实地导航训练提高大脑功能连接模式稳定性

doi:10.3724/SP.J.1041.2024.01661

摘要/Abstract

摘要：

空间导航主要依赖于两种空间表征：自我中心参照表征与环境中心参照表征。然而, 个体在现实环境中的空间导航能力提升与这两种空间表征存在何种关联仍未可知。为此, 本研究结合行为测量与功能核磁共振技术(fMRI), 对非熟悉环境实地空间导航训练前后个体空间导航能力和大脑全局性功能连接模式的改变进行分析, 系统考察个体实地空间导航能力提高的内在神经机制。研究结果发现, 训练组被试在训练后进行空间导航任务时, 自我中心参照表征的核心脑区——顶上小叶(SPL)的神经活动显著增强。更为重要地, 训练显著提高了以SPL为核心的全脑功能连接模式的稳定性, 且与个体导航任务表现的提高呈正相关。上述结果表明, 实地空间导航能力的提高与自我中心参照表征的增强存在密切关联, 并进一步表现为SPL与全脑其他区域的信息交互通路的固化。

关键词: 空间导航, 自我中心参照, 顶上小叶, 功能连接模式

Abstract:

Spatial navigation involves both egocentric (body-centered) and allocentric (environment-centered) spatial representations, which are hosted in structurally and functionally segregated brain regions. The two types of representations are flexibly weighted in response to changing environmental cues and landmarks during the navigational process, thereby achieving a stable and robust neural code of the target location. However, it remains unknown whether and how improvements in real-world navigational proficiency are related to these two types of spatial representations.

In the present study, participants who were unfamiliar with the campus layout (newly arrived university freshmen) received a real-world navigation training for 20 days. Before and after the training, participants received fMRI scanning when they performed a distance judgment task and a paper folding task (as a control). In addition, they were comprehensively tested for their navigational ability via several behavioral tasks (live pointing, offsite direction estimation and offsite distance estimation) outside the scanner. A control group comprised participants who underwent the same fMRI scanning and behavioral tests but did not receive any training. By comparing the training-induced changes in regional activation and task-based global functional connectivity (FC) patterns between the two groups, we investigated the neural correlates of the improvement in real-world navigation performance.

We found that the real-world navigation training improved participants' performance during all the behavioral tasks. At the neural level, we observed significant training-induced activation enhancement in the right superior parietal lobule (rSPL), a core brain region that hosts egocentric representation. Moreover, the training increased the global FC pattern stability with the rSPL as the seed region during the distance judgment task, although it had no significant effects on the FC pattern stability during the baseline task. Finally, the increase in global FC pattern stability also predicted individual’s improvement in behavioral performance during the distance judgment task. Notably, these effects were found only in the trained group; no similar effects were observed in the control group. These findings indicated that improvement in real-word navigation ability was associated with enhanced egocentric representation. Moreover, the navigation training consolidated the information exchange routes among brain regions, thereby enhancing the precision of cognitive map retrieval.

In summary, our study highlights the importance of egocentric representation enhancement in rSPL in improving real-world navigation ability in unfamiliar environments. Furthermore, navigation training facilitates spatial information retrieval by reinforcing the information exchange pathways between the rSPL and other brain areas.

Key words: spatial navigation, egocentric referencing, superior parietal lobule (SPL), functional connectivity pattern

中图分类号:

B842

俞梦霞, 宋宜颖, 刘嘉. (2024). 实地导航训练提高大脑功能连接模式稳定性. 心理学报, 56(12), 1661-1675.

YU Mengxia, SONG Yiying, LIU Jia. (2024). Real-world navigation training enhances the stability of large-scale brain connectivity patterns. Acta Psychologica Sinica, 56(12), 1661-1675.

