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Cited by 195Visual Attention and Saliency DetectionVisual perception and processing mechanismsNeural and Behavioral Psychology Studies

Altering Spatial Priority Maps via Reward-Based Learning

Open access
Chelazzi, L., E to inova, J., Calletti, R., Lo Gerfo, E., Sani, I., Della Libera, C., Santandrea, E.·2014·Journal of Neuroscience
DOI 10.1523/jneurosci.0277-14.2014PMC PMC6608215
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Abstract

Spatial priority maps are real-time representations of the behavioral salience of locations in the visual field, resulting from the combined influence of stimulus driven activity and top-down signals related to the current goals of the individual. They arbitrate which of a number of (potential) targets in the visual scene will win the competition for attentional resources. As a result, deployment of visual attention to a specific spatial location is determined by the current peak of activation (corresponding to the highest behavioral salience) across the map. Here we report a behavioral study performed on healthy human volunteers, where we demonstrate that spatial priority maps can be shaped via reward-based learning, reflecting long-lasting alterations (biases) in the behavioral salience of specific spatial locations. These biases exert an especially strong influence on performance under conditions where multiple potential targets compete for selection, conferring competitive advantage to targets presented in spatial locations associated with greater reward during learning relative to targets presented in locations associated with lesser reward. Such acquired biases of spatial attention are persistent, are nonstrategic in nature, and generalize across stimuli and task contexts. These results suggest that reward-based attentional learning can induce plastic changes in spatial priority maps, endowing these representations with the "intelligent" capacity to learn from experience.

AI snapshot

Written from the paper’s full text.

TL;DR

A behavioral study in healthy human volunteers shows that reward-based training can durably bias spatial priority maps, giving a competitive advantage to targets appearing at locations previously associated with higher reward. These biases persisted after a 4 d delay without reward feedback and generalized across stimuli and task contexts.

Key findings

  • In double-target trials where only one target was reported, the probability of reporting the target at an 80Hh location versus a 20Lh location increased by 0.084 (8.4%) from baseline to test (t(23) = 3.084, p = 0.005, r = 0.541); the 50Hh–50Lh comparison was unchanged (Δ = −0.0028, t(23) = 0.084, p = 0.934).
  • The theoretical reward imbalance correlated strongly with the acquired change in attentional priority: R² = 0.921, F(1,6) = 69.9494, p = 0.0016.
  • Overall double-target performance improved from baseline to test: correctly identified targets rose from 66.51 ± 3.19% to 77.22 ± 4.14% (t(23) = 4.0302, p < 0.001, r = 0.643); double reports increased by 12.83 ± 2.13%, single reports decreased by 7.76 ± 2.08%, and null reports showed a trend toward decrease (−5.08 ± 2.66%, p = 0.069).
  • In the single-target condition, accuracy improved with session (F(1,23) = 8.937, p = 0.007) but was not influenced by reward level (F(3,69) = 0.214, p = 0.886), indicating the reward effect was detectable mainly under cross-target competition.

Methods

  • Twenty-four healthy right-handed volunteers (9 males; mean ± SD age, 21.04 ± 1.9 years) completed baseline, two training sessions (800 trials each), and a test session after a 4 d delay.
  • Training required discriminating the upper-triangle color of a single target among seven nontargets; correct responses yielded high (10 points) or low (1 point) reward, with reward probability biased by location (80Hh, 50Hh, 50Lh, 20Lh) and hemifield counterbalanced across participants.
  • Baseline/test used a visual search task with one or two targets (letters/digits) among seven or six nonalphanumeric distractors, displayed for ~70 ms; 640 trials total (192 single-target, 448 double-target), with no reward feedback. Analyses used ANOVAs, t-tests, and linear regression.

Limitations

  • The paper does not include a formal limitations section. It states that reward effects were evident only under cross-target competition and not in the single-target condition, and it offers no neural/mechanistic data; candidate brain substrates are discussed as speculative.
  • The authors consider an alternative account involving hippocampal/contextual spatial memory but note it would make the lack of a single-target effect less obvious; this remains unresolved.
  • Evident from the text: the sample was small and mostly students, the training reward schedule was predetermined and deceptive, and the study is purely behavioral, so the proposed plasticity in spatial priority maps is inferred rather than directly measured.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1523/jneurosci.0277-14.2014

Cites

Statistics

Nothing to recompute.

