We thank Dr. D. Chen and Dr. C. Yen for sharing the AFNI script to set up the real-time fMRI for PV 5 and the AFNI team for the software support. This research was supported by NIH Brain Initiative funding (RF1NS113278-01, R01 MH111438-01), and the S10 instrument grant (S10 RR023009-01) to Martinos Center, German Research Foundation (DFG) Yu215/3-1, BMBF 01GQ1702, and the internal funding from Max Planck Society.

This study was performed in accordance with the German Animal Welfare Act (TierSchG) and Animal Welfare Laboratory Animal Ordinance (TierSchVersV). The experimental protocol described here was reviewed by the ethics commission (&#167;15 TierSchG) and approved by the state authority (Regierungspr&#228;sidium, T&#252;bingen, Baden-W&#252;rttemberg, Germany).
1. Preparing the BOLD-fMRI experimental set-up for small animal study
<ol>
	<li>Turn on the console software to control imaging parameters and acquire MRI data. 
	NOTE: The proposed real-time fMRI set-up is implemented utilizing macro-functions of the console software (version 6) in parallel with the image processing functions of AFNI.</li>
	<li>Find MR sequences (i.e., Position, Localizer, Rapid Acquisition with Relaxation Enhancement (RARE), and 3D echo-planar imaging (EPI) with the workspace explorer, and then drag and append them in the scan list. 
	NOTE: Position and Localizer sequences are used to identify a region of interest (ROI) in a brain. A RARE sequence is used for an anatomy scan. A 3D EPI sequence is used to measure dynamic BOLD responses.</li>
	<li>Place the predefined macro scripts, &#8220;Setup_rt3DEPI&#8221; and &#8220;Feed2AFNI_rt3DEPI&#8221; in the macro script path (e.g., &#8220;/opt/(PV version)/prog/curdir/(user name)/ParaVision/macros&#8221;). Activate the 3D EPI reconstruction options, &#8220;Pre Image Series Activities&#8221; and &#8220;Execute Macro&#8221; in the &#8220;Data Reconstruction&#8221; user interface menu, and then link the predefined macro script, &#8220;Setup_rt3DEPI&#8221;, before clicking the &#8220;Scan&#8221; button. 
	NOTE: The macro scripts are included in the Supplementary files.</li>
	<li>Install the AFNI software for the real-time BOLD-fMRI analysis and visualization.</li>
</ol>
2. Catheterization and ventilation surgery
<ol>
	<li>Set up a ventilator and physiological status monitoring systems such as thermometer, blood pressure and respiration recording as shown in Figure 1. Set a constant frequency of 60 &#177; 1 breath/min with the ventilator and a temperature of 37 &#176;C using an MR-compatible heating pad with a feedback control set.</li>
	<li>Anesthetize an adult male Sprague-Dawley rat (300-600 g) in a chamber with 5% isoflurane for induction and deliver 2-2.5% isoflurane for surgery from a vaporizer. Check the depth of anesthesia by pinching the hindpaw and confirming the lack of a withdrawal response.</li>
	<li>Intubate the animal with a 14 G plastic cannula for ventilation (60 &#177; 1 breath/min with a mixture of 70% air and 30% oxygen). Adjust end-tidal carbon dioxide (CO2) to be in the range of 25 &#177; 5 mmHg29. 
	NOTE: The intubation is critical for maintaining proper CO2 levels through fMRI experiments.</li>
	<li>Place the animal in a supine position on a surgery table and shave a thigh with an electric razor. And then, make an incision on the shaved skin with surgical scissors. 
	NOTE: The length of the incision is around 1-2 cm in a longitudinal direction.</li>
	<li>Find a femoral artery and vein under the incised region for catheterization and separate the individual femoral artery and vein from the surrounding tissues.</li>
	<li>Fasten one side of the separated femoral artery with a surgical suture and hold the other side with micro bulldog forceps. Then, make a small incision between the tied regions on the femoral artery.</li>
	<li>Insert a catheter into the femoral artery through the small incision and tie the catheter and the artery together with surgical sutures. Monitor the arterial blood pressure constantly with the physiological monitoring system to be in the range of 80-120 mmHg and measure the arterial blood gas regularly to maintain pO2 of minimum 90 mmHg and pCO2 of 30-45 mmHg during scanning. 
	NOTE: This catheterization is critical for monitoring the arterial blood pressure during fMRI experiments.</li>
	<li>Fasten both ends of the femoral vein with silk braided surgical sutures. Then, make a small incision between the tied regions on the femoral vein. Use forceps to perform the suturing. 
	NOTE: The size of the suture is around 1-2 cm.</li>
	<li>Insert a catheter into the femoral vein. Tie the catheter and the vein together with surgical sutures. 
	NOTE: This catheterization is critical for administrating alpha-chloralose through the vein and adjusting the anesthetic levels during fMRI experiments. If the animal is not well anesthetized, it will start to breathe spontaneously. In this case, more alpha-chloralose must be administrated to avoid respiratory motion artifacts.</li>
	<li>Suture the surgical incision on the shaved skin. Once the surgical procedures are completed, keep the animal anesthetized by infusing a bolus of alpha-chloralose with the dosage of ~80 mg/kg through the catheter connected to the femoral vein and stop isoflurane administration at the same time.</li>
</ol>
3. Placing the animal inside the MRI scanner
<ol>
	<li>Transfer the anesthetized animal to the MRI scanner as soon as 2.10 step is done and secure it on a custom-made cradle.</li>
	<li>Insert a real-time feedback rectal thermometer on the animal to monitor the animal&#8217;s temperature. Place a heating pad under the animal&#8217;s torso to control the temperature. Maintain the body temperature at 37.0 &#177; 0.5 &#176;C during MRI scans.</li>
	<li>Deliver alpha-chloralose with ~25 mg/kg/h solution in a mixture of pancuronium (~2 mg/kg/h), a muscle relaxer, continuously while keeping the animal anesthetized and reducing motion artifacts in fMRI images. Monitor the blood pressure and respiration by adjusting the amount of drug and the rate of ventilation according to the physiological status.</li>
	<li>Administer ophthalmic ointment on the eyes of the animal to prevent dryness during fMRI experiments. Fix the animal&#8217;s head safely with two ear bars to avoid head motion artifacts.</li>
	<li>Fix a transceiver surface coil on the head. Tune and match the coil to the Larmor frequency (e.g., 599 MHz on 14.1 T) on the head before MRI measurements. 
	NOTE: Here, 22 mm diameter coil is used to cover the whole brain of a rat.</li>
	<li>Insert a pair of needle electrodes into the skin of the forepaw between digits 1 and 4 and fix them with surgical tape. And then, confirm that the stimulation works properly after connecting a stimulation input cable to these electrodes30.</li>
	<li>Insert the animal into the MRI bore and place it at the iso-center approximately.</li>
</ol>
4. Measuring anatomical MR images
<ol>
	<li>Click the calibration menu button in the main user interface. Perform the calibrations of the MRI system clicking the following items in the Adjustment Platform user interface (see Help menu in the console software): Find the basic resonance frequency, Calibrate the RF pulse power, Set the optimal receiver gain, Measure the B0 map in the animal for shimming, Run global linear shims based on non-localized free induction decay (FID) integral. 
	NOTE: This step takes less than 2 min.</li>
