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Neuromodulation of Attention
Open accessAbstract
Attention is critical to high-level cognition and attention deficits are a hallmark of neurologic and neuropsychiatric disorders. Although years of research indicates that distinct neuromodulators influence attentional control, a mechanistic account that traverses levels of analysis (cells, circuits, behavior) is missing. However, such an account is critical to guide the development of next-generation pharmacotherapies aimed at forestalling or remediating the global burden associated with disorders of attention. Here, we summarize current neuroscientific understanding of how attention affects single neurons and networks of neurons. We then review key results that have informed our understanding of how neuromodulation shapes these neuron and network properties and thereby enables the appropriate allocation of attention to relevant external or internal events. Finally, we highlight areas where we believe hypotheses can be formulated and tackled experimentally in the near future, thereby critically increasing our mechanistic understanding of how attention is implemented at the cellular and network levels.
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“Among numerous cognitive domains, working memory serves as the basis of other higher order cognitive processes including but not limited to recognition memory (27–29), which is mediated by mPFC function.”
From Effects of Lisdexamfetamine, a Prodrug of D-Amphetamine, on Locomotion, Spatial Cognitive Processing and Neurochemical Profiles in Rats: A Comparison With Immediate-Release Amphetamine (2022) · cites this paper as [28]
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“In network models of local cortical circuits, state-dependent increases in inhibitory and excitatory drive can cause convergence of competing, unstable patterns of activity to a single, stable representation221”
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Citations
Cites
Control of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388
Neural Mechanisms of Selective Visual Attention
Desimone, R., & Duncan, J. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001205 · Cited by 8,388
The relation of strength of stimulus to rapidity of habit formation
Yerkes, R. M., & Dodson, J. D. (1908) · Journal of Comparative Neurology and Psychology · doi:10.1002/cne.920180503 · Cited by 6,911
Aston-Jones, G., & Cohen, J. D. (2005) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.28.061604.135709 · Cited by 4,472
Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention
Fries, P., Reynolds, J. H., Rorie, A. E., & Desimone, R. (2001) · Science · doi:10.1126/science.1055465 · Cited by 2,786
The physiology, signaling, and pharmacology of dopamine receptors
Beaulieu, J.-M., & Gainetdinov, R. R. (2011) · Pharmacological Reviews · doi:10.1124/pr.110.002642 · Cited by 2,763
Rhythms for cognition: communication through coherence
Fries, P. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.034 · Cited by 2,725
Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex
Funahashi, S., Bruce, C. J., & Goldman-Rakic, P. S. (1989) · Journal of Neurophysiology · doi:10.1152/jn.1989.61.2.331 · Cited by 2,685
Berridge, C. W., & Waterhouse, B. D. (2003) · Brain Research Reviews · doi:10.1016/s0165-0173(03)00143-7 · Cited by 2,529
Flagged first, then by citations
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Items 301–349 of 349
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Morgan, J., Albanna, B. F., & Herman, J. P. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.09.622721
Learning enhances behaviorally relevant representations in apical dendritesPreprint
Benezra, S. E., Patel, K., Campos, C. P., Hillman, E. M. C., & Bruno, R. M. (2024) · eLife · doi:10.7554/elife.98349.2
Aperiodic Pupil Fluctuations at Rest Predict Orienting of Visual Attention
Wang, R., & Jia, J. (2025) · Psychophysiology · doi:10.1111/psyp.14755
Aksoy, Z., & Doğuer, Ç. (2025) · Journal of the American Nutrition Association · doi:10.1080/27697061.2025.2480140 · Cited by 1
Kuang, C., & Duncan, N. W. (2025) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/bs.plm.2025.03.003
Noorman, S., Stein, T., Zantvoord, J. B., Fahrenfort, J. J., & van Gaal, S. (2025) · eLife · doi:10.7554/elife.100530.2
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Sonkusare, S., Iyer, K. K., Hearne, L. J., Phogat, R., van der Meer, J. N., Dionisio, S. A., Shine, J. M., & Breakspear, M. J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.14.664815 · Cited by 1
