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Attentional spreading over feature attributes and feature dimensions:Distributed top-down modulation or joint neural coding?

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How the brain solves this problem to boost the processing of combinations of different features that are represented across multiple neural areas is largely unknown... Reaction times (RTs) recorded under different cueing conditions demonstrated the co-selection of unattended features, with attention spreading from the attended feature attribute in a particular feature dimension to other feature attributes and other feature dimensions... Importantly, this processing benefit was not restricted to the task-relevant object but extended to the unattended object... Consequently, top-down modulation of neural activity in lower visual areas is broadly tuned, targeting all cells representing the cued feature dimension(s) with only a weak preference for the cued feature attribute(s)... As a result, attention spreads to uncued feature attributes and to jointly cued feature dimensions... In the second model we assume joint coding of stimulus features such that neurons having a preference for a particular motion direction also have a preference for a specific color... We also assume that neurons are not always perfectly tuned to their preferred feature(s), thus providing a (small) response to non-preferred feature values as well... Attentional feedback in this model precisely targets cells tuned for the cued feature attribute, or the combination of attributes... In this approach, attentional spreading to uncued feature dimensions is mediated by joint tuning, whereas spreading to uncued feature attributes in the same feature dimension is mediated by imperfect tuning... It turns out that both approaches, with appropriately chosen parameters, can qualitatively explain the differences in RTs between the stimulation conditions (Fig. 1)... The next step is to develop a neurophysiologically plausible model that allows for explicit predictions for electrophysiological experiments to critically test the proposed mechanisms.

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Comparison of Median RT. (A) Experimental data of Exp. 1 from Ref. [1]. (B) Data from first model. (C) Data from second model. Different cuing conditions on x-axis: C: correct, W: wrong, F: feature, O: object. Left column shows RT to a speed change, right column to a color change.
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Figure 1: Comparison of Median RT. (A) Experimental data of Exp. 1 from Ref. [1]. (B) Data from first model. (C) Data from second model. Different cuing conditions on x-axis: C: correct, W: wrong, F: feature, O: object. Left column shows RT to a speed change, right column to a color change.

Mentions: It turns out that both approaches, with appropriately chosen parameters, can qualitatively explain the differences in RTs between the stimulation conditions (Fig. 1). The next step is to develop a neurophysiologically plausible model that allows for explicit predictions for electrophysiological experiments to critically test the proposed mechanisms.


Attentional spreading over feature attributes and feature dimensions:Distributed top-down modulation or joint neural coding?
Comparison of Median RT. (A) Experimental data of Exp. 1 from Ref. [1]. (B) Data from first model. (C) Data from second model. Different cuing conditions on x-axis: C: correct, W: wrong, F: feature, O: object. Left column shows RT to a speed change, right column to a color change.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4697591&req=5

Figure 1: Comparison of Median RT. (A) Experimental data of Exp. 1 from Ref. [1]. (B) Data from first model. (C) Data from second model. Different cuing conditions on x-axis: C: correct, W: wrong, F: feature, O: object. Left column shows RT to a speed change, right column to a color change.
Mentions: It turns out that both approaches, with appropriately chosen parameters, can qualitatively explain the differences in RTs between the stimulation conditions (Fig. 1). The next step is to develop a neurophysiologically plausible model that allows for explicit predictions for electrophysiological experiments to critically test the proposed mechanisms.

View Article: PubMed Central - HTML

AUTOMATICALLY GENERATED EXCERPT
Please rate it.

How the brain solves this problem to boost the processing of combinations of different features that are represented across multiple neural areas is largely unknown... Reaction times (RTs) recorded under different cueing conditions demonstrated the co-selection of unattended features, with attention spreading from the attended feature attribute in a particular feature dimension to other feature attributes and other feature dimensions... Importantly, this processing benefit was not restricted to the task-relevant object but extended to the unattended object... Consequently, top-down modulation of neural activity in lower visual areas is broadly tuned, targeting all cells representing the cued feature dimension(s) with only a weak preference for the cued feature attribute(s)... As a result, attention spreads to uncued feature attributes and to jointly cued feature dimensions... In the second model we assume joint coding of stimulus features such that neurons having a preference for a particular motion direction also have a preference for a specific color... We also assume that neurons are not always perfectly tuned to their preferred feature(s), thus providing a (small) response to non-preferred feature values as well... Attentional feedback in this model precisely targets cells tuned for the cued feature attribute, or the combination of attributes... In this approach, attentional spreading to uncued feature dimensions is mediated by joint tuning, whereas spreading to uncued feature attributes in the same feature dimension is mediated by imperfect tuning... It turns out that both approaches, with appropriately chosen parameters, can qualitatively explain the differences in RTs between the stimulation conditions (Fig. 1)... The next step is to develop a neurophysiologically plausible model that allows for explicit predictions for electrophysiological experiments to critically test the proposed mechanisms.

No MeSH data available.


Related in: MedlinePlus