Publications

Abstract

This study investigated two questions. One is: To what degree is sentence processing beyond single words independent of the input modality (speech vs. reading)? The second question is: Which parts of the network recruited by both modalities is sensitive to syntactic complexity? These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere frontotemporoparietal network was found to be supramodal in nature, i.e., independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior temporal lobe (LaTL) showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior temporal lobe, posterior MTG, and left inferior parietal lobe (LIPL) all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.

Abstract

Language processing involves the ability to store and integrate pieces of
information in working memory over short periods of time. According to
the dominant view, information is maintained through sustained, elevated
neural activity. Other work has argued that short-term synaptic facilitation
can serve as a substrate of memory. Here, we propose an account where
memory is supported by intrinsic plasticity that downregulates neuronal
firing rates. Single neuron responses are dependent on experience and we
show through simulations that these adaptive changes in excitability pro-
vide memory on timescales ranging from milliseconds to seconds. On this
account, spiking activity writes information into coupled dynamic variables
that control adaptation and move at slower timescales than the membrane
potential. From these variables, information is continuously read back into
the active membrane state for processing. This neuronal memory mech-
anism does not rely on persistent activity, excitatory feedback, or synap-
tic plasticity for storage. Instead, information is maintained in adaptive
conductances that reduce firing rates and can be accessed directly with-
out cued retrieval. Memory span is systematically related to both the time
constant of adaptation and baseline levels of neuronal excitability. Inter-
ference effects within memory arise when adaptation is long-lasting. We
demonstrate that this mechanism is sensitive to context and serial order
which makes it suitable for temporal integration in sequence processing
within the language domain. We also show that it enables the binding of
linguistic features over time within dynamic memory registers. This work
provides a step towards a computational neurobiology of language.

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.