GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Disentangling causal webs in the brain using functional magnetic resonance imaging: A review of current approaches
    MIT Press ; 2019
    In:  Network Neuroscience Vol. 3, No. 2 ( 2019-01), p. 237-273
    Details
    In: Network Neuroscience, MIT Press, Vol. 3, No. 2 ( 2019-01), p. 237-273
    Abstract: In the past two decades, functional Magnetic Resonance Imaging (fMRI) has been used to relate neuronal network activity to cognitive processing and behavior. Recently this approach has been augmented by algorithms that allow us to infer causal links between component populations of neuronal networks. Multiple inference procedures have been proposed to approach this research question but so far, each method has limitations when it comes to establishing whole-brain connectivity patterns. In this paper, we discuss eight ways to infer causality in fMRI research: Bayesian Nets, Dynamical Causal Modelling, Granger Causality, Likelihood Ratios, Linear Non-Gaussian Acyclic Models, Patel’s Tau, Structural Equation Modelling, and Transfer Entropy. We finish with formulating some recommendations for the future directions in this area.
    Type of Medium: Online Resource
    ISSN: 2472-1751
    URL: Article
    DOI: 10.1162/netn_a_00062
    Language: English
    Publisher: MIT Press
    Publication Date: 2019
    detail.hit.zdb_id: 2900481-0
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    Neural Tracking in Infancy Predicts Language Development in Children With and Without Family History of Autism
    MIT Press ; 2022
    In:  Neurobiology of Language Vol. 3, No. 3 ( 2022-08-17), p. 495-514
    Details
    In: Neurobiology of Language, MIT Press, Vol. 3, No. 3 ( 2022-08-17), p. 495-514
    Abstract: During speech processing, neural activity in non-autistic adults and infants tracks the speech envelope. Recent research in adults indicates that this neural tracking relates to linguistic knowledge and may be reduced in autism. Such reduced tracking, if present already in infancy, could impede language development. In the current study, we focused on children with a family history of autism, who often show a delay in first language acquisition. We investigated whether differences in tracking of sung nursery rhymes during infancy relate to language development and autism symptoms in childhood. We assessed speech-brain coherence at either 10 or 14 months of age in a total of 22 infants with high likelihood of autism due to family history and 19 infants without family history of autism. We analyzed the relationship between speech-brain coherence in these infants and their vocabulary at 24 months as well as autism symptoms at 36 months. Our results showed significant speech-brain coherence in the 10- and 14-month-old infants. We found no evidence for a relationship between speech-brain coherence and later autism symptoms. Importantly, speech-brain coherence in the stressed syllable rate (1–3 Hz) predicted later vocabulary. Follow-up analyses showed evidence for a relationship between tracking and vocabulary only in 10-month-olds but not in 14-month-olds and indicated possible differences between the likelihood groups. Thus, early tracking of sung nursery rhymes is related to language development in childhood.
    Type of Medium: Online Resource
    ISSN: 2641-4368
    URL: Article
    DOI: 10.1162/nol_a_00074
    Language: English
    Publisher: MIT Press
    Publication Date: 2022
    detail.hit.zdb_id: 3011523-1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    Unification of Speaker and Meaning in Language Comprehension: An fMRI Study
    MIT Press ; 2009
    In:  Journal of Cognitive Neuroscience Vol. 21, No. 11 ( 2009-11-01), p. 2085-2099
    Details
    In: Journal of Cognitive Neuroscience, MIT Press, Vol. 21, No. 11 ( 2009-11-01), p. 2085-2099
    Abstract: When interpreting a message, a listener takes into account several sources of linguistic and extralinguistic information. Here we focused on one particular form of extralinguistic information, certain speaker characteristics as conveyed by the voice. Using functional magnetic resonance imaging, we examined the neural structures involved in the unification of sentence meaning and voice-based inferences about the speaker's age, sex, or social background. We found enhanced activation in the inferior frontal gyrus bilaterally (BA 45/47) during listening to sentences whose meaning was incongruent with inferred speaker characteristics. Furthermore, our results showed an overlap in brain regions involved in unification of speaker-related information and those used for the unification of semantic and world knowledge information [inferior frontal gyrus bilaterally (BA 45/47) and left middle temporal gyrus (BA 21)]. These findings provide evidence for a shared neural unification system for linguistic and extralinguistic sources of information and extend the existing knowledge about the role of inferior frontal cortex as a crucial component for unification during language comprehension.
    Type of Medium: Online Resource
    ISSN: 0898-929X , 1530-8898
    URL: Article
    DOI: 10.1162/jocn.2008.21161
    Language: English
    Publisher: MIT Press
    Publication Date: 2009
    SSG: 5,2
    SSG: 7,11
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 4
    Online Resource
    Online Resource
    Reasoning with Exceptions: An Event-related Brain Potentials Study
    MIT Press ; 2011
    In:  Journal of Cognitive Neuroscience Vol. 23, No. 2 ( 2011-02-01), p. 471-480
    Details
    In: Journal of Cognitive Neuroscience, MIT Press, Vol. 23, No. 2 ( 2011-02-01), p. 471-480
    Abstract: Defeasible inferences are inferences that can be revised in the light of new information. Although defeasible inferences are pervasive in everyday communication, little is known about how and when they are processed by the brain. This study examined the electrophysiological signature of defeasible reasoning using a modified version of the suppression task. Participants were presented with conditional inferences (of the type “if p, then q; p, therefore q”) that were preceded by a congruent or a disabling context. The disabling context contained a possible exception or precondition that prevented people from drawing the conclusion. Acceptability of the conclusion was indeed lower in the disabling condition compared to the congruent condition. Further, we found a large sustained negativity at the conclusion of the disabling condition relative to the congruent condition, which started around 250 msec and was persistent throughout the entire epoch. Possible accounts for the observed effect are discussed.
    Type of Medium: Online Resource
    ISSN: 0898-929X , 1530-8898
    URL: Article
    DOI: 10.1162/jocn.2009.21360
    Language: English
    Publisher: MIT Press
    Publication Date: 2011
    SSG: 5,2
    SSG: 7,11
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 5
    Online Resource
    Online Resource
    Increasing robustness of pairwise methods for effective connectivity in magnetic resonance imaging by using fractional moment series of BOLD signal distributions
    MIT Press ; 2019
    In:  Network Neuroscience Vol. 3, No. 4 ( 2019-01), p. 1009-1037
    Details
    In: Network Neuroscience, MIT Press, Vol. 3, No. 4 ( 2019-01), p. 1009-1037
    Abstract: Author Summary Estimating causal interactions from functional magnetic resonance imaging (fMRI) data is a formidable task. Recent advances in this field include methods for pairwise inference. In the first step of this procedure, connections are revealed by means of functional connectivity. In the second step, every detected connection is analyzed separately to reveal the direction of the causal links. We introduce an advance to the second step of this procedure by building a classifier based on the novel concept of fractional moments of the BOLD distribution combined into cumulants. The classifier is trained on datasets generated under the dynamic causal modeling (DCM) generative model. Using fractional cumulants gives a measure resilient to confounding effects such as differential noise levels across different areas of the connectome.
    Type of Medium: Online Resource
    ISSN: 2472-1751
    URL: Article
    DOI: 10.1162/netn_a_00099
    Language: English
    Publisher: MIT Press
    Publication Date: 2019
    detail.hit.zdb_id: 2900481-0
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...