Review
Attention in the real world: toward understanding its neural basis

https://doi.org/10.1016/j.tics.2014.02.004Get rights and content

Highlights

  • Real-world visual search is mediated by attentional templates in the visual cortex.

  • ‘What’ templates represent target-diagnostic properties.

  • ‘Where’ templates represent likely target locations.

  • Attentional templates are shaped by familiarity, scene context, and scene memory.

The efficient selection of behaviorally relevant objects from cluttered environments supports our everyday goals. Attentional selection has typically been studied in search tasks involving artificial and simplified displays. Although these studies have revealed important basic principles of attention, they do not explain how the brain efficiently selects familiar objects in complex and meaningful real-world scenes. Findings from recent neuroimaging studies indicate that real-world search is mediated by ‘what’ and ‘where’ attentional templates that are implemented in high-level visual cortex. These templates represent target-diagnostic properties and likely target locations, respectively, and are shaped by object familiarity, scene context, and memory. We propose a framework for real-world search that incorporates these recent findings and specifies directions for future study.

Section snippets

Attentional selection in daily life

The primary goal of selective visual attention is to focus processing resources on behaviorally relevant objects in our visual environment. In our daily lives, we direct attention (and, with it, often our eyes) all the time: when searching for a coffee cup in the cupboard, when looking out for cars while crossing the street, or when trying to find a friend at a conference. Because we perform so many visual searches every day, often for the same objects (e.g., people) and often within the same

Classical approaches to the study of visual search

To study the process of selecting behaviorally relevant information from cluttered displays in the laboratory, behavioral and neurophysiological studies have typically greatly reduced the complexity of the real world by having participants perform search tasks in displays comprising simple and well-defined stimuli presented on uniform backgrounds (Figure 1B). For example, in a display comprising red and green lines of different orientation, observers search for the presence of a specific target

The next frontier: understanding the neural basis of real-world visual search

In daily life, we select meaningful objects from meaningful scenes. Indeed, we usually do not direct attention to an empty region in space and we rarely decide to detect simple features such as horizontal lines or upward motion. Thus, although studies using simplified displays have been fundamental for our understanding of basic attention mechanisms, their results are not readily applicable to real-world scenarios. For example, what would be the behavioral prediction for detecting people in the

Neural basis of category-level search in real-world scenes

Recent neuroimaging studies have started to investigate the neural basis of visual search in real-world scenes 25, 26, 27, 28, 29, 30, 31, 32. In a series of studies 27, 28, 30, functional MRI (fMRI) activity was measured while participants detected the presence of objects from a cued category (cars, people) in briefly presented photographs of outdoor scenes like those in Figure 1A. The presented scenes were new to the participants, contained a large number of distracter objects, varied greatly

A framework for real-world search

The studies reviewed in the previous section have provided ample evidence that real-world search is aided by content-specific attentional templates that are implemented in object-selective cortex and carry a neural signature reminiscent of processes that are also used during the feedforward activation of object representations. We refer to these templates as the ‘what’ templates. In addition to the ‘what’ templates, recent studies have shown that spatial biases are generated during template

Concluding remarks and future directions

We have argued that attentional selection under naturalistic conditions uses additional and partly different mechanisms compared with those that have been studied using artificial displays. This provides only one example indicating that a full understanding of cognition will be possible only by considering the complexity of the real world 1, 66. There are many outstanding questions (Box 4). Addressing these questions will require consideration of findings from multiple fields, including not

References (102)

  • A.D. Wagner

    Parietal lobe contributions to episodic memory retrieval

    Trends Cogn. Sci.

    (2005)
  • C.E. Curtis et al.

    Persistent activity in the prefrontal cortex during working memory

    Trends Cogn. Sci.

    (2003)
  • M.A. Silver et al.

    Topographic maps in human frontal and parietal cortex

    Trends Cogn. Sci.

    (2009)
  • L. Itti et al.

    A saliency-based search mechanism for overt and covert shifts of visual attention

    Vision Res.

    (2000)
  • D. Nardo

    Stimulus-driven orienting of visuo-spatial attention in complex dynamic environments

    Neuron

    (2011)
  • C.D. Gilbert et al.

    Adult visual cortical plasticity

    Neuron

    (2012)
  • H.P. Op de Beeck et al.