	<li>Run a Position sequence by clicking the &#8220;Scan&#8221; button to find the head location of the animal inside the MRI bore. If the head is not located at the iso-center, adjust the head location while moving the cradle back and forth until the head is located at the iso-center.</li>
	<li>Run a Localizer sequence by clicking the &#8220;Scan&#8221; button to identify an ROI in the head. Select Map Shim and define the ROI of the shim volume to cover the whole brain in the localizer image and then, run a high order (e.g., 2nd or 3rd order) shimming using the &#8220;Shim up to&#8221; option to reduce the main magnetic field (B0) inhomogeneities at the ROI. 
	NOTE: The high order shimming is a critical step to improve the quality of BOLD-fMRI data when EPI sequences are used.</li>
	<li>Run a T2-weighted RARE sequence by clicking the &#8220;Scan&#8221; button to acquire anatomical images covering the whole brain in a coronal view (e.g., the following sequence parameters are used: repetition time (TR) 4000 ms, effective echo time (TE) 36.1 ms, matrix 128 x 128, field of view (FOV) 19.2x19.2 mm2, number of slices 32, slice thickness 0.3 mm, RARE factor 8). 
	NOTE: In the following real-time fMRI visualization step, the anatomical images are used to register 3D EPI images as a template.</li>
</ol>
5. Real-Time fMRI software set-up and fMRI response visualization
<ol>
	<li>Open a terminal window and go to the real-time AFNI plugin path using the following command: 
	cd /home/(user name)/rt_afni 
	NOTE: The AFNI plugin script, &#8220;afni_rt&#8221; is included in the Supplementary files.</li>
	<li>Execute AFNI software with the real-time plugin using the command and options below. 
	afni -rt 
	-yestplugouts 
	-DAFNI_REALTIME_MP_HOST_PORT=localhost:(port number) 
	-DAFNI_REALTIME_Graph=Realtime 
	-DAFNI_FIM_IDEAL=(Paradigm) 
	NOTE: In the first case, the code allows external programs to exchange data with AFNI while in the second case the real-time plugin will attempt to open a TCP socket to the user-defined localhost and port. In the third and fourth cases, the codes will plot the time course of fMRI data in real-time and plot the time course of the user-defined paradigm in the fMRI time course respectively when real-time fMRI data are acquired. For further details, check https://afni.nimh.nih.gov/pub/dist/doc/program_help/README.environment.html.</li>
	<li>Monitor upcoming AFNI BRIK files defined by using the command &#8220;Dimon&#8221; as shown in Figure 2 with the following options: 
	Dimon -tr (TR of EPI) -nt (NRepetitions of EPI) 
	-rt -quit 
	-infile_pattern realtime*.BRIK 
	-file_type AFNI 
	NOTE: &#8220;Dimon&#8221; is a command to monitor the real-time acquisition of AFNI image files using the following options: &#8220;-rt&#8221; which executes the real-time plugin and &#8220;-infile_pattern (data name).BRIK -file_type AFNI&#8221; which allows the plugin to read the specific BRIK files and to send them into AFNI for display and formatting. For further details, check https://afni.nimh.nih.gov/pub/dist/doc/program_help/Dimon.html.</li>
	<li>Use &#8220;pvcmd&#8221; command with the following options: 
	pvcmd -a JMacroManager JMMExecuteMacro -category $USER -macro Feed2AFNI_rt3DEPI 
	NOTE: This code exists in the macro script, &#8220;Setup_rt3DEPI&#8221;, to run the background macro script, &#8220;Feed2AFNI_rt3DEPI&#8221;, right after clicking &#8220;Scan&#8221; button for EPI acquisition.</li>
	<li>Use &#8220;exec pvcmd&#8221; command with the following options to get EPI acquisition parameters. 
	exec pvcmd -a ParxServer -r ParamGetValue -psid $ParSpaceId -param (PVM parameters of EPI) -id 10 -args $AcqKey $ParSpaceId $ProcnoPath</li>
	<li>Use &#8220;exec to3d&#8221; command with the following options to convert EPI raw data to AFNI files in real-time in the background macro script, &#8220;Feed2AFNI_rt3DEPI&#8221;. 
	exec to3d -omri -xFOV $FOV_X -yFOV $FOV_Y -zFOV $FOV_Z -prefix $LastVolName $ImgFormat$Path2dseq</li>
	<li>Make sure that EPI geometrical information is consistent with the anatomy orientation. 
	NOTE: The &#8220;to3d&#8221; AFNI command will run automatically with the geometrical information such as the field of view (FOV) and matrix size to convert the fMRI raw data into one AFNI BRIK data whenever each 3D volume data is stored after every single TR as shown in Figure 2. The image orientation can be changed with the geometrical information parameters of &#8220;to3d&#8221;. For further details, check https://afni.nimh.nih.gov/pub/dist/doc/program_help/to3d.html.</li>
	<li>Turn on an electrical stimulus isolator and perform electrical forepaw stimulation for one evoked fMRI study (e.g., 3Hz, 4s pulse width 300us, 2.5mA) using stimulation blocks. 
	NOTE: Here, the block-design paradigm consists of 10 pre-stimulation scans, 3 stimulation scans and 12 inter-stimulation scans (15 scans per epoch).</li>
	<li>Run a T2*-weighted 3D EPI sequence by clicking the &#8220;Scan&#8221; button for the BOLD-fMRI study (e.g., the following parameters are used: TR/TE 1500/14 ms, matrix 64 x 64 x 32, FOV 19.2 x 19.2 x 9.6 mm3, and resolution 300 x 300 x 300 &#181;m3). 
	NOTE: As soon as clicking the &#8220;Scan&#8221; button, monitoring, and processing raw data will be done by using the predefined macro scripts in real-time. Once one AFNI BRIK dataset is converted, voxel-wise time course graphs for 3D EPI images are displayed in the AFNI software and automatically updated for every single TR.</li>
	<li>To overlay the EPI images on top of the anatomical RARE images, convert the RARE images to an AFNI BRIK dataset using the command &#8220;to3d&#8221; as in step 5.6, then register the EPI images to the anatomical images using the &#8220;align_epi_anat.py&#8221; AFNI script with the following options: 
	align_epi_anat.py -anat anatomy_template_al+orig -epi epi.$(epi data number)+orig -epi_base 1 -suffix _volreg -rat_align -cost lpa -epi2anat 
	NOTE: For further details, check https://afni.nimh.nih.gov/pub/dist/doc/program_help/ align_epi_anat.py.html.</li>
	<li>To process functional maps of the BOLD responses, calculate the deconvolution of 3D+time dataset with a specific stimulus time series using the &#8220;3dDeconvolve&#8221; command with the following options: 
	3dDeconvolve -input (input file name)+orig. -nfirst 0 -polort 3 -num_stimts 1 -stim_times 1 (stimulation paradigm file name) &#39;BLOCK(4,1)&#39; -stim_label 1 forepaw -tout -fout -rout 
	NOTE: Image processing steps such as spatial smoothing or temporal filtering have been incorporated into a customized AFNI data processing script. For further details, check https://afni.nimh.nih.gov/afni/doc/help/3dDeconvolve.html.</li>
	<li>To visualize functional maps of the BOLD signals, use an interactive clustering in the AFNI software. Open the &#8220;Define Overlay&#8221; option and use the &#8220;Clusters&#8221; function from the AFNI user interface menu.</li>
	<li>After the last fMRI scan, take the animal out of the MRI scanner and euthanize it according to the approved protocols. 
	NOTE: Image processing functions of AFNI and macro-functions in the latest console software were used to process the real-time fMRI data. Detailed information and descriptions of macro-functions can be found from the help menu in the console software. The AFNI software is a freeware, that can be directly downloaded through the NIMH-AFNI website. The related scripts to build the linkage between AFNI and the console system are attached.</li>
</ol>

