Does the Component Processes Task Assess Text-Based Inferences Important for Reading Comprehension? A Path Analysis in Primary School Children.

Using a component processes task (CPT) that differentiates between higher-level cognitive processes of reading comprehension provides important advantages over commonly used general reading comprehension assessments. The present study contributes to further development of the CPT by evaluating the relative contributions of its components (text memory, text inferencing, and knowledge integration) and working memory to general reading comprehension within a single study using path analyses. Participants were 173 third- and fourth-grade children. As hypothesized, knowledge integration was the only component of the CPT that directly contributed to reading comprehension, indicating that the text-inferencing component did not assess inferential processes related to reading comprehension. Working memory was a significant predictor of reading comprehension over and above the component processes. Future research should focus on finding ways to ensure that the text-inferencing component taps into processes important for reading comprehension.

Processing multiple non-adjacent dependencies: evidence from sequence learning.

Processing non-adjacent dependencies is considered to be one of the hallmarks of human language. Assuming that sequence-learning tasks provide a useful way to tap natural-language-processing mechanisms, we cross-modally combined serial reaction time and artificial-grammar learning paradigms to investigate the processing of multiple nested (A(1)A(2)A(3)B(3)B(2)B(1)) and crossed dependencies (A(1)A(2)A(3)B(1)B(2)B(3)), containing either three or two dependencies. Both reaction times and prediction errors highlighted problems with processing the middle dependency in nested structures (A(1)A(2)A(3)B(3)_B(1)), reminiscent of the 'missing-verb effect' observed in English and French, but not with crossed structures (A(1)A(2)A(3)B(1)_B(3)). Prior linguistic experience did not play a major role: native speakers of German and Dutch-which permit nested and crossed dependencies, respectively-showed a similar pattern of results for sequences with three dependencies. As for sequences with two dependencies, reaction times and prediction errors were similar for both nested and crossed dependencies. The results suggest that constraints on the processing of multiple non-adjacent dependencies are determined by the specific ordering of the non-adjacent dependencies (i.e. nested or crossed), as well as the number of non-adjacent dependencies to be resolved (i.e. two or three). Furthermore, these constraints may not be specific to language but instead derive from limitations on structured sequence learning.

Age affects chunk-based, but not rule-based learning in artificial grammar acquisition.

Explicit learning is well known to decline with age, but divergent results have been reported for implicit learning. Here, we assessed the effect of aging on implicit vs. explicit learning within the same task. Fifty-five young (mean 32 years) and 55 elderly (mean 64 years) individuals were exposed to letter strings generated by an artificial grammar. Subsequently, participants classified novel strings as grammatical or nongrammatical. Acquisition of superficial ("chunk-based") and structural ("rule-based") features of the grammar were analyzed separately. We found that overall classification accuracy was diminished in the elderly, driven by decreased performance on items that required chunk-based knowledge. Performance on items requiring rule-based knowledge was comparable between groups. Results indicate that rule-based and chunk-based learning are differentially affected by age: while rule-based learning, reflecting implicit learning, is preserved, chunk-based learning, which contains at least some explicit learning aspects, declines with age. Our findings may explain divergent results on implicit learning tasks in previous studies on aging. They may also help to better understand compensatory mechanisms during the aging process.

Increasing dopamine levels in the brain improves feedback-based procedural learning in healthy participants: an artificial-grammar-learning experiment.

Recently, an increasing number of studies have suggested a role for the basal ganglia and related dopamine inputs in procedural learning, specifically when learning occurs through trial-by-trial feedback (Shohamy, Myers, Kalanithi, & Gluck. (2008). Basal ganglia and dopamine contributions to probabilistic category learning. Neuroscience and Biobehavioral Reviews, 32, 219-236). A necessary relationship has however only been demonstrated in patient studies. In the present study, we show for the first time that increasing dopamine levels in the brain improves the gradual acquisition of complex information in healthy participants. We implemented two artificial-grammar-learning tasks, one with and one without performance feedback. Learning was improved after levodopa intake for the feedback-based learning task only, suggesting that dopamine plays a specific role in trial-by-trial feedback-based learning. This provides promising directions for future studies on dopaminergic modulation of cognitive functioning.

Electrical stimulation of Broca's area enhances implicit learning of an artificial grammar.

