Improving the workflow of real-time fMRI Neurofeedback experiments Michael Lührs1,2, Florian Krause1,2, Caroline Benjamins1,2,Sascha Brunheim1,2, Judith Eck1,2, Quentin Noirhomme1,2, Mona Rosenke1,2, Rainer Goebel1,2 1Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands 2Brain Innovation B.V., Maastricht, Netherlands, Introduction Methods During the last decade the number and complexity of real-time functional magnetic resonance imaging (rtfMRI) neurofeedback (NF) experiments has dramatically increased. We developed a new software to improve the workflow of standard rtfMRI NF experiments and thus make these applications more accessible for clinical settings. The newly developed software combined with the improved workflow promises to reduce the amount of possible errors when running rtMRI NF experiments as well as the required scanning time. These developments can be applied to multiple MR systems and experimental designs allowing even novel experimenters to run complex rtfMRI NF experiments. We applied the workflow on a Siemens Prisma scanner in combination with Turbo-BrainVoyager 3.2, a real-time analysis software for fMRI data and Expyriment [1] for stimulus as well as feedback presentation. Results The workflow was used in nine rtfMRI experiments with three different subjects. Each experiment consisted of 54 minutes of scanning. We were able to complete five runs in each session in less than 90 minutes including the acquisition of pulse and respiration data. The Scan Session Tool hereby aids in recording all scanning details in a standardized way and allows the automatic organization of all scanning related data and files, thus facilitating/simplifying multi-center studies. The FBE shows a delay in data transfer times compared to the COE. The jittering in FBE s not present in COE. The COE was in mean 293.37ms faster than FBE. Standard deviation in FBE (87.14ms) was much higher compared to COE (18.29ms) due to the observed jitter and file read write procedures. The jittering artefact seems to be related to data size and TR. Similar results were observed using a Siemens 3T Prisma MRI. Conclusion We showed that standardizing the procedure of rtfMRI NF experiments is important to decrease the probability of errors while at the same time reducing the difficulty to perform an rtfMRI NF experiment. Additionally we showed that the connection oriented data transfer procedures of fMRI images leads to an decrease in transfer time variability. The research leading to these results has received funding from the European Community's Seventh Framework Programme FP7/2007-2013 under grant agreement number PITN-GA-2011-290011. Usual rtfMRI NF experiments consist of multiple scan sessions for which the main structure is the same or similar for all sessions and subjects. Assuming this repetitive structure, the improved workflow offers several small automatized procedures to simplify the tasks involved in running the experiments. As a first step we predefine one rtfMRI NF experiment session and prepare all necessary settings and components in advance. These configurations can be used for the session without changing the settings during the experiment. One example workflow (Figure 1) consists of a structural scan followed by a functional localizer (FL) and multiple NF runs. Figure 1: rtfMRI NF experiment workflow 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 Time after trigger (ms) Volume Data transfer times (Siemens 7T Magnetom) 1000TR Fast 1000TR Slow 1250TR Fast 1250TR Slow 1500TR Fast 1500TR Slow 1750TR Fast 1750TR Slow 2000TR Fast 2000TR Slow Because of errors and problems t