Claims the paper makes

0 of 41 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    In the baseline single-target condition, participants correctly identified the target on 57.1 ± 2.9% of trials.

    “In the single-target condition, on average participants correctly identified the target on 57.1 Ϯ 2.9% of the trials.”
    Quote in the paperNot a substantial claim
  • Findingown data

    RT decreased significantly along subsequent blocks (F(3,69)=23.492, p<0.001, partial eta^2=0.505).

    “Although RT decreased significantly along subsequent blocks (F (3,69) ϭ 23.492, p Ͻ 0.001, ␩ p 2 ϭ 0.505; Fig. 2A)”
    Quote in the paperNot a substantial claim
  • Findingown data

    There was no evidence of an effect of reward level on RT (main effect F(3,69)=0.152, p=0.928; block by reward level interaction F(9,207)=0.657, p=0.747).

    “there was no evidence of an effect of reward level (main effect of reward level: F (3,69) ϭ 0.152, p ϭ 0.928; block by reward level interaction: F (9,207) ϭ 0.657, p ϭ 0.747).”
    Quote in the paperSubstantial claim
  • Findingown data

    Accuracy of report increased significantly along subsequent training blocks (F(3,69)=44.966, p<0.001, partial eta^2=0.662).

    “As shown in Figure 2A, accuracy of report increased significantly along subsequent training blocks (F (3,69) ϭ 44.966, p Ͻ 0.001, ␩ p 2 ϭ 0.662).”
    Quote in the paperSubstantial claim
  • Findingown data

    At test, spatial locations associated with an overall more positive outcome during training (80Hh) were prioritized with respect to spatial locations associated with an overall less positive outcome (20Lh).

    “tions associated with an overall more positive outcome during training (80Hh) were prioritized with respect to spatial locations associated with an overall less positive outcome (20Lh).”
    Quote in the paperSubstantial claim
  • May combine two claims. 18
  • The quote only partly states this claim. 1
  • Classified as probably not a substantial claim. 16

  • May combine two claims.

    Findingown data

    Accuracy was not influenced by reward level during training, either as a main effect (F(3,69)=0.087, p=0.967) or as a block by reward level interaction (F(9,207)=0.328, p=0.965).

    “Instead, accuracy was not influenced by reward level during training either in the form of a main effect (F (3,69) ϭ 0.087, p ϭ 0.967) or in the form of a block by reward level interaction (F (9,207) ϭ 0.328, p ϭ 0.965).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    During the first training session, accuracy of target discrimination averaged 71.9 ± 1.9% (SEM) and RT averaged 902.7 ± 33.79 ms.

    “During training, performance of the participants started off relatively poor, with accuracy of target discrimination corresponding on average to 71.9 Ϯ 1.9% (SEM) and RT corresponding on average to 902.7 Ϯ 33.79 ms during the first training session”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Participants were well aware of the reward feedback they received on each trial, as indicated by high performance (93 ± 2% and 95.5 ± 1.8% during the first and second training session, respectively) in reporting the amount of reward earned when queried.

    “Participants were nonetheless well aware of the reward feedback they received on each trial, as indicated by a high level of performance (93 Ϯ 2% and 95.5 Ϯ 1.8%, on average, during the first and second training session, respectively) in reporting the amount of reward earned on the current trial, when specifically queried”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    During the second training session, accuracy averaged 81.9 ± 2.4% and RT averaged 765.75 ± 23.43 ms.

    “Participants then achieved an overall relatively high proficiency, with accuracy corresponding on average to 81.9 Ϯ 2.4% and RT corresponding on average to 765.75 Ϯ 23.43 ms during the second training session.”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data

    In the test session after a 4 d delay, the incidence of double reports increased by 12.83 ± 2.13% relative to baseline (t(23)=6.037, p<0.001, r=0.783).

    “with a significant increase in the incidence of double reports (i.e., trials in which participants reported both targets correctly: 12.83 Ϯ 2.13%; t (23) ϭ 6.037, p Ͻ 0.001, r ϭ 0.783)”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Reward-dependent alterations in target identification performance occurred with a high degree of spatial resolution, affecting spatial locations associated with a critical reward imbalance (80Hh and 20Lh), without spreading to nearby locations (50Hh or 50Lh) for which rewards were delivered in a balanced fashion.

