Individual differences in spatial navigation: A multi-scale perspective

doi:10.3724/SP.J.1042.2023.01642

Abstract

Abstract:

Spatial navigation is an essential aspect of daily life that exhibits significant individual differences. The decline in spatial navigation is considered a critical early behavioral manifestation of various brain disorders, particularly Alzheimer's disease (AD). However, the biological and environmental origins of such differences remain poorly defined. In this study, we conducted a multi-scale review of the latest research on spatial navigation to explore the formation mechanisms of individual differences.
We summarized the multi-level individual differences in spatial navigation from a measurement perspective, including personal long-term experience or learning in real environments, virtual reality technology, and online games and big data. We then reviewed and discussed the formation mechanisms from both genetic and environmental factors. In terms of genetic factors, we found that the heritability of spatial ability was approximately 60%. Several candidate genes, including Bcl-2, S100B, and APOE and a few other genes, were proposed to affect spatial navigation behaviors. The mechanism of action studies gradually shifted from the biological perspective to the brain mechanism perspective. The hippocampus, retrosplenial cortex (RSC), and parahippocampal place area (PPA) were identified as important brain regions where genetic factors act on spatial navigation. However, the complete neurogenetic pathway model has not been established yet.
Regarding environmental exposure, cultural background, living environment, early life experience, navigation software use, and lifestyle were found to shape individuals' spatial navigation ability. However, the environmental associations were relatively superficial. Related studies mostly focused on the structure and function of the hippocampus, and further investigation of its mechanism of action, particularly the brain mechanism, is still lacking.
To overcome these limitations, we propose a gene/environment-brain-behavior model to map the links between genetic and environmental factors and individual differences in spatial navigation. Future research could be developed in three directions. Firstly, genome-wide association studies (GWAS) can be used to comprehensively reveal the key genetic variations influencing spatial navigation ability. Bioinformatics methods, such as polygenic score or polygenic risk score, genetic correlation, and enrichment analysis, can explore the key pathways of related genetic factors. Secondly, gene-environment interaction studies can reveal the complex pathways among genetics, environment, cognition, and behavior, and big data can help make it possible. Finally, brain imaging genetics research can correlate genetics, brain imaging, cognition, and behavior. Through international multicenter collaborations and cohort databases, spatial navigation-related imaging metrics can be correlated with multimodal genetic information to comprehensively reveal key genes and genetic mechanisms affecting brain networks of spatial navigation.
In conclusion, integrative analysis of multi-omics and clinical data would be promising for future studies concerning the complex pathways of spatial navigation. Results will help us understand the development patterns of spatial navigation and further explore the potential clinical applications relevant to brain diseases.

Key words: spatial navigation, individual differences, genetic basis, cognitive map, environmental factors

CLC Number:

B842

ZHANG Fengxiang, CHEN Meixuan, PU Yi, KONG Xiang-Zhen. Individual differences in spatial navigation: A multi-scale perspective[J]. Advances in Psychological Science, 2023, 31(9): 1642-1664.