Artificial grammar learning constitutes a well-established model for the acquisition of grammatical knowledge in a natural setting. Previous neuroimaging studies demonstrated that Broca's area (left BA 44/45) is similarly activated by natural syntactic processing and artificial grammar learning. The current study was conducted to investigate the causal relationship between Broca's area and learning of an artificial grammar by means of transcranial direct current stimulation (tDCS). Thirty-eight healthy subjects participated in a between-subject design, with either anodal tDCS (20 min, 1 mA) or sham stimulation, over Broca's area during the acquisition of an artificial grammar. Performance during the acquisition phase, presented as a working memory task, was comparable between groups. In the subsequent classification task, detecting syntactic violations, and specifically, those where no cues to superficial similarity were available, improved significantly after anodal tDCS, resulting in an overall better performance. A control experiment where 10 subjects received anodal tDCS over an area unrelated to artificial grammar learning further supported the specificity of these effects to Broca's area. We conclude that Broca's area is specifically involved in rule-based knowledge, and here, in an improved ability to detect syntactic violations. The results cannot be explained by better tDCS-induced working memory performance during the acquisition phase. This is the first study that demonstrates that tDCS may facilitate acquisition of grammatical knowledge, a finding of potential interest for rehabilitation of aphasia.

White matter integrity in the vicinity of Broca's area predicts grammar learning success.

Humans differ substantially in their ability to implicitly extract structural regularities from experience, as required for learning the grammar of a language. The mechanisms underlying this fundamental inter-individual difference, which may determine initial success in language learning, are incompletely understood. Here, we use diffusion tensor magnetic resonance imaging (DTI) to determine white matter integrity around Broca's area, which is crucially involved in both natural and artificial language processing. Twelve young, right-handed individuals completed an artificial grammar learning task, and DTI of their brains were acquired. Inter-individual variability in performance correlated with white matter integrity (increasing fractional anisotropy (FA)) in fibres arising from Broca's area (left BA 44/45), but not from its right-hemispheric homologue. Variability in performance based on superficial familiarity did not show this association. Moreover, when Broca's area was used as a seed mask for probabilistic tractography, we found that mean FA values within the generated tracts was higher in subjects with better grammar learning. Our findings provide the first evidence that integrity of white matter fibre tracts arising from Broca's area is intimately linked with the ability to extract grammatical rules. The relevance of these findings for acquisition of a natural language has to be established in future studies.

Syntactic structure and artificial grammar learning: the learnability of embedded hierarchical structures.

Embedded hierarchical structures, such as "the rat the cat ate was brown", constitute a core generative property of a natural language theory. Several recent studies have reported learning of hierarchical embeddings in artificial grammar learning (AGL) tasks, and described the functional specificity of Broca's area for processing such structures. In two experiments, we investigated whether alternative strategies can explain the learning success in these studies. We trained participants on hierarchical sequences, and found no evidence for the learning of hierarchical embeddings in test situations identical to those from other studies in the literature. Instead, participants appeared to solve the task by exploiting surface distinctions between legal and illegal sequences, and applying strategies such as counting or repetition detection. We suggest alternative interpretations for the observed activation of Broca's area, in terms of the application of calculation rules or of a differential role of working memory. We claim that the learnability of hierarchical embeddings in AGL tasks remains to be demonstrated.

Five days versus a lifetime: intense associative vocabulary training generates lexically integrated words.

PURPOSE: The best predictor of successful language therapy in both the acute and chronic stages after stroke is the treatment intensity, i.e., number of hours trained per week. Associative learning should be particularly suited for intense training because it places low demands on (executive) cognitive functions. It is as of yet unresolved, however, whether associative training is a valid language learning approach. It could merely produce superficial associations of acoustic-visual information, which remain outside lexical and conceptual networks. METHODS: We here examined if five days of associative training in a miniature vocabulary are sufficient for an integration of novel words into the learner's mental lexicon. Twelve healthy subjects were trained 20 min daily for five consecutive days simply by frequent couplings of object pictures with novel words. RESULTS: Correct responses for couplings of novel words and object names increased from a chance level of 50 percent on day 1 to >90 percent accuracy on day 5. Prior to and immediately after the vocabulary training, a cross-modal semantic priming test was administered to determine the degree of lexical integration of the novel words into the language system already in situ. CONCLUSIONS: Results show that learned novel words had acquired semantic characteristics, which were comparable to words of subjects' native language acquired over a lifetime. Thus, comprehensive integration of the novel words into existing conceptual and lexical networks occurred after just five days of training. This lays the foundation for probing associative training approaches in aphasia therapy, with the hope of increasing therapy efficiency.