图/表 11

图1 实验中所用位置的地图注：图中数字位置代表实验中所用的50个地点。红色星号位置为fMRI实验距离判断任务中的目的地位置。

图2 fMRI实验流程图

图3 导航训练过程中指路正确率变化趋势注：误差线代表标准误(SEM)

表1 距离判断任务中被试的行为表现(M ± SD)

被试组	测试时间	正确率(%)	反应时(s)	反应效率
训练组	前测	78.58 ± 6.94	4.79 ± 0.70	16.79 ± 3.28
训练组	后测	87.35 ± 4.83	4.40 ± 0.67	20.25 ± 3.13
控制组	前测	78.71 ± 8.51	4.14 ± 0.79	19.55 ± 4.02
控制组	后测	76.95 ± 8.32	4.08 ± 0.89	19.67 ±4.72

图4 前后测fMRI实验任务中被试行为表现注：反应效率 = 正确率(%)/反应时(s)。误差线代表标准误(SEM), ***p < 0.001, **p < 0.01, n.s. p > 0.05。

表2 展开图判断任务中被试的行为表现(M ± SD)

被试组	测试时间	正确率(%)	反应时(s)	反应效率
训练组	前测	78.45 ± 9.22	5.43 ± 0.40	14.52 ± 2.08
训练组	后测	86.33 ± 9.87	5.01 ± 0.64	17.65 ± 4.02
控制组	前测	81.32 ± 12.68	4.73 ± 0.96	18.20 ± 5.90
控制组	后测	82.16 ± 13.96	4.45 ± 1.20	20.58 ± 9.24

表3 训练组后测距离判断任务中激活增强脑区

脑区	半球	MNI坐标(x, y, z)	体素数量	Z值
顶内沟	左	−48, −38, 40	134	3.63
扣带旁回	右	2, 48, 18	199	3.56
扣带回	左	−4, −34, 24	131	3.53
额上回	左	−24, 34, 48	146	3.49
楔前叶	左	−6, −40, 44	122	3.29
额极	左	−8, 44, 46	235	3.24
额极/额上回	右	22, 40, 42	119	3.24
尾状核	左	−12, 18, 0	119	3.19

图5 右侧SPL在距离判断任务中激活的训练效应注：体素水平p < 0.01, 团块水平p < 0.01, 使用AFNI中的3dClustSim进行多重比较校正。图B为各条件下以峰值点为中心, 半径3 mm的小球的平均信号变化百分比, 只作呈现。误差线代表标准误(SEM), *p < 0.05, n.s. p > 0.05。

图6 导航训练引起连接模式稳定性的提高及其过程特异性注：上图呈现了某一被试在前测距离判断任务下以rSPL为种子点得到的功能连接Z值图以及连接模式稳定性计算方法的示例。下图中误差线代表标准误(SEM), **p < 0.01, *p < 0.05, n.s. p > 0.05。

图7 训练引起的连接模式稳定性变化与行为的相关

图8 前后测导航能力行为测试中被试行为表现注：误差线代表标准误(SEM), **p < 0.01, *p < 0.05, ᵻ 0.05 < p < 0.1, n.s. p > 0.1。

