Name: co-analysis of brain structure and function using fmri and diffusion-weighted imaging
Uploaded: 2012-11-08T12:00:00
Description: Watch this Scientific Journal Video about Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging at JoVE.com

List acknowledgements and funding sources. The work is supported by NIH RO1-MH54246 (M. B.), National Science Foundation BCS0923763 (M.B.), the Defense Advanced Research Projects Agency (DARPA) under contract NBCHZ090439 (W. S.), the Office of Naval Research (ONR) under award N00014-11-1-0399 (W. S.), and the Army Research Lab (ARL) under contract W911NF-10-2-0022 (W. S.). The views, opinions, and/or findings contained in this presentation are those of the authors and should not be interpreted as representing the official views or policies, either expressed or implied, of the above agencies or the United States Department of Defense.

1. Equipment for MR Data Acquisition
Figures 2 and 3 summarize a number of choices to be made in diffusion MRI acquisition, data reconstruction, and fiber tracking. Keep in mind that these choices typically involve trade-offs, and the best choice may depend upon one's research objectives. For example, DSI and multi-shell HARDI (see Figure 2) typically use higher "b-values" (i.e., stronger diffusion weighting) than DTI. As a result, these methods have be...

<ol>
	<li>Wedeen, V. a. n. J., Hagmann, P., Tseng, W. I., Reese, T. G., Weisskoff, 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=Mapping+complex+tissue+architecture+with+diffusion+spectrum+magnetic+resonance+imaging.">Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging.</a> Magnetic Resonance in Medicine. 54 (6), 1377-1386 (2005).</li><li>Wedeen, V. J., Wang, R. P., Schmahmann, J. D., Benner, T., Tseng, W. Y. I., Dai, G., Pandya, D. N., 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=Diffusion+spectrum+magnetic+resonance+imaging+(DSI)+tractography+of+crossing+fibers.">Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers.</a> NeuroImage. 41 (4), 1267-1277 (2008).</li><li>Pipe, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pulse+Sequences+for+Diffusion-weighted+MRI.">Pulse Sequences for Diffusion-weighted MRI.</a> Diffusion MRI: From quantitative measurement to in-vivo neuroanatomy. , 12-35 (2009).</li><li>Le Bihan, D., Poupon, C., Amadon, A., Lethimonnier, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Artifacts+and+pitfalls+in+diffusion+MRI.">Artifacts and pitfalls in diffusion MRI.</a> Journal of Magnetic Resonance Imaging: JMRI. 24 (3), 478-488 (2006).</li><li>Tuch, D. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Q-ball+imaging.">Q-ball imaging.</a> Magnetic Resonance in Medicine. 52 (6), 1358-1372 (2004).</li><li>Sakaie, K. E., Lowe, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+objective+method+for+regularization+of+fiber+orientation+distributions+derived+from+diffusion-weighted+MRI.">An objective method for regularization of fiber orientation distributions derived from diffusion-weighted MRI.</a> NeuroImage. 34 (1), 169-176 (2007).</li><li>Reese, T. G., Benner, T., Wang, R., Feinberg, D. A., Wedeen, V. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Halving+imaging+time+of+whole+brain+diffusion+spectrum+imaging+and+diffusion+tractography+using+simultaneous+image+refocusing+in+EPI.">Halving imaging time of whole brain diffusion spectrum imaging and diffusion tractography using simultaneous image refocusing in EPI.</a> Journal of Magnetic Resonance Imaging. 29 (3), 517-522 (2009).</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>Cox, R. W., 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=Software+tools+for+analysis+and+visualization+of+fMRI+data.">Software tools for analysis and visualization of fMRI data.</a> NMR in Biomedicine. 10 (4-5), 171-178 (1997).</li><li>Goebel, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BRAINVOYAGER:+a+program+for+analyzing+and+visualizing+functional+and+structural+magnetic+resonance+data+sets.">BRAINVOYAGER: a program for analyzing and visualizing functional and structural magnetic resonance data sets.</a> NeuroImage. 3, S604 (1996).</li><li>Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., 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=Advances+in+functional+and+structural+MR+image+analysis+and+implementation+as+FSL.">Advances in functional and structural MR image analysis and implementation as FSL.</a> NeuroImage. 23, S208-S219 (2004).</li><li>Woolrich, M. W., Jbabdi, S., Patenaude, B., Chappell, M., Makni, S., Behrens, T., Beckmann, C., 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=Bayesian+analysis+of+neuroimaging+data+in+FSL.">Bayesian analysis of neuroimaging data in FSL.