The cognitive and neural mechanisms of statistical learning and its relationship with language
收稿日期: 2019-09-5 网络出版日期: 2020-09-15
Received: 2019-09-5 Online: 2020-09-15
Statistical learning (SL), which was first addressed in the seminal study on speech segmentation of infants by
Statistical learning (SL), which was first addressed in the seminal study on speech segmentation of infants by
徐贵平, 范若琳, 金花. (2020).
XU Guiping, FAN Ruolin, JIN Hua. (2020).
统计学习(statistical learning, SL)是指个体在外部环境的连续刺激流中逐渐发现刺激统计规律的过程, 个体在统计学习上的差异体现在其对频率、概率等统计结构信息的敏感性, 统计学习对语言等认知活动有重要的影响(Arnon, 2019; Erickson & Thiessen, 2015; Saffran & Kirkham, 2018; Thiessen, Kronstein, & Hufnagle, 2013; 武秋艳, 邓园, 2012)。统计学习最早是在Saffran, Aslin和Newport (1996)关于8个月大婴儿听觉语音切分的经典研究中提出, 研究者给婴儿呈现2分钟的连续语音流, 语音流由4个三音节的无意义单词bidaku, padoti, golabu和tupiro组成, 结果发现婴儿能在连续语音流刺激中感知到不同音节间的转移概率(transitional probability, 以下简称TP)差异从而表现出词汇切分能力。TP作为一种条件概率其计算方法如下: 假设X和Y两个音节联合出现时顺序为XY, 那么Y在X出现的条件下出现的概率(称之为“顺序TP”): P (Y|X)=P (XY)/P (X), 而X在Y出现的条件下出现的概率(称之为“逆序TP”): P (X|Y)=P (XY)/P (Y), 其中, P (XY)指整个刺激序列中刺激XY联合出现的频率, P (X)指刺激X出现的频率, P (Y)指刺激Y出现的频率, 如无特别说明统计学习研究中的TP一般指顺序TP。由此可知, 同一单词内两个音节间的TP肯定高于单词间两个音节的TP, 若个体能感知到不同音节间TP的差异, 那么个体就能进行词汇切分和词汇识别(Aslin, Saffran, & Newport, 1998; Saffran et al., 1996)。个体对TP的敏感性具有一定的神经电生理基础, 研究发现失匹配负波(mismatch negativity, MMN)的波幅能有效地反映听觉刺激序列中TP的差异(Fitzgerald & Todd, 2018; Koelsch, Busch, Jentschke, & Rohrmeier, 2016)。
经典统计学习范式中包括刺激熟悉过程和学习结果测试两个阶段, 以视觉统计学习任务为例, 刺激材料为24个抽象黑色图形(如图1所示), 共形成8个三联体(triplet)。刺激熟悉过程: 给受试者呈现10分钟视觉图形流, 每次呈现1个图形200 ms, 间隔200 ms。8个三联体的顺序伪随机, 同一个三联体不连续出现, 三联体内三个图形呈现的先后顺序固定, 每个三联体重复75次。要求受试者注意屏幕中央依次出现的视觉图形, 但指导语中不会告知受试者三联体的存在。学习结果测试: 受试者需完成32个试次的二选一的迫选再认测试(two-alternative-forced-choice, 2AFC)。每个试次中会给受试者先后呈现两个三联体, 其中, 一个三联体是在熟悉阶段重复出现的目标刺激(TP = 1), 而另一个三联体则是由24个图形中的三个图形组成但从未在熟悉阶段出现过的干扰刺激(TP = 0)。测试任务是要求受试者判断其对先后呈现的两个三联体中哪一个更熟悉。受试者成功从干扰项中再认出熟悉阶段见过的三联体, 即说明其在熟悉阶段对图形之间的TP进行了统计学习, 再认正确率即为视觉统计学习分数, 是衡量个体视觉统计学习能力的重要行为指标(Frost, Siegelman, Narkiss, & Afek, 2013)。Batterink和Paller提出统计学习至少包含了与知觉和记忆加工相关的两个子成分, 一是知觉组合, 二是记忆存储和提取, 以语言的听觉统计学习为例, 知觉组合主要是将反复同时出现的相邻单个刺激(如: 音节“tu”和“be”)组合成一个复合体(如: 双音节单词“tube”), 也就是词汇切分的过程, 而记忆存储则是将这些复合体保存下来以备结果测试阶段提取用(Batterink & Paller, 2017, 2019)。
传统观点认为统计学习过程中主要有两个外在特征: 一是学习者在学习过程中没有接受外部指导, 在刺激熟悉阶段学习者不会被告知要学习的内容, 二是学习者对学习到的统计知识没有外显意识, 从再认测试结果可以推测其是否掌握了刺激的统计规律, 但是学习者即使掌握了统计规律也不能将其外显报告出来。研究者常把统计学习和内隐学习联系在一起, 内隐学习是指个体在没有外部指导下学习且对所学的东西没有外显意识的一种学习, 最早由Reber (1967)提出(Batterink, Reber, Neville, & Paller, 2015), 此外, 统计学习和内隐学习的内容都涉及序列及概率等统计结构信息, 由此, 不少研究者也直接将统计学习称为内隐统计学习(Goujon, Didierjean, & Thorpe, 2015; Jost, Conway, Purdy, Walk, & Hendricks, 2015; Perkovic & Orquin, 2018)。然而, 有研究者开始质疑用“个体不能外显报告刺激的统计规律”这个单一的外部行为指标来判断“统计学习者没有外显意识”这个学习特征的合理性, 这种“全或无”式的指标可能过于简单和严格, 会导致低估学习者的外显知识。研究者以再认测试后学习者对测试阶段的选择的主观自信程度这个外部行为指标作为统计学习外显知识的评价指标之一, 结果发现个体对迫选测试阶段的选择的主观自信程度和其统计学习的再认成绩是密切相关的(Batterink et al., 2015; Bertels, Franco, & Destrebecqz, 2012)。也就是说, 即使个体不能报告具体的统计规律也并不代表个体对统计学习没有外显知识。新近有研究者提出统计学习和内隐学习虽有重叠但实际上各自侧重学习的不同方面, 前者更关注学习内容, 如刺激所蕴含的频率和概率分布等统计结构信息, 而后者则更关注学习特点, 包括知识表征形式到底是抽象规则还是样例以及学习者对于知识的外显意识程度等(Arnon, 2019)。要厘清统计学习和内隐及外显学习之间的相对关系还需结合统计学习过程的认知神经方面的研究证据。
统计学习提出后, 后续研究相继证实了其在语言和非语言等不同认知领域, 在视、听不同通道, 在婴儿、儿童及成人等不同年龄个体, 在健康、自闭症谱系障碍等不同人群, 甚至在人类和猴子等不同物种上的普遍存在(Arnon, 2019; Kirkham, Slemmer, & Johnson, 2002; Milne, Petkov, & Wilson, 2018; Monroy, Meyer, Schroer, Gerson, & Hunnius, 2019; Newport, 2016; Raviv & Arnon, 2018; Roser, Aslin, McKenzie, Zahra, & Fiser, 2015; Saffran & Kirkham, 2018; Santolin & Saffran, 2018; Schwab et al., 2016; Shufaniya & Arnon, 2018; Slone & Johnson, 2018; 唐溢 等, 2015)。早期观点认为婴儿已经具备统计学习能力, 因此, 这是一种早期成熟的能力且不会随着年龄增长而有显著变化, 例如, 研究发现6岁儿童和成人听觉统计学习任务中的成绩并无显著差异(Saffran, Newport, Aslin, Tunick, & Barrueco, 1997), 而近期不少研究者则支持“个体统计学习能力会随年龄增长而发展变化且同时受刺激类型和通道等因素的制约”这一观点(Frost, Armstrong, Siegelman, & Christiansen, 2015), 5~12岁儿童听觉语言刺激的统计学习不受年龄影响, 但视觉统计学习及听觉非语言刺激的统计学习都可随年龄增长而进步(Arciuli & Simpson, 2011; Raviv & Arnon, 2018; Shufaniya & Arnon, 2018)。近年来, 研究者开始关注不同个体在不同领域和不同通道下的不同类型统计学习所具有的特异性及其在语言等认知中的作用(Frost et al., 2015; Krogh, Vlach, & Johnson, 2012)。
近期研究表明统计学习存在显著的个体差异, 从统计学习的测试成绩来看, 样本总体的平均成绩显著优于机遇水平, 但就个体统计学习成绩的分布来看是存在显著个体差异的, 约有三分之一的受试者成绩低于机遇水平(Arnon, 2019; Frost et al., 2015; Siegelman, Bogaerts, & Frost, 2017; Siegelman & Frost, 2015), 而对老、中、青三个不同年龄组的成人听觉统计学习的一项差异研究也发现, 统计学习随着年龄增长存在退化现象, 并且这种退化跟工作记忆更新能力随年龄增长的下降有关(Palmer, Hutson, & Mattys, 2018)。来自儿童识字能力(Spencer, Kaschak, Jones, & Lonigan, 2015), 儿童对被动句和宾语从句的句法理解(Kidd & Arciuli, 2016)和大学生对关系从句的加工(Misyak, Christiansen, & Tomblin, 2010)等方面的证据都表明统计学习的这种个体差异也会直接影响统计学习在语言中的作用, 该部分内容将在介绍统计学习在语言中的作用时具体阐述。由此, 本研究将侧重从统计学习的认知神经机制和统计学习与语言的关系两个方面总结分析该领域的新进展并提出未来研究展望。
继大量行为研究证实了统计学习在跨领域、跨通道、跨群体中的普遍存在, 研究者开始探讨这种普遍存在的统计学习的内在认知神经机制, 主要围绕对统计学习过程和统计学习特异性这两方面的神经机制展开, 以下将从这两方面进行阐述。
统计学习全程包括了刺激熟悉和学习结果测试两个阶段, 事实上, 刺激熟悉阶段是真正“纯粹”的在线学习过程, 包含了知觉组合和记忆存储的过程, 而学习结果测试阶段则主要反映了记忆的提取过程。Cunillera及其团队通过听觉统计学习的ERP研究发现, 在刺激熟悉阶段呈现的音节流中, 构成无意义词的三个音节相对非词的三个音节会在300~500 ms的时间窗诱发一个显著的类似N400的负成分, 并且随着词汇音节暴露的时间越长该成分的波幅会变小, 研究者认为该成分就是词汇切分的神经电生理标记, 进一步的fMRI研究则发现词汇切分过程中颞上回后部和腹侧前运动皮层的上部有显著激活(Cunillera et al., 2009; Cunillera, Toro, Sebastian-Galles, & Rodriguez-Fornells, 2006)。Batterink和Paller (2017)比较了刺激熟悉阶段符合组词规律和随机两种音节流下诱发的脑电的神经夹带(neural entrainment)差异, 进一步揭示了知觉组合过程的神经电生理模式。研究通过莫莱小波变换以两种条件下词频率和音节频率的试次间同步性(inter-trial coherence, ITC)的比例为词汇学习指标(word learning index, WLI), 结果发现符合组词规律的音节流诱发的WLI大于随机音节流所诱发的, 随着个体对刺激熟悉度的增加该差距会增大, 且刺激熟悉阶段的脑电WLI能预测测试阶段词汇学习的行为表现。此外, Batterink和Paller (2019)采用视觉的跨通道干扰任务对比了有无干扰下听觉统计学习的神经夹带差异, 结果发现两种条件下统计学习知觉组合过程中的神经夹带并无显著差异, 结果表明知觉组合过程并不需要有意注意的参与。但是, 基于当前研究结果, 本研究认为目前还很难分离知觉组合和存储两个子过程, 未来需要整合多模态的神经数据来进一步揭示知觉组合和存储之间的关系, 寻找二者在时间或空间上分离的证据。
同时, 以往对学习结果测试阶段的研究主要关注学习者离线的再认正确率, 而忽视对学习者在线的再认过程本身的研究。对统计学习效果的判断是依据个体在学习结果测试阶段是否对具有不同TP的刺激做出差别化反应去推测其在刺激熟悉阶段是否掌握了刺激流所蕴含的统计规律, 而这个差别化的反应不仅应体现在学习者从干扰刺激中再认出刺激熟悉阶段的三联体这个离线的行为指标, 还应体现在大脑的再认过程中的神经活动模式。研究发现, 相对干扰刺激, 学习者在再认阶段看到目标三联体会在700~1000 ms的时间窗诱发更大的后正成分(late positive component, LPC), 进一步比较学习者对目标三联体中前、中、后不同位置的音节刺激进行再认时的反应时及P300波幅的差异, 结果发现, 在启动效应的作用下, 目标三联体中越靠后的音节被正确再认的速度越快, 其在400~800 ms的时间窗诱发的P300效应也越小, 因为概率越大及越容易被预测的刺激诱发的P300效应会越小(Batterink, 2017; Batterink et al., 2015)。
此外, 以往在学习结果测试阶段对统计学习中的外显知识的考察也主要依赖于对三联体出现概率的离线估计, 这可能导致低估了统计学习过程中外显学习的参与而高估了内隐学习的参与。已有研究表明, 内隐学习记忆系统主要依赖于纹状体等基底神经节核团(basal ganglia), 而外显学习记忆系统主要依赖于海马等内侧颞叶皮层(medial temporal lobe, MTL) (Knowlton, Mangels, & Squire, 1996; Squire, Stark, & Clark, 2004)。由此, 研究者通过考察不同类型统计学习过程中外显学习和内隐学习的脑功能区的激活和连接等神经模式, 进一步揭示了统计学习过程中外显和内隐学习系统的动态卷入, 结果发现, 不同类型的统计学习中外显和内隐两个学习记忆系统的卷入是不同的(Batterink, Paller, & Reber, 2019; Sawi & Rueckl, 2018)。研究者采用睡眠监控和fMRI技术考察睡眠对于听觉声调统计学习的影响, 结果发现, 受试者间隔24小时经历睡眠后测试的成绩优于仅间隔30分就测试的成绩, 且慢波睡眠的量能有效其预测统计学习的成绩和脑功能区的激活, 睡眠后纹状体和旁海马回的连接减弱而壳核和颞平面的连接增强, 结果表明统计学习过程伴随着学习记忆系统从海马到纹状体的逐渐转移, 且睡眠有助于该转移过程(Durrant, Cairney, & Lewis, 2013)。也就是说, 统计学习并非由统一的内隐学习记忆系统所支配, 在统计学习全程中, 个体的外显和内隐两个学习记忆系统的卷入是动态变化的, 统计学习的具体类型会调节这种变化。
尽管统计学习被证实是一种普遍存在, 但近年来研究者开始关注统计学习特异性的神经机制, 即不同个体在不同领域、不同通道的不同类型统计学习的神经特异性。从统计学习的领域特异性来看, 大脑对不同领域的统计信息进行加工时, 其神经活动模式是存在差异的。内侧颞叶皮层在提取时间统计规则中起着重要作用(Schapiro, Gregory, Landau, McCloskey, & Turk-Browne, 2014), 而当根据声音的统计规律进行类别学习时, 纹状体后部对刺激的统计结构信息比较敏感, 其与左侧颞上沟的连接强度和类别学习的离线成绩相关(Lim, Fiez, & Holt, 2019)。来自婴儿面孔识别的ERP研究则发现6.5个月大婴儿可根据双峰分布而非单峰分布的频率信息进行统计学习(Altvater-Mackensen, Jessen, & Grossmann, 2017)。而Monroy团队通过脑电和眼动的系列研究表明, 婴儿能够通过观察连续的动作序列而掌握统计规律从而产生一定的动作预期, 这种动作预期可反映在其眼动模式上(Monroy, Gerson, & Hunnius, 2017), 而当测试阶段出现违背预期的动作时会在中部电极250~750 ms的时间窗诱发一个负电位(Monroy, Gerson, Dominguez-Martinez et al., 2019), 脑电的频域分析则发现预期动作会伴随mu节律(7~9 Hz)的抑制(Monroy et al., 2019)。
从统计学习的通道特异性来看, 视、听不同通道的统计学习可能存在大脑偏侧化差异, 统计学习对语言等认知影响也可能受到这种差异的制约(Karuza et al., 2013; Qi, Sanchez Araujo, Georgan, Gabrieli, & Arciuli, 2018; Roser, Fiser, Aslin, & Gazzaniga, 2011)。Roser等人(2011)采用左右视野下的视觉统计学习任务比较了裂脑人和控制组的学习成绩以考察统计学习的大脑不对称性, 结果支持了视觉统计学习的大脑右半球优势。Karuza等人(2013)采用fMRI技术探讨了听觉分词任务下的统计学习的神经活动模式, 则发现左脑额下回的激活和统计学习成绩存在显著相关。Qi等人(2018)进一步比较了听觉统计学习和视觉统计学习对儿童和成人的阅读发展的影响差异, 结果发现听觉统计学习对阅读发展的影响更大, 这可能与听觉统计学习和语言大脑功能区的左侧化有关, 但还需要未来研究进一步确认统计学习通道的神经特异性和语言等认知的神经特异性之间的关联。