    “Reward-dependent alterations in target identification performance occurred with a high degree of spatial resolution, affecting spatial locations associated with a critical reward imbalance (80Hh and 20Lh), without spreading to nearby locations (50Hh or 50Lh) for which rewards were delivered in a balanced fashion.”
    • Also stated in: § Discussion · plain
      “affected performance with a high degree of spatial resolution”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The percentage of correctly identified targets in the double-target condition was 66.51 ± 3.19% during baseline and rose to 77.22 ± 4.14% during the test phase, a significant learning effect (t(23)=4.0302, p<0.001, r=0.643).

    “Whereas the percentage of correctly identified targets in the double target condition corresponded to 66.51 Ϯ 3.19% during the baseline phase, this percentage rose to 77.22 Ϯ 4.14% during the test phase, reflecting a significant learning effect (t (23) ϭ 4.0302, p Ͻ 0.001, r ϭ 0.643).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In the baseline single-target condition, accuracy of report varied significantly across display locations (F(7,161)=19.176, p<0.001, partial eta^2=0.455), with better performance for most lateralized locations compared with locations closer to the vertical midline.

    “accuracy of report varied significantly across display locations (F (7,161) ϭ 19.176, p Ͻ 0.001, ␩ p 2 ϭ 0.455), with better performance for most lateralized locations compared with locations closer to the vertical midline”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    The stimulus display was designed so that both target shapes appeared the same number of times and with the same probability at all spatial locations in the circular array.

    “The stimulus display was designed so that both target shapes (with an upper white and an upper black triangle) appeared the same number of times and with the same probability at all spatial locations in the circular array.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Spatial priority maps can be shaped via reward-based learning, reflecting long-lasting alterations (biases) in the behavioral salience of specific spatial locations.

    “Here we report a behavioral study performed on healthy human volunteers, where we demonstrate that spatial priority maps can be shaped via reward-based learning, reflecting long-lasting alterations (biases) in the behavioral salience of specific spatial locations.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The baseline-to-test changes in performance are attributable to reward-based training rather than repeated exposure to the task or other practice effects.
    • Rests on an assumption: The spatial reward schedule during training is learned and represented spatially by participants.

  • May combine two claims.

    Interpretationown data

    The reward-based training regimen leads to long-lasting alterations in spatial priority maps, in turn modifying the ability of observers to locate and identify task-relevant information at various locations in the visual field.

    “we could provide clear-cut evidence that our reward-based training regimen leads to long-lasting alterations in spatial priority maps, in turn modifying the ability of our observers to locate and identify task-relevant information at the various locations in the visual field.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The baseline-to-test changes in performance are attributable to reward-based training rather than repeated exposure to the task or other practice effects.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductreasoning

    Different spatial configurations of reward assignments across the eight locations were created so that individual participants had their own reward schedule, controlling for the possibility that effects produced by the reward manipulation could result from a mere preference for particular locations in space.

    “To avoid the possible confound stemming from a fixed association of the predetermined reward biases with specific spatial locations, we created different spatial configurations of reward assignments across the eight locations, so that individual participants had their own reward schedule.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Spatial priority maps are real-time representations of the behavioral salience of locations in the visual field, resulting from the combined influence of stimulus-driven activity and top-down signals related to the current goals of the individual.

    “Spatial priority maps are real-time representations of the behavioral salience of locations in the visual field, resulting from the combined influence of stimulus driven activity and top-down signals related to the current goals of the individual.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Itti and Koch, 2001

      Not checked in the free run.

    • cites Thompson and Bichot, 2005

      Not checked in the free run.

    • cites Fecteau and Munoz, 2006

      Not checked in the free run.

  • May combine two claims.

    Study design and conductnone given

    The reward value obtainable by responding correctly on each trial was fully predetermined and decoupled from actual velocity and overall accuracy of responses, and balanced across all experimental conditions.

    “Although participants were told that the rewards received depended on their performance, the reward value that could be obtained by responding correctly on each trial was fully predetermined, so that gained values were completely decoupled from actual velocity and overall accuracy of responses, and balanced across all experimental conditions, being high or low with the same overall probability (50”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The reward-based training protocol is able to induce considerable and durable changes in the attentional priority of specific spatial locations, and these plastic changes can occur with a high degree of spatial resolution.

