Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task

Detalhes bibliográficos
Autor(a) principal: Carvalho, Fabiana M.
Data de Publicação: 2016
Outros Autores: Chaim, Khallil T., Sanchez, Tiago A., Araújo, Dráulio Barros de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRN
DOI: 10.3389/fnhum.2016.00268
Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/23079
Resumo: The updating of prospective internal models is necessary to accurately predict future observations. Uncertainty-driven internal model updating has been studied using a variety of perceptual paradigms, and have revealed engagement of frontal and parietal areas. In a distinct literature, studies on temporal expectations have also characterized a time-perception network, which relies on temporal orienting of attention. However, the updating of prospective internal models is highly dependent on temporal attention, since temporal attention must be reoriented according to the current environmental demands. In this study, we used functional magnetic resonance imaging (fMRI) to evaluate to what extend the continuous manipulation of temporal prediction would recruit update-related areas and the time-perception network areas. We developed an exogenous temporal task that combines rhythm cueing and time-to-contact principles to generate implicit temporal expectation. Two patterns of motion were created: periodic (simple harmonic oscillation) and non-periodic (harmonic oscillation with variable acceleration). We found that non-periodic motion engaged the exogenous temporal orienting network, which includes the ventral premotor and inferior parietal cortices, and the cerebellum, as well as the presupplementary motor area, which has previously been implicated in internal model updating, and the motion-sensitive area MT+. Interestingly, we found a right-hemisphere preponderance suggesting the engagement of explicit timing mechanisms. We also show that the periodic motion condition, when compared to the non-periodic motion, activated a particular subset of the default-mode network (DMN) midline areas, including the left dorsomedial prefrontal cortex (DMPFC), anterior cingulate cortex (ACC), and bilateral posterior cingulate cortex/precuneus (PCC/PC). It suggests that the DMN plays a role in processing contextually expected information and supports recent evidence that the DMN may reflect the validation of prospective internal models and predictive control. Taken together, our findings suggest that continuous manipulation of temporal predictions engages representations of temporal prediction as well as task-independent updating of internal models.
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spelling Carvalho, Fabiana M.Chaim, Khallil T.Sanchez, Tiago A.Araújo, Dráulio Barros de2017-05-25T18:04:18Z2017-05-25T18:04:18Z2016-06-02https://repositorio.ufrn.br/jspui/handle/123456789/2307910.3389/fnhum.2016.00268engtemporal expectationtemporal predictionattentioninternal modelfMRITime-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Taskinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleThe updating of prospective internal models is necessary to accurately predict future observations. Uncertainty-driven internal model updating has been studied using a variety of perceptual paradigms, and have revealed engagement of frontal and parietal areas. In a distinct literature, studies on temporal expectations have also characterized a time-perception network, which relies on temporal orienting of attention. However, the updating of prospective internal models is highly dependent on temporal attention, since temporal attention must be reoriented according to the current environmental demands. In this study, we used functional magnetic resonance imaging (fMRI) to evaluate to what extend the continuous manipulation of temporal prediction would recruit update-related areas and the time-perception network areas. We developed an exogenous temporal task that combines rhythm cueing and time-to-contact principles to generate implicit temporal expectation. Two patterns of motion were created: periodic (simple harmonic oscillation) and non-periodic (harmonic oscillation with variable acceleration). We found that non-periodic motion engaged the exogenous temporal orienting network, which includes the ventral premotor and inferior parietal cortices, and the cerebellum, as well as the presupplementary motor area, which has previously been implicated in internal model updating, and the motion-sensitive area MT+. Interestingly, we found a right-hemisphere preponderance suggesting the engagement of explicit timing mechanisms. We also show that the periodic motion condition, when compared to the non-periodic motion, activated a particular subset of the default-mode network (DMN) midline areas, including the left dorsomedial prefrontal cortex (DMPFC), anterior cingulate cortex (ACC), and bilateral posterior cingulate cortex/precuneus (PCC/PC). It suggests that the DMN plays a role in processing contextually expected information and supports recent evidence that the DMN may reflect the validation of prospective internal models and predictive control. Taken together, our findings suggest that continuous manipulation of temporal predictions engages representations of temporal prediction as well as task-independent updating of internal