Journal articles on the topic 'FMRI signal'
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Choi, Uk-Su, Yul-Wan Sung, and Seiji Ogawa. "Effects of Physiological Signal Removal on Resting-State Functional MRI Metrics." Brain Sciences 13, no. 1 (December 20, 2022): 8. http://dx.doi.org/10.3390/brainsci13010008.
Full textKim, Seong-Gi, and Seiji Ogawa. "Biophysical and Physiological Origins of Blood Oxygenation Level-Dependent fMRI Signals." Journal of Cerebral Blood Flow & Metabolism 32, no. 7 (March 7, 2012): 1188–206. http://dx.doi.org/10.1038/jcbfm.2012.23.
Full textLogothetis, Nikos K. "The neural basis of the blood–oxygen–level–dependent functional magnetic resonance imaging signal." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 357, no. 1424 (August 29, 2002): 1003–37. http://dx.doi.org/10.1098/rstb.2002.1114.
Full textHayward, Peter. "Ephemeral signal in fMRI." Lancet Neurology 2, no. 4 (April 2003): 204. http://dx.doi.org/10.1016/s1474-4422(03)00369-7.
Full textBednařík, Petr, Ivan Tkáč, Federico Giove, Mauro DiNuzzo, Dinesh K. Deelchand, Uzay E. Emir, Lynn E. Eberly, and Silvia Mangia. "Neurochemical and BOLD Responses during Neuronal Activation Measured in the Human Visual Cortex at 7 Tesla." Journal of Cerebral Blood Flow & Metabolism 35, no. 4 (January 7, 2015): 601–10. http://dx.doi.org/10.1038/jcbfm.2014.233.
Full textGui, Renzhou, Tongjie Chen, and Han Nie. "Classification of Task-State fMRI Data Based on Circle-EMD and Machine Learning." Computational Intelligence and Neuroscience 2020 (August 1, 2020): 1–10. http://dx.doi.org/10.1155/2020/7691294.
Full textWang, Maosen, Yi He, Terrence J. Sejnowski, and Xin Yu. "Brain-state dependent astrocytic Ca2+ signals are coupled to both positive and negative BOLD-fMRI signals." Proceedings of the National Academy of Sciences 115, no. 7 (January 30, 2018): E1647—E1656. http://dx.doi.org/10.1073/pnas.1711692115.
Full textGrössinger, Doris, Silvia Erika Kober, Stefan M. Spann, Rudolf Stollberger, and Guilherme Wood. "Real-Time Functional Magnetic Resonance Imaging as a Tool for Neurofeedback." Lernen und Lernstörungen 9, no. 3 (July 2020): 151–62. http://dx.doi.org/10.1024/2235-0977/a000300.
Full textTong, Yunjie, Kimberly P. Lindsey, and Blaise deB Frederick. "Partitioning of Physiological Noise Signals in the Brain with Concurrent Near-Infrared Spectroscopy and fMRI." Journal of Cerebral Blood Flow & Metabolism 31, no. 12 (August 3, 2011): 2352–62. http://dx.doi.org/10.1038/jcbfm.2011.100.
Full textShen, Yuji, Risto A. Kauppinen, Rishma Vidyasagar, and Xavier Golay. "A Functional Magnetic Resonance Imaging Technique Based on Nulling Extravascular Gray Matter Signal." Journal of Cerebral Blood Flow & Metabolism 29, no. 1 (August 27, 2008): 144–56. http://dx.doi.org/10.1038/jcbfm.2008.96.
Full textJego, Pierrick, Jesús Pacheco-Torres, Alfonso Araque, and Santiago Canals. "Functional MRI in Mice Lacking IP3-Dependent Calcium Signaling in Astrocytes." Journal of Cerebral Blood Flow & Metabolism 34, no. 10 (August 6, 2014): 1599–603. http://dx.doi.org/10.1038/jcbfm.2014.144.
Full textWang, Xiao, Xiao-Hong Zhu, Yi Zhang, and Wei Chen. "Large Enhancement of Perfusion Contribution on fMRI Signal." Journal of Cerebral Blood Flow & Metabolism 32, no. 5 (March 7, 2012): 907–18. http://dx.doi.org/10.1038/jcbfm.2012.26.