Figures/Tables 4

References 198

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范式名称	测试类型	基本介绍	主要参考文献	应用举例
圣芭芭拉方向感量表	空间导航能力	自我报告式问卷, 共15道题目, 综合衡量出个体在环境尺度下更新和维持方向的能力、学习空间布局的能力以及寻路能力等	Hegarty et al., (2002)	男性的得分显著高于女性(Kong, Huang, et al., 2017)
导航策略量表	空间导航策略	自我报告式问卷, 共14道题目, 创建场景要求参与者考虑他们使用各项策略的程度, 进而将导航策略分为定位策略(orientation strategy)和路线策略(route strategy)。	Lawton (1994)	女性更常使用路线策略(Lawton & Kallai, 2002; Ulrich et al., 2019)
空间焦虑量表	空间焦虑特质	自我报告式问卷, 包含8个可能让参与者产生焦虑的寻路情景	Lawton (1994); Lawton & Kallai (2002)	女性的空间焦虑程度更高, 且空间焦虑程度与空间导航能力呈反比(Lawton, 1994)
成人空间焦虑量表	空间焦虑特质	自我报告式问卷, 包含想象(Imagery)、操作(Manipulation)和导航(Navigation)三个分量表, 要求参与者根据所给的24种空间加工相关情景对焦虑程度进行打分	Lyons et al., (2018)	女性三种空间加工的焦虑程度均高于男性(Sokolowski et al., 2019)
真实环境导航范式	空间导航能力	在真实环境下(如室内、街道、公园等)学习路线后完成环境知识相关测验(如：路线重复任务、距离估计任务、指向任务、地图绘制任务等)	Barrash (1994)	相比较年轻人, 老年人的各项表现要更差(Muffato et al., 2016)
虚拟水迷宫测试	空间导航能力 (空间学习能力、空间记忆能力)	要求参与者尽快找到圆形运动场下隐藏的固定平台。在学习试次, 记录自行探索下的轨迹距离、花费时间等; 在探测试次, 平台被移除, 记录正确率、反应时、在目标所在象限中所走的距离/时间占比、路线与平台交叉点的数量等	Moffat & Resnick (2002)	相比较成年人, 老年人的任务表现更差, 且小脑和楔状叶的激活更低(Reynolds et al., 2019); 在此基础上发展出了记忆岛范式、圆形竞技场范式等
记忆岛范式	空间导航能力	依次训练参与者导航到可见目标和同一位置隐藏目标, 探测试次移走目标。通过反应时、正确率、目标所在象限花费时间百分比等效率指标衡量空间导航能力	Rizk-Jackson et al., (2006)	在儿童、成年人和老年人中均发现存在男性优势(Yasen et al., 2015)
寻路任务	空间导航能力	训练阶段要求参与者按照任何顺序找到所给目标; 测试阶段要求其再次找到这些目标。以实际行走距离与最短路径长度之差和最短路径长度的比值作为导航效率的指标	He et al., (2019)	SBSOD得分更高的个体在没有环境障碍物的情况下表现出更高导航效率(He et al., 2019)
Y型迷宫、八臂迷宫、星型迷宫范式	导航策略	在学习试次, 参与者成功学习从起点到终点的路线; 在探测试次, 不知情条件下改变参与者起点位置或改变环境中的地标线索, 通过其选择区分导航策略	Iaria et al., (2003); Iglói et al., (2010); Rodgers et al., (2012);	不同策略所涉及的神经回路不同, 基于位置的策略由左侧小脑小叶VIIA Crus I、内侧顶叶皮层及右侧海马之间的一致性活动支持, 而基于反应的策略由右侧小叶VIIA Crus I、内侧前额叶皮层和左侧海马之间的一致性活动支持(Iglói et al., 2015)
双解决方案范式	导航策略	在虚拟迷宫中以指定路线学习地标位置后, 要求参与者从随机起点导航到学习过的某一目标位置。可区分导航策略为学习过的路线或走捷径	Marchette et al., (2011)	男性更多采用走捷径的策略(Boone et al., 2018)
指向任务	路径整合能力	从起点出发, 到达某一位置后指出起点的方向, 以指向角度偏差作为衡量指标	Lawton & Morrin (1999)	借助fMRI, 发现海马−尾状核功能连接能显著正向预测路径整合任务表现(Kong, Pu, et al., 2017)
三角形完成任务	路径整合能力	蒙住双眼的参与者在主试引导下完成三角形的前两条边, 然后独自走回心理上的出发点	Worchel (1951)	相比年轻人, 老年人前庭神经功能的丧失导致在该任务上表现更差(Xie et al., 2017)
延迟匹配样本范式	路径整合能力	先后观看两段视频, 参与者需要判断两段视频中的移动距离是否相同或角度是否相同	Chrastil et al., (2016)	海马、压后皮质和内侧前额叶皮层的灰质体积与路径整合能力的个体差异相关(Chrastil et al., 2017)
Virtual Silcton范式	认知地图能力	要求参与者学习主路线后再经过连接路线, 从而区分出路线内建筑和路线间建筑。之后完成系列任务, 如指向任务、模型建立任务、路线成员任务等, 比较路线间指向误差和路线内指向误差	Weisberg & Newcombe (2015)	能否形成认知地图上存在较大的个体差异(Weisberg & Newcombe, 2018)
相对方向判断任务	空间定向/视角转换能力	参与者观察城市地图后, 依次呈现两个十字路口, 要求其回答站在第一个路口指向第二个路口的方向。	Kraemer et al., (2017)	不同认知风格影响空间定向能力, 相较于语言策略的认知风格, 视觉策略更有利于相对方向判断(Kraemer et al., 2017)
空间重定向范式	空间定向能力	参与者迷失方向后, 根据边界线索找出先前隐藏物体。选择环境不同角落的频率百分比可用来衡量个体的空间定向能力及其使用策略	Hermer & Spelke (1994)	3~6岁儿童的海马功能差异与空间重定向的使用策略有关(Vieites et al., 2020)
物体位置记忆范式	空间记忆能力	在存在可见边界、远端方向线索及路标线索的圆形竞技场, 学习阶段要求参与者收集目标物体并记下位置, 测试阶段要求其根据线索重新找到物体所在的位置	Doeller et al., (2008);	携带APOE4风险基因的健康个体内嗅皮层中网格细胞受损, 空间记忆更差(Kunz et al., 2015)
自由探索范式	自由探索模式	在自由探索中不断找到目标物体, 量化个体自由探索中的轨迹, 最终形成不同轨迹指标	Gagnon et al., (2018);	不同探索模式影响个体的认知地图能力(Brunec et al., 2023)