从统计学习的个体特异性来看, 大量行为研究表明统计学习存在显著的个体差异, 但关于统计学习个体差异的神经机制尚不清楚。一方面, 有研究者通过比较成人、9~12岁和6~9岁儿童等三组人群在视觉统计学习测试阶段诱发的P300指标, 结果发现三组人群无显著差异, 作者认为这是支持个体统计学习的发展不变性(developmental invariance)的神经电生理证据(Jost et al., 2015)。而另一方面, 有研究者认为不同个体的统计学习存在神经特异性。研究者采用sMRI技术考察了5~8.5岁儿童的左侧额下皮层、海马和尾状核等三个兴趣脑区的皮层厚度和统计学习成绩之间的关系, 结果表明, 儿童左侧额下皮层的厚度和右侧海马的体积能预测其统计学习成绩, 尽管两个区域的厚度和体积不随年龄而变化, 但是年龄越大的儿童, 右侧海马对其统计学习的预测更强(Finn, Kharitonova, Holtby, & Sheridan, 2019)。此外, 与正常儿童相比, 自闭症谱系障碍儿童在视觉统计学习中诱发的N1和P300效应都较弱, N1波幅与其非言语智力分数相关, P300波幅与其社会适应能力相关(Jeste et al., 2015)。
统计学习的概念来自经典的婴儿语音切分研究, 早期研究侧重探讨统计学习对语言习得的影响, 近期研究开始关注二者之间的交互作用, 在进一步深入探讨统计学习在不同语言学习领域的具体作用的基础上, 考察个体母语和双语等语言学习经验对其统计学习的影响。
统计学习对语言的影响研究主要在两方面得到了扩展: 一是探讨统计学习对语音之外的其他语言任务的影响, 二是探讨统计学习对二语学习的影响。统计学习在语言中的作用最初是在语音词汇识别中得到确认, 后续研究则进一步证实其在语法、拼写、阅读等较复杂的语言任务中的作用(Elleman, Steacy, & Compton, 2019; Treiman, Kessler, Boland, Clocksin, & Chen, 2018)。大学生可以根据统计的分布信息学习人工语法中的内容词(Reeder, Newport, & Aslin, 2013), 而进一步对比20岁左右青年人和70岁以上老年人的统计学习, 则发现老年人也能根据统计信息学习人工语法词类, 但是成绩要差于青年人(Schwab et al., 2016)。此外, 个体统计学习成绩存在个体差异且这种差异能有效预测其关系从句的理解成绩(Misyak et al., 2010)。统计学习和阅读成绩之间的相关在儿童和成人两个群体上都得到了证实, 统计学习能力是预测阅读成绩的重要指标之一(Arciuli & Simpson, 2012)。而结构方程建模分析结果也揭示了统计学习对幼儿早期识字技能的预测作用(Spencer et al., 2015)。此外, ERP和fMRI的研究表明统计学习和语言加工过程中诱发的脑电和激活的脑区等神经模式有相似之处, 为统计学习在语言中的作用存在神经基础提供了支持证据(Christiansen, Conway, & Onnis, 2012; Petersson, Folia, & Hagoort, 2012)。
此外, 统计学习在语言学习中的作用也在语言发展障碍人群中得到进一步确认(Saffran, 2018)。例如, 阅读障碍大学生其听觉统计学习成绩优于机遇水平, 但是仍然显著差于正常对照组, 结果表明阅读障碍存在一般性统计学习缺陷(Gabay, Thiessen, & Holt, 2015)。对有、无发展性语言障碍(developmental language disorder, DLD)的两组受试者的听觉语言统计学习的研究进行元分析, 结果发现有发展性语言障碍的个体伴随明显的统计学习缺陷, 这也进一步确认了统计学习在语言学习中的作用(Lammertink, Boersma, Wijnen, & Rispens, 2017)。此外, 植入人工耳蜗的聋童由于早期的语言剥夺导致其统计学习成绩差于健听儿童, 而统计学习成绩相对好的聋童在其植入耳蜗后语言改善更好(Conway, Pisoni, Anaya, Karpicke, & Henning, 2011)。
除上述研究, 研究者也开始关注个体的统计学习能力是如何影响其二语学习的, 主要是因为二语学习存在有别于母语学习的特异性。语言特点和习得时间是影响语言学习的两个重要变量, 母语研究中可以分别探讨这两个因素的影响, 例如, 通过比较不同母语阅读障碍者在行为和神经上的共性与差异可以考察语言特点的影响(D'Mello & Gabrieli, 2018; Hu et al., 2010; Siok, Perfetti, Jin, & Tan, 2004), 也可以通过比较不同年龄开始学习母语的学习者在行为和神经上的的共性与差异考察习得时间的影响, 尤其是关键期前后的学习者, 例如, 成年后脱盲者和文盲就提供了很好的被试模型(Carreiras et al., 2009; Dehaene, Cohen, Morais, & Kolinsky, 2015)。研究者对比了前哥伦比亚游击队成员中的成年脱盲者和文盲及儿童期开始识字的成人等三组人群的大脑结构, 结果发现, 相对文盲, 识字的成人胼胝体压部的白质更多, 而双侧角回、背侧枕回和颞中回以及左侧缘上回和颞上回等区域的灰质更多, 而相对儿童期开始识字的成人, 成年脱盲者连接左右角回和背侧枕回的胼胝体部分白质更多(Carreiras et al., 2009)。然而, 二语学习的研究中这两个因素会变得更复杂且很难分离。首先, 母语学习和二语学习之间存在交互作用, 二语学习必须同时考虑母语和二语的语言特点, 而不同类型的二语学习者其母语和二语的语言特点的差异本身也存在差异(de Bruin, 2019), 那么, 统计学习对母语学习的影响就不能直接推论到其对二语学习的影响, 尤其是母语和二语存在很大语言差异时。其次, 即使二语学习者的母语和要学习的二语是相同的, 如果学习者开始学习二语的年龄不同, 其二语学习的认知神经机制也会存在差异(Das, Padakannaya, Pugh, & Singh, 2011)。同时, 相对母语学习, 二语学习者开始学习二语的年龄存在更大变异, 且关键期后的母语学习者属于少数情况(尤其是口语的习得)而关键期后的二语学习者却并非如此, 尤其在当前全球化进程中的多语需求刺激下, 成人外语学习者数量也是与日俱增(Cores-Bilbao, Fernandez-Corbacho, Machancoses, & Fonseca-Mora, 2019; Kramsch, 2014), 那么, 统计学习对关键期前的婴儿、儿童语言学习的影响也不能直接推论到其对关键期后的成人语言学习的影响。因此, 探讨统计学习对二语学习的影响具有重要的理论和现实意义。
统计学习影响婴儿非母语加工的研究主要探讨了2岁以内单语婴儿是如何加工非母语语言刺激的。研究发现, 婴儿同样能对非母语语言刺激进行统计学习, 但其统计学习在1岁左右会发生重要转变, 从跨语言普遍性转变为母语特异性。婴儿能根据非母语语言刺激中的统计线索进行音义的联结学习(Hay, Pelucchi, Estes, & Saffran, 2011)。Kuhl团队研究表明, 婴儿的语言习得具有高度可塑性, 随年龄增长其学习新语言的能力急速下降。婴儿一开始具有跨语言的普遍统计学习能力, 6~8个月的英语母语婴儿即便是短期接触非母语的普通话语音刺激/tɕʰ/和/ɕ/, 也能表现出跟普通话母语婴儿一样的语音分辨能力, 然后婴儿逐渐对母语刺激的统计信息更加敏感, 对母语语音的辨别能力逐渐增强而对非母语语音的辨别能力则逐渐减弱, 8~10个月是发生转变的关键期, 10~12个月的婴儿对非母语语音的敏感性下降(Kuhl, 2004; Kuhl, Tsao, & Liu, 2003)。新近研究者对88名5、11、14个月大的三组荷兰婴儿的非母语普通话一声和四声的声调统计学习进行了研究, 结果发现婴儿随着月龄的增加其辨别非母语声调的能力也逐渐下降(Liu & Kager, 2017)。
然而, 统计学习影响成人二语学习的研究则相对匮乏, 且主要是来自视觉统计学习方面的证据。Frost等(2013)作为先驱者首先采用视觉统计学习任务考察了母语为英语的成人希伯来语二语学习者个体统计学习能力和二语识字能力之间的关系。结果发现, 视觉统计学习能力好的二语学习者能更好地掌握希伯来语单词中的闪族结构。此外, 吴娴团队以成人的汉语母语者和汉语二语学习者为研究对象, 比较分析了两组人在中文假形声字的形音转换任务中的大脑神经模式, 计算了两组人在视觉统计学习任务中的成绩和负责形音转换加工的6个兴趣区脑激活之间的相关, 结果发现, 汉语母语者视觉统计学习成绩和左侧顶下小叶的激活存在显著负相关, 而汉语二语学习者视觉统计学习成绩和左侧额下回的激活显著负相关, 研究表明个体统计学习的能力和单词识别中的形音转换加工密切相关(Yu et al., 2019)。
与大量关于统计学习对语言的影响研究相比, 语言经验对统计学习的影响研究则匮乏得多, 这些研究主要探讨了母语经验和双语经验对统计学习的影响。首先, 不同母语者的统计学习会受其母语特点的影响而表现出语言特异性。英语和韩语中分别采用“in Sapporo”这样的中心语在前(head-initial)和“Sapporo in”这样的中心语在后(head-final)的语序结构, 这种语序结构就会导致英语中顺序TP偏低而逆序TP偏高, 因为“in”之后可以搭配很多其他词而“Sapporo”之前则只有很少的词可以组合, 而韩语则反之。由此, 研究者考察了语言中不同语序结构对其成年母语使用者的听觉语言刺激(无意义音节)、视觉非语言刺激(抽象图形)和听觉非语言刺激(纯音)等不同类型统计学习的影响, 结果发现, 语言特点会制约个体的统计学习偏好, 母语韩语者对顺序TP更敏感, 而母语英语者对逆序TP更敏感, 且这种偏好只表现在语言刺激的统计学习中(Onnis & Thiessen, 2013)。进一步对比不同月龄英语和韩语婴儿听觉统计学习的特点发现, 7个月大英语婴儿对顺序和逆序TP没有偏好, 但13个月大英语婴儿已表现出和英语成人一样的逆序TP偏好。由此, 研究者认为个体的统计偏好是在母语经验的影响下而逐渐发展起来的(Thiessen, Onnis, Hong, & Lee, 2019)。
其次, 双语经验有利于语言刺激的统计学习。有研究比较了英语单语者、汉语单语者、汉语-英语双语者、英语-非声调语(韩语、西班牙语、德语、法语等)双语者等4组成人完成一项人工声调语言统计学习任务的表现以考察先前语言经验(母语和双语)对后继学习的影响。结果发现, 汉语单语者成绩高于机遇水平, 但和英语单语者的成绩没有显著差异, 而汉语-英语双语者和英语-非声调语双语者的统计学习成绩显著高于机遇水平且优于其他两组单语者。该研究表明, 母语声调语言的经验对学习新的声调语言并没有显著的正迁移作用, 但无论双语经验中是否有声调语言的经验, 双语经验都有助于学习新的人工声调语言(Wang & Saffran, 2014)。随后的一项追踪研究也进一步证实了双语经验在新语言刺激的统计学习中的作用。研究者比较了母语非声调语的汉语初学者学习汉语前后半年在人工声调语言听觉统计学习和视觉统计学习的表现及其与控制组的差异, 结果发现汉语学习组和控制组的视觉统计学习半年后均有显著改善, 但听觉统计学习成绩仅汉语学习组有显著改善(Potter, Wang, & Saffran, 2017)。
此外, 来自双语婴儿和单语婴儿的对比研究也进一步支持了双语经验对语言统计学习的促进作用。通过对比14个月大的两组婴儿在两种人工语言中利用音节转移概率进行词汇切分的能力, 结果发现, 当单独呈现一种人工语言的语音流时, 单语婴儿能够进行统计学习并表现出词切分能力, 而当两种人工语言的语音流交替出现时, 仅双语婴儿能根据各自的统计转移概率完成两种语言的词切分(Antovich & Estes, 2018)。然而, 新近也有研究者质疑了双语经验对统计学习的促进作用, 研究者比较了英语单语者、西班牙语-加泰罗尼亚语双语者、西班牙语-英语双语者等三组人在视觉图形统计学习中的表现, 该统计学习中同时包含了两种统计规律, 结果发现三组受试者均能发现两种统计规律且学习成绩无显著差异, 由此, 研究者认为双语经验对统计学习并无显著的促进作用(Bulgarelli, Bosch, & Weiss, 2019)。对比以上研究可以发现, 双语经验对统计学习的促进作用主要体现在听觉语言刺激的统计学习中, 在视觉非语言刺激的统计学习中并没有体现出来。因此, 双语经验对统计学习的影响可能受到领域或通道的制约, 未来研究需进一步探讨制约双语经验对统计学习的影响的因素及其内在的认知神经机制。
尽管统计学习的普遍存在被大量证实, 但当前对统计学习内在认知神经机制的认识还不够清楚(Sawi & Rueckl, 2018), 未来研究需整合脑-行为不同层面的多模态数据信息, 探讨统计学习自身及其与语言等认知活动交互作用的认知神经机制, 更好地服务于当前全球化进程下外语学习的国际性需求。
以往统计学习的研究主要集中在证实普遍存在和探讨其特异性两个方面, 但大多依赖测试阶段的再认成绩这个指标, 指标单一且相对缺乏对刺激熟悉阶段的研究, 而实际上统计学习真正的“纯粹”学习过程是在刺激熟悉阶段, 即个体是如何逐步掌握刺激所蕴含的统计结构的动态过程及其神经活动模式的变化, 未来可从以下两个方面进一步研究。
首先, 在离线评价基础上, 进一步丰富测试阶段关于学习效果和学习者外显知识的在线评价手段。对学习效果的评价, 除了经典的学习者对三联体整体的再认正确率以外, 可进一步考察三联体再认过程的大脑神经活动模式, 以及学习者对三联体中前、中、后不同位置刺激的局部加工的行为和神经模式(Batterink et al., 2015)。对学习者外显知识的离线评价, 除了测试后学习者主观信心程度的总体评价, 可让受试者对每个测试试次中的选择进行主观评价(Batterink et al., 2015; Bertels et al., 2012)。Batterink等人(2015)要求受试者对每一个测试试次中的选择进行三类评价: “记住” (remember), 是指受试者根据之前的学习对选项有记忆并对作出的选择是有信心的; “熟悉” (familiar), 是指受试者觉得二选一的选项中有一个是相对更熟悉的, 但是没有特定的记忆; “猜” (guess), 是指受试者不知道哪一个选项是正确的, 感觉是随机作出选择的。结果表明, 受试者对选择的三种分类条件下的再认成绩存在显著差异, 判断为“猜”的情况下其正确率和机遇水平无显著差异。此外, 还可通过受试者在测试阶段内隐和外显学习系统的神经指标的动态变化推测其外显知识情况, 这对于研究婴幼儿、自闭症甚至猴子等不能通过外部评价测量其外显知识的特殊对象的统计学习的神经机制显得尤为重要(Finn et al., 2019)。
其次, 如何在缺乏外部行为评价指标的情况下, 整合fMRI、sMRI、ERP、DTI、MEG等脑的多模态数据揭示刺激熟悉阶段的统计学习的动态变化, 可包括三个方面的内容: 一是对比分析刺激熟悉的不同阶段其神经模式差异, 揭示在线学习过程中的动态变化模式, 例如, 采用MEG技术分析比较了听觉统计学习的不同阶段, 结果发现修正已习得统计知识比学习新的统计知识更耗费时间(Daikoku, Yatomi, & Yumoto, 2017)。二是建立在线学习过程中的神经指标和测试阶段的学习效果的直接联系, 例如, 学习第二阶段背侧听觉和前运动皮层的连接强度和听觉词汇学习的成绩相关(Lopez-Barroso et al., 2015); 左侧额下回的激活和统计学习成绩相关(Karuza et al., 2013); 视觉统计学习500~1000 ms诱发的事件相关电位与语法判断反应时相关(Daltrozzo et al., 2017)。三是在线学习过程中内隐和外显学习系统的神经卷入和测试阶段外显认知评价结果之间的关系, 例如, 统计学习过程伴随着学习记忆系统从海马到纹状体的逐渐转移(Durrant et al., 2013); 内隐和外显学习记忆脑区的结构和统计学习成绩之间的关系(Finn et al., 2019)。在以上内容的研究基础上, 通过分析比较不同个体在不同领域和不同通道下的不同类型统计学习的动态学习过程, 提高对统计学习特异性的认识, 从而进一步丰富统计学习的认知神经机制。
当前全球化进程对成人的多语竞争力提出了更高需求, 本研究认为未来统计学习研究的一个重要方面是揭示统计学习在成人二语学习中的独特作用机制以促进语言学习。当前该方面的研究还处于初步探索阶段, 未来研究应整合多模态数据, 进一步确认统计学习影响成人二语学习的认知机制和神经基础。
