Determinants and mechanisms of attentional modulation of neural processing.
Open accessAbstract
This review contrasts the most-studied variety of attention, visuospatial attention, with several types of nonspatial visual attention. We: 1) discuss the manner in which spatial and nonspatial varieties of attention are experimentally defined, and the ecological validity of the paradigms in which they are studied, 2) review and compare differing effects of spatial and nonspatial attention on neural processing, 3) discuss the manner in which attention operates within the framework of an anatomical visual hierarchy, as well as 4) how attention relates to the temporal dynamics of visual processing, 5) describe cellular circuits and physiological processes that appear to be involved in attention effects, 6) discuss the relationship of attentional physiology to the perceptual and cognitive effects of attention, and 7) consider the strengths and limitations of several current models of selective attention. Throughout, we attempt to integrate the findings of monkey and human studies whenever possible. We have three main conclusions. First, two models, the Neural Specificity Model of Harter and colleagues and the Feature Similarity Gain Model of Treue and colleagues best incorporate findings in relation to both spatial and nonspatial varieties of attention. Significantly, these models explicitly note that the specific neuronal components used in attentional modulation of processing are flexible and determined by task demands. Second, current evidence also provides strong bases for deriving testable hypotheses about the specific brain mechanisms utilized by attention. Cellular processes, brain circuits and neurotransmitter components can and should be incorporated into our models of attention. Finally, it is increasingly evident that we can and should analyze temporal patterns of attentional modulation, both within and across brain areas. These patterns provide critical information on the dynamics of attention.
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The case for feedforward multisensory convergence during early cortical processing
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Self-citationPredictive coding as a model of biased competition in visual attention
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Virtual reality and consciousness inference in dreaming
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“…are implicated in both REM sleep and attentional gating: synchronous gain (Chawla et al., 1999) mediated by fast oscillatory or synchronized activity (Womelsdorf and Fries, 2006) and classical neuromodulatory (e.g., cholinergic) neurotransmission (Schroeder et al., 2001; Hirayama et al., 2004).”
BackgroundTransient Attention Enhances Perceptual Performance and fMRI Response in Human Visual Cortex
Liu, T., Pestilli, F., & Carrasco, M. (2005) · Neuron · doi:10.1016/j.neuron.2004.12.039 · Cited by 192 · see citing works
Schroeder, C., Smiley, J., Fu, K., McGinnis, T., O'Connell, M. N., & Hackett, T. (2003) · International Journal of Psychophysiology · doi:10.1016/s0167-8760(03)00120-x · Cited by 193 · see citing works
Self-citationFeature-Based Attention Modulates Orientation-Selective Responses in Human Visual Cortex
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Searching for Targets within the Spatial Layout of Visual Short-Term Memory
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A Feedback Model of Visual Attention
Spratling, M., & Johnson, M. H. (2004) · Journal of Cognitive Neuroscience · doi:10.1162/089892904322984526 · Cited by 152 · see citing works
Sehatpour, P., Molholm, S., Javitt, D. C., & Foxe, J. J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.07.049 · Cited by 146 · see citing works
Intermodal Auditory, Visual, and Tactile Attention Modulates Early Stages of Neural Processing
Karns, C. M., & Knight, R. T. (2008) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21037 · Cited by 122 · see citing works
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Predictive Coding or Evidence Accumulation? False Inference and Neuronal Fluctuations
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Large-Scale Visuomotor Integration in the Cerebral Cortex
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Self-citationSpatial attention changes excitability of human visual cortex to direct stimulation
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Cortical Region Interactions and the Functional Role of Apical Dendrites
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Embodied inference: or "I think therefore I am, if I am what I think"
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Human–simian correspondence in the early cortical processing of multisensory cues
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Self-citationEarly visual and auditory processing rely on modality-specific attentional resources
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Transcranial Magnetic Stimulation Reveals Intrinsic Perceptual and Attentional Rhythms
Dugué, L., & VanRullen, R. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00154 · Cited by 50 · see citing works
Knuth, K. H., Shah, A. S., Truccolo, W., Ding, M., Bressler, S. L., & Schroeder, C. E. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00663.2005 · Cited by 54 · see citing works
Self-citationA feedback model of perceptual learning and categorization
Spratling, M., & Johnson, M. H. (2006) · Visual Cognition · doi:10.1080/13506280500168562 · Cited by 52 · see citing works
Bailey, N. W., Freedman, G., Raj, K., Sullivan, C. M., Rogasch, N. C., Chung, S. W., Hoy, K. E., Chambers, R., Hassed, C. S., Dam, N. T. V., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0203096 · Cited by 65 · see citing works
Sustained attention and apical dendrite activity in recurrent circuits.
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Early involvement of the temporal area in attentional selection of grating orientation: an ERP study
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Temporal Characteristics of Audiovisual Information Processing
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Sharma, J., 杉原, 弘., Yarden Katz, A., Schummers, J., Tenenbaum, J. B., & Sur, M. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu086 · Cited by 34 · see citing works
Deouell, L. Y. (2002) · Consciousness and Cognition · doi:10.1016/s1053-8100(02)00024-7 · Cited by 29 · see citing works
Electrostimulation as a Prosthesis for Repair of Information Flow in a Computer Model of Neocortex
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Cox, M. A., Dougherty, K., Adams, G. K., Reavis, E. A., Westerberg, J. A., Moore, B., Leopold, D. A., & Maier, A. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx305 · Cited by 25 · see citing works
Task Relevance Enhances Early Transient and Late Slow-Wave Activity of Distributed Cortical Sources
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Contribution of FEF to Attentional Periodicity during Visual Search: A TMS Study
Dugué, L., Beck, A.-A., Marqué, P., & Rufin Vanrullen, A. (2019) · eNeuro · doi:10.1523/eneuro.0357-18.2019 · Cited by 24 · see citing works
A single functional model of drivers and modulators in cortex
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Induced Gamma-band Activity Elicited by Visual Representation of Unattended Objects
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Neural Mechanisms of Rapid Sensitivity to Syntactic Anomaly
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Can whole brain nerve conduction velocity be derived from surface-recorded visual evoked potentials?
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Adaptive sensory coding of gaze direction in schizophrenia
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Event based self-supervised temporal integration for multimodal sensor data.
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Current Source Density Analysis of Ongoing Neural Activity: Theory and Application
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Attentional modulation of early-stage visual processing in schizophrenia
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- Authors
- Schroeder, C.
- Venue
- Frontiers in bioscience
- Publisher
- IMR Press
- Published
- 2001
- Volume
- 6
- Issue
- 1
- Pages
- d672
- ISSN
- 1093-4715 (ISSN-L)
- 1093-9946
- OpenAlex
- W19535118
- Cited by
- 87
- References
- 85
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 1 · 2020: 1 · 2019: 3 · 2018: 2 · 2017: 2 · 2016: 1 · 2015: 1 · 2014: 4 · 2013: 2 · 2012: 5
- FWCI
- 0.43
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Frontiers in bioscience (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health (MH60358, MH61989, R01MH061989, R03MH063434, R01MH060358)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- visual attention, visuospatial attention, visual hierarchy, temporal dynamics of visual processing, neurotransmitter mechanisms, brain circuits
- MeSH terms
- Animals, Attention, Cognition, Humans, Neural Pathways, Visual Cortex, Visual Pathways, Visual Perception
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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