<ol>
	<li>Ogawa, S., Lee, T. M., Kay, A. R., Tank, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Brain+magnetic+resonance+imaging+with+contrast+dependent+on+blood+oxygenation.">Brain magnetic resonance imaging with contrast dependent on blood oxygenation.</a> Proceedings of the National Academy of Sciences U.S.A. 87 (24), 9868-9872 (1990).</li><li>Belliveau, J. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+mapping+of+the+human+visual+cortex+by+magnetic+resonance+imaging.">Functional mapping of the human visual cortex by magnetic resonance imaging.</a> Science. 254 (5032), 716-719 (1991).</li><li>Stehling, M. K., Turner, R., Mansfield, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Echo-planar+imaging:+magnetic+resonance+imaging+in+a+fraction+of+a+second.">Echo-planar imaging: magnetic resonance imaging in a fraction of a second.</a> Science. 254 (5028), 43-50 (1991).</li><li>Bandettini, P. A., Wong, E. C., Hinks, R. S., Tikofsky, R. S., Hyde, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Time+course+EPI+of+human+brain+function+during+task+activation.">Time course EPI of human brain function during task activation.</a> Magnetic Resonance in Medicine. 25 (2), 390-397 (1992).</li><li>Kwong, K. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamic+magnetic+resonance+imaging+of+human+brain+activity+during+primary+sensory+stimulation.">Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation.</a> Proceedings of the National Academy of Science U. S. A. 89 (12), 5675-5679 (1992).</li><li>Ogawa, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intrinsic+signal+changes+accompanying+sensory+stimulation:+functional+brain+mapping+with+magnetic+resonance+imaging.">Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging.</a> Proceedings of the National Academy of Science U. S. A. 89 (13), 5951-5955 (1992).</li><li>Biswal, B., Yetkin, F. Z., Haughton, V. M., Hyde, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+connectivity+in+the+motor+cortex+of+resting+human+brain+using+echo-planar+MRI.">Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.</a> Magnetic Resonance in Medicine. 34 (4), 537-541 (1995).</li><li>Logothetis, N. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=What+we+can+do+and+what+we+cannot+do+with+fMRI.">What we can do and what we cannot do with fMRI.</a> Nature. 453 (7197), 869-878 (2008).</li><li>Kim, S. G., Ogawa, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biophysical+and+physiological+origins+of+blood+oxygenation+level-dependent+fMRI+signals.">Biophysical and physiological origins of blood oxygenation level-dependent fMRI signals.</a> Journal of Cerebral Blood Flow and Metabolism. 32 (7), 1188-1206 (2012).</li><li>Peltier, S. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+connectivity+changes+with+concentration+of+sevoflurane+anesthesia.">Functional connectivity changes with concentration of sevoflurane anesthesia.</a> Neuroreport. 16 (3), 285-288 (2005).</li><li>Dopfel, D., Zhang, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mapping+stress+networks+using+functional+magnetic+resonance+imaging+in+awake+animals.">Mapping stress networks using functional magnetic resonance imaging in awake animals.</a> Neurobiology of Stress. 9, 251-263 (2018).</li><li>Hu, X. P., Le, T. H., Parrish, T., Erhard, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Retrospective+Estimation+and+Correction+of+Physiological+Fluctuation+in+Functional+Mri.">Retrospective Estimation and Correction of Physiological Fluctuation in Functional Mri.</a> Magnetic Resonance in Medicine. 34 (2), 201-212 (1995).</li><li>Birn, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+physiological+noise+in+resting-state+functional+connectivity.">The role of physiological noise in resting-state functional connectivity.</a> Neuroimage. 62 (2), 864-870 (2012).</li><li>Caballero-Gaudes, C., Reynolds, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methods+for+cleaning+the+BOLD+fMRI+signal.">Methods for cleaning the BOLD fMRI signal.</a> Neuroimage. 154, 128-149 (2017).</li><li>Pais-Roldan, P., Biswal, B., Scheffler, K., Yu, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identifying+Respiration-Related+Aliasing+Artifacts+in+the+Rodent+Resting-State+fMRI.">Identifying Respiration-Related Aliasing Artifacts in the Rodent Resting-State fMRI.</a> Frontiers in Neuroscience. 12, 00788 (2018).</li><li>Glover, G. H., Li, T. Q., Ress, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Image-based+method+for+retrospective+correction+of+physiological+motion+effects+in+fMRI:+RETROICOR.">Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR.</a> Magnetic Resonance in Medicine. 44 (1), 162-167 (2000).</li><li>Chang, C., Cunningham, J. P., Glover, G. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+heart+rate+on+the+BOLD+signal:+The+cardiac+response+function.">Influence of heart rate on the BOLD signal: The cardiac response function.</a> Neuroimage. 44 (3), 857-869 (2009).</li><li>Birn, R. M., Diamond, J. B., Smith, M. A., Bandettini, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Separating+respiratory-variation-related+neuronal-activity-related+fluctuations+in+fluctuations+from+fMRI.">Separating respiratory-variation-related neuronal-activity-related fluctuations in fluctuations from fMRI.</a> Neuroimage. 31 (4), 1536-1548 (2006).</li><li>Golestani, A. M., Chang, C., Kwinta, J. B., Khatamian, Y. B., Chen, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mapping+the+end-tidal+CO2+response+function+in+the+resting-state+BOLD+fMRI+signal:+Spatial+specificity,+test-retest+reliability+and+effect+of+fMRI+sampling+rate.">Mapping the end-tidal CO2 response function in the resting-state BOLD fMRI signal: Spatial specificity, test-retest reliability and effect of fMRI sampling rate.</a> Neuroimage. 104, 266-277 (2015).</li><li>Lu, H. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+animal+functional+magnetic+resonance+imaging+and+its+application+to+neurophamacological+studies.">Real-time animal functional magnetic resonance imaging and its application to neurophamacological studies.