Publications

Displaying 1 - 21 of 21
  • Andics, A., McQueen, J. M., & Petersson, K. M. (2013). Mean-based neural coding of voices. NeuroImage, 79, 351-360. doi:10.1016/j.neuroimage.2013.05.002.

    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.
  • Kristensen, L. B., Wang, L., Petersson, K. M., & Hagoort, P. (2013). The interface between language and attention: Prosodic focus marking recruits a general attention network in spoken language comprehension. Cerebral Cortex, 23, 1836-1848. doi:10.1093/cercor/bhs164.

    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.

    Additional information

    Kirstensen_Cer_Cor_Suppl_Mat.doc
  • Nieuwenhuis, I. L., Folia, V., Forkstam, C., Jensen, O., & Petersson, K. M. (2013). Sleep promotes the extraction of grammatical rules. PLoS One, 8(6): e65046. doi:10.1371/journal.pone.0065046.

    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.
  • Segaert, K., Kempen, G., Petersson, K. M., & Hagoort, P. (2013). Syntactic priming and the lexical boost effect during sentence production and sentence comprehension: An fMRI study. Brain and Language, 124, 174-183. doi:10.1016/j.bandl.2012.12.003.

    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.

    Additional information

    Segaert_Supplementary_data_2013.docx
  • Segaert, K., Weber, K., De Lange, F., Petersson, K. M., & Hagoort, P. (2013). The suppression of repetition enhancement: A review of fMRI studies. Neuropsychologia, 51, 59-66. doi:10.1016/j.neuropsychologia.2012.11.006.

    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.
  • Whitmarsh, S., Udden, J., Barendregt, H., & Petersson, K. M. (2013). Mindfulness reduces habitual responding based on implicit knowledge: Evidence from artificial grammar learning. Consciousness and Cognition, (3), 833-845. doi:10.1016/j.concog.2013.05.007.

    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.
  • Folia, V., Uddén, J., Forkstam, C., Ingvar, M., Hagoort, P., & Petersson, K. M. (2008). Implicit learning and dyslexia. Annals of the New York Academy of Sciences, 1145, 132-150. doi:10.1196/annals.1416.012.

    Abstract

    Several studies have reported an association between dyslexia and implicit learning deficits. It has been suggested that the weakness in implicit learning observed in dyslexic individuals may be related to sequential processing and implicit sequence learning. In the present article, we review the current literature on implicit learning and dyslexia. We describe a novel, forced-choice structural "mere exposure" artificial grammar learning paradigm and characterize this paradigm in normal readers in relation to the standard grammaticality classification paradigm. We argue that preference classification is a more optimal measure of the outcome of implicit acquisition since in the preference version participants are kept completely unaware of the underlying generative mechanism, while in the grammaticality version, the subjects have, at least in principle, been informed about the existence of an underlying complex set of rules at the point of classification (but not during acquisition). On the basis of the "mere exposure effect," we tested the prediction that the development of preference will correlate with the grammaticality status of the classification items. In addition, we examined the effects of grammaticality (grammatical/nongrammatical) and associative chunk strength (ACS; high/low) on the classification tasks (preference/grammaticality). Using a balanced ACS design in which the factors of grammaticality (grammatical/nongrammatical) and ACS (high/low) were independently controlled in a 2 × 2 factorial design, we confirmed our predictions. We discuss the suitability of this task for further investigation of the implicit learning characteristics in dyslexia.
  • Forkstam, C., Elwér, A., Ingvar, M., & Petersson, K. M. (2008). Instruction effects in implicit artificial grammar learning: A preference for grammaticality. Brain Research, 1221, 80-92. doi:10.1016/j.brainres.2008.05.005.

    Abstract

    Human implicit learning can be investigated with implicit artificial grammar learning, a paradigm that has been proposed as a simple model for aspects of natural language acquisition. In the present study we compared the typical yes–no grammaticality classification, with yes–no preference classification. In the case of preference instruction no reference to the underlying generative mechanism (i.e., grammar) is needed and the subjects are therefore completely uninformed about an underlying structure in the acquisition material. In experiment 1, subjects engaged in a short-term memory task using only grammatical strings without performance feedback for 5 days. As a result of the 5 acquisition days, classification performance was independent of instruction type and both the preference and the grammaticality group acquired relevant knowledge of the underlying generative mechanism to a similar degree. Changing the grammatical stings to random strings in the acquisition material (experiment 2) resulted in classification being driven by local substring familiarity. Contrasting repeated vs. non-repeated preference classification (experiment 3) showed that the effect of local substring familiarity decreases with repeated classification. This was not the case for repeated grammaticality classifications. We conclude that classification performance is largely independent of instruction type and that forced-choice preference classification is equivalent to the typical grammaticality classification.
  • Petersson, K. M. (2008). On cognition, structured sequence processing, and adaptive dynamical systems. American Institute of Physics Conference Proceedings, 1060(1), 195-200.

