汉语声调水平映射规则的内隐学习及其长度迁移效应

内隐学习领域关注的重要问题是被试能够习得何种结构及其相应的学习机制。远距离规则的研究为澄清这一问题提供了新的视角。现有研究已证实被试能够内隐地习得并迁移固定长度的远距离规则。按照内隐学习抽象性的观点,如果被试习得的是远距离的抽象规则本身,那么迁移也同时会发生在不同长度的材料上。因此,研究以独特的汉语声调水平映射规则为材料,通过对表面特征与底层规则之间的分离操作,探讨声调水平映射规则的内隐习得和长度迁移,结果表明被试不仅能够习得这一规则,还能够将该规则灵活迁移到不同长度的材料上,进一步为内隐学习的抽象性特点和无限性的学习机制提供强有力的新证据。     

高低情感开放性者概率内隐序列学习进程差异

大五人格情感开放性子量表(openness/feeling)能否预测内隐序列学习的问题存在争议。本研究采用概率性内隐序列学习范式, 比较高低情感开放性者在各反应刺激间隔(response stimulus interval, 即RSI)的差异。发现：(1) RSI = 0 ms和250 ms, 高分组在转移组块后习得高概率序列, RSI = 500 ms及以上在其之前习得; 所有RSI点低分组都在其之前习得。每个RSI点只有高分组习得低概率序列。证明随RSI增加两者内隐进程有本质差异, openness/feeling子量表可预测内隐序列学习个体差异。(2)低概率序列可作为测量概率性内隐序列学习及个体差异的新指标, 经典转移组块、再认、生成任务的测量效果却十分有限。     

智障儿童和正常儿童外显记忆与内隐记忆的比较研究

本实验采取加工分离程序(PDP)对38名弱智儿童的外显记忆与内隐记忆进行研究,并与47名正常儿童进行比较,结果认为:(1)正常儿童外显记忆明显优于弱智儿童,但在内隐记忆方面,正常儿童与弱智儿童没有显著差异;(2)本实验中,年龄对内隐记忆和外显记忆均没有影响。研究结果对弱智儿童的教育方面有启示作用;另外,PDP实验由于其本身的复杂性,在对特殊人群进行施测时,需要特别注意。     

Hyperspecificity in visual implicit learning: learning of spatial layout is contingent on item identity

Humans conduct visual search faster when the same display is presented for a 2nd time, showing implicit learning of repeated displays. This study examines whether learning of a spatial layout transfers to other layouts that are occupied by items of new shapes or colors. The authors show that spatial context learning is sometimes contingent on item identity. For example, when the training session included some trials with black items and other trials with white items, learning of the spatial layout became specific to the trained color--no transfer was seen when items were in a new color during testing. However, when the training session included only trials in black (or white), learning transferred to displays with a new color. Similar results held when items changed shapes after training. The authors conclude that implicit visual learning is sensitive to trial context and that spatial context learning can be identity contingent.     

First demonstration of effective spatial training for near transfer to spatial performance and far transfer to a range of mathematics skills at 8 years

There is evidence that spatial thinking is malleable, and that spatial and mathematical skills are associated (Mix et al. [2016] Journal of Experimental Psychology: General, 145, 1206; Mix et al. [2017] Journal of Cognition and Development, 18, 465; Uttal et al. [2013] Psychological Bulletin, 139, 352). However, few studies have investigated transfer of spatial training gains to mathematics outcomes in children, and no known studies have compared different modes of spatial instruction (explicit vs. implicit instruction). Based on a sample of 250 participants, this study compared the effectiveness of explicit and implicit spatial instruction in eliciting near transfer (to the specific spatial skills trained), intermediate transfer (to untrained spatial skills) and far transfer (to mathematics domains) at age 8. Spatial scaling and mental rotation skills were chosen as training targets as previous studies have found, and proposed explanations for, associations between these skills and mathematics in children of this age (Journal of Experimental Psychology: General, 145, 2016 and 1206). In this study, spatial training led to near, intermediate and far transfer of gains. Mental visualization and proportional reasoning were proposed to explain far transfer from mental rotation and spatial scaling skills respectively. For most outcomes, except for geometry, there was no difference in the effectiveness of implicit (practice with feedback) compared to explicit instruction (instructional videos). From a theoretical perspective, the study identified a specific causal effect of spatial skills on mathematics skills in children. Practically, the results also highlight the potential of instructional videos as a method of introducing spatial thinking into the classroom.     

