Area-specific information processing in prefrontal cortex during a probabilistic inference task

• Verfasst von: Demanuele, Charmaine [VerfasserIn]
• Verfasst von: Kirsch, Peter [VerfasserIn]
• Verfasst von: Zink, Mathias [VerfasserIn]
• Verfasst von: Meyer-Lindenberg, Andreas [VerfasserIn]
• Verfasst von: Durstewitz, Daniel [VerfasserIn]
• Titel: Area-specific information processing in prefrontal cortex during a probabilistic inference task
• Titelzusatz: a multivariate fMRI BOLD time series analysis
• Verf.angabe: Charmaine Demanuele, Peter Kirsch, Christine Esslinger, Mathias Zink, Andreas Meyer-Lindenberg, Daniel Durstewitz
• E-Jahr: 2015
• Jahr: August 10, 2015
• Umfang: 14 S.
• Fussnoten: Gesehen am 14.02.2018
• Titel Quelle: Enthalten in: PLOS ONE
• Ort Quelle: San Francisco, California, US : PLOS, 2006
• Jahr Quelle: 2015
• Band/Heft Quelle: 10(2015,8) Artikel-Nummer e0135424, 14 Seiten
• ISSN Quelle: 1932-6203
• DOI: doi:10.1371/journal.pone.0135424
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Cognition
• Sach-SW: Functional magnetic resonance imaging
• Sach-SW: Algorithms
• Sach-SW: Decision making
• Sach-SW: Freshwater fish
• Sach-SW: Information processing
• Sach-SW: Prefrontal cortex
• Sach-SW: Test statistics
• K10plus-PPN: 1569821003

Abstract

Introduction: Discriminating spatiotemporal stages of information processing involved in complex cognitive processes remains a challenge for neuroscience. This is especially so in prefrontal cortex whose subregions, such as the dorsolateral prefrontal (DLPFC), anterior cingulate (ACC) and orbitofrontal (OFC) cortices are known to have differentiable roles in cognition. Yet it is much less clear how these subregions contribute to different cognitive processes required by a given task. To investigate this, we use functional MRI data recorded from a group of healthy adults during a “Jumping to Conclusions” probabilistic reasoning task. Methods: We used a novel approach combining multivariate test statistics with bootstrap-based procedures to discriminate between different task stages reflected in the fMRI blood oxygenation level dependent signal pattern and to unravel differences in task-related information encoded by these regions. Furthermore, we implemented a new feature extraction algorithm that selects voxels from any set of brain regions that are jointly maximally predictive about specific task stages. Results: Using both the multivariate statistics approach and the algorithm that searches for maximally informative voxels we show that during the Jumping to Conclusions task, the DLPFC and ACC contribute more to the decision making phase comprising the accumulation of evidence and probabilistic reasoning, while the OFC is more involved in choice evaluation and uncertainty feedback. Moreover, we show that in presumably non-task-related regions (temporal cortices) all information there was about task processing could be extracted from just one voxel (indicating the unspecific nature of that information), while for prefrontal areas a wider multivariate pattern of activity was maximally informative. Conclusions/Significance: We present a new approach to reveal the different roles of brain regions during the processing of one task from multivariate activity patterns measured by fMRI. This method can be a valuable tool to assess how area-specific processing is altered in psychiatric disorders such as schizophrenia, and in healthy subjects carrying different genetic polymorphisms.