Effects of induced orthographic and semantic knowledge on subsequent learning: A test of the partial knowledge hypothesis.

Word learning can build the high-quality word representations that support skilled reading and language comprehension. According to the partial knowledge hypothesis, words that are partially known, also known as "frontier words" (Durso & Shore, 1991), may be good targets for instruction precisely because they are already familiar. However, studies investigating this question have produced mixed findings, and individual differences in baseline knowledge have complicated results both within and across studies. We present two studies that took a different approach, controlling both familiarity and the nature of the familiarizing episode. We controlled familiarity with novel words through pre-exposure ("pre-familiarization") in isolation, to induce form-based familiarity, or in sentences that provided few clues to meaning, to induce partial semantic knowledge. The number of pre-exposures varied (0, 1, or 4). After the pre-familiarization phase, we presented the words in several highly informative sentences to support meaning acquisition. Participants included both adults and typically developing children, ages 9-12. Participants' self-rated familiarity with target words, and their knowledge of the words' meanings and orthography were each measured at baseline, immediately after learning, and one week later. Orthographic and semantic word learning showed contrasting effects of pre-familiarization. For orthographic learning, it was the number, rather than the type, of pre-familiarizations that mattered most. By contrast, the number of pre-familiarizations had little impact on word semantic learning; further, pre-familiarization in low-constraint sentences did not consistently boost subsequent learning. These findings suggest that familiarity with a word prior to instruction does not necessarily improve word-learning outcomes, and they highlight the importance of repeated exposures to high quality contexts for robust word learning.

FN400 and LPC memory effects for concrete and abstract words.

According to dual-process models, recognition memory depends on two neurocognitive mechanisms: familiarity, which has been linked to the frontal N400 (FN400) effect in studies using ERPs, and recollection, which is reflected by changes in the late positive complex (LPC). Recently, there has been some debate over the relationship between FN400 familiarity effects and N400 semantic effects. According to one view, these effects are one and the same. Proponents of this view have suggested that the frontal distribution of the FN400 could be due to stimulus concreteness: recognition memory experiments commonly use highly imageable or concrete words (or pictures), which elicit semantic ERPs with a frontal distribution. In the present study, we tested this claim using a recognition memory paradigm in which subjects memorized concrete and abstract nouns; half of the words changed font color between study and test. FN400 and LPC old/new effects were observed for abstract as well as concrete words, and were stronger over right hemisphere electrodes for concrete words. However, there was no difference in anteriority of the FN400 effect for the two word types. These findings challenge the notion that the frontal distribution of the FN400 old/new effect is fully explained by stimulus concreteness.

Interdisciplinary perspectives on the development, integration, and application of cognitive ontologies.

We discuss recent progress in the development of cognitive ontologies and summarize three challenges in the coordinated development and application of these resources. Challenge 1 is to adopt a standardized definition for cognitive processes. We describe three possibilities and recommend one that is consistent with the standard view in cognitive and biomedical sciences. Challenge 2 is harmonization. Gaps and conflicts in representation must be resolved so that these resources can be combined for mark-up and interpretation of multi-modal data. Finally, Challenge 3 is to test the utility of these resources for large-scale annotation of data, search and query, and knowledge discovery and integration. As term definitions are tested and revised, harmonization should enable coordinated updates across ontologies. However, the true test of these definitions will be in their community-wide adoption which will test whether they support valid inferences about psychological and neuroscientific data.

Sharing and Integration of Cognitive Neuroscience Data: Metric and Pattern Matching across Heterogeneous ERP Datasets.

In the present paper, we use data mining methods to address two challenges in the sharing and integration of data from electrophysiological (ERP) studies of human brain function. The first challenge, ERP metric matching, is to identify correspondences among distinct summary features ("metrics") in ERP datasets from different research labs. The second challenge, ERP pattern matching, is to align the ERP patterns or "components" in these datasets. We address both challenges within a unified framework. The utility of this framework is illustrated in a series of experiments using ERP datasets that are designed to simulate heterogeneities from three sources: (a) different groups of subjects with distinct simulated patterns of brain activity, (b) different measurement methods, i.e, alternative spatial and temporal metrics, and (c) different patterns, reflecting the use of alternative pattern analysis techniques. Unlike real ERP data, the simulated data are derived from known source patterns, providing a gold standard for evaluation of the proposed matching methods. Using this approach, we demonstrate that the proposed method outperforms well-known existing methods, because it utilizes cluster-based structure and thus achieves finer-grained representation of the multidimensional (spatial and temporal) attributes of ERP data.

