Neuroplasticity induced by working memory training: A spatio-temporal model of decreased distribution in brain regions based on fMRI experiments

doi:10.3724/SP.J.1042.2022.00255

Abstract

Abstract:

Working memory training (WMT) induces neuroplasticity, but its specific mechanism remains unclear. In order to explore the spatio-temporal characteristics of brain function changes induced by WMT, the findings of 37 fMRI papers on WMT in normal population over the last 20 years were investigated with a step-by-step approach, including 5 methods and the following 6 steps, as well as with two assumptions based on the two theories— “Extended Parieto-Frontal Integration Theory” (ExtPFIT) and “neuro efficiency hypothesis”. Step 1, the changes of activation pattern and function connectivity in various brain regions before and after WMT among the 37 papers were compared using descriptive review, frequency analysis and Chi-square test. It was found that 5 association areas, 7 macro regions and 3 sub-regions of the brain were changed by WMT. Especially, the number of articles reporting decreased activation in 3 sub-regions—superior frontal gyrus, inferior parietal lobule and cingulate gyrus was more than that reporting increased activation in them, and this difference was statistically significant. Step 2, 26 out of the 37 papers were used to conduct meta-analysis with activation likelihood estimation method, and it showed that 3 sub-regions with the statistically significant effects in their decreased activation were middle frontal gyrus (BA6 and 8), superior frontal gyrus (BA6) and anterior cingulate gyrus (BA24 and 32). Step 3, based on the comprehensive results of qualitative and quantitative research analyses, a spatio-temporal model of decreased distribution in brain regions of WMT was proposed, and there were 5 results and their discussions obtained with the said model. Step 4, 31 out of the 37 papers were analyzed using non-parametric tests to check the factors that possibly regulated the training effect of WMT, which showed that the respective effect of task type and time of the training on brain activation had statistically significant. Step 5, according to the above analyses, 3 conclusions were drawn regarding the spatio-temporal characteristics of the neuroplasticity induced by WMT in normal population, i.e. 1) WMT can either weaken or enhance the brain activities, and the weakening effect appears more prominent. In addition, updating and shorter time of WMT tend to induce more weakening effects; 2) Such changes occur mostly in the frontal-parietal association area, but also possibly in the temporal lobe, occipital lobe, cingulate gyrus, striatum and other association areas, which reflects the whole brain functional association within a certain range. It highlights the spatial characteristics of the neuroplasticity, which fits in easily with ExtPFIT; 3) The 4 sub-regions of the middle frontal gyrus, superior frontal gyrus, inferior parietal lobule and cingulate gyrus (anterior in particular) in decreased activation mainly reflect the spatial characteristics of the neuroplasticity which fits in easily with “neural efficiency hypothesis” and “smarter brains may be slightly lazier”. Step 6, it was proposed that further research of the neuroplasticity induced by WMT was to possibly focus on low brain activity on its plasticity, distinguish the temporal characteristics of the training effect reflected in 4 sub-regions of middle frontal gyrus, superior frontal gyrus, inferior parietal lobule and cingulate gyrus (anterior in particular), as well as to probe the comprehensive influencing factors that increase or decrease the brain activities.

Key words: working memory training, neuroplasticity, a spatio-temporal model of decreased distribution in brain regions, middle frontal gyrus, superior frontal gyrus, anterior cingulate gyrus

CLC Number:

B842

CHEN Xingming, FU Tong, LIU Chang, ZHANG Bin, FU Yunfa, LI Enze, ZHANG Jian, CHEN Shengqiang, DANG Caiping. Neuroplasticity induced by working memory training: A spatio-temporal model of decreased distribution in brain regions based on fMRI experiments[J]. Advances in Psychological Science, 2022, 30(2): 255-274.

