Publications

Abstract

Expectancy mechanisms are routinely used by the cognitive system in stimulus processing and in anticipation of appropriate responses. Electrophysiology research has documented negative shifts of brain activity when expectancies are violated within a local stimulus context (e.g., reading an implausible word in a sentence) or more globally between consecutive stimuli (e.g., a narrative of images with an incongruent end). In this EEG study, we examine the interaction between expectancies operating at the level of stimulus plausibility and at more global level of contextual congruency to provide evidence for, or against, a disassociation of the underlying processing mechanisms. We asked participants to verify the congruency of pairs of cross-modal stimuli (a sentence and a scene), which varied in plausibility. ANOVAs on ERP amplitudes in selected windows of interest show that congruency violation has longer-lasting (from 100 to 500 ms) and more widespread effects than plausibility violation (from 200 to 400 ms). We also observed critical interactions between these factors, whereby incongruent and implausible pairs elicited stronger negative shifts than their congruent counterpart, both early on (100–200 ms) and between 400–500 ms. Our results suggest that the integration mechanisms are sensitive to both global and local effects of expectancy in a modality independent manner. Overall, we provide novel insights into the interdependence of expectancy during meaning integration of cross-modal stimuli in a verification task

Abstract

Artificial grammar learning (AGL) has been probed with forced-choice behavioral tests (active tests). Recent attempts to probe the outcomes of learning (implicitly acquired knowledge) with eye-movement responses (passive tests) have shown null results. However, these latter studies have not tested for sensitivity effects, for example, increased eye movements on a printed violation. In this study, we tested for sensitivity effects in AGL tests with (Experiment 1) and without (Experiment 2) concurrent active tests (preference- and grammaticality classification) in an eye-tracking experiment. Eye movements discriminated between sequence types in passive tests and more so in active tests. The eye-movement profile did not differ between preference and grammaticality classification, and it resembled sensitivity effects commonly observed in natural syntax processing. Our findings show that the outcomes of implicit structured sequence learning can be characterized in eye tracking. More specifically, whole trial measures (dwell time, number of fixations) showed robust AGL effects, whereas first-pass measures (first-fixation duration) did not. Furthermore, our findings strengthen the link between artificial and natural syntax processing, and they shed light on the factors that determine performance differences in preference and grammaticality classification tests

Abstract

How can we grasp the temporal structure of events? A few studies have indicated that representations of temporal structure are acquired when there is an intention to learn, but not when learning is incidental. Response-to-stimulus intervals, uncorrelated temporal structures, unpredictable ordinal information, and lack of metrical organization have been pointed out as key obstacles to incidental temporal learning, but the literature includes piecemeal demonstrations of learning under all these circumstances. We suggest that the unacknowledged effects of ordinal load may help reconcile these conflicting findings, ordinal load referring to the cost of identifying the sequence of events (e.g., tones, locations) where a temporal pattern is embedded. In a first experiment, we manipulated ordinal load into simple and complex levels. Participants learned ordinal-simple sequences, despite their uncorrelated temporal structure and lack of metrical organization. They did not learn ordinal-complex sequences, even though there were no response-to-stimulus intervals nor unpredictable ordinal information. In a second experiment, we probed learning of ordinal-complex sequences with strong metrical organization, and again there was no learning. We conclude that ordinal load is a key obstacle to incidental temporal learning. Further analyses showed that the effect of ordinal load is to mask the expression of temporal knowledge, rather than to prevent learning.

Abstract

The suitability of the Artificial Grammar Learning (AGL) paradigm to capture relevant aspects of the acquisition of linguistic structures has been empirically tested in a number of EEG studies. Some have shown a syntax-related P600 component, but it has not been ruled out that the AGL P600 effect is a response to surface features (e.g., subsequence familiarity) rather than the underlying syntax structure. Therefore, in this study, we controlled for the surface characteristics of the test sequences (associative chunk strength) and recorded the EEG before (baseline preference classification) and
after (preference and grammaticality classification) exposure to a grammar. A typical, centroparietal P600 effect was elicited by grammatical violations after exposure, suggesting that the AGL P600 effect signals a response to structural irregularities. Moreover, preference and grammaticality classification showed a qualitatively similar ERP profile, strengthening the idea that the implicit structural mere
exposure paradigm in combination with preference classification is a suitable alternative to the traditional grammaticality classification test.

Abstract

Non-adjacent dependencies are challenging for the language learning machinery and are acquired later than adjacent dependencies. In this transcranial magnetic stimulation (TMS) study, we show that participants successfully discriminated between grammatical and non-grammatical sequences after having implicitly acquired an artificial language with crossed non-adjacent dependencies. Subsequent to transcranial magnetic stimulation of Broca’s region, discrimination was impaired compared to when a language-irrelevant control region (vertex) was stimulated. These results support the view that Broca’s region is engaged in structured sequence processing and extend previous functional neuroimaging results on artificial grammar learning (AGL) in two directions: first, the results establish that Broca’s region is a causal component in the processing of non-adjacent dependencies, and second, they show that implicit processing of non-adjacent dependencies engages Broca’s region. Since patients with lesions in Broca’s region do not always show grammatical processing difficulties, the result that Broca’s region is causally linked to processing of non-adjacent dependencies is a step towards clarification of the exact nature of syntactic deficits caused by lesions or perturbation to Broca’s region. Our findings are consistent with previous results and support a role for Broca’s region in general structured sequence processing, rather than a specific role for the processing of hierarchically organized sentence structure.

