An Extended Normalization Model of Attention Accounts for Feature-Based Attentional Enhancement of Both Response and Coherence Gain

Schwedhelm, Philipp; Krishna, B. Suresh; Treue, Stefan

doi:10.1371/journal.pcbi.1005225

Cited by 21 publications

(20 citation statements)

References 48 publications

(69 reference statements)

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“…The best fit of our population profiles by the NMoA is presented in S14A Fig and is comparable to the FSGM fit yet requires a large array of assumptions about the properties of the neural population at hand. However, the NMoA [37,38] can also be parameterized to account for de-aligned feature attention by adding 1 free parameter to the model. Matching the success of the eFSGM, this off-target attention also improves the prediction of the NMoA (see S2 Text and S14 Fig, compare B versus A).…”

Section: Resultsmentioning

confidence: 99%

Strategic deployment of feature-based attentional gain in primate visual cortex

et al. 2019

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Attending to visual stimuli enhances the gain of those neurons in primate visual cortex that preferentially respond to the matching locations and features (on-target gain). Although this is well suited to enhance the neuronal representation of attended stimuli, it is nonoptimal under difficult discrimination conditions, as in the presence of similar distractors. In such cases, directing attention to neighboring neuronal populations (off-target gain) has been shown to be the most efficient strategy, but although such a strategic deployment of attention has been shown behaviorally, its underlying neural mechanisms are unknown. Here, we investigated how attention affects the population responses of neurons in the middle temporal (MT) visual area of rhesus monkeys to bidirectional movement inside the neurons’ receptive field (RF). The monkeys were trained to focus their attention onto the fixation spot or to detect a direction or speed change in one of the motion directions (the “target”), ignoring the distractor motion. Population activity profiles were determined by systematically varying the patterns’ directions while maintaining a constant angle between them. As expected, the response profiles show a peak for each of the 2 motion directions. Switching spatial attention from the fixation spot into the RF enhanced the peak representing the attended stimulus and suppressed the distractor representation. Importantly, the population data show a direction-dependent attentional modulation that does not peak at the target feature but rather along the slopes of the activity profile representing the target direction. Our results show that attentional gains are strategically deployed to optimize the discriminability of target stimuli, in line with an optimal gain mechanism proposed by Navalpakkam and Itti.

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Section: Resultsmentioning

confidence: 99%

Strategic deployment of feature-based attentional gain in primate visual cortex

et al. 2019

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“…A contrast gain effect is reflected in the contrast response or psychometric functions as a gain multiplication on the effective strength of sensory input (e.g., Martínez-Trujillo & Treue, 2002 ; Reynolds, Pasternak, & Desimone, 2000 ; Schwedhelm, Krishna, & Treue, 2016 ), which therefore results in a horizontal shift of the function ( Figure 1 a). When considering the underlying neural mechanism for a contrast gain modulation by higher level cognitive factors such as VSTM load or attention (as opposed to actual stimulus input factors), a contrast gain modulation is proposed to reflect an interactive modulation of the stimulus-evoked response in sensory visual cortex neurons, reflecting a modulation of their sensitivity during their processing of the stimulus contrast and thus making it appear as a change in the effective strength of the sensory input in the contrast response function (e.g., Ling & Carrasco, 2006 ).…”

Section: Introductionmentioning

confidence: 99%

Effects of visual short-term memory load and attentional demand on the contrast response function

Konstantinou

Lavie

2020

Journal of Vision

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Visual short-term memory (VSTM) load leads to impaired perception during maintenance. Here, we fitted the contrast response function to psychometric orientation discrimination data while also varying attention demand during maintenance to investigate: (1) whether VSTM load effects on perception are mediated by a modulation of the contrast threshold, consistent with contrast gain accounts, or by the function asymptote (1 lapse rate), consistent with response gain accounts; and (2) whether the VSTM load effects on the contrast response function depend on the availability of attentional resources. We manipulated VSTM load via the number of items in the memory set in a color and location VSTM task and assessed the contrast response function for an orientation discrimination task during maintenance. Attention demand was varied through spatial cuing of the orientation stimulus. Higher VSTM load increased the estimated contrast threshold of the contrast response function without affecting the estimated asymptote, but only when the discrimination task demanded attention. When attentional demand was reduced (in the cued conditions), the VSTM load effects on the contrast threshold were eliminated. The results suggest that VSTM load reduces perceptual sensitivity by increasing contrast thresholds, suggestive of a contrast gain modulation mechanism, as long as the perceptual discrimination task demands attention. These findings support recent claims that attentional resources are shared between perception and VSTM maintenance processes.

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“…Normalization Model of Attention (NMA) (Reynolds and Heeger, 2009) (also see, Boynton, 2009;Lee and Maunsell, 2009;Schwedhelm et al, 2016;Ni and 93 Maunsell, 2017).…”

Section: Introductionmentioning

confidence: 99%

Different computations underlie overt and covert spatial attention

Pan

Carrasco

2020

Preprint

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Perception and action are tightly coupled: visual responses at the saccade target are enhanced right before saccade onset. This phenomenon, presaccadic attention, is a form of overt attention—deployment of visual attention with concurrent eye movements. Presaccadic attention is well-documented, but its underlying computational process remains unknown. This is in stark contrast with covert attention—deployment of visual attention without concurrent eye movements—for which the computational process is well characterized. Here, a series of psychophysical experiments reveal that presaccadic attention modulates visual performance only via response gain changes even when attention field size increases, violating the predictions of a normalization model of attention, which has been widely used to explain the computations underlying covert attention. Our empirical results and model comparisons reveal that the perceptual modulations by overt and covert spatial attention are mediated through different computations.

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An Extended Normalization Model of Attention Accounts for Feature-Based Attentional Enhancement of Both Response and Coherence Gain

Cited by 21 publications

References 48 publications

Strategic deployment of feature-based attentional gain in primate visual cortex

Strategic deployment of feature-based attentional gain in primate visual cortex

Effects of visual short-term memory load and attentional demand on the contrast response function

Different computations underlie overt and covert spatial attention

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