静息状态大脑活动预测任务状态下脑部激活
Brain Activity in Resting-State Predicts Brain Activity in Task Execution
摘要: 人们在感知、思维和问题解决方面存在着许多差异,认知神经科学的一个重要目标就是探究这些差异现象背后的成因,了解这些差异有助于我们深入理解大脑活动和行为之间的联系。任务态功能磁共振成像(task functional magnetic resonance imaging, tfMRI)是研究个体神经活动差异的主要方法之一。但是任务态研究依赖于外部的实验任务和刺激,不能很好地解释个体之间脑部激活差异的来源。而静息态功能磁共振成像(resting-state functional magnetic resonance imaging, rsfMRI)不依赖于外部的试验任务和刺激,可以在一定程度上更好地预测个体神经活动的差异。本文从功能分化和功能整合两个方面,论述了静息态功能磁共振成像预测个体任务状态下脑激活的有效性和可行性。结果认为,静息态因为其简便易行,不依赖外部刺激,不依靠个体反应等优势,能很好地预测个体在任务执行状态下的脑激活,并且能一定程度上解释个体的脑激活的来源。据此,静息态预测任务状态下脑部激活的研究方法可以广泛应用于研究个体脑激活差异的研究当中。
Abstract: An important goal of cognitive neuroscience is to explore the causes behind the differences in perception, thoughts, and problem-solving among people which can help us gain insights into the connections between brain activity and behaviors. Task functional magnetic resonance imaging (tfMRI) is one of the main methods to find those differences. However, task functional magnetic resonance studies rely on external experimental tasks or stimuli, which may not explain the source of the differences in brain activation between individuals well. Resting-state functional magnetic resonance imaging (rsfMRI) can predict differences in neural activity better, and it does not rely on external experimental tasks or stimuli. In this paper, we discussed the effectiveness and feasibility of resting-state functional magnetic resonance imaging in predicting brain activation in task execution, from two aspects: functional differentiation and functional integration. The resting-state functional magnetic resonance imaging is simple and easy to operate, does not rely on external stimuli, does not rely on individual response, can predict the brain activation of individuals in the state of task execution well, and can explain the source of the brain activation to a certain extent. Those advantages suggest that the resting-state functional magnetic resonance imaging prediction method can be widely used in the study of individual differences in brain activation.
文章引用:何飞澜 (2021). 静息状态大脑活动预测任务状态下脑部激活. 心理学进展, 11(1), 184-193. https://doi.org/10.12677/AP.2021.111021

参考文献

[1] Anand, A., Li, Y., Wang, Y., Lowe, M. J., & Dzemidzic, M. (2009). Resting State Corticolimbic Connectivity Abnormalities in Unmedicated Bipolar Disorder and Unipolar Depression. Psychiatry Research, 171, 189-198.
https://doi.org /10.1016/j.pscychresns.2008.03.012
[2] Baldassarre, A., Lewis, C. M., Committeri, G., Snyder, A. Z., Romani, G. L., & Corbetta, M. (2012). Individual Variability in Functional Connectivity Predicts Performance of a Perceptual Task. Proceedings of the National Academy of Sciences of the United States of America, 109, 3516-3521.
https://doi.org /10.1073/pnas.1113148109
[3] Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. J. (1995). Functional Connectivity in the Motor Cortex of Resting Human Brain Using Echo-Planar MRI. Magnetic Resonance in Medicine, 34, 537-541.
https://doi.org /10.1002/mrm.1910340409
[4] Buckner, R. L., Krienen, F. M., & Yeo, B. T. (2013). Opportunities and Limitations of Intrinsic Functional Connectivity MRI. Nature Neuroscience, 16, 832-837.
https://doi.org /10.1038/nn.3423
[5] Bunge, S. A., Dudukovic, N. M., Thomason, M. E., Vaidya, C. J., & Gabrieli, J. D. E. (2002). Immature Frontal Lobe Contributions to Cognitive Control in Children: Evidence from fMRI. Neuron, 33, 301-311.
https://doi.org /10.1016/S0896-6273(01)00583-9
[6] Chen, S. H. A., Wu, C.-Y., Lua, R.-P., Akoshi, M. M., & Nakai, T. (2013). Age Related Changes in Resting-State and Task-Activated Functional MRI Networks. 2013 7th International Symposium on Medical Information and Communication Technology (ISMICT), Tokyo, 6-8 March 2013, 218-222.
https://doi.org /10.1109/ISMICT.2013.6521732
[7] Engel, S. A., Rumelhart, D. E., Wandell, B. A., Lee, A. T., Glover, G. H., Chichilnisky, E. J. et al. (1994). fMRI of Human Visual Cortex. Nature, 369, 525.
https://doi.org /10.1038/369525a0
[8] Essen, D. C. V., Smith, S. M., Barch, D. M., Behrens, T. E. J., & Ugurbil, K. (2013). The WU-Minn Human Connectome Project: An Overview. NeuroImage, 80, 62-79.
https://doi.org /10.1016/j.neuroimage.2013.05.041
[9] Fox, M. D., & Raichle, M. E. (2007). Spontaneous Fluctuations in Brain Activity Observed with Functional Magnetic Resonance Imaging. Nature Reviews Neuroscience, 8, 700-711.