Implicit serial learning: Questions inspired by Hebb (1961)

Implicit serial learning occurs when indirect measures such as transfer reveal learning of a repeating sequence even when subjects are not informed ofthe repeating sequence, are not asked to learn it, and do not become of aware of it. This phenomenon is reminiscent of an experiment by Hebb(1961), who studied the repetition of sequences in a serial recall task. Two experiments investigated the relation between implicit serial learning and ideas about learning forwarded by Hebb and others who used his method. The experiments showed that implicit serial learning occurs even when the repeating sequence is intermixed with randomly generated sequences instead of being repeated continuously, that the organization of the sequence into regularly or irregularly grouped subsequences determines the extent of learning, and that the repetition effect observed does not depend on subjects' ability to recognize the repetition.     

Implicit transfer of spatial structure in visuomotor sequence learning

Implicit learning and transfer in sequence learning are essential in daily life. Here, we investigated the implicit transfer of visuomotor sequences following a spatial transformation. In the two experiments, participants used trial and error to learn a sequence consisting of several button presses, known as the m × n task (Hikosaka et al., 1995). After this learning session, participants learned another sequence in which the button configuration was spatially transformed in one of the following ways: mirrored, rotated, and random arrangement. Our results showed that even when participants were unaware of the transformation rules, accuracy of transfer session in the mirrored and rotated groups was higher than that in the random group (i.e., implicit transfer occurred). Both those who noticed the transformation rules and those who did not (i.e., explicit and implicit transfer instances, respectively) showed faster performance in the mirrored sequences than in the rotated sequences. Taken together, the present results suggest that people can use their implicit visuomotor knowledge to spatially transform sequences and that implicit transfers are modulated by a transformation cost, similar to that in explicit transfer.     

Implicit motor sequence learning is represented in response locations

Previous work (Willingham, 1999) has indicated that implicit motor sequence learning is not primarily perceptual; that is, what is learned is not a sequence of stimuli. Still other work has indicated that implicit motor sequence learning is not specific to particular muscle groups or effectors. In the present work, we tested whether implicit motor sequence learning would be represented as a sequence of response locations. In Experiment 1, learning showed very poor transfer when the response locations were changed, even though the stimulus positions were unchanged. In Experiment 2, participants switched their hand positions at transfer, so that one group of participants pushed the same sequence of keys but used a different sequence of finger movements to do so, whereas another group pushed a different sequence of keys but used the same sequence of finger movements used at training. Knowledge of the sequence was shown at transfer only if the sequence of response locations was maintained, not the sequence of finger movements.     

The Relation Between Implicit and Explicit Learning: Evidence for Parallel Development

Much research has focused on the separability of implicit and explicit learning, but less has focused on how they might interact. A recent model suggests that in the motor-skill domain, explicit knowledge can guide movement, and the implicit system learns in parallel, based on these movements. Functional imaging studies do not support that contention, however; they indicate that learning is exclusively implicit or explicit. In the experiment reported here, participants learned a motor sequencing task either implicitly or explicitly. At transfer, most of the stimuli were random, but the sequence occasionally appeared; thus, it was not obvious that explicit knowledge could be applied to the task. Nevertheless, participants with explicit training showed sequence knowledge equivalent to those with implicit training, implying that implicit knowledge had been acquired in parallel with explicit knowledge. This result has implications for the development of automaticity and of motor-skill learning.     

