Publications

Abstract

Reinstatement of memory-related neural activity measured with high temporal precision potentially provides a useful index for real-time monitoring of the timing of activation of memory content during cognitive processing. The utility of such an index extends to any situation where one is interested in the (relative) timing of activation of different sources of information in memory, a paradigm case of which is tracking lexical activation during language processing. Essential for this approach is that memory reinstatement effects are robust, so that their absence (in the average) definitively indicates that no lexical activation is present. We used electroencephalography to test the robustness of a reported subsequent memory finding involving reinstatement of frequency-specific entrained oscillatory brain activity during subsequent recognition. Participants learned lists of words presented on a background flickering at either 6 or 15 Hz to entrain a steady-state brain response. Target words subsequently presented on a non-flickering background that were correctly identified as previously seen exhibited reinstatement effects at both entrainment frequencies. Reliability of these statistical inferences was however critically dependent on the approach used for multiple comparisons correction. We conclude that effects are not robust enough to be used as a reliable index of lexical activation during language processing.

Abstract

Oscillatory neural dynamics have been steadily receiving more attention as a robust and temporally precise signature of network activity related to language processing. We have recently proposed that oscillatory dynamics in the beta and gamma frequency ranges measured during sentence-level comprehension might be best explained from a predictive coding perspective. Under our proposal we related beta oscillations to both the maintenance/change of the neural network configuration responsible for the construction and representation of sentence-level meaning, and to top–down predictions about upcoming linguistic input based on that sentence-level meaning. Here we zoom in on these particular aspects of our proposal, and discuss both old and new supporting evidence. Finally, we present some preliminary magnetoencephalography data from an experiment comparing Dutch subject- and object-relative clauses that was specifically designed to test our predictive coding framework. Initial results support the first of the two suggested roles for beta oscillations in sentence-level language comprehension.

Abstract

For native speakers, many studies suggest a link between oscillatory neural activity in the beta frequency range and syntactic processing. For late second language (L2) learners on the other hand, the extent to which the neural architecture supporting syntactic processing is similar to or different from that of native speakers is still unclear. In a series of four experiments, we used electroencephalography to investigate the link between beta oscillatory activity and the processing of grammatical gender agreement in Dutch determiner-noun pairs, for Dutch native speakers, and for German L2 learners of Dutch. In Experiment 1 we show that for native speakers, grammatical gender agreement violations are yet another among many syntactic factors that modulate beta oscillatory activity during sentence comprehension. Beta power is higher for grammatically acceptable target words than for those that mismatch in grammatical gender with their preceding determiner. In Experiment 2 we observed no such beta modulations for L2 learners, irrespective of whether trials were sorted according to objective or subjective syntactic correctness. Experiment 3 ruled out that the absence of a beta effect for the L2 learners in Experiment 2 was due to repetition of the target nouns in objectively correct and incorrect determiner-noun pairs. Finally, Experiment 4 showed that when L2 learners are required to explicitly focus on grammatical information, they show modulations of beta oscillatory activity, comparable to those of native speakers, but only when trials are sorted according to participants’ idiosyncratic lexical representations of the grammatical gender of target nouns. Together, these findings suggest that beta power in L2 learners is sensitive to violations of grammatical gender agreement, but only when the importance of grammatical information is highlighted, and only when participants' subjective lexical representations are taken into account.

Abstract

There is a growing literature investigating the relationship between oscillatory neural dynamics measured using EEG and/or MEG, and sentence-level language comprehension. Recent proposals have suggested a strong link between predictive coding accounts of the hierarchical flow of information in the brain, and oscillatory neural dynamics in the beta and gamma frequency ranges. We propose that findings relating beta and gamma oscillations to sentence-level language comprehension might be unified under such a predictive coding account. Our suggestion is that oscillatory activity in the beta frequency range may reflect both the active maintenance of the current network configuration responsible for representing the sentence-level meaning under construction, and the top-down propagation of predictions to hierarchically lower processing levels based on that representation. In addition, we suggest that oscillatory activity in the low and middle gamma range reflect the matching of top-down predictions with bottom-up linguistic input, while evoked high gamma might reflect the propagation of bottom-up prediction errors to higher levels of the processing hierarchy. We also discuss some of the implications of this predictive coding framework, and we outline ideas for how these might be tested experimentally

Abstract

The role of neuronal oscillations during language comprehension is not yet well understood. In this paper we review and reinterpret the functional roles of beta- and gamma-band oscillatory activity during language comprehension at the sentence and discourse level. We discuss the evidence in favor of a role for beta and gamma in unification (the unification hypothesis), and in light of mounting evidence that cannot be accounted for under this hypothesis, we explore an alternative proposal linking beta and gamma oscillations to maintenance and prediction (respectively) during language comprehension. Our maintenance/prediction hypothesis is able to account for most of the findings that are currently available relating beta and gamma oscillations to language comprehension, and is in good agreement with other proposals about the roles of beta and gamma in domain-general cognitive processing. In conclusion we discuss proposals for further testing and comparing the prediction and unification hypotheses.

Abstract

EEG mu rhythms (8-13Hz) recorded at fronto-central electrodes are generally considered as markers of motor cortical activity in humans, because they are modulated when participants perform an action, when they observe another’s action or even when they imagine performing an action. In this study, we analyzed the time-frequency (TF) modulation of mu rhythms while participants read action language (“You will cut the strawberry cake”), abstract language (“You will doubt the patient´s argument”), and perceptive language (“You will notice the bright day”). The results indicated that mu suppression at fronto-central sites is associated with action language rather than with abstract or perceptive language. Also, the largest difference between conditions occurred quite late in the sentence, while reading the first noun, (contrast Action vs. Abstract), or the second noun following the action verb (contrast Action vs. Perceptive). This suggests that motor activation is associated with the integration of words across the sentence beyond the lexical processing of the action verb. Source reconstruction localized mu suppression associated with action sentences in premotor cortex (BA 6). The present study suggests (1) that the understanding of action language activates motor networks in the human brain, and (2) that this activation occurs online based on semantic integration across multiple words in the sentence.