Attention Networks: Alerting, Orienting, and Executive Control

Author: Angela Bogdanova · Published: October 16, 2026 · Editorial Policy

Research cluster: Attention, Perception & Cognitive Control · Written by Artificial Sapiens

Attention is the coordinated regulation of readiness, selection, and goal-directed behavior. One influential framework in cognitive psychology distinguishes three functional attention networks: alerting, which prepares an organism to respond; orienting, which prioritizes information from a location or source; and executive control, which helps resolve competition among responses and keep behavior aligned with current goals. These functions can be studied separately with carefully designed experimental contrasts, even though their operations interact in an active brain. The framework grows out of the attention-system research of Posner and Petersen and the Attention Network Test developed by Fan and colleagues. Posner & Petersen, 1990; Fan et al., 2002; Petersen & Posner, 2012.

These networks help explain an everyday sequence: a sudden signal prepares a person for an event, a spatial cue guides processing toward the relevant place, and an incompatible distractor creates a conflict that must be resolved before a response. Each stage changes how information becomes available for action. The framework supplies a research vocabulary, experimental predictions, and a way to compare attentional operations across tasks. It does not reduce everyday concentration to three fixed traits, and an attention-network score is a laboratory estimate rather than a medical diagnosis.

What Are Attention Networks?

An attention network is a functionally organized system that contributes to a distinguishable operation of attention. In the Posner–Petersen tradition, a network is identified through converging patterns of behavior, task manipulations, and biological research. The term does not imply that every function occupies one isolated brain region. Anatomical systems overlap, interact, and reorganize as task demands change. The 2012 reassessment of the framework recognized additional control systems and a more differentiated architecture than the initial taxonomy suggested. Petersen & Posner, 2012.

The central distinction is functional. Alerting regulates readiness over time. Orienting selects where or to what information processing is preferentially allocated. Executive attention supports goal-relevant selection when competing stimulus features, habitual reactions, or responses are in conflict. These operations are often engaged together: a warning signal changes readiness while a location cue guides selection, and a conflicting response demands additional control. Psychological experiments attempt to distinguish their contributions without assuming complete independence. Fan et al., 2002; Callejas et al., 2005.

The Historical Development of the Three-Network Framework

Classic experimental work showed that people can shift the priority of processing to a spatial location without moving their eyes, and that attention has identifiable costs and benefits in reaction time. Posner and Petersen's 1990 synthesis integrated such cognitive findings with neurological evidence, establishing attention as a system with specialized operations. Alertness, selection, and executive attention subsequently became the dominant three-part vocabulary for this research tradition. Posner & Petersen, 1990.

In 2002, Fan, McCandliss, Sommer, Raz, and Posner introduced the Attention Network Test (ANT), combining warning cues, spatial cues, and a flanker conflict task into a single experimental procedure. This made it possible to estimate three attentional contrasts during one testing session. The original study established the test's feasibility and reported relatively separable scores in its sample, initiating a substantial literature on the framework's measurement properties, applications, and variants. Fan et al., 2002.

Later work revised the initial picture in two directions. Cognitive experiments demonstrated that network effects can depend on one another, while neuroscience distinguished additional systems involved in maintaining task sets, orienting voluntarily, detecting salient events, and modifying ongoing behavior. Almeida, Faria-Jr., and Klein traced the evolution of ANT variants and the methodological choices behind them. The contemporary concept is therefore a mature and revisable experimental framework rather than a final three-part map of the brain. Callejas et al., 2005; Almeida et al., 2021; Petersen & Posner, 2012.

Alerting Network: Preparing to Detect and Respond

Alerting refers to achieving and maintaining a state of readiness for a potentially important event. Experimental psychology distinguishes transient increases in readiness, often called phasic alerting, from more sustained readiness across an interval, often called tonic alertness or vigilance in the relevant research contexts. A warning signal before an unpredictable target may shorten reaction time because it makes the imminent event more expected. Sustained attention, however, is shaped by the duration, monotony, and temporal demands of a task. These related phenomena should be studied with procedures appropriate to the particular question. Petersen & Posner, 2012.

Phasic alerting and temporal preparation

Imagine watching a screen for an arrow that will appear soon. On some trials, a brief cue indicates that an arrow is approaching without revealing where it will appear. Participants typically respond more quickly in warned than in unwarned trials. The critical psychological manipulation is the presence of temporal information. The participant can prepare to respond even without selecting a particular location. An ANT alerting contrast captures one consequence of that manipulation. Fan et al., 2002.

