Dorsal Attention Network

What is the dorsal attention network?

As the network that focuses human attention, the dorsal attention network (DAN) is the brain’s “aperture.”

The DAN is a consistent, bilateral network for the steady holding of attention, and it has many ways of contributing to intellectual capabilities.

As the brain’s aperture, the DAN is frequently activated in relation to other active brain networks. To illustrate these relationships, think of attention as a camera lens. Imagine photographing a garden, with each of the main brain networks as a different flower. When shifting the camera from one to the next, the aperture is adjusted to bring each new plant into sharp focus. The DAN responds similarly, guiding attention to whichever network (or networks) is most prominent and active.

The human brain receives sensory input constantly, and it cannot equally attend to every sensory signal at all times. Instead, the DAN focuses the brain’s attention to hone in on a particular moment’s most important sensory inputs.

To return to the analogy, as you decide how to frame the camera’s shot, your attention is focused on the visual elements in front of you. Though your sensorimotor network is still actively sending sensory cues about the feel of the camera and the heat of the sun, these are not your primary focus because your attention is on the photograph. The DAN selects the most pertinent sensory information for a particular moment to guide your attention.

Share this article
DAN

Discovery of the DAN

 

In 1984, Posner and colleagues1 studied the effects of damage to the parietal lobe on attention. The results of the damage produced disengagement of attention.1 However, this disengagement was not replicated by damage to the frontal, midbrain, or temporal control series.1

In the late 20th century, studies began using imaging techniques to evaluate spatial2 and visual attention.3 Shifts in attention activated the superior parietal lobe, and further study evaluated how these areas correlate with the occipital lobe for efficient and inefficient visuospatial shifts of attention.3,4

Using functional magnetic resonance imaging (fMRI) scans, these theories of attention processing became more closely associated with the DAN, after the turn of the century. The DAN was shown to be activated for spatial attention, eye movements, and hand-eye coordination.5,6 Today, neuroscience acknowledges both top-down and bottom-up attention processing for goal-directed processes and stimulus-driven responses,6,7 respectively.

What is attention?

 

“Attention” is arguably the highest-level cognitive process. In other words, it is possibly the most essential process underlying all sophisticated thinking skills. Its main components are alertness, selectivity, and processing capacity,1 and these varieties of attention permeate most cognitive processes.

There are two modes of attentional processing: bottom-up and top-down attention.

Bottom-up processing is an efficient shift of attention in response to preconscious stimulus, such as motion, orientation,4,8 unexpected noises, or visual changes.9 For example, if while photographing the garden, you heard a person laugh unexpectedly, you may still turn your head to locate the source of the noise — even if you had been engrossed in the composition of your next shot the moment before. The brain’s ventral attention network (VAN) is responsible for this bottom-up shift (more on this below).

Top-down processing, on the other hand, is based on spatial attention, and it enables you to selectively choose where to focus attention based on your expectations10 and conscious goals. When attention shifts,8 it highlights items in the visual field successively as processing occurs in a sequence.4 The DAN uses preconceived notions of visual features, scenes, or the preparation of specific responses as it processes each new idea or event under scrutiny.11 This mode of attention is considered inefficient compared to bottom-up attention because it is a conscious search method, which requires time to process.4

To enable harmonious attention shifts, the DAN does not operate alone. Other brain networks also assist with stimulus response and focus control.

Dorsal versus ventral attention networks

 

The ventral attention network switches attention in response to salient or unexpected stimuli, like shock, frightening events, or “oddball” occurrences.6 This reorienting response occurs unilaterally in the right hemisphere with functional areas in the temporoparietal cortex and inferior frontal cortex.6

The DAN holds attention for a person to focus and tune out miscellaneous noises or environmental changes, while the VAN acts as a “circuit breaker.”6 It interrupts ongoing cognitive activity11 and redirects attention in response to salient or distracting events.6 However, the DAN’s focused attention can still suppress bottom-up shifts in attention.11 This is commonly seen when a person is working or studying, and they actively ignore external distractions.

Unlike the DAN, the VAN is not included in the seven main brain network model, though it may be isolated in alternate schema, such as the 17-network model.12 Each of the functional areas that make up the VAN — though closely connected and activated during unexpected events — are more commonly activated in association with other networks. When BOLD signals are used to cluster functional areas based on similar activity, there are seven main clusters that coactivate more frequently than any other sequences.12 These networks work together for common cognitive functions, but that does not mean these functional areas are solely implicated in those specific functions.

