Identification of activated regions during a language task

Carli, Diego De; Garreffa, Girolamo; Colonnese, Claudio; Giulietti, Giovanni; Labruna, Ludovica; Briselli, Ennio; Ken, S.; Macrì, Monica; Maraviglia, B.

doi:10.1016/j.mri.2007.03.031

Cited by 38 publications

(22 citation statements)

References 32 publications

(34 reference statements)

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“…On the other hand, they also found specific (e.g., left inferior frontal, BA 47) activation for auditoryverbal material, suggesting that the engagement of frontal regions in our study may reflect language-specific processes during WM encoding. Indeed, most of the brain regions showing SSE-related activation increase in our study are known from language studies, such as the left pars orbitalis (BA 47) for semantic processing (De Carli et al, 2007;Chou et al, 2006;Demb et al, 1995), dorsomedial pFC for semantic processing (Binder & Desai, 2011) and text comprehension ( Yarkoni, Speer, & Zacks, 2008), middle temporal gyrus for semantic relatedness effects (e.g., bed, rest; McDermott, Petersen, Watson, & Ojemann, 2003), and sentence generation (Brown, Martinez, & Parsons, 2006), or the IPL, specifically the supramarginal gyrus for semantic processing and integration (Chou et al, 2006) and the angular gyrus for semantic memory retrieval (Binder, Desai, Graves, & Conant, 2009). This is supported by our observation that the overall activation pattern strongly resembles the networks reported for semantic processing (Binder & Desai, 2011) as well as the one proposed for imagination and sequential pattern prediction (Buckner, 2010).…”

Section: Sentence Structure Leads To Enriched Encodingmentioning

confidence: 81%

Brain Signature of Working Memory for Sentence Structure: Enriched Encoding and Facilitated Maintenance

Bonhage

Fiebach

Bahlmann

et al. 2014

Journal of Cognitive Neuroscience

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Sentences are easier to memorize than ungrammatical word strings, a phenomenon known as the sentence superiority effect. Yet, it is unclear how higher-order linguistic information facilitates verbal working memory and how this is implemented in the neural system. The goal of the current fMRI study was to specify the brain mechanisms underlying the sentence superiority effect during encoding and during maintenance in working memory by manipulating syntactic structure and working memory load. The encoding of sentence material, as compared with the encoding of ungrammatical word strings, recruited not only inferior frontal (BA 47) and anterior temporal language-related areas but also the medial-temporal lobe, which is not classically reported for language tasks. During maintenance, it was sentence structure as contrasted with ungrammatical word strings that led to activation decrease in Broca's area, SMA, and parietal regions. Furthermore, in Broca's area, an interaction effect revealed a load effect for ungrammatical word strings but not for sentences. The sentence superiority effect, thus, is neurally reflected in a twofold pattern, consisting of increased activation in classical language as well as memory areas during the encoding phase and decreased maintenance-related activation. This pattern reflects how chunking, based on sentential syntactic and semantic information, alleviates rehearsal demands and thus leads to improved working memory performance.

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Section: Sentence Structure Leads To Enriched Encodingmentioning

confidence: 81%

Brain Signature of Working Memory for Sentence Structure: Enriched Encoding and Facilitated Maintenance

Bonhage

Fiebach

Bahlmann

et al. 2014

Journal of Cognitive Neuroscience

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“…Although neural processes are quite distributed and bilaterally activate multiple cortical regions (Bullmore and Sporns, 2009; Bressler and Menon, 2010), there is considerable agreement that specific regions (such as the left iFG and left superior temporal gyrus (STG) consistently show increased activation during language processing (Cabeza and Nyberg, 2000; Papathanassiou, 2000; Blank et al, 2002; De Carli et al, 2007). The same applies to visual perception and visual imagery processes, which bilaterally activate multiple cortical regions, in particular occipital and parietal lobes (Kosslyn et al, 1993, 1999; Alivisatos and Petrides, 1996).…”

Section: Resultsmentioning

confidence: 99%

Neurological Evidence Linguistic Processes Precede Perceptual Simulation in Conceptual Processing

Louwerse

Hutchinson

2012

Front. Psychology

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There is increasing evidence from response time experiments that language statistics and perceptual simulations both play a role in conceptual processing. In an EEG experