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Investigating Neural Responses Underlying Product Valuation in The Real-World Using Wireless Electroencephalography and Eye-Tracking
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  • Hannah Roberts,
  • John Tyson-Carr,
  • Vicente Soto,
  • Nicholas Fallon,
  • Timo Giesbrecht,
  • Andrej Stancak
Hannah Roberts
University of Liverpool

Corresponding Author:[email protected]

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John Tyson-Carr
University of Liverpool
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Vicente Soto
Universidad Adolfo Ibanez
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Nicholas Fallon
University of Liverpool
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Timo Giesbrecht
Unilever
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Andrej Stancak
University of Liverpool
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Abstract

Research in freely moving participants demonstrated that eye-movement related potentials (EMRPs) obtained during wireless EEG and eye-tracking can resolve low versus higher subjective value (SV) of products within 200 ms of first viewing. It remains unknown whether neural components underpinning SV are computed linearly or in distinct clusters. A limited stimulus value range may have prevented detection of linear discrimination of EMRP components by SV. The residual presence of oculomotor artefacts could have contributed to the lack of discrimination of EMRPs for individual SVs. The present study investigated whether EMRPs during product viewing would encode SVs linearly by expanding retail-value range and implementing guided-saccade artefacts removal. Participants viewed 216 product images in a mock-gallery. Continuous 64-channel wireless EEG and eye-tracking data were recorded. Willingness-to-pay was evaluated in an auction, categorising products by SV. Adaptive Spatial Filtering removed oculomotor artefacts from guided-saccade recordings. EMRPs were analysed using independent component (IC) and clustering analysis. Four ICs between 50 ̵̵ 230 ms resolved product SVs. One IC showed linearly decreasing activity paralleling increasing SV, with strongest activation for low-value. Other ICs responded preferentially to medium-value. ICs resolving early SVs (50 ̵̵ 60 ms) differentiated the low-value category from other categories. Cortical components elicited during free-viewing of products in quasi-naturalistic settings were mostly tuned to specific bands of SV with only one IC representing SV linearly. SVs appear to be formed automatically during initial product viewing and are represented on a coarse value grid, with the lowest SV products being processed earliest.