Abstract

The social significance of recognizing the person who talks to us is obvious, but the neural mechanisms that mediate talker identification are unclear. Regions along the bilateral superior temporal sulcus (STS) and the inferior frontal cortex (IFC) of the human brain are selective for voices, and they are sensitive to rapid voice changes. Although it has been proposed that voice recognition is supported by prototype-centered voice representations, the involvement of these category-selective cortical regions in the neural coding of such "mean voices" has not previously been demonstrated. Using fMRI in combination with a voice identity learning paradigm, we show that voice-selective regions are involved in the mean-based coding of voice identities. Voice typicality is encoded on a supra-individual level in the right STS along a stimulus-dependent, identity-independent (i.e., voice-acoustic) dimension, and on an intra-individual level in the right IFC along a stimulus-independent, identity-dependent (i.e., voice identity) dimension. Voice recognition therefore entails at least two anatomically separable stages, each characterized by neural mechanisms that reference the central tendencies of voice categories.

Abstract

In spoken language, pitch accent can mark certain information as focus, whereby more attentional resources are allocated to the focused information. Using functional magnetic resonance imaging, this study examined whether pitch accent, used for marking focus, recruited general attention networks during sentence comprehension. In a language task, we independently manipulated the prosody and semantic/pragmatic congruence of sentences. We found that semantic/pragmatic processing affected bilateral inferior and middle frontal gyrus. The prosody manipulation showed bilateral involvement of the superior/inferior parietal cortex, superior and middle temporal cortex, as well as inferior, middle, and posterior parts of the frontal cortex. We compared these regions with attention networks localized in an auditory spatial attention task. Both tasks activated bilateral superior/inferior parietal cortex, superior temporal cortex, and left precentral cortex. Furthermore, an interaction between prosody and congruence was observed in bilateral inferior parietal regions: for incongruent sentences, but not for congruent ones, there was a larger activation if the incongruent word carried a pitch accent, than if it did not. The common activations between the language task and the spatial attention task demonstrate that pitch accent activates a domain general attention network, which is sensitive to semantic/pragmatic aspects of language. Therefore, attention and language comprehension are highly interactive.

Abstract

Grammar acquisition is a high level cognitive function that requires the extraction of complex rules. While it has been proposed that offline time might benefit this type of rule extraction, this remains to be tested. Here, we addressed this question using an artificial grammar learning paradigm. During a short-term memory cover task, eighty-one human participants were exposed to letter sequences generated according to an unknown artificial grammar. Following a time delay of 15 min, 12 h (wake or sleep) or 24 h, participants classified novel test sequences as Grammatical or Non-Grammatical. Previous behavioral and functional neuroimaging work has shown that classification can be guided by two distinct underlying processes: (1) the holistic abstraction of the underlying grammar rules and (2) the detection of sequence chunks that appear at varying frequencies during exposure. Here, we show that classification performance improved after sleep. Moreover, this improvement was due to an enhancement of rule abstraction, while the effect of chunk frequency was unaltered by sleep. These findings suggest that sleep plays a critical role in extracting complex structure from separate but related items during integrative memory processing. Our findings stress the importance of alternating periods of learning with sleep in settings in which complex information must be acquired.

Abstract

Behavioral syntactic priming effects during sentence comprehension are typically observed only if both the syntactic structure and lexical head are repeated. In contrast, during production syntactic priming occurs with structure repetition alone, but the effect is boosted by repetition of the lexical head. We used fMRI to investigate the neuronal correlates of syntactic priming and lexical boost effects during sentence production and comprehension. The critical measure was the magnitude of fMRI adaptation to repetition of sentences in active or passive voice, with or without verb repetition. In conditions with repeated verbs, we observed adaptation to structure repetition in the left IFG and MTG, for active and passive voice. However, in the absence of repeated verbs, adaptation occurred only for passive sentences. None of the fMRI adaptation effects yielded differential effects for production versus comprehension, suggesting that sentence comprehension and production are subserved by the same neuronal infrastructure for syntactic processing.

Abstract

Repetition suppression in fMRI studies is generally thought to underlie behavioural facilitation effects (i.e., priming) and it is often used to identify the neuronal representations associated with a stimulus. However, this pays little heed to the large number of repetition enhancement effects observed under similar conditions. In this review, we identify several cognitive variables biasing repetition effects in the BOLD response towards enhancement instead of suppression. These variables are stimulus recognition, learning, attention, expectation and explicit memory. We also evaluate which models can account for these repetition effects and come to the conclusion that there is no one single model that is able to embrace all repetition enhancement effects. Accumulation, novel network formation as well as predictive coding models can all explain subsets of repetition enhancement effects.

