Pubblicazioni

Autori:

Ferrante, Oscar; Chelazzi, Leonardo; Santandrea, Elisa

Titolo:

Statistical learning of target and distractor spatial probability shape a common attentional priority computation

Anno:

2023

Tipologia prodotto:

Articolo in Rivista

Tipologia ANVUR:

Articolo su rivista

Lingua:

Inglese

Formato:

A Stampa

Referee:

Sì

Nome rivista:

Cortex

ISSN Rivista:

0010-9452

N° Volume:

169

Editore:

Masson

Intervallo pagine:

95-117

Parole chiave:

Distractor suppression; Spatial priority maps; Statistical learning; Target selection; Visual selective attention

Breve descrizione dei contenuti:

Converging evidence recently put forward the notion that dedicated neurocognitive mechanisms do exist for the suppression of salient, but irrelevant distractors. Along this line, it is plausible to hypothesize that, in appropriate contexts, experience-dependent forms of attentional learning might selectively induce plastic changes within this dedicated circuitry, thus allowing an independent shaping of priorities at the service of attentional filtering. Conversely, previous work suggested that statistical learning (SL) of both target and distractor spatial probability distributions converge in adjusting only the overall attentional priority of locations: in fact, in the presence of an independent manipulation, either related to the target or to the distractor only, SL induces indirect effects (e.g., changes in filtering efficiency due to an uneven distribution of targets), suggesting that SL-induced plastic changes affect a shared neural substrate. Here we tested whether, when (conflicting) target- and distractor-related manipulations are concurrently applied to the very same locations, dedicated mechanisms might support the selective encoding of spatial priority in relation to the specific attentional operation involved. In three related experiments, human healthy participants discriminated the direction of a target arrow, while ignoring a salient distractor, if present; both target and distractor spatial probability distributions were concurrently manipulated in relation to each single location. Critically, the selection bias produced by the target-related SL was marginally reduced by an adverse distractor contingency, and the suppression bias generated by the distractor-related SL was erased, or even reversed, by an adverse target contingency. Our results suggest that even conflicting target- and distractor-related SL manipulations result in the adjustment of a unique spatial priority computation, likely because the process directly relies on direct plastic alterations of shared spatial priority map(s).

Pagina Web:

https://doi.org/10.1016/j.cortex.2023.08.013

Id prodotto:

136158

Handle IRIS:

11562/1112947

ultima modifica:

9 novembre 2023

Citazione bibliografica:

Ferrante, Oscar; Chelazzi, Leonardo; Santandrea, Elisa, Statistical learning of target and distractor spatial probability shape a common attentional priority computation «Cortex» , vol. 169 , 2023 , pp. 95-117

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