Functional areas from each of the main networks fire together as members of other “sub-networks,” such as the language system or the ventral attention network. Subnetworks are hybrid groups from other networks for specific tasks.

The functional areas associated with the VAN work together for bottom-up attention tasks, but they are more frequently activated with the other main networks in the seven-network model. Whereas, the functional areas associated with the DAN most frequently fire together for top-down attention tasks.

That said, activity of the DAN and VAN are so closely correlated, it can be difficult to differentiate between the activity of one or the other — except in a lab environment. Under these conditions, specific tasks can be designed for VAN-only or DAN-only fMRI tests. However, in real life, neither network is believed to function independently. There is always a dynamic, attentional control in response to top-down decision making or bottom-up stimuli.13

Since attention is so closely correlated with other networks, it must also be considered how the DAN holds attention in relationship to cognitive control.

Location of the DAN in the brain

 

While the VAN is unilaterally located in the right hemisphere, the DAN is a bilateral network. It demonstrates strong connectivity (see Connectomics) between areas in the lateral occipital lobe, the pre-central sulcus, the dorsal-most portion of the superior frontal sulcus considered to be the frontal eye fields (FEF), the ventral premotor cortex, superior parietal lobule, intraparietal sulcus, and motion-sensitive middle temporal area.5

DAN_AXI

AXIAL VIEW

DAN_SAG-1

SAGITTAL VIEW

Screen Shot 2021-05-11 at 4.23.58 pm

CORONAL VIEW

The main functional areas in the DAN:

Want to dive deeper?

How the dorsal attention network interacts with the central executive network

 

Since the brain’s networks are so closely connected, no process occurs in a vacuum. Though the DAN holds attention, it does not do so without input from the brain’s central executive network (CEN).

The CEN is the brain’s “external mind,” and it is implicated in active decision making for working memory14 and task directives.15,16These two networks consistently work together as the CEN decides what the DAN will focus on next. A simplified comparison would be that in a battle, the CEN is the general, and the DAN is the lieutenant.

In their work studying task direction, Corbetta and Shulman6,17 found that areas in the DAN forming the dorsal frontoparietal network were implicated in top-down distribution of visual attention.6 The CEN directs the DAN’s focused attention for task set maintenance for the duration of a task,17 as well as goal-directed stimulus response.

Yet, there is also a constant balance between the CEN and the default mode network (DMN), the brain’s “internal mind.” The CEN and DMN are the brain’s dominant control networks, and they are both associated with attention. When the brain’s internal processing becomes less deactivated, activity of the DMN interrupts the DAN’s focus, causing lapses in attention.18 Then, when the brain switches away from internal processing, the CEN refocuses on external task direction19 and re-engages the DAN to hold attention on the tasks or actions at hand.

 

Pathology resulting in changes to the DAN

 

Since the brain’s attentional networks are implicated in most major cognitive processes, degeneration and pathology in the brain can disrupt or cause damage to attentional capabilities.

Neurodegenerative diseases and strokes can result in impairment of top-down processing,43as well as symptoms of spatial neglect. Neglect can occur contralaterally,44 with patients suffering damage to the right hemisphere having difficulty noticing stimuli on the left side of space.6 Neglect is most frequently associated with stroke, and can be more severe following right-hemisphere damage.45 This syndrome manifests as the inability to orient or perceive sensory information on one side of space and contralateral to the lesion.45

In addition to attentional and sensory disruption due to neurodegenerative disorders, the DAN is also associated with neuropsychiatric disorders, like schizophrenia46 and attention-deficit/hyperactivity disorder (ADHD).47

In particular, ADHD exhibits abnormal, spontaneous connectivity fluctuations between major networks, such as the DAN, VAN, DMN, and salience network.47 Higher functional connectivity between networks is associated with inattentional behavior, such as mind-wandering and attentional changes.47 Likewise, decreased functional connectivity between areas of the DAN and the DMN correlates with less control over DMN deactivation48 and can result in lapses in attention.

As researchers continue to evaluate the DAN and the implications of changes or damage to the network, studies are also being conducted on other common forms of neuropathology and the implications for patients.