范式名称	测试类型	基本介绍	主要参考文献	应用举例
圣芭芭拉方向感量表	空间导航能力	自我报告式问卷, 共15道题目, 综合衡量出个体在环境尺度下更新和维持方向的能力、学习空间布局的能力以及寻路能力等	Hegarty et al., (2002)	男性的得分显著高于女性(Kong, Huang, et al., 2017)
导航策略量表	空间导航策略	自我报告式问卷, 共14道题目, 创建场景要求参与者考虑他们使用各项策略的程度, 进而将导航策略分为定位策略(orientation strategy)和路线策略(route strategy)。	Lawton (1994)	女性更常使用路线策略(Lawton & Kallai, 2002; Ulrich et al., 2019)
空间焦虑量表	空间焦虑特质	自我报告式问卷, 包含8个可能让参与者产生焦虑的寻路情景	Lawton (1994); Lawton & Kallai (2002)	女性的空间焦虑程度更高, 且空间焦虑程度与空间导航能力呈反比(Lawton, 1994)
成人空间焦虑量表	空间焦虑特质	自我报告式问卷, 包含想象(Imagery)、操作(Manipulation)和导航(Navigation)三个分量表, 要求参与者根据所给的24种空间加工相关情景对焦虑程度进行打分	Lyons et al., (2018)	女性三种空间加工的焦虑程度均高于男性(Sokolowski et al., 2019)
真实环境导航范式	空间导航能力	在真实环境下(如室内、街道、公园等)学习路线后完成环境知识相关测验(如：路线重复任务、距离估计任务、指向任务、地图绘制任务等)	Barrash (1994)	相比较年轻人, 老年人的各项表现要更差(Muffato et al., 2016)
虚拟水迷宫测试	空间导航能力 (空间学习能力、空间记忆能力)	要求参与者尽快找到圆形运动场下隐藏的固定平台。在学习试次, 记录自行探索下的轨迹距离、花费时间等; 在探测试次, 平台被移除, 记录正确率、反应时、在目标所在象限中所走的距离/时间占比、路线与平台交叉点的数量等	Moffat & Resnick (2002)	相比较成年人, 老年人的任务表现更差, 且小脑和楔状叶的激活更低(Reynolds et al., 2019); 在此基础上发展出了记忆岛范式、圆形竞技场范式等
记忆岛范式	空间导航能力	依次训练参与者导航到可见目标和同一位置隐藏目标, 探测试次移走目标。通过反应时、正确率、目标所在象限花费时间百分比等效率指标衡量空间导航能力	Rizk-Jackson et al., (2006)	在儿童、成年人和老年人中均发现存在男性优势(Yasen et al., 2015)
寻路任务	空间导航能力	训练阶段要求参与者按照任何顺序找到所给目标; 测试阶段要求其再次找到这些目标。以实际行走距离与最短路径长度之差和最短路径长度的比值作为导航效率的指标	He et al., (2019)	SBSOD得分更高的个体在没有环境障碍物的情况下表现出更高导航效率(He et al., 2019)
Y型迷宫、八臂迷宫、星型迷宫范式	导航策略	在学习试次, 参与者成功学习从起点到终点的路线; 在探测试次, 不知情条件下改变参与者起点位置或改变环境中的地标线索, 通过其选择区分导航策略	Iaria et al., (2003); Iglói et al., (2010); Rodgers et al., (2012);	不同策略所涉及的神经回路不同, 基于位置的策略由左侧小脑小叶VIIA Crus I、内侧顶叶皮层及右侧海马之间的一致性活动支持, 而基于反应的策略由右侧小叶VIIA Crus I、内侧前额叶皮层和左侧海马之间的一致性活动支持(Iglói et al., 2015)
双解决方案范式	导航策略	在虚拟迷宫中以指定路线学习地标位置后, 要求参与者从随机起点导航到学习过的某一目标位置。可区分导航策略为学习过的路线或走捷径	Marchette et al., (2011)	男性更多采用走捷径的策略(Boone et al., 2018)
指向任务	路径整合能力	从起点出发, 到达某一位置后指出起点的方向, 以指向角度偏差作为衡量指标	Lawton & Morrin (1999)	借助fMRI, 发现海马−尾状核功能连接能显著正向预测路径整合任务表现(Kong, Pu, et al., 2017)
三角形完成任务	路径整合能力	蒙住双眼的参与者在主试引导下完成三角形的前两条边, 然后独自走回心理上的出发点	Worchel (1951)	相比年轻人, 老年人前庭神经功能的丧失导致在该任务上表现更差(Xie et al., 2017)
延迟匹配样本范式	路径整合能力	先后观看两段视频, 参与者需要判断两段视频中的移动距离是否相同或角度是否相同	Chrastil et al., (2016)	海马、压后皮质和内侧前额叶皮层的灰质体积与路径整合能力的个体差异相关(Chrastil et al., 2017)
Virtual Silcton范式	认知地图能力	要求参与者学习主路线后再经过连接路线, 从而区分出路线内建筑和路线间建筑。之后完成系列任务, 如指向任务、模型建立任务、路线成员任务等, 比较路线间指向误差和路线内指向误差	Weisberg & Newcombe (2015)	能否形成认知地图上存在较大的个体差异(Weisberg & Newcombe, 2018)
相对方向判断任务	空间定向/视角转换能力	参与者观察城市地图后, 依次呈现两个十字路口, 要求其回答站在第一个路口指向第二个路口的方向。	Kraemer et al., (2017)	不同认知风格影响空间定向能力, 相较于语言策略的认知风格, 视觉策略更有利于相对方向判断(Kraemer et al., 2017)
空间重定向范式	空间定向能力	参与者迷失方向后, 根据边界线索找出先前隐藏物体。选择环境不同角落的频率百分比可用来衡量个体的空间定向能力及其使用策略	Hermer & Spelke (1994)	3~6岁儿童的海马功能差异与空间重定向的使用策略有关(Vieites et al., 2020)
物体位置记忆范式	空间记忆能力	在存在可见边界、远端方向线索及路标线索的圆形竞技场, 学习阶段要求参与者收集目标物体并记下位置, 测试阶段要求其根据线索重新找到物体所在的位置	Doeller et al., (2008);	携带APOE4风险基因的健康个体内嗅皮层中网格细胞受损, 空间记忆更差(Kunz et al., 2015)
自由探索范式	自由探索模式	在自由探索中不断找到目标物体, 量化个体自由探索中的轨迹, 最终形成不同轨迹指标	Gagnon et al., (2018);	不同探索模式影响个体的认知地图能力(Brunec et al., 2023)

