<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Luckett, Patrick H</style></author><author><style face="normal" font="default" size="100%">Lee, John J</style></author><author><style face="normal" font="default" size="100%">Park, Ki Yun</style></author><author><style face="normal" font="default" size="100%">Raut, Ryan V</style></author><author><style face="normal" font="default" size="100%">Meeker, Karin L</style></author><author><style face="normal" font="default" size="100%">Gordon, Evan M</style></author><author><style face="normal" font="default" size="100%">Snyder, Abraham Z</style></author><author><style face="normal" font="default" size="100%">Ances, Beau M</style></author><author><style face="normal" font="default" size="100%">Leuthardt, Eric C</style></author><author><style face="normal" font="default" size="100%">Shimony, Joshua S</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Resting state network mapping in individuals using deep learning.</style></title><secondary-title><style face="normal" font="default" size="100%">Front Neurol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Front Neurol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2023</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">1055437</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;INTRODUCTION: &lt;/b&gt;Resting state functional MRI (RS-fMRI) is currently used in numerous clinical and research settings. The localization of resting state networks (RSNs) has been utilized in applications ranging from group analysis of neurodegenerative diseases to individual network mapping for pre-surgical planning of tumor resections. Reproducibility of these results has been shown to require a substantial amount of high-quality data, which is not often available in clinical or research settings.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;In this work, we report voxelwise mapping of a standard set of RSNs using a novel deep 3D convolutional neural network (3DCNN). The 3DCNN was trained on publicly available functional MRI data acquired in  = 2010 healthy participants. After training, maps that represent the probability of a voxel belonging to a particular RSN were generated for each participant, and then used to calculate mean and standard deviation (STD) probability maps, which are made publicly available. Further, we compared our results to previously published resting state and task-based functional mappings.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Our results indicate this method can be applied in individual subjects and is highly resistant to both noisy data and fewer RS-fMRI time points than are typically acquired. Further, our results show core regions within each network that exhibit high average probability and low STD.&lt;/p&gt;&lt;p&gt;&lt;b&gt;DISCUSSION: &lt;/b&gt;The 3DCNN algorithm can generate individual RSN localization maps, which are necessary for clinical applications. The similarity between 3DCNN mapping results and task-based fMRI responses supports the association of specific functional tasks with RSNs.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gordon, Evan M</style></author><author><style face="normal" font="default" size="100%">Chauvin, Roselyne J</style></author><author><style face="normal" font="default" size="100%">Van, Andrew N</style></author><author><style face="normal" font="default" size="100%">Rajesh, Aishwarya</style></author><author><style face="normal" font="default" size="100%">Nielsen, Ashley</style></author><author><style face="normal" font="default" size="100%">Newbold, Dillan J</style></author><author><style face="normal" font="default" size="100%">Lynch, Charles J</style></author><author><style face="normal" font="default" size="100%">Seider, Nicole A</style></author><author><style face="normal" font="default" size="100%">Krimmel, Samuel R</style></author><author><style face="normal" font="default" size="100%">Scheidter, Kristen M</style></author><author><style face="normal" font="default" size="100%">Monk, Julia</style></author><author><style face="normal" font="default" size="100%">Miller, Ryland L</style></author><author><style face="normal" font="default" size="100%">Metoki, Athanasia</style></author><author><style face="normal" font="default" size="100%">Montez, David F</style></author><author><style face="normal" font="default" size="100%">Zheng, Annie</style></author><author><style face="normal" font="default" size="100%">Elbau, Immanuel</style></author><author><style face="normal" font="default" size="100%">Madison, Thomas</style></author><author><style face="normal" font="default" size="100%">Nishino, Tomoyuki</style></author><author><style face="normal" font="default" size="100%">Myers, Michael J</style></author><author><style face="normal" font="default" size="100%">Kaplan, Sydney</style></author><author><style face="normal" font="default" size="100%">Badke D'Andrea, Carolina</style></author><author><style face="normal" font="default" size="100%">Demeter, Damion V</style></author><author><style face="normal" font="default" size="100%">Feigelis, Matthew</style></author><author><style face="normal" font="default" size="100%">Ramirez, Julian S B</style></author><author><style face="normal" font="default" size="100%">Xu, Ting</style></author><author><style face="normal" font="default" size="100%">Barch, Deanna M</style></author><author><style face="normal" font="default" size="100%">Smyser, Christopher D</style></author><author><style face="normal" font="default" size="100%">Rogers, Cynthia E</style></author><author><style face="normal" font="default" size="100%">Zimmermann, Jan</style></author><author><style face="normal" font="default" size="100%">Botteron, Kelly N</style></author><author><style face="normal" font="default" size="100%">Pruett, John R</style></author><author><style face="normal" font="default" size="100%">Willie, Jon T</style></author><author><style face="normal" font="default" size="100%">Brunner, Peter</style></author><author><style face="normal" font="default" size="100%">Shimony, Joshua S</style></author><author><style face="normal" font="default" size="100%">Kay, Benjamin P</style></author><author><style face="normal" font="default" size="100%">Marek, Scott</style></author><author><style face="normal" font="default" size="100%">Norris, Scott A</style></author><author><style face="normal" font="default" size="100%">Gratton, Caterina</style></author><author><style face="normal" font="default" size="100%">Sylvester, Chad M</style></author><author><style face="normal" font="default" size="100%">Power, Jonathan D</style></author><author><style face="normal" font="default" size="100%">Liston, Conor</style></author><author><style face="normal" font="default" size="100%">Greene, Deanna J</style></author><author><style face="normal" font="default" size="100%">Roland, Jarod L</style></author><author><style face="normal" font="default" size="100%">Petersen, Steven E</style></author><author><style face="normal" font="default" size="100%">Raichle, Marcus E</style></author><author><style face="normal" font="default" size="100%">Laumann, Timothy O</style></author><author><style face="normal" font="default" size="100%">Fair, Damien A</style></author><author><style face="normal" font="default" size="100%">Dosenbach, Nico U F</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A somato-cognitive action network alternates with effector regions in motor cortex.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nature</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Cognition</style></keyword><keyword><style  face="normal" font="default" size="100%">Datasets as Topic</style></keyword><keyword><style  face="normal" font="default" size="100%">Foot</style></keyword><keyword><style  face="normal" font="default" size="100%">Hand</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Infant</style></keyword><keyword><style  face="normal" font="default" size="100%">Infant, Newborn</style></keyword><keyword><style  face="normal" font="default" size="100%">Macaca</style></keyword><keyword><style  face="normal" font="default" size="100%">Magnetic Resonance Imaging</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Mouth</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2023</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">617</style></volume><pages><style face="normal" font="default" size="100%">351-359</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations, despite evidence for concentric functional zones and maps of complex actions. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action and physiological control, arousal, errors and pain. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions and connectivity to internal organs such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7960</style></issue></record></records></xml>