Minimal Information for Neural Electromagnetic Ontologies (MINEMO): A standards-compliant method for analysis and integration of event-related potentials (ERP) data.

We present MINEMO (Minimal Information for Neural ElectroMagnetic Ontologies), a checklist for the description of event-related potentials (ERP) studies. MINEMO extends MINI (Minimal Information for Neuroscience Investigations)to the ERP domain. Checklist terms are explicated in NEMO, a formal ontology that is designed to support ERP data sharing and integration. MINEMO is also linked to an ERP database and web application (the NEMO portal). Users upload their data and enter MINEMO information through the portal. The database then stores these entries in RDF (Resource Description Framework), along with summary metrics, i.e., spatial and temporal metadata. Together these spatial, temporal, and functional metadata provide a complete description of ERP data and the context in which these data were acquired. The RDF files then serve as inputs to ontology-based labeling and meta-analysis. Our ultimate goal is to represent ERPs using a rich semantic structure, so results can be queried at multiple levels, to stimulate novel hypotheses and to promote a high-level, integrative account of ERP results across diverse study methods and paradigms.

Predicting Robust Vocabulary Growth from Measures of Incremental Learning.

We report a study of incremental learning of new word meanings over multiple episodes. A new method called MESA (Markov Estimation of Semantic Association) tracked this learning through the automated assessment of learner-generated definitions. The multiple word learning episodes varied in the strength of contextual constraint provided by sentences, in the consistency of this constraint, and in the spacing of sentences provided for each trained word. Effects of reading skill were also examined. Results showed that MESA scores increased with each word learning encounter. MESA growth curves were affected by context constraint, spacing of practice, and reading skill. Most important, the accuracy of participant responses (MESA scores) during learning predicted which words would be retained over a 1-week period. These results support the idea that word learning is incremental and that partial gains in knowledge depend on properties of both the context and the learner. The introduction of MESA presents new opportunities to test word-learning theories and the complex factors that affect growth of word knowledge over time and in different contexts.

Lexical quality in the brain: ERP evidence for robust word learning from context.

We examined event-related potentials (ERPs) before and after word learning, using training contexts that differed in their level of contextual support for meaning acquisition. Novel words appeared either in contexts that were semantically constraining, providing strong cues to meaning, or in contexts that were weakly constraining, that is, uninformative. After each sentence, participants were shown the word in isolation and were asked to generate a close synonym. Immediately after training, words trained in high-constraint contexts elicited a smaller left temporal negativity (N300(FT7)) compared with words trained in low-constraint contexts, and both types of trained words elicited a stronger medial frontal negativity (N350(Fz)) relative to familiar words. Two days after training the N300(FT7) disappeared and was replaced by a later, left parietal (P600(Pz)) effect. To examine robust learning, we administered a semantic priming test two days after training. Familiar words and words trained in high-constraint contexts elicited strong N400 effects. By contrast, words trained in low-constraint contexts elicited a weak N400 effect, and novel (untrained rare) words elicited no semantic priming. These findings suggest that supportive contexts and the use of an active meaning-generation task may lead to robust word learning. The effects of this training can be observed as changes in an early left frontal component, as well as the classical N400 effect. We discuss implications for theories of "partial" semantic knowledge and for robust word learning and instruction.

ERP measures of partial semantic knowledge: left temporal indices of skill differences and lexical quality.

This study examines the sensitivity of early event-related potentials (ERPs) to degrees of word semantic knowledge. Participants with strong, average, or weak vocabulary skills made speeded lexical decisions to letter strings. To represent the full spectrum of word knowledge among adult native-English speakers, we used rare words that were orthographically matched with more familiar words and with pseudowords. Since the lexical decision could not reliably be made on the basis of word form, subjects were obliged to use semantic knowledge to perform the task. A d' analysis suggested that high-skilled subjects adopted a more conservative strategy in response to rare versus more familiar words. Moreover, the high-skilled participants showed a trend towards an enhanced "N2c" to rare words, and a similar posterior temporal effect reached significance approximately 650 ms. Generators for these effects were localized to left temporal cortex. We discuss implications of these results for word learning and for theories of lexical semantic access.

Measuring incremental changes in word knowledge: experimental validation and implications for learning and assessment.