基因	基因全称	研究对象	参考文献	主要关联
BCL-2	protooncogene B-cell lymphoma-2	动物模型	Rondi-Reig et al., (2001)	正常小鼠过表达BCL-2后, 齿状回体积更大、神经元更多; CA1区的LTP削弱
			Hu et al., (2011)	正常小鼠的BCL-2抑制表达与海马细胞凋亡有关
			Wang & Han (2009)	海洛因暴露小鼠的BCL-2基因表达减少, 海马CA1和齿状回出现显著的神经元凋亡
			Wang et al., (2017)	二硫化碳暴露小鼠的BCL-2基因表达减少, 海马CA1和CA3区出现显著的神经元凋亡
			Long et al., (2020); Yuliani et al., (2021)	通过刺激改善记忆受损小鼠的表现后, 海马CA1区和锥体细胞层BCL-2基因的蛋白表达和mRNA表达明显增多, 细胞凋亡减少
			Wang et al., (2009)	增加患血管性痴呆小鼠的BCL-2基因表达, 海马CA1区凋亡细胞数量减少
			Wang et al., (2011)	增加Aβ_1-40诱发的阿尔茨海默病大鼠的BCL-2基因表达, 能明显改善其的空间学习和记忆功能
S100B	S100 calcium- binding protein B	动物模型	Gerlai & Roder (1996)	携带大量S100B基因的小鼠在水迷宫表现测试更差, 具体机制为过量的S100B影响钙依赖的突触过程, 进而导致LTP的减弱及与海马相关的功能受损
			Mori et al., (2010)	过高浓度的S100B 能加重AD小鼠以星形胶质细胞增多和小胶质细胞增多为特征的脑部炎症
			Nishiyama et al., (2002)	敲除S100B的小鼠海马CA1区可以观察到LTP显著增强
			Kleindienst et al., (2005)	脑损伤小鼠注入低浓度S100B后, 海马内神经发生增强, 空间导航能力增强
		人类	Simpson et al., (2010)	AD患者的尸体中, 海马和颞叶区域S100B mRNA和蛋白浓度增高
			Peskind et al., (2001)	AD患者脑脊液中, S100B浓度更高
			Lambert et al., (2007)	S100B基因中rs2300403位点与更低的认知表现有关
			Wang et al., (2021)	rs9722位点通过改变miRNA的结合能力上调S100B表达
			Kong, Song, et al., (2017)	rs3788266通过S100B蛋白水平作用于右前部RSC从而影响场景识别能力
APOE	Apolipoprotein E	动物模型	Riddell et al., (2008)	AOPE4等位基因数量与小鼠大脑、脑脊液和血浆中的APOE蛋白水平负相关, 与患AD风险正相关
		人类	Castellano et al., (2011); Cruchaga et al., (2012)	AOPE4与更低的APOE载脂蛋白浓度有关, 从而影响淀粉样蛋白的清除, 导致Aβ的产生和沉积, 增加AD患病风险
			Laczó et al., (2014)	APOE4纯合子的轻度认知障碍个体右侧海马体积萎缩
			Flowers & Rebeck (2020)	携带APOE4风险基因的健康个体小部分海马区域受到影响
			Kunz et al., (2015)	携带APOE4风险基因的健康个体内嗅皮层中网格细胞受损, 但部分海马活动增强
			(Bierbrauer et al., 2020)	携带有APOE4风险基因的健康个体对空间中的路标或边界线索表现出更强的依赖性, 体现了RSC以及边界细胞对路径整合能力的补偿作用
			Hardcastle et al., (2015)	携带APOE4风险基因的健康个体表现出边界细胞对误差角度的纠正补偿作用