Abstract

Participants were unknowingly exposed to complex regularities in a working memory task. The existence of implicit knowledge was subsequently inferred from a preference for stimuli with similar grammatical regularities. Several affective traits have been shown to influence
AGL performance positively, many of which are related to a tendency for automatic responding. We therefore tested whether the mindfulness trait predicted a reduction of grammatically congruent preferences, and used emotional primes to explore the influence of affect. Mindfulness was shown to correlate negatively with grammatically congruent responses. Negative primes were shown to result in faster and more negative evaluations.
We conclude that grammatically congruent preference ratings rely on habitual responses, and that our findings provide empirical evidence for the non-reactive disposition of the mindfulness trait.

Abstract

Purpose of review: The human brain supports acquisition mechanisms that can extract structural regularities implicitly from experience without the induction of an explicit model. Reber defined the process by which an individual comes to respond appropriately to the statistical structure of the input ensemble as implicit learning. He argued that the capacity to generalize to new input is based on the acquisition of abstract representations that reflect underlying structural regularities in the acquisition input. We focus this review of the implicit learning literature on studies published during 2004 and 2005. We will not review studies of repetition priming ('implicit memory'). Instead we focus on two commonly used experimental paradigms: the serial reaction time task and artificial grammar learning. Previous comprehensive reviews can be found in Seger's 1994 article and the Handbook of Implicit Learning. Recent findings: Emerging themes include the interaction between implicit and explicit processes, the role of the medial temporal lobe, developmental aspects of implicit learning, age-dependence, the role of sleep and consolidation. Summary: The attempts to characterize the interaction between implicit and explicit learning are promising although not well understood. The same can be said about the role of sleep and consolidation. Despite the fact that lesion studies have relatively consistently suggested that the medial temporal lobe memory system is not necessary for implicit learning, a number of functional magnetic resonance studies have reported medial temporal lobe activation in implicit learning. This issue merits further research. Finally, the clinical relevance of implicit learning remains to be determined.

Abstract

In this paper we investigate the neural correlates of syntactic classification of an acquired grammatical sequence structure in an event-related FMRI study. During acquisition, participants were engaged in an implicit short-term memory task without performance feedback. We manipulated the statistical frequency-based and rule-based characteristics of the classification stimuli independently in order to investigate their role in artificial grammar acquisition. The participants performed reliably above chance on the classification task. We observed a partly overlapping corticostriatal processing network activated by both manipulations including inferior prefrontal, cingulate, inferior parietal regions, and the caudate nucleus. More specifically, the left inferior frontal BA 45 and the caudate nucleus were sensitive to syntactic violations and endorsement, respectively. In contrast, these structures were insensitive to the frequency-based manipulation.

Abstract

The posterior medial parietal cortex and left prefrontal cortex (PFC) have both been implicated in the recollection of past episodes. In a previous study, we found the posterior precuneus and left lateral inferior frontal cortex to be activated during episodic source memory retrieval. This study further examines the role of posterior precuneal and left prefrontal activation during episodic source memory retrieval using a similar source memory paradigm but with longer latency between encoding and retrieval. Our results suggest that both the precuneus and the left inferior PFC are important for regeneration of rich episodic contextual associations and that the precuneus activates in tandem with the left inferior PFC during correct source retrieval. Further, results suggest that the left ventro-lateral frontal region/ frontal operculum is involved in searching for task-relevant information (BA 47) and subsequent monitoring or scrutiny (BA 44/45) while regions in the dorsal inferior frontal cortex are important for information selection (BA 45/46).

Abstract

Recent FMRI studies indicate that language related brain regions are engaged in artificial grammar (AG) processing. In the present study we investigate the Reber grammar by means of formal analysis and network simulations. We outline a new method for describing the network dynamics and propose an approach to grammar extraction based on the state-space dynamics of the network. We conclude that statistical frequency-based and rule-based acquisition procedures can be viewed as complementary perspectives on grammar learning, and more generally, that classical cognitive models can be viewed as a special case of a dynamical systems perspective on information processing

Abstract

We present two simple arguments for the potential relevance of a neurobiological analogue of the finite-state architecture. The first assumes the classical cognitive framework, is wellknown, and is based on the assumption that the brain is finite with respect to its memory organization. The second is formulated within a general dynamical systems framework and is based on the assumption that the brain sustains some level of noise and/or does not utilize infinite precision processing. We briefly review the classical cognitive framework based on Church–Turing computability and non-classical approaches based on analog processing in dynamical systems. We conclude that the dynamical neurobiological analogue of the finitestate architecture appears to be relevant, at least at an implementational level, for cognitive brain systems