</a> NeuroImage. 45, S173-S186 (2009).</li><li>Friston, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Statistical parametric mapping: the analysis of functional brain images. , (2007).</li><li>Nichols, T., Hayasaka, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Controlling+the+familywise+error+rate+in+functional+neuroimaging:+a+comparative+review.">Controlling the familywise error rate in functional neuroimaging: a comparative review.</a> Statistical Methods in Medical Research. 12 (5), 419-446 (2003).</li><li>Benjamini, Y., Hochberg, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Controlling+the+false+discovery+rate:+a+practical+and+powerful+approach+to+multiple+testing.">Controlling the false discovery rate: a practical and powerful approach to multiple testing.</a> Journal of the Royal Statistical Society, Series B (Methodological. 57 (1), 289-300 (1995).</li><li>Logan, B. R., Rowe, D. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+evaluation+of+thresholding+techniques+in+fMRI+analysis.">An evaluation of thresholding techniques in fMRI analysis.</a> NeuroImage. 22, 95-108 (2004).</li><li>Basser, P. J., Mattiello, J., LeBihan, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+the+effective+self-diffusion+tensor+from+the+NMR+spin+echo.">Estimation of the effective self-diffusion tensor from the NMR spin echo.</a> Journal of Magnetic Resonance, Series B. 103 (3), 247-254 (1994).</li><li>Basser, P. J., Mattiello, J., LeBihan, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MR+diffusion+tensor+spectroscopy+and+imaging.">MR diffusion tensor spectroscopy and imaging.</a> Biophysical Journal. 66 (1), 259-267 (1994).</li><li>Frank, L. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anisotropy+in+high+angular+resolution+diffusion-weighted+MRI.">Anisotropy in high angular resolution diffusion-weighted MRI.</a> Magnetic Resonance in Medicine. 45 (6), 935-939 (2001).</li><li>Frank, L. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+anisotropy+in+high+angular+resolution+diffusion-weighted+MRI.">Characterization of anisotropy in high angular resolution diffusion-weighted MRI.</a> Magnetic Resonance in Medicine. 47 (6), 1083-1099 (2002).</li><li>Tuch, D. S., Reese, T. G., Wiegell, M. R., Makris, N., Belliveau, J. W., Wedeen, V. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High+angular+resolution+diffusion+imaging+reveals+intravoxel+white+matter+fiber+heterogeneity.">High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity.</a> Magnetic Resonance in Medicine. 48 (4), 577-582 (2002).</li><li>Descoteaux, M., Angelino, E., Fitzgibbons, S., Deriche, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regularized,+fast,+and+robust+analytical+Q-ball+imaging.">Regularized, fast, and robust analytical Q-ball imaging.</a> Magnetic Resonance in Medicine. 58 (3), 497-510 (2007).</li><li>Tuch, D. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Q-ball+imaging.">Q-ball imaging.</a> Magnetic Resonance in Medicine. 52 (6), 1358-1372 (2004).</li><li>Yeh, F. C., Wedeen, V. J., Tseng, W. -. Y. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Generalized+Q-sampling+imaging.">Generalized Q-sampling imaging.</a> IEEE Transactions on Medical Imaging. 29 (9), 1626-1635 (2010).</li><li>Wang, R., Benner, T., Sorensen, A. G., Wedeen, V. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diffusion+Toolkit:+a+software+package+for+diffusion+imaging+data+processing+and+tractography.">Diffusion Toolkit: a software package for diffusion imaging data processing and tractography.</a> Proc. Intl. Soc. Mag. Reson. Med. , 3720 (2007).</li><li>Sundaram, S. K., Kumar, A., Makki, M. I., Behen, M. E., Chugani, H. T., Chugani, D. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diffusion+tensor+imaging+of+frontal+lobe+in+autism+spectrum+disorder.">Diffusion tensor imaging of frontal lobe in autism spectrum disorder.</a> Cereb Cortex. 18 (11), 2659-2665 (2008).</li><li>Greenberg, A. S., Verstynen, T., Chiu, Y. -. C., Yantis, S., Schneider, W., Behrmann, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visuotopic+Cortical+Connectivity+Underlying+Attention+Revealed+with+White-Matter+Tractography.">Visuotopic Cortical Connectivity Underlying Attention Revealed with White-Matter Tractography.</a> The Journal of Neuroscience. 32 (8), 2773-2782 (2012).</li><li>Slotnick, S. D., Yantis, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Efficient+acquisition+of+human+retinotopic+maps.">Efficient acquisition of human retinotopic maps.</a> Human Brain Mapping. 