized processing of target stimuli while suppressing responses to irrelevant information, thereby improving attentional selection efficiency (Aston-Jones & Cohen, 2005). Furthermore, the phasic pattern is closely associated with event-related potential (ERP) components such as the P3, providing electrophysiological evidence for the LC-NE system's role in rapid identification of "unexpected events" and behavioral updating (Nieuwenhuis et al., 2005). At the behavioral level, the phasic pattern facilitates rapid focusing and responding to critical signals, supporting target detection, motivation-driven behavior execution, and adaptive adjustment, representing an important mechanism through which the LC-NE system regulates task performance. In contrast, tonic firing levels are closely related to overall alertness states and exhibit a classic inverted-U-shaped modulation pattern. When LC neuronal tonic activity is too low, individuals show attentional dispersion and cannot maintain focus on current tasks, resulting in poor behavioral performance and lacking task-related phasic responses; when tonic activity is at moderate levels, phasic responses to target stimuli are enhanced, achieving optimal behavioral performance; when tonic activity is too high (e.g., under high stress or arousal), it may suppress phasic discharge responses, causing attentional resource dispersion and difficulty in goal maintenance, leading to behavioral performance decline (Chamberlain & Robbins, 2013; Unsworth & Robison, 2017).

This inverted-U relationship reflects the nonlinear modulation of cortical excitability by the LC-NE system and aligns closely with the classic Yerkes-Dodson law regarding the relationship between arousal and performance (Yerkes & Dodson, 1908). Based on these mechanisms, Aston-Jones and Cohen (2005) proposed the "adaptive gain theory." This theory suggests that the LC-NE system achieves dynamic balance between "exploitation" (utility-driven behavior) and "exploration" (environmental exploration) by modulating the degree to which cortical neurons respond to signals (or "signal gain"). When task utility is high, LC neurons maintain moderate tonic activity accompanied by strong phasic discharges to enhance processing efficiency of target information and suppress interference from irrelevant information, thereby improving goal-directed behavior efficiency. Conversely, when task utility declines, LC neurons tend to show increased tonic activity and decreased phasic activity, making individual attention more easily distracted and shifting toward exploring new cues or behaviors.

Building upon the clarification of these two firing patterns and their corresponding behavioral functions, current research has increasingly focused on their switching mechanisms and regulatory conditions. Existing evidence indicates that behavioral states (e.g., goal utility), task difficulty, and cognitive load changes can all influence the dynamic switching of LC neuronal firing patterns (Gabay, Pertzov, et al., 2011; Sara & Bouret, 2012). For example, the "network reset theory" posits that sudden salient stimuli can evoke synchronized phasic discharges in LC neurons, thereby interrupting current neural activity patterns and initiating new attentional states (Sara & Bouret, 2012). Unlike the adaptive gain theory's emphasis on how the LC-NE system modulates neural activity and responses through phasic and tonic modes, the network reset theory highlights the unique role of LC neurons in promoting neural network reorganization (a comparative summary of the two theories is presented in Table 1 [TABLE:1]). This theory suggests that phasic LC activation is not merely a response to stimuli but a key mechanism triggering network dynamic reorganization. By altering functional connectivity between different brain regions, the LC-NE system enables the brain to flexibly adjust attentional and behavioral strategies to cope with unexpected events (Bouret & Sara, 2005). In the model proposed by Bouret and Sara (2005), phasic and tonic LC activity coordinately support a flexible attention system. When tonic activity and overall NE release levels are low, it helps maintain task engagement when expecting target-relevant stimuli and prevents premature behavioral shifting; when tonic activity and NE release levels are elevated, it increases attentional dispersion and behavioral switching likelihood, reflecting a more exploratory mode. Additionally, Totah et al. (2021) further noted that phasic discharges are often accompanied by highly synchronized activity in LC neuronal populations, a process potentially regulated by the PFC-LC circuit. Future research could further explore the switching mechanisms between LC firing patterns and their relationship with PFC regulatory circuits.

In summary, LC-NE system regulation of attention does not stem from simple neural excitability enhancement but rather through dynamic coordination of tonic and phasic firing patterns to achieve fine-tuned modulation of cognitive system response states. This mechanism establishes a crucial neurophysiological foundation for individuals to maintain tasks and switch strategies in complex environments.

2.1 LC-NE System and Attention: Evidence from Pupil Dilation

Pupil dilation (PD) is a sensitive and stable physiological indicator for measuring arousal level and cognitive effort. Wang and Li (2024) noted in their review that pupillary responses are closely related to LC-NE system activity. Numerous pharmacological and neurophysiological studies further demonstrate that PD is closely associated with LC neuronal firing patterns (Beatty, 1982; Dragone et al., 2018; Gabay, Chica, et al., 2011; Unsworth & Robison, 2017) and can serve as an indirect indicator of LC-NE system activity (R. H. Hou et al., 2005; Joshi et al., 2016; Morad et al., 2000; Phillips et al., 2000; Varazzani et al., 2015). For instance, pharmacological studies have found that modafinil, a drug that increases central NE levels, enhances subjective alertness and induces PD, while clonidine, which reduces NE levels, decreases subjective alertness and causes pupil constriction (R. H. Hou et al., 2005). Animal electrophysiological studies have also found that PD is significantly positively correlated with LC firing frequency (Joshi et al., 2016; Rajkowski et al., 1994; Reimer et al., 2016; Varazzani et al., 2015), with noticeable pupil dilation observed approximately 300 ms after LC discharge. Notably, although other brain regions (e.g., thalamus) are also associated with pupillary changes, LC neuronal firing activity shows the most significant predictive effect on pupil changes (Joshi et al., 2016).