首先, 并非所有的双语者都是相同的, 个体在语言经验和认知能力上的差异会制约统计学习在其二语学习中的作用, 如何在这些因素制约下提高个体对二语中不同类型刺激的统计规律的敏感性是促进二语学习的关键问题, 尤其是当二语和母语存在较大的差异时。双语研究中需要非常细致地描述和评估双语者的语言经验和个体在统计学习、认知控制、工作记忆、智力等认知方面的差异(de Bruin, 2019; Hung et al., 2019; Kuo et al., 2015)。以阅读为例, 阅读的神经机制会受到语言特点和习得时间的影响, 因表音和表意文字中形-音和形-义之间的匹配度不同, 英文阅读障碍者存在左脑颞顶区的激活异常, 而中文阅读障碍者在左脑额中回存在结构和功能的异常, 但中文阅读障碍者在左脑颞顶区的激活是否异常还存在分歧(D'Mello & Gabrieli, 2018; Hu et al., 2010; Siok et al., 2004)。即使同样是表音文字, 形-音之间的透明度也存在差异, 阅读意大利语和印地语等形-音透明度较高的文字时, 背侧通路中与语音加工相关的脑区激活会增强, 而阅读英语等形-音透明度较低的文字时, 腹侧通路中与语义加工相关的脑区激活会增强, 对于印地语-英语双语者而言, 其阅读印地语和英语时的神经活动模式差异则与英语学习时间有关(Das et al., 2011)。因此, 当母语和二语分属表音表意不同文字系统或有声调无声调不同语言的话, 在母语迁移的影响下二语学习者对视、听等不同类型统计学习的统计规律可能具有不同的敏感性, 从而影响统计学习在二语学习中的作用。此外, 不同刺激不同通道下的不同类型统计学习能力的个体差异与听、说、读、写等不同方面语言能力之间是什么样的关系?与学习者的智力、认知控制、工作记忆等其他认知因素相比, 二语学习者统计学习能力独立解释二语学习成绩的变异程度究竟如何?这些都是未来研究需回答的问题。
其次, 已有研究表明成人二语学习具有重要的神经生物学基础(Kuhl et al., 2016; Mamiya, Richards, Coe, Eichler, & Kuhl, 2016)。Mamiya等人(2016)采用DTI技术追踪了留美中国大学生参加英语语言课程前后的大脑白质结构变化, 结果发现, 大学生参加课程时间越久其右上纵束的各向异性分数(fractional anisotropy, FA)越高而径向扩散系数(radial diffusivity, RD)越低, 并且个体儿茶酚胺氧位甲基转移酶(catechol-O-methyltransferase, COMT)基因的类型会影响其二语学习时间和大脑白质结构变化之间的关系, COMT genotype和FA两个因素能很好地解释学生语言课程的成绩的变异。类似地, Kuhl等人(2016)采用DTI技术考察了生活在美国的成人西班牙语-英语的双语者的大脑白质结构和其在美国生活时间及二语使用时间的关系, 结果发现, 左侧额枕下束的各向异性分数与受试者在美生活及讲英语的年限均有显著正相关, 而该区域的径向扩散系数则与受试者在美生活及听英语的年限均有显著负相关。那么, 在伴随二语学习发生的这些大脑结构变化过程中, 统计学习究竟起到什么样的作用呢?统计学习和成人二语学习在行为和脑两个层面的关联究竟是怎样的?以及这些关联又在不同类型二语学习者以及二语学习不同阶段发生哪些动态变化呢?这些也都是未来研究需回答的问题。
最后, 统计学习是一种在年龄、通道、刺激类型等因素的制约下具有一定可塑性的能力, 未来研究可以在探讨有效促进统计学习的因素的基础上, 针对不同群体的不同语言需求有针对性地设计统计学习的干预方案, 从而促进语言学习等认知能力的提高(Deocampo, Smith, Kronenberger, Pisoni, & Conway, 2018)。统计学习的干预是通过提高个体对统计结构信息的敏感性来达到提高相应认知能力的目的, 干预思路可考虑从直接干预和间接干预两方面入手。直接干预可考虑通过结合不同个体的统计学习偏好来设计统计学习材料及其呈现方式来提高个体对统计规律的敏感性。研究表明, 双峰分布信息较单峰分布信息更有利于婴儿的语音和面孔的统计学习(Altvater-Mackensen et al., 2017; 宋新燕, 孟祥芝, 2012), 而与刺激的统计规律一致的二级跨通道线索能有效促进统计学习, 研究发现当视觉的形状和色彩的联结一致性与听觉语音刺激的统计规律一致时听觉统计学习成绩会提高(Forest, Lichtenfeld, Alvarez, & Finn, 2019), 因此, 未来研究可考虑将语言信息分布特点和视听通道整合等两个因素结合进一步探讨促进不同人群语言统计学习的最佳组合。而间接干预则是通过跨领域的音乐训练等达到促进语言统计学习的目的。研究表明音乐训练能提高个体对听觉刺激的一般性的识别和预测能力从而促进其语言统计学习的能力(Francois, Chobert, Besson, & Schon, 2013; Francois & Schon, 2011; Zhao & Kuhl, 2016)。ERP研究发现, 与未接受专业音乐训练的普通人相比, 接受过12年以上专业音乐训练的成人音乐家在新的人工语言中的听觉统计学习成绩更好(Francois & Schon, 2011)。对8岁儿童进行音乐训练并追踪研究2年发现, 接受音乐训练的儿童在行为和脑电指标上都表现出了更好地语音切分能力(Francois et al., 2013)。Zhao和Kuhl (2016)进一步采用MEG技术在oddball范式下考察了音乐训练对于9个月大婴儿音乐和语音加工的影响, 结果发现, 与控制组婴儿相比, 音乐和语音违背的刺激会在受音乐训练的婴儿的听觉皮层和前额叶皮层诱发更大的失匹配反应(mismatch response, MMR)。未来研究需进一步检验传统音乐训练对个体语音统计学习的促进作用并深入探讨其作用的认知神经机制, 帮助建立促进语言学习的最佳音乐训练方案, 包括音乐训练的形式和时间等。同时, 以语音和音乐刺激为材料, 直接比较两种材料的统计学习训练在不同人群语言学习中的促进作用, 检验不同统计学习训练在不同人群中的适用性。
Brain responses reveal that infants' face discrimination is guided by statistical learning from distributional information,
Learning across languages: Bilingual experience supports dual language statistical word segmentation,
Statistical learning in typically developing children: The role of age and speed of stimulus presentation,
It is possible that statistical learning (SL) plays a role in almost every mental activity. Indeed, research on SL has grown rapidly over recent decades in an effort to better understand perception and cognition. Yet, there remain gaps in our understanding of how SL operates, in particular with regard to its (im)mutability. Here, we investigated whether participant-related variables (such as age) and task-related variables (such as speed of stimulus presentation) affect visual statistical learning (VSL) in typically developing children. We tested 183 participants ranging in age from 5 to 12 years and compared three speeds of presentation (using stimulus durations of 800, 400 and 200 msecs). A multiple regression analysis revealed significant effects of both age and speed of presentation - after attention during familiarization and gender had been taken into consideration. VSL followed a developmental trajectory whereby learning increased with age. The amount of learning increased with longer presentation times (as shown by Turk-Browne, Junge & Scholl, 2005, in their study of adults). There was no significant interaction between the two variables. These findings assist in elucidating the nature of statistical learning itself. While statistical learning can be observed in very young children and at remarkably fast presentation times, participant- and task-related variables do impact upon this type of learning. The findings reported here may serve to enhance our understanding of individual differences in the cognitive and perceptual processes that are thought to rely, at least in part, on SL (e.g. language processing and object recognition).
Statistical learning is related to reading ability in children and adults,
Statistical learning, implicit learning, and first language acquisition: A critical evaluation of two developmental predictions.
Computation of conditional probability statistics by 8- month-old infants,
Rapid statistical learning supporting word extraction from continuous speech,
Online neural monitoring of statistical learning,
The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the reaction time (RT) task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning.
Statistical learning of speech regularities can occur outside the focus of attention,
Statistical learning, the process of extracting regularities from the environment, plays an essential role in many aspects of cognition, including speech segmentation and language acquisition. A key component of statistical learning in a linguistic context is the perceptual binding of adjacent individual units (e.g., syllables) into integrated composites (e.g., multisyllabic words). A second, conceptually dissociable component of statistical learning is the memory storage of these integrated representations. Here we examine whether these two dissociable components of statistical learning are differentially impacted by top-down, voluntary attentional resources. Learners' attention was either focused towards or diverted from a speech stream made up of repeating nonsense words. Building on our previous findings, we quantified the online perceptual binding of individual syllables into component words using an EEG-based neural entrainment measure. Following exposure, statistical learning was assessed using offline tests, sensitive to both perceptual binding and memory storage. Neural measures verified that our manipulation of selective attention successfully reduced limited-capacity resources to the speech stream. Diverting attention away from the speech stream did not alter neural entrainment to the component words or post-exposure familiarity ratings, but did impact performance on an indirect reaction-time based memory test. We conclude that theoretically dissociable components of statistically learning are differentially impacted by attention and top-down processing resources. A reduction in attention to the speech stream may impede memory storage of the component words. In contrast, the moment-by-moment perceptual binding of speech regularities can occur even while learners' attention is focused on a demanding concurrent task, and we found no evidence that selective attention modulates this process. These results suggest that learners can acquire basic statistical properties of language without directly focusing on the speech input, potentially opening up previously overlooked opportunities for language learning, particularly in adult learners.
Understanding the neural bases of implicit and statistical learning.
Both implicit learning and statistical learning focus on the ability of learners to pick up on patterns in the environment. It has been suggested that these two lines of research may be combined into a single construct of
Implicit and explicit contributions to statistical learning,