    Abstract

    Cognitive neuroscience approaches the brain as a cognitive system: a system that functionally is conceptualized in terms of information processing. We outline some aspects of this concept and consider a physical system to be an information processing device when a subclass of its physical states can be viewed as representational/cognitive and transitions between these can be conceptualized as a process operating on these states by implementing operations on the corresponding representational structures. We identify a generic and fundamental problem in cognition: sequentially organized structured processing. Structured sequence processing provides the brain, in an essential sense, with its processing logic. In an approach addressing this problem, we illustrate how to integrate levels of analysis within a framework of adaptive dynamical systems. We note that the dynamical system framework lends itself to a description of asynchronous event-driven devices, which is likely to be important in cognition because the brain appears to be an asynchronous processing system. We use the human language faculty and natural language processing as a concrete example through out.
  • De Rover, M., Petersson, K. M., Van der Werf, S. P., Cools, A. R., Berger, H. J., & Fernández, G. (2008). Neural correlates of strategic memory retrieval: Differentiating between spatial-associative and temporal-associative strategies. Human Brain Mapping, 29, 1068-1079. doi:10.1002/hbm.20445.

    Abstract

    Remembering complex, multidimensional information typically requires strategic memory retrieval, during which information is structured, for instance by spatial- or temporal associations. Although brain regions involved in strategic memory retrieval in general have been identified, differences in retrieval operations related to distinct retrieval strategies are not well-understood. Thus, our aim was to identify brain regions whose activity is differentially involved in spatial-associative and temporal-associative retrieval. First, we showed that our behavioral paradigm probing memory for a set of object-location associations promoted the use of a spatial-associative structure following an encoding condition that provided multiple associations to neighboring objects (spatial-associative condition) and the use of a temporal- associative structure following another study condition that provided predominantly temporal associations between sequentially presented items (temporal-associative condition). Next, we used an adapted version of this paradigm for functional MRI, where we contrasted brain activity related to the recall of object-location associations that were either encoded in the spatial- or the temporal-associative condition. In addition to brain regions generally involved in recall, we found that activity in higher-order visual regions, including the fusiform gyrus, the lingual gyrus, and the cuneus, was relatively enhanced when subjects used a spatial-associative structure for retrieval. In contrast, activity in the globus pallidus and the thalamus was relatively enhanced when subjects used a temporal-associative structure for retrieval. In conclusion, we provide evidence for differential involvement of these brain regions related to different types of strategic memory retrieval and the neural structures described play a role in either spatial-associative or temporal-associative memory retrieval.
  • Scheeringa, R., Bastiaansen, M. C. M., Petersson, K. M., Oostenveld, R., Norris, D. G., & Hagoort, P. (2008). Frontal theta EEG activity correlates negatively with the default mode network in resting state. International Journal of Psychophysiology, 67, 242-251. doi:10.1016/j.ijpsycho.2007.05.017.

    Abstract

    We used simultaneously recorded EEG and fMRI to investigate in which areas the BOLD signal correlates with frontal theta power changes, while subjects were quietly lying resting in the scanner with their eyes open. To obtain a reliable estimate of frontal theta power we applied ICA on band-pass filtered (2–9 Hz) EEG data. For each subject we selected the component that best matched the mid-frontal scalp topography associated with the frontal theta rhythm. We applied a time-frequency analysis on this component and used the time course of the frequency bin with the highest overall power to form a regressor that modeled spontaneous fluctuations in frontal theta power. No significant positive BOLD correlations with this regressor were observed. Extensive negative correlations were observed in the areas that together form the default mode network. We conclude that frontal theta activity can be seen as an EEG index of default mode network activity.
  • Tendolkar, I., Arnold, J., Petersson, K. M., Weis, S., Brockhaus-Dumke, A., Van Eijndhoven, P., Buitelaar, J., & Fernandez, G. (2008). Contributions of the medial temporal lobe to declarative memory retrieval: Manipulating the amount of contextual retrieval. Learning and Memory, 15(9), 611-617. doi:10.1101/lm.916708.