18 (1), 22-29 (2003).</li><li>Greenberg, A. S., Esterman, M., Wilson, D., Serences, J. T., Yantis, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Control+of+spatial+and+feature-based+attention+in+frontoparietal+cortex.">Control of spatial and feature-based attention in frontoparietal cortex.</a> The Journal of Neuroscience. 30 (43), 14330-14339 (2010).</li><li>Kastner, S., Ungerleider, L. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+of+visual+attention+in+the+human+cortex.">Mechanisms of visual attention in the human cortex.</a> Annual Review of Neuroscience. 23, 315-341 (2000).</li><li>B&#252;rgel, U., Amunts, K., Hoemke, L., Mohlberg, H., Gilsbach, J. M., Zilles, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=White+matter+fiber+tracts+of+the+human+brain:+Three-dimensional+mapping+at+microscopic+resolution,+topography+and+intersubject+variability.">White matter fiber tracts of the human brain: Three-dimensional mapping at microscopic resolution, topography and intersubject variability.</a> NeuroImage. 29 (4), 1092-1105 (2006).</li><li>Behrens, T. E. J., Jbabdi, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> MR Diffusion Tractography. Diffusion MRI: From quantitative measurement to in-vivo neuroanatomy. , 333-352 (2009).</li><li>Verstynen, T., Jarbo, K., Pathak, S., Schneider, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+mapping+of+microstructural+somatotopies+in+the+human+corticospinal+pathways.">In vivo mapping of microstructural somatotopies in the human corticospinal pathways.</a> Journal of Neurophysiology. 105 (1), 336-346 (2011).</li><li>Jarbo, K., Verstynen, T., Schneider, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+quantification+of+global+connectivity+in+the+human+corpus+callosum.">In vivo quantification of global connectivity in the human corpus callosum.</a> NeuroImage. , (2012).</li><li>Verstynen, T., Badre, D., Jarbo, K., Schneider, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microstructural+organizational+patterns+in+the+human+corticostriatal+system.">Microstructural organizational patterns in the human corticostriatal system.</a> , (2012).</li><li>Wang, Y., Fern&#225;ndez-Miranda, J. C., Verstynen, T., Pathak, S., Schneider, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identifying+human+brain+tracts+with+tractography+and+fiber+microdissection:+mapping+connectivity+of+the+middle+longitudinal+fascicle+as+the+dorsal+auditory+pathway.">Identifying human brain tracts with tractography and fiber microdissection: mapping connectivity of the middle longitudinal fascicle as the dorsal auditory pathway.</a> , (2012).</li><li>Fernandez-Miranda, J. C., Engh, J. A., Pathak, S. K., Madhok, R., Boada, F. E., Schneider, W., Kassam, 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=High-definition+fiber+tracking+guidance+for+intraparenchymal+endoscopic+port+surgery.">High-definition fiber tracking guidance for intraparenchymal endoscopic port surgery.</a> Journal of Neurosurgery. 113 (5), 990-999 (2010).</li><li>Fernandez-Miranda, J. C., Engh, J., Pathak, S., Wang, Y., Jarbo, K., Verstynen, T., Boada, F., Schneider, W., Friedlander, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-definition+fiber+tractography+of+the+human+brain:+neuroanatomical+validation+and+neurosurgical+applications.">High-definition fiber tractography of the human brain: neuroanatomical validation and neurosurgical applications.</a> , (2012).</li><li>Shin, S., Verstynen, T., Pathak, S., Jarbo, K., Hricik, A., Maserati, M., Beers, S., Puccio, A. M., Okonkwo, D., Schneider, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High+definition+fiber+tracking+for+assessment+of+neurologic+deficit+in+a+case+of+traumatic+brain+injury.">High definition fiber tracking for assessment of neurologic deficit in a case of traumatic brain injury.</a> Journal of Neurosurgery. , (2012).</li><li>Mori, S., Crain, B. J., Chacko, V. P., Van Zijl, P. C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+tracking+of+axonal+projections+in+the+brain+by+magnetic+resonance+imaging.">Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging.</a> Annals of Neurology. 45 (2), 265-269 (1999).</li><li>Tournier, J., Mori, S., Leemans, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diffusion+tensor+imaging+and+beyond.">Diffusion tensor imaging and beyond.</a> Magnetic Resonance in Medicine. 65 (6), 1532-1556 (2011).</li><li>Seunarine, K. K., Alexander, D. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Multiple Fibers: Beyond the Diffusion Tensor. Diffusion MRI: From quantitative measurement to in-vivo neuroanatomy. , (2009).</li></ol>