Figures/Tables 13

References 66

	*代表元分析用到的文献
[1]	宋杰, 赵琬, 张秋梅, 李君. (2020). 大学生工作记忆广度训练迁移效应的行为学与影像学研究. 中华行为医学与脑科学杂志, 29(10), 909-914.
[2]	Alagapan, S., Lustenberger, C., Hadar, E., Shin, H. W., & Frӧhlich, F. (2019). Low-frequency direct cortical stimulation of left superior frontal gyrus enhances working memory performance. NeuroImage, 184, 697-706. doi: 10.1016/j.neuroimage.2018.09.064 URL
[3]	Assem, M., Blank, I. A., Mineroff, Z., Ademoğlu, A., & Fedorenko, E. (2020). Activity in the fronto-parietal multiple-demand network is robustly associated with individual differences in working memory and fluid intelligence. Cortex, 131, 1-16. doi: 10.1016/j.cortex.2020.06.013 URL
[4]	Bäckman, L., Waris, O., Johansson, J., Andersson, M., Rinne, J. O., Alakurtti, K., … Nyberg, L. (2017). Increased dopamine release after working-memory updating training: Neurochemical correlates of transfer. Scientific Reports, 7(1), 7160. doi: 10.1038/s41598-017-07577-y pmid: 28769095
[5]	* Beatty, E. L., Jobidon, M.-E., Bouak, F., Nakashima, A., Smith, I., Lam, Q., … Vartanian, O. (2015). Transfer of training from one working memory task to another: Behavioural and neural evidence. Frontiers in Systems Neuroscience, 9, 86. doi: 10.3389/fnsys.2015.00086 pmid: 26082694
[6]	Briggs, R. G., Khan, A. B., Chakraborty, A. R., Abraham, C. J., Anderson, C. D., Karas, P. J., … Sughrue, M. E. (2020). Anatomy and white matter connections of the superior frontal gyrus. Clinical Anatomy, 33(6), 823-832. doi: 10.1002/ca.v33.6 URL
[7]	Brooks, S. J., Mackenzie-Phelan, R., Tully, J., & Schiöth, H. B. (2020). Review of the neural processes of working memory training: Controlling the impulse to throw the baby out with the bathwater. Frontiers in Psychiatry, 11, 512761. doi: 10.3389/fpsyt.2020.512761 URL
[8]	Buschkuehl, M., Jaeggi, S. M., & Jonides, J. (2012). Neuronal effects following working memory training. Developmental Cognitive Neuroscience, 2, 167-179.
[9]	* Clark, C. M., Lawlor-Savage, L., & Goghari, V. M. (2017). Functional brain activation associated with working memory training and transfer. Behavioural Brain Research, 334, 34-49. doi: 10.1016/j.bbr.2017.07.030 URL
[10]	Constantinidis, C., & Klingberg, T. (2016). The neuroscience of working memory capacity and training. Nature Reviews. Neuroscience, 17(7), 438-449. doi: 10.1038/nrn.2016.43 pmid: 27225070
[11]	* Dahlin, E., Neely, A. S., Larsson, A., Backman, L., & Nyberg, L. (2008). Transfer of learning after updating training mediated by the striatum. Science, 320(5882), 1510-1512. doi: 10.1126/science.1155466 pmid: 18556560
[12]	Dörrenbächer, S., Wu, C., Zimmer, H., & Kray, J. (2020). Plasticity in brain activity dynamics after task-shifting training in older adults. Neuropsychologia, 136, 107285. doi: S0028-3932(19)30326-4 pmid: 31809779
[13]	Eickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009). Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: A random-effects approach based on empirical estimates of spatial uncertainty. Human Brain Mapping, 30(9), 2907-2926. doi: 10.1002/hbm.20718 pmid: 19172646
[14]	* Emch, M., Ripp, I., Wu, Q., Yakushev, I., & Koch, K. (2019). Neural and behavioral effects of an adaptive online verbal working memory training in healthy middle-aged adults. Frontiers in Aging Neuroscience, 11, 300. doi: 10.3389/fnagi.2019.00300 URL
[15]	Eschmann, K. C. J., Bader, R., & Mecklinger, A. (2020). Improving episodic memory: Frontal-midline theta neurofeedback training increases source memory performance. NeuroImage, 222, 117219. doi: S1053-8119(20)30705-9 pmid: 32750499
[16]	* Flegal, K. E., Ragland, J. D., & Ranganath, C. (2019). Adaptive task difficulty influences neural plasticity and transfer of training. NeuroImage, 188, 111-121. doi: 10.1016/j.neuroimage.2018.12.003 URL
[17]	* Garavan, H., Kelley, D., Rosen, A., Rao, S. M., & Stein, E. A. (2000). Practice-related functional activation changes in a working memory task. Microscopy Research and Technique, 51(1), 54-63. pmid: 11002353