The goal of this study was to test a new technique for assessing vocabulary development. This technique is based on an algorithm for scoring the accuracy of word definitions using a continuous scale (Collins-Thompson & Callan, 2007). In an experiment with adult learners, target words were presented in six different sentence contexts, and the number of informative versus misleading contexts was systematically manipulated. Participants generated a target definition after each sentence, and the definition-scoring algorithm was used to assess the degree of accuracy on each trial. We observed incremental improvements in definition accuracy across trials. Moreover, learning curves were sensitive to the proportion of misleading contexts, the use of spaced versus massed practice, and individual differences, demonstrating the utility of this procedure for capturing specific experimental effects on the trajectory of word learning. We discuss the implications of these results for measurement of meaning, vocabulary assessment, and instructional design.

A framework to support automated classification and labeling of brain electromagnetic patterns.

This paper describes a framework for automated classification and labeling of patterns in electroencephalographic (EEG) and magnetoencephalographic (MEG) data. We describe recent progress on four goals: 1) specification of rules and concepts that capture expert knowledge of event-related potentials (ERP) patterns in visual word recognition; 2) implementation of rules in an automated data processing and labeling stream; 3) data mining techniques that lead to refinement of rules; and 4) iterative steps towards system evaluation and optimization. This process combines top-down, or knowledge-driven, methods with bottom-up, or data-driven, methods. As illustrated here, these methods are complementary and can lead to development of tools for pattern classification and labeling that are robust and conceptually transparent to researchers. The present application focuses on patterns in averaged EEG (ERP) data. We also describe efforts to extend our methods to represent patterns in MEG data, as well as EM patterns in source (anatomical) space. The broader aim of this work is to design an ontology-based system to support cross-laboratory, cross-paradigm, and cross-modal integration of brain functional data. Tools developed for this project are implemented in MATLAB and are freely available on request.

Hemispheric differences in strong versus weak semantic priming: evidence from event-related brain potentials.

GOALS: Research with lateralized word presentation has suggested that strong ("close") and weak ("remote") semantic associates are processed differently in the left and right cerebral hemispheres [e.g., Beeman, M. j., & Chiarello, C. (1998). Complementary right- and left-hemisphere language comprehension. Current Directions in Psychological Science, 7(1), 2-8]. Recently, this hypothesis has been challenged [Coney, J. (2002). The effect of associative strength on priming in the cerebral hemispheres. Brain and Cognition, 50(2), 234-241]. We predicted that foveal presentation of strong and weak associates would elicit different patterns of hemispheric activity, as indexed by high-density event-related brain potentials (ERPs), and that source localization of the scalp potentials would help clarify the nature of hemispheric contributions to semantic organization. METHODS: 128-channel ERPs were recorded in two experiments as subjects performed a lexical decision task. Word trials were equally divided into strongly related, weakly related, and unrelated word pairs. All words were foveally presented. SOA was 800 ms in Experiment 1, and 200 ms in Experiment 2. RESULTS: Topographic analyses revealed medial frontal (MFN) and parietal (N400/LPC) effects for both strong and weak associates. Between approximately 450 and 550 ms, the magnitude of the N400/LPC effect indicated priming for both strong and weak associates over left parietal sites, while priming over right parietal sites was restricted to strongly related word pairs. During this interval, spatiotemporal source modeling showed that these scalp effects were best accounted for by ipsilateral sources in the medial temporal lobe. The observed pattern of asymmetries for strong versus weak associates is not consistent with certain proposals regarding the complementarity of right- and left-hemisphere contributions to semantics. It is, however, consistent with findings from visual half-field studies (Hasbrooke and Chiarello, 1998). We discuss the relevance of these results for theories of hemispheric asymmetry and meta-control in lexical semantic access.

Automated protocol for evaluation of electromagnetic component separation (APECS): Application of a framework for evaluating statistical methods of blink extraction from multichannel EEG.

