Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/92457
DC Field | Value | Language |
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dc.contributor.author | Sayal, Alexandre | - |
dc.contributor.author | Sousa, Teresa | - |
dc.contributor.author | Duarte, João V. | - |
dc.contributor.author | Costa, Gabriel Nascimento Ferreira da | - |
dc.contributor.author | Martins, Ricardo Filipe Alves | - |
dc.contributor.author | Castelo-Branco, Miguel | - |
dc.date.accessioned | 2021-01-13T18:40:07Z | - |
dc.date.available | 2021-01-13T18:40:07Z | - |
dc.date.issued | 2020-11-01 | - |
dc.identifier.issn | 10538119 | pt |
dc.identifier.uri | https://hdl.handle.net/10316/92457 | - |
dc.description.abstract | Hysteresis is a well-known phenomenon in physics that relates changes in a system with its prior history. It is also part of human visual experience (perceptual hysteresis), and two different neural mechanisms might explain it: persistence (a cause of positive hysteresis), which forces to keep a current percept for longer, and adaptation (a cause of negative hysteresis), which in turn favors the switch to a competing percept early on. In this study, we explore the neural correlates underlying these mechanisms and the hypothesis of their competitive balance, by combining behavioral assessment with fMRI. We used machine learning on the behavioral data to distinguish between positive and negative hysteresis, and discovered a neural correlate of persistence at a core region of the ventral attention network, the anterior insula. Our results add to the understanding of perceptual multistability and reveal a possible mechanistic explanation for the regulation of different forms of perceptual hysteresis. | pt |
dc.language.iso | eng | pt |
dc.rights | openAccess | pt |
dc.subject | Bistable visual motion; Hysteresis; Perceptual decision; Perceptual history | pt |
dc.title | Identification of competing neural mechanisms underlying positive and negative perceptual hysteresis in the human visual system | pt |
dc.type | article | - |
degois.publication.firstPage | 117153 | pt |
degois.publication.title | NeuroImage | pt |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S105381192030639X | pt |
dc.peerreviewed | yes | pt |
dc.identifier.doi | 10.1016/j.neuroimage.2020.117153 | pt |
degois.publication.volume | 221 | pt |
dc.date.embargo | 2020-11-01 | * |
uc.date.periodoEmbargo | 0 | pt |
item.languageiso639-1 | en | - |
item.fulltext | Com Texto completo | - |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
crisitem.author.researchunit | CNC - Center for Neuroscience and Cell Biology | - |
crisitem.author.researchunit | CIBIT - Coimbra Institute for Biomedical Imaging and Translational Research | - |
crisitem.author.orcid | 0001-8586-9554 | - |
crisitem.author.orcid | 0000-0001-9630-1155 | - |
crisitem.author.orcid | 0000-0001-7184-185X | - |
crisitem.author.orcid | 0000-0003-4364-6373 | - |
Appears in Collections: | I&D CIBIT - Artigos em Revistas Internacionais |
Files in This Item:
File | Description | Size | Format | |
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full-text.pdf | full-text | 1.54 MB | Adobe PDF | View/Open |
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