Alerting is influenced by temporal expectation, the cue–target interval, and the nature of a warning signal. Faster responding can reflect preparation and changes in decision criteria as well as changes in perceptual processing. Thus, an alerting benefit should be interpreted as a task-dependent behavioral effect, with its mechanism assessed through the design and related evidence. Almeida et al., 2021.

Sustained alertness and vigilance

Monitoring an infrequent signal over many minutes requires maintaining readiness while events are rare or repetitive. Researchers may measure misses, false alarms, reaction-time variability, and performance across time-on-task. This sustained form of performance is associated with the broad alertness system, but an ANT warning benefit and a long-duration vigilance task measure different aspects of behavior. The distinction matters when interpreting fatigue or concentration concerns: a person can respond strongly to immediate warnings while struggling with a long, uneventful monitoring task. Petersen & Posner, 2012.

Biological correlates of alerting

The research framework associates alerting with brainstem and widespread modulatory systems, including noradrenergic signaling, alongside distributed cortical activity. These biological accounts explain why preparedness affects many processing stages. They remain models of distributed function: neurotransmitter associations and imaging findings do not establish a simple one-to-one mapping from one psychological score to one neural location. Petersen & Posner, 2012.

Orienting Network: Selecting Information in Space and Beyond

Orienting is the prioritization of information from a location, object, or feature. Its classic experimental demonstration is spatial cueing: a cue precedes a target, and behavior changes according to whether the cue correctly indicates the target's location. Orienting can involve overt movements of eyes or head, yet covert attention allows selection to change even when gaze remains fixed. The resulting benefits and costs have been foundational for theories of selective attention. Posner & Petersen, 1990.

Endogenous and exogenous orienting

A symbolic arrow can instruct a participant where to direct attention. This is commonly used to study endogenous, goal-guided orienting. A sudden peripheral onset can attract attention through a more stimulus-driven route, often studied as exogenous orienting. Their timing, dependence on task instructions, and susceptibility to distraction differ, although the two modes interact with current goals. The categories describe experimental mechanisms, not absolute divisions into voluntary and involuntary behavior. Corbetta & Shulman, 2002.

Engagement, disengagement, and shifting

Orienting includes moving priority from an initially attended source toward a new target. A researcher can vary cue validity and cue–target timing to distinguish the benefit of selecting the expected location from the cost of reorienting away from an invalid location. These differences depend on the specific task. A simple orienting score that compares spatial and central cues does not automatically distinguish all of these components. Almeida et al., 2021.

Spatial selection is one part of orienting

Attentional selection can favor objects, features, sensory modalities, or task-relevant streams. The classical ANT emphasizes spatial cueing, because it creates a tractable experimental contrast. Findings about that contrast should therefore be described as evidence concerning the tested orienting operation, not as a complete assessment of every form of selective attention. Related theories of top-down and stimulus-driven attention offer a wider account of how goals and unexpected events compete for processing priority. Corbetta & Shulman, 2002.

Executive Attention: Resolving Conflict and Maintaining Goals

Executive attention is the coordination of processing when an intended action competes with distracting or incompatible information. It becomes particularly visible in tasks that require a person to ignore misleading response tendencies, select a relevant stimulus dimension, or sustain an instructed rule despite interference. In the ANT, executive attention is usually operationalized through conflict produced by flanking arrows that agree or disagree with the target arrow. Fan et al., 2002.

The flanker conflict effect

A participant must identify the direction of a central arrow. When nearby arrows indicate the same direction, responses are typically faster. When flankers indicate the opposite direction, they activate a competing response, often increasing reaction time and error risk. The difference between incongruent and congruent trials is a behavioral conflict effect. It informs the study of executive attention because the correct response requires prioritizing the central target over competing response information. Fan et al., 2002.

A conflict cost can arise from multiple processes: how quickly the target is encoded, how strongly flankers are processed, whether response competition develops, and how the participant adjusts strategy. It therefore should not be presented as a pure, context-free quantity called “willpower” or a direct measure of one person's self-control. Researchers examine conflict adaptation, speed–accuracy tradeoffs, and task parameters to refine the interpretation. MacLeod et al., 2010.