Human behavioral studies also provide evidence supporting the association between PD and LC neuronal activation levels during attentional guidance. For example, Dragone et al. (2018) found that high-predictability cues elicited stronger PD responses compared to low-predictability cues, suggesting that phasic LC discharge participates in attentional regulation. Moreover, baseline pupil size gradually decreased across trials, indicating a dynamic adjustment process of LC tonic activity during actual task performance. In other words, LC tonic activation is typically reflected in baseline pupil size, while event-evoked phasic activation is manifested through changes in PD. It is worth noting that PD may also be influenced by other neurotransmitter systems. For instance, while short-term PD changes are primarily related to the NE system, sustained PD during motor activity is more likely associated with sustained activation of the cholinergic system (Reimer et al., 2016). Therefore, PD can serve not only as an indicator of LC-NE system activity but also as a measure of other neural systems regulating bodily functions, providing an important perspective for investigating the coordinated regulation of arousal and attention by multiple neuromodulatory systems.

However, using PD as an indicator of LC-NE system activity has certain limitations. The primary issue is that pupil size is highly susceptible to task-irrelevant variables such as environmental brightness and blinking, which can weaken its validity as an indicator of LC-NE system activity (Gabay, Pertzov, et al., 2011; Mathôt et al., 2018). To reduce interference from irrelevant variables like brightness, researchers have proposed using contrast methods between task conditions to analyze pupillary responses. For example, Gabay and Pertzov et al. (2011) designed two tasks with identical visual attributes but different attentional loads (a simple localization task versus a complex discrimination task) and found that the complex task elicited more significant phasic PD compared to the simple task. Furthermore, if PD indeed reflects LC-NE system activity, its phasic changes should temporally correspond closely with behavioral responses. Based on this, the study further employed time-lock analysis anchored to behavioral responses to more accurately extract pupillary changes associated with LC-NE system activation during attentional processing. The results showed that significant phasic PD was only observed in the high-demand complex task. These findings not only support the feasibility of using PD as an indicator of LC-NE system activity in specific tasks but also highlight the flexibility of the LC-NE system in attentional regulation.

Notably, using PD as a valid indicator of LC-NE system activity requires two key prerequisites. First, LC neuronal activation should be primarily related to behavioral responses rather than being directly driven by stimulus presentation (Rajkowski et al., 2004). Second, changes in arousal state should be reflected through phasic pupillary changes time-locked to behavioral responses, not merely through alterations in baseline pupil size (Beatty, 1982). When these prerequisites are met, PD can serve as an effective non-invasive physiological indicator for reflecting the dynamic characteristics of the LC-NE system in attentional regulation.

2.2 LC-NE System and Attention: Evidence from Event-Related Potentials

ERP is a neurophysiological technique with high temporal resolution commonly used to investigate the brain's dynamic responses during attentional processing. ERP components are widely used as indirect neurophysiological indicators of LC-NE system activity when exploring its attentional regulatory mechanisms. Current research primarily focuses on the P3 and N2 components, which are considered closely related to LC-NE system function (Martín & René, 2012; Nieuwenhuis et al., 2005; Warren et al., 2011; Warren & Holroyd, 2012).

The P3 (also called P300) is an important ERP component regarded as a neurophysiological indicator reflecting the reallocation of attentional resources to novel or salient stimuli (Polich, 2007). Studies have found that damage to the LC region or its NE ascending pathways in both rodents and primates attenuates cortical P3 activity (Ehlers & Chaplin, 1992; Nieuwenhuis et al., 2005; Pineda et al., 1989), suggesting that the LC is a key modulatory source of the P3. Additionally, NE agonists such as clonidine reduce P3 amplitude in both humans (Halliday et al., 1994) and non-human primates (Swick et al., 1994), further supporting the close connection between P3 and the LC-NE system. Temporally, phasic LC neuronal discharge typically occurs approximately 150–200 ms after stimulus presentation, while NE-induced cortical modulatory effects occur 100–200 ms post-stimulus, which aligns closely with the classic P3 latency (Berridge & Waterhouse, 2003; Foote et al., 1983). Based on this, Nieuwenhuis et al. (2005) proposed the "LC-P3 theory," suggesting that the P3 reflects phasic enhancement of cortical neural responses triggered by NE release from the LC. Subsequently, Martín and René (2012) further noted that this enhancement is primarily manifested in the processing of task-relevant stimuli—when NE is released, the responsivity of target neurons in the brain is enhanced, which can further improve the signal-to-noise ratio of subsequent target neuron processing, enabling the brain to capture and process relevant information more efficiently. More direct evidence comes from Vazey et al. (2018), who used optogenetics to induce phasic discharge in rat LC neurons and observed ERP responses similar to human N1 and P3 components in the rat cortex, providing experimental evidence for a causal relationship between LC neuronal discharge and ERP components. Additionally, in cognitive control tasks, the NoGo-P3 is considered related to response inhibition. Research has found that at the individual level, PD indices reflecting LC-NE system activity can predict NoGo-P3 amplitude, suggesting that the LC-NE system also participates in regulating response inhibition processes (Chmielewski et al., 2016). Overall, the LC-P3 theory supports the core hypothesis of the adaptive gain theory at the electrophysiological level, namely that phasic LC discharge can enhance the responsivity of task-relevant neurons, thereby optimizing attention and cognitive control processes.