Statistical learning allows learners to detect regularities in the environment and appears to emerge automatically as a consequence of experience. Statistical learning paradigms bear many similarities to those of artificial grammar learning and other types of implicit learning. However, whether learning effects in statistical learning tasks are driven by implicit knowledge has not been thoroughly examined. The present study addressed this gap by examining the role of implicit and explicit knowledge within the context of a typical auditory statistical learning paradigm. Learners were exposed to a continuous stream of repeating nonsense words. Learning was tested (a) directly via a forced-choice recognition test combined with a remember/know procedure and (b) indirectly through a novel reaction time (RT) test. Behavior and brain potentials revealed statistical learning effects with both tests. On the recognition test, accurate responses were associated with subjective feelings of stronger recollection, and learned nonsense words relative to nonword foils elicited an enhanced late positive potential indicative of explicit knowledge. On the RT test, both RTs and P300 amplitudes differed as a function of syllable position, reflecting facilitation attributable to statistical learning. Explicit stimulus recognition did not correlate with RT or P300 effects on the RT test. These results provide evidence that explicit knowledge is accrued during statistical learning, while bringing out the possibility that dissociable implicit representations are acquired in parallel. The commonly used recognition measure primarily reflects explicit knowledge, and thus may underestimate the total amount of knowledge produced by statistical learning. Indirect measures may be more sensitive indices of learning, capturing knowledge above and beyond what is reflected by recognition accuracy.
How implicit is visual statistical learning?,
Multi-pattern visual statistical learning in monolinguals and bilinguals,
An anatomical signature for literacy,
Similar neural correlates for language and sequential learning: Evidence from event-related brain potentials,
Implicit sequence learning in deaf children with cochlear implants,
Deaf children with cochlear implants (CIs) represent an intriguing opportunity to study neurocognitive plasticity and reorganization when sound is introduced following a period of auditory deprivation early in development. Although it is common to consider deafness as affecting hearing alone, it may be the case that auditory deprivation leads to more global changes in neurocognitive function. In this paper, we investigate implicit sequence learning abilities in deaf children with CIs using a novel task that measured learning through improvement to immediate serial recall for statistically consistent visual sequences. The results demonstrated two key findings. First, the deaf children with CIs showed disturbances in their visual sequence learning abilities relative to the typically developing normal-hearing children. Second, sequence learning was significantly correlated with a standardized measure of language outcome in the CI children. These findings suggest that a period of auditory deprivation has secondary effects related to general sequencing deficits, and that disturbances in sequence learning may at least partially explain why some deaf children still struggle with language following cochlear implantation.
A music-mediated language learning experience: Students' awareness of their socio-emotional skills,
In a society where mobility, globalization and contact with people from other cultures have become its distinctive traits, the enhancement of plurilingualism and intercultural understanding should be of the utmost concern. From a positive psychology perspective, agency is the human capacity to affect other people positively or negatively through one's actions. This agentic vision can be related to mediation, a concept rooted in socio-cultural learning theory, where social interaction is considered a fundamental cornerstone in the development of cognition. These social interactions in the language learning setting may be facilitated through musical activities due to their social bonding effect. This paper tries to offer insights into how a music-mediated experience in language learning may develop students' interpersonal and collaborative competences to become active members of a more inclusive society. Mediation, considered to be a paradigm shift in the foreign language classroom and for different out-of-class language learning possibilities, could also provide an environment where learners maximize their emotional intelligence. Our paper focuses on this paradigm shift spearheaded by the Common European Framework for Languages Companion Volume (CEFR/CV) and the considerable repercussions it is bound to have for foreign language didactics, as cooperative tasks become central to foreign language learning. We hypothesize that mediated language learning experiences (MeLLEs) imply a socio-emotional change in learners, focusing on the others, on their needs and interests, by trying to help them understand texts, concepts or facilitating communication with their peers. An intervention with a music-MeLLE was designed and implemented in an L2 classroom of adult learners with divergent backgrounds. A self-assessment scale with mediation descriptors and the socio-emotional expertise scale (SEE) were administered. Results show that students become more mindful of their strengths, and of their capacity for collaboration and teamwork. This leads to more awareness of their mediation skills. Students' mediation skills correlate significantly with their socio-emotional skills - specifically with their expressivity. The implementation of a music-mediated experience also promoted tolerance and enhanced learners' intrinsic motivations for language learning at the same time as acknowledging their diversity.
Time course and functional neuroanatomy of speech segmentation in adults,
The present investigation was devoted to unraveling the time-course and brain regions involved in speech segmentation, which is one of the first processes necessary for learning a new language in adults and infants. A specific brain electrical pattern resembling the N400 language component was identified as an indicator of speech segmentation of candidate words. This N400 trace was clearly elicited after a short exposure to the words of the new language and showed a decrease in amplitude with longer exposure. Two brain regions were observed to be active during this process: the posterior superior temporal gyrus and the superior part of the ventral premotor cortex. We interpret these findings as evidence for the existence of an auditory-motor interface that is responsible for isolating possible candidate words when learning a new language in adults.
The effects of stress and statistical cues on continuous speech segmentation: An event-related brain potential study,
Cognitive neuroscience of dyslexia,
Purpose: This review summarizes what is known about the structural and functional brain bases of dyslexia. Method: We review the current literature on structural and functional brain differences in dyslexia. This includes evidence about differences in gray matter anatomy, white matter connectivity, and functional activations in response to print and language. We also summarize findings concerning brain plasticity in response to interventions. Results: We highlight evidence relating brain function and structure to instructional issues such as diagnosis and prognosis. We also highlight evidence about brain differences in early childhood, before formal reading instruction in school, which supports the importance of early identification and intervention. Conclusion: Neuroimaging studies of dyslexia reveal how the disorder is related to differences in structure and function in multiple neural circuits.
