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RESEARCH PRODUCT
Spatiotemporal Neurodynamics Underlying Internally and Externally Driven Temporal Prediction: A High Spatial Resolution ERP Study
Antonino VallesiGiovanni MentoPatrizia BisiacchiVincenza Tarantinosubject
AdultCognitive NeuroscienceArray data typeElectroencephalographyCue050105 experimental psychologyYoung Adult03 medical and health sciences0302 clinical medicinemedicineHumans0501 psychology and cognitive sciencesEvoked PotentialsImage resolutionCerebral CortexCommunicationSettore M-PSI/02 - Psicobiologia E Psicologia FisiologicaArtificial neural networkmedicine.diagnostic_testbusiness.industryFunctional Neuroimaging05 social sciencesElectroencephalographyCognitionAnticipation PsychologicalAnticipationCombined approachContingent negative variationTime PerceptionCuesEvoked PotentialPsychologybusinessNeurosciencePsychomotor Performance030217 neurology & neurosurgeryHumandescription
Abstract Temporal prediction (TP) is a flexible and dynamic cognitive ability. Depending on the internal or external nature of information exploited to generate TP, distinct cognitive and brain mechanisms are engaged with the same final goal of reducing uncertainty about the future. In this study, we investigated the specific brain mechanisms involved in internally and externally driven TP. To this end, we employed an experimental paradigm purposely designed to elicit and compare externally and internally driven TP and a combined approach based on the application of a distributed source reconstruction modeling on a high spatial resolution electrophysiological data array. Specific spatiotemporal ERP signatures were identified, with significant modulation of contingent negative variation and frontal late sustained positivity in external and internal TP contexts, respectively. These different electrophysiological patterns were supported by the engagement of distinct neural networks, including a left sensorimotor and a prefrontal circuit for externally and internally driven TP, respectively.
year | journal | country | edition | language |
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2015-01-01 | Journal of Cognitive Neuroscience |