</a> Magnetic Resonance Imaging. 26 (9), 1266-1272 (2008).</li><li>Cox, R. W., Jesmanowicz, A., Hyde, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+functional+magnetic+resonance+imaging.">Real-time functional magnetic resonance imaging.</a> Magnetic Resonance Medicine. 33 (2), 230-236 (1995).</li><li>Lee, C. C., Jack, C. R., Rossman, P. J., Riederer, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+reconstruction+and+high-speed+processing+in+functional+MR+imaging.">Real-time reconstruction and high-speed processing in functional MR imaging.</a> American Journal of Neuroradiology. 19 (7), 1297-1300 (1998).</li><li>Voyvodic, J. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+fMRI+paradigm+control,+physiology,+and+behavior+combined+with+near+real-time+statistical+analysis.">Real-time fMRI paradigm control, physiology, and behavior combined with near real-time statistical analysis.</a> Neuroimage. 10 (2), 91-106 (1999).</li><li>Cohen, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+functional+magnetic+resonance+imaging.">Real-time functional magnetic resonance imaging.</a> Methods. 25 (2), 201-220 (2001).</li><li>Posse, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+approach+to+measure+single-event+related+brain+activity+using+real-time+fMRI:+Feasibility+of+sensory,+motor,+and+higher+cognitive+tasks.">A new approach to measure single-event related brain activity using real-time fMRI: Feasibility of sensory, motor, and higher cognitive tasks.</a> Human Brain Mapping. 12 (1), 25-41 (2001).</li><li>Decharms, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reading+and+controlling+human+brain+activation+using+real-time+functional+magnetic+resonance+imaging.">Reading and controlling human brain activation using real-time functional magnetic resonance imaging.</a> Trends in Cognitive Sciences. 11 (11), 473-481 (2007).</li><li>Bruhl, A. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Making+Sense+of+Real-Time+Functional+Magnetic+Resonance+Imaging+(rtfMRI)+and+rtfMRI+Neurofeedback.">Making Sense of Real-Time Functional Magnetic Resonance Imaging (rtfMRI) and rtfMRI Neurofeedback.</a> International Journal of Neuropsychopharmacology. 18 (6), (2015).</li><li>Cox, R. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=AFNI:+Software+for+analysis+and+visualization+of+functional+magnetic+resonance+neuroimages.">AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages.</a> Computers and Biomedical Research. 29 (3), 162-173 (1996).</li><li>Liou, W. W., Goshgarian, H. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+assessment+of+the+effect+of+chronic+phrenicotomy+on+the+induction+of+the+crossed+phrenic+phenomenon.">Quantitative assessment of the effect of chronic phrenicotomy on the induction of the crossed phrenic phenomenon.</a> Experimental Neurology. 127 (1), 145-153 (1994).</li><li>Shih, Y. Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultra+high-resolution+fMRI+and+electrophysiology+of+the+rat+primary+somatosensory+cortex.">Ultra high-resolution fMRI and electrophysiology of the rat primary somatosensory cortex.</a> Neuroimage. 73, 113-120 (2013).</li><li>Masamoto, K., Kim, T., Fukuda, M., Wang, P., Kim, S. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Relationship+between+neural,+vascular,+and+BOLD+signals+in+isoflurane-anesthetized+rat+somatosensory+cortex.">Relationship between neural, vascular, and BOLD signals in isoflurane-anesthetized rat somatosensory cortex.</a> Cerebral Cortex. 17 (4), 942-950 (2007).</li><li>van Alst, T. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anesthesia+differentially+modulates+neuronal+and+vascular+contributions+to+the+BOLD+signal.">Anesthesia differentially modulates neuronal and vascular contributions to the BOLD signal.</a> Neuroimage. 195, 89-103 (2019).</li><li>Wu, T. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+isoflurane+anesthesia+on+resting-state+fMRI+signals+and+functional+connectivity+within+primary+somatosensory+cortex+of+monkeys.">Effects of isoflurane anesthesia on resting-state fMRI signals and functional connectivity within primary somatosensory cortex of monkeys.</a> Brain and Behavior. 6 (12), 00591 (2016).</li><li>Liu, X., Zhu, X. H., Zhang, Y., Chen, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+change+of+functional+connectivity+specificity+in+rats+under+various+anesthesia+levels+and+its+neural+origin.">The change of functional connectivity specificity in rats under various anesthesia levels and its neural origin.</a> Brain Topography. 26 (3), 363-377 (2013).</li><li>Liu, X. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiphasic+modification+of+intrinsic+functional+connectivity+of+the+rat+brain+during+increasing+levels+of+propofol.">Multiphasic modification of intrinsic functional connectivity of the rat brain during increasing levels of propofol.</a> Neuroimage. 83, 581-592 (2013).</li><li>Hutchison, R. M., Hutchison, M., Manning, K. Y., Menon, R. S., Everling, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isoflurane+induces+dose-dependent+alterations+in+the+cortical+connectivity+profiles+and+dynamic+properties+of+the+brain's+functional+architecture.">Isoflurane induces dose-dependent alterations in the cortical connectivity profiles and dynamic properties of the brain's functional architecture.</a> Human Brain Mapping. 35 (12), 5754-5775 (2014).</li><li>He, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultra-Slow+Single-Vessel+BOLD+and+CBV-Based+fMRI+Spatiotemporal+Dynamics+and+Their+Correlation+with+Neuronal+Intracellular+Calcium+Signals.">Ultra-Slow Single-Vessel BOLD and CBV-Based fMRI Spatiotemporal Dynamics and Their Correlation with Neuronal Intracellular Calcium Signals.</a> Neuron. 97 (4), 925-939 (2018).</li><li>Yoshida, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physiological+effects+of+a+habituation+procedure+for+functional+MRI+in+awake+mice+using+a+cryogenic+radiofrequency+probe.">Physiological effects of a habituation procedure for functional MRI in awake mice using a cryogenic radiofrequency probe.</a> Journal of Neuroscience Methods. 274, 38-48 (2016).</li></ol>