Full textHe, Yi, Maosen Wang, and Xin Yu. "High spatiotemporal vessel-specific hemodynamic mapping with multi-echo single-vessel fMRI." Journal of Cerebral Blood Flow & Metabolism 40, no. 10 (November 7, 2019): 2098–114. http://dx.doi.org/10.1177/0271678x19886240.
Full textRaut, Savita V., and Dinkar M. Yadav. "A decomposition model and voxel selection framework for fMRI analysis to predict neural response of visual stimuli." Biomedical Engineering / Biomedizinische Technik 63, no. 2 (March 28, 2018): 163–75. http://dx.doi.org/10.1515/bmt-2016-0194.
Full textPower, Jonathan D., Mark Plitt, Stephen J. Gotts, Prantik Kundu, Valerie Voon, Peter A. Bandettini, and Alex Martin. "Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data." Proceedings of the National Academy of Sciences 115, no. 9 (February 12, 2018): E2105—E2114. http://dx.doi.org/10.1073/pnas.1720985115.
Full textSalch, Andrew, Adam Regalski, Hassan Abdallah, Raviteja Suryadevara, Michael J. Catanzaro, and Vaibhav A. Diwadkar. "From mathematics to medicine: A practical primer on topological data analysis (TDA) and the development of related analytic tools for the functional discovery of latent structure in fMRI data." PLOS ONE 16, no. 8 (August 12, 2021): e0255859. http://dx.doi.org/10.1371/journal.pone.0255859.
Full textPalmer, Helen S. "Optogenetic fMRI Sheds Light on the Neural Basis of the BOLD Signal." Journal of Neurophysiology 104, no. 4 (October 2010): 1838–40. http://dx.doi.org/10.1152/jn.00535.2010.
Full textFischer, David, Otto Rapalino, Matteo Fecchio, and Brian L. Edlow. "Ictal fMRI: Mapping Seizure Topography with Rhythmic BOLD Oscillations." Brain Sciences 12, no. 12 (December 13, 2022): 1710. http://dx.doi.org/10.3390/brainsci12121710.
Full textZhang, Jiang, Huafu Chen, Fang Fang, Hualin Liu, and Wei Liao. "A FREQUENCY SIGNAL METHOD FOR fMRI DATA ANALYSIS." Biomedical Engineering: Applications, Basis and Communications 22, no. 05 (October 2010): 377–83. http://dx.doi.org/10.4015/s1016237210002134.
Full textZhong, Yuan, Gang Zheng, Yijun Liu, and Guangming Lu. "Independent Component Analysis of Instantaneous Power-Based fMRI." Computational and Mathematical Methods in Medicine 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/579652.
Full textHarel, Noam, Sang-Pil Lee, Tsukasa Nagaoka, Dae-Shik Kim, and Seong-Gi Kim. "Origin of Negative Blood Oxygenation Level—Dependent fMRI Signals." Journal of Cerebral Blood Flow & Metabolism 22, no. 8 (August 2002): 908–17. http://dx.doi.org/10.1097/00004647-200208000-00002.
Full textZhu, David C., Takashi Tarumi, Muhammad Ayaz Khan, and Rong Zhang. "Vascular Coupling in Resting-State FMRI: Evidence from Multiple Modalities." Journal of Cerebral Blood Flow & Metabolism 35, no. 12 (July 15, 2015): 1910–20. http://dx.doi.org/10.1038/jcbfm.2015.166.
Full textNikolaou, F., C. Orphanidou, P. Papakyriakou, K. Murphy, R. G. Wise, and G. D. Mitsis. "Spontaneous physiological variability modulates dynamic functional connectivity in resting-state functional magnetic resonance imaging." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2067 (May 13, 2016): 20150183. http://dx.doi.org/10.1098/rsta.2015.0183.
Full textCifre, I., M. Zarepour, S. G. Horovitz, S. A. Cannas, and D. R. Chialvo. "Further results on why a point process is effective for estimating correlation between brain regions." Papers in Physics 12 (June 18, 2020): 120003. http://dx.doi.org/10.4279/pip.120003.
