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Abstract #3129

PROBABILISTIC MODEL-BASED FUNCTIONAL PARCELLATION OF THE PRIMARY OLFACTORY CORTEX

Prasanna Karunanayaka1, Jiaming Lu2, Christopher Sica1, Bing Zhang2, Qing Yang1, Paul Eslinger3, and Ronald Janssen4

1Radiology, Center for NMR Research, Penn State University College of Medicine, Hershey, PA, United States, 2Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Nanjing, China, 3Neurology, Penn State University College of Medicine, Hershey, PA, United States, 4Radboud University Nijmegen, Donders Centre for Brain Cognition and Behaviour, Nijmegen, The Netherlands, Nijmegen, Netherlands

The primary olfactory cortex (POC) is the largest recipient of olfactory bulb projections. It has a functionally versatile organization with extensive reciprocal connections to several higher-order cortical regions likely resulting in specific brain signals. Here, we propose a Bayesian model-based clustering approach, applied solely to resting state functional MRI time courses, to identify intrinsic POC functional parcellations. Results of this study suggest that multiple regions within the POC, with clear inter-hemispheric correspondence and functional relevance, can be identified using resting state fMRI data.

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