https://doi.org /10.1038/nrn2201
[10] Greicius, M. D., & Menon, V. (2004). Default-Mode Activity during a Passive Sensory Task: Uncoupled from Deactivation but Impacting Activation. Journal of Cognitive Neuroscience, 16, 1484-1492.
https://doi.org /10.1162/0898929042568532
[11] Greicius, M. D., Flores, B. H., Menon, V., Glover, G. H., Solvason, H. B., Kenna, H., Schatzberg, A. F. et al. (2007). Resting-State Functional Connectivity in Major Depression: Abnormally Increased Contributions from Subgenual Cingulate Cortex and Thalamus. Biological Psychiatry, 62, 429-437.
https://doi.org /10.1016/j.biopsych.2006.09.020
[12] Hasson, U., Nusbaum, H. C., & Small, S. L. (2009). Task-Dependent Organization of Brain Regions Active during Rest. Proceedings of the National Academy of Sciences of the United States of America, 106, 10841-10846.
https://doi.org /10.1073/pnas.0903253106
[13] Jenkinson, M., & Smith, S. (2001). A Global Optimisation Method for Robust Affine Registration of Brain Images. Medical Image Analysis, 5, 143-156.
https://doi.org /10.1016/S1361-8415(01)00036-6
[14] Kanai, R., & Rees, G. (2011). The Structural Basis of Inter-Individual Differences in Human Behaviour and Cognition. Nature Reviews Neuroscience, 12, 231-242.
https://doi.org /10.1038/nrn3000
[15] Kannurpatti, S. S., Rypma, B., & Biswal, B. B. (2012). Prediction of Task-Related BOLD fMRI with Amplitude Signatures of Resting-State fMRI. Frontiers in Systems Neuroscience, 6, 7.
https://doi.org /10.3389/fnsys.2012.00007
[16] Kong, F., Hu, S., Wang, X., Song, Y., & Liu, J. (2015). Neural Correlates of the Happy Life: The Amplitude of Spontaneous Low Frequency Fluctuations Predicts Subjective Well-Being. Neuroimage, 107, 136-145.
https://doi.org /10.1016/j.neuroimage.2014.11.033
[17] Lai, C. H., & Wu, Y. T. (2015). The Changes in the Low-Frequency Fluctuations of Cingulate Cortex and Postcentral Gyrus in the Treatment of Panic Disorder: The MRI Study. The World Journal of Biological Psychiatry, 17, 58-65.
https://doi.org /10.3109/15622975.2015.1017604
[18] Lemée, J. M., Berro, D. M., Bernard, F., Chinier, E., Leiber, L. M., Menei, P., & Ter Minassian, A. (2019). Resting-State Functional Magnetic Resonance Imaging versus Task-Based Activity for Language Mapping and Correlation with Perioperative Cortical Mapping. Brain and Behavior, 9, e01362.
https://doi.org /10.1002/brb3.1362
[19] Madhyastha, T. M., Askren, M. K., Boord, P., & Grabowski, T. J. (2015). Dynamic Connectivity at Rest Predicts Attention Task Performance. Brain Connect, 5, 45-59.
https://doi.org /10.1089/brain.2014.0248
[20] Mennes, M., Kelly, C., Zuo, X. N., Di Martino, A., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2010). Inter-Individual Differences in Resting-State Functional Connectivity Predict Task-Induced BOLD Activity. Neuroimage, 50, 1690-1701.
https://doi.org /10.1016/j.neuroimage.2010.01.002
[21] Muraskin, J., Dodhia, S., Lieberman, G., Garcia, J. O., Verstynen, T., Vettel, J. M. et al. (2016). Brain Dynamics of Post-Task Resting State Are Influenced by Expertise: Insights from Baseball Players. Human Brain Mapping, 37, 4454-4471.
https://doi.org /10.1002/hbm.23321
[22] Ochsner, K. N., Bunge, S. A., Gross, J. J., & Gabrieli, J. D. E. (2002). Rethinking Feelings: An fMRI Study of the Cognitive Regulation of Emotion. Journal of Cognitive Neuroscience, 14, 1215-1229.
https://doi.org /10.1162/089892902760807212
[23] Plata-Bello, J., Modroño, C., Hernández-Martín, E., Pérez-Martín, Y., Fariña, H., Castañón-Pérez, A. et al. (2017). The Mirror Neuron System Also Rests. Brain Structure and Function, 222, 2193-2202.
https://doi.org /10.1007/s00429-016-1335-5
[24] Sakaki, M., Nga, L., & Mather, M. (2013). Amygdala Functional Connectivity with Medial Prefrontal Cortex at Rest Predicts the Positivity Effect in Older Adults’ Memory. Journal of Cognitive Neuroscience, 25, 1206-1224.
https://doi.org /10.1162/jocn_a_00392
[25] Sala-Llonch, R., Pena-Gomez, C., Arenaza-Urquijo, E. M., Vidal-Pineiro, D., Bargallo, N., Junque, C., & Bartres-Faz, D. (2012). Brain Connectivity during Resting State and Subsequent Working Memory Task Predicts Behavioural Performance. Cortex, 48, 1187-1196.
