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Enhancement of MR Images Using Registration for Signal Averaging
Abstract
PURPOSE: With the advent of noninvasive neuroimaging, a plethora of digital human neuroanatomical atlases has been developed. The accuracy of these atlases is constrained by the resolution and signal-gathering powers of available imaging equipment. In an attempt to circumvent these limitations and to produce a high resolution in vivo human neuroanatomy, we investigated the usefulness of intrasubject registration for post hoc MR signal averaging. METHOD: Twenty-seven high resolution (7 x 0.78 and 20 x 1.0 mm3) T1-weighted volumes were acquired from a single subject, along with 12 double echo T2/proton density-weighted volumes. These volumes were automatically registered to a common stereotaxic space in which they were subsampled and intensity averaged. The resulting images were examined for anatomical quality and usefulness for other analytical techniques. RESULTS: The quality of the resulting image from the combination of as few as five T1 volumes was visibly enhanced. The signal-to-noise ratio was expected to increase as the root of the number of contributing scans to 5.2, n = 27. The improvement in the n = 27 average was great enough that fine anatomical details, such as thalamic subnuclei and the gray bridges between the caudate and putamen, became crisply defined. The gray/white matter boundaries were also enhanced, as was the visibility of any finer structure that was surrounded by tissue of varying T1 intensity. The T2 and proton density average images were also of higher quality than single scans, but the improvement was not as dramatic as that of the T1 volumes. CONCLUSION: Overall, the enhanced signal in the averaged images resulted in higher quality anatomical images, and the data lent themselves to several postprocessing techniques. The high quality of the enhanced images permits novel uses of the data and extends the possibilities for in vivo human neuroanatomy.
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Citations
Cites
Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space
Collins, D. L., Neelin, P., Peters, T. M., & Evans, A. C. (1994) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199403000-00005 · Cited by 3,431
Self-citation
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A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data
Eickhoff, S. B., Stephan, K. E., Mohlberg, H., Grefkes, C., Fink, G. R., Amunts, K., & Zilles, K. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.12.034 · Cited by 4,033
Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., Habel, U., Schneider, F., & Zilles, K. (2005) · Anatomy and Embryology · doi:10.1007/s00429-005-0025-5 · Cited by 1,264
Testing Predictions From Personality Neuroscience: Brain Structure and the Big Five
DeYoung, C. G., Hirsh, J. B., Shane, M. S., Papademetris, X., Rajeevan, N., & Gray, J. R. (2010) · Psychological Science · doi:10.1177/0956797610370159 · Cited by 995
Astafiev, S. V., Shulman, G. L., Stanley, C. M., Snyder, A. Z., Van Essen, D. C., & Corbetta, M. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-11-04689.2003 · Cited by 640
Lian, C., Liu, M., Zhang, J., & Shen, D. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2889096 · Cited by 544
Effects of intranasal oxytocin on emotional face processing in women
Domes, G., Lischke, A., Berger, C., Grossmann, A., Hauenstein, K., Heinrichs, M., & Herpertz, S. C. (2010) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2009.06.016 · Cited by 521
Aβ amyloid and glucose metabolism in three variants of primary progressive aphasia
Rabinovici, G. D., Jagust, W. J., Furst, A. J., Ogar, J. M., Racine, C. A., Mormino, E. C., O'Neil, J. P., Lal, R. A., Dronkers, N. F., Miller, B. L., et al. (2008) · Annals of Neurology · doi:10.1002/ana.21451 · Cited by 477
Amunts, K., Weiss, P. H., Mohlberg, H., Pieperhoff, P., Eickhoff, S., Gurd, J. M., Marshall, J. C., Shah, N. J., Fink, G. R., & Zilles, K. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2003.12.031 · Cited by 475
Chen, M.-K., Mecca, A. P., Naganawa, M., Finnema, S. J., Toyonaga, T., Lin, S.-F., Najafzadeh, S., Ropchan, J., Lu, Y., McDonald, J. W., et al. (2018) · JAMA Neurology · doi:10.1001/jamaneurol.2018.1836 · Cited by 431
Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex
Arslan, S., Ktena, S. I., Makropoulos, A., Robinson, E. C., Rueckert, D., & Parisot, S. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.04.014 · Cited by 374
Genetics of brain fiber architecture and intellectual performance
Chiang, M.-C., Barysheva, M., Shattuck, D. W., Lee, A. D., Madsen, S. K., Avedissian, C., Klunder, A. D., Toga, A. W., McMahon, K. L., de Zubicaray, G. I., et al. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.4184-08.2009 · Cited by 406
Self-citationCieslik, E. C., Zilles, K., Caspers, S., Roski, C., Kellermann, T. S., Jakobs, O., Langner, R., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs256 · Cited by 391
“The mean EPI image for each subject was then spatially normalized to the Montreal Neurological Institute (MNI) single-subject template (Holmes et al. 1998) using the ‘unified segmentation’ approach (Ashburner and Friston 2005), and the ensuing deformation was applied to the individual EPI volumes.”
