Publications

Abstract

Naming speed deficits are well documented in developmental dyslexia, expressed by slower naming times and more errors in response to familiar items. Here we used event-related potentials (ERPs) to examine at what processing level the deficits in dyslexia emerge during a discrete-naming task. Dyslexic and skilled adult control readers performed a primed object-naming task, in which the relationship between the prime and the target was manipulated along perceptual, semantic and phonological dimensions. A 3×2 design that crossed Relationship Type (Visual, Phonemic Onset, and Semantic) with Relatedness (Related and Unrelated) was used. An attenuated N/P190 – indexing early visual processing – and N300 – which index late visual processing – was observed to pictures preceded by perceptually related (vs. unrelated) primes in the control but not in the dyslexic group. These findings suggest suboptimal processing in early stages of object processing in dyslexia, when integration and mapping of perceptual information to a more form-specific percept in memory take place. On the other hand, both groups showed an N400 effect associated with semantically related pictures (vs. unrelated), taken to reflect intact integration of semantic similarities in both dyslexic and control readers. We also found an electrophysiological effect of phonological priming in the N400 range – that is, an attenuated N400 to objects preceded by phonemic related primes vs. unrelated – while it showed a more widespread distributed and more pronounced over the right hemisphere in the dyslexics. Topographic differences between groups might have originated from a word form encoding process with different characteristics in dyslexics compared to control readers.

Abstract

his study investigates the interaction between surface and colour knowledge information during object recognition. In two different experiments, participants were instructed to decide whether two presented stimuli belonged to the same object identity. On the non-matching trials, we manipulated the shape and colour knowledge information activated by the two stimuli by creating four different stimulus pairs: (1) similar in shape and colour (e.g. TOMATO–APPLE); (2) similar in shape and dissimilar in colour (e.g. TOMATO–COCONUT); (3) dissimilar in shape and similar in colour (e.g. TOMATO–CHILI PEPPER) and (4) dissimilar in both shape and colour (e.g. TOMATO–PEANUT). The object pictures were presented in typical and atypical colours and also in black-and-white. The interaction between surface and colour knowledge showed to be contingent upon shape information: while colour knowledge is more important for recognising structurally similar shaped objects, surface colour is more prominent for recognising structurally dissimilar shaped objects.

Abstract

During oral reading, the eyes tend to be ahead of the voice (eye-voice span, EVS). It has been hypothesized that the extent to which this happens depends on the automaticity of reading processes, namely on the speed of print-to-sound conversion. We tested whether EVS is affected by another automaticity component – immunity from interference. To that end, we manipulated word familiarity (high-frequency, lowfrequency, and pseudowords, PW) and word length as proxies of immunity from interference, and we used linear mixed effects models to measure the effects of both variables on the time interval at which readers do parallel processing by gazing at word N C 1 while not having articulated word N yet (offset EVS). Parallel processing was enhanced by automaticity, as shown by familiarity length interactions on offset EVS, and it was impeded by lack of automaticity, as shown by the transformation of offset EVS into voice-eye span (voice ahead of the offset of the eyes) in PWs. The relation between parallel processing and automaticity was strengthened by the fact that offset EVS predicted reading velocity. Our findings contribute to understand how the offset EVS, an index that is obtained in oral reading, may tap into different components of automaticity that underlie reading ability, oral or silent. In addition, we compared the duration of the offset EVS with the average reference duration of stages in word production, and we saw that the offset EVS may accommodate for more than the articulatory programming stage of word N.

Abstract

Two different forms of parafoveal dysfunction have been hypothesized as core deficits of dyslexic individuals: reduced parafoveal preview benefits (“too little parafovea”) and increased costs of parafoveal load (“too much parafovea”). We tested both hypotheses in a single eye-tracking experiment using a modified serial rapid automatized naming (RAN) task. Comparisons between dyslexic and non-dyslexic adults showed reduced parafoveal preview benefits in dyslexics, without increased costs of parafoveal load. Reduced parafoveal preview benefits were observed in a naming task, but not in a silent letter-finding task, indicating that the parafoveal dysfunction may be consequent to the overload with extracting phonological information from orthographic input. Our results suggest that dyslexics’ parafoveal dysfunction is not based on strict visuo-attentional factors, but nevertheless they stress the importance of extra-phonological processing. Furthermore, evidence of reduced parafoveal preview benefits in dyslexia may help understand why serial RAN is an important reading predictor in adulthood

Abstract

When learning a new language, we build brain networks to process and represent the acquired words and syntax and integrate these with existing language representations. It is an open question whether the same or different neural mechanisms are involved in learning and processing a novel language compared to the native language(s). Here we investigated the neural repetition effects of repeating known and novel word orders while human subjects were in the early stages of learning a new language. Combining a miniature language with a syntactic priming paradigm, we examined the neural correlates of language learning online using functional magnetic resonance imaging (fMRI). In left inferior frontal gyrus (LIFG) and posterior temporal cortex the repetition of novel syntactic structures led to repetition enhancement, while repetition of known structures resulted in repetition suppression. Additional verb repetition led to an
increase in the syntactic repetition enhancement effect in language-related brain regions. Similarly the repetition of verbs led to repetition enhancement effects in areas related to lexical and semantic processing, an effect that continued to increase in a subset of these regions. Repetition enhancement might reflect a mechanism to build and strengthen a neural network to process novel syntactic structures and lexical items. By contrast, the observed repetition suppression points to overlapping neural mechanisms for native and new language constructions when these have sufficient structural similarities.

