Suppression effects in feature-based attention.

Attending to a feature enhances visual processing of that feature, but it is less clear what occurs to unattended features. Single-unit recording studies in middle temporal (MT) have shown that neuronal modulation is a monotonic function of the difference between the attended and neuron's preferred direction. Such a relationship should predict a monotonic suppressive effect in psychophysical performance. However, past research on suppressive effects of feature-based attention has remained inconclusive. We investigated the suppressive effect for motion direction, orientation, and color in three experiments. We asked participants to detect a weak signal among noise and provided a partially valid feature cue to manipulate attention. We measured performance as a function of the offset between the cued and signal feature. We also included neutral trials where no feature cues were presented to provide a baseline measure of performance. Across three experiments, we consistently observed enhancement effects when the target feature and cued feature coincided and suppression effects when the target feature deviated from the cued feature. The exact profile of suppression was different across feature dimensions: Whereas the profile for direction exhibited a "rebound" effect, the profiles for orientation and color were monotonic. These results demonstrate that unattended features are suppressed during feature-based attention, but the exact suppression profile depends on the specific feature. Overall, the results are largely consistent with neurophysiological data and support the feature-similarity gain model of attention.

[1]  John T. Serences,et al.  Feature- and Object-Based Attentional Modulation in the Human Visual System , 2014 .

[2]  Leslie G. Ungerleider,et al.  Mechanisms of visual attention in the human cortex. , 2000, Annual review of neuroscience.

[3]  Christian M. Stoppel,et al.  Separable Mechanisms Underlying Global Feature-Based Attention , 2012, The Journal of Neuroscience.

[4]  Bevil R. Conway,et al.  Applicability of white-noise techniques to analyzing motion responses. , 2010, Journal of neurophysiology.

[5]  Rhea T. Eskew,et al.  Higher order color mechanisms: A critical review , 2009, Vision Research.

[6]  Marisa Carrasco,et al.  Feature-based attention modulates orientation-selective responses in human visual cortex , 2010 .

[7]  D. Butts,et al.  Tuning Curves, Neuronal Variability, and Sensory Coding , 2006, PLoS biology.

[8]  M. Tinker.  Dvorine pseudo-isochromatic plates. (Rev. Ed.). , 1955 .

[9]  John H. R. Maunsell,et al.  Feature-based attention in visual cortex , 2006, Trends in Neurosciences.

[10]  Scott D. Brown,et al.  Perceptual consequences of feature-based attentional enhancement and suppression. , 2012, Journal of vision.

[11]  Preeti Verghese,et al.  The psychophysics of visual search , 2000, Vision Research.

[12]  D. Heeger,et al.  Decoding and Reconstructing Color from Responses in Human Visual Cortex , 2009, The Journal of Neuroscience.

[13]  G. Boynton,et al.  Effects of feature-based attention on the motion aftereffect at remote locations , 2006, Vision Research.

[14]  Anthony J. Movshon,et al.  Optimal representation of sensory information by neural populations , 2006, Nature Neuroscience.

[15]  M. Carrasco,et al.  How spatial and feature-based attention affect the gain and tuning of population responses , 2009, Vision Research.

[16]  Bevil R. Conway,et al.  Specialized Color Modules in Macaque Extrastriate Cortex , 2007, Neuron.

[17]  J. Reynolds,et al.  Attentional modulation of visual processing. , 2004, Annual review of neuroscience.

[18]  P. Verghese.  Visual Search and Attention A Signal Detection Theory Approach , 2001, Neuron.

[19]  John K. Tsotsos,et al.  Attending to orientation results in an inhibitory surround in orientation space , 2008, Perception & psychophysics.

[20]  G. Boynton,et al.  Global effects of feature-based attention in human visual cortex , 2002, Nature Neuroscience.

[21]  M. Carrasco.  Visual attention: The past 25 years , 2011, Vision Research.

[22]  Peter Neri,et al.  Attentional control of sensory tuning in human visual perception. , 2012, Journal of neurophysiology.

[23]  S. Treue,et al.  Feature-Based Attention Increases the Selectivity of Population Responses in Primate Visual Cortex , 2004, Current Biology.

[24]  P. Lennie,et al.  The machinery of colour vision , 2007, Nature Reviews Neuroscience.

[25]  Geoffrey M Boynton,et al.  The Representation of Behavioral Choice for Motion in Human Visual Cortex , 2007, The Journal of Neuroscience.

[26]  Stefan Treue,et al.  Different populations of neurons contribute to the detection and discrimination of visual motion , 2001, Vision Research.

[27]  Taosheng Liu,et al.  Global feature-based attention to orientation. , 2011, Journal of vision.

[28]  Preeti Verghese,et al.  Attention to locations and features: different top-down modulation of detector weights. , 2005, Journal of vision.

[29]  F A Wichmann,et al.  Ning for Helpful Comments and Suggestions. This Paper Benefited Con- Siderably from Conscientious Peer Review, and We Thank Our Reviewers the Psychometric Function: I. Fitting, Sampling, and Goodness of Fit , 2001 .

[30]  Alex L. White,et al.  Feature-based attention involuntarily and simultaneously improves visual performance across locations. , 2011, Journal of vision.

[31]  W. Newsome,et al.  A selective impairment of motion perception following lesions of the middle temporal visual area (MT) , 1988, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[32]  M. Masson,et al.  Using confidence intervals in within-subject designs , 1994, Psychonomic bulletin & review.

[33]  Matthew F. Peterson,et al.  Statistical decision theory to relate neurons to behavior in the study of covert visual attention , 2009, Vision Research.

[34]  T. Albright.  Direction and orientation selectivity of neurons in visual area MT of the macaque. , 1984, Journal of neurophysiology.

[35]  Paul S Khayat,et al.  Attention Differentially Modulates Similar Neuronal Responses Evoked by Varying Contrast and Direction Stimuli in Area MT , 2010, The Journal of Neuroscience.

[36]  Bevil R. Conway,et al.  Space-time maps and two-bar interactions of different classes of direction-selective cells in macaque V-1. , 2003, Journal of neurophysiology.

[37]  Frans A. J. Verstraten,et al.  Attentional modulation of adaptation to two-component transparent motion , 1995, Vision Research.

[38]  Viola S. Störmer,et al.  Feature-Based Attention Elicits Surround Suppression in Feature Space , 2014, Current Biology.

[39]  J. P. Thomas,et al.  A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays , 2000, Perception & psychophysics.

[40]  Taosheng Liu,et al.  Constant spread of feature-based attention across the visual field , 2011, Vision Research.

[41]  C. Ripamonti,et al.  Computational Colour Science Using MATLAB , 2004 .

[42]  S. Luck,et al.  Discrete fixed-resolution representations in visual working memory , 2008, Nature.

[43]  D. Regan,et al.  Postadaptation orientation discrimination. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[44]  Marisa Carrasco,et al.  Feature-Based Attention Modulates Orientation-Selective Responses in Human Visual Cortex , 2007, Neuron.

[45]  Stefan Treue,et al.  Feature-based attention influences motion processing gain in macaque visual cortex , 1999, Nature.

[46]  G. Boynton,et al.  Global feature-based attention for motion and color , 2003, Vision Research.