Full textChang, Catie, David A. Leopold, Marieke Louise Schölvinck, Hendrik Mandelkow, Dante Picchioni, Xiao Liu, Frank Q. Ye, Janita N. Turchi, and Jeff H. Duyn. "Tracking brain arousal fluctuations with fMRI." Proceedings of the National Academy of Sciences 113, no. 16 (April 5, 2016): 4518–23. http://dx.doi.org/10.1073/pnas.1520613113.
Full textKashyap, Amrit, and Shella Keilholz. "Dynamic properties of simulated brain network models and empirical resting-state data." Network Neuroscience 3, no. 2 (January 2019): 405–26. http://dx.doi.org/10.1162/netn_a_00070.
Full textMitra, A., A. Z. Snyder, C. D. Hacker, and M. E. Raichle. "Lag structure in resting-state fMRI." Journal of Neurophysiology 111, no. 11 (June 1, 2014): 2374–91. http://dx.doi.org/10.1152/jn.00804.2013.
Full textEkstrom, Arne D. "Regional variation in neurovascular coupling and why we still lack a Rosetta Stone." Philosophical Transactions of the Royal Society B: Biological Sciences 376, no. 1815 (November 16, 2020): 20190634. http://dx.doi.org/10.1098/rstb.2019.0634.
Full textAutio, Joonas A., Artem Shatillo, Rashid Giniatullin, and Olli H. Gröhn. "Parenchymal Spin-Lock fMRI Signals Associated with Cortical Spreading Depression." Journal of Cerebral Blood Flow & Metabolism 34, no. 5 (February 5, 2014): 768–75. http://dx.doi.org/10.1038/jcbfm.2014.16.
Full textCaballero-Gaudes, César, and Richard C. Reynolds. "Methods for cleaning the BOLD fMRI signal." NeuroImage 154 (July 2017): 128–49. http://dx.doi.org/10.1016/j.neuroimage.2016.12.018.
Full textParrish, Todd B., Darren R. Gitelman, Kevin S. LaBar, and M. Marsel Mesulam. "Signal to noise influence on clinical fMRI." NeuroImage 11, no. 5 (May 2000): S532. http://dx.doi.org/10.1016/s1053-8119(00)91463-0.
Full textPower, Jonathan D., Bradley L. Schlaggar, and Steven E. Petersen. "Studying Brain Organization via Spontaneous fMRI Signal." Neuron 84, no. 4 (November 2014): 681–96. http://dx.doi.org/10.1016/j.neuron.2014.09.007.
Full textHansen, Lars Kai, Finn Årup Nielsen, and Jan Larsen. "Exploring fMRI data for periodic signal components." Artificial Intelligence in Medicine 25, no. 1 (May 2002): 35–44. http://dx.doi.org/10.1016/s0933-3657(02)00007-6.
Full textHyde, James S., and Andrzej Jesmanowicz. "Cross-correlation: An fMRI signal-processing strategy." NeuroImage 62, no. 2 (August 2012): 848–51. http://dx.doi.org/10.1016/j.neuroimage.2011.10.064.
Full textBoynton, Geoffrey M., Stephen A. Engel, and David J. Heeger. "Linear systems analysis of the fMRI signal." NeuroImage 62, no. 2 (August 2012): 975–84. http://dx.doi.org/10.1016/j.neuroimage.2012.01.082.
Full textErné, S. N., H. P. Müller, H. G. Kammrath, R. Tomczak, and A. Wunderlich. "Signal to Noise Improvement in fMRI Analysis." Biomedizinische Technik/Biomedical Engineering 44, s2 (1999): 181–83. http://dx.doi.org/10.1515/bmte.1999.44.s2.181.
Full textAl Zoubi, Obada, Ahmad Mayeli, Masaya Misaki, Aki Tsuchiyagaito, Vadim Zotev, Hazem Refai, Martin Paulus, and Jerzy Bodurka. "Canonical EEG microstates transitions reflect switching among BOLD resting state networks and predict fMRI signal." Journal of Neural Engineering 18, no. 6 (December 1, 2021): 066051. http://dx.doi.org/10.1088/1741-2552/ac4595.
Full textWang, Kainan S., David V. Smith, and Mauricio R. Delgado. "Using fMRI to study reward processing in humans: past, present, and future." Journal of Neurophysiology 115, no. 3 (March 1, 2016): 1664–78. http://dx.doi.org/10.1152/jn.00333.2015.