序列位置内隐学习产生机制的实验研究

内隐学习是当今认知和学习领域继内隐记忆之后又一重要的研究课题。该研究利用序列反应时研究程式,通过两个实验,对序列位置内隐学习产生的机制进行了探讨。结果表明：（１）在序列反应时任务程式中,随着反应一刺激间隔的延长,序列位置内隐学习的学习量逐渐减少;（２）异形同模式迁移组和异形异模式迁移组被试间内隐学习量无显著差异,被试未能内隐地习得抽象的序列模式。说明序列位置内隐学习产生的基础是水平联结,在该实验条件下没有发现垂直联结存在的证据。     

Effects of sleep loss, time of day, and extended mental work on implicit and explicit learning of sequences

Tacit knowledge is part of many professional skills and can be studied experimentally with implicit-learning paradigms. The authors explored the effects of 2 different stressors, loss of sleep and mental fatigue, on implicit learning in a serial-response time (RT) task. In the 1st experiment, 1 night of sleep deprivation was shown to impair implicit but not explicit sequence learning. In the 2nd experiment, no impairment of both types of sequence learning was found after 1.5 hr of mental work. Serial-RT performance, in contrast, suffered from both stressors. These findings suggest that sleep deprivation induces specific risks for automatic, skill-based behavior that are not present in consciously controlled performance.     

Position-item associations play a role in the acquisition of order knowledge in an implicit serial reaction time task

Knowledge of sequential regularities plays a key role in forms of explicit and implicit memory, such as working memory and motor skills. Despite important advances in the study of sequence knowledge in the past century, the theoretical development of implicit and explicit memory has occurred separately. Unlike the literature on implicit sequence learning, the explicit learning literature differentiates between 2 forms of representation of serial structure, chaining (C is the item following B in the sequence A-B-C-D) and ordinal position knowledge (C is the 3rd item). In 3 experiments, we demonstrate that these 2 forms of sequence knowledge can be acquired in implicit sequence learning. In Experiment 1, 2 trained sequences were recombined at transfer such that the strength of (a) associations between serial positions and sequence elements as well as (b) associations between successive sequence elements could be estimated. In Experiment 2, we compared sequence elements placed at the trained versus untrained serial position. Experiment 3 reduced cues that can be used to determine the start of a sequence within the stream of trials. Our results suggest that the discussion held in explicit memory research about different forms of representation of sequences knowledge also is relevant for implicit sequence learning.     

Is There Cross-format Transfer in Implicit Invariance Learning?

Three experiments investigated cross-form transfer in the invariance learning paradigm introduced by McGeorge and Burton (1990). The results suggest that the transfer observed by McGeorge and Burton depended on subjects' ability to use a response strategy discovered by Wright and Burton (1995). When that strategy was denied to subjects (Experiments 1 and 2), no cross-form transfer was observed; when the strategy was made available (Experiment 3), cross-form transfer re-emerged. These results suggest that this form of learning, like many other forms of implicit learning and memory, is hyperspecific.     

Implicit learning differences: a question of developmental level?

A. S. Reber's (1992) proposition that the implicit learning system should demonstrate invariance of intellectual level (IQ) was examined by comparing 20 children with intellectual disability (mean mental age [MA] = approximately 5.8 years) with 20 intellectually gifted children (mean MA = approximately 12.4 years) of similar chronological age (CA; approximately 9.5 years). Implicit learning was assessed using a task involving covariation of 2 incidental cues. Explicit learning was assessed using a task of similar logical structure. Contrary to the IQ-invariance proposition, implicit learning as well as explicit learning varied with intellectual level. A secondary aim was to distinguish the contributions of CA, IQ, and MA to implicit learning. This was done by combining the samples of children in the present study with 2 samples of younger and older children of average ability from a study by M. Maybery, M. Taylor, and A. O'Brien-Malone (1995). Analyses showed that MA is critical to implicit learning.     

内隐序列学习与中央执行功能的关系

内隐序列学习与一般认知的关系一直处于争议之中。近年来,越来越多的研究显示内隐序列学习与工作记忆（尤其是中央执行功能）存在显著关联。基于此,本研究通过两个实验来探测两者的相关及机制。实验1从行为与脑电两个角度探讨经典位置序列学习与中央执行功能的相关,发现经典位置序列学习的内隐习得量与中央执行功能的抑制、刷新功能的强度呈负相关,与转换功能没有显著相关,脑电结果也支持了这一结论。实验2在内隐序列学习中加入认知冲突来增加中央执行功能的负荷。结果发现在高抑制功能负荷任务条件下,内隐习得量与抑制功能强度的相关性发生了反转,进一步证明内隐序列学习与中央执行功能的抑制子成分在脑功能上的关系：不同条件下呈现竞争、协作等不同状态。     