Sascha K&#246;hler is an employee at Bruker BioSpin MRI GmbH.

Real-time monitoring of the fMRI signal helps experimenters adjust the physiology of animals to optimize functional mapping. Motion artifacts in awake animals, as well as the anesthetic effect, are major factors that mediate the variability of fMRI signals, confounding the biological interpretation of the signal by itself31,32,33,34,35,<sup class="x...

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive method to measure the hemodynamic responses1,2,3,4,5,6,7,8,9, e.g., the blood-oxygen-level-dependent (BOLD), cerebral blood volume and flow signal, associated with neural activity in the brain. In animal studies, hemodynamic signals can be affected by anesthesia10, the stress level of awake animals11, as well as the potential non-physiological artifacts, e.g., cardiac pulsation and respiratory motions12,13,14,15. Although many post-processing methods have been developed to provide a retrospective analysis of the fMRI signal for the task-related and resting-state functional dynamics and connectivity mapping16,17,18,19, there are few techniques to provide a real-time brain function mapping solution and instantaneous readouts in the animal brain20 (most of which are mainly used for human brain mapping21,22,23,24,25,26,27). In particular, this kind of real-time fMRI mapping method is lacking in animal studies. It is necessary to set up an fMRI platform to enable the investigation of real-time brain state-dependent physiological stages and to provides real-time biofeedback stimulation paradigm for animal brain functional studies.
In the present work, we illustrate a real-time fMRI experimental set-up with the customized macro-functions of the MRI console software, demonstrating real-time monitoring of the evoked BOLD-fMRI responses in the primary forepaw somatosensory cortex (FP-S1) of the anesthetized rats. This real-time set-up allows for the visualization of the ongoing brain activation in functional maps, as well as individual time courses in a voxel-wise manner, using the existing neuroimage analysis software, Analysis of Functional NeuroImages (AFNI)28. The preparation of the real-time fMRI experimental set-up for the animal study is described in the protocol. Besides the animal set-up, we provide detailed procedures to set up the visualization and analysis of the real-time fMRI signals using the latest console software in parallel with the image processing scripts. In summary, the proposed real-time fMRI set-up for animal studies is a powerful tool for monitoring the dynamic fMRI signals in the animal brain using the MRI console system.

<table>
	<tbody>
		<tr>
			<td>14.1T Bruker MRI system</td>
			<td>Bruker BioSpin MRI GmbH</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>A365 Stimulus Isolator</td>
			<td>World Precision Instruments</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>AcqKnowledge Software</td>
			<td>Biopac</td>
			<td>RRID:SCR_014279, http://www.biopac.com/product/acqknowledge-software/</td>
			<td></td>
		</tr>
		<tr>
			<td>AFNI</td>
			<td>Cox, 1996</td>
			<td>RRID:SCR_005927, http://afni.nimh.nih.gov</td>
			<td></td>
		</tr>
		<tr>
			<td>CO2SMO (ETCO2/SpO2 Monitor), Model 7100</td>
			<td>Novametrix Medical Systems Inc</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Isoflurane</td>
			<td>CP-Pharma</td>
			<td>Cat# 1214</td>
			<td></td>
		</tr>
		<tr>
			<td>Master-9</td>
			<td>A.M.P.I</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Nanoliter Injector</td>
			<td>World Precision Instruments</td>
			<td>Cat# NANOFIL</td>
			<td></td>
		</tr>
		<tr>
			<td>Pancuronium Bromide</td>
			<td>Inresa Arzneimittel</td>
			<td>Cat# 34409.00.00</td>
			<td></td>
		</tr>
		<tr>
			<td>ParaVision 6</td>
			<td>Bruker BioSpin MRI GmbH</td>
			<td>RRID:SCR_001964</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline (PBS)</td>
			<td>Gibco</td>
			<td>Cat# 10010-023</td>
			<td></td>
		</tr>
		<tr>
			<td>Rat: Sprague Dawley rat</td>
			<td>Charles River Laboratories</td>
			<td>Crl:CD(SD)</td>
			<td></td>
		</tr>
		<tr>
			<td>SAR-830/AP Ventilator</td>
			<td>CWE</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>&#945;-chloralose</td>
			<td>Sigma-Aldrich</td>
			<td>Cat# C0128-25G;RRID</td>
			<td></td>
		</tr>
	</tbody>
</table>

real-time fmri brain mapping in animals

Dynamic fMRI responses vary largely according to the physiological conditions of animals either under anesthesia or in awake states. We developed a real-time fMRI platform to guide experimenters to monitor fMRI responses instantaneously during acquisition, which can be used to modify the physiology of animals to achieve desired hemodynamic responses in animal brains. The real-time fMRI set-up is based on a 14.1T preclinical MRI system, enabling the real-time mapping of dynamic fMRI responses in the primary forepaw somatosensory cortex (FP-S1) of anesthetized rats. Instead of a retrospective analysis to investigate confounding sources leading to the variability of fMRI signals, the real-time fMRI platform provides a more effective scheme to identify dynamic fMRI responses using customized macro-functions and a common neuroimage analysis software in the MRI system. Also, it provides immediate troubleshooting feasibility and a real-time biofeedback stimulation paradigm for brain functional studies in animals.

Figure 3 and Figure 4 show a representative real-time voxel-wise BOLD-fMRI time course and functional maps with electrical forepaw stimulation (3 Hz, 4 s, pulse width 300 us, 2.5 mA). The fMRI design paradigm comprises 10 pre-stimulation scans, 3 stimulation scans, and 12 inter-stimulation scans with a total of 8 epochs (130 scans). The total scan time is 3 min 15 sec (195 sec). Figure 3 shows the voxel-wise time course (black line)...

Watch this Scientific Journal Video about Real-Time fMRI Brain Mapping in Animals at JoVE.com

Real-Time fMRI Brain Mapping in Animals

Animal brain functional mapping can benefit from the real-time functional magnetic resonance imaging (fMRI) experimental set-up. Using the latest software implemented in the animal MRI system, we established a real-time monitoring platform for small animal fMRI.

Dynamic fMRI responses vary largely according to the physiological conditions of animals either under anesthesia or in awake states. We developed a ...

Research

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Neuroscience

3.4K Views.  Max Planck Institute for Biological Cybernetics. Animal brain functional mapping can benefit from the real-time functional magnetic resonance imaging (fMRI) experimental set-up. Using the latest software implemented in the animal MRI system, we established a real-time monitoring platform for small animal fMRI.