The N2 is another ERP component considered closely related to the LC-NE system, typically associated with conflict monitoring and inhibitory control. In classic psychological paradigms such as Go/NoGo and Flanker tasks, conflicting or incongruent stimuli usually elicit larger N2 amplitudes (Fong et al., 2018; Gajewski & Falkenstein, 2013; Nieuwenhuis et al., 2003). For example, in Go/NoGo tasks, individuals must suppress automatic response tendencies elicited by frequent Go trials, and therefore rare NoGo trials evoke more significant N2 components (Falkenstein et al., 1999; Kopp, Mattler, et al., 1996). Similarly, in Flanker tasks, distractor stimuli activate response options that conflict with the target, also leading to N2 enhancement (Kopp, Rist, et al., 1996). Although the N2 component is less commonly used to directly measure LC activity, recent research has begun exploring its relationship with the LC-NE system, particularly under high cognitive load and conflict situations where N2 may reflect early modulatory effects of the LC-NE system (Patel & Azzam, 2005). For instance, Warren et al. (2011) found in a face oddball task that N2 scalp distribution changes with task conditions, possibly reflecting differential involvement of various cortical regions under NE modulation. Based on this, Warren and Holroyd (2012) further revised the "LC-P3 theory," proposing that N2 may correspond to initial NE release during early LC neuronal discharge, while P3 reflects subsequent NE depletion. This theory naturally explains the temporal sequence relationship between N2 and P3 and emphasizes the critical role of the LC-NE system in generating both ERP components. Research by Hong et al. (2014) also supports this theory, finding that both N2 and P3 amplitudes correlate with baseline pupil size, suggesting both are closely related to LC function. Overall, ERP research provides important evidence for understanding the temporal characteristics of the LC-NE system during attentional processes. However, due to its limited spatial resolution, researchers have recently begun using functional magnetic resonance imaging (fMRI) to compensate for ERP's spatial localization limitations. For example, Walz et al. (2013) used combined EEG-fMRI and found functional coupling between brain activity during the N2 time window and midbrain region activity during the P3 phase, suggesting these regions may coordinately participate in attentional neuromodulation through the LC-NE system.

2.3 Comparison and Integration of LC-NE System Measurement Indicators

Current research on LC-NE system modulation of attention primarily uses PD and ERP components as main measurement indicators, with a few studies also incorporating fMRI to supplement spatial evidence. These three methods each have distinct advantages and limitations in temporal resolution, spatial resolution, and applicable scenarios: PD and ERP are better suited for revealing dynamic temporal processes, while fMRI can provide spatial localization and network-level evidence.

PD offers high temporal resolution for real-time tracking of LC-NE system dynamics and has been validated in both human and animal studies (Dragone et al., 2018; Joshi et al., 2016; Joshi & Gold, 2020; Reimer et al., 2016). PD is also widely applied in tasks requiring continuous tracking of arousal levels, attentional dynamics, and cognitive effort changes (Gabay, Pertzov, et al., 2011; Murphy et al., 2011, 2014). However, PD is susceptible to interference from non-task factors such as environmental brightness, blinking, and emotion, making its validity as an indirect indicator of LC-NE system activity in attentional regulation controversial (Joshi & Gold, 2020). ERP, on the other hand, can track the temporal characteristics of the LC-NE system in attentional processing with millisecond precision, particularly the P3 component's close relationship with phasic LC discharge (Murphy et al., 2011; Nieuwenhuis et al., 2005). This method is suitable for tasks involving target detection, inhibitory control, and conflict monitoring (Warren & Holroyd, 2012), but its low spatial resolution only allows indirect reflection of LC activity through scalp electrical signals, making precise localization difficult. In contrast, fMRI offers higher spatial resolution for observing functional connectivity with cortical and subcortical regions. Studies using resting-state and task-based fMRI have revealed network interactions between the LC and regions such as the PFC, ACC, thalamus, and amygdala (Liebe et al., 2020; Murphy et al., 2014). However, its limited temporal resolution typically requires combination with pupillometry or ERP to compensate, thereby achieving high spatiotemporal precision tracking of LC-NE activity.

2.4 Multimodal Measurement Evidence Strengthening the LC-NE System-Attention Relationship

Multimodal measurement provides a richer and more precise perspective for revealing the mechanisms of LC-NE system function in attention. Murphy et al. (2014) simultaneously recorded PD and fMRI signals and found significant correlations between PD and blood oxygen level-dependent signal changes in the LC region during both resting state and oddball tasks, further supporting the validity of PD as an indirect indicator of LC-NE system activity. Additionally, Ding et al. (2021) combined positron emission tomography (PET), fMRI, and norepinephrine transporter (NET) radioactive tracers to conduct multimodal imaging studies of LC-NE system function across different racial groups. The results showed that compared to other groups, African descent groups exhibited faster LC-NE system functional decline, suggesting they may face higher risks for attentional dysfunction. These findings not only demonstrate the methodological advantages of multimodal techniques in validating LC-NE system-attention relationships but also showcase their potential in revealing group differences and attention deficit disorders.