Statistical learning of an auditory sequence and reorganization of acquired knowledge: A time course of word segmentation and ordering,
Visual statistical learning is related to natural language ability in adults: An ERP study,
Statistical learning (SL) is believed to enable language acquisition by allowing individuals to learn regularities within linguistic input. However, neural evidence supporting a direct relationship between SL and language ability is scarce. We investigated whether there are associations between event-related potential (ERP) correlates of SL and language abilities while controlling for the general level of selective attention. Seventeen adults completed tests of visual SL, receptive vocabulary, grammatical ability, and sentence completion. Response times and ERPs showed that SL is related to receptive vocabulary and grammatical ability. ERPs indicated that the relationship between SL and grammatical ability was independent of attention while the association between SL and receptive vocabulary depended on attention. The implications of these dissociative relationships in terms of underlying mechanisms of SL and language are discussed. These results further elucidate the cognitive nature of the links between SL mechanisms and language abilities.
Neuroimaging reveals dual routes to reading in simultaneous proficient readers of two orthographies,
Orthographic differences across languages impose differential weighting on distinct component processes, and consequently on different pathways during word-reading tasks. Readers of transparent orthographies such as Italian and Hindi are thought to rely on spelling-to-sound assembly and show increased activation in phonologically tuned areas along the dorsal pathway, whereas reading an opaque orthography such as English is thought to rely more on lexically mediated processing associated with increased activation of semantically tuned regions along the ventral pathway. To test if biliterate Hindi/English readers exhibit orthography-specific reading pathways, we used behavioural measures and functional neuroimaging. Reaction times and activation patterns of monolingual English and Hindi readers were compared to two groups of adult biliterates; 14 simultaneous readers who learnt to read both languages at age 5 and 10 sequential readers who learnt Hindi at 5 and English at 10. Simultaneous, but not sequential readers demonstrated relative activation differences of dorsal and ventral areas in the two languages. Similar to native counterparts, simultaneous readers preferentially activated the left inferior temporal gyrus for English and left inferior parietal lobule (L-IPL) for Hindi, whereas, sequential readers showed higher activation along the L-IPL for reading both languages. We suggest that early simultaneous exposure to reading distinct orthographies results in orthography-specific plasticity that persists through adulthood.
Not all bilinguals are the same: A call for more detailed assessments and descriptions of bilingual experiences,
Illiterate to literate: Behavioural and cerebral changes induced by reading acquisition,
The acquisition of literacy transforms the human brain. By reviewing studies of illiterate subjects, we propose specific hypotheses on how the functions of core brain systems are partially reoriented or 'recycled' when learning to read. Literacy acquisition improves early visual processing and reorganizes the ventral occipito-temporal pathway: responses to written characters are increased in the left occipito-temporal sulcus, whereas responses to faces shift towards the right hemisphere. Literacy also modifies phonological coding and strengthens the functional and anatomical link between phonemic and graphemic representations. Literacy acquisition therefore provides a remarkable example of how the brain reorganizes to accommodate a novel cultural skill.
The role of statistical learning in understanding and treating spoken language outcomes in deaf children with cochlear implants,
Purpose: Statistical learning-the ability to learn patterns in environmental input-is increasingly recognized as a foundational mechanism necessary for the successful acquisition of spoken language. Spoken language is a complex, serially presented signal that contains embedded statistical relations among linguistic units, such as phonemes, morphemes, and words, which represent the phonotactic and syntactic rules of language. In this review article, we first review recent work that demonstrates that, in typical language development, individuals who display better nonlinguistic statistical learning abilities also show better performance on different measures of language. We next review research findings that suggest that children who are deaf and use cochlear implants may have difficulties learning sequential input patterns, possibly due to auditory and/or linguistic deprivation early in development, and that the children who show better sequence learning abilities also display improved spoken language outcomes. Finally, we present recent findings suggesting that it may be possible to improve core statistical learning abilities with specialized training and interventions and that such improvements can potentially impact and facilitate the acquisition and processing of spoken language. Method: We conducted a literature search through various online databases including PsychINFO and PubMed, as well as including relevant review articles gleaned from the reference sections of other review articles used in this review. Search terms included various combinations of the following: sequential learning, sequence learning, statistical learning, sequence processing, procedural learning, procedural memory, implicit learning, language, computerized training, working memory training, statistical learning training, deaf, deafness, hearing impairment, hearing impaired, DHH, hard of hearing, cochlear implant(s), hearing aid(s), and auditory deprivation. To keep this review concise and clear, we limited inclusion to the foundational and most recent (2005-2018) relevant studies that explicitly included research or theoretical perspectives on statistical or sequential learning. We here summarize and synthesize the most recent and relevant literature to understanding and treating language delays in children using cochlear implants through the lens of statistical learning. Conclusions: We suggest that understanding how statistical learning contributes to spoken language development is important for understanding some of the difficulties that children who are deaf and use cochlear implants might face and argue that it may be beneficial to develop novel language interventions that focus specifically on improving core foundational statistical learning skills.
Overnight consolidation aids the transfer of statistical knowledge from the medial temporal lobe to the striatum,
Sleep is important for abstraction of the underlying principles (or gist) which bind together conceptually related stimuli, but little is known about the neural correlates of this process. Here, we investigate this issue using overnight sleep monitoring and functional magnetic resonance imaging (fMRI). Participants were exposed to a statistically structured sequence of auditory tones then tested immediately for recognition of short sequences which conformed to the learned statistical pattern. Subsequently, after consolidation over either 30 min or 24h, they performed a delayed test session in which brain activity was monitored with fMRI. Behaviorally, there was greater improvement across 24h than across 30 min, and this was predicted by the amount of slow wave sleep (SWS) obtained. Functionally, we observed weaker parahippocampal responses and stronger striatal responses after sleep. Like the behavioral result, these differences in functional response were predicted by the amount of SWS obtained. Furthermore, connectivity between striatum and parahippocampus was weaker after sleep, whereas connectivity between putamen and planum temporale was stronger. Taken together, these findings suggest that abstraction is associated with a gradual shift from the hippocampal to the striatal memory system and that this may be mediated by SWS.
The role of statistical learning in word reading and spelling development: More questions than answers,
This special issue bundles a set of eight empirical studies and one review article that explore the role of SL mechanisms (both domain-specific and domain-general) in supporting word reading and spelling development, and vice-versa. In this introduction to the special issue, we worked to summarize the extent to which studies support our hypotheses relating SL to reading and spelling development while also pointing out inconsistencies across studies that require us to refine and rethink our hypotheses.
Statistical learning of language: Theory, validity, and predictions of a statistical learning account of language acquisition,
Prefrontal and hippocampal structure predict statistical learning ability in early childhood,
Hierarchical timescales of statistical learning revealed by mismatch negativity to auditory pattern deviations,
Superior learning in synesthetes: Consistent grapheme- color associations facilitate statistical learning,
Music training for the development of speech segmentation,
The role of music training in fostering brain plasticity and developing high cognitive skills, notably linguistic abilities, is of great interest from both a scientific and a societal perspective. Here, we report results of a longitudinal study over 2 years using both behavioral and electrophysiological measures and a test-training-retest procedure to examine the influence of music training on speech segmentation in 8-year-old children. Children were pseudo-randomly assigned to either music or painting training and were tested on their ability to extract meaningless words from a continuous flow of nonsense syllables. While no between-group differences were found before training, both behavioral and electrophysiological measures showed improved speech segmentation skills across testing sessions for the music group only. These results show that music training directly causes facilitation in speech segmentation, thereby pointing to the importance of music for speech perception and more generally for childrens language development. Finally these results have strong implications for promoting the development of music-based remediation strategies for children with language-based learning impairments.
Musical expertise boosts implicit learning of both musical and linguistic structures,
Musical training is known to modify auditory perception and related cortical organization. Here, we show that these modifications may extend to higher cognitive functions and generalize to processing of speech. Previous studies have shown that adults and newborns can segment a continuous stream of linguistic and nonlinguistic stimuli based only on probabilities of occurrence between adjacent syllables or tones. In the present experiment, we used an artificial (sung) language learning design coupled with an electrophysiological approach. While behavioral results were not clear cut in showing an effect of expertise, Event-Related Potentials data showed that musicians learned better than did nonmusicians both musical and linguistic structures of the sung language. We discuss these findings in terms of practice-related changes in auditory processing, stream segmentation, and memory processes.
Domain generality versus modality specificity: The paradox of statistical learning,
Statistical learning (SL) is typically considered to be a domain-general mechanism by which cognitive systems discover the underlying distributional properties of the input. However, recent studies examining whether there are commonalities in the learning of distributional information across different domains or modalities consistently reveal modality and stimulus specificity. Therefore, important questions are how and why a hypothesized domain-general learning mechanism systematically produces such effects. Here, we offer a theoretical framework according to which SL is not a unitary mechanism, but a set of domain-general computational principles that operate in different modalities and, therefore, are subject to the specific constraints characteristic of their respective brain regions. This framework offers testable predictions and we discuss its computational and neurobiological plausibility.
What predicts successful literacy acquisition in a second language?,
In the study reported here, we examined whether success (or failure) in assimilating the structure of a second language can be predicted by general statistical-learning abilities that are nonlinguistic in nature. We employed a visual-statistical-learning (VSL) task, monitoring our participants' implicit learning of the transitional probabilities of visual shapes. A pretest revealed that performance in the VSL task was not correlated with abilities related to a general g factor or working memory. We found that, on average, native speakers of English who more accurately picked up the implicit statistical structure embedded in the continuous stream of shapes better assimilated the Semitic structure of Hebrew words. Languages and their writing systems are characterized by idiosyncratic correlations of form and meaning, and our findings suggest that these correlations are picked up in the process of literacy acquisition, as they are picked up in any other type of learning, for the purpose of making sense of the environment.
Impaired statistical learning in developmental dyslexia,
PURPOSE: Developmental dyslexia (DD) is commonly thought to arise from phonological impairments. However, an emerging perspective is that a more general procedural learning deficit, not specific to phonological processing, may underlie DD. The current study examined if individuals with DD are capable of extracting statistical regularities across sequences of passively experienced speech and nonspeech sounds. Such statistical learning is believed to be domain-general, to draw upon procedural learning systems, and to relate to language outcomes. METHOD: DD and control groups were familiarized with a continuous stream of syllables or sine-wave tones, the ordering of which was defined by high or low transitional probabilities across adjacent stimulus pairs. Participants subsequently judged two 3-stimulus test items with either high or low statistical coherence as being the most similar to the sounds heard during familiarization. RESULTS: As with control participants, the DD group was sensitive to the transitional probability structure of the familiarization materials as evidenced by above-chance performance. However, the performance of participants with DD was significantly poorer than controls across linguistic and nonlinguistic stimuli. In addition, reading-related measures were significantly correlated with statistical learning performance of both speech and nonspeech material. CONCLUSION: Results are discussed in light of procedural learning impairments among participants with DD.
Investigating implicit statistical learning mechanisms through contextual cueing,
Since its inception, the contextual cueing (CC) paradigm has generated considerable interest in various fields of cognitive sciences because it constitutes an elegant approach to understanding how statistical learning (SL) mechanisms can detect contextual regularities during a visual search. In this article we review and discuss five aspects of CC: (i) the implicit nature of learning, (ii) the mechanisms involved in CC, (iii) the mediating factors affecting CC, (iv) the generalization of CC phenomena, and (v) the dissociation between implicit and explicit CC phenomena. The findings suggest that implicit SL is an inherent component of ongoing processing which operates through clustering, associative, and reinforcement processes at various levels of sensory-motor processing, and might result from simple spike-timing-dependent plasticity.
Linking sounds to meanings: Infant statistical learning in a natural language,
The processes of infant word segmentation and infant word learning have largely been studied separately. However, the ease with which potential word forms are segmented from fluent speech seems likely to influence subsequent mappings between words and their referents. To explore this process, we tested the link between the statistical coherence of sequences presented in fluent speech and infants' subsequent use of those sequences as labels for novel objects. Notably, the materials were drawn from a natural language unfamiliar to the infants (Italian). The results of three experiments suggest that there is a close relationship between the statistics of the speech stream and subsequent mapping of labels to referents. Mapping was facilitated when the labels contained high transitional probabilities in the forward and/or backward direction (Experiment 1). When no transitional probability information was available (Experiment 2), or when the internal transitional probabilities of the labels were low in both directions (Experiment 3), infants failed to link the labels to their referents. Word learning appears to be strongly influenced by infants' prior experience with the distribution of sounds that make up words in natural languages.