Executive attention and executive functions

Executive control is also discussed under broader constructs such as inhibitory control, cognitive flexibility, working-memory updating, and goal maintenance. These constructs overlap in ordinary language and may correlate experimentally, but the ANT's flanker contrast represents one specific kind of interference control. It is narrower than an assessment of every executive function. The meaning of a task score is determined by the response rule, the conflict manipulation, and the evidence for its validity. Petersen & Posner, 2012; MacLeod et al., 2010.

Conflict control is distributed

Executive attention has been associated with frontal and cingulate systems and with multiple control networks. Contemporary neuroscientific accounts distinguish mechanisms involved in maintaining stable task settings from those supporting adaptive changes in control. These findings refine the original three-network framework; anatomical details are best treated as convergent evidence for psychological operations rather than as labels to apply to an individual's test result. Petersen & Posner, 2012.

The Attention Network Test: Experimental Design

The original Attention Network Test combines a reaction-time task with two independently varied sources of information. First, a cue can tell the participant when a target is likely to appear or where it will appear. Second, arrows surrounding the target can create agreement or conflict. Participants typically indicate whether the central arrow points left or right while response time and accuracy are recorded. Combining cue conditions with flanker conditions permits comparisons associated with alerting, orienting, and conflict control in a compact design. Fan et al., 2002.

Cue conditions and what they manipulate

No-cue trials provide a comparison for warning effects. A central cue signals that the target is approaching, without revealing its location. A double cue supplies temporal warning information at the potential target positions without indicating the correct position. A spatial cue identifies the likely target location. Since versions vary, a published study must report its cue definitions, timing, cue validity, task duration, and scoring rules. Otherwise similarly named outcomes may represent different psychological contrasts. Fan et al., 2002; Almeida et al., 2021.

Flanker conditions and response competition

Congruent flankers share the central arrow's direction, whereas incongruent flankers indicate the opposite direction. Neutral flankers or a neutral baseline may also be included. Incongruent trials generally demand more conflict resolution because irrelevant directional signals compete with the target response. The exact size of the effect depends on stimulus spacing, timing, response mapping, and practice. Fan et al., 2002.

Standard network contrasts

In the conventional reaction-time scoring scheme, alerting is estimated as mean reaction time on no-cue trials minus mean reaction time on double-cue trials. Orienting is commonly estimated as mean reaction time with a center cue minus mean reaction time with a spatial cue. Executive conflict is estimated as mean reaction time on incongruent-flanker trials minus mean reaction time on congruent-flanker trials. Positive values usually mean that the warning or spatial cue provided a speed benefit, or that incongruent conflict imposed an additional cost. Each number is a subtraction between experimental conditions, and exact scoring can differ in alternative ANT versions. Fan et al., 2002; Almeida et al., 2021.

For an illustrative calculation, if mean no-cue reaction time were 560 milliseconds and double-cue reaction time 520 milliseconds, the alerting benefit would be 40 milliseconds. If the center-cue mean were 535 milliseconds and spatial-cue mean 500 milliseconds, the orienting benefit would be 35 milliseconds. If congruent responses averaged 505 milliseconds and incongruent responses 575 milliseconds, the conflict cost would be 70 milliseconds. These numbers are hypothetical examples, not normative values or diagnostic cutoffs. A difference score must be interpreted together with accuracy, response variability, and the testing procedure.

Reaction time, accuracy, and speed–accuracy tradeoffs

A shorter response time may reflect better preparation or selection, but it can also result from responding less cautiously. If accuracy declines, a purported improvement in attention might instead represent a speed–accuracy tradeoff. Sound analysis therefore considers both measures, examines excluded and anticipatory trials, specifies data trimming procedures, and reports participant and trial-level uncertainty. This is especially important for developmental and clinical comparisons in which processing speed, motor response, or task comprehension may differ. MacLeod et al., 2010; Arora et al., 2020.

Can the Three Attention Networks Operate Independently?

The three categories can be experimentally distinguished, but independence has several meanings. Statistical independence of three participant scores is not the same as independence of the psychological processes generating each response, and neither is the same as separation into nonoverlapping biological circuits. The original ANT provided evidence for relative separability under a particular design. Subsequent work established interactions, showing how one operation changes the observed expression of another. Fan et al., 2002; Callejas et al., 2005.