参考文献 62

[1]	Aguirre, G. K., & D'Esposito, M. (1999). Topographical disorientation: A synthesis and taxonomy. Brain, 122(9), 1613-1628.
[2]	Bassett, D. S., Wymbs, N. F., Porter, M. A., Mucha, P. J., Carlson, J. M., & Grafton, S. T. (2011). Dynamic reconfiguration of human brain networks during learning. Proceedings of the National Academy of Sciences, 108(18), 7641-7646.
[3]	Bassett, D. S., Yang, M., Wymbs, N. F., & Grafton, S. T. (2015). Learning-induced autonomy of sensorimotor systems. Nature Neuroscience, 18(5), 744-751. doi: 10.1038/nn.3993 pmid: 25849989
[4]	Bi, T., Chen, J., Zhou, T., He, Y., & Fang, F. (2014). Function and structure of human left fusiform cortex are closely associated with perceptual learning of faces. Current Biology, 24(2), 222-227. doi: 10.1016/j.cub.2013.12.028 pmid: 24412207
[5]	Boccia, M., Guariglia, C., Sabatini, U., & Nemmi, F. (2016). Navigating toward a novel environment from a route or survey perspective: Neural correlates and context-dependent connectivity. Brain Structure and Function, 221(4), 2005-2021.
[6]	Boccia, M., Nemmi, F., & Guariglia, C. (2014). Neuropsychology of environmental navigation in humans: Review and meta-analysis of FMRI studies in healthy participants. Neuropsychology Review, 24, 236-251. doi: 10.1007/s11065-014-9247-8 pmid: 24488500
[7]	Byrne, P., Becker, S., & Burgess, N. (2007). Remembering the past and imagining the future: A neural model of spatial memory and imagery. Psychological Review, 114(2), 340-375. doi: 10.1037/0033-295X.114.2.340 pmid: 17500630
[8]	Chen, Q., Weidner, R., Weiss, P. H., Marshall, J. C., & Fink, G. R. (2012). Neural interaction between spatial domain and spatial reference frame in parietal-occipital junction. Journal of Cognitive Neuroscience, 24(11), 2223-2236. pmid: 22721375
[9]	Ciaramelli, E., Rosenbaum, R. S., Solcz, S., Levine, B., & Moscovitch, M. (2010). Mental space travel: Damage to posterior parietal cortex prevents egocentric navigation and reexperiencing of remote spatial memories. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36(3), 619-634.
[10]	Dosher, B. A., & Lu, Z. L. (1998). Perceptual learning reflects external noise filtering and internal noise reduction through channel reweighting. Proceedings of the National Academy of Sciences, 95(23), 13988-13993.
[11]	Dresler, M., Shirer, W. R., Konrad, B. N., Müller, N. C., Wagner, I. C., Fernández, G., ... Greicius, M. D. (2017). Mnemonic training reshapes brain networks to support superior memory. Neuron, 93(5), 1227-1235. e1226. doi: S0896-6273(17)30087-9 pmid: 28279356
[12]	Epstein, R. A., Patai, E. Z., Julian, J. B., & Spiers, H. J. (2017). The cognitive map in humans: Spatial navigation and beyond. Nature Neuroscience, 20(11), 1504-1513. doi: 10.1038/nn.4656 pmid: 29073650
[13]	Evans, G. W., & Pezdek, K. (1980). Cognitive mapping: Knowledge of real-world distance and location information. Journal of Experimental Psychology: Human Learning and Memory, 6(1), 13-24.
[14]	Frankenstein, J., Mohler, B. J., Bülthoff, H. H., & Meilinger, T. (2012). Is the map in our head oriented north?. Psychological Science, 23(2), 120-125. doi: 10.1177/0956797611429467 pmid: 22207644
[15]	Gagnon, S. A., Brunyé, T. T., Gardony, A., Noordzij, M. L., Mahoney, C. R., & Taylor, H. A. (2014). Stepping into a map: Initial heading direction influences spatial memory flexibility. Cognitive Science, 38(2), 275-302. doi: 10.1111/cogs.12055 pmid: 23855500
[16]	Galati, G., Lobel, E., Vallar, G., Berthoz, A., Pizzamiglio, L., & Le Bihan, D. (2000). The neural basis of egocentric and allocentric coding of space in humans: A functional magnetic resonance study. Experimental Brain Research, 133(2), 156-164. doi: 10.1007/s002210000375 pmid: 10968216