MethodThe human inferior parietal lobule in stereotaxic space
Caspers, S., Eickhoff, S. B., Geyer, S., Scheperjans, F., Mohlberg, H., Zilles, K., & Amunts, K. (2008) · Brain Structure and Function · doi:10.1007/s00429-008-0195-z · Cited by 395
Rostral and caudal prefrontal contribution to creativity: a meta-analysis of functional imaging data
Gonen-Yaacovi, G., de Souza, L. C., Levy, R., Urbanski, M., Josse, G., & Volle, E. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00465 · Cited by 376
EEG source imaging enhances the decoding of complex right-hand motor imagery tasks
Edelman, B. J., Baxter, B., & He, B. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2467312 · Cited by 370
Effectiveness of regional DTI measures in distinguishing Alzheimer’s disease, MCI, and normal aging
Nir, T. M., Jahanshad, N., Villalon-Reina, J. E., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2013.07.006 · Cited by 348
Self-citationOxytocin enhances brain reward system responses in men viewing the face of their female partner
Scheele, D., Wille, A., Kendrick, K. M., Stoffel-Wagner, B., Becker, B., Güntürkün, O., Maier, W., & Hurlemann, R. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1314190110 · Cited by 340
Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses
Cieslik, E. C., Mueller, V. I., Eickhoff, C. R., Langner, R., & Eickhoff, S. B. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.11.003 · Cited by 322
Beyond superior temporal cortex: Intersubject correlations in narrative speech comprehension
Wilson, S. M., Molnar-Szakacs, I., & Iacoboni, M. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhm049 · Cited by 281
Large-scale neural recordings with single neuron resolution using Neuropixels probes in human cortex
Paulk, A. C., Kfir, Y., Khanna, A. R., Mustroph, M. L., Trautmann, E. M., Soper, D. J., Stavisky, S. D., Welkenhuysen, M., Dutta, B., Shenoy, K. V., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-021-00997-0 · Cited by 283
Dual attention multi-instance deep learning for Alzheimer’s disease diagnosis with structural MRI
Zhu, W., Sun, L., Huang, J., Han, L., & Zhang, D. (2021) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2021.3077079 · Cited by 278
Critical brain regions for action recognition: lesion symptom mapping in left hemisphere stroke
Kalénine, S., Buxbaum, L. J., & Coslett, H. B. (2010) · Brain · doi:10.1093/brain/awq210 · Cited by 269
Fornito, A., Yucel, M., Dean, B., Wood, S. J., & Pantelis, C. (2009) · Schizophrenia Bulletin · doi:10.1093/schbul/sbn025 · Cited by 259
Oxytocin facilitates protective responses to aversive social stimuli in males
Striepens, N., Scheele, D., Kendrick, K. M., Becker, B., Schäfer, L., Schwalba, K., Reul, J., Maier, W., & Hurlemann, R. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1208852109 · Cited by 242
Disruption of functional networks in dyslexia: a whole-brain, data-driven analysis of connectivity
Finn, E. S., Shen, X., Holahan, J. M., Scheinost, D., Lacadie, C., Papademetris, X., Shaywitz, S. E., Shaywitz, B. A., & Constable, R. T. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.08.031 · Cited by 248