3.1 LC-NE Regulatory Mechanisms in Attentional Alerting

Attentional alerting refers to a state in which individuals proactively increase sensitivity and response readiness to upcoming stimuli before receiving external information (Petersen & Posner, 2012). Maintaining attentional alerting primarily depends on coordinated regulation by the right hemisphere frontoparietal network, thalamus, and LC-NE system. Neuroimaging studies have found that when individuals perform alerting or sustained attention tasks, right frontal and parietal regions are activated, suggesting this network plays a central role in maintaining alert states (Coull et al., 1996; Sturm & Willmes, 2001). Meanwhile, the thalamus, as an arousal regulation center, participates in phasic and tonic alerting regulation through coordination with frontoparietal cortex (Sturm & Willmes, 2001). Additionally, the LC-NE system influences various cognitive processes including visual attention by regulating overall arousal levels and setting baseline states for cortical activity through extensive neural projection networks (Euler et al., 1946). In spatial cueing tasks, researchers assess alerting effect strength by comparing reaction times between alerted and non-cued conditions and have found this effect is modulated by LC-NE system functional state (Fernandez-Duque & Posner, 1997), providing behavioral evidence for the LC-NE system's role in attentional alerting regulation.

The LC-NE system participates in dynamic regulation of attentional alerting by modulating NE release levels. Animal studies show that alarm stimuli can activate LC neurons and promote NE release, thereby enhancing alertness levels (Aston-Jones & Cohen, 2005); conversely, blocking the NE system significantly weakens the alerting effect of warning signals (Marrocco et al., 1994). Related pharmacological studies further support this mechanism—drugs that inhibit NE release (such as clonidine and dexmedetomidine) weaken attentional alerting effects, while drugs that enhance NE release amplify such effects (Petersen & Posner, 2012). Additionally, Coull et al.'s (1999) PET study found that administering α₂ receptor agonists at rest weakened functional connectivity between frontal lobe, thalamus, and visual cortex, but during attentional tasks, it significantly enhanced activity in the parietal cortex-centered attentional network, indicating that LC-NE system regulation of attentional states is highly context-dependent.

Beyond NE release level modulation, LC neuronal firing patterns also participate in attentional alerting regulation. Research has shown that LC firing patterns are closely related to attentional performance: both excessively high and low firing frequencies lead to attentional dispersion, while moderate frequencies typically correspond to optimal task performance (Aston-Jones et al., 1991). The adaptive gain theory posits that the appearance of task-relevant goals can induce phasic firing mode in LC neurons, triggering attentional alerting states that enhance processing of target stimuli and utilization of cognitive resources; when task utility remains consistently low, LC neurons tend to shift to tonic firing mode, maintaining responsiveness to all stimuli and prompting individuals to disengage from current tasks to explore other potentially valuable activities (Aston-Jones & Cohen, 2005). This mechanism supports dynamic balance between "task maintenance" and "strategy switching." Notably, transitions between LC firing patterns occur very rapidly, with phasic discharge activity attenuation observable within approximately 50–60 ms after stimulus onset (Foote et al., 1980). This rapid dynamic adjustment enables the LC-NE system to flexibly modulate sensitivity to external stimuli, optimizing attentional resource allocation and facilitating processing of task-relevant information.

3.2 LC-NE Regulatory Mechanisms in Attentional Orienting

Attentional orienting refers to the process of shifting attention from the current focus to a target stimulus that will be selected or attended to (Petersen & Posner, 2012). Numerous studies have shown that two key neural networks in the cerebral cortex jointly participate in attentional processing of external stimuli: the dorsal attention network (DAN) and the ventral attention network (VAN) (Corbetta & Shulman, 2002). The DAN is primarily associated with top-down attentional control (Chica et al., 2013), with core regions including the intraparietal sulcus (IPS), superior parietal lobule (SPL), and frontal eye field (FEF) (Corbetta et al., 2008). Neuroimaging studies show that when individuals need to focus attention on specific spatial locations based on cues, the DAN including FEF and IPS is significantly activated (Corbetta & Shulman, 2002). In contrast, the VAN primarily participates in bottom-up attentional shifting, with core regions including the temporoparietal junction (TPJ) and ventral frontal cortex (VFC) (Corbetta et al., 2008). When salient stimuli appear at non-cued locations, TPJ activation significantly increases, driving attention to shift from the previous focus to the new target (Corbetta et al., 2000; Corbetta & Shulman, 2002). Notably, the DAN and VAN are not independent but can dynamically switch under LC-NE system regulation according to task demands and environmental changes. According to the network reset theory, when salient stimuli appear, the LC-NE system can promote rapid attentional reorienting through phasic discharge activity, specifically by evoking signal transmission from TPJ and prompting attention to switch from the task-oriented DAN to the externally novel stimulus-sensitive VAN (Corbetta et al., 2008). Recent research further shows that during salient stimulus processing, when LC neuronal phasic activity increases, effective connectivity from the salience network (SN) to the DAN is enhanced, suggesting that the LC-NE system specifically regulates DAN functional integration through the SN, thereby promoting dynamic allocation of attentional resources (He et al., 2023). Additionally, Bouret and Richmond (2015) proposed that LC neuronal activity is related to the energy investment required for goal-directed behavior. Based on this, research has further applied this to attentional regulation in different contexts: when individuals process high-reward or target-relevant cues, LC-NE system activation increases, preferentially activating the DAN to support goal-directed attention; conversely, when processing low-reward or non-target cues, LC-NE system activation decreases, DAN activation reduces, and the VAN maintains sensitivity to external novel stimuli (Hofmeister & Sterpenich, 2015). These evidences collectively demonstrate that the LC-NE system achieves flexible allocation of attentional resources between goal-directed and stimulus-driven behaviors through specific regulation of the DAN and VAN, thereby maintaining adaptive behavior and task performance.