[17]	Grady, C. L., Rieck, J. R., Nichol, D., Rodrigue, K. M., & Kennedy, K. M. (2021). Influence of sample size and analytic approach on stability and interpretation of brain-behavior correlations in task-related fMRI data. Human Brain Mapping, 42(1), 204-219.
[18]	Hao, X., Huang, Y., Song, Y., Kong, X., & Liu, J. (2017). Experience with the cardinal coordinate system contributes to the precision of cognitive maps. Frontiers in Psychology, 8, 1166. doi: 10.3389/fpsyg.2017.01166 pmid: 28744248
[19]	Hirshhorn, M., Grady, C., Rosenbaum, R. S., Winocur, G., & Moscovitch, M. (2012). Brain regions involved in the retrieval of spatial and episodic details associated with a familiar environment: An fMRI study. Neuropsychologia, 50(13), 3094-3106. doi: 10.1016/j.neuropsychologia.2012.08.008 pmid: 22910274
[20]	Huang, Y., Zhen, Z., Song, Y., Zhu, Q., Wang, S., & Liu, J. (2013). Motor training increases the stability of activation patterns in the primary motor cortex. PLoS One, 8(1), e53555.
[21]	Iaria, G., Chen, J. K., Guariglia, C., Ptito, A., & Petrides, M. (2007). Retrosplenial and hippocampal brain regions in human navigation: Complementary functional contributions to the formation and use of cognitive maps. European Journal of Neuroscience, 25(3), 890-899. pmid: 17298595
[22]	Janzen, G., Jansen, C., & van Turennout, M. (2008). Memory consolidation of landmarks in good navigators. Hippocampus, 18(1), 40-47. pmid: 17924521
[23]	Janzen, G., & Van Turennout, M. (2004). Selective neural representation of objects relevant for navigation. Nature Neuroscience, 7(6), 673-677. doi: 10.1038/nn1257 pmid: 15146191
[24]	Jonker, T. R., Seli, P., Cheyne, J. A., & Smilek, D. (2013). Performance reactivity in a continuous-performance task: Implications for understanding post-error behavior. Consciousness and Cognition, 22(4), 1468-1476. doi: 10.1016/j.concog.2013.10.005 pmid: 24177237
[25]	Jordan, K., Schadow, J., Wuestenberg, T., Heinze, H. J., & Jäncke, L. (2004). Different cortical activations for subjects using allocentric or egocentric strategies in a virtual navigation task. Neuroreport, 15(1), 135-140. pmid: 15106845
[26]	Keerativittayayut, R., Aoki, R., Sarabi, M. T., Jimura, K., & Nakahara, K. (2018). Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance. Elife, 7, e32696.
[27]	Kitchin, R. M. (1994). Cognitive maps: What are they and why study them? Journal of Environmental Psychology, 14(1), 1-19.
[28]	Klatzky, R. L. (1998). Allocentric and egocentric spatial representations: Definitions, distinctions, and interconnections. In Freska, C., Habel, C., & Wender, K.F. (Eds.), Spatial cognition: An interdisciplinary approach to representing and processing spatial knowledge (pp. 1-17). Springer.
[29]	Kravitz, D. J., Saleem, K. S., Baker, C. I., & Mishkin, M. (2011). A new neural framework for visuospatial processing. Nature Reviews Neuroscience, 12(4), 217-230. doi: 10.1038/nrn3008 pmid: 21415848
[30]	Liu, N., Li, H., Su, W., & Chen, Q. (2017). Common and specific neural correlates underlying the spatial congruency effect induced by the egocentric and allocentric reference frame. Human Brain Mapping, 38(4), 2112-2127. doi: 10.1002/hbm.23508 pmid: 28054740
[31]	Maguire, E. A., Burgess, N., Donnett, J. G., Frackowiak, R. S., Frith, C. D., & O'Keefe, J. (1998). Knowing where and getting there: A human navigation network. Science, 280(5365), 921-924. doi: 10.1126/science.280.5365.921 pmid: 9572740