High-resolution DWI and fiber tractography provide a powerful approach for examining the connective structure of the human brain. Here, we present evidence that this structural architecture is meaningfully related to brain function, assessed by fMRI. By using tractography seeds based on fMRI task activation, we find evidence that brain areas which are co-active during visual attention are anatomically connectedconsistent with prior knowledge of functional neuroanatomy (Figure 7). Similarly, the functiona...

co-analysis of brain structure and function using fmri and diffusion-weighted imaging

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)1, 2 protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for the purpose of monitoring task-relevant brain activity in networks of interest.

Watch this Scientific Journal Video about Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging at JoVE.com

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

We describe a novel approach for simultaneous analysis of brain function and structure using magnetic resonance imaging (MRI). We assess brain structure with high-resolution diffusion-weighted imaging and white-matter fiber tractography. Unlike standard structural MRI, these techniques allow us to directly relate anatomical connectivity to functional properties of brain networks.

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when ...

co-analysis-brain-structure-function-using-fmri-diffusion-weighted

Research

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Neuroscience

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 ...

DiOLISTIC Labeling of Neurons from Rodent and Non-human Primate Brain Slices

DiOLISTIC staining uses the gene gun to introduce fluorescent dyes, such as DiI, into neurons of brain slices (Gan et al., 2009; O'Brien and Lummis, 2007; Gan et al., 2000). Here we provide a detailed description of each step required together with exemplary images of good and bad outcomes that will help when setting up the technique. In our experience, a few steps proved critical for the successful application of DiOLISTICS. These considerations include the quality of the DiI-coated bullets, the extent of fixative exposure, and the concentration of detergent used in the incubation solutions. Tips and solutions for common problems are provided. This is a versatile labeling technique that can be applied to multiple animal species at a wide range of ages. Unlike other fluorescent labeling techniques that are limited to preparations from young animals or restricted to mice because they rely on the expression of a fluorescent transgene, DiOLISTIC labeling can be applied to animals of all ages, species and genotypes and it can be used in combination with immunostaining to identify a specific subpopulation of cells. Here we demonstrate the use of DiOLISTICS to label neurons in brain slices from adult mice and adult non-human primates with the purpose of quantifying dendrite branching and dendritic spine morphology.

We demonstrate the use of the gene gun to introduce fluorescent dyes, such as DiI, into neurons in brain slices from rodents and non-human primates of different ages. In this particular case, we use adult mice (3-6 months old) and adult cynomologus monkeys (9-15 years old). This technique, originally described by the laboratory of Dr. Lichtman (Gan et al., 2000), is well suited for the study of dendritic branching and dendritic spine morphology and can be combined with traditional immunostaining, if detergents are kept at a low concentration.

DiOLISTIC staining uses the gene gun to introduce fluorescent dyes, such as DiI, into neurons of brain slices (Gan et al., 2009; O'Brien and Lummis, 2007; ...

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 ...

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 ...