    “Together, these results demonstrate that our reward-based training protocol is able to induce considerable and durable changes in the attentional priority of specific spatial locations and that these plastic changes can occur with a high degree of spatial resolution.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Performance in the double-target single-report condition reflects the relative attentional priority of the two target locations.
    • Rests on an assumption: The spatial reward schedule during training is learned and represented spatially by participants.

  • Classified as probably not a substantial claim.

    Premisecitation

    Spatial priority maps guide attention (and behavior) on the basis of a 'winner-take all' principle, wherein attention is deployed to the location corresponding to peak activity in the map.

    “Spatial priority maps guide attention (and behavior) on the basis of a “winner-take all” principle, wherein attention is deployed to the location corresponding to peak activity in the map (Itti and Koch, 2001;Thompson and Bichot, 2005;Fecteau and Munoz, 2006;Bisley and Goldberg, 2010).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Itti and Koch, 2001

      Not checked in the free run.

    • cites Thompson and Bichot, 2005

      Not checked in the free run.

    • cites Fecteau and Munoz, 2006

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Some of the same brain structures have been demonstrated to be highly sensitive to reward signals, although within the context of behavioral paradigms that are clearly different from the one used here, namely, paradigms investigating value-driven choice behavior (with reward acting as incentive) and not involving any learning component.

    “Interestingly, some of the same brain structures have been demonstrated to be highly sensitive to reward signals, although within the context of behavioral paradigms that are clearly different from the one used here, namely, paradigms investigating value-driven choice behavior (with reward acting as incentive) and not involving any learning component.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Neural activity in parietal and frontal regions, and in the caudate nucleus, differentially encodes the expected reward value associated with a given object or location, demonstrating sensitivity to the motivational salience and/or valence of visual stimuli and locations.

    “Neural activity in these regions has been shown to differentially encode the expected reward value associated with a given object or location, demonstrating the sensitivity of parietal and frontal regions, and of the caudate nucleus, to the motivational salience and/or valence of visual stimuli and locations (Leon and Shadlen, 1999;Platt and Glimcher, 1999;Glimcher, 2003”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Leon and Shadlen, 1999

      Not checked in the free run.

    • cites Platt and Glimcher, 1999

      Not checked in the free run.

    • cites Glimcher, 2003

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationown data

    The spatial priority map illustrates the competitive advantage (or disadvantage) acquired by spatial locations associated with specific reward levels as a result of the training procedure.

    “The spatial priority map nicely illustrates the competitive advantage (or disadvantage) acquired by spatial locations associated with specific reward levels as a result of the training procedure.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Spatial priority maps are topographically organized maps of the external visual world, in which the behavioral priority of locations (or objects) is proportionally represented by differential neuronal activity.

    “Spatial priority maps are topographically organized maps of the external visual world, in which the behavioral priority of locations (or objects) is proportionally represented by differential neuronal activity (Thompson and Bichot, 2005;Fecteau and Munoz, 2006;Bisley and Goldberg, 2010).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Thompson and Bichot, 2005

      Not checked in the free run.

    • cites Fecteau and Munoz, 2006

      Not checked in the free run.

    • cites Bisley and Goldberg, 2010

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    Cortical regions in the posterior parietal and frontal cortex have been identified as candidate spatial priority maps and can be regarded as potential substrates of the learning effects described here, although the contribution of subcortical structures including the superior colliculus and the caudate nucleus should not be excluded.

    “Based on electrophysiological evidence, cortical regions in the posterior parietal (Gottlieb et al., 1998;Kusunoki et al., 2000;Ipata et al., 2009;Bisley and Goldberg, 2010; e.g., LIP) and frontal cortex (Thompson and Bichot, 2005;Thompson et al., 2005; e.g., FEF) have been identified as candidate spatial priority maps (Serences and Yantis, 2007;Jerde et al., 2012;Ptak, 2012;Jerde and Curtis, 2013”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Gottlieb et al., 1998

      Not checked in the free run.

    • cites Thompson and Bichot, 2005

      Not checked in the free run.

    • cites Serences and Yantis, 2007

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    The results do not reflect a general facilitation in attentional orienting toward the visual hemifield more frequently associated with positive outcome during training, but rather an alteration in the attentional priority of discrete spatial locations based on the associated high (or low) probability of positive outcome.