Developmental dyslexia in Chinese and English populations: Dissociating the effect of dyslexia from language differences,
Common neural basis of motor sequence learning and word recognition and its relation with individual differences in reading skill,
To investigate the neural basis of a common statistical learning mechanism involved in motor sequence learning and decoding, we recorded same participants' brain activation in a serial reaction time (SRT) and word reading task using functional magnetic resonance imaging. In the SRT, a manual response was made depending on the location of a visual cue, and the order of the locations was either fixed or random. In the word reading task, visual words were passively presented. Compared to less skilled readers, more skilled readers showed greater differences in activation in the inferior frontal gyrus pars triangularis (IFGpTr) and the insula between the ordered and random condition in the SRT task and greater activation in those regions in the word reading task. It suggests that extraction of statistically predictable patterns in the IFGpTr and insula contributes to both motor sequence learning and orthographic learning, and therefore predicts individual differences in decoding skill.
Electrophysiological evidence of heterogeneity in visual statistical learning in young children with ASD,
Statistical learning is characterized by detection of regularities in one's environment without an awareness or intention to learn, and it may play a critical role in language and social behavior. Accordingly, in this study we investigated the electrophysiological correlates of visual statistical learning in young children with autism spectrum disorder (ASD) using an event-related potential shape learning paradigm, and we examined the relation between visual statistical learning and cognitive function. Compared to typically developing (TD) controls, the ASD group as a whole showed reduced evidence of learning as defined by N1 (early visual discrimination) and P300 (attention to novelty) components. Upon further analysis, in the ASD group there was a positive correlation between N1 amplitude difference and non-verbal IQ, and a positive correlation between P300 amplitude difference and adaptive social function. Children with ASD and a high non-verbal IQ and high adaptive social function demonstrated a distinctive pattern of learning. This is the first study to identify electrophysiological markers of visual statistical learning in children with ASD. Through this work we have demonstrated heterogeneity in statistical learning in ASD that maps onto non-verbal cognition and adaptive social function.
Exploring the neurodevelopment of visual statistical learning using event-related brain potentials,
The neural correlates of statistical learning in a word segmentation task: An fMRI study,
Functional magnetic resonance imaging (fMRI) was used to assess neural activation as participants learned to segment continuous streams of speech containing syllable sequences varying in their transitional probabilities. Speech streams were presented in four runs, each followed by a behavioral test to measure the extent of learning over time. Behavioral performance indicated that participants could discriminate statistically coherent sequences (words) from less coherent sequences (partwords). Individual rates of learning, defined as the difference in ratings for words and partwords, were used as predictors of neural activation to ask which brain areas showed activity associated with these measures. Results showed significant activity in the pars opercularis and pars triangularis regions of the left inferior frontal gyrus (LIFG). The relationship between these findings and prior work on the neural basis of statistical learning is discussed, and parallels to the frontal/subcortical network involved in other forms of implicit sequence learning are considered.
Individual differences in statistical learning predict children's comprehension of syntax,
Variability in children's language acquisition is likely due to a number of cognitive and social variables. The current study investigated whether individual differences in statistical learning (SL), which has been implicated in language acquisition, independently predicted 6- to 8-year-old's comprehension of syntax. Sixty-eight (N = 68) English-speaking children completed a test of comprehension of four syntactic structures, a test of SL utilizing nonlinguistic visual stimuli, and several additional control measures. The results revealed that SL independently predicted comprehension of two syntactic structures that show considerable variability in this age range: passives and object relative clauses. These data suggest that individual differences in children's capacity for SL are associated with the acquisition of the syntax of natural languages.
Visual statistical learning in infancy: Evidence for a domain general learning mechanism,
The rapidity with which infants come to understand language and events in their surroundings has prompted speculation concerning innate knowledge structures that guide language acquisition and object knowledge. Recently, however, evidence has emerged that by 8 months, infants can extract statistical patterns in auditory input that are based on transitional probabilities defining the sequencing of the input's components (Science 274 (1996) 1926). This finding suggests powerful learning mechanisms that are functional in infancy, and raises questions about the domain generality of such mechanisms. We habituated 2-, 5-, and 8-month-old infants to sequences of discrete visual stimuli whose ordering followed a statistically predictable pattern. The infants subsequently viewed the familiar pattern alternating with a novel sequence of identical stimulus components, and exhibited significantly greater interest in the novel sequence at all ages. These results provide support for the likelihood of domain general statistical learning in infancy, and imply that mechanisms designed to detect structure inherent in the environment may play an important role in cognitive development.
A neostriatal habit learning system in humans,
Amnesic patients and nondemented patients with Parkinson's disease were given a probabilistic classification task in which they learned which of two outcomes would occur on each trial, given the particular combination of cues that appeared. Amnesic patients exhibited normal learning of the task but had severely impaired declarative memory for the training episode. In contrast, patients with Parkinson's disease failed to learn the probabilistic classification task, despite having intact memory for the training episode. This double dissociation shows that the limbic-diencephalic regions damaged in amnesia and the neostriatum damaged in Parkinson's disease support separate and parallel learning systems. In humans, the neostriatum (caudate nucleus and putamen) is essential for the gradual, incremental learning of associations that is characteristic of habit learning. The neostriatum is important not just for motor behavior and motor learning but also for acquiring nonmotor dispositions and tendencies that depend on new associations.
Under the hood of statistical learning: A statistical MMN reflects the magnitude of transitional probabilities in auditory sequences,
Within the framework of statistical learning, many behavioural studies investigated the processing of unpredicted events. However, surprisingly few neurophysiological studies are available on this topic, and no statistical learning experiment has investigated electroencephalographic (EEG) correlates of processing events with different transition probabilities. We carried out an EEG study with a novel variant of the established statistical learning paradigm. Timbres were presented in isochronous sequences of triplets. The first two sounds of all triplets were equiprobable, while the third sound occurred with either low (10%), intermediate (30%), or high (60%) probability. Thus, the occurrence probability of the third item of each triplet (given the first two items) was varied. Compared to high-probability triplet endings, endings with low and intermediate probability elicited an early anterior negativity that had an onset around 100 ms and was maximal at around 180 ms. This effect was larger for events with low than for events with intermediate probability. Our results reveal that, when predictions are based on statistical learning, events that do not match a prediction evoke an early anterior negativity, with the amplitude of this mismatch response being inversely related to the probability of such events. Thus, we report a statistical mismatch negativity (sMMN) that reflects statistical learning of transitional probability distributions that go beyond auditory sensory memory capabilities.
Teaching foreign languages in an era of globalization: Introduction,
Statistical learning across development: Flexible yet constrained,
Much research in the past two decades has documented infants' and adults' ability to extract statistical regularities from auditory input. Importantly, recent research has extended these findings to the visual domain, demonstrating learners' sensitivity to statistical patterns within visual arrays and sequences of shapes. In this review we discuss both auditory and visual statistical learning to elucidate both the generality of and constraints on statistical learning. The review first outlines the major findings of the statistical learning literature with infants, followed by discussion of statistical learning across domains, modalities, and development. The second part of this review considers constraints on statistical learning. The discussion focuses on two categories of constraint: constraints on the types of input over which statistical learning operates and constraints based on the state of the learner. The review concludes with a discussion of possible mechanisms underlying statistical learning.
Early language acquisition: Cracking the speech code,
Neuroimaging of the bilingual brain: Structural brain correlates of listening and speaking in a second language,
Diffusion tensor imaging was used to compare white matter structure between American monolingual and Spanish-English bilingual adults living in the United States. In the bilingual group, relationships between white matter structure and naturalistic immersive experience in listening to and speaking English were additionally explored. White matter structural differences between groups were found to be bilateral and widespread. In the bilingual group, experience in listening to English was more robustly correlated with decreases in radial and mean diffusivity in anterior white matter regions of the left hemisphere, whereas experience in speaking English was more robustly correlated with increases in fractional anisotropy in more posterior left hemisphere white matter regions. The findings suggest that (a) foreign language immersion induces neuroplasticity in the adult brain, (b) the degree of alteration is proportional to language experience, and (c) the modes of immersive language experience have more robust effects on different brain regions and on different structural features.
Foreign- language experience in infancy: Effects of short-term exposure and social interaction on phonetic learning,
Acquisition of Chinese characters: The effects of character properties and individual differences among second language learners,
Statistical learning in specific language impairment: A meta-analysis,
Role of the striatum in incidental learning of sound categories,
Statistical learning of speech sounds is most robust during the period of perceptual attunement,
Although statistical learning has been shown to be a domain-general mechanism, its constraints, such as its interactions with perceptual development, are less well understood and discussed. This study is among the first to investigate the distributional learning of lexical pitch in non-tone-language-learning infants, exploring its interaction with language-specific perceptual attunement during the first 2years after birth. A total of 88 normally developing Dutch infants of 5, 11, and 14months were tested via a distributional learning paradigm and were familiarized on a unimodal or bimodal distribution of high-level versus high-falling tones in Mandarin Chinese. After familiarization, they were tested on a tonal contrast that shared equal distributional information in either modality. At 5months, infants in both conditions discriminated the contrast, whereas 11-month-olds showed discrimination only in the bimodal condition. By 14months, infants failed to discriminate the contrast in either condition. Results indicate interplay between infants' long-term linguistic experience throughout development and short-term distributional learning during the experiment, and they suggest that the influence of tonal distributional learning varies along the perceptual attunement trajectory, such that opportunities for distributional learning effects appear to be constrained in the beginning and at the end of perceptual attunement. The current study contributes to previous research by demonstrating an effect of age on learning from distributional cues.
Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis,
Brain white matter structure and COMT gene are linked to second-language learning in adults,
Auditory and visual sequence learning in humans and monkeys using an artificial grammar learning paradigm,
Language flexibly supports the human ability to communicate using different sensory modalities, such as writing and reading in the visual modality and speaking and listening in the auditory domain. Although it has been argued that nonhuman primate communication abilities are inherently multisensory, direct behavioural comparisons between human and nonhuman primates are scant. Artificial grammar learning (AGL) tasks and statistical learning experiments can be used to emulate ordering relationships between words in a sentence. However, previous comparative work using such paradigms has primarily investigated sequence learning within a single sensory modality. We used an AGL paradigm to evaluate how humans and macaque monkeys learn and respond to identically structured sequences of either auditory or visual stimuli. In the auditory and visual experiments, we found that both species were sensitive to the ordering relationships between elements in the sequences. Moreover, the humans and monkeys produced largely similar response patterns to the visual and auditory sequences, indicating that the sequences are processed in comparable ways across the sensory modalities. These results provide evidence that human sequence processing abilities stem from an evolutionarily conserved capacity that appears to operate comparably across the sensory modalities in both human and nonhuman primates. The findings set the stage for future neurobiological studies to investigate the multisensory nature of these sequencing operations in nonhuman primates and how they compare to related processes in humans.
On-line individual differences in statistical learning predict language processing,
Considerable individual differences in language ability exist among normally developing children and adults. Whereas past research have attributed such differences to variations in verbal working memory or experience with language, we test the hypothesis that individual differences in statistical learning may be associated with differential language performance. We employ a novel paradigm for studying statistical learning on-line, combining a serial-reaction time task with artificial grammar learning. This task offers insights into both the timecourse of and individual differences in statistical learning. Experiment 1 charts the micro-level trajectory for statistical learning of nonadjacent dependencies and provides an on-line index of individual differences therein. In Experiment 2, these differences are then shown to predict variations in participants' on-line processing of long-distance dependencies involving center-embedded relative clauses. The findings suggest that individual differences in the ability to learn from experience through statistical learning may contribute to variations in linguistic performance.
Sensitivity to structure in action sequences: An infant event-related potential study,
Infants are sensitive to structure and patterns within continuous streams of sensory input. This sensitivity relies on statistical learning, the ability to detect predictable regularities in spatial and temporal sequences. Recent evidence has shown that infants can detect statistical regularities in action sequences they observe, but little is known about the neural process that give rise to this ability. In the current experiment, we combined electroencephalography (EEG) with eye-tracking to identify electrophysiological markers that indicate whether 8-11-month-old infants detect violations to learned regularities in action sequences, and to relate these markers to behavioral measures of anticipation during learning. In a learning phase, infants observed an actor performing a sequence featuring two deterministic pairs embedded within an otherwise random sequence. Thus, the first action of each pair was predictive of what would occur next. One of the pairs caused an action-effect, whereas the second did not. In a subsequent test phase, infants observed another sequence that included deviant pairs, violating the previously observed action pairs. Event-related potential (ERP) responses were analyzed and compared between the deviant and the original action pairs. Findings reveal that infants demonstrated a greater Negative central (Nc) ERP response to the deviant actions for the pair that caused the action-effect, which was consistent with their visual anticipations during the learning phase. Findings are discussed in terms of the neural and behavioral processes underlying perception and learning of structured action sequences.