    Abstract

    We investigated how the hippocampus and its adjacent mediotemporal structures contribute to contextual and noncontextual declarative memory retrieval by manipulating the amount of contextual information across two levels of the same contextual dimension in a source memory task. A first analysis identified medial temporal lobe (MTL) substructures mediating either contextual or noncontextual retrieval. A linearly weighted analysis elucidated which MTL substructures show a gradually increasing neural activity, depending on the amount of contextual information retrieved. A hippocampal engagement was found during both levels of source memory but not during item memory retrieval. The anterior MTL including the perirhinal cortex was only engaged during item memory retrieval by an activity decrease. Only the posterior parahippocampal cortex showed an activation increasing with the amount of contextual information retrieved. If one assumes a roughly linear relationship between the blood-oxygenation level-dependent (BOLD) signal and the associated cognitive process, our results suggest that the posterior parahippocampal cortex is involved in contextual retrieval on the basis of memory strength while the hippocampus processes representations of item-context binding. The anterior MTL including perirhinal cortex seems to be particularly engaged in familiarity-based item recognition. If one assumes departure from linearity, however, our results can also be explained by one-dimensional modulation of memory strength.
  • Uddén, J., Folia, V., Forkstam, C., Ingvar, M., Fernández, G., Overeem, S., Van Elswijk, G., Hagoort, P., & Petersson, K. M. (2008). The inferior frontal cortex in artificial syntax processing: An rTMS study. Brain Research, 1224, 69-78. doi:10.1016/j.brainres.2008.05.070.

    Abstract

    The human capacity to implicitly acquire knowledge of structured sequences has recently been investigated in artificial grammar learning using functional magnetic resonance imaging. It was found that the left inferior frontal cortex (IFC; Brodmann's area (BA) 44/45) was related to classification performance. The objective of this study was to investigate whether the IFC (BA 44/45) is causally related to classification of artificial syntactic structures by means of an off-line repetitive transcranial magnetic stimulation (rTMS) paradigm. We manipulated the stimulus material in a 2 × 2 factorial design with grammaticality status and local substring familiarity as factors. The participants showed a reliable effect of grammaticality on classification of novel items after 5days of exposure to grammatical exemplars without performance feedback in an implicit acquisition task. The results show that rTMS of BA 44/45 improves syntactic classification performance by increasing the rejection rate of non-grammatical items and by shortening reaction times of correct rejections specifically after left-sided stimulation. A similar pattern of results is observed in FMRI experiments on artificial syntactic classification. These results suggest that activity in the inferior frontal region is causally related to artificial syntax processing.
  • Van Wingen, G. A., Van Broekhoven, F., Verkes, R. J., Petersson, K. M., Bäckström, T., Buitelaar, J. K., & Fernández, G. (2008). Progesterone selectively increases amygdala reactivity in women. Molecular Psychiatry, 13, 325-333. doi:doi:10.1038/sj.mp.4002030.

    Abstract

    The acute neural effects of progesterone are mediated by its neuroactive metabolites allopregnanolone and pregnanolone. These neurosteroids potentiate the inhibitory actions of c-aminobutyric acid (GABA). Progesterone is known to produce anxiolytic effects in animals, but recent animal studies suggest that pregnanolone increases anxiety after a period of low allopregnanolone concentration. This effect is potentially mediated by the amygdala and related to the negative mood symptoms in humans that are observed during increased allopregnanolone levels. Therefore, we investigated with functional magnetic resonance imaging (MRI) whether a single progesterone administration to healthy young women in their follicular phase modulates the amygdala response to salient, biologically relevant stimuli. The progesterone administration increased the plasma concentrations of progesterone and allopregnanolone to levels that are reached during the luteal phase and early pregnancy. The imaging results show that progesterone selectively increased amygdala reactivity. Furthermore, functional connectivity analyses indicate that progesterone modulated functional coupling of the amygdala with distant brain regions. These results reveal a neural mechanism by which progesterone may mediate adverse effects on anxiety and mood.
  • Carlsson, K., Petrovic, P., Skare, S., Petersson, K. M., & Ingvar, M. (2000). Tickling expectations: Neural processing in anticipation of a sensory stimulus. Journal of Cognitive Neuroscience, 12(4), 691-703. doi:10.1162/089892900562318.
  • Ingvar, M., & Petersson, K. M. (2000). Functional maps and brain networks. In A. W. Toga (Ed.), Brain mapping: The systems (pp. 111-140). San Diego: Academic Press.
  • Lansner, A., Sandberg, A., Petersson, K. M., & Ingvar, M. (2000). On forgetful attractor network memories. In H. Malmgren, M. Borga, & L. Niklasson (Eds.), Artificial neural networks in medicine and biology: Proceedings of the ANNIMAB-1 Conference, Göteborg, Sweden, 13-16 May 2000 (pp. 54-62). Heidelberg: Springer Verlag.

