内隐序列学习与注意负荷关系的实验研究

采用2(注意负荷:高、低)单因素被试内实验设计,以18名在校大学生为被试,运用行为实验及事件相关电位技术,对内隐序列学习是否需要注意负荷的参与进行实验研究。结果发现:(1)在高、低注意负荷条件下都出现了内隐序列学习效应;(2)高注意负荷序列探测刺激诱发的P1、N1波幅显著大于低注意负荷序列探测刺激诱发的,表明高注意负荷条件下需要更多的注意;(3)高、低注意负荷序列内隐序列学习量差异不显著,表明内隐序列学习不受注意负荷影响。     

Manipulating attentional load in sequence learning through random number generation

Implicit learning is often assumed to be an effortless process. However, some artificial grammar learning and sequence learning studies using dual tasks seem to suggest that attention is essential for implicit learning to occur. This discrepancy probably results from the specific type of secondary task that is used. Different secondary tasks may engage attentional resources differently and therefore may bias performance on the primary task in different ways. Here, we used a random number generation (RNG) task, which may allow for a closer monitoring of a participant's engagement in a secondary task than the popular secondary task in sequence learning studies: tone counting (TC). In the first two experiments, we investigated the interference associated with performing RNG concurrently with a serial reaction time (SRT) task. In a third experiment, we compared the effects of RNG and TC. In all three experiments, we directly evaluated participants' knowledge of the sequence with a subsequent sequence generation task. Sequence learning was consistently observed in all experiments, but was impaired under dual-task conditions. Most importantly, our data suggest that RNG is more demanding and impairs learning to a greater extent than TC. Nevertheless, we failed to observe effects of the secondary task in subsequent sequence generation. Our studies indicate that RNG is a promising task to explore the involvement of attention in the SRT task.     

Consolidating behavioral and neurophysiologic findings to explain the influence of contextual interference during motor sequence learning

Motor sequence learning under high levels of contextual interference (CI) disrupts initial performance but supports delayed test and transfer performance when compared to learning under low CI. Integrating findings from early behavioral work and more recent experimental efforts that incorporated neurophysiologic measures led to a novel account of the role of CI during motor sequence learning. This account focuses on important contributions from two neural regions—the dorsal premotor area and the SMA complex—that are recruited earlier and more extensively during the planning of a motor sequence in a high CI context. It is proposed that activation of these regions is critical to early adaptation of sequence structure amenable to long-term storage. Moreover, greater CI enhances access to newly acquired motor sequence knowledge through (1) the emergence of temporary functional connectivity between neural sites previously described as crucial to successful long-term performance of sequential behaviors, and (2) heightened excitability of M1—a key constituent of the temporary coupled neural circuits, and the primary candidate for storage of motor memory.     

Sequence learning in pianists and nonpianists: An fMRI study of motor expertise

Previous studies of motor learning have proposed a distinction between fast and slow learning, but these mechanisms have rarely been examined simultaneously. We examined the influence of longterm motor expertise (slow learning) while pianists and nonpianists performed alternating epochs of sequenced and random keypresses in response to visual cues (fast learning) during functional neuroimaging. All of the participants demonstrated learning of the sequence as demonstrated by decreasing reaction times (RTs) on sequence trials relative to random trials throughout the session. Pianists also demonstrated faster RTs and superior sequence acquisition in comparison with nonpianists. Withinsession decreases in bilateral sensorimotor and parietal activation were observed for both groups. Additionally, there was more extensive activation throughout the session for pianists in comparison with nonpianists across a network of primarily right-lateralized prefrontal, sensorimotor, and parietal regions. These findings provide evidence that different neural systems subserve slow and fast phases of learning.     

Interactions between encoding and retrieval in the domain of sequence-learning

In this article, the authors propose to characterize sequence learning in terms of automatic versus non-automatic processing and to apply this contrast independently to knowledge acquisition and retrieval. In several experiments of sequence learning, automaticity of both the acquisition and retrieval of the acquired knowledge was independently assessed. It was found that the sequence learning order can be demonstrated under all combinations of knowledge acquisition and retrieval. In particular, at least in the simple sequences the authors used, this applies in cases in which both the acquisition and the retrieval of knowledge are strictly automatic--that is, when neither is required for the task nor beneficial to deliberate behavior. The proposed framework has implications for the notion of sequence learning and the investigation of learning in general.     