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

Theeffects of spatial filtering in functional magnetic resonance imaging were investigated by reevaluating the data of a previous study of episodic memory encoding at 2 × 2 × 4-mm3 resolution with use of a SPM99 analysis involving a Gaussian kernel of 8-mm full width at half maximum. In addition, a multisubject analysis of activated regions was performed by normalizing the functional images to an approximate Talairach brain atlas. In individual subjects, spatial filtering merged activations in anatomically separated brain regions. Moreover, small foci of activated pixels which originated from veins became blurred and hence indistinguishable from parenchymal responses. The multisubject analysis resulted in activation of the hippocampus proper, a finding which could not be confirmed by the activation maps obtained at high resolution. It is concluded that the validity of multisubject fMRI analyses can be considerably improved by first analyzing individual data sets at optimum resolution to assess the effects of spatial filtering and minimize the risk of signal contamination by macroscopically visible vessels.

Abstract

There is much evidence for the existence of multiple memory systems. However, it has been argued that tasks assumed to reflect different memory systems share basic processing components and are mediated by overlapping neural systems. Here we used multivariate analysis of PET-data to analyze similarities and differences in brain activity for multiple tests of working memory, semantic memory, and episodic memory. The results from two experiments revealed between-systems differences, but also between-systems similarities and within-system differences. Specifically, support was obtained for a task-general working-memory network that may underlie active maintenance. Premotor and parietal regions were salient components of this network. A common network was also identified for two episodic tasks, cued recall and recognition, but not for a test of autobiographical memory. This network involved regions in right inferior and polar frontal cortex, and lateral and medial parietal cortex. Several of these regions were also engaged during the working-memory tasks, indicating shared processing for episodic and working memory. Fact retrieval and synonym generation were associated with increased activity in left inferior frontal and middle temporal regions and right cerebellum. This network was also associated with the autobiographical task, but not with living/non-living classification, and may reflect elaborate retrieval of semantic information. Implications of the present results for the classification of memory tasks with respect to systems and/or processes are discussed.

Abstract

It has been suggested that placebo analgesia involves both higher order cognitive networks and endogenous opioid systems. The rostral anterior cingulate cortex (rACC) and the brainstem are implicated in opioid analgesia, suggesting a similar role for these structures in placebo analgesia. Using positron emission tomography, we confirmed that both opioid and placebo analgesia are associated with increased activity in the rACC. We also observed a covariation between the activity in the rACC and the brainstem during both opioid and placebo analgesia, but not during the pain-only condition. These findings indicate a related neural mechanism in placebo and opioid analgesia.

Abstract

It has been suggested that placebo analgesia involves both higher order cognitive networks and endogenous opioid systems. The rostral anterior cingulate cortex (rACC) and the brainstem are implicated in opioid analgesia, suggesting a similar role for these structures in placebo analgesia. Using positron emission tomography, we confirmed that both opioid and placebo analgesia are associated with increased activity in the rACC. We also observed a covariation between the activity in the rACC and the brainstem during both opioid and placebo analgesia, but not during the pain-only condition. These findings indicate a related neural mechanism in placebo and opioid analgesia.

Abstract

Several functional imaging studies of pain, using a number of different experimental paradigms and a variety of reference states, have failed to detect activations in the somatosensory cortices, while other imaging studies of pain have reported significant activations in these regions. The role of the somatosensory areas in pain processing has therefore been debated. In the present study the left hand was immersed in painfully cold water (standard cold pressor test) and in nonpainfully cold water during 2 min, and PET-scans were obtained either during the first or the second minute of stimulation. We observed no significant increase of activity in the somatosensory regions when the painful conditions were directly compared with the control conditions. In order to better understand the role of the primary somatosensory cortex (S1) in pain processing we used a regression analysis to study the relation between a ROI (region of interest) in the somatotopic S1-area for the stimulated hand and other regions known to be involved in pain processing. We hypothesized that although no increased activity was observed in the S1 during pain, this region would change its covariation pattern during noxious input as compared to the control stimulation if it is involved in or affected by the processing of pain. In the nonpainful cold conditions widespread regions of the ipsilateral and contralateral somatosensory cortex showed a positive covariation with the activity in the S1-ROI. However, during the first and second minute of pain this regression was significantly attenuated. During the second minute of painful stimulation there was a significant positive covariation between the activity in the S1-ROI and the other regions that are known to be involved in pain processing. Importantly, this relation was significantly stronger for the insula and the orbitofrontal cortex bilaterally when compared to the nonpainful state. The results indicate that the S1-cortex may be engaged in or affected by the processing of pain although no differential activity is observed when pain is compared with the reference condition.

Abstract

A realtime online learning system with capacity limits needs to gradually forget old information in order to avoid catastrophic forgetting. This can be achieved by allowing new information to overwrite old, as in a so-called palimpsest memory. This paper describes an incremental learning rule based on the Bayesian confidence propagation neural network that has palimpsest properties when employed in an attractor neural network. The network does not suffer from catastrophic forgetting, has a capacity dependent on the learning time constant and exhibits faster convergence for newer patterns.