Children with autism spectrum disorder (ASD) often have increased hyperconnectivity between functional areas critical for attention.49 Conversely, adults with ASD demonstrate hypoconnectivity between these areas,49 suggesting that developmental stages may impact the functional connectivity between brain areas responsible for goal-driven attention.50

Changes to the brain’s functional connectivity may also result from other therapies and treatments. Shen and colleagues51 evaluated the impact of chemotherapy on breast cancer patients, while looking for consistent changes to various brain regions. The study found that changes occurred in the frontoparietal lobe and the occipital lobe, and it was posited that these changes may be associated with the DAN and the result of chemotherapy and psychological distress.51

Since the efficient, goal-driven processes of the DAN are key elements of cognition, the network is highly correlated with many of the brain’s other functional areas. Being a highly active brain network, its wide-ranging correlations make it a key problem area for pathology and resulting disorders. As research continues to study the biomarkers of neurodegenerative and neuropsychological diseases, a greater understanding of the DAN may help lead to possible therapies and treatments.

Explore other networks

Reference list

 

  1. Posner MI, Walker JA, Friedrich FJ, Rafal RD. Effects of parietal injury on covert orienting of attention. J Neurosci. 1984;4(7):1863-1874. doi.org/10.1523/JNEUROSCI.04-07-01863.1984.
  2. Petersen SE, Corbetta M, Miezin FM, Shulman GL. PET studies of parietal involvement in spatial attention: comparison of different task types. Can J Exp Psychol. 1994;48(2):319-338. doi:10.1037/1196-1961.48.2.319.
  3. Corbetta M, Shulman GL, Miezin FM, Petersen SE. Superior parietal cortex activation during spatial attention shifts and visual feature conjunction [published correction appears in Science 1995 Dec 1;270(5241):1423]. Science. 1995;270(5237):802-805. doi:10.1126/science.270.5237.802.
  4. Leonards U, Sunaert S, Van Hecke P, Orban GA. Attention mechanisms in visual search—An fMRI study. J Cogn Neurosci. 2000;12(Supplement 2):61-75. doi.org/10.1162/089892900564073.
  5. Vincent JL, Kahn I, Snyder AZ, Raichle ME, Buckner RL. Evidence for a frontoparietal control system revealed by intrinsic functional connectivity [published correction appears in J Neurophysiol. 2011 Mar;105(3):1427]. J Neurophysiol. 2008;100(6):3328-3342. doi:10.1152/jn.90355.2008.
  6. Corbetta M, Shulman GL. Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci. 2002;3(3):201-215. doi:10.1038/nrn755.
  7. Ocasio W. Attention to Attention. Organization Science. 2011;22(5):1286-1296. doi.org/10.1287/orsc.1100.0602.
  8. Treisman AM. Visual perception of features and objects. Defense Technical Information Center website. https://apps.dtic.mil/sti/citations/ADA248578. Published September 14, 1991. Accessed May 9, 2021.
  9. Jonides J. Voluntary versus automatic control over the mind's eye's movement. Atten Perform. https://sites.lsa.umich.edu/jonides-lab/wp-content/uploads/sites/439/2016/10/1981_1.pdf. Published 1981. Accessed March 1, 2021.

  10. Cherry K. What is top-down processing? VeryWell Mind website. https://www.verywellmind.com/what-is-top-down-processing-2795975. Updated October 18, 2020. Accessed February 27, 2021.
  11. Corbetta M, Patel G, Shulman GL. The reorienting system of the human brain: from environment to theory of mind. Neuron. 2008;58(3):306-324. doi:10.1016/j.neuron.2008.04.017.
  12. Yeo BT, Krienen FM, Sepulcre J, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106(3):1125-1165. doi:10.1152/jn.00338.2011.
  13. Vossel S, Geng JJ, Fink GR. Dorsal and ventral attention systems: distinct neural circuits but collaborative roles. Neuroscientist. 2014;20(2):150-159. doi:10.1177/1073858413494269.
  14. Dosenbach NU, Fair DA, Miezin FM, et al. Distinct brain networks for adaptive and stable task control in humans. Proc Natl Acad Sci U S A. 2007;104(26):11073-11078. doi:10.1073/pnas.0704320104.
  15. Menon V. Large-scale brain networks and psychopathology: a unifying triple network model. Trends Cogn Sci. 2011;15(10):483-506. doi:10.1016/j.tics.2011.08.003.
  16. Koechlin, E. Architecture of central executive functions in the human prefrontal cortex. 2007. https://www.princeton.edu/~yael/NIPSWorkshop/KoechlinAbstract.pdf. Accessed January 28, 2021.
  17. Dosenbach NU, Visscher KM, Palmer ED, et al. A core system for the implementation of task sets. Neuron. 2006;50(5):799-812. doi:10.1016/j.neuron.2006.04.031.
  18. Weissman D, Roberts K, Visscher K, et al. The neural bases of momentary lapses in attention. Nat Neurosci. 2006;9:971-978. doi.org/10.1038/nn1727.

