Interactions Between Rhythmic and Feature Predictions to Create Parallel Time-Content Associations
The brain is inherently proactive, constantly predicting the when (moment) and what (content) of future input in order to optimize information processing. Previous research on such predictions has mainly studied the “when” or “what” domain separately, missing to investigate the potential integration...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-08-01
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| Series: | Frontiers in Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fnins.2019.00791/full |
| _version_ | 1819290362703773696 |
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| author | Sanne ten Oever Sanne ten Oever Alexander T. Sack Alexander T. Sack |
| author_facet | Sanne ten Oever Sanne ten Oever Alexander T. Sack Alexander T. Sack |
| author_sort | Sanne ten Oever |
| collection | DOAJ |
| description | The brain is inherently proactive, constantly predicting the when (moment) and what (content) of future input in order to optimize information processing. Previous research on such predictions has mainly studied the “when” or “what” domain separately, missing to investigate the potential integration of both types of predictive information. In the absence of such integration, temporal cues are assumed to enhance any upcoming content at the predicted moment in time (general temporal predictor). However, if the when and what prediction domain were integrated, a much more flexible neural mechanism may be proposed in which temporal-feature interactions would allow for the creation of multiple concurrent time-content predictions (parallel time-content predictor). Here, we used a temporal association paradigm in two experiments in which sound identity was systematically paired with a specific time delay after the offset of a rhythmic visual input stream. In Experiment 1, we revealed that participants associated the time delay of presentation with the identity of the sound. In Experiment 2, we unexpectedly found that the strength of this temporal association was negatively related to the EEG steady-state evoked responses (SSVEP) in preceding trials, showing that after high neuronal responses participants responded inconsistent with the time-content associations, similar to adaptation mechanisms. In this experiment, time-content associations were only present for low SSVEP responses in previous trials. These results tentatively show that it is possible to represent multiple time-content paired predictions in parallel, however, future research is needed to investigate this interaction further. |
| first_indexed | 2024-12-24T03:21:32Z |
| format | Article |
| id | doaj.art-cd06bd8a607f4b7eaec882cf45a33655 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-12-24T03:21:32Z |
| publishDate | 2019-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-cd06bd8a607f4b7eaec882cf45a336552022-12-21T17:17:29ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2019-08-011310.3389/fnins.2019.00791448747Interactions Between Rhythmic and Feature Predictions to Create Parallel Time-Content AssociationsSanne ten Oever0Sanne ten Oever1Alexander T. Sack2Alexander T. Sack3Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, NetherlandsMaastricht Brain Imaging Centre, Maastricht, NetherlandsDepartment of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, NetherlandsMaastricht Brain Imaging Centre, Maastricht, NetherlandsThe brain is inherently proactive, constantly predicting the when (moment) and what (content) of future input in order to optimize information processing. Previous research on such predictions has mainly studied the “when” or “what” domain separately, missing to investigate the potential integration of both types of predictive information. In the absence of such integration, temporal cues are assumed to enhance any upcoming content at the predicted moment in time (general temporal predictor). However, if the when and what prediction domain were integrated, a much more flexible neural mechanism may be proposed in which temporal-feature interactions would allow for the creation of multiple concurrent time-content predictions (parallel time-content predictor). Here, we used a temporal association paradigm in two experiments in which sound identity was systematically paired with a specific time delay after the offset of a rhythmic visual input stream. In Experiment 1, we revealed that participants associated the time delay of presentation with the identity of the sound. In Experiment 2, we unexpectedly found that the strength of this temporal association was negatively related to the EEG steady-state evoked responses (SSVEP) in preceding trials, showing that after high neuronal responses participants responded inconsistent with the time-content associations, similar to adaptation mechanisms. In this experiment, time-content associations were only present for low SSVEP responses in previous trials. These results tentatively show that it is possible to represent multiple time-content paired predictions in parallel, however, future research is needed to investigate this interaction further.https://www.frontiersin.org/article/10.3389/fnins.2019.00791/fullpredictionEEGtemporal informationrhythmadaptation |
| spellingShingle | Sanne ten Oever Sanne ten Oever Alexander T. Sack Alexander T. Sack Interactions Between Rhythmic and Feature Predictions to Create Parallel Time-Content Associations Frontiers in Neuroscience prediction EEG temporal information rhythm adaptation |
| title | Interactions Between Rhythmic and Feature Predictions to Create Parallel Time-Content Associations |
| title_full | Interactions Between Rhythmic and Feature Predictions to Create Parallel Time-Content Associations |
| title_fullStr | Interactions Between Rhythmic and Feature Predictions to Create Parallel Time-Content Associations |
| title_full_unstemmed | Interactions Between Rhythmic and Feature Predictions to Create Parallel Time-Content Associations |
| title_short | Interactions Between Rhythmic and Feature Predictions to Create Parallel Time-Content Associations |
| title_sort | interactions between rhythmic and feature predictions to create parallel time content associations |
| topic | prediction EEG temporal information rhythm adaptation |
| url | https://www.frontiersin.org/article/10.3389/fnins.2019.00791/full |
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