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Decoding conscious tactile perception in fMRI

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Dabbagh,  Alice
Max Planck Research Group Pain Perception, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Nierhaus,  Till
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Neurocomputation and Neuroimaging Unit, Department of Education and Psychology, Freie Universität Berlin;

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Villringer,  Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
MindBrainBody Institute, Berlin School of Mind and Brain, Humboldt- Universität zu Berlin;

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Grund,  Martin
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Dabbagh, A., Nierhaus, T., Villringer, A., & Grund, M. (2019). Decoding conscious tactile perception in fMRI. Poster presented at 7th MindBrainBody Symposium (MBBS 2019), Berlin, Germany.


Cite as: https://hdl.handle.net/21.11116/0000-0003-2A8A-3
Abstract
Introduction: Which brain areas are informative for decoding conscious tactile perception? Research on the neural correlates of consciousness has pointed to a fronto-parietal brain network broadcasting perceptual content. We utilized the sensitivity of fMRI multivariate pattern analysis to identify brain regions that carry information about conscious perception. Methods: Participants performed a tactile detection task in a Siemens Prisma 3 Tesla scanner. They had to report the perception of single electrical pulses that were applied to the left index finger and adjusted to an individual sensory detection threshold of 50%. Using the BOLD response amplitudes from detected and undetected trials, we applied a regions-of-interest (ROI) classification within each participant for the activation patterns in precuneus (PCUN), primary and secondary somatosensory cortex (S1 & S2) and inferior frontal gyrus (IFG). Additionally, we performed a searchlight classification of detected and undetected trials for each participant. Results: While the activation patterns from S1, S2, PCUN and IFG allowed for above-chance classification, they did not differ significantly in their accuracy rate. The searchlight analysis revealed significant clusters in S1, S2, PCUN, IFG, premotor cortex, angular gyrus, anterior cingulate cortex and prefrontal cortex. Discussion: The results of the ROI classification support the notion of a joint network including S1, S2, PCUN and IFG, processing and exchanging shared information. The searchlight analysis points to a broadly distributed informative pattern throughout the entire brain, which suggests the global availability of the conscious percept.