@article{490ac9ad5fd34e42ab7f7e2d14e652a7,
title = "Adaptation to visual numerosity changes neural numerosity selectivity",
abstract = "Perceiving numerosity, i.e. the set size of a group of items, is an evolutionarily preserved ability found in humans and animals. A useful method to infer the neural underpinnings of a given perceptual property is sensory adaptation. Like other primary perceptual attributes, numerosity is susceptible to adaptation. Recently, we have shown numerosity-selective neural populations with a topographic organization in the human brain. Here, we investigated whether numerosity adaptation can affect the numerosity selectivity of these populations using ultra-high field (7 Tesla) functional magnetic resonance imaging (fMRI). Participants viewed stimuli of changing numerosity (1 to 7 dots), which allowed the mapping of numerosity selectivity. We interleaved a low or high numerosity adapter stimulus with these mapping stimuli, repeatedly presenting 1 or 20 dots respectively to adapt the numerosity-selective neural populations. We analyzed the responses using custom-build population receptive field neural models of numerosity encoding and compared estimated numerosity preferences between adaptation conditions. We replicated our previous studies where we found several topographic maps of numerosity-selective responses. We found that overall, numerosity adaptation altered the preferred numerosities within the numerosity maps, resulting in predominantly attractive biases towards the numerosity of the adapter. The differential biases could be explained by the difference between the unadapted preferred numerosity and the numerosity of the adapter, with attractive biases being observed with higher difference. The results could link perceptual numerosity adaptation effects to changes in neural numerosity selectivity.",
keywords = "Adaptation, High-field 7T fMRI, Numerosity, Topographic maps",
author = "Andromachi Tsouli and Yuxuan Cai and {van Ackooij}, Martijn and Shir Hofstetter and Harvey, {Ben M.} and {te Pas}, {Susan F.} and {van der Smagt}, {Maarten J.} and Dumoulin, {Serge O.}",
note = "Funding Information: This work was supported in part by the AMMODO KNAW Award (SD). The Spinoza Centre for Neuroimaging is a joint institute of the University of Amsterdam, Academic Medical Center, VU University, VU Medical Center, Netherlands Institute for Neuroscience and the Royal Netherlands Academy of Sciences. The code generated during this study is available in the Vistasoft repository (https://github.com/vistalab/vistasoft). The datasets supporting the current study are available from the corresponding author on request. The datasets have not yet been deposited in a public repository because of (biometric) data protection issues, in compliance with the General Data Protection Regulation (GDPR; https://ec.europa.eu/info/law/law-topic/data-protection/data-protection-eu_en) for data protection in the European Union, and in compliance with the data sharing policy as reviewed by the Medical Ethical Review Committee of the University Medical Center Utrecht. Conceptualization: A.T. B.M.H. S.F.T.P. M.J.V.D.S. and S.O.D.; Methodology: A.T. B.M.H. S.F.T.P. M.J.V.D.S. and S.O.D.; Software: M.V.A. B.M.H. and S.O.D.; Validation: A.T. Y.C. M.V.A. S.H. B.M.H. and S.O.D.; Formal Analysis: A.T. Y.C. S.H. B.M.H. S.F.T.P. M.J.V.D.S. and S.O.D.; Investigation: A.T. and Y.C.; Data Curation: A.T. Y.C. and M.V.A.; Writing ? Original Draft: A.T.; Writing ? Review & Editing: A.T. Y.C. M.V.A. S.H. B.M.H. S.F.T.P. M.J.V.D.S. and S.O.D.; Visualization: A.T. Y.C. S.H. and B.M.H.; Supervision: B.M.H. S.F.T.P. M.J.V.D.S. and S.O.D.; Project administration: B.M.H. S.F.T.P. M.J.V.D.S. and S.O.D.; Funding Acquisition: S.O.D. Publisher Copyright: {\textcopyright} 2021 Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = apr,
day = "1",
doi = "10.1016/j.neuroimage.2021.117794",
language = "English",
volume = "229",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Academic Press",
}