Video: Real-Time fMRI Brain Mapping in Animals

Simultaneous fMRI and Electrophysiology in the Rodent Brain

To examine the neural basis of the blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) signal, we have developed a rodent model in which functional MRI data and in vivo intracortical recording can be performed simultaneously. The combination of MRI and electrical recording is technically challenging because the electrodes used for recording distort the MRI images and the MRI acquisition induces noise in the electrical recording. To minimize the mutual interference of the two modalities, glass microelectrodes were used rather than metal and a noise removal algorithm was implemented for the electrophysiology data. In our studies, two microelectrodes were separately implanted in bilateral primary somatosensory cortices (SI) of the rat and fixed in place. One coronal slice covering the electrode tips was selected for functional MRI. Electrode shafts and fixation positions were not included in the image slice to avoid imaging artifacts. The removed scalp was replaced with toothpaste to reduce susceptibility mismatch and prevent Gibbs ringing artifacts in the images. The artifact structure induced in the electrical recordings by the rapidly-switching magnetic fields during image acquisition was characterized by averaging all cycles of scans for each run. The noise structure during imaging was then subtracted from original recordings. The denoised time courses were then used for further analysis in combination with the fMRI data. As an example, the simultaneous acquisition was used to determine the relationship between spontaneous fMRI BOLD signals and band-limited intracortical electrical activity. Simultaneous fMRI and electrophysiological recording in the rodent will provide a platform for many exciting applications in neuroscience in addition to elucidating the relationship between the fMRI BOLD signal and neuronal activity.

We have developed a method for simultaneous functional magnetic resonance imaging and electrophysiological recording in the rodent brain, providing a platform for the investigation of the relationship between neural activity and the blood oxygenation level dependent (BOLD) MRI signal.

To examine the neural basis of the blood oxygenation level dependent (BOLD) magnetic resonance imaging (MRI) signal, we have developed a rodent model in ...

Combining Transcranial Magnetic Stimulation and fMRI to Examine the Default Mode Network

The default mode network is a group of brain regions that are active when an individual is not focused on the outside world and the brain is at "wakeful rest."1,2,3 It is thought the default mode network corresponds to self-referential or "internal mentation".2,3
It has been hypothesized that, in humans, activity within the default mode network is correlated with certain pathologies (for instance, hyper-activation has been linked to schizophrenia 4,5,6 and autism spectrum disorders 7 whilst hypo-activation of the network has been linked to Alzheimer's and other neurodegenerative diseases 8). As such, noninvasive modulation of this network may represent a potential therapeutic intervention for a number of neurological and psychiatric pathologies linked to abnormal network activation. One possible tool to effect this modulation is Transcranial Magnetic Stimulation: a non-invasive neurostimulatory and neuromodulatory technique that can transiently or lastingly modulate cortical excitability (either increasing or decreasing it) via the application of localized magnetic field pulses.9
In order to explore the default mode network's propensity towards and tolerance of modulation, we will be combining TMS (to the left inferior parietal lobe) with functional magnetic resonance imaging (fMRI). Through this article, we will examine the protocol and considerations necessary to successfully combine these two neuroscientific tools.

In this article, we examine the methodology and considerations relevant to the combination of TMS and fMRI to examine the effects of brain stimulation on the default network.

The default mode network is a group of brain regions that are active when an individual is not focused on the outside world and the brain is at "wakeful ...

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), magnetoencephalography or functional magnetic-resonance imaging. These techniques have either inherently low temporal or low spatial resolution, and suffer from low signal-to-noise ratio and/or poor high-frequency sensitivity. Thus, they are suboptimal for exploring the short-lived spatio-temporal dynamics of many of the underlying brain processes. In contrast, the invasive technique of electrocorticography (ECoG) provides brain signals that have an exceptionally high signal-to-noise ratio, less susceptibility to artifacts than EEG, and a high spatial and temporal resolution (i.e., &lt;1 cm/&lt;1 millisecond, respectively). ECoG involves measurement of electrical brain signals using electrodes that are implanted subdurally on the surface of the brain. Recent studies have shown that ECoG amplitudes in certain frequency bands carry substantial information about task-related activity, such as motor execution and planning1, auditory processing2 and visual-spatial attention3. Most of this information is captured in the high gamma range (around 70-110 Hz). Thus, gamma activity has been proposed as a robust and general indicator of local cortical function1-5. ECoG can also reveal functional connectivity and resolve finer task-related spatial-temporal dynamics, thereby advancing our understanding of large-scale cortical processes. It has especially proven useful for advancing brain-computer interfacing (BCI) technology for decoding a user's intentions to enhance or improve communication6 and control7. Nevertheless, human ECoG data are often hard to obtain because of the risks and limitations of the invasive procedures involved, and the need to record within the constraints of clinical settings. Still, clinical monitoring to localize epileptic foci offers a unique and valuable opportunity to collect human ECoG data. We describe our methods for collecting recording ECoG, and demonstrate how to use these signals for important real-time applications such as clinical mapping and brain-computer interfacing. Our example uses the BCI2000 software platform8,9 and the SIGFRIED10 method, an application for real-time mapping of brain functions. This procedure yields information that clinicians can subsequently use to guide the complex and laborious process of functional mapping by electrical stimulation.
Prerequisites and Planning:
Patients with drug-resistant partial epilepsy may be candidates for resective surgery of an epileptic focus to minimize the frequency of seizures. Prior to resection, the patients undergo monitoring using subdural electrodes for two purposes: first, to localize the epileptic focus, and second, to identify nearby critical brain areas (i.e., eloquent cortex) where resection could result in long-term functional deficits. To implant electrodes, a craniotomy is performed to open the skull. Then, electrode grids and/or strips are placed on the cortex, usually beneath the dura. A typical grid has a set of 8 x 8 platinum-iridium electrodes of 4 mm diameter (2.3 mm exposed surface) embedded in silicon with an inter-electrode distance of 1cm. A strip typically contains 4 or 6 such electrodes in a single line. The locations for these grids/strips are planned by a team of neurologists and neurosurgeons, and are based on previous EEG monitoring, on a structural MRI of the patient's brain, and on relevant factors of the patient's history. Continuous recording over a period of 5-12 days serves to localize epileptic foci, and electrical stimulation via the implanted electrodes allows clinicians to map eloquent cortex. At the end of the monitoring period, explantation of the electrodes and therapeutic resection are performed together in one procedure.
In addition to its primary clinical purpose, invasive monitoring also provides a unique opportunity to acquire human ECoG data for neuroscientific research. The decision to include a prospective patient in the research is based on the planned location of their electrodes, on the patient's performance scores on neuropsychological assessments, and on their informed consent, which is predicated on their understanding that participation in research is optional and is not related to their treatment. As with all research involving human subjects, the research protocol must be approved by the hospital's institutional review board. The decision to perform individual experimental tasks is made day-by-day, and is contingent on the patient's endurance and willingness to participate. Some or all of the experiments may be prevented by problems with the clinical state of the patient, such as post-operative facial swelling, temporary aphasia, frequent seizures, post-ictal fatigue and confusion, and more general pain or discomfort.
At the Epilepsy Monitoring Unit at Albany Medical Center in Albany, New York, clinical monitoring is implemented around the clock using a 192-channel Nihon-Kohden Neurofax monitoring system. Research recordings are made in collaboration with the Wadsworth Center of the New York State Department of Health in Albany. Signals from the ECoG electrodes are fed simultaneously to the research and the clinical systems via splitter connectors. To ensure that the clinical and research systems do not interfere with each other, the two systems typically use separate grounds. In fact, an epidural strip of electrodes is sometimes implanted to provide a ground for the clinical system. Whether research or clinical recording system, the grounding electrode is chosen to be distant from the predicted epileptic focus and from cortical areas of interest for the research. Our research system consists of eight synchronized 16-channel g.USBamp amplifier/digitizer units (g.tec, Graz, Austria). These were chosen because they are safety-rated and FDA-approved for invasive recordings, they have a very low noise-floor in the high-frequency range in which the signals of interest are found, and they come with an SDK that allows them to be integrated with custom-written research software. In order to capture the high-gamma signal accurately, we acquire signals at 1200Hz sampling rate-considerably higher than that of the typical EEG experiment or that of many clinical monitoring systems. A built-in low-pass filter automatically prevents aliasing of signals higher than the digitizer can capture. The patient's eye gaze is tracked using a monitor with a built-in Tobii T-60 eye-tracking system (Tobii Tech., Stockholm, Sweden). Additional accessories such as joystick, bluetooth Wiimote (Nintendo Co.), data-glove (5th Dimension Technologies), keyboard, microphone, headphones, or video camera are connected depending on the requirements of the particular experiment.
Data collection, stimulus presentation, synchronization with the different input/output accessories, and real-time analysis and visualization are accomplished using our BCI2000 software8,9. BCI2000 is a freely available general-purpose software system for real-time biosignal data acquisition, processing and feedback. It includes an array of pre-built modules that can be flexibly configured for many different purposes, and that can be extended by researchers' own code in C++, MATLAB or Python. BCI2000 consists of four modules that communicate with each other via a network-capable protocol: a Source module that handles the acquisition of brain signals from one of 19 different hardware systems from different manufacturers; a Signal Processing module that extracts relevant ECoG features and translates them into output signals; an Application module that delivers stimuli and feedback to the subject; and the Operator module that provides a graphical interface to the investigator.
A number of different experiments may be conducted with any given patient. The priority of experiments will be determined by the location of the particular patient's electrodes. However, we usually begin our experimentation using the SIGFRIED (SIGnal modeling For Realtime Identification and Event Detection) mapping method, which detects and displays significant task-related activity in real time. The resulting functional map allows us to further tailor subsequent experimental protocols and may also prove as a useful starting point for traditional mapping by electrocortical stimulation (ECS).
Although ECS mapping remains the gold standard for predicting the clinical outcome of resection, the process of ECS mapping is time consuming and also has other problems, such as after-discharges or seizures. Thus, a passive functional mapping technique may prove valuable in providing an initial estimate of the locus of eloquent cortex, which may then be confirmed and refined by ECS. The results from our passive SIGFRIED mapping technique have been shown to exhibit substantial concurrence with the results derived using ECS mapping10.
The protocol described in this paper establishes a general methodology for gathering human ECoG data, before proceeding to illustrate how experiments can be initiated using the BCI2000 software platform. Finally, as a specific example, we describe how to perform passive functional mapping using the BCI2000-based SIGFRIED system.