As an important regulatory component of VAN-mediated exogenous attention, the LC-NE system also deeply participates in specific regulation processes of exogenous attentional orienting through dynamic changes in firing patterns. In classic exogenous spatial cueing tasks, if a target appears at the cued location after a short stimulus onset asynchrony (SOA), individuals respond faster; conversely, when SOA is long (greater than 300 ms), responses are faster when targets appear at non-cued locations. This phenomenon is called "inhibition of return" (IOR) (Posner & Cohen, 1984), with the mechanism being suppression of reflexive attention to facilitate strategic attention deployment, thereby improving visual search efficiency (Okon-Singer et al., 2020). It should be noted that IOR onset time is influenced by task type: in more difficult discrimination tasks, IOR appears later, while in simple detection tasks, IOR appears earlier (Lupiáñez et al., 1997). This difference may be related to different firing patterns of the LC-NE system: in difficult tasks, LC neurons activate in phasic mode, allocating more attentional resources to target stimuli while suppressing attention to peripheral cues, thus delaying IOR onset; in simple tasks, LC neurons exhibit more tonic firing, reducing attentional resources allocated to targets, allowing peripheral cues as distractors to receive more processing and causing earlier IOR onset (Gabay, Pertzov, et al., 2011; Gabay & Henik, 2010). Additionally, external threat cues can also enhance LC-NE system activation and trigger stronger IOR effects, further emphasizing the important role of the LC-NE system in exogenous attention regulation (Okon-Singer et al., 2020).

Research from animal models also provides more direct causal evidence for revealing LC-NE system function in attentional orienting. For example, Janitzky et al. (2015) used optogenetics to temporarily inhibit mouse LC neuronal activity and found this manipulation severely disrupted flexible switching of attention between different dimensions, suggesting that LC-NE plays a critical role in regulating attentional orienting shifts. Similarly, Vazey et al. (2018) used optical stimulation to evoke phasic discharge activity in LC neurons and found this induced electrophysiological responses similar to human ERP N1 and P3 components in rat cortex. This rapid phasic discharge not only enhanced neural responses to stimuli in sensory cortex but also improved goal-directed information processing and attentional reorienting, further confirming the fine regulatory role of the LC-NE system in attentional orienting.

Despite substantial evidence showing LC-NE system involvement in attentional orienting, controversy remains regarding whether it directly regulates this process. One view suggests that LC-NE primarily modulates attentional alerting while the orienting process is dominated by the cholinergic system (Slater et al., 2022). For example, Ikeda et al. (2017) found that the NE agonist modafinil increased alerting activation levels in occipital regions but did not significantly affect orienting responses. However, other perspectives propose that the LC-NE system has common regulatory effects on both alerting and orienting: as a core mechanism for regulating neural activity gain, LC-NE can act on continuously changing states of alertness, orienting, and task-related attentional processes (Aston-Jones & Cohen, 2005; Bouret & Sara, 2005; Sara & Bouret, 2012). Geva et al. (2013) used PD as an LC-NE system activity indicator and found that temporal cues elicited larger early PD components compared to no-cue conditions, while spatially informative double cues further accelerated this component's activation, suggesting it may integrate neural processing of alerting and orienting. Bast et al. (2018) also noted that phasic LC neuronal activity can simultaneously regulate both alerting and orienting attentional subsystems. More direct causal evidence comes from Ghosh and Maunsell's (2024) non-human primate electrophysiological study, which found that LC neurons only discharged when contralateral visual stimuli were effectively attended, and this discharge was closely related to enhanced perceptual sensitivity. Importantly, optogenetic activation of LC neurons significantly improved monkeys' detection ability for contralateral stimuli, demonstrating that the LC-NE system not only regulates overall arousal levels but also possesses spatially specific attentional regulation functions, providing strong support for LC-NE system simultaneous modulation of both alerting and orienting.

3.3 LC-NE Regulatory Mechanisms in Executive Control

Executive control of attention refers to the ability to monitor and resolve conflicts between expectations, stimuli, and responses (Petersen & Posner, 2012). This process relies on the coordinated action of attentional and inhibitory processes. The attentional process refers to the ability to effectively focus or shift attention to task-relevant information sources (Miyake et al., 2000), while the inhibitory process helps individuals shield against interference from irrelevant stimuli, with its core mechanism being the suppression of automatic or impulsive behavioral responses to achieve cognitive control (Friedman & Miyake, 2004). These highly interactive and mutually constraining cognitive functions are not only crucial for maintaining goal-directed behavior but also enable individuals to flexibly respond to changing environmental demands. Neuroimaging research has identified the ACC and PFC within the frontoparietal network as important nodes in the attentional control network, with the ACC primarily responsible for conflict monitoring and the PFC dominating cognitive control execution (Kerns et al., 2004). The LC-NE system plays a vital role in regulating this attentional control demand-based neural network (Cohen et al., 2004). Specifically, the LC dynamically modulates PFC neural activity levels through widespread NE release, thereby regulating attentional control and other higher-order cognitive functions (Aston-Jones & Cohen, 2005; Sara & Bouret, 2012).