  19. Ekhtiari H, Nasseri P, Yavari F, Mokri A, Monterosso J. Neuroscience of drug craving for addiction medicine: From circuits to therapies. In: Ekhtiari H, Paulus M, eds. Progress in Brain Research. Amsterdam, Netherlands: Elsevier. 2016;223:115-141. doi.org/10.1016/bs.pbr.2015.10.002.
  20. Glasser MF, Coalson TS, Robinson EC et al. A multi-modal parcellation of human cerebral cortex. Brain. 2016;536(7615):2093-2107. doi: 10.1038/nature18933.

  21. Paus T. Location and function of the human frontal eye-field: a selective review. Neuropsychologia. 1996;34(6):475-483. doi: 10.1016/0028-3932(95)00134-4.
  22. Petit L, Clark VP, Ingeholm J, Haxby JV. Dissociation of saccade-related and pursuit-related activation in human frontal eye fields as revealed by fMRI. J Neurophysiol. 1997;77(6):3386-3390. doi: 10.1152/jn.1997.77.6.3386.
  23. Pierrot-Deseilligny C. Saccade and smooth-pursuit impairment after cerebral hemispheric lesions. Eur Neurol. 1994;34(3):121-134. doi: 10.1159/000117025.
  24. Pierrot-Deseilligny C, Gaymard B, Muri R, Rivaud S. Cerebral ocular motor signs. J Neurol. 1997;244(2):65-70. doi: 10.1007/s004150050051.
  25. Fecteau JH, Munoz DP. Salience, relevance, and firing: a priority map for target selection. Trends Cogn Sci. 2006;10(8):382-390. doi: 10.1016/j.tics.2006.06.011.
  26. Pierrot-Deseilligny C, Muri RM, Nyffeler T, Milea D. The role of the human dorsolateral prefrontal cortex in ocular motor behavior. Ann N Y Acad Sci. 2005;1039:239-251. doi: 10.1196/annals.1325.023.
  27. Allan PG, Briggs RG, Conner AK, et al. Parcellation-based tractographic modeling of the dorsal attention network. Brain Behav. 2019;9:e01365. doi.org/10.1002/brb3.1365.
  28. Wang J, Yang Y, Fan L, et al. Convergent functional architecture of the superior parietal lobule unraveled with multimodal neuroimaging approaches. Hum Brain Mapp. 2015;36(1):238-257. https://doi.org/10.1002/hbm.22626.
  29. Scheperjans F, Eickhoff SB, Homke L, et al. Probabilistic maps, morphometry, and variability of cytoarchitectonic areas in the human superior parietal cortex. Cereb Cortex. 2008;18(9):2141-2157. doi:10.1093/ cercor/bhm241.
  30. Mars RB, Jbabdi S, Sallet J, et al. Diffusion-weighted imaging tractography-based parcellation of the human parietal cortex and comparison with human and macaque resting-state functional connectivity. J Neurosci. 2011;31(11):4087-4100. doi: 10.1523/JNEUROSCI.5102-10.2011.
  31. Galletti C, Fattori P. The dorsal visual stream revisited: Stable circuits or dynamic pathways? Cortex. 2018;98:203-217. doi: 10.1016/j.cortex.2017.01.009
  32. Fogassi L, Gallese V, Buccino G, Craighero L, Fadiga L, Rizzolatti G. Cortical mechanism for the visual guidance of hand grasping movements in the monkey: A reversible inactivation study. Brain J Neurol. 2001;124(3):571-586. doi: 10.1093/brain/124.3.571.
  33. Passingham RE, Chung A, Goparaju B, Cowey A, Vaina LM. Using action understanding to understand the left inferior parietal cortex in the human brain. Brain Res. 2014;1582:64-76. doi: 10.1016/j.brainres.2014.07.035.
  34. Grefkes C, Fink GR. Review: The functional organization of the intraparietal sulcus in humans and monkeys. J Anat. 2005;207(1):3-17. doi: 10.1111/j.1469-7580.2005.00426.x.