Toddlers' action prediction: Statistical learning of continuous action sequences,
The current eye-tracking study investigated whether toddlers use statistical information to make anticipatory eye movements while observing continuous action sequences. In two conditions, 19-month-old participants watched either a person performing an action sequence (Agent condition) or a self-propelled visual event sequence (Ghost condition). Both sequences featured a statistical structure in which certain action pairs occurred with deterministic transitional probabilities. Toddlers learned the transitional probabilities between the action steps of the deterministic action pairs and made predictive fixations to the location of the next action in the Agent condition but not in the Ghost condition. These findings suggest that young toddlers gain unique information from the statistical structure contained within action sequences and are able to successfully predict upcoming action steps based on this acquired knowledge. Furthermore, predictive gaze behavior was correlated with reproduction of sequential actions following exposure to statistical regularities. This study extends previous developmental work by showing that statistical learning can guide the emergence of anticipatory eye movements during observation of continuous action sequences.
The infant motor system predicts actions based on visual statistical learning,
Motor theories of action prediction propose that our motor system combines prior knowledge with incoming sensory input to predict other people's actions. This prior knowledge can be acquired through observational experience, with statistical learning being one candidate mechanism. But can knowledge learned through observation alone transfer into predictions generated in the motor system? To examine this question, we first trained infants at home with videos of an unfamiliar action sequence featuring statistical regularities. At test, motor activity was measured using EEG and compared during perceptually identical time windows within the sequence that preceded actions which were either predictable (deterministic) or not predictable (random). Findings revealed increased motor activity preceding the deterministic but not the random actions, providing the first evidence that the infant motor system can use knowledge from statistical learning to predict upcoming actions. As such, these results support theories in which the motor system underlies action prediction.
Statistical language learning: Computational, maturational, and linguistic constraints,
Our research on statistical language learning shows that infants, young children, and adults can compute, online and with remarkable speed, how consistently sounds co-occur, how frequently words occur in similar contexts, and the like, and can utilize these statistics to find candidate words in a speech stream, discover grammatical categories, and acquire simple syntactic structure in miniature languages. However, statistical learning is not merely learning the patterns presented in the input. When their input is inconsistent, children sharpen these statistics and produce a more systematic language than the one to which they are exposed. When input languages inconsistently violate tendencies that are widespread in human languages, learners shift these languages to be more aligned with language universals, and children do so much more than adults. These processes explain why children acquire language (and other patterns) more effectively than adults, and also may explain how systematic language structures emerge in communities where usages are varied and inconsistent. Most especially, they suggest that usage-based learning approaches must account for differences between adults and children in how usage properties are acquired, and must also account for substantial changes made by adult and child learners in how input usage properties are represented during learning.
Language experience changes subsequent learning,
What are the effects of experience on subsequent learning? We explored the effects of language-specific word order knowledge on the acquisition of sequential conditional information. Korean and English adults were engaged in a sequence learning task involving three different sets of stimuli: auditory linguistic (nonsense syllables), visual non-linguistic (nonsense shapes), and auditory non-linguistic (pure tones). The forward and backward probabilities between adjacent elements generated two equally probable and orthogonal perceptual parses of the elements, such that any significant preference at test must be due to either general cognitive biases, or prior language-induced biases. We found that language modulated parsing preferences with the linguistic stimuli only. Intriguingly, these preferences are congruent with the dominant word order patterns of each language, as corroborated by corpus analyses, and are driven by probabilistic preferences. Furthermore, although the Korean individuals had received extensive formal explicit training in English and lived in an English-speaking environment, they exhibited statistical learning biases congruent with their native language. Our findings suggest that mechanisms of statistical sequential learning are implicated in language across the lifespan, and experience with language may affect cognitive processes and later learning.
Statistical learning for speech segmentation: Age-related changes and underlying mechanisms,
Statistical learning (SL) is a powerful learning mechanism that supports word segmentation and language acquisition in infants and young adults. However, little is known about how this ability changes over the life span and interacts with age-related cognitive decline. The aims of this study were to: (a) examine the effect of aging on speech segmentation by SL, and (b) explore core mechanisms underlying SL. Across four testing sessions, young, middle-aged, and older adults were exposed to continuous speech streams at two different speech rates, both with and without cognitive load. Learning was assessed using a two-alterative forced-choice task in which words from the stream were pitted against either part-words, which occurred across word boundaries in the stream, or nonwords, which never appeared in the stream. Participants also completed a battery of cognitive tests assessing working memory and executive functions. The results showed that speech segmentation by SL was remarkably resilient to aging, although age effects were visible in the more challenging conditions, namely, when words had to be discriminated from part-words, which required the formation of detailed phonological representations, and when SL was performed under cognitive load. Moreover, an analysis of the cognitive test data indicated that performance against part-words was predicted mostly by memory updating, whereas performance against nonwords was predicted mostly by working memory storage capacity. Taken together, the data show that SL relies on a combination of implicit and explicit skills, and that age effects on SL are likely to be linked to an age-related selective decline in memory updating. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Implicit statistical learning in real-world environments leads to ecologically rational decision making,
Ecological rationality results from matching decision strategies to appropriate environmental structures, but how does the matching happen? We propose that people learn the statistical structure of the environment through observation and use this learned structure to guide ecologically rational behavior. We tested this hypothesis in the context of organic foods. In Study 1, we found that products from healthful food categories are more likely to be organic than products from nonhealthful food categories. In Study 2, we found that consumers' perceptions of the healthfulness and prevalence of organic products in many food categories are accurate. Finally, in Study 3, we found that people perceive organic products as more healthful than nonorganic products when the statistical structure justifies this inference. Our findings suggest that people believe organic foods are more healthful than nonorganic foods and use an organic-food cue to guide their behavior because organic foods are, on average, 30% more healthful.
What artificial grammar learning reveals about the neurobiology of syntax,
Second language experience facilitates statistical learning of novel linguistic materials,
Hearing matters more than seeing: A cross-modality study of statistical learning and reading ability,
The developmental trajectory of children's auditory and visual statistical learning abilities: Modality-based differences in the effect of age,
From shared contexts to syntactic categories: The role of distributional information in learning linguistic form- classes,
A fundamental component of language acquisition involves organizing words into grammatical categories. Previous literature has suggested a number of ways in which this categorization task might be accomplished. Here we ask whether the patterning of the words in a corpus of linguistic input (distributional information) is sufficient, along with a small set of learning biases, to extract these underlying structural categories. In a series of experiments, we show that learners can acquire linguistic form-classes, generalizing from instances of the distributional contexts of individual words in the exposure set to the full range of contexts for all the words in the set. Crucially, we explore how several specific distributional variables enable learners to form a category of lexical items and generalize to novel words, yet also allow for exceptions that maintain lexical specificity. We suggest that learners are sensitive to the contexts of individual words, the overlaps among contexts across words, the non-overlap of contexts (or systematic gaps in information), and the size of the exposure set. We also ask how learners determine the category membership of a new word for which there is very sparse contextual information. We find that, when there are strong category cues and robust category learning of other words, adults readily generalize the distributional properties of the learned category to a new word that shares just one context with the other category members. However, as the distributional cues regarding the category become sparser and contain more consistent gaps, learners show more conservatism in generalizing distributional properties to the novel word. Taken together, these results show that learners are highly systematic in their use of the distributional properties of the input corpus, using them in a principled way to determine when to generalize and when to preserve lexical specificity.
Enhanced visual statistical learning in adults with autism,
OBJECTIVE: Individuals with autism spectrum disorder (ASD) are often characterized as having social engagement and language deficiencies, but a sparing of visuospatial processing and short-term memory (STM), with some evidence of supranormal levels of performance in these domains. The present study expanded on this evidence by investigating the observational learning of visuospatial concepts from patterns of covariation across multiple exemplars. METHOD: Child and adult participants with ASD, and age-matched control participants, viewed multishape arrays composed from a random combination of pairs of shapes that were each positioned in a fixed spatial arrangement. RESULTS: After this passive exposure phase, a posttest revealed that all participant groups could discriminate pairs of shapes with high covariation from randomly paired shapes with low covariation. Moreover, learning these shape-pairs with high covariation was superior in adults with ASD than in age-matched controls, whereas performance in children with ASD was no different than controls. CONCLUSIONS: These results extend previous observations of visuospatial enhancement in ASD into the domain of learning, and suggest that enhanced visual statistical learning may have arisen from a sustained bias to attend to local details in complex arrays of visual features.
Right hemisphere dominance in visual statistical learning,
Several studies report a right hemisphere advantage for visuospatial integration and a left hemisphere advantage for inferring conceptual knowledge from patterns of covariation. The present study examined hemispheric asymmetry in the implicit learning of new visual feature combinations. A split-brain patient and normal control participants viewed multishape scenes presented in either the right or the left visual fields. Unbeknownst to the participants, the scenes were composed from a random combination of fixed pairs of shapes. Subsequent testing found that control participants could discriminate fixed-pair shapes from randomly combined shapes when presented in either visual field. The split-brain patient performed at chance except when both the practice and the test displays were presented in the left visual field (right hemisphere). These results suggest that the statistical learning of new visual features is dominated by visuospatial processing in the right hemisphere and provide a prediction about how fMRI activation patterns might change during unsupervised statistical learning.
Statistical learning as a window into developmental disabilities,
Until recently, most behavioral studies of children with intellectual and developmental disabilities (IDD) have used standardized assessments as a means to probe etiology and to characterize phenotypes. Over the past decade, however, tasks originally developed to investigate learning processes in typical development have been brought to bear on developmental processes in children with IDD.This brief review will focus on one learning process in particular-statistical learning-and will provide an overview of what has been learned thus far from studies using statistical learning tasks with different groups of children with IDD conditions. While a full picture is not yet available, results to date suggest that studies of learning are both feasible and informative about learning processes that may differ across diagnostic groups, particularly as they relate to language acquisition.More generally, studies focused on learning processes may be highly informative about different developmental trajectories both across groups and within groups of children.
Statistical learning by 8-month-old infants,
Learners rely on a combination of experience-independent and experience-dependent mechanisms to extract information from the environment. Language acquisition involves both types of mechanisms, but most theorists emphasize the relative importance of experience-independent mechanisms. The present study shows that a fundamental task of language acquisition, segmentation of words from fluent speech, can be accomplished by 8-month-old infants based solely on the statistical relationships between neighboring speech sounds. Moreover, this word segmentation was based on statistical learning from only 2 minutes of exposure, suggesting that infants have access to a powerful mechanism for the computation of statistical properties of the language input.
Infant statistical learning,
Perception involves making sense of a dynamic, multimodal environment. In the absence of mechanisms capable of exploiting the statistical patterns in the natural world, infants would face an insurmountable computational problem. Infant statistical learning mechanisms facilitate the detection of structure. These abilities allow the infant to compute across elements in their environmental input, extracting patterns for further processing and subsequent learning. In this selective review, we summarize findings that show that statistical learning is both a broad and flexible mechanism (supporting learning from different modalities across many different content areas) and input specific (shifting computations depending on the type of input and goal of learning). We suggest that statistical learning not only provides a framework for studying language development and object knowledge in constrained laboratory settings, but also allows researchers to tackle real-world problems, such as multilingualism, the role of ever-changing learning environments, and differential developmental trajectories.
Incidental language learning: Listening (and learning) out of the corner of your ear,
Constraints on statistical learning across species,
Both human and nonhuman organisms are sensitive to statistical regularities in sensory inputs that support functions including communication, visual processing, and sequence learning. One of the issues faced by comparative research in this field is the lack of a comprehensive theory to explain the relevance of statistical learning across distinct ecological niches. In the current review we interpret cross-species research on statistical learning based on the perceptual and cognitive mechanisms that characterize the human and nonhuman models under investigation. Considering statistical learning as an essential part of the cognitive architecture of an animal will help to uncover the potential ecological functions of this powerful learning process.