内隐序列学习意识的具身机制

内隐序列学习意识已有三类理论如全局工作平台理论、神经可塑性理论、新异刺激理论都忽略了身体感受的关键因素, 难以揭示意识产生的根本原因。具身意识理论和研究发现, 运动/情感镜像神经元系统及与自我、认知控制系统的交互, 是初级/高级意识产生的本源, 但未涉及内隐序列学习规则意识这个对人类学习认知至关重要的领域。内隐序列学习研究实质上已接近揭示其学习机制正是感知觉运动具身学习, 其意识机制很可能是感知觉运动/情感具身意识, 并且其意识加工脑区与具身意识脑区有关键重合。未来研究可采用Granger因果大脑网络技术证明内隐序列学习意识的具身本源, 并考察已有三类意识理论的具身基础, 以及探索意识影响因素的具身机制。     

Effector-independent and effector-dependent sequence representations underlie general and specific perceptuomotor sequence learning

Perceptuomotor sequence learning could be due to learning of effector-independent sequence information (e.g., response locations), effector-dependent information (e.g., motor movements of a particular effector), or both. Evidence also suggests that learning of statistical regularities in sequences (general-regularity learning) and specific sequences (specific-sequence learning) are dissociable. The authors examined the degree to which general and specific-sequence learning rely on effector-independent and effector-dependent representations. During training, participants typed sequences that followed a construction rule with a subset of sequences repeatedly processed. At test, effector-independent and effector-dependent learning was examined with respect to general-regularity and specific-sequence learning. Results suggest that general-regularity learning is subserved by effector-independent sequence representations, whereas specific-sequence learning is subserved by effector-dependent sequence representations, further dissociating these types of learning.     

A cognitive neuroscience account of posttraumatic stress disorder and its treatment

Recent research in the areas of animal conditioning, the neural systems underlying emotion and memory, and the effect of fear on these systems is reviewed. This evidence points to an important distinction between hippocampally-dependent and non-hippocampally-dependent forms of memory that are differentially affected by extreme stress. The cognitive science perspective is related to a recent model of posttraumatic stress disorder, dual representation theory, that also posits separate memory systems underlying vivid reexperiencing versus ordinary autobiographical memories of trauma. This view is compared with other accounts in the literature of traumatic memory processes in PTSD, and the contrasting implications for therapy are discussed.     

An analysis of letter expertise in a levels-of-categorization framework

While there has been increasing effort in dissociating the neural substrates recruited by perception of different objects, the theoretical and behavioural work needed to understand such dissociation lags behind. In an attempt to compare expertise in letter and face perception, we outline a theoretical framework that characterizes different types of object expertise based on the task demand (level of abstraction) required in object categorization. Face perception requires categorization at a subordinate level, whereas letter perception involves mainly basic-level categorization. Accordingly face and letter perception should represent two different types of expertise and display different neural and behavioural markers. Results from three behavioural experiments supported the predictions of the framework in that letter expertise is characterized by an enhancement of the basic-level advantage, instead of its attenuation as typically found for face perception. We compare this framework with Farah's taxonomy of visual abilities based on cooccurrence of deficits in visual agnosias.     

Hippocampus, cortex, and basal ganglia: insights from computational models of complementary learning systems

We present a framework for understanding how the hippocampus, neocortex, and basal ganglia work together to support cognitive and behavioral function in the mammalian brain. This framework is based on computational tradeoffs that arise in neural network models, where achieving one type of learning function requires very different parameters from those necessary to achieve another form of learning. For example, we dissociate the hippocampus from cortex with respect to general levels of activity, learning rate, and level of overlap between activation patterns. Similarly, the frontal cortex and associated basal ganglia system have important neural specializations not required of the posterior cortex system. Taken together, this overall cognitive architecture, which has been implemented in functioning computational models, provides a rich and often subtle means of explaining a wide range of behavioral and cognitive neuroscience data. Here, we summarize recent results in the domains of recognition memory, contextual fear conditioning, effects of basal ganglia lesions on stimulus-response and place learning, and flexible responding.     

Imaging brain plasticity during motor skill learning

The search for the neural substrates mediating the incremental acquisition of skilled motor behaviors has been the focus of a large body of animal and human studies in the past decade. Much less is known, however, with regard to the dynamic neural changes that occur in the motor system during the different phases of learning. In this paper, we review recent findings, mainly from our own work using fMRI, which suggest that: (i) the learning of sequential finger movements produces a slowly evolving reorganization within primary motor cortex (M1) over the course of weeks and (ii) this change in M1 follows more dynamic, rapid changes in the cerebellum, striatum, and other motor-related cortical areas over the course of days. We also briefly review neurophysiological and psychophysical evidence for the consolidation of motor skills, and we propose a working hypothesis of its underlying neural substrate in motor sequence learning.     