[32]	Milivojevic, B., Johnson, B., Hamm, J., & Corballis, M. (2003). Non-identical neural mechanisms for two types of mental transformation: Event-related potentials during mental rotation and mental paper folding. Neuropsychologia, 41(10), 1345-1356. pmid: 12757907
[33]	Mohr, H., Wolfensteller, U., Betzel, R. F., Mišić, B., Sporns, O., Richiardi, J., & Ruge, H. (2016). Integration and segregation of large-scale brain networks during short-term task automatization. Nature Communications, 7(1), 13217.
[34]	Montello, D. R. (1998). A new framework for understanding the acquisition of spatial knowledge in large-scale environments. In Egenhofer, M. J., & Golledge, R. G. (eds.), Spatial and temporal reasoning in geographic information systems (pp. 143-154). New York: Oxford University Press.
[35]	Morgan, L. K., MacEvoy, S. P., Aguirre, G. K., & Epstein, R. A. (2011). Distances between real-world locations are represented in the human hippocampus. Journal of Neuroscience, 31(4), 1238-1245. doi: 10.1523/JNEUROSCI.4667-10.2011 pmid: 21273408
[36]	Neggers, S. F., Van der Lubbe, R. H., Ramsey, N. F., & Postma, A. (2006). Interactions between ego- and allocentric neuronal representations of space. Neuroimage, 31(1), 320-331. pmid: 16473025
[37]	Nemmi, F., Piras, F., Péran, P., Incoccia, C., Sabatini, U., & Guariglia, C. (2013). Landmark sequencing and route knowledge: An fMRI study. Cortex, 49(2), 507-519. doi: 10.1016/j.cortex.2011.11.016 pmid: 22225882
[38]	Nori, R., & Piccardi, L. (2011). Familiarity and spatial cognitive style:How important are they for spatial representation. In Thomas, J. B. (Ed.), Spatial memory: Visuospatial processes, cognitive performance and developmental effects (pp. 123-144). New York: Nova Science Publishers.
[39]	Parslow, D. M., Rose, D., Brooks, B., Fleminger, S., Gray, J. A., Giampietro, V., ... Andrew, C. (2004). Allocentric spatial memory activation of the hippocampal formation measured with fMRI. Neuropsychology, 18(3), 450-461. doi: 10.1037/0894-4105.18.3.450 pmid: 15291723
[40]	Reifegerste, J., Jarvis, R., & Felser, C. (2020). Effects of chronological age on native and nonnative sentence processing: Evidence from subject-verb agreement in German. Journal of Memory and Language, 111, 104083.
[41]	Rosenbaum, R. S., Winocur, G., Grady, C. L., Ziegler, M., & Moscovitch, M. (2007). Memory for familiar environments learned in the remote past: fMRI studies of healthy people and an amnesic person with extensive bilateral hippocampal lesions. Hippocampus, 17(12), 1241-1251. pmid: 17853413
[42]	Rosenbaum, R. S., Ziegler, M., Winocur, G., Grady, C. L., & Moscovitch, M. (2004). “I have often walked down this street before”: fMRI studies on the hippocampus and other structures during mental navigation of an old environment. Hippocampus, 14(7), 826-835. doi: 10.1002/hipo.10218 pmid: 15382253
[43]	Ruotolo, F., Ruggiero, G., Raemaekers, M., Iachini, T., Van der Ham, I., Fracasso, A., & Postma, A. (2019). Neural correlates of egocentric and allocentric frames of reference combined with metric and non-metric spatial relations. Neuroscience, 409, 235-252. doi: S0306-4522(19)30261-1 pmid: 31004694
[44]	Saj, A., Cojan, Y., Musel, B., Honoré, J., Borel, L., & Vuilleumier, P. (2014). Functional neuro-anatomy of egocentric versus allocentric space representation. Neurophysiologie Clinique/Clinical Neurophysiology, 44(1), 33-40.
[45]	Schinazi, V. R., & Epstein, R. A. (2010). Neural correlates of real-world route learning. Neuroimage, 53(2), 725-735. doi: 10.1016/j.neuroimage.2010.06.065 pmid: 20603219
[46]	Schinazi, V. R., Nardi, D., Newcombe, N. S., Shipley, T. F., & Epstein, R. A. (2013). Hippocampal size predicts rapid learning of a cognitive map in humans. Hippocampus, 23(6), 515-528. doi: 10.1002/hipo.22111 pmid: 23505031