Reading and the neurocognitive bases of statistical learning,
The necessity of the medial temporal lobe for statistical learning,
The sensory input that we experience is highly patterned, and we are experts at detecting these regularities. Although the extraction of such regularities, or statistical learning (SL), is typically viewed as a cortical process, recent studies have implicated the medial temporal lobe (MTL), including the hippocampus. These studies have employed fMRI, leaving open the possibility that the MTL is involved but not necessary for SL. Here, we examined this issue in a case study of LSJ, a patient with complete bilateral hippocampal loss and broader MTL damage. In Experiments 1 and 2, LSJ and matched control participants were passively exposed to a continuous sequence of shapes, syllables, scenes, or tones containing temporal regularities in the co-occurrence of items. In a subsequent test phase, the control groups exhibited reliable SL in all conditions, successfully discriminating regularities from recombinations of the same items into novel foil sequences. LSJ, however, exhibited no SL, failing to discriminate regularities from foils. Experiment 3 ruled out more general explanations for this failure, such as inattention during exposure or difficulty following test instructions, by showing that LSJ could discriminate which individual items had been exposed. These findings provide converging support for the importance of the MTL in extracting temporal regularities.
Aging and the statistical learning of grammatical form classes,
Language learners must place unfamiliar words into categories, often with few explicit indicators about when and how that word can be used grammatically. Reeder, Newport, and Aslin (2013) showed that college students can learn grammatical form classes from an artificial language by relying solely on distributional information (i.e., contextual cues in the input). Here, 2 experiments revealed that healthy older adults also show such statistical learning, though they are poorer than young at distinguishing grammatical from ungrammatical strings. This finding expands knowledge of which aspects of learning vary with aging, with potential implications for second language learning in late adulthood. (PsycINFO Database Record
Statistical learning is not age-invariant during childhood: Performance improves with age across modality,
Humans are capable of extracting recurring patterns from their environment via statistical learning (SL), an ability thought to play an important role in language learning and learning more generally. While much work has examined statistical learning in infants and adults, less work has looked at the developmental trajectory of SL during childhood to see whether it is fully developed in infancy or improves with age, like many other cognitive abilities. A recent study showed modality-based differences in the effect of age during childhood: While visual SL improved with age, auditory SL did not. This finding was taken as evidence for modality-based differences in SL. However, since that study used auditory linguistic stimuli (syllables), the differential effect of age may have been driven by stimulus type (linguistic vs. non-linguistic) rather than modality. Here, we ask whether age will affect performance similarly in the two modalities when non-linguistic auditory stimuli are used (familiar sounds instead of syllables). We conduct a large-scale study of children's performance on visual and non-linguistic auditory SL during childhood (ages 5-12 years). The results show a similar effect of age in both modalities: Unlike previous findings, both visual and non-linguistic auditory SL improved with age. These findings highlight the stimuli-sensitive nature of SL and suggest that modality-based differences may be stimuli-dependent, and that age-invariance may be limited to linguistic stimuli.
Measuring individual differences in statistical learning: Current pitfalls and possible solutions,
Most research in statistical learning (SL) has focused on the mean success rates of participants in detecting statistical contingencies at a group level. In recent years, however, researchers have shown increased interest in individual abilities in SL, either to predict other cognitive capacities or as a tool for understanding the mechanism underlying SL. Most if not all of this research enterprise has employed SL tasks that were originally designed for group-level studies. We argue that from an individual difference perspective, such tasks are psychometrically weak, and sometimes even flawed. In particular, the existing SL tasks have three major shortcomings: (1) the number of trials in the test phase is often too small (or, there is extensive repetition of the same targets throughout the test); (2) a large proportion of the sample performs at chance level, so that most of the data points reflect noise; and (3) the test items following familiarization are all of the same type and an identical level of difficulty. These factors lead to high measurement error, inevitably resulting in low reliability, and thereby doubtful validity. Here we present a novel method specifically designed for the measurement of individual differences in visual SL. The novel task we offer displays substantially superior psychometric properties. We report data regarding the reliability of the task and discuss the importance of the implementation of such tasks in future research.
Statistical learning as an individual ability: Theoretical perspectives and empirical evidence,
Although the power of statistical learning (SL) in explaining a wide range of linguistic functions is gaining increasing support, relatively little research has focused on this theoretical construct from the perspective of individual differences. However, to be able to reliably link individual differences in a given ability such as language learning to individual differences in SL, three critical theoretical questions should be posed: Is SL a componential or unified ability? Is it nested within other general cognitive abilities? Is it a stable capacity of an individual? Following an initial mapping sentence outlining the possible dimensions of SL, we employed a battery of SL tasks in the visual and auditory modalities, using verbal and non-verbal stimuli, with adjacent and non-adjacent contingencies. SL tasks were administered along with general cognitive tasks in a within-subject design at two time points to explore our theoretical questions. We found that SL, as measured by some tasks, is a stable and reliable capacity of an individual. Moreover, we found SL to be independent of general cognitive abilities such as intelligence or working memory. However, SL is not a unified capacity, so that individual sensitivity to conditional probabilities is not uniform across modalities and stimuli.
Biological abnormality of impaired reading is constrained by culture,
Developmental dyslexia is characterized by a severe reading problem in people who have normal intelligence and schooling. Impaired reading of alphabetic scripts is associated with dysfunction of left temporoparietal brain regions. These regions perform phonemic analysis and conversion of written symbols to phonological units of speech (grapheme-to-phoneme conversion); two central cognitive processes that mediate reading acquisition. Furthermore, it has been assumed that, in contrast to cultural diversities, dyslexia in different languages has a universal biological origin. Here we show using functional magnetic resonance imaging with reading-impaired Chinese children and associated controls, that functional disruption of the left middle frontal gyrus is associated with impaired reading of the Chinese language (a logographic rather than alphabetic writing system). Reading impairment in Chinese is manifested by two deficits: one relating to the conversion of graphic form (orthography) to syllable, and the other concerning orthography-to-semantics mapping. Both of these processes are critically mediated by the left middle frontal gyrus, which functions as a centre for fluent Chinese reading that coordinates and integrates various information about written characters in verbal and spatial working memory. This finding provides an insight into the fundamental pathophysiology of dyslexia by suggesting that rather than having a universal origin, the biological abnormality of impaired reading is dependent on culture.
When learning goes beyond statistics: Infants represent visual sequences in terms of chunks,
Much research has documented infants' sensitivity to statistical regularities in auditory and visual inputs, however the manner in which infants process and represent statistically defined information remains unclear. Two types of models have been proposed to account for this sensitivity: statistical models, which posit that learners represent statistical relations between elements in the input; and chunking models, which posit that learners represent statistically-coherent units of information from the input. Here, we evaluated the fit of these two types of models to behavioral data that we obtained from 8-month-old infants across four visual sequence-learning experiments. Experiments examined infants' representations of two types of structures about which statistical and chunking models make contrasting predictions: illusory sequences (Experiment 1) and embedded sequences (Experiments 2-4). In all four experiments, infants discriminated between high probability sequences and low probability part-sequences, providing strong evidence of learning. Critically, infants also discriminated between high probability sequences and statistically-matched sequences (illusory sequences in Experiment 1, embedded sequences in Experiments 2-3), suggesting that infants learned coherent chunks of elements. Experiment 4 examined the temporal nature of chunking, and demonstrated that the fate of embedded chunks depends on amount of exposure. These studies contribute important new data on infants' visual statistical learning ability, and suggest that the representations that result from infants' visual statistical learning are best captured by chunking models.
Statistical learning is related to early literacy- related skills,
It has been demonstrated that statistical learning, or the ability to use statistical information to learn the structure of one's environment, plays a role in young children's acquisition of linguistic knowledge. Although most research on statistical learning has focused on language acquisition processes, such as the segmentation of words from fluent speech and the learning of syntactic structure, some recent studies have explored the extent to which individual differences in statistical learning are related to literacy-relevant knowledge and skills. The present study extends on this literature by investigating the relations between two measures of statistical learning and multiple measures of skills that are critical to the development of literacy-oral language, vocabulary knowledge, and phonological processing-within a single model. Our sample included a total of 553 typically developing children from prekindergarten through second grade. Structural equation modeling revealed that statistical learning accounted for a unique portion of the variance in these literacy-related skills. Practical implications for instruction and assessment are discussed.
The medial temporal lobe,
The extraction and integration framework: A two-process account of statistical learning,
The term statistical learning in infancy research originally referred to sensitivity to transitional probabilities. Subsequent research has demonstrated that statistical learning contributes to infant development in a wide array of domains. The range of statistical learning phenomena necessitates a broader view of the processes underlying statistical learning. Learners are sensitive to a much wider range of statistical information than the conditional relations indexed by transitional probabilities, including distributional and cue-based statistics. We propose a novel framework that unifies learning about all of these kinds of statistical structure. From our perspective, learning about conditional relations outputs discrete representations (such as words). Integration across these discrete representations yields sensitivity to cues and distributional information. To achieve sensitivity to all of these kinds of statistical structure, our framework combines processes that extract segments of the input with processes that compare across these extracted items. In this framework, the items extracted from the input serve as exemplars in long-term memory. The similarity structure of those exemplars in long-term memory leads to the discovery of cues and categorical structure, which guides subsequent extraction. The extraction and integration framework provides a way to explain sensitivity to both conditional statistical structure (such as transitional probabilities) and distributional statistical structure (such as item frequency and variability), and also a framework for thinking about how these different aspects of statistical learning influence each other.
Early developing syntactic knowledge influences sequential statistical learning in infancy,
Adults' linguistic background influences their sequential statistical learning of an artificial language characterized by conflicting forward-going and backward-going transitional probabilities. English-speaking adults favor backward-going transitional probabilities, consistent with the head-initial structure of English. Korean-speaking adults favor forward-going transitional probabilities, consistent with the head-final structure of Korean. These experiments assess when infants develop this directional bias. In the experiments, 7-month-old infants showed no bias for forward-going or backward-going regularities. By 13months, however, English-learning infants favored backward-going transitional probabilities over forward-going transitional probabilities, consistent with English-speaking adults. This indicates that statistical learning rapidly adapts to the predominant syntactic structure of the native language. Such adaptation may facilitate subsequent learning by highlighting statistical structures that are likely to be informative in the native linguistic environment.
Statistical learning and spelling: Older prephonological spellers produce more wordlike spellings than younger prephonological spellers,
The authors analyzed the spellings of 179 U.S. children (age = 3 years, 2 months-5 years, 6 months) who were prephonological spellers, in that they wrote using letters that did not reflect the phonemes in the target items. Supporting the idea that children use their statistical learning skills to learn about the outer form of writing before they begin to spell phonologically, older prephonological spellers showed more knowledge about English letter patterns than did younger prephonological spellers. The written productions of older prephonological spellers were rated by adults as more similar to English words than were the productions of younger prephonological spellers. The older children s spellings were also more wordlike on several objective measures, including length, variability of letters within words, and digram frequency.
Statistical learning of a tonal language: The influence of bilingualism and previous linguistic experience,
While research shows that adults attend to both segmental and suprasegmental regularities in speech, including syllabic transitional probabilities as well as stress and intonational patterns, little is known about how statistical learning operates given input from tonal languages. In the current study, we designed an artificial tone language to address several questions: can adults track regularities in a tonal language? Is learning enhanced by previous exposure to tone-marking languages? Does bilingualism affect learning in this task? To address these questions, we contrasted the performance of English monolingual adults (Experiment 1), Mandarin monolingual and Mandarin-English bilingual adults (Experiment 2), and non-tonal bilingual adults (Experiment 3) in a statistical learning task using an artificial tone language. The pattern of results suggests that while prior exposure to tonal languages did not lead to significant improvements in performance, bilingual experience did enhance learning outcomes. This study represents the first demonstration of statistical learning of an artificial tone language and suggests a complex interplay between prior language experience and subsequent language learning.
Neuroimaging evidence for sensitivity to orthography-to-phonology conversion in native readers and foreign learners of Chinese,
Musical intervention enhances infants' neural processing of temporal structure in music and speech,
传统观点认为统计学习过程中主要有两个外在特征: 一是学习者在学习过程中没有接受外部指导, 在刺激熟悉阶段学习者不会被告知要学习的内容, 二是学习者对学习到的统计知识没有外显意识, 从再认测试结果可以推测其是否掌握了刺激的统计规律, 但是学习者即使掌握了统计规律也不能将其外显报告出来.研究者常把统计学习和内隐学习联系在一起, 内隐学习是指个体在没有外部指导下学习且对所学的东西没有外显意识的一种学习, 最早由
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