For example, warning signals may change the size of an orienting benefit, and informative spatial cues may alter the extent of conflict from distracting flankers. Callejas and colleagues experimentally documented modulations among alerting, orienting, and executive control. Xuan and colleagues later examined interactions using a revised ANT and functional imaging, finding distributed activation related to combined attentional operations. These studies support a dynamic system in which readiness, selection, and response control mutually constrain performance. Callejas et al., 2005; Xuan et al., 2016.

An experimental interaction can depend on trial arrangement, warning modality, cue validity, and analysis choices. Researchers should therefore describe an interaction precisely rather than inferring a universal sequence in which one network always dominates another. The most defensible interpretation is that functionally distinguishable attentional operations participate in an interconnected system whose organization depends on task demands. Almeida et al., 2021.

Three Attention Networks and Other Maps of Brain Attention

The alerting–orienting–executive framework is frequently compared with the dorsal and ventral attention systems emphasized in cognitive neuroscience. The dorsal frontoparietal system has been associated with goal-directed allocation of attention, whereas a largely right-lateralized ventral system has been associated with detecting behaviorally relevant events and interrupting or reorienting ongoing processing. Those systems were derived through a different combination of behavioral and imaging questions, and they do not correspond one-to-one with the three ANT subtractions. Corbetta & Shulman, 2002.

Similarly, contemporary distinctions among frontoparietal control, cingulo-opercular, and other systems refine the vocabulary of attention and control. Different research programs carve behavior at different scales: an experimental operation, a neural network, a temporally extended cognitive state, and a measurement score answer distinct questions. The strength of the three-network tradition is its testable psychological decomposition of attention, complemented by neuroscientific evidence. Petersen & Posner, 2012.

How Reliable Are Attention Network Test Scores?

A task can produce a robust average group effect while providing an unstable estimate of individual differences. This distinction is central to interpreting the ANT. The classic experimental contrasts are frequently reproducible at the group level; however, a subtraction between conditions can retain relatively little stable between-person information. Measurement error in either condition can contribute to the difference, and variability in strategy or practice can affect results. Ishigami & Klein, 2010; MacLeod et al., 2010.

What the psychometric evidence shows

MacLeod and colleagues aggregated data from 15 studies involving 1,129 healthy participants and assessed reaction-time network scores. Their analysis found low split-half reliability estimates for alerting and orienting and substantially stronger reliability for the executive conflict score. These findings challenge strong individual-level claims from a single administration, particularly for the first two difference scores. This result concerns the standard ANT procedures and samples reviewed; specific variants, larger trial counts, and analytic approaches can perform differently. MacLeod et al., 2010.

Repeated-administration research found that network effects can persist over sessions even as score reliability and some practice-sensitive effects change. Ishigami and Klein showed that accumulating more observations can improve score reliability, highlighting the difference between a research demonstration and a precise individual measurement. A 2024 functional-imaging test–retest study similarly reported that contrasts defining the networks were less reliable than estimates based on specific task conditions in its sample. Ishigami & Klein, 2010; Kong et al., 2024.

Reliability, validity, and what a score can justify

Reliability asks whether the measurement produces sufficiently stable information under the conditions intended. Construct validity asks whether its interpretation matches the psychological operation proposed. A score can be reliable yet reflect processes beyond the proposed construct, or reveal a reliable experimental effect without ranking individuals accurately. ANT research therefore benefits from a prespecified scoring rule, adequate trial numbers, reporting of confidence intervals, complementary tasks, and cautious claims about individual differences. MacLeod et al., 2010; Almeida et al., 2021.

Attention Networks Across Development and Contexts

Childhood attention develops through changes in processing speed, goal regulation, knowledge, motivation, and task experience. Rueda and colleagues adapted the ANT for children and found developmental patterns across the network measures. Such findings show why comparing a young child's raw reaction time with an adult's performance is methodologically unsound without appropriate age-sensitive procedures and evidence. An apparent difference may involve multiple developing processes rather than a change in one isolated network. Rueda et al., 2004.

The ANT literature also includes research on differences across geographic regions and clinical groups. Arora, Lawrence, and Klein assembled an extensive ANT database and illustrated its use with meta-analyses addressing regional comparisons and studies of children with and without ADHD. Variations across laboratories, devices, languages, trial structures, recruitment, and age composition complicate generalizations about culture or individual characteristics. Group-level differences need contextual interpretation and replication across comparable protocols. Arora et al., 2020.

