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      Prestimulus feedback connectivity biases the content of visual experiences

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          Significance

          Ongoing neural activity influences stimulus detection—that is, whether or not an object is seen. Here, we uncover how it could influence the content of what is seen. In ambiguous situations, for instance, ongoing neural fluctuations might bias perception toward one or the other interpretation. Indeed, we show increased information flow from category-selective brain regions (here, the fusiform face area [FFA]) to the primary visual cortex before participants subsequently report seeing faces rather than a vase in the Rubin face/vase illusion. Our results identify a neural connectivity pathway that biases future perception and helps determine mental content.

          Abstract

          Ongoing fluctuations in neural excitability and in networkwide activity patterns before stimulus onset have been proposed to underlie variability in near-threshold stimulus detection paradigms—that is, whether or not an object is perceived. Here, we investigated the impact of prestimulus neural fluctuations on the content of perception—that is, whether one or another object is perceived. We recorded neural activity with magnetoencephalography (MEG) before and while participants briefly viewed an ambiguous image, the Rubin face/vase illusion, and required them to report their perceived interpretation in each trial. Using multivariate pattern analysis, we showed robust decoding of the perceptual report during the poststimulus period. Applying source localization to the classifier weights suggested early recruitment of primary visual cortex (V1) and ∼160-ms recruitment of the category-sensitive fusiform face area (FFA). These poststimulus effects were accompanied by stronger oscillatory power in the gamma frequency band for face vs. vase reports. In prestimulus intervals, we found no differences in oscillatory power between face vs. vase reports in V1 or in FFA, indicating similar levels of neural excitability. Despite this, we found stronger connectivity between V1 and FFA before face reports for low-frequency oscillations. Specifically, the strength of prestimulus feedback connectivity (i.e., Granger causality) from FFA to V1 predicted not only the category of the upcoming percept but also the strength of poststimulus neural activity associated with the percept. Our work shows that prestimulus network states can help shape future processing in category-sensitive brain regions and in this way bias the content of visual experiences.

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          Most cited references54

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          Identifying true brain interaction from EEG data using the imaginary part of coherency.

          The main obstacle in interpreting EEG/MEG data in terms of brain connectivity is the fact that because of volume conduction, the activity of a single brain source can be observed in many channels. Here, we present an approach which is insensitive to false connectivity arising from volume conduction. We show that the (complex) coherency of non-interacting sources is necessarily real and, hence, the imaginary part of coherency provides an excellent candidate to study brain interactions. Although the usual magnitude and phase of coherency contain the same information as the real and imaginary parts, we argue that the Cartesian representation is far superior for studying brain interactions. The method is demonstrated for EEG measurements of voluntary finger movement. We found: (a) from 5 s before to movement onset a relatively weak interaction around 20 Hz between left and right motor areas where the contralateral side leads the ipsilateral side; and (b) approximately 2-4 s after movement, a stronger interaction also at 20 Hz in the opposite direction. It is possible to reliably detect brain interaction during movement from EEG data. The method allows unambiguous detection of brain interaction from rhythmic EEG/MEG data.
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            Confidence Intervals from Normalized Data: A correction to Cousineau (2005)

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              Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses.

              Evoked activity in the mammalian cortex and the resulting behavioral responses exhibit a large variability to repeated presentations of the same stimulus. This study examined whether the variability can be attributed to ongoing activity. Ongoing and evoked spatiotemporal activity patterns in the cat visual cortex were measured with real-time optical imaging; local field potentials and discharges of single neurons were recorded simultaneously, by electrophysiological techniques. The evoked activity appeared deterministic, and the variability resulted from the dynamics of ongoing activity, presumably reflecting the instantaneous state of cortical networks. In spite of the large variability, evoked responses in single trials could be predicted by linear summation of the deterministic response and the preceding ongoing activity. Ongoing activity must play an important role in cortical function and cannot be ignored in exploration of cognitive processes.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                6 August 2019
                22 July 2019
                22 July 2019
                : 116
                : 32
                : 16056-16061
                Affiliations
                [1] aCentre for Cognitive Neuroscience, University of Salzburg , 5020 Salzburg, Austria;
                [2] bThe Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA 02139;
                [3] cDepartment of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
                [4] dCenter for Biomagnetismus, Department of Neurosurgery, University Hospital, 91054 Erlangen , Germany;
                [5] eCenter for Mind/Brain Sciences (CIMeC), University of Trento , 38123 Trento, Italy
                Author notes
                1To whom correspondence may be addressed. Email: elie.elrassi@ 123456sbg.ac.at .

                Edited by Riitta Hari, Aalto University, Espoo, Finland, and approved June 25, 2019 (received for review October 8, 2018)

                Author contributions: N.M.-V. and N.W. designed research; N.M.-V. performed research; E.R. analyzed data; and E.R., A.W., and N.W. wrote the paper.

                Author information
                http://orcid.org/0000-0003-1927-5373
                Article
                201817317
                10.1073/pnas.1817317116
                6689959
                31332019
                83eba956-e1d8-48bb-ae1c-a24c32fee601
                Copyright © 2019 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                History
                Page count
                Pages: 6
                Funding
                Funded by: FWF Austrian Science Fund
                Award ID: W 1233-G17
                Award Recipient : Elie Rassi Award Recipient : Andreas Wutz Award Recipient : Nathan Weisz
                Funded by: European Research Council
                Award ID: ERC StG 283404
                Award Recipient : Elie Rassi Award Recipient : Andreas Wutz Award Recipient : Nathan Weisz
                Funded by: FWF Lise-Meitner fellowship
                Award ID: M02496
                Award Recipient : Elie Rassi Award Recipient : Andreas Wutz Award Recipient : Nathan Weisz
                Categories
                Biological Sciences
                Neuroscience
                Social Sciences
                Psychological and Cognitive Sciences

                prestimulus,connectivity,meg,visual object perception,oscillations

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