[18]	Genç, E., Fraenz, C., Schlüter, C., Friedrich, P., Hossiep, R., Voelkle, M. C., … Jung, R. E. (2018). Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence. Nature Communications, 9(1):1905. doi: 10.1038/s41467-018-04268-8 URL
[19]	Gogulski, J., Zetter, R., Nyrhinen, M., Pertovaara, A., & Carlson, S. (2017). Neural substrate for metacognitive accuracy of tactile working memory. Cerebral Cortex, 27, 5343-5352. doi: 10.1093/cercor/bhx219 URL
[20]	Gur, R. C., Butler, E. R., Moore, T. M., Rosen, A. F. G., Ruparel, K., Satterthwaite, T. D., … Gur, R. E. (2020). Structural and functional brain parameters related to cognitive performance across development: Replication and extension of the Parieto-Frontal Integration Theory in a single sample. Cerebral Cortex, 31(3), 1444-1463. doi: 10.1093/cercor/bhaa282 URL
[21]	Han, Q., Zhang, Y., Liu, D. H., Wang, Y., Feng, Y. J., Yin, X. T., & Wang, J. (2018). Disrupted local neural activity and functional connectivity in subjective tinnitus patients: Evidence from resting-state fMRI study. Neuroradiology, 60(11), 1193-1201. doi: 10.1007/s00234-018-2087-0 pmid: 30159629
[22]	Harms, M. P., Wang, L., Csernansky, J. G., & Barch, D. M. (2013). Structure-function relationship of working memory activity with hippocampal and prefrontal cortex volumes. Brain Structure & Function, 218(1), 173-186.
[23]	Heinzel, S., Lorenz, R. C., Brockhaus, W.-R., Wüstenberg, T., Kathmann, N., Heinz, A., & Rapp, M. A. (2014). Working memory load-dependent brain response predicts behavioral training gains in older adults. Journal of Neuroscience, 34(4), 1224-1233. doi: 10.1523/JNEUROSCI.2463-13.2014 URL
[24]	* Heinzel, S., Lorenz, R. C., Pelz, P., Heinz, A., Walter, H., Kathmann, N., … Stelzel, C. (2016). Neural correlates of training and transfer effects in working memory in older adults. NeuroImage, 134, 236-249. doi: 10.1016/j.neuroimage.2016.03.068 URL
[25]	Hempel, A., Giesel, F. L., Garcia Caraballo, N. M., Amann, M., Meyer, H., Wüstenberg, T., … Schröder, J. (2004). Plasticity of cortical activation related to working memory during training. The American Journal of Psychiatry, 161(4), 745-747. doi: 10.1176/appi.ajp.161.4.745 URL
[26]	Iordan, A. D., Cooke, K. A., Moored, K. D., Katz, B., Buschkuehl, M., Jaeggi, S. M., … Reuter-Lorenz, P. A. (2020). Neural correlates of working memory training: Evidence for plasticity in older adults. NeuroImage, 217, 116887. doi: 10.1016/j.neuroimage.2020.116887 URL
[27]	* Jansma, J. M., Ramsey, N. F., Slagter, H. A., & Kahn, R. S. (2001). Functional anatomical correlates of controlled and automatic processing. Journal of Cognitive Neuroscience, 13(6), 730-743. pmid: 11564318
[28]	Japee, S., Holiday, K., Satyshur, M. D., Mukai, I., & Ungerleider, L. G. (2015). A role of right middle frontal gyrus in reorienting of attention: A case study. Frontiers in Systems Neuroscience, 9, 23.
[29]	* Jolles, D. D., Grol, M. J., van Buchem, M. A., Rombouts, S. A. R. B., & Crone, E. A. (2010). Practice effects in the brain: Changes in cerebral activation after working memory practice depend on task demands. NeuroImage, 52(2), 658-668. doi: 10.1016/j.neuroimage.2010.04.028 URL
[30]	Jolles, D. D., van Buchem, M. A., Crone, E. A., & Rombouts, S. A. R. B. (2013). Functional brain connectivity at rest changes after working memory training. Human Brain Mapping, 34(2), 396-406. doi: 10.1002/hbm.21444 URL
[31]	Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence. The Behavioral and Brain Sciences, 30(2), 135-187. doi: 10.1017/S0140525X07001185 URL
[32]	Kanske, P., & Kotz, S. A. (2011). Emotion triggers executive attention: Anterior cingulate cortex and amygdala responses to emotional words in a conflict task. Human Brain Mapping, 32(2), 198-208. doi: 10.1002/hbm.21012 URL
[33]	* Kelly, A. M. C., Hester, R., Foxe, J. J., Shpaner, M., & Garavan, H. (2006). Flexible cognitive control: Effects of individual differences and brief practice on a complex cognitive task. NeuroImage, 31(2), 866-886. pmid: 16520064
[34]	* Kühn, S., Schmiedek, F., Noack, H., Wenger, E., Bodammer, N. C., Lindenberger, U., & Lövden, M. (2013). The dynamics of change in striatal activity following updating training. Human Brain Mapping, 34(7), 1530-1541. doi: 10.1002/hbm.v34.7 URL