    “Hence, our results do not reflect a general facilitation in attentional orienting toward the visual hemifield more frequently associated with positive outcome during training, but rather an alteration in the attentional priority of discrete spatial locations based on the associated high (or low) probability of positive outcome.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    The observed changes in performance for certain spatial locations were measured after a 4 d delay from the training phase, and in an extinction regimen, when rewards were no longer available, being therefore nonstrategic in nature.

    “Importantly, the observed changes in performance for certain spatial locations were measured after a 4 d delay from the training phase, and in an extinction regimen, when rewards were no longer available, being therefore nonstrategic in nature (Chelazzi et al., 2013).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Chelazzi et al., 2013

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Attentional resources can be systematically oriented toward the spatial location(s) associated with the maximum expected reward in the current trial.

    “For example, attentional resources can be systematically oriented toward the spatial location(s) associated with the maximum expected reward in the current trial (Serences, 2008;Navalpakkam et al., 2009).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Serences, 2008

      Not checked in the free run.

    • cites Navalpakkam et al., 2009

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    The described effects in Camara et al. (2013) only marginally relate to our findings as they entail a short-term influence of reward, transitorily affecting performance without systematically altering the attentional priority of specific locations.

    “At any rate, the described effects only marginally relate to our findings as they entail a short-term influence of reward, transitorily affecting performance without systematically altering the attentional priority of specific locations.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    In the present study, reward was used as a feedback on performance and was demonstrated to act as a teaching signal to shape attention and behavior for future episodes of selection involving the same locations.

    “Instead, in our study, reward was used as a feedback on performance and was demonstrated to act as a teaching signal to shape attention and behavior for future episodes of selection involving the same locations (Chelazzi et al., 2013).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Chelazzi et al., 2013

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    A recent study revealed a significant intertrial influence of valence information associated with specific spatial locations, dynamically affecting the online deployment of spatial attention.

    “More directly related to the present research, a recent study revealed a significant intertrial influence of valence information associated with specific spatial locations, dynamically affecting the online deployment of spatial attention (Camara et al., 2013).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Camara et al., 2013

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    A recent study demonstrated that reward associations can magnify the influence exerted by acquired spatial memories on current visual search processes within natural visual scenes, resulting in a reward-associated memory-based orienting of attention in space.

    “Interestingly, a recent study demonstrated that reward associations can magnify the influence exerted by acquired spatial memories on current visual search processes within natural visual scenes, resulting in a reward-associated memory-based orienting of attention in space (Doallo et al., 2013).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Doallo et al., 2013

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Visual exploration and attentional selection of visual targets can be biased in the short-term by an asymmetrical distribution of available rewards across space.

    “In the same vein, an elegant study (Lucas et al., 2013) has recently demonstrated that visual exploration and attentional selection of visual targets can be biased in the short-term by an asymmetrical distribution of available rewards across space.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Lucas et al., 2013

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    In value learning studies, responses were slower for probes (or targets) appearing in the spatial location previously occupied by highly rewarded items, reflecting the typical cost in performance associated with inhibition of return.

    “Participants learned to associate specific stimuli (or features) with more or less positive outcomes in a value learning training phase; afterward, when the same stimuli were used as uninformative cues in a typical probe task (Rutherford et al., 2010) or as irrelevant distractors in a visual search array (Anderson et al., 2011b), responses were slower for probes (or targets) appearing in the”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Rutherford et al., 2010

      Not checked in the free run.

    • cites Anderson et al., 2011b

      Not checked in the free run.

    • cites Klein, 2000

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationnone given

    The present study addresses a different and more dramatic effect of reward on attentional processing in the spatial domain.

    “What we address here is a different and more dramatic effect of reward on attentional processing in the spatial domain.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    If available rewards were asymmetrically distributed from the left to the right of the target array in a 'gambling' search task, both healthy participants and neglect patients developed a short-lasting leftward bias in target choice.

    “Specifically, if available rewards were asymmetrically distributed from the left to the right of the target array in a “gambling” search task, both healthy participants and neglect patients developed a short-lasting leftward bias in target choice (Lucas et al., 2013), likely reflecting the enactment of specific cognitive strategies aimed at maximizing the earning of reward during the experiment.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Lucas et al., 2013

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Space-based attentional guidance following an informative exogenous sensory cue is relatively impermeable to reward-based influences.