    The neural basis of visual object learning

    Trends Cogn. Sci.

    (2010)
  • N.K. Logothetis

    Shape representation in the inferior temporal cortex of monkeys

    Curr. Biol.

    (1995)
  • H. Liu

    Timing, timing, timing: fast decoding of object information from intracranial field potentials in human visual cortex

    Neuron

    (2009)
  • S.G. Kuai

    Learning optimizes decision templates in the human visual cortex

    Curr. Biol.

    (2013)
  • M.M. Chun

    Contextual cueing of visual attention

    Trends Cogn. Sci.

    (2000)
  • I. Biederman

    Scene perception: detecting and judging objects undergoing relational violations

    Cogn. Psychol.

    (1982)
  • M.R. Greene et al.

    Recognition of natural scenes from global properties: seeing the forest without representing the trees

    Cogn. Psychol.

    (2009)
  • J.M. Wolfe

    Visual search in scenes involves selective and nonselective pathways

    Trends Cogn. Sci.

    (2011)
  • A. Oliva et al.

    The role of context in object recognition

    Trends Cogn. Sci.

    (2007)
  • J.M. Wolfe

    How fast can you change your mind? The speed of top-down guidance in visual search

    Vision Res.

    (2004)
  • J.J. Gibson

    The Ecological Approach to Visual Perception

    (1979)
  • J.M. Wolfe et al.

    What attributes guide the deployment of visual attention and how do they do it?

    Nat. Rev. Neurosci.

    (2004)
  • J.M. Wolfe

    Guided search: an alternative to the feature integration model for visual search

    J. Exp. Psychol. Hum. Percept. Perform.

    (1989)
  • J. Duncan et al.

    Visual search and stimulus similarity

    Psychol. Rev.

    (1989)
  • R. Desimone et al.

    Neural mechanisms of selective visual attention

    Annu. Rev. Neurosci.

    (1995)
  • M.R. Cohen et al.

    Attention improves performance primarily by reducing interneuronal correlations

    Nat. Neurosci.

    (2009)
  • P. Fries

    Modulation of oscillatory neuronal synchronization by selective visual attention

    Science

    (2001)
  • T.J. Buschman et al.

    Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices

    Science

    (2007)
  • G.G. Gregoriou

    High-frequency, long-range coupling between prefrontal and visual cortex during attention

    Science

    (2009)
  • Y.B. Saalmann

    The pulvinar regulates information transmission between cortical areas based on attention demands

    Science

    (2012)
  • S. Treue et al.

    Feature-based attention influences motion processing gain in macaque visual cortex

    Nature

    (1999)
  • N.P. Bichot

    Parallel and serial neural mechanisms for visual search in macaque area V4

    Science

    (2005)
  • L. Chelazzi

    A neural basis for visual search in inferior temporal cortex

    Nature

    (1993)
  • S.J. Luck

    Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex

    J. Neurophysiol.

    (1997)
  • E.K. Miller

    Neural mechanisms of visual working memory in prefrontal cortex of the macaque

    J. Neurosci.

    (1996)
  • S.C. Rao

    Integration of what and where in the primate prefrontal cortex

    Science

    (1997)
  • S. Kastner et al.

    Mechanisms of visual attention in the human cortex

    Annu. Rev. Neurosci.

    (2000)
  • M. Siegel

    Spectral fingerprints of large-scale neuronal interactions

    Nat. Rev. Neurosci.

    (2012)
  • T. Cukur

    Attention during natural vision warps semantic representation across the human brain

    Nat. Neurosci.

    (2013)
  • F. Guo

    Feature-independent neural coding of target detection during search of natural scenes

    J. Neurosci.

    (2012)
  • M.V. Peelen

    Neural mechanisms of rapid natural scene categorization in human visual cortex

    Nature

    (2009)
  • M.V. Peelen et al.

    A neural basis for real-world visual search in human occipitotemporal cortex

    Proc. Natl. Acad. Sci. U.S.A.

    (2011)
  • T.J. Preston

    Neural representations of contextual guidance in visual search of real-world scenes

    J. Neurosci.

    (2013)
  • K.N. Seidl

    Neural evidence for distracter suppression during visual search in real-world scenes

    J. Neurosci.

    (2012)
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