[35]	Lancaster, J. L., Tordesillas-Gutiérrez, D., Martinez, M., Salinas, F., Evans, A., Zilles, K., … Fox, P. T. (2007). Bias between MNI and Talairach coordinates analyzed using the ICBM-152 brain template. Human Brain Mapping, 28(11), 1194-1205. pmid: 17266101
[36]	Landau, S. M., Garavan, H., Schumacher, E. H., & D'Esposito, M. (2007). Regional specificity and practice: Dynamic changes in object and spatial working memory. Brain Research, 1180, 78-89. pmid: 17916334
[37]	* Landau, S. M., Schumacher, E. H., Garavan, H., Druzgal, T. J., & D'Esposito, M. (2004). A functional MRI study of the influence of practice on component processes of working memory. NeuroImage, 22(1), 211-221. pmid: 15110011
[38]	Li, W., Qin, W., Liu, H. G., Fan, L. Z., Wang, J. J., Jiang, T. Z., & Yu, C. S. (2013). Subregions of the human superior frontal gyrus and their connections. NeuroImage, 78, 46-58. doi: 10.1016/j.neuroimage.2013.04.011 URL
[39]	* Li, Y. X., Hu, Y. Z., Zhao, M., Wang, Y. Q., Huang, J., & Chen, F. Y. (2013). The neural pathway underlying a numerical working memory task in abacus-trained children and associated functional connectivity in the resting brain. Brain Research, 1539, 24-33. doi: 10.1016/j.brainres.2013.09.030 URL
[40]	Lobier, M., Palva, J. M., & Palva, S. (2018). High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention. NeuroImage, 165, 222-237. doi: 10.1016/j.neuroimage.2017.10.044 URL
[41]	* Milham, M. P., Banich, M. T., Claus, E. D., & Cohen, N. J. (2003). Practice-related effects demonstrate complementary roles of anterior cingulate and prefrontal cortices in attentional control. NeuroImage, 18(2), 483-493. pmid: 12595201
[42]	* Miró-Padilla, A., Bueichekú, E., & Ávila, C. (2020). Locating neural transfer effects of n-back training on the central executive: A longitudinal fMRI study. Scientific Reports, 10(1), 5226. doi: 10.1038/s41598-020-62067-y pmid: 32251354
[43]	* Miró-Padilla, A., Bueichekú, E., Ventura-Campos, N., Flores-Compañ, M.-J., Parcet, M. A., & Ávila, C. (2019). Long-term brain effects of N-back training: An fMRI study. Brain Imaging and Behavior, 13(4), 1115-1127. doi: 10.1007/s11682-018-9925-x pmid: 30006860
[44]	Neale, C., Johnston, P., Hughes, M., & Scholey, A. (2015). Functional activation during the rapid visual information processing task in a middle aged cohort: An fMRI study. PloS One, 10(10), e0138994. doi: 10.1371/journal.pone.0138994 URL
[45]	* Nęcka, E., Gruszka, A., Hampshire, A., Sarzyńska-Wawer, J., Anicai, A.-E., … Soreq, E. (2021). The effects of working memory training on brain activity. Brain Sciences, 11(2), 155. doi: 10.3390/brainsci11020155 URL
[46]	* Olesen, P. J., Westerberg, H., & Klingberg, T. (2004). Increased prefrontal and parietal activity after training of working memory. Nature Neuroscience, 7(1), 75-79. doi: 10.1038/nn1165 URL
[47]	Owens, M. M., Duda, B., Sweet, L. H., & MacKillop, J. (2018). Distinct functional and structural neural underpinnings of working memory. NeuroImage, 174, 463-471. doi: S1053-8119(18)30228-3 pmid: 29551458
[48]	Pozzi, E., Vijayakumar, N., Rakesh, D., & Whittle, S. (2020). Neural correlates of emotion regulation in adolescents and emerging adults: A meta-analytic study. Biological Psychiatry, 89(2), 194-204. doi: 10.1016/j.biopsych.2020.08.006 URL
[49]	Salmi, J., Nyberg, L., & Laine, M. (2018). Working memory training mostly engages general-purpose large-scale networks for learning. Neuroscience & Biobehavioral Reviews, 93, 108-122. doi: 10.1016/j.neubiorev.2018.03.019 URL
[50]	Salmi, J., Vilà-Balló, A., Soveri, A., Rostan, C., Rodríguez-Fornells, A., Lehtonen, M., & Laine, M. (2019). Working memory updating training modulates a cascade of event-related potentials depending on task load. Neurobiology of Learning and Memory, 166, 107085. doi: S1074-7427(19)30152-2 pmid: 31513849
[51]	* Salminen, T., Kühn, S., Frensch, P. A., & Schubert, T. (2016). Transfer after dual n-back training depends on striatal activation change. Journal of Neuroscience, 36(39), 10198-10213. doi: 10.1523/JNEUROSCI.2305-15.2016 pmid: 27683914