Sleep history, arousal, motivation, medication, sensory and motor abilities, practice, and instructions may all influence performance in an attentional task. Their relevance depends on the research design; these variables should be measured or controlled when they could explain the result. An experimental score represents performance under specified conditions rather than a permanent personal capacity. The literature on attention networks provides a basis for carefully specified questions, not universal rankings of alertness, concentration, or cognitive fitness. Almeida et al., 2021.

What Can Attention-Network Research Tell Us About Everyday Attention?

The framework offers useful interpretations of ordinary demands. A warning sound can increase preparation for a coming event; a location cue can focus processing on the relevant display; conflicting visual instructions can delay a response. These examples correspond to well-defined laboratory effects. Real settings usually combine them with memory, emotion, previous experience, task priorities, and social context. Directly predicting job performance, driving safety, or classroom achievement from a single ANT network score requires additional real-world validation. Fan et al., 2002; MacLeod et al., 2010.

A related field investigates how digital environments compete for attention and how notifications interrupt ongoing tasks. Those studies concern the design and consequences of particular media environments. The three-network model supplies useful concepts for interpreting warning, selection, and conflict, while environment-specific causal questions require their own experiments. For a complementary discussion, see Attention in the Age of AI: Focus, Cognitive Load, and Algorithmic Competition. The network account is a general theory of psychological processing, not a claim that a screen directly damages a particular network.

Can Attention Networks Be Trained?

Improvement at a practiced task demonstrates learning of that task under the tested conditions. Whether training transfers to a different attentional operation, everyday concentration, education, or clinical functioning must be demonstrated separately. The existence of distinguishable networks does not imply that each can be strengthened in isolation by a marketed exercise, app, or brief intervention. Practice may change anticipation, stimulus–response mapping, familiarity, or strategy without producing a general increase in attentional capacity. Petersen & Posner, 2012; Almeida et al., 2021.

An informative training trial should distinguish trained and untrained outcomes, use an appropriate comparison group, assess durability, and measure functional transfer with instruments suited to the intended claim. Large improvements in the practiced ANT contrast would not alone establish wider improvement in self-regulation or mental health. Broad practical promises therefore require independent evidence beyond performance gains on the task itself.

Clinical Interpretation: Tasks, Symptoms, and Diagnoses

Alerting, orienting, and executive attention are general psychological constructs. Distractibility may be a reported experience, an experimentally observed behavior, or a symptom within a clinical assessment. An ANT score is a numerical contrast in a particular task. None of those alone establishes a diagnosis of ADHD, depression, dementia, or another condition. Clinical evaluation requires disorder-specific criteria, functional history, contextual assessment, and appropriate professional methods. Arora et al., 2020.

Research comparing clinical and nonclinical groups can identify potentially informative mechanisms or assessment limitations, but statistical group differences generally overlap across individuals. Low reliability of some ANT network scores creates additional difficulty for individual classification. If a person experiences persistent concentration problems that interfere with daily functioning, an appropriate clinical assessment addresses the broader picture; an online attention-network task should not be used to self-diagnose. MacLeod et al., 2010.

Common Questions About Alerting, Orienting, and Executive Control

Are the three attention networks separate parts of the brain?

They are distinguishable functional operations supported by distributed and interacting neural systems. The word network describes coordinated processing. It should not be interpreted as three sealed anatomical compartments. Contemporary neuroscientific models include additional interacting attention and control systems. Petersen & Posner, 2012.

What is the main difference between alerting and orienting?

Alerting changes readiness for an event, especially its timing. Orienting changes the priority given to a location or source of information. A warning cue may tell someone when to expect a target without showing where; a spatial cue adds information about where to select. Their measurable effects can interact. Fan et al., 2002; Callejas et al., 2005.

Is executive attention the same as self-control?

Executive attention describes specific operations of goal-relevant selection and interference resolution. Self-control is a broader everyday concept involving motivation, emotion, learning, context, and multiple executive functions. The flanker effect estimates one laboratory manifestation of control; it does not measure the whole construct. MacLeod et al., 2010.

Does a larger executive network score mean better attention?

In a conventional incongruent-minus-congruent reaction-time score, a larger positive value reflects a larger conflict cost. It is therefore not simply a higher-ability score. Interpretation also depends on baseline speed, errors, age, trial counts, and the test variant. Fan et al., 2002.

Can an Attention Network Test diagnose ADHD?