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Mettini, E., & Wiegel, N. L. (2025) · Journal of Pedagogical Studies · doi:10.12737/2500-3305-2025-10-3-127-143
Acetylcholine enhances deviance detection in Hodgkin-Huxley neuronal networks
Fang, F., Huang, Z., & Chao, Z. C. (2026) · Cognitive Neurodynamics · doi:10.1007/s11571-026-10522-3
Liu, J., Jiang, L., Li, X., Wu, J., & Liu, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.06.669021
Multisensory Attenuation of the Pupil Light Response in Autistic and Non‐Autistic Children
Brittenham, C., Vanneau, T., & Molholm, S. (2026) · European Journal of Neuroscience · doi:10.1111/ejn.70578
Ghassemkhani, K., & Dotta, B. T. (2025) · Research Square · doi:10.21203/rs.3.rs-7456351/v1
Kim, A. J., Zhao, C., Guo, F., Pappas, I., Dahl, M. J., Jacobs, H. I. L., Wang, D. J. J., & Mather, M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.07.680973
Çoban, C., & Bulut, S. D. (2025) · Psychiatry Research · doi:10.1016/j.psychres.2025.116778
Kurikawa, T., & Kaneko, K. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.108381
Jiang, S., Ma, Y., Shi, Y., Zou, Y., Yang, Z., Zhi, W., Zhao, Z., Shen, W., Chen, L., Wu, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26661119
Jiang, S., Ma, Y., Shi, Y., Zou, Y., Yang, Z., Zhi, W., Zhao, Z., Shen, W., Chen, L., Wu, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26661140
Jiang, S., Ma, Y., Shi, Y., Zou, Y., Yang, Z., Zhi, W., Zhao, Z., Shen, W., Chen, L., Wu, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26661128
Bast, N., Mason, L., Ecker, C., Baumeister, S., Banaschewski, T., Jones, E. J. H., Murphy, D., Buitelaar, J. K., Loth, E., Pandina, G., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22610867
Jiang, S., Ma, Y., Shi, Y., Zou, Y., Yang, Z., Zhi, W., Zhao, Z., Shen, W., Chen, L., Wu, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26661137
Jiang, S., Ma, Y., Shi, Y., Zou, Y., Yang, Z., Zhi, W., Zhao, Z., Shen, W., Chen, L., Wu, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26661131
Jiang, S., Ma, Y., Shi, Y., Zou, Y., Yang, Z., Zhi, W., Zhao, Z., Shen, W., Chen, L., Wu, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26661125
Jiang, S., Ma, Y., Shi, Y., Zou, Y., Yang, Z., Zhi, W., Zhao, Z., Shen, W., Chen, L., Wu, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26661122
Veith, V. K., Quigley, C., & Treue, S. (2021) · Figshare · doi:10.6084/m9.figshare.14227939
Jiang, S., Ma, Y., Shi, Y., Zou, Y., Yang, Z., Zhi, W., Zhao, Z., Shen, W., Chen, L., Wu, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26661143
Jiang, S., Ma, Y., Shi, Y., Zou, Y., Yang, Z., Zhi, W., Zhao, Z., Shen, W., Chen, L., Wu, Y., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26661134
Visual attention modulation by the dopaminergic system in the medial prefrontal cortex (mPFC)
kolaei, H. A. V., Darvish, A.-H., & Safari, M.-S. (2025) · Economy of Tajikistan · doi:10.61882/phypha.29.3.335
Xing, L., Yujie, C. H. E. N., Chengguo, M. I. A. O., & Yang, Z. (2026) · Advances in Psychological Science · doi:10.3724/sp.j.1042.2026.0313
Stimulus-Driven Thermodynamic Shifts and Geometric Reorganization in Mouse Primary Visual CortexPreprint
Liu, J., Jiang, L., Li, X., Wu, J., & Liu, J. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.12.705646
Chhabria, K., Duckworth, J. C., Yao, P., Fassihi, A., & Kleinfeld, D. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.20.707130
Dyce, G., Singh, T., Mattingley, J. B., & Arabzadeh, E. (2026) · Research Square · doi:10.21203/rs.3.rs-4368226/v2
Dyce, G., Singh, T., Mattingley, J. B., & Arabzadeh, E. (2026) · Research Square · doi:10.21203/rs.3.rs-4368226/v3
Flexibility in value-based decision-making
Jahn, C. I. (2018) · theses.fr (ABES) · doi:10.70675/24ffd7ecz04aez45dez9bfdzff312b4881a8
Quilgars, C. (2021) · theses.fr (ABES) · doi:10.70675/4b84b239z423bz46aaza3eaz54db476be688
Yao, Y., Gonzalez, C. S., Geirnaert, S., Gillebert, C. R., Tuytelaars, T., & Bertrand, A. (2026) · Journal of Neural Engineering · doi:10.1088/1741-2552/aea449
Hammami, A., Hammami, R., Mahmoudi, A., Rebai, H., & van den Tillaar, R. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1844921
Intrinsic Population Dynamics are a Neuronal Substrate for Visual AttentionPreprint
Schmidt, F. H., Młynarski, W. F., Georges, A., Sumser, A., Tkačik, G., & Joesch, M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.02.729565
[These authors contributed equally (shared senior authorship): Markus Werkle-Bergner, Mara Mather.]