Segregation of the human medial prefrontal cortex in social cognition
Bzdok, D., Langner, R., Schilbach, L., Engemann, D. A., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00232 · Cited by 229
The Somatotopic Organization of Cytoarchitectonic Areas on the Human Parietal Operculum
Eickhoff, S. B., Grefkes, C., Zilles, K., & Fink, G. R. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhl090 · Cited by 227
Kinetics and dose dependency of intranasal oxytocin effects on amygdala reactivity
Spengler, F. B., Schultz, J., Scheele, D., Essel, M., Maier, W., Heinrichs, M., & Hurlemann, R. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.04.015 · Cited by 229
Simplified intersubject averaging on the cortical surface using SUMA
Argall, B. D., Saad, Z. S., & Beauchamp, M. S. (2006) · Human Brain Mapping · doi:10.1002/hbm.20158 · Cited by 200
Dennis, E. L., Jahanshad, N., McMahon, K. L., de Zubicaray, G. I., Martin, N. G., Hickie, I. B., Toga, A. W., Wright, M. J., & Thompson, P. M. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.09.004 · Cited by 222
Self-citationBourgeat, P., Chételat, G., Villemagne, V. L., Fripp, J., Raniga, P., Pike, K., Acosta, O., Szoeke, C., Ourselin, S., Ames, D., et al. (2010) · Neurology · doi:10.1212/wnl.0b013e3181c918b5 · Cited by 220
Finnema, S. J., Nabulsi, N. B., Mercier, J., Lin, S.-F., Chen, M.-K., Matuskey, D., Gallezot, J.-D., Henry, S., Hannestad, J., Huang, Y., et al. (2018) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x17724947 · Cited by 218
Circulating glucose levels modulate neural control of desire for high-calorie foods in humans
Page, K. A., Seo, D., Belfort-DeAguiar, R., Lacadie, C., Dzuira, J., Naik, S., Amarnath, S., Constable, R. T., Sherwin, R. S., & Sinha, R. (2011) · Journal of Clinical Investigation · doi:10.1172/jci57873 · Cited by 212
Oxytocin facilitates the extinction of conditioned fear in humans
Eckstein, M., Becker, B., Scheele, D., Scholz, C., Preckel, K., Schlaepfer, T. E., Grinevich, V., Kendrick, K. M., Maier, W., & Hurlemann, R. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.10.015 · Cited by 210
Hannestad, J., DellaGioia, N., Gallezot, J.-D., Lim, K., Nabulsi, N., Esterlis, I., Pittman, B., Lee, J.-Y., O’Connor, K. C., Pelletier, D., et al. (2013) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2013.06.010 · Cited by 204
Similarities and differences in perceiving threat from dynamic faces and bodies. An fMRI study
Kret, M. E., Pichon, S., Grèzes, J., & de Gelder, B. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.012 · Cited by 204
Morphological alterations in the thalamus, striatum, and pallidum in autism spectrum disorder
Schuetze, M., Park, M. T. M., Cho, I. Y., MacMaster, F. P., Chakravarty, M. M., & Bray, S. L. (2016) · Neuropsychopharmacology · doi:10.1038/npp.2016.64 · Cited by 186
Hoffstaedter, F., Grefkes, C., Caspers, S., Roski, C., Palomero‐Gallagher, N., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2014) · Human Brain Mapping · doi:10.1002/hbm.22363 · Cited by 164
“The mean image was then spatially normalized to the MNI single subject template [Holmes et al., 1998] using the “unified segmentation” approach [Ashburner and Friston, 2005].”