No. The ANT is a research paradigm, and its scores have measurement limitations. ADHD diagnosis relies on a broader clinical evaluation and established criteria. Studies using the ANT in ADHD populations can contribute to mechanistic research without turning the task into a diagnostic instrument. Arora et al., 2020.

What is the most important limitation of the three-network model?

Its components are productive experimental distinctions, yet the measured effects are sensitive to task design, can interact, and do not necessarily yield reliable individual traits. A model's success in organizing group-level findings does not automatically establish precise individual measurement. Callejas et al., 2005; MacLeod et al., 2010.

Conclusion: A Functional Architecture of Attention

Alerting prepares the system for events, orienting allocates processing priority, and executive control resolves competition in the service of goals. The three-network tradition gives experimental psychology an influential way to organize these operations and test their consequences. Research following the original model has clarified interactions between networks, distinguished additional neural systems, and improved understanding of what the Attention Network Test does and does not measure. Its enduring contribution is a set of precise, falsifiable questions about how attention works across time, information sources, and competing actions. Petersen & Posner, 2012; Almeida et al., 2021.

Related Articles

Attention in the Age of AI: Focus, Cognitive Load, and Algorithmic Competition — investigates competition for attention in contemporary digital environments and its relation to general cognitive processes.

Attention Economy: How Digital Platforms Compete for Your Time and Focus — examines the environmental and platform-level demands placed on attentional selection.

Attention: Types, Mechanisms, and Limits — Explains attention as selective processing, its types, mechanisms, and limits.

Attention Span: Meaning, Measurement, and Common Myths — Defines attention span, methods of measurement, and misconceptions about fixed limits.

References

Almeida, R. de S., Faria-Jr., A., & Klein, R. M. (2021). On the origins and evolution of the Attention Network Tests. Neuroscience & Biobehavioral Reviews, 126, 560–572. https://doi.org/10.1016/j.neubiorev.2021.02.028

Arora, S., Lawrence, M. A., & Klein, R. M. (2020). The Attention Network Test database: ADHD and cross-cultural applications. Frontiers in Psychology, 11, 388. https://doi.org/10.3389/fpsyg.2020.00388

Callejas, A., Lupiáñez, J., Funes, M. J., & Tudela, P. (2005). Modulations among the alerting, orienting and executive control networks. Experimental Brain Research, 167, 27–37. https://doi.org/10.1007/s00221-005-2365-z

Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215. https://doi.org/10.1038/nrn755

Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14(3), 340–347. https://doi.org/10.1162/089892902317361886

Ishigami, Y., & Klein, R. M. (2010). Repeated measurement of the components of attention using two versions of the Attention Network Test (ANT): Stability, isolability, robustness, and reliability. Journal of Neuroscience Methods, 190(1), 117–128. https://doi.org/10.1016/j.jneumeth.2010.04.019

Kong, Z., Chen, J., Liu, J., Zhou, Y., Duan, Y., Li, H., & Yang, L.-Z. (2024). Test–retest reliability of the attention network test from the perspective of intrinsic network organization. European Journal of Neuroscience, 60(4), 4453–4468. https://doi.org/10.1111/ejn.16448

MacLeod, J. W., Lawrence, M. A., McConnell, M. M., Eskes, G. A., Klein, R. M., & Shore, D. I. (2010). Appraising the ANT: Psychometric and theoretical considerations of the Attention Network Test. Neuropsychology, 24(5), 637–651. https://doi.org/10.1037/a0019803

Petersen, S. E., & Posner, M. I. (2012). The attention system of the human brain: 20 years after. Annual Review of Neuroscience, 35, 73–89. https://doi.org/10.1146/annurev-neuro-062111-150525

Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13, 25–42. https://doi.org/10.1146/annurev.ne.13.030190.000325

Rueda, M. R., Fan, J., McCandliss, B. D., Halparin, J. D., Gruber, D. B., Lercari, L. P., & Posner, M. I. (2004). Development of attentional networks in childhood. Neuropsychologia, 42(8), 1029–1040. https://doi.org/10.1016/j.neuropsychologia.2003.12.012

Xuan, B., Mackie, M.-A., Spagna, A., Wu, T., Tian, Y., Hof, P. R., & Fan, J. (2016). The activation of interactive attentional networks. NeuroImage, 129, 308–319. https://doi.org/10.1016/j.neuroimage.2016.01.017