[47]	Shepard, R. N., & Feng, C. (1972). A chronometric study of mental paper folding. Cognitive Psychology, 3(2), 228-243.
[48]	Siegel, A. W., & White, S. H. (1975). The development of spatial representations of large-scale environments. Advances in Child Development and Behavior, 10, 9-55. pmid: 1101663
[49]	Spiers, H. J., & Maguire, E. A. (2006). Thoughts, behaviour, and brain dynamics during navigation in the real world. Neuroimage, 31(4), 1826-1840. doi: 10.1016/j.neuroimage.2006.01.037 pmid: 16584892
[50]	Spiers, H. J., & Maguire, E. A. (2007). A navigational guidance system in the human brain. Hippocampus, 17(8), 618-626. doi: 10.1002/hipo.20298 pmid: 17492693
[51]	Sulpizio, V., Committeri, G., Lambrey, S., Berthoz, A., & Galati, G. (2013). Selective role of lingual/parahippocampal gyrus and retrosplenial complex in spatial memory across viewpoint changes relative to the environmental reference frame. Behavioural Brain Research, 242, 62-75. doi: 10.1016/j.bbr.2012.12.031 pmid: 23274842
[52]	Suthana, N. A., Ekstrom, A. D., Moshirvaziri, S., Knowlton, B., & Bookheimer, S. Y. (2009). Human hippocampal CA1 involvement during allocentric encoding of spatial information. Journal of Neuroscience, 29(34), 10512-10519. doi: 10.1523/JNEUROSCI.0621-09.2009 pmid: 19710304
[53]	Tambini, A., Rimmele, U., Phelps, E. A., & Davachi, L. (2017). Emotional brain states carry over and enhance future memory formation. Nature Neuroscience, 20(2), 271-278. doi: 10.1038/nn.4468 pmid: 28024158
[54]	Taylor, H. A., & Tversky, B. (1992). Spatial mental models derived from survey and route descriptions. Journal of Memory and Language, 31(2), 261-292.
[55]	Visser, R. M., Scholte, H. S., & Kindt, M. (2011). Associative learning increases trial-by-trial similarity of BOLD-MRI patterns. Journal of Neuroscience, 31(33), 12021-12028. doi: 10.1523/JNEUROSCI.2178-11.2011 pmid: 21849562
[56]	Vogeley, K., & Fink, G. R. (2003). Neural correlates of the first-person-perspective. Trends in Cognitive Sciences, 7(1), 38-42. doi: 10.1016/s1364-6613(02)00003-7 pmid: 12517357
[57]	Weniger, G., Ruhleder, M., Wolf, S., Lange, C., & Irle, E. (2009). Egocentric memory impaired and allocentric memory intact as assessed by virtual reality in subjects with unilateral parietal cortex lesions. Neuropsychologia, 47(1), 59-69. doi: 10.1016/j.neuropsychologia.2008.08.018 pmid: 18789955
[58]	Weniger, G., Siemerkus, J., Schmidt-Samoa, C., Mehlitz, M., Baudewig, J., Dechent, P., & Irle, E. (2010). The human parahippocampal cortex subserves egocentric spatial learning during navigation in a virtual maze. Neurobiology of Learning and Memory, 93(1), 46-55. doi: 10.1016/j.nlm.2009.08.003 pmid: 19683063
[59]	Wolbers, T., & Wiener, J. M. (2014). Challenges for identifying the neural mechanisms that support spatial navigation: The impact of spatial scale. Frontiers in Human Neuroscience, 8, 571. doi: 10.3389/fnhum.2014.00571 pmid: 25140139
[60]	Xue, G., Dong, Q., Chen, C., Lu, Z., Mumford, J. A., & Poldrack, R. A. (2010). Greater neural pattern similarity across repetitions is associated with better memory. Science, 330(6000), 97-101. doi: 10.1126/science.1193125 pmid: 20829453
[61]	Yu, M., Li, X., Song, Y., & Liu, J. (2021). Visual association learning induces global network reorganization. Neuropsychologia, 154, 107789.
[62]	Yu, M., Song, H., Huang, J., Song, Y., & Liu, J. (2020). Motor learning improves the stability of large-scale brain connectivity pattern. Frontiers in Human Neuroscience, 14, 571733.