[52]	Sánchez-Pérez, N., Inuggi, A., Castillo, A., Campoy, G., García-Santos, J. M., González-Salinas, C., & Fuentes, L. J. (2019). Computer-based cognitive training improves brain functional connectivity in the attentional networks: A study with primary school-aged children. Frontiers in Behavioral Neuroscience, 13, 1-12. doi: 10.3389/fnbeh.2019.00001 URL
[53]	* Sayala, S., Sala, J. B., & Courtney, S. M. (2006). Increased neural efficiency with repeated performance of a working memory task is information-type dependent. Cerebral Cortex, 16(5), 609-617. pmid: 16079245
[54]	* Schneiders, J. A., Opitz, B., Krick, C. M., & Mecklinger, A. (2011). Separating intra-modal and across-modal training effects in visual working memory: An fMRI investigation. Cerebral Cortex, 21(11), 2555-2564. doi: 10.1093/cercor/bhr037 URL
[55]	* Schneiders, J. A., Opitz, B., Tang, H., Deng, Y., Xie, C. X., Li, H., & Mecklinger, A. (2012). The impact of auditory working memory training on the fronto-parietal working memory network. Frontiers in Human Neuroscience, 6, 173. doi: 10.3389/fnhum.2012.00173 pmid: 22701418
[56]	* Schweizer, S., Grahn, J., Hampshire, A., Mobbs, D., & Dalgleish, T. (2013). Training the emotional brain: Improving affective control through emotional working memory training. Journal of Neuroscience, 33(12), 5301-5311. doi: 10.1523/JNEUROSCI.2593-12.2013 pmid: 23516294
[57]	Song, P., Lin, H., Liu, C., Jiang, Y., Lin, Y., Xue, Q., … Wang, Y. (2019). Transcranial magnetic stimulation to the middle frontal gyrus during attention modes induced dynamic module reconfiguration in brain networks. Frontiers in Neuroinformatics, 13, 1-9. doi: 10.3389/fninf.2019.00001 URL
[58]	Takeuchi, H., Taki, Y., Nouchi, R., Hashizume, H., Sekiguchi, A., Kotozaki, Y., … Kawashima, R. (2013). Effects of working memory training on functional connectivity and cerebral blood flow during rest. Cortex, 49(8), 2106-2125. doi: 10.1016/j.cortex.2012.09.007 pmid: 23079491
[59]	* Takeuchi, H., Taki, Y., Nouchi, R., Hashizume, H., Sekiguchi, A., Kotozaki, Y., … Kawashima, R. (2014). Working memory training improves emotional states of healthy individuals. Frontiers in Systems Neuroscience, 8, 200. doi: 10.3389/fnsys.2014.00200 pmid: 25360090
[60]	Thompson, T. W., Waskom, M. L., & Gabrieli, J. D. E. (2016). Intensive working memory training produces functional changes in large-scale frontoparietal networks. Journal of Cognitive Neuroscience, 28(4), 575-588. doi: 10.1162/jocn_a_00916 pmid: 26741799
[61]	Turkeltaub, P. E., Eickhoff, S. B., Laird, A. R., Fox, M., Wiener, M., & Fox, P. (2012). Minimizing within-experiment and within-group effects in Activation Likelihood Estimation meta-analyses. Human Brain Mapping, 33(1), 1-13. doi: 10.1002/hbm.21186 pmid: 21305667
[62]	* Wang, C., Xu, T. Y., Geng, F. J., Hu, Y. Z., Wang, Y. Q., Liu, H. F., & Chen, F. Y. (2019). Training on abacus-based mental calculation enhances visuospatial working memory in children. The Journal of Neuroscience, 39(33), 6439-6448. doi: 10.1523/JNEUROSCI.3195-18.2019 URL
[63]	* Westerberg, H., & Klingberg, T. (2007). Changes in cortical activity after training of working memory--A single-subject analysis. Physiology & Behavior, 92(1-2), 186-192. doi: 10.1016/j.physbeh.2007.05.058 URL
[64]	Zanto, T. P., & Gazzaley, A. (2013). Fronto-parietal network: Flexible hub of cognitive control. Trends in Cognitive Sciences, 17(12), 602-603. doi: 10.1016/j.tics.2013.10.001 URL
[65]	Zhou, H., Geng, F. J., Wang, Y. Q., Wang, C. J., Hu, Y. Z., & Chen, F. Y. (2019). Transfer effects of abacus training on transient and sustained brain activation in the frontal- parietal network. Neuroscience, 408, 135-146. doi: S0306-4522(19)30239-8 pmid: 30981864
[66]	Zhu, J., Li, J. X., Li, X. W., Rao, J., Hao, Y. R., Ding, Z. J., & Wang, G. P. (2018). Neural basis of the emotional conflict processing in major depression: ERPs and source localization analysis on the N450 and P300 components. Frontiers in Human Neuroscience, 12, 214. doi: 10.3389/fnhum.2018.00214 URL