Reinforcement learning in the brain

A wealth of research focuses on the decision-making processes that animals and humans employ when selecting actions in the face of reward and punishment. Initially such work stemmed from psychological investigations of conditioned behavior, and explanations of these in terms of computational models. Increasingly, analysis at the computational level has drawn on ideas from reinforcement learning, which provide a normative framework within which decision-making can be analyzed. More recently, the fruits of these extensive lines of research have made contact with investigations into the neural basis of decision making. Converging evidence now links reinforcement learning to specific neural substrates, assigning them precise computational roles. Specifically, electrophysiological recordings in behaving animals and functional imaging of human decision-making have revealed in the brain the existence of a key reinforcement learning signal, the temporal difference reward prediction error. Here, we first introduce the formal reinforcement learning framework. We then review the multiple lines of evidence linking reinforcement learning to the function of dopaminergic neurons in the mammalian midbrain and to more recent data from human imaging experiments. We further extend the discussion to aspects of learning not associated with phasic dopamine signals, such as learning of goal-directed responding that may not be dopamine-dependent, and learning about the vigor (or rate) with which actions should be performed that has been linked to tonic aspects of dopaminergic signaling. We end with a brief discussion of some of the limitations of the reinforcement learning framework, highlighting questions for future research.     

Generalized lessons about sequence learning from the study of the serial reaction time task

Over the last 20 years researchers have used the serial reaction time (SRT) task to investigate the nature of spatial sequence learning. They have used the task to identify the locus of spatial sequence learning, identify situations that enhance and those that impair learning, and identify the important cognitive processes that facilitate this type of learning. Although controversies remain, the SRT task has been integral in enhancing our understanding of implicit sequence learning. It is important, however, to ask what, if anything, the discoveries made using the SRT task tell us about implicit learning more generally. This review analyzes the state of the current spatial SRT sequence learning literature highlighting the stimulus-response rule hypothesis of sequence learning which we believe provides a unifying account of discrepant SRT data. It also challenges researchers to use the vast body of knowledge acquired with the SRT task to understand other implicit learning literatures too often ignored in the context of this particular task. This broad perspective will make it possible to identify congruences among data acquired using various different tasks that will allow us to generalize about the nature of implicit learning.     

Unilateral implicit motor learning deficit in developmental dyslexia

It has been suggested that developmental dyslexia involves various literacy, sensory, motor skill, and processing speed deficits. Some recent studies have shown that individuals with developmental dyslexia exhibit implicit motor learning deficits, which may be related to cerebellar functioning. However, previous studies on implicit motor learning in developmental dyslexics have produced conflicting results. Findings from cerebellar lesion patients have shown that patients' implicit motor learning performance varied when different hands were used to complete tasks. This suggests that dyslexia may have different effects on implicit motor learning between the two hands if cerebellar dysfunction is involved. To specify this question, we used a one-handed version of a serial reaction time task to compare the performance of 27 Chinese children with developmental dyslexics with another 27 age-matched children without reading difficulties. All the subjects were students from two primary schools, Grades 4 to 6. The results showed that children with developmental dyslexic responded more slowly than nondyslexic children, and exhibited no implicit motor learning in the condition of left-hand response. In contrast, there was no significant difference in reaction time between two groups of children when they used the right hand to respond. This finding indicates that children with developmental dyslexia exhibited normal motor skill and implicit motor learning ability provided the right hand was used. Taken together, these results suggested that Chinese children with developmental dyslexia exhibit unilateral deficits in motor skill and implicit motor learning in the left hand. Our findings lend partial support to the cerebellar deficit theory of developmental dyslexia.     

A neural cognitive model of argumentation with application to legal inference and decision making

Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data).     

Visual context does not promote concurrent sequence learning

Concurrent sequence learning (CSL) of two or more sequences refers to the concurrent maintenance, in memory, of the two or more sequence representations. Research using the serial reaction time task has established that CSL is possible when the different sequences involve different dimensions (e.g., visuospatial locations versus manual keypresses). Recently some studies have suggested that visual context can promote CSL if the different sequences are embedded in different visual contexts. The results of these studies have been difficult to interpret because of various limitations. Addressing the limitations, the current study suggests that visual context does not promote CSL and that CSL may not be possible when the different sequences involve the same elements (i.e., the same target locations, response keys and effectors).     