    Abstract

    A recurrently connected attractor neural network with a Hebbian learning rule is currently our best ANN analogy for a piece cortex. Functionally biological memory operates on a spectrum of time scales with regard to induction and retention, and it is modulated in complex ways by sub-cortical neuromodulatory systems. Moreover, biological memory networks are commonly believed to be highly distributed and engage many co-operating cortical areas. Here we focus on the temporal aspects of induction and retention of memory in a connectionist type attractor memory model of a piece of cortex. A continuous time, forgetful Bayesian-Hebbian learning rule is described and compared to the characteristics of LTP and LTD seen experimentally. More generally, an attractor network implementing this learning rule can operate as a long-term, intermediate-term, or short-term memory. Modulation of the print-now signal of the learning rule replicates some experimental memory phenomena, like e.g. the von Restorff effect.
  • Petersson, K. M., Reis, A., Askelöf, S., Castro-Caldas, A., & Ingvar, M. (2000). Language processing modulated by literacy: A network analysis of verbal repetition in literate and illiterate subjects. Journal of Cognitive Neuroscience, 12(3), 364-382. doi:10.1162/089892900562147.
  • Petrovic, P., Petersson, K. M., Ghatan, P., Stone-Elander, S., & Ingvar, M. (2000). Pain related cerebral activation is altered by a distracting cognitive task. Pain, 85, 19-30.

    Abstract

    It has previously been suggested that the activity in sensory regions of the brain can be modulated by attentional mechanisms during parallel cognitive processing. To investigate whether such attention-related modulations are present in the processing of pain, the regional cerebral blood ¯ow was measured using [15O]butanol and positron emission tomography in conditions involving both pain and parallel cognitive demands. The painful stimulus consisted of the standard cold pressor test and the cognitive task was a computerised perceptual maze test. The activations during the maze test reproduced findings in previous studies of the same cognitive task. The cold pressor test evoked signi®cant activity in the contralateral S1, and bilaterally in the somatosensory association areas (including S2), the ACC and the mid-insula. The activity in the somatosensory association areas and periaqueductal gray/midbrain were significantly modified, i.e. relatively decreased, when the subjects also were performing the maze task. The altered activity was accompanied with significantly lower ratings of pain during the cognitive task. In contrast, lateral orbitofrontal regions showed a relative increase of activity during pain combined with the maze task as compared to only pain, which suggests the possibility of the involvement of frontal cortex in modulation of regions processing pain
  • Sandberg, A., Lansner, A., Petersson, K. M., & Ekeberg, Ö. (2000). A palimpsest memory based on an incremental Bayesian learning rule. Neurocomputing, 32(33), 987-994. doi:10.1016/S0925-2312(00)00270-8.

    Abstract

    Capacity limited memory systems need to gradually forget old information in order to avoid catastrophic forgetting where all stored information is lost. This can be achieved by allowing new information to overwrite old, as in the so-called palimpsest memory. This paper describes a new such learning rule employed in an attractor neural network. The network does not exhibit catastrophic forgetting, has a capacity dependent on the learning time constant and exhibits recency e!ects in retrieval
  • Sandberg, A., Lansner, A., Petersson, K. M., & Ekeberg, Ö. (2000). A palimpsest memory based on an incremental Bayesian learning rule. In J. M. Bower (Ed.), Computational Neuroscience: Trends in Research 2000 (pp. 987-994). Amsterdam: Elsevier.

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