Abstract #0726

Physiopy: A community-driven suite of tools for physiological recordings in neuroimaging

Katherine Louise Bottenhorn¹, Daniel Alcalà-Lopez², Apoorva Ayyagari³, Molly G Bright⁴, César Caballero-Gaudes², Inés Chavarria², Vicente Ferrer², Soichi Hayashi⁵, Vittorio Iacovella⁶, François Lespinasse⁷, Ross Davis Markello⁸, Stefano Moia², Robert Oostenveld^9,10, Taylor Salo¹, Rachael Stickland⁴, Eneko Uruñuela², Merel Margaretha van der Thiel¹¹, and Kristina M Zvolanek¹²

¹Department of Psychology, Florida International University, Miami, FL, United States, ²Basque Center on Cognition, Brain and Language, Donostia, Spain, ³Northwestern University, Chicago, IL, United States, ⁴Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, United States, ⁵Indiana University, Bloomington, IN, United States, ⁶CIMeC - Center for Mind / Brain Sciences, The University of Trento, Trento, Italy, ⁷Psychology, Université de Montréal, Montréal, QC, Canada, ⁸McGill University, Montréal, QC, Canada, ⁹Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, ¹⁰NatMEG, Karolinska Institutet, Stockholm, Sweden, ¹¹Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, ¹²Biomedical Engineering, Northwestern University, Chicago, IL, United States

Physiopy is a community-driven effort that aims to offer a full data preparation pipeline for non-neural physiological recordings in neuroimaging research and to build consensus on “best practices” among researchers of this specific domain. Its primary goal is to facilitate physiological data collection and sharing, according to an existing data standard and ontology. Corollary goals of the community are to provide recommendations and tools for (1) physiological data acquisition in the MR environment, (2) appropriate processing of these data, (3) organization of resulting datasets and meta-data, and (4) computing metrics for the removal of confounding physiological signals from fMRI data.

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