Dahl, M., Kulesza, A., Werkle‐Bergner, M., & Mather, M. (2023) · MPG.PuRe (Max Planck Society)
Organización anatomofuncional de la red de atención frontoparietal en la infancia
Martínez, S. S. (2026) · Escritos de Psicología / Psychological Writings · doi:10.24310/escpsi.19.1.2026.22181
Atiya-Malki, A., & Tarrasch, R. (2026) · Mindfulness · doi:10.1007/s12671-026-02937-0
Berthier, M. L., Gómez-Pérez, Á. Y., Dávila, G., Torres‐Prioris, M. J., Birba, A., & García, A. M. (2026) · Aphasiology · doi:10.1080/02687038.2026.2708827
Animal consciousness – What does the term consciousness tell us when dealing with animals?
Ehret, G. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-29258-3.00023-9
Niu, T., Li, R., & Li, M. (2026) · Brain Sciences · doi:10.3390/brainsci16090915
Lee, I., Lin, S.-H. N., Kuo, R., Lin, C., & Chang, L.-H. (2026) · NMR in Biomedicine · doi:10.1002/nbm.70389
The normalization mechanism of emotional modulation on rhythmic temporal attention
Jinfang, C. A. I., Wang, S., 岳小溪, Lin, Y. H., & Sun, Y. (2026) · Acta Psychologica Sinica · doi:10.3724/sp.j.1041.2026.2270
Inter- and intra- individual variability in audiovisual multisensory processes in healthy ageing
Middelmann, N. K., Ecabert, L., Ortega, E. V., Griffa, A., Guevara, A. B., Allali, G., Bartlett, J. E., & Murray, M. M. (2026) · Aging Brain · doi:10.1016/j.nbas.2026.100168
Dopamine modulation of motor and implicit learning contributions to auditory temporal attention
Zalta, A., Spitz, L.-F., Schnitzler, A., Morillon, B., & Florin, E. (2026) · iScience · doi:10.1016/j.isci.2026.117541
A Critical Time Window of Neocortex Modulation for Remote Fear Memory in Rats and Humans
Cao, L., Zhang, Y., Liu, X., Li, Z., Lu, T., Deng, J., Zhang, W., Li, P., Lin, X., Feng, S., et al. (2026) · Advanced Science · doi:10.1002/advs.202520707
Metadata
- Authors
- Thiele, A., & Bellgrove, M. A.
- Affiliations
- Newcastle University (GB)
- Monash University (AU)
- Corresponding author
- Thiele, Alexander
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2018-02
- Volume
- 97
- Issue
- 4
- Pages
- 769-785
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC6204752
- OpenAlex
- W2788231085
- Cited by
- 350
- References
- 215
- Citations by year
- 2026: 36 · 2025: 33 · 2024: 54 · 2023: 52 · 2022: 45 · 2021: 50 · 2020: 32 · 2019: 35 · 2018: 13
- FWCI
- 4.34
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Neuron (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Monash University Research Portal (Monash University) (submittedVersion, cc-by)
- Newcastle University ePrints (Newcastle Univesity) (cc-by)
- Funders
- Wellcome Trust (093104)
- MRC (MR/P013031/1)
- NC3R (NC/P000940/1)
- Australian Research Council (FT130101488, DP150100986)
- Newcastle University
- Monash University
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- attention, neuromodulation, attention deficits, single neurons, neural circuits, attentional control, attention allocation
- MeSH terms
- Acetylcholine, Animals, Attention, Biogenic Amines, Brain, Dopamine, Humans, Neural Pathways, Neurons, Norepinephrine, Serotonin
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