Empirical studies show that NE-related drugs can enhance PFC functional activity, thereby improving performance in attention and response inhibition tasks (Chamberlain et al., 2009; Nagashima et al., 2014). Interestingly, LC-NE system modulation of attentional control shows an inverted-U-shaped pattern: moderate NE levels are most beneficial for attentional control, while excessively high or low NE levels lead to attentional maintenance failure (Aston-Jones et al., 1999; Ramos & Arnsten, 2007). Based on this mechanism, Unsworth and Robison (2017) proposed that tonic activity levels of the LC-NE system play a decisive role in attentional control systems during task execution. Only when tonic NE levels are in the moderate range can LC neurons generate effective phasic discharge responses to appropriately modulate PFC activation states and achieve attentional resource allocation for goal-directed processing. Robison et al. (2023) further confirmed this hypothesis, finding stable associations between phasic LC discharge responses and individual attentional control abilities, supporting the central role of the LC-NE system in attentional regulation.

At the behavioral regulation level, NE not only enhances attention but also effectively inhibits impulsive responses—that is, suppresses driving effects from irrelevant or interfering stimuli. Both animal and human studies provide supporting evidence. For example, Bari et al. (2020) used optogenetics to modulate LC neuronal activity in mice and found that activating the LC-NE system enhanced goal-directed attention and reduced impulsive responses, while inhibiting LC neuronal activity led to attentional dispersion and increased impulsive responses. Similar results have been observed in human studies, where pharmacological intervention in NE reuptake processes effectively improved individuals' response inhibition abilities (Chamberlain et al., 2006). Functional neuroimaging research has further revealed functional interactions between the LC-NE system and cognitive control networks, showing significant functional connectivity between LC activation patterns and regions including the dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), dorsal parietal lobe (DPL), motor and visual areas, suggesting the LC-NE system plays a key regulatory role in cognitive conflict resolution (Köhler et al., 2016). Additionally, Grueschow et al. (2020) found in a response conflict task that response time changes in conflict trials were highly correlated with functional coupling strength between the conflict monitoring region—the dorsomedial prefrontal cortex (DMPFC)—and the LC-NE system, with stronger coupling associated with more efficient conflict resolution. Animal tracing studies also support the existence of structural and functional connections between the DMPFC and LC-NE system (Chandler, Gao, et al., 2014; Chandler, Waterhouse, et al., 2014). Furthermore, Grueschow et al. (2022) found in an emotional Stroop task that functional coupling between the LC-NE system and frontoparietal cortex as well as parts of the striatum was significantly enhanced during conflict trials, with coupling strength positively correlated with individual conflict resolution efficiency. These evidences indicate that dynamic interactions between the LC-NE system and cognitive control networks play a central regulatory role in goal-directed behavior and response inhibition.

As mentioned previously, PD is an important physiological indicator of LC-NE system activity. Building on this, research has further found that PD not only reflects overall attentional state but also systematically reveals the regulation processes of the three attentional subsystems—alerting, orienting, and executive control (see Table 2 [TABLE:2]) (Geva et al., 2013; Joshi et al., 2016). At the attentional alerting level, high alertness is typically accompanied by larger and more stable baseline pupil diameter, while fatigue or low alertness states are characterized by reduced baseline pupil diameter and increased fluctuations (R. H. Hou et al., 2005; Morad et al., 2000). In sustained attention tasks, individuals' baseline pupil diameter and task-evoked pupillary responses gradually decline over time, reflecting attenuation of attentional alerting levels (Beatty, 1982; Fried et al., 2014; Unsworth & Robison, 2016). The adaptive gain theory also suggests that when individuals are in low arousal and low tension states, pupil diameter is small; under high arousal, pupil diameter increases significantly; and optimal attentional performance corresponds to moderate pupil diameter levels, reflecting phasic LC activation (Aston-Jones & Cohen, 2005). Additionally, PD is highly coupled with α-β band desynchronization in EEG, suggesting both may depend on NE release mechanisms. Meanwhile, individuals' PD response intensity to fearful stimuli can effectively predict their attentional task performance, with individuals showing stronger PD responses typically achieving better performance (Dahl et al., 2020), further supporting the role of the LC-NE system in attention and alerting regulation. In spatial orienting tasks, PD is also considered an important indicator of LC-NE system activity. For example, Gabay and Pertzov et al. (2011) found that PD is highly sensitive to task processing demands: in difficult tasks, PD shows response-locked phasic characteristics corresponding to phasic LC discharge, while in simple tasks, PD changes are more similar to baseline fluctuations associated with tonic discharge. This demonstrates that LC-NE system regulation of attentional orienting can also be reflected through PD and shares similar neural regulatory mechanisms with alerting attention. Furthermore, at the executive control level, research shows that executive control processes are accompanied by significant late PD responses, with amplitude increasing with conflict level (Geva et al., 2013), suggesting executive control is also closely related to PD triggered by LC activation. In summary, PD is not only a sensitive indicator of LC-NE system activity but can also systematically reflect the dynamic regulatory characteristics of the three major attentional subsystems: alerting, orienting, and executive control.

4.1 LC-NE and ADHD

Attention-deficit/hyperactivity disorder (ADHD) is a common childhood neurocognitive disorder characterized by inattention, hyperactivity, and impulsive behavior (Gawrilow et al., 2014). Although the underlying pathophysiological mechanisms of ADHD are not fully understood, research indicates that NE plays a crucial role in ADHD development (Huang et al., 2022; Liao et al., 2019).