Full textRamsey, Nick F., Brenda S. Kirkby, Peter Van Gelderen, Karen F. Berman, Jeff H. Duyn, Joe A. Frank, Venkata S. Mattay, et al. "Functional Mapping of Human Sensorimotor Cortex with 3D BOLD fMRI Correlates Highly with H215O PET rCBF." Journal of Cerebral Blood Flow & Metabolism 16, no. 5 (September 1996): 755–64. http://dx.doi.org/10.1097/00004647-199609000-00001.
Full textWen, Jie, Manu S. Goyal, Serguei V. Astafiev, Marcus E. Raichle, and Dmitriy A. Yablonskiy. "Genetically defined cellular correlates of the baseline brain MRI signal." Proceedings of the National Academy of Sciences 115, no. 41 (September 25, 2018): E9727—E9736. http://dx.doi.org/10.1073/pnas.1808121115.
Full textTian, Lixia, Juejing Ren, and Yufeng Zang. "Regional homogeneity of resting state fMRI signals predicts Stop signal task performance." NeuroImage 60, no. 1 (March 2012): 539–44. http://dx.doi.org/10.1016/j.neuroimage.2011.11.098.
Full textLotze, M., W. Grodd, F. A. Rodden, E. Gut, P. W. Schönle, B. Kardatzki, and L. G. Cohen. "Neuroimaging Patterns Associated with Motor Control in Traumatic Brain Injury." Neurorehabilitation and Neural Repair 20, no. 1 (March 2006): 14–23. http://dx.doi.org/10.1177/1545968305282919.
Full textFeige, Bernd, Klaus Scheffler, Fabrizio Esposito, Francesco Di Salle, Jürgen Hennig, and Erich Seifritz. "Cortical and Subcortical Correlates of Electroencephalographic Alpha Rhythm Modulation." Journal of Neurophysiology 93, no. 5 (May 2005): 2864–72. http://dx.doi.org/10.1152/jn.00721.2004.
Full textSchabdach, Jenna, Rafael Ceschin, Vanessa Schmithorst, M. Dylan Tisdall, Aaron Alexander-Bloch, and Ashok Panigrahy. "A Descriptive Review of the Impact of Patient Motion in Early Childhood Resting-State Functional Magnetic Resonance Imaging." Diagnostics 12, no. 5 (April 20, 2022): 1032. http://dx.doi.org/10.3390/diagnostics12051032.
Full textYarmish, Gail, and Michael L. Lipton. "Functional Magnetic Resonance Imaging: From Acquisition to Application." Einstein Journal of Biology and Medicine 20, no. 1 (March 2, 2016): 2. http://dx.doi.org/10.23861/ejbm200320103.
Full textCao, Benchun, Yanchun Liang, Shinichi Yoshida, and Renchu Guan. "Facial Expression Decoding based on fMRI Brain Signal." International Journal of Computers Communications & Control 14, no. 4 (August 5, 2019): 475–88. http://dx.doi.org/10.15837/ijccc.2019.4.3433.
Full textDeng, Fan, Dajiang Zhu, Jinglei Lv, Lei Guo, and Tianming Liu. "FMRI Signal Analysis Using Empirical Mean Curve Decomposition." IEEE Transactions on Biomedical Engineering 60, no. 1 (January 2013): 42–54. http://dx.doi.org/10.1109/tbme.2012.2221125.
Full textLiu, Thomas T. "Noise contributions to the fMRI signal: An overview." NeuroImage 143 (December 2016): 141–51. http://dx.doi.org/10.1016/j.neuroimage.2016.09.008.
Full textLiu, Thomas T., Alican Nalci, and Maryam Falahpour. "The global signal in fMRI: Nuisance or Information?" NeuroImage 150 (April 2017): 213–29. http://dx.doi.org/10.1016/j.neuroimage.2017.02.036.
Full textLipschutz, Brigitte, John Ashburner, Karl Friston, and Cathy Price. "Assessing study-specific regional variation in fMRI signal." NeuroImage 11, no. 5 (May 2000): S460. http://dx.doi.org/10.1016/s1053-8119(00)91391-0.
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