models.info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNORIGINALTime-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task.pdfTime-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task.pdfDraulioAraujo_ICe_Time-Perception Network_2016application/pdf1978949https://repositorio.ufrn.br/bitstream/123456789/23079/1/Time-Perception%20Network%20and%20Default%20Mode%20Network%20Are%20Associated%20with%20Temporal%20Prediction%20in%20a%20Periodic%20Motion%20Task.pdfb18cd7180828fcb77adc592a6051245cMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.ufrn.br/bitstream/123456789/23079/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52TEXTTime-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task.pdf.txtTime-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task.pdf.txtExtracted texttext/plain65845https://repositorio.ufrn.br/bitstream/123456789/23079/5/Time-Perception%20Network%20and%20Default%20Mode%20Network%20Are%20Associated%20with%20Temporal%20Prediction%20in%20a%20Periodic%20Motion%20Task.pdf.txt096cc740d9716a45266c38519a2b9813MD55THUMBNAILTime-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task.pdf.jpgTime-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task.pdf.jpgIM Thumbnailimage/jpeg8282https://repositorio.ufrn.br/bitstream/123456789/23079/6/Time-Perception%20Network%20and%20Default%20Mode%20Network%20Are%20Associated%20with%20Temporal%20Prediction%20in%20a%20Periodic%20Motion%20Task.pdf.jpgb6f16fe06f98f12a0d5b29ccb6886b50MD56123456789/230792021-07-08 15:41:31.549oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2021-07-08T18:41:31Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false
dc.title.pt_BR.fl_str_mv Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
title Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
spellingShingle Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
Carvalho, Fabiana M.
temporal expectation
temporal prediction
attention
internal model
fMRI
title_short Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
title_full Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
title_fullStr Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
title_full_unstemmed Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
title_sort Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task
author Carvalho, Fabiana M.
author_facet Carvalho, Fabiana M.
Chaim, Khallil T.
Sanchez, Tiago A.
Araújo, Dráulio Barros de
author_role author
author2 Chaim, Khallil T.
Sanchez, Tiago A.
Araújo, Dráulio Barros de
author2_role author
author
author
dc.contributor.author.fl_str_mv Carvalho, Fabiana M.
Chaim, Khallil T.
Sanchez, Tiago A.
Araújo, Dráulio Barros de
dc.subject.por.fl_str_mv temporal expectation
temporal prediction
attention
internal model
fMRI
topic temporal expectation
temporal prediction
attention
internal model
fMRI
description The updating of prospective internal models is necessary to accurately predict future observations. Uncertainty-driven internal model updating has been studied using a variety of perceptual paradigms, and have revealed engagement of frontal and parietal areas. In a distinct literature, studies on temporal expectations have also characterized a time-perception network, which relies on temporal orienting of attention. However, the updating of prospective internal models is highly dependent on temporal attention, since temporal attention must be reoriented according to the current environmental demands. In this study, we used functional magnetic resonance imaging (fMRI) to evaluate to what extend the continuous manipulation of temporal prediction would recruit update-related areas and the time-perception network areas. We developed an exogenous temporal task that combines rhythm cueing and time-to-contact principles to generate implicit temporal expectation. Two patterns of motion were created: periodic (simple harmonic oscillation) and non-periodic (harmonic oscillation with variable acceleration). We found that non-periodic motion engaged the exogenous temporal orienting network, which includes the ventral premotor and inferior parietal cortices, and the cerebellum, as well as the presupplementary motor area, which has previously been implicated in internal model updating, and the motion-sensitive area MT+. Interestingly, we found a right-hemisphere preponderance suggesting the engagement of explicit timing mechanisms. We also show that the periodic motion condition, when compared to the non-periodic motion, activated a particular subset of the default-mode network (DMN) midline areas, including the left dorsomedial prefrontal cortex (DMPFC), anterior cingulate cortex (ACC), and bilateral posterior cingulate cortex/precuneus (PCC/PC). It suggests that the DMN plays a role in processing contextually expected information and supports recent evidence that the DMN may reflect the validation of prospective internal models and predictive control. Taken together, our findings suggest that continuous manipulation of temporal predictions engages representations of temporal prediction as well as task-independent updating of internal models.
publishDate 2016
dc.date.issued.fl_str_mv 2016-06-02
dc.date.accessioned.fl_str_mv 2017-05-25T18:04:18Z
dc.date.available.fl_str_mv 2017-05-25T18:04:18Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv https://repositorio.ufrn.br/jspui/handle/123456789/23079
dc.identifier.doi.none.fl_str_mv 10.3389/fnhum.2016.00268
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