Non-invasive Parenchymal, Vascular and Metabolic High-frequency Ultrasound and Photoacoustic Rat Deep Brain Imaging

Photoacoustics and high frequency ultrasound stands out as powerful tools for neurobiological applications enabling high-resolution imaging on the central nervous system of small animals. However, transdermal and transcranial neuroimaging is frequently affected by low sensitivity, image aberrations and loss of space resolution, requiring scalp or even skull removal before imaging. To overcome this challenge, a new protocol is presented to gain significant insights in brain hemodynamics by photoacoustic and high-frequency ultrasounds imaging with the animal skin and skull intact. The procedure relies on the passage of ultrasound (US) waves and laser directly through the fissures that are naturally present on the animal cranium. By juxtaposing the imaging transducer device exactly in correspondence to these selected areas where the skull has a reduced thickness or is totally absent, one can acquire high quality deep images and explore internal brain regions that are usually difficult to anatomically or functionally describe without an invasive approach. By applying this experimental procedure, significant data can be collected in both sonic and optoacoustic modalities, enabling to image the parenchymal and the vascular anatomy far below the head surface. Deep brain features such as parenchymal convolutions and fissures separating the lobes were clearly visible. Moreover, the configuration of large and small blood vessels was imaged at several millimeters of depth, and precise information were collected about blood fluxes, vascular stream velocities and the hemoglobin chemical state. This repertoire of data could be crucial in several research contests, ranging from brain vascular disease studies to experimental techniques involving the systemic administration of exogenous chemicals or other objects endowed with imaging contrast enhancement properties. In conclusion, thanks to the presented protocol, the US and PA techniques become an attractive noninvasive performance-competitive means for cortical and internal brain imaging, retaining a significant potential in many neurologic fields.

The present work describes a new protocol to perform non-invasive high-frequency ultrasound and photoacoustic based imaging on rat brain, to efficiently visualize deep subcortical regions and their vascular patterns by directing signals on skull foramina naturally present on animal cranium.

Photoacoustics and high frequency ultrasound stands out as powerful tools for neurobiological applications enabling high-resolution imaging on the central ...

Imaging Serotonergic Fibers in the Mouse Spinal Cord Using the CLARITY/CUBIC Technique

Long descending fibers to the spinal cord are essential for locomotion, pain perception, and other behaviors. The fiber termination pattern in the spinal cord of the majority of these fiber systems have not been thoroughly investigated in any species. Serotonergic fibers, which project to the spinal cord, have been studied in rats and opossums on histological sections and their functional significance has been deduced based on their fiber termination pattern in the spinal cord. With the development of CLARITY and CUBIC techniques, it is possible to investigate this fiber system and its distribution in the spinal cord, which is likely to reveal previously unknown features of serotonergic supraspinal pathways. Here, we provide a detailed protocol for imaging the serotonergic fibers in the mouse spinal cord using the combined CLARITY and CUBIC techniques. The method involves perfusion of a mouse with a hydrogel solution and clarification of the tissue with a combination of clearing reagents. Spinal cord tissue was cleared in just under two weeks, and the subsequent immunofluorescent staining against serotonin was completed in less than ten days. With a multi-photon fluorescent microscope, the tissue was scanned and a 3D image was reconstructed using Osirix software.

Supraspinal projections are important for pain perception and other behaviors, and serotonergic fibers are one of these fiber systems. The present study focused on the application of the combined CLARITY/CUBIC protocol to the mouse spinal cord in order to investigate the termination of these serotonergic fibers.

Long descending fibers to the spinal cord are essential for locomotion, pain perception, and other behaviors. The fiber termination pattern in the spinal ...