  35. Carlile S, Leung J. The Perception of Auditory Motion. Trends Hear. 2016;20:2331216516644254. Published April 19, 2016. doi:10.1177/2331216516644254.
  36. Mruczek RE, von Loga IS, Kastner S. The representation of tool and non-tool object information in the human intraparietal sulcus. J Neurophysiol. 2013;109(12):2883-2896. doi: 10.1152/jn.00658.2012.
  37. Britten KH. Mechanisms of self-motion perception. Annu Rev Neurosci. 2008;31(1):389-410. doi: 10.1146/annurev.neuro.29.051605.112953.
  38. Ilg UJ. The role of areas MT and MST in coding of visual motion underlying the execution of smooth pursuit. Vision Res. 2008;48(20):2062-2069. doi: 10.1016/j.visres.2008.04.015.
  39. Born RT, Bradley DC. Structure and function of visual area MT. Annu Rev Neurosci. 2005;28(1):157-189. doi: 10.1146/annurev.neuro.26.041002.131052.
  40. Grill-Spector K, Malach R. The human visual cortex. Annu Rev Neurosci. 2004;27(1):649-677. doi: 10.1146/annurev.neuro.27.070203.144220.
  41. Epstein RA. Parahippocampal and retrosplenial contributions to human spatial navigation. Trends Cogn Sci. 2008;12(10):388-396. doi: 10.1016/j.tics.2008.07.004.
  42. Kolster H, Peeters R, Orban GA. The retinotopic organization of the human middle temporal area MT/V5 and its cortical neighbors. J Neurosci. 2010;30(29):9801-9820. doi: 10.1523/JNEUROSCI.2069-10.2010.
  43. Li R, Wu X, Fleisher AS, Reiman EM, Chen K, Yao L. Attention-related networks in Alzheimer's disease: a resting functional MRI study. Hum Brain Mapp. 2012;33(5):1076-1088. doi:10.1002/hbm.21269.
  44. Wright WG, Gurfinkel V, King L, Horak F. Parkinson's disease shows perceptuomotor asymmetry unrelated to motor symptoms. Neurosci Lett. 2007;417(1):10-15. doi:10.1016/j.neulet.2007.02.016.
  45. Li K, Malhotra PA. Spatial neglect. Pract Neurol. 2015;15:333-339. dx.doi.org/10.1136/practneurol-2015-001115.
  46. Hasenkamp W, James GA, Boshoven W, Duncan E. Altered engagement of attention and default networks during target detection in schizophrenia. Schizophr Res. 2011;125(2-3):169-173. doi.org/10.1016/j.schres.2010.08.041.
  47. Kucyi A, Hove MJ, Biederman J, Van Dijk KR, Valera EM. Disrupted functional connectivity of cerebellar default network areas in attention-deficit/hyperactivity disorder. Hum Brain Mapp. 2015;36(9):3373-3386. doi:10.1002/hbm.22850.
  48. Sato JR, Hoexter MQ, Castellanos XF, Rohde LA. Abnormal brain connectivity patterns in adults with ADHD: A coherence study. PLoS One. 2012;7(9):e45671 doi.org/10.1371/journal.pone.0045671.
  49. Farrant K, Uddin LQ. Atypical developmental of dorsal and ventral attention networks in autism. Dev Sci. 2016;19:550-563. doi.org/10.1111/desc.12359.
  50. Fitzgerald J, Johnson K, Kehoe E, et al. Disrupted functional connectivity in dorsal and ventral attention networks during attention orienting in autism spectrum disorders. Autism Res. 2015;8:136-152. doi.org/10.1002/aur.1430.
  51. Shen CY, Chen VCH, Yeh DC. et al. Association of functional dorsal attention network alterations with breast cancer and chemotherapy. Sci Rep. 2019;9(104). doi.org/10.1038/s41598-018-36380-6