基因	基因全称	研究对象	参考文献	主要关联
BCL-2	protooncogene B-cell lymphoma-2	动物模型	Rondi-Reig et al., (2001)	正常小鼠过表达BCL-2后, 齿状回体积更大、神经元更多; CA1区的LTP削弱
			Hu et al., (2011)	正常小鼠的BCL-2抑制表达与海马细胞凋亡有关
			Wang & Han (2009)	海洛因暴露小鼠的BCL-2基因表达减少, 海马CA1和齿状回出现显著的神经元凋亡
			Wang et al., (2017)	二硫化碳暴露小鼠的BCL-2基因表达减少, 海马CA1和CA3区出现显著的神经元凋亡
			Long et al., (2020); Yuliani et al., (2021)	通过刺激改善记忆受损小鼠的表现后, 海马CA1区和锥体细胞层BCL-2基因的蛋白表达和mRNA表达明显增多, 细胞凋亡减少
			Wang et al., (2009)	增加患血管性痴呆小鼠的BCL-2基因表达, 海马CA1区凋亡细胞数量减少
			Wang et al., (2011)	增加Aβ_1-40诱发的阿尔茨海默病大鼠的BCL-2基因表达, 能明显改善其的空间学习和记忆功能
S100B	S100 calcium- binding protein B	动物模型	Gerlai & Roder (1996)	携带大量S100B基因的小鼠在水迷宫表现测试更差, 具体机制为过量的S100B影响钙依赖的突触过程, 进而导致LTP的减弱及与海马相关的功能受损
			Mori et al., (2010)	过高浓度的S100B 能加重AD小鼠以星形胶质细胞增多和小胶质细胞增多为特征的脑部炎症
			Nishiyama et al., (2002)	敲除S100B的小鼠海马CA1区可以观察到LTP显著增强
			Kleindienst et al., (2005)	脑损伤小鼠注入低浓度S100B后, 海马内神经发生增强, 空间导航能力增强
		人类	Simpson et al., (2010)	AD患者的尸体中, 海马和颞叶区域S100B mRNA和蛋白浓度增高
			Peskind et al., (2001)	AD患者脑脊液中, S100B浓度更高
			Lambert et al., (2007)	S100B基因中rs2300403位点与更低的认知表现有关
			Wang et al., (2021)	rs9722位点通过改变miRNA的结合能力上调S100B表达
			Kong, Song, et al., (2017)	rs3788266通过S100B蛋白水平作用于右前部RSC从而影响场景识别能力
APOE	Apolipoprotein E	动物模型	Riddell et al., (2008)	AOPE4等位基因数量与小鼠大脑、脑脊液和血浆中的APOE蛋白水平负相关, 与患AD风险正相关
		人类	Castellano et al., (2011); Cruchaga et al., (2012)	AOPE4与更低的APOE载脂蛋白浓度有关, 从而影响淀粉样蛋白的清除, 导致Aβ的产生和沉积, 增加AD患病风险
			Laczó et al., (2014)	APOE4纯合子的轻度认知障碍个体右侧海马体积萎缩
			Flowers & Rebeck (2020)	携带APOE4风险基因的健康个体小部分海马区域受到影响
			Kunz et al., (2015)	携带APOE4风险基因的健康个体内嗅皮层中网格细胞受损, 但部分海马活动增强
			(Bierbrauer et al., 2020)	携带有APOE4风险基因的健康个体对空间中的路标或边界线索表现出更强的依赖性, 体现了RSC以及边界细胞对路径整合能力的补偿作用
			Hardcastle et al., (2015)	携带APOE4风险基因的健康个体表现出边界细胞对误差角度的纠正补偿作用