OBJECTIVE: We present APECS (Automated Protocol for Evaluation of Electromagnetic Component Separation), a framework for evaluating the accuracy of blind source separation algorithms in removing artifacts from EEG data. APECS applies multiple, automated procedures to quantify the extent to which blinks are removed, and the degree to which nonocular activity is left intact. METHODS: APECS was used to evaluate blink removal using three BSS algorithms: Second-Order Blind Inference (SOBI) and two Independent Component Analysis (ICA) implementations, FastICA and Infomax. The algorithms were applied to a series of blink-free EEG datasets, which were contaminated with real or simulated blinks. Extracted components were assumed to contain blink activity if correlation of their spatial projectors to a predefined blink template exceeded some threshold, and if polarity inverted above and below the eyes. Blink-related components were then subtracted to produce filtered data. The success of each data decomposition is evaluated through the use of multiple, automated metrics, to determine which decomposition best approximates the ideal solution (complete separation of blink from nonblink activity). RESULTS: The outcomes for the evaluation measures were generally congruent, but also provided different and complementary information about the quality of each data decomposition. Under our testing framework, Infomax outperformed both FastICA and SOBI. Best results were achieved when blink activity loaded onto a single component. CONCLUSIONS: Multiple metrics, both quantitative and qualitative, are important in evaluating algorithms for artifact extraction. SIGNIFICANCE: Failure to achieve complete separation of blink from nonblink activity can affect experimental outcomes, as illustrated here, using an ERP study of word-nonword discrimination. This illustrates the importance of methods for evaluation of artifact extraction results.

Frontal and posterior sources of event-related potentials in semantic comprehension.

An important question in brain and language research is how activity in multiple brain networks is coordinated over time during semantic comprehension. To address this question, we applied spatiotemporal source analysis to event-related potentials (ERPs) recorded as subjects read words that were meaningful or incongruous in the context of a sentence (N400 paradigm). The incongruous word was placed either early in the sentence or at the end. Source analysis showed activity in language areas of the left hemisphere, right temporal cortex and medial limbic cortex. The initial detection of semantic incongruity (approximately 250 ms) engaged the left prefrontal cortex and left anterior cingulate. In the critical (300-500 ms) interval, regional sources in left and right lateral prefrontal cortex, right temporal cortex, and both anterior and posterior cingulate were responsive to the semantic manipulation. Left hemisphere activity preceded right hemisphere activity, and semantic effects in frontal regions began earlier and were more sustained than the transient effects within posterior cortical regions. Findings are discussed with respect to recent theories of corticothalamic and corticolimbic networks in attention and semantic processing.

Frontolimbic response to negative feedback in clinical depression.

Functional neuroimaging suggests that limbic regions of the medial frontal cortex may be abnormally active in individuals with depression. These regions, including the anterior cingulate cortex, are engaged in both action regulation, such as monitoring errors and conflict, and affect regulation, such as responding to pain. The authors examined whether clinically depressed subjects would show abnormal sensitivity of frontolimbic networks as they evaluated negative feedback. Depressed subjects and matched control subjects performed a video game in the laboratory as a 256-channel EEG was recorded. Speed of performance on each trial was graded with a feedback signal of A, C, or F. By 350 ms after the feedback signal, depressed subjects showed a larger medial frontal negativity for all feedback compared with control subjects with a particularly striking response to the F grade. This response was strongest for moderately depressed subjects and was attenuated for subjects who were more severely depressed. Localization analyses suggested that negative feedback engaged sources in the anterior cingulate and insular cortices. These results suggest that moderate depression may sensitize limbic networks to respond strongly to aversive events.

Parametric analysis of event-related potentials in semantic comprehension: evidence for parallel brain mechanisms.

In event-related potential (ERP) studies of cognitive processes, the electrophysiological responses are typically contrasted between experimental conditions that are taken to represent discrete categories (e.g. attended vs. unattended stimuli, or real vs. nonsense words). Because categorical variation is less powerful than continuous or parametric variation, a more effective method may be to relate continuous variation in the cognitive process with matching variation in the electrophysiological responses. We assessed continuous variation in the expectancy and meaningfulness of words in different sentence contexts by having subjects rate the words along these two dimensions. ERP averages were then created for each word by averaging the ERP across all subjects' responses to that word. A parametric principal components analysis was then conducted by multiplying the factor topographies from the temporal PCA by the parameter correlation maps for each rating parameter. This analysis showed that both expectancy and meaningfulness begin to influence lexical processing around 200 ms. Source localization of the expectancy N2 (recognition potential) pointed to a source in the left fusiform gyrus region (visual word form area). Source localization of the meaningfulness N2 (meaning recognition potential) suggested a right inferior posterior source, such as in the right cerebellum or right fusiform area. Further research with parametric analysis of dense array ERPs may clarify the multiple neural mechanisms of word recognition.