Molecular and neuroimaging studies show that individuals with ADHD exhibit abnormalities in NE signaling function (Liao et al., 2019; Sigurdardottir et al., 2021), typically accompanied by reduced activity in brain regions related to attentional processing, with PFC abnormalities being most prominent (B. A. Anderson, 2021). As one of the most extensively affected brain regions in ADHD, PFC dysfunction is considered the core neural basis for attentional control deficits in ADHD individuals (Arnsten, 2009). Animal studies provide further experimental evidence for this mechanism. Research found that optogenetic inhibition of LC projections to the PFC in mice led to significantly increased attentional dispersion and impulsive behavior, suggesting this pathway has important effects on executive control function (Bari et al., 2020). These findings collectively reveal the critical role of the LC-NE system in frontoparietal network regulation and provide important empirical support for understanding the neural mechanisms of ADHD-related symptoms. Building on this, clinical research further considers the LC-NE system an important target for pharmacological intervention. The NET is considered one of the key targets for ADHD medication (Vanicek et al., 2014). Drugs such as methylphenidate (MPH) can block NE reuptake by inhibiting NET activity, thereby improving NE neurotransmission efficiency in the PFC region (Hannestad et al., 2010) and subsequently enhancing attentional function and behavioral control. Related studies show that NET inhibitors have good efficacy in alleviating core ADHD symptoms (Angyal et al., 2018; Huang et al., 2022). Zhang et al. (2023) noted in their review that the LC-NE system not only plays an important role in attentional regulation but also serves as a key target for treating attentional dysfunction. In summary, the LC-NE system plays a critical role in attentional deficits and impulse control disorders in ADHD by regulating prefrontal function and related neural network activity. Its functional imbalance not only provides support for revealing the neurophysiological basis of ADHD but also offers an important target direction for precise pharmacological intervention.

4.2 LC-NE and ASD

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by core deficits in social communication (Dawson et al., 2012), often showing abnormal attentional processing, particularly reduced selective attention to social stimuli (Bast et al., 2018). Specific manifestations include weakened phasic alerting abilities (Orekhova & Stroganova, 2014) and impaired attentional orienting function (Jaworski & Eigsti, 2017).

Increasing research suggests the LC-NE system plays an important role in ASD pathophysiology. Studies indicate that the LC-NE system may participate in broader pathophysiological regulation in ASD (London, 2018), and its functional abnormalities may directly affect attentional processing performance in ASD individuals (Bast et al., 2018). Pupillary changes are considered peripheral physiological indicators of LC-NE system activity, highly coupled during attentional regulation (Wang & Li, 2024). Research has shown that atypical pupillary response patterns in children with ASD reflect LC-NE system functional abnormalities (W. Hou et al., 2024). Specifically, in resting states, children with ASD exhibit significantly larger pupil diameters than typically developing children (C. J. Anderson & Colombo, 2009; W. Hou et al., 2024; Keehn et al., 2021; Kim et al., 2022), suggesting their LC is in a state of sustained hyperactivation, which may affect environmental information filtering and effective allocation of attentional resources. In task states, attentional disengagement ability is significantly reduced in children with ASD, and disengagement speed is negatively correlated with resting pupil diameter (Keehn et al., 2021), further revealing potential links between sustained hyperactivation of the LC-NE system and impaired attentional regulation.

Research has found that individuals with ASD show clear deficits in attentional processing (Hames et al., 2016; Landry & Parker, 2013; Mutreja et al., 2016). For example, in tasks requiring attentional orienting, they show longer reaction times (Mutreja et al., 2016) and lower accuracy (Hames et al., 2016). A meta-analysis also confirmed that ASD individuals across age stages show moderate effect size orienting attention deficits (Landry & Parker, 2013). Neuroimaging studies have found abnormal functional connectivity between the salience network and other attention systems in children with ASD during resting state (Green et al., 2016), suggesting the LC-NE system may fail to effectively coordinate dynamic allocation of attentional resources. In summary, LC-NE system functional abnormalities may be key to attentional processing deficits in ASD individuals. With the development of neurotechnologies such as pupillometry and functional imaging, LC-NE system dysfunction is expected to become an important biomarker for identifying ASD neural phenotypes and provide potential neuromodulation targets for precision intervention strategies.

4.3 LC-NE and Anxiety and Depressive Disorders

Anxiety and depressive disorders are the most common types of mood disorders, both exhibiting varying degrees of attentional control function impairment. According to attentional control theory, anxiety weakens individuals' top-down attentional control and reduces attentional switching flexibility (Eysenck et al., 2007). Research has found that both children and adults with anxiety disorders show attentional control deficits (Mogg et al., 2015; Pacheco-Unguetti et al., 2011), while major depressive disorder (MDD) patients tend to persistently attend to negative information (Rudich-Strassler et al., 2022). These abnormal attentional patterns are believed to be closely related to hyperactivation of the LC-NE system (Zhang et al., 2023). Animal studies provide direct evidence for this hypothesis. For example, McCall et al. (2015) used optogenetics to activate endogenous projections from corticotropin-releasing hormone neurons in the amygdala to the LC, which induced tonic discharge in LC neurons accompanied by significant anxiety-like behavior. Subsequent research further found that activating LC-to-amygdala NE projection pathways also enhanced amygdala neural activity and triggered anxiety responses (McCall et al., 2017). Additionally, threatening stimuli can directly evoke LC neuronal discharge (Morris et al., 2020), and under stress states, high-frequency tonic discharge in LC neurons releases large amounts of NE, overactivating α₁ and β receptors and inhibiting PFC function (Birnbaum et al., 1999; Ramos et al., 2005), thereby exacerbating attentional dispersion and impulse control deficits (Arnsten et al., 2007). This series of findings collectively reveals that the LC-NE system may constitute the neural basis for attentional dysfunction in mood disorders. Clinically, NE reuptake inhibitors (such as reboxetine) can effectively alleviate anxiety, fear anticipation, and depressive symptoms by enhancing NE synaptic transmission function (Montgomery, 1997; Versiani et al., 2002), further confirming the rationality of the LC-NE system as a drug target for mood disorders. In summary, the LC-NE system plays a key role in attentional control deficits caused by mood disorders by regulating neural activity in the PFC and amygdala, providing important support for understanding the neurobiological mechanisms of mood disorders and developing targeted pharmacological interventions.