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

We present a method for collecting electrocorticographic signals for research purposes from humans who are undergoing invasive epilepsy monitoring. We show how to use the BCI2000 software platform for data collection, signal processing and stimulus presentation. Specifically, we demonstrate SIGFRIED, a BCI2000-based tool for real-time functional brain mapping.

Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), ...

Design and Assembly of an Ultra-light Motorized Microdrive for Chronic Neural Recordings in Small Animals

The ability to chronically record from populations of neurons in freely behaving animals has proven an invaluable tool for dissecting the function of neural circuits underlying a variety of natural behaviors, including navigation1 , decision making 2,3, and the generation of complex motor sequences4,5,6. Advances in precision machining has allowed for the fabrication of light-weight devices suitable for chronic recordings in small animals, such as mice and songbirds. The ability to adjust the electrode position with small remotely controlled motors has further increased the recording yield in various behavioral contexts by reducing animal handling.6,7
 Here we describe a protocol to build an ultra-light motorized microdrive for long-term chronic recordings in small animals. Our design evolved from an earlier published version7, and has been adapted for ease-of use and cost-effectiveness to be more practical and accessible to a wide array of researchers. This proven design 8,9,10,11 allows for fine, remote positioning of electrodes over a range of ~ 5 mm and weighs less than 750 mg when fully assembled. We present the complete protocol for how to build and assemble these drives, including 3D CAD drawings for all custom microdrive components.

The design, fabrication and assembly of an ultra-light motorized microdrive is described. The device provides a cost-effective and easy-to-use solution for chronic recordings of single units in small behaving animals.

The ability to chronically record from populations of neurons in freely behaving animals has proven an invaluable tool for dissecting the function of ...

Functional Imaging of Auditory Cortex in Adult Cats using High-field fMRI

Current knowledge of sensory processing in the mammalian auditory system is mainly derived from electrophysiological studies in a variety of animal models, including monkeys, ferrets, bats, rodents, and cats. In order to draw suitable parallels between human and animal models of auditory function, it is important to establish a bridge between human functional imaging studies and animal electrophysiological studies. Functional magnetic resonance imaging (fMRI) is an established, minimally invasive method of measuring broad patterns of hemodynamic activity across different regions of the cerebral cortex. This technique is widely used to probe sensory function in the human brain, is a useful tool in linking studies of auditory processing in both humans and animals and has been successfully used to investigate auditory function in monkeys and rodents. The following protocol describes an experimental procedure for investigating auditory function in anesthetized adult cats by measuring stimulus-evoked hemodynamic changes in auditory cortex using fMRI. This method facilitates comparison of the hemodynamic responses across different models of auditory function thus leading to a better understanding of species-independent features of the mammalian auditory cortex.

Functional studies of the auditory system in mammals have traditionally been conducted using spatially-focused techniques such as electrophysiological recordings. The following protocol describes a method of visualizing large-scale patterns of evoked hemodynamic activity in the cat auditory cortex using functional magnetic resonance imaging.

Current knowledge of sensory processing in the mammalian auditory system is mainly derived from electrophysiological studies in a variety of animal ...

