Publications

Displaying 1 - 10 of 10
  • Lopopolo, A., Van de Bosch, A., Petersson, K. M., & Willems, R. M. (2021). Distinguishing syntactic operations in the brain: Dependency and phrase-structure parsing. Neurobiology of Language, 2(1), 152-175. doi:10.1162/nol_a_00029.

    Abstract

    Finding the structure of a sentence — the way its words hold together to convey meaning — is a fundamental step in language comprehension. Several brain regions, including the left inferior frontal gyrus, the left posterior superior temporal gyrus, and the left anterior temporal pole, are supposed to support this operation. The exact role of these areas is nonetheless still debated. In this paper we investigate the hypothesis that different brain regions could be sensitive to different kinds of syntactic computations. We compare the fit of phrase-structure and dependency structure descriptors to activity in brain areas using fMRI. Our results show a division between areas with regard to the type of structure computed, with the left ATP and left IFG favouring dependency structures and left pSTG favouring phrase structures.
  • Araújo, S., Faísca, L., Bramão, I., Reis, A., & Petersson, K. M. (2015). Lexical and sublexical orthographic processing: An ERP study with skilled and dyslexic adult readers. Brain and Language, 141, 16-27. doi:10.1016/j.bandl.2014.11.007.

    Abstract

    This ERP study investigated the cognitive nature of the P1–N1 components during orthographic processing. We used an implicit reading task with various types of stimuli involving different amounts of sublexical or lexical orthographic processing (words, pseudohomophones, pseudowords, nonwords, and symbols), and tested average and dyslexic readers. An orthographic regularity effect (pseudowords– nonwords contrast) was observed in the average but not in the dyslexic group. This suggests an early sensitivity to the dependencies among letters in word-forms that reflect orthographic structure, while the dyslexic brain apparently fails to be appropriately sensitive to these complex features. Moreover, in the adults the N1-response may already reflect lexical access: (i) the N1 was sensitive to the familiar vs. less familiar orthographic sequence contrast; (ii) and early effects of the phonological form (words-pseudohomophones contrast) were also found. Finally, the later N320 component was attenuated in the dyslexics, suggesting suboptimal processing in later stages of phonological analysis.
  • Araújo, S., Reis, A., Petersson, K. M., & Faísca, L. (2015). Rapid automatized naming and reading performance: A meta-analysis. Journal of Educational Psychology, 107(3), 868-883. doi:10.1037/edu0000006.

    Abstract

    Evidence that rapid naming skill is associated with reading ability has become increasingly prevalent in recent years. However, there is considerable variation in the literature concerning the magnitude of this relationship. The objective of the present study was to provide a comprehensive analysis of the evidence on the relationship between rapid automatized naming (RAN) and reading performance. To this end, we conducted a meta-analysis of the correlational relationship between these 2 constructs to (a) determine the overall strength of the RAN–reading association and (b) identify variables that systematically moderate this relationship. A random-effects model analysis of data from 137 studies (857 effect sizes; 28,826 participants) indicated a moderate-to-strong relationship between RAN and reading performance (r = .43, I2 = 68.40). Further analyses revealed that RAN contributes to the 4 measures of reading (word reading, text reading, non-word reading, and reading comprehension), but higher coefficients emerged in favor of real word reading and text reading. RAN stimulus type and type of reading score were the factors with the greatest moderator effect on the magnitude of the RAN–reading relationship. The consistency of orthography and the subjects’ grade level were also found to impact this relationship, although the effect was contingent on reading outcome. It was less evident whether the subjects’ reading proficiency played a role in the relationship. Implications for future studies are discussed.
  • Fransson, P., Merboldt, K.-D., Petersson, K. M., Ingvar, M., & Frahm, J. (2002). On the effects of spatial filtering — A comparative fMRI study of episodic memory encoding at high and low resolution. NeuroImage, 16(4), 977-984. doi:10.1006/nimg.2002.1079.

    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.
  • Nyberg, L., Forkstam, C., Petersson, K. M., Cabeza, R., & Ingvar, M. (2002). Brain imaging of human memory systems: Between-systems similarities and within-system differences. Cognitive Brain Research, 13(2), 281-292. doi:10.1016/S0926-6410(02)00052-6.

    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.
  • Petersson, K. M. (2002). Brain physiology. In R. Behn, & C. Veranda (Eds.), Proceedings of The 4th Southern European School of the European Physical Society - Physics in Medicine (pp. 37-38). Montreux: ESF.
  • Petrovic, P., Kalso, E., Petersson, K. M., & Ingvar, M. (2002). Placebo and opioid analgesia - Imaging a shared neuronal network. Science, 295(5560), 1737-1740. doi:10.1126/science.1067176.

    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.
  • Petrovic, P., Kalso, E., Petersson, K. M., & Ingvar, M. (2002). Placebo and opioid analgesia - Imaging a shared neuronal network. Science, 295(5560), 1737-1740. doi:10.1126/science.1067176.

    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.
  • Petrovic, P., Petersson, K. M., Hansson, P., & Ingvar, M. (2002). A regression analysis study of the primary somatosensory cortex during pain. NeuroImage, 16(4), 1142-1150. doi:10.1006/nimg.2002.1069.

    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.
  • Sandberg, A., Lansner, A., Petersson, K. M., & Ekeberg, Ö. (2002). A Bayesian attractor network with incremental learning. Network: Computation in Neural Systems, 13(2), 179-194. doi:10.1088/0954-898X/13/2/302.

    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.

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