5 Summary and Outlook

The LC-NE system, as a major neuromodulatory center in the brain, plays a critical role in attentional regulation through its extensive neural projections, diverse receptor regulatory mechanisms, and flexible firing patterns. This system not only participates in regulating multiple attentional subsystems including alerting, orienting, and executive control, but its functional abnormalities are also associated with attentional disorders such as ADHD and ASD, and it may become an effective neural target for intervening in various attentional disorders. The application of non-invasive physiological indicators (such as pupil dilation PD and event-related potentials ERP) has already provided evidential support for revealing the mechanisms of LC-NE system regulation of attention, and the development of multimodal measurement techniques has opened new opportunities for understanding LC-NE system function. Despite significant progress in recent research on LC-NE system regulation of attention, several challenges remain, and future research urgently needs to deepen in the following aspects:

First, current indirect indicators used to assess LC-NE system activity (such as PD and ERP) still have controversial reliability and specificity. Taking PD as an example, its changes are regulated not only by the LC-NE system but also influenced by multiple neurotransmitter systems including acetylcholine and serotonin (Cazettes et al., 2021; Reimer et al., 2016), limiting its explanatory power as a specific functional indicator of LC-NE. Furthermore, Megemont et al. (2022) found in mouse studies that PD is highly correlated with LC discharge activity only during events with significantly increased amplitude and is affected by brain state fluctuations. This suggests that single indicators have limitations in reflecting LC-NE system activity, and future research urgently needs to cross-validate multiple neural and physiological indicators including PD and ERP components, using multimodal fusion modeling to replace single assessment approaches and improve the sensitivity and specificity of LC-NE system activity representation. Notably, despite these limitations, methods such as pupillometry and ERP still maintain the advantage of millisecond-level temporal resolution, enabling effective capture of rapid dynamic regulation of attentional processes by the LC-NE system. However, temporal advantages alone cannot solve spatial localization challenges. Due to the small volume and deep brainstem location of the LC, conventional 3T fMRI cannot achieve precise imaging of its activity. Future research could utilize ultra-high-field 7T fMRI (Berger et al., 2023; Koshmanova et al., 2023) to improve spatial resolution, combined with the temporal resolution advantages of pupillometry and ERP, to achieve high spatiotemporal precision tracking of LC-NE in attentional regulation. Additionally, under clinically indicated conditions, intracranial electroencephalography (iEEG) technology, which possesses both millisecond-level temporal and spatial resolution, could be used to reveal the regulatory effects of the LC-NE system on attentional network nodes such as the PFC, parietal cortex, and TPJ.

Second, although observational studies have revealed correlational features between LC-NE activity and attentional performance, the lack of systematic intervention studies prevents clear identification of causal mechanisms of LC-NE in attentional regulation. Future research could combine pharmacological stimulation, transcranial magnetic stimulation (TMS), and transcranial electrical stimulation (tES) to reveal the neural mechanisms of LC-NE system regulation of attention from a causal perspective. Additionally, deep brain stimulation (DBS) could serve as an invasive causal intervention method, acting on key network nodes highly coupled with the LC-NE system in clinically indicated individuals to provide critical evidence for clarifying its causal role in attentional regulation. Furthermore, combining these neuromodulation methods with observational indicators such as pupillometry, ERP, and fMRI signals can achieve complementarity between causal manipulation and dynamic recording, thereby more comprehensively revealing the functional characteristics of the LC-NE system during attentional regulation.

Finally, the functional connectivity mechanisms between the LC and multiple key regions in attentional networks (such as PFC, parietal cortex, TPJ, etc.) require further investigation. Although existing research has revealed interaction patterns between the LC and attentional networks in subsystems such as alerting, orienting, and executive control through animal models (Bari et al., 2020; Ghosh & Maunsell, 2024; Janitzky et al., 2015; Marrocco et al., 1994), dynamic functional connectivity in human tasks still lacks systematic research support. Additionally, the LC-NE system may have functional differences across different age stages—for example, its supportive role in attention development during childhood and adolescence and its potential association with attention decline in elderly populations—making this developmental perspective worthy of further exploration. Meanwhile, emerging computational modeling frameworks (such as predictive coding and gain control frameworks) provide new theoretical tools for explaining the dynamic roles of LC-NE in different task contexts and are expected to combine with empirical research to promote the establishment of unified mechanism models. Overall, deepening our understanding of the LC-NE system's role in attention will not only help build more complete models of attentional regulation neural mechanisms but also provide more precise pathways and theoretical foundations for interventions in attentional disorders.

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