    “Interestingly, a recent study demonstrated that space-based attentional guidance following an informative exogenous sensory cue is relatively impermeable to reward-based influences (Shomstein and Johnson, 2013), perhaps implying that basic, hard-wired principles governing attentional deployment in space are rather strong and inflexible.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Shomstein and Johnson, 2013

      Not checked in the free run.

33 of 33

  • The paper relies on this without support.

    No prior studies have reported analogous effects of reward in the spatial domain.

    “Despite a rapidly expanding literature addressing the influence of reward on the attentional processing of color and shape information and the resulting changes in the attentional priority of such features, thus far analogous effects of rewards in the spatial domain have never been reported (but for related findings, see Discussion).”

  • The paper relies on this without support.

    The baseline-to-test changes in performance are attributable to reward-based training rather than repeated exposure to the task or other practice effects.

    “After a 4 d delay following the last training session, participants were engaged in a test session, identical to the baseline session, where reward feedbacks were not delivered”

  • The paper relies on this without support.

    Performance in the double-target single-report condition reflects the relative attentional priority of the two target locations.

    “This condition is the one in which a maximal difference in priority between the two target locations should follow the imbalanced delivery of rewards during the training phase, and the singly reported target should reflect such difference in priority.”

  • The paper relies on this without support.

    The spatial reward schedule during training is learned and represented spatially by participants.

    “Crucially, in both training sessions, the schedule of reward assignment was systematically biased so that each of the eight spatial locations in the stimulus array was associated with a specific probability of receiving high versus low reward.”
4 of 4

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Learned associations keep affecting selection even when the training and test task are very different.

    “Some studies have shown, however, that learned associations keep affecting selection even when the training and test task are very different (e.g., Chelazzi et al., 2014; Jahfari & Theeuwes, 2016; Lee & Shomstein, 2014; Raymond & O’Brien, 2009).”

    From Selection history: How reward modulates selectivity of visual attention. (2018) · cites this paper as Chelazzi et al., 2014

  • Reward-learning affects the allocation of attention with strong biases toward previously rewarded locations.

    “and reward-learning in turn affects the allocation of attention with strong biases toward previously rewarded locations52.”

    From Paying attention to attention in depression (2019) · cites this paper as [52]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Baseline target-identification rate conflicts with report frequencies

    Major

    The reported baseline double-target trials had a single correct report on 58% of trials and two correct reports on 25.2%. That gives (58 + 2 × 25.2) / 2 = 54.2% of targets identified, not the stated 66.51%.

  • An 80Lh location is named in an 80Hh-20Lh pair

    Minor

    The pair consists of an 80Hh and a 20Lh location, so it cannot contain the stated 80Lh location. The paper's reward categories define 80Hh, not 80Lh.

2 of 2

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References 78 · Cited by 195

Authors
Chelazzi, L., E to inova, J., Calletti, R., Lo Gerfo, E., Sani, I., Della Libera, C., & Santandrea, E.
Affiliations
University of Verona (IT)
ORCID
Venue
Journal of Neuroscience
Publisher
Society for Neuroscience
Published
2014-06-18
Volume
34
Issue
25
Pages
8594-8604
ISSN
  • 0270-6474 (ISSN-L)
  • 1529-2401
DOI
10.1523/jneurosci.0277-14.2014
PMC
PMC6608215
OpenAlex
W2164903550
Semantic Scholar
7b49f14e3dc050894f5e4d9e089cf96cdc8fdad9
Cited by
195
References
78
Citations by year
2026: 8 · 2025: 23 · 2024: 15 · 2023: 14 · 2022: 12 · 2021: 12 · 2020: 18 · 2019: 15 · 2018: 17 · 2017: 18 · 2016: 22 · 2015: 17 · 2014: 4
FWCI
18.10
Type
journal article
Language
en
Open access
Locations
  • Journal of Neuroscience (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • BOA (University of Milano-Bicocca) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Keywords
reward learning, spatial attention, top-down attention, attentional competition, attentional bias, visual attention
MeSH terms
Attention, Female, Humans, Learning, Male, Photic Stimulation, Psychomotor Performance, Reaction Time, Reward, Young Adult

About these checks

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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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