https://doi.org /10.1016/j.cortex.2011.07.006
[26] Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., & Beckmann, C. F. (2009). Correspondence of the Brain’s Functional Architecture during Activation and Rest. Proceedings of the National Academy of Sciences, 106, 13040-13045.
https://doi.org /10.1073/pnas.0905267106
[27] Smitha, K. A., Arun, K. M., Rajesh, P. G., Thomas, B., Radhakrishnan, A., Sarma, P. S. et al. (2019). Resting fMRI as an Alternative for Task-Based fMRI for Language Lateralization in Temporal Lobe Epilepsy Patients: A Study Using Independent Component Analysis. Neuroradiology, 61, 803-810.
https://doi.org /10.1007/s00234-019-02209-w
[28] Tavor, I., Jones, O. P., Mars, R. B., Smith, S. M., Behrens, T. E., & Jbabdi, S. (2016). Task-Free MRI Predicts Individual Differences in Brain Activity during Task Performance. Science, 352, 216-220.
https://doi.org /10.1126/science.aad8127
[29] Thomason, M. E., Chang, C. E., Glover, G. H., Gabrieli, J. D. E., Greicius, M. D., & Gotlib, I. H. (2008). Default-Mode Function and Task-Induced Deactivation Have Overlapping Brain Substrates in Children. Neuroimage, 41, 1493-1503.
https://doi.org /10.1016/j.neuroimage.2008.03.029
[30] Tian, L., Ren, J., & Zang, Y. (2012). Regional Homogeneity of Resting State fMRI Signals Predicts Stop Signal Task Performance. Neuroimage, 60, 539-544.
https://doi.org /10.1016/j.neuroimage.2011.11.098
[31] Toro, R., Fox, P. T., & Paus, T. (2008). Functional Coactivation Map of the Human Brain. Cerebral Cortex, 18, 2553-2559.
https://doi.org /10.1093/cercor/bhn014
[32] Tung, K. C., Uh, J., Mao, D., Xu, F., Xiao, G., & Lu, H. (2013). Alterations in Resting Functional Connectivity Due to Recent Motor Task. NeuroImage, 78, 316-324.
https://doi.org /10.1016/j.neuroimage.2013.04.006
[33] Wang, L., Laviolette, P., O’Keefe, K., Putcha, D., Bakkour, A., Van Dijk, K. R., Sperling, R. A. et al. (2010). Intrinsic Connectivity between the Hippocampus and Posteromedial Cortex Predicts Memory Performance in Cognitively Intact Older Individuals. Neuroimage, 51, 910-917.
https://doi.org /10.1016/j.neuroimage.2010.02.046
[34] Wang, Z., Liu, J., Zhong, N., Qin, Y., Zhou, H., & Li, K. (2012). Changes in the Brain Intrinsic Organization in Both On-Task State and Post-Task Resting State. Neuroimage, 62, 394-407.
https://doi.org /10.1016/j.neuroimage.2012.04.051
[35] Yang, Y., Zhong, N., Imamura, K., Lu, S., Li, M., Zhou, H., Li, K. et al. (2016). Task and Resting-State fMRI Reveal Altered Salience Responses to Positive Stimuli in Patients with Major Depressive Disorder. PLoS ONE, 11, e0155092.
https://doi.org /10.1371/journal.pone.0155092
[36] Yuan, R., Di, X., Kim, E. H., Barik, S., Rypma, B., & Biswal, B. B. (2013). Regional Homogeneity of Resting-State fMRI Contributes to Both Neurovascular and Task Activation Variations. Magnetic Resonance Imaging, 31, 1492-1500.
https://doi.org /10.1016/j.mri.2013.07.005
[37] Zang, Y. F., He, Y., Zhu, C.-Z., Cao, Q.-J. et al. (2007). Altered Baseline Brain Activity in Children with ADHD Revealed by Resting-State Functional MRI. Brain & Development, 29, 83-91.
https://doi.org /10.1016/j.braindev.2006.07.002
[38] Zang, Y., Jiang, T., Lu, Y., He, Y., & Tian, L. (2004). Regional Homogeneity Approach to fMRI Data Analysis. Neuroimage, 22, 394-400.
https://doi.org /10.1016/j.neuroimage.2003.12.030
[39] Zou, Q. H., Zhu, C. Z., Yang, Y., Zuo, X. N., Long, X. Y., Cao, Q. J. et al. (2008). An Improved Approach to Detection of Amplitude of Low-Frequency Fluctuation (ALFF) for Resting-State fMRI: Fractional ALFF. Journal of Neuroscience Methods, 172, 137-141.
https://doi.org /10.1016/j.jneumeth.2008.04.012
[40] Zou, Q., Ross, T. J., Gu, H., Geng, X., Zuo, X. N., Hong, L. E., Yang, Y. et al. (2013). Intrinsic Resting-State Activity Predicts Working Memory Brain Activation and Behavioral Performance. Human Brain Mapping, 34, 3204-3215.
https://doi.org /10.1002/hbm.22136