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Matthew Heath, Jon Bell, Clay Holroyd, Olav Krigolson; Behavioural and electrophysiological evidence of visual vector inversion in antipointing. Journal of Vision 2012;12(9):1086. doi: https://doi.org/10.1167/12.9.1086.
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© ARVO (1962-2015); The Authors (2016-present)
Antipointing requires suppressing a stimulus-driven response and reaching mirror-symmetrical (180° spatial transformation) to an exogenously or endogenously presented target. Notably, antipointing produces longer response latencies than their stimulus-driven counterparts (i.e., propointing) and elicits a visual-field specific pattern of endpoint bias (Maraj and Heath 2010: Exp Brain Res). In particular, antipointing trials in left and right space respectively under- and overshot veridical target location: a pattern of results consistent with a perceptual representation of visual space. The present study examined the contemporaneous behavioural and event-related brain potentials (ERP) of pro- and antipointing to determine whether the visual-field specific endpoint bias in the later task is related to: (1) the reallocation of visual attention and/or (2) the visual remapping of target properties in mirror- symmetrical space (i.e., vector inversion). A priori, we identified the N100 and P300 as providing the candidate ERP components associated with attention reallocation and vector inversion, respectively. In terms of target presentation, participants were provided advanced information pertaining to the nature of the task (i.e., pro- vs. antipointing) and electroencephalographic data were collected following target onset. As expected, antiponiting - but not propointing - produced a visual-field specific pattern of endpoint bias. Moreover, the N100 at electrodes PO7 and PO8 showed a lateralized response to target presentation that did not differ between the pro and antipointing conditions. In contrast, the later occurring P300 showed a reliable (and bilateral) between-task difference. Thus, our ERP data indicate that antipointing is mediated by a process of visual vector inversion. What is more, the combined ERP and behavioural data indicate that vector inversion is subserved via perception-based visual networks.
Meeting abstract presented at VSS 2012
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