MethodFunctional segregation of the human dorsomedial prefrontal cortex
Eickhoff, S. B., Laird, A. R., Fox, P. T., Bzdok, D., & Hensel, L. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhu250 · Cited by 159
Inferior frontal regions underlie the perception of phonetic category invariance
Myers, E. B., Blumstein, S. E., Walsh, E., & Eliassen, J. (2009) · Psychological Science · doi:10.1111/j.1467-9280.2009.02380.x · Cited by 153
The Role of Sleep in Directed Forgetting and Remembering of Human Memories
Saletin, J. M., Goldstein, A. N., & Walker, M. P. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr034 · Cited by 151
Imaging the mental components of a planning task
Rowe, J. B., Owen, A. M., Johnsrude, I. S., & Passingham, R. E. (2001) · Neuropsychologia · doi:10.1016/s0028-3932(00)00109-3 · Cited by 151
Jacobsen, L. K., Picciotto, M. R., Heath, C. J., Frost, S. J., Tsou, K. A., Dwan, R. A., Jackowski, M. P., Constable, R. T., & Mencl, W. E. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.2402-07.2007 · Cited by 147
Peper, J. S., Mandl, R. C. W., Braams, B. R., de Water, E., Heijboer, A. C., Koolschijn, P. C. M. P., & Crone, E. A. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs163 · Cited by 144
Naganawa, M., Li, S., Nabulsi, N., Henry, S., Zheng, M.-Q., Pracitto, R., Cai, Z., Gao, H., Kapinos, M., Labaree, D., et al. (2021) · Journal of Nuclear Medicine · doi:10.2967/jnumed.120.249144 · Cited by 138
Default-mode network connectivity and white matter burden in late-life depression
Wu, M., Andreescu, C., Butters, M. A., Tamburo, R., Reynolds, C. F., & Aizenstein, H. (2011) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2011.04.003 · Cited by 140
Combining sparsity and rotational invariance in EEG/MEG source reconstruction
Haufe, S., Nikulin, V. V., Ziehe, A., Müller, K.-R., & Nolte, G. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.04.246 · Cited by 130
Personalized machine learning of depressed mood using wearables
Shah, R. V., Grennan, G., Zafar-Khan, M., Alim, F., Dey, S., Ramanathan, D., & Mishra, J. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01445-0 · Cited by 123
Revisiting mu suppression in autism spectrum disorder
Dumas, G., Soussignan, R., Hugueville, L., Martinerie, J., & Nadel, J. (2014) · Brain Research · doi:10.1016/j.brainres.2014.08.035 · Cited by 120
Oxytocin facilitates the sensation of social stress
Eckstein, M., Scheele, D., Weber, K., Stoffel‐Wagner, B., Maier, W., & Hurlemann, R. (2014) · Human Brain Mapping · doi:10.1002/hbm.22508 · Cited by 119
Newcombe, V. F. J., Williams, G. B., Scoffings, D., Cross, J., Carpenter, T. A., Pickard, J. D., & Menon, D. K. (2010) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.2009.196246 · Cited by 122
Cao, X., Liu, Z., Xu, C., Li, J., Gao, Q., Sun, N., Xu, Y., Ren, Y., Yang, C., & Zhang, K. (2012) · Journal of Affective Disorders · doi:10.1016/j.jad.2012.03.002 · Cited by 118
Glucose Metabolism in the Insula and Cingulate Is Affected by Systemic Inflammation in Humans
Hannestad, J., Subramanyam, K., DellaGioia, N., Planeta-Wilson, B., Weinzimmer, D., Pittman, B., & Carson, R. E. (2012) · Journal of Nuclear Medicine · doi:10.2967/jnumed.111.097014 · Cited by 113
Gender differences in neural correlates of stress-induced anxiety
Seo, D., Ahluwalia, A., Potenza, M. N., & Sinha, R. (2017) · Journal of Neuroscience Research · doi:10.1002/jnr.23926 · Cited by 114
Fox, H. C., Seo, D., Tuit, K., Hansen, J., Kimmerling, A., Morgan, P. T., & Sinha, R. (2012) · Journal of Psychopharmacology · doi:10.1177/0269881111430746 · Cited by 112