其他影响因素	主要参考文献	重要关联
性别	Coutrot et al., (2018); Boone et al., (2018); Voyer et al., (2007);	在总体能力、导航策略使用、线索利用方面等均存在差异
年龄	Stangl et al., (2020)	老年人表现出全方位的空间导航能力减弱
文化背景	Berry (1971)	狩猎文化下的民族拥有更开阔的环境与探索需求, 表现出更强的导航能力
语言习惯	Goeke et al., (2015); Hao et al., (2017)	地心参照体系的语言表述更有利于空间能力
居住环境	Coutrot et al., (2022)	街道网络复杂度更高的成长环境与更高的空间导航能力有关
童年探索经验	Lawton & Kallai (2002)	早期拥有更多探索经验的个体在成年后导航表现更好
父母教育	Szechter & Liben (2004); Pruden et al., (2011)	父母的空间图形教育与空间语言教育分别促进空间图形表征能力与空间语言形成
地图训练	Uttal (2000); Griesbauer et al., (2022)	有助于认知地图的形成
导航软件依赖	Dahmani & Bohbot (2020); Hejtmánek et al., (2018); Ruginski et al., (2019)	过渡依赖GPS损害个体对空间知识的学习和获取能力、空间记忆能力, 带来习惯性路线学习
健康状态	Dobric et al., (2022); Firth et al., (2018); Jacka et al., (2015); Marshall & Born (2007)	良好的健康状况可能通过影响海马进而影响空间导航能力
疾病	Bremner et al., (2007); Herrero et al., (2006); Sheline et al., (2002); Smith (2015)	病理性焦虑、抑郁、自闭症、创伤后应激障碍等可能通过影响海马进而影响空间导航能力