Children retain implicitly learned phonological sequences better than adults: a longitudinal study

Whereas adults often rely on explicit memory, children appear to excel in implicit memory, which plays an important role in the acquisition of various cognitive skills, such as those involved in language. The current study aimed to test the assertion of an age‐dependent shift in implicit versus explicit learning within a theoretical framework that explains the link between implicit sequence memory and word‐form acquisition, using the Hebb repetition paradigm. We conducted a one‐year, multiple‐session longitudinal study in which we presented auditory sequences of syllables, co‐presented with pictures of aliens, for immediate serial recall by a group of children (8–9 years) and by an adult group. The repetition of one Hebb sequence was explicitly announced, while the repetition of another Hebb sequence was unannounced and, therefore, implicit. Despite their overall inferior recall performance, the children showed better offline retention of the implicit Hebb sequence, compared with adults who showed a significant decrement across the delays. Adults had gained more explicit knowledge of the implicit sequence than children, but this could not explain the age‐dependent decline in the delayed memory for it. There was no significant age‐effect for delayed memory of the explicit Hebb sequence, with both age groups showing retention. Overall performance by adults was positively correlated with measures of post‐learning awareness. Performance by children was positively correlated with vocabulary knowledge. We conclude that children outperform adults in the retention over time of implicitly learned phonological sequences that will gradually consolidate into novel word‐forms. The findings are discussed in the light of maturational differences for implicit versus explicit memory systems that also play a role in language acquisition. A video abstract of this article can be viewed at: https://youtu.be/G5nOfJB72t4     

Implicit sequence learning in a search task

This study investigated the effects of selection demands on implicit sequence learning. Participants in a search condition looked for a target among seven distractors and responded on the target identity. The responses followed a deterministic sequence, and sequence learning was compared to that found in two control conditions in which the targets were presented alone, either at a central location or over a series of unpredictable locations. Sequence learning was obtained in all conditions, and it was equivalent for the two variable location conditions, regardless of the perceptual demands. Larger effects of learning were observed in the central location, both on the indirect measures and on the measures taken from a cued-generation task. The expression of learning decreased selectively in this condition when the sequence validity was reduced over a test block. These results are consistent with the claims that implicit and explicit learning are mixed in this central condition and that implicit learning is not affected by selection difficulty.     

How Theory Matters: Formative Assessment Theory and Practices and Their Different Relations to Education

The positioning of theory in relation to educational practice has provoked much recent debate, with some arguing that educational theory constrains thinking in education, while others dismiss ??theory?? out of hand as belonging to the world of the ??academic??, abstracted from the ??realities?? of the classroom. This paper views theory as necessarily implicated in all practices, but argues that depending on the theories embraced, and the understanding of theory itself, education can be understood in very different ways. Resisting the separation of theory from practice, the paper takes up the call to consider the entanglement of theory with practice, or how theory matters. It takes formative assessment as a particularly fertile case for this discussion. Formative assessment has been considerably developed in schooling across different national education systems. Its aspiration is for assessment to support learning, rather than only to credentialise learning. Having first emerged as a concept when behaviourism held sway, it has been considered through different theoretical lenses. Drawing upon empirical studies of classroom assessment practices, the paper draws out the different ??mattering?? implicated in the different languages of assessment used by practitioners, raising questions about the practices this produced. The paper concludes by asking if formative assessment could become ??educational?? in a more radical sense, if opportunities to focus on the contingencies and politics of our meaning-making were sometimes taken up more openly and dialogically with students, as opposed to formative assessment sitting in a instrumental relationship to a given curriculum.     

Sensori‐motor experience leads to changes in visual processing in the developing brain

Since Broca’s studies on language processing, cortical functional specialization has been considered to be integral to efficient neural processing. A fundamental question in cognitive neuroscience concerns the type of learning that is required for functional specialization to develop. To address this issue with respect to the development of neural specialization for letters, we used functional magnetic resonance imaging (fMRI) to compare brain activation patterns in pre‐school children before and after different letter‐learning conditions: a sensori‐motor group practised printing letters during the learning phase, while the control group practised visual recognition. Results demonstrated an overall left‐hemisphere bias for processing letters in these pre‐literate participants, but, more interestingly, showed enhanced blood oxygen‐level‐dependent activation in the visual association cortex during letter perception only after sensori‐motor (printing) learning. It is concluded that sensori‐motor experience augments processing in the visual system of pre‐school children. The change of activation in these neural circuits provides important evidence that ‘learning‐by‐doing’ can lay the foundation for, and potentially strengthen, the neural systems used for visual letter recognition.