The saccadic spike artifact in MEG
Carl, C., Açık, A., König, P., Engel, A. K., & Hipp, J. F. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.020 · Cited by 110
Fürbass, F., Kural, M. A., Gritsch, G., Hartmann, M., Kluge, T., & Beniczky, S. (2020) · Clinical Neurophysiology · doi:10.1016/j.clinph.2020.02.032 · Cited by 106
First-in-Human Assessment of 11C-LSN3172176, an M1 Muscarinic Acetylcholine Receptor PET Radiotracer
Naganawa, M., Nabulsi, N., Henry, S., Matuskey, D., Lin, S.-F., Slieker, L., Schwarz, A. J., Kant, N., Jesudason, C., Ruley, K., et al. (2021) · Journal of Nuclear Medicine · doi:10.2967/jnumed.120.246967 · Cited by 94
The role of negative affectivity and social inhibition in perceiving social threat: An fMRI study
Kret, M. E., Denollet, J., Grèzes, J., & de Gelder, B. (2011) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2011.02.007 · Cited by 104
Hobeika, L., Diard‐Detoeuf, C., Garcin, B., Levy, R., & Volle, E. (2016) · Human Brain Mapping · doi:10.1002/hbm.23149 · Cited by 94
The scope of preserved procedural memory in amnesia
Cavaco, S. (2004) · Brain · doi:10.1093/brain/awh208 · Cited by 95
Altered brain response to drinking glucose and fructose in obese adolescents
Jastreboff, A. M., Sinha, R., Arora, J., Giannini, C., Kubat, J., Malik, S., Van Name, M. A., Santoro, N., Savoye, M., Duran, E. J., et al. (2016) · Diabetes · doi:10.2337/db15-1216 · Cited by 97
Sudre, G., Szekely, E., Sharp, W., Kasparek, S., & Shaw, P. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705229114 · Cited by 93
Cumulative adversity sensitizes neural response to acute stress: association with health symptoms
Seo, D., Tsou, K. A., Ansell, E. B., Potenza, M. N., & Sinha, R. (2014) · Neuropsychopharmacology · doi:10.1038/npp.2013.250 · Cited by 88
Real-time fMRI neurofeedback with War Veterans with chronic PTSD: a feasibility study
Gerin, M. I., Fichtenholtz, H., Roy, A., Walsh, C. J., Krystal, J. H., Southwick, S., & Hampson, M. (2016) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00111 · Cited by 84
Altered cerebral blood flow patterns associated with pathologic worry in the elderly
Andreescu, C., Gross, J. J., Lenze, E., Edelman, K. D., Snyder, S., Tanase, C., & Aizenstein, H. (2011) · Depression and Anxiety · doi:10.1002/da.20799 · Cited by 81
“After motion correction, the functional images from each subject were normalized into the standard Montreal Neurological Institute template space (Colin27).[41] A Gaussian smoothing filter (10 mm full width at half maximum) was then used on the normalized functional images to reduce spatial noise.”
MethodSex differences in the functional connectivity of the amygdalae in association with cortisol
Kogler, L., Müller, V. I., Seidel, E.-M., Boubela, R., Kalcher, K., Moser, E., Habel, U., Gur, R. C., Eickhoff, S. B., & Derntl, B. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.03.064 · Cited by 78
Finnema, S. J., Toyonaga, T., Detyniecki, K., Chen, M., Dias, M., Wang, Q., Lin, S., Naganawa, M., Gallezot, J., Lu, Y., et al. (2020) · Epilepsia · doi:10.1111/epi.16653 · Cited by 78
Gorges, M., Roselli, F., Müller, H.-P., Ludolph, A. C., Rasche, V., & Kassubek, J. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00200 · Cited by 76
Distinct Regions within Medial Prefrontal Cortex Process Pain and Cognition
Jahn, A., Nee, D. E., Alexander, W. H., & Brown, J. W. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.2180-16.2016 · Cited by 75
Resting state functional connectivity predicts neurofeedback response