内隐序列学习中转移组块的数量和位置效应

表征质量理论对意识增长持渐进观点,忽视新异刺激对意识的突变式影响;新异刺激理论强调意识突变,忽视新异刺激本身的表征质量增长。本研究采用经典确定性内隐序列学习范式,将转移组块作为新异刺激,操控其数量和位置,探究新异刺激如何通过表征质量来影响内隐学习和意识。结果表明：（1）数量效应显著,即两个转移组块更能促进内隐学习量,说明新异刺激本身需要足够的表征质量才能发挥“意外事件”的作用。（2）在位置效应上,两个转移组块且靠前的设置更能提高受控意识,表明第一个新异刺激必须出现在原序列初级表征质量阶段,才能使被试对新异刺激和原序列进行对比,加之第二个新异刺激的与之呼应,促进原序列意识增加。     

儿童对空间位置协变的外显学习和内隐学习的比较研究

内隐学习是无意识地获得关于刺激环境的复杂知识的过程,是不同于外显学习模式的另一种学习模式。空间位置协变是一种复杂的关系,能被人们加工、储存、运用却不被意识。本研究采用反应时和预估正确率两个指标,通过实验比较了儿童对空间位置协变的外显学习和内隐学习的效果。结果表明,儿童在面临像空间位置协变这样的复杂任务时有内隐学习模式出现,并且内隐学习的效果优于外显学习。     

Sequence‐specific procedural learning deficits in children with specific language impairment

This study tested the procedural deficit hypothesis of specific language impairment (SLI) by comparing children's performance in two motor procedural learning tasks and an implicit verbal sequence learning task. Participants were 7‐ to 11‐year‐old children with SLI (n = 48), typically developing age‐matched children (n = 20) and younger typically developing children matched for receptive grammar (n = 28). In a serial reaction time task, the children with SLI performed at the same level as the grammar‐matched children, but poorer than age‐matched controls in learning motor sequences. When tested with a motor procedural learning task that did not involve learning sequential relationships between discrete elements (i.e. pursuit rotor), the children with SLI performed comparably with age‐matched children and better than younger grammar‐matched controls. In addition, poor implicit learning of word sequences in a verbal memory task (the Hebb effect) was found in the children with SLI. Together, these findings suggest that SLI might be characterized by deficits in learning sequence‐specific information, rather than generally weak procedural learning.     

Intact implicit learning in autism spectrum conditions

Individuals with autism spectrum condition (ASC) have diagnostic impairments in skills that are associated with an implicit acquisition; however, it is not clear whether ASC individuals show specific implicit learning deficits. We compared ASC and typically developing (TD) individuals matched for IQ on five learning tasks: four implicit learning tasks—contextual cueing, serial reaction time, artificial grammar learning, and probabilistic classification learning tasks—that used procedures expressly designed to minimize the use of explicit strategies, and one comparison explicit learning task, paired associates learning. We found implicit learning to be intact in ASC. Beyond no evidence of differences, there was evidence of statistical equivalence between the groups on all the implicit learning tasks. This was not a consequence of compensation by explicit learning ability or IQ. Furthermore, there was no evidence to relate implicit learning to ASC symptomatology. We conclude that implicit mechanisms are preserved in ASC and propose that it is disruption by other atypical processes that impact negatively on the development of skills associated with an implicit acquisition.     

Application of deep transfer learning for automated brain abnormality classification using MR images

Magnetic resonance imaging (MRI) is the most common imaging technique used to detect abnormal brain tumors. Traditionally, MRI images are analyzed manually by radiologists to detect the abnormal conditions in the brain. Manual interpretation of huge volume of images is time consuming and difficult. Hence, computer-based detection helps in accurate and fast diagnosis. In this study, we proposed an approach that uses deep transfer learning to automatically classify normal and abnormal brain MR images. Convolutional neural network (CNN) based ResNet34 model is used as a deep learning model. We have used current deep learning techniques such as data augmentation, optimal learning rate finder and fine-tuning to train the model. The proposed model achieved 5-fold classification accuracy of 100% on 613 MR images. Our developed system is ready to test on huge database and can assist the radiologists in their daily screening of MR images.