	1.额上回(额内回)	2. 额中回	3. 额下回	4. 顶内沟	5. 顶上小叶	6. 顶下小叶	7. 扣带回	8. 纹状体
减弱频次	10	12	7	5	5	13	13	4
增强频次	0	5	4	4	6	4	0	6
df	1	1	1	1	1	1	1	1
χ²	*	2.88	0.82	0.11	0.09	4.77	*	0.40
p	*	0.143	0.549	1.000	1.000	0.049	*	0.754

	1.额上回(额内回)	2. 额中回	3. 额下回	4. 顶内沟	5. 顶上小叶	6. 顶下小叶	7. 扣带回	8. 纹状体
减弱频次	10	12	7	5	5	13	13	4
增强频次	0	5	4	4	6	4	0	6
df	1	1	1	1	1	1	1	1
χ²	*	2.88	0.82	0.11	0.09	4.77	*	0.40
p	*	0.143	0.549	1.000	1.000	0.049	*	0.754

脑区	半球	MNI坐标			体积(mm³)	ALE值	p	BA
脑区	半球	x	y	z	体积(mm³)	ALE值	p	BA
额中回	右	36	20	40	352	0.021	p < 0.001	6, 8
额上回/额内回/腹侧前扣带回	左	-2	12	52	1024	0.028	p < 0.001	6, 32, 24

脑区	半球	MNI坐标			体积(mm³)	ALE值	p	BA
脑区	半球	x	y	z	体积(mm³)	ALE值	p	BA
额中回	右	36	20	40	352	0.021	p < 0.001	6, 8
额上回/额内回/腹侧前扣带回	左	-2	12	52	1024	0.028	p < 0.001	6, 32, 24

序号	影响因素	减弱频次(秩次平均与总和)	增强频次(秩次平均与总和)	df	χ²/Z	p
1	人数(秩和检验)	21(16.48, 346)	12(17.92, 215)		-0.41	0.680
2	神经技术	21	12	1	2.94	0.125
	BOLD	20	1
	FC	9	3
3	年龄(3个阶段)	21	12	2	5.81	0.064
	儿童	0	3
	青年	17	7
	中老年	4	2
4	训练任务类型(6类)	21	12	5	10.56	0.023
	更新	14	3
	短时记忆	4	5
	抑制	0	3
	转换	1	0
	计算	1	0
	综合	1	1
5	训练时间(3段)	21	12	2	7.57	0.019
	4周以下	15	4
	4~6周	6	5
	6周以上	0	3