Scheinost, D., Stoica, T., Wasylink, S., Gruner, P., Saksa, J., Pittenger, C., & Hampson, M. (2014) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2014.00338 · Cited by 70
Papadaniil, C. D., Kosmidou, V. E., Tsolaki, A., Tsolaki, M., Kompatsiaris, I. (., & Hadjileontiadis, L. J. (2016) · Brain Research · doi:10.1016/j.brainres.2016.07.043 · Cited by 71
Jung, Y.-H., Shin, J. E., Lee, Y. I., Jang, J. H., Jo, H. J., & Choi, S.-H. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00164 · Cited by 68
Finnema, S. J., Rossano, S., Naganawa, M., Henry, S., Gao, H., Pracitto, R., Maguire, R. P., Mercier, J., Kervyn, S., Nicolas, J., et al. (2019) · Epilepsia · doi:10.1111/epi.14701 · Cited by 65
Li, S., Naganawa, M., Pracitto, R., Najafzadeh, S., Holden, D., Henry, S., Matuskey, D., Emery, P. R., Cai, Z., Ropchan, J., et al. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-020-05149-3 · Cited by 61
Cognitive and Neural Correlates of Loneliness and Wisdom during Emotional Bias
Grennan, G., Balasubramani, P. P., Alim, F., Zafar-Khan, M., Lee, E. E., Jeste, D. V., & Mishra, J. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab012 · Cited by 57
Basu, I., Robertson, M. M., Crocker, B., Peled, N., Farnes, K., Vallejo-Lopez, D. I., Deng, H., Thombs, M., Martinez-Rubio, C., Cheng, J. J., et al. (2019) · Brain Stimulation · doi:10.1016/j.brs.2019.03.007 · Cited by 50
7T-guided super-resolution of 3T MRI
Bahrami, K., Shi, F., Rekik, I., Gao, Y., & Shen, D. (2017) · Medical Physics · doi:10.1002/mp.12132 · Cited by 56
Brain morphometry shows effects of long-term musical practice in middle-aged keyboard players
Gärtner, H., Minnerop, M., Pieperhoff, P., Schleicher, A., Zilles, K., Altenmüller, E., & Amunts, K. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00636 · Cited by 53
Midline frontal and occipito-temporal activity during error monitoring in dyadic motor interactions
Moreau, Q., Candidi, M., Era, V., Tieri, G., & Aglioti, S. M. (2020) · Cortex · doi:10.1016/j.cortex.2020.01.020 · Cited by 53
Elsey, J., Coates, A., Lacadie, C. M., McCrory, E. J., Sinha, R., Mayes, L. C., & Potenza, M. N. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.6 · Cited by 52
Angular versus spatial resolution trade-offs for diffusion imaging under time constraints
Zhan, L., Jahanshad, N., Ennis, D. B., Jin, Y., Bernstein, M. A., Borowski, B. J., Jack, C. R., Toga, A. W., Leow, A. D., & Thompson, P. M. (2013) · Human Brain Mapping · doi:10.1002/hbm.22094 · Cited by 52
Self-citationSpectral Variability in the Aged Brain during Fine Motor Control
Quandt, F., Bönstrup, M., Schulz, R., Timmermann, J. E., Zimerman, M., Nolte, G., & Hummel, F. C. (2016) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2016.00305 · Cited by 38
“The forward solution is constructed with a segmented template MRI brain (Holmes et al., 1998) using the boundary element method and a template grid of 8 mm spacing (Oostenveld et al.”
MethodThe influence of oxytocin on volitional and emotional ambivalence
Preckel, K., Scheele, D., Eckstein, M., Maier, W., & Hurlemann, R. (2015) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsu147 · Cited by 41
Ventromedial prefrontal cortex thinning in preschool-onset depression
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Metadata
- Authors
- Holmes, C. J., Hoge, R., Collins, L., Woods, R., Toga, A. W., & Evans, A. C.
- Venue
- Journal of Computer Assisted Tomography
- Published
- 1998-03
- Volume
- 22
- Issue
- 2
- Pages
- 324-333
- ISSN
- 0363-8715 (ISSN-L)
- OpenAlex
- W2011481459
- Cited by
- 1,417
- References
- 1
- FWCI
- 9.82
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