Deep Brain Stimulation with Simultaneous fMRI in Rodents

In order to visualize the global and downstream neuronal responses to deep brain stimulation (DBS) at various targets, we have developed a protocol for using blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) to image rodents with simultaneous DBS. DBS fMRI presents a number of technical challenges, including accuracy of electrode implantation, MR artifacts created by the electrode, choice of anesthesia and paralytic to minimize any neuronal effects while simultaneously eliminating animal motion, and maintenance of physiological parameters, deviation from which can confound the BOLD signal.&#160;Our laboratory has developed a set of procedures that are capable of overcoming most of these possible issues. For electrical stimulation, a homemade tungsten bipolar microelectrode is used, inserted stereotactically at the stimulation site in the anesthetized subject. In preparation for imaging, rodents are fixed on a plastic headpiece and transferred to the magnet bore. For sedation and paralysis during scanning, a cocktail of dexmedetomidine and pancuronium is continuously infused, along with a minimal dose of isoflurane; this preparation minimizes the BOLD ceiling effect of volatile anesthetics. In this example experiment, stimulation of the subthalamic nucleus (STN) produces BOLD responses which are observed primarily in ipsilateral cortical regions, centered in motor cortex. Simultaneous DBS and fMRI allows the unambiguous modulation of neural circuits dependent on stimulation location and stimulation parameters, and permits observation of neuronal modulations free of regional bias. This technique may be used to explore the downstream effects of modulating neural circuitry at nearly any brain region, with implications for both experimental and clinical DBS.

This protocol describes a standard method for simultaneous functional magnetic resonance imaging and deep brain stimulation in the rodent. The combined use of these experimental tools allows for the exploration of global downstream activity in response to electrical stimulation at virtually any brain target.

In order to visualize the global and downstream neuronal responses to deep brain stimulation (DBS) at various targets, we have developed a protocol for ...

An Ex Vivo Laser-induced Spinal Cord Injury Model to Assess Mechanisms of Axonal Degeneration in Real-time

Injured CNS axons fail to regenerate and often retract away from the injury site. Axons spared from the initial injury may later undergo secondary axonal degeneration. Lack of growth cone formation, regeneration, and loss of additional myelinated axonal projections within the spinal cord greatly limits neurological recovery following injury. To assess how central myelinated axons of the spinal cord respond to injury, we developed an ex vivo living spinal cord model utilizing transgenic mice that express yellow fluorescent protein in axons and a focal and highly reproducible laser-induced spinal cord injury to document the fate of axons and myelin (lipophilic fluorescent dye Nile Red) over time using two-photon excitation time-lapse microscopy. Dynamic processes such as acute axonal injury, axonal retraction, and myelin degeneration are best studied in real-time. However, the non-focal nature of contusion-based injuries and movement artifacts encountered during in vivo spinal cord imaging make differentiating primary and secondary axonal injury responses using high resolution microscopy challenging. The ex vivo spinal cord model described here mimics several aspects of clinically relevant contusion/compression-induced axonal pathologies including axonal swelling, spheroid formation, axonal transection, and peri-axonal swelling providing a useful model to study these dynamic processes in real-time. Major advantages of this model are excellent spatiotemporal resolution that allows differentiation between the primary insult that directly injures axons and secondary injury mechanisms; controlled infusion of reagents directly to the perfusate bathing the cord; precise alterations of the environmental milieu (e.g., calcium, sodium ions, known contributors to axonal injury, but near impossible to manipulate in vivo); and murine models also offer an advantage as they provide an opportunity to visualize and manipulate genetically identified cell populations and subcellular structures. Here, we describe how to isolate and image the living spinal cord from mice to capture dynamics of acute axonal injury.

An Ex Vivo Laser-induced Spinal Cord Injury Model to Assess Mechanisms of Axonal Degeneration in Real-time

We present a protocol utilizing two-photon excitation time-lapse microscopy to simultaneously visualize the dynamics of axon and myelin injuries in real time. This proposed protocol permits studies of both intrinsic and extrinsic factors which can influence central myelinated axon fate after injury and contribute to permanent clinical disability.

Injured CNS axons fail to regenerate and often retract away from the injury site. Axons spared from the initial injury may later undergo secondary axonal ...

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain.

The ability to induce and/or control neural plasticity may be critical in future treatments for neurologic disorders and the recovery from brain injury. In this paper, we present a protocol on the use of neurofeedback training with functional magnetic resonance imaging to modulate human brain function.

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control ...

Real-time Iontophoresis with Tetramethylammonium to Quantify Volume Fraction and Tortuosity of Brain Extracellular Space

This review describes the basic concepts and protocol to perform the real-time iontophoresis (RTI) method, the gold-standard to explore and quantify the extracellular space (ECS) of the living brain. The ECS surrounds all brain cells and contains both interstitial fluid and extracellular matrix. The transport of many substances required for brain activity, including neurotransmitters, hormones, and nutrients, occurs by diffusion through the ECS. Changes in the volume and geometry of this space occur during normal brain processes, like sleep, and pathological conditions, like ischemia. However, the structure and regulation of brain ECS, particularly in diseased states, remains largely unexplored. The RTI method measures two physical parameters of living brain: volume fraction and tortuosity. Volume fraction is the proportion of tissue volume occupied by ECS. Tortuosity is a measure of the relative hindrance a substance encounters when diffusing through a brain region as compared to a medium with no obstructions. In RTI, an inert molecule is pulsed from a source microelectrode into the brain ECS. As molecules diffuse away from this source, the changing concentration of the ion is measured over time using an ion-selective microelectrode positioned roughly 100 &#181;m away. From the resulting diffusion curve, both volume fraction and tortuosity can be calculated. This technique has been used in brain slices from multiple species (including humans) and in vivo to study acute and chronic changes to ECS. Unlike other methods, RTI can be used to examine both reversible and irreversible changes to the brain ECS in real time.

This protocol describes real-time iontophoresis, a method that measures physical parameters of the extracellular space (ECS) of living brains. The diffusion of an inert molecule released into the ECS is used to calculate the ECS volume fraction and tortuosity. It is ideal for studying acute reversible changes to brain ECS.

This review describes the basic concepts and protocol to perform the real-time iontophoresis (RTI) method, the gold-standard to explore and quantify the ...

Live-cell Measurement of Odorant Receptor Activation Using a Real-time cAMP Assay

The enormous sizes of the mammalian odorant receptor (OR) families present difficulties to find their cognate ligands among numerous volatile chemicals. To efficiently and accurately deorphanize ORs, we combine the use of a heterologous cell line to express mammalian ORs and a genetically modified biosensor plasmid to measure cAMP production downstream of OR activation in real time. This assay can be used to screen odorants against ORs and vice versa. Positive odorant-receptor interactions from the screens can be subsequently confirmed by testing against various odor concentrations, generating concentration-response curves. Here we used this method to perform a high-throughput screening of an odorous compound against a human OR library expressed in Hana3A cells and confirmed that the positively-responding receptor is the cognate receptor for the compound of interest. We found this high-throughput detection method to be efficient and reliable in assessing OR activation and our data provide an example of its potential use in OR functional studies.

Characterizing the function of odorant receptors serves an indispensable part in the deorphanization process. We describe a method to measure the activation of odorant receptors in real time using a cAMP assay.

The enormous sizes of the mammalian odorant receptor (OR) families present difficulties to find their cognate ligands among numerous volatile chemicals. ...

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Subtitles

Real-Time fMRI Brain Mapping in Animals