Peering at Brain Polysomes with Atomic Force Microscopy

The translational machinery, i.e., the polysome or polyribosome, is one of the biggest and most complex cytoplasmic machineries in cells. Polysomes, formed by ribosomes, mRNAs, several proteins and non-coding RNAs, represent integrated platforms where translational controls take place. However, while the ribosome has been widely studied, the organization of polysomes is still lacking comprehensive understanding. Thus much effort is required in order to elucidate polysome organization and any novel mechanism of translational control that may be embedded. Atomic force microscopy (AFM) is a type of scanning probe microscopy that allows the acquisition of 3D images at nanoscale resolution. Compared to electron microscopy (EM) techniques, one of the main advantages of AFM is that it can acquire thousands of images both in air and in solution, enabling the sample to be maintained under near physiological conditions without any need for staining and fixing procedures. Here, a detailed protocol for the accurate purification of polysomes from mouse brain and their deposition on mica substrates is described. This protocol enables polysome imaging in air and liquid with AFM and their reconstruction as three-dimensional objects. Complementary to cryo-electron microscopy (cryo-EM), the proposed method can be conveniently used for systematically analyzing polysomes and studying their organization.

While ribosome structure has been extensively characterized, the organization of polysomes is still understudied. To overcome this lack of knowledge, we present here a detailed preparation protocol for accurate imaging of mammalian polysomes by atomic force microscopy (AFM) in air and liquid.

The translational machinery, i.e., the polysome or polyribosome, is one of the biggest and most complex cytoplasmic machineries in cells. Polysomes, ...

A Free-breathing fMRI Method to Study Human Olfactory Function

The study of human olfaction is a highly complex and valuable field with applications ranging from biomedical research to clinical evaluation. Currently, evaluation of the functions of the human central olfactory system with functional magnetic resonance imaging (fMRI) is still a challenge because of several technical difficulties. There are some significant variables to take into account when considering an effective method for mapping the function of the central olfactory system using fMRI, including proper odorant selection, the interaction between odor presentation and respiration, and potential anticipation of or habituation to odorants. An event-related, respiration-triggered olfactory fMRI technique can accurately administer odorants to stimulate the olfactory system while minimizing potential interference. It can effectively capture the precise onsets of fMRI signals in the primary olfactory cortex using our data post-processing method. The technique presented here provides an efficient and practical means for generating reliable olfactory fMRI results. Such a technique can ultimately be applied in the clinical realm as a diagnostic tool for diseases associated with olfactory degeneration, including Alzheimer&#39;s and Parkinson&#39;s disease, as we begin to further understand the complexities of the human olfactory system.

We present the technical challenges and solutions for obtaining reliable functional magnetic resonance imaging (fMRI) data from the human central olfactory system. This includes special considerations in olfactory fMRI paradigm design, descriptions of fMRI data acquisition with an MRI-compatible olfactometer, odorant selection, and a special software tool for data post-processing.

The study of human olfaction is a highly complex and valuable field with applications ranging from biomedical research to clinical evaluation. Currently, ...

Studying Brain Function in Children Using Magnetoencephalography

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique which directly measures magnetic fields produced by the electrical activity of the human brain. MEG is quiet and less likely to induce claustrophobia compared with magnetic resonance imaging (MRI). It is therefore a promising tool for investigating brain function in young children. However, analysis of MEG data from pediatric populations is often complicated by head movement artefacts which arise as a consequence of the requirement for a spatially-fixed sensor array that is not affixed to the child's head. Minimizing head movements during MEG sessions can be particularly challenging as young children are often unable to remain still during experimental tasks. The protocol presented here aims to reduce head movement artefacts during pediatric MEG scanning. Prior to visiting the MEG laboratory, families are provided with resources that explain the MEG system and the experimental procedures in simple, accessible language. An MEG familiarization session is conducted during which children are acquainted with both the researchers and the MEG procedures. They are then trained to keep their head still whilst lying inside an MEG simulator. To help children feel at ease in the novel MEG environment, all of the procedures are explained through the narrative of a space mission. To minimize head movement due to restlessness, children are trained and assessed using fun and engaging experimental paradigms. In addition, children's residual head movement artefacts are compensated for during the data acquisition session using a real-time head movement tracking system. Implementing these child-friendly procedures is important for improving data quality, minimizing participant attrition rates in longitudinal studies, and ensuring that families have a positive research experience.

This article introduces a child-friendly research protocol designed to improve data quality by reducing head movement during pediatric magnetoencephalography (MEG). We familiarize families with the MEG environment, train children to remain still using an MEG simulator, and correct for residual head movement artefacts using a real-time head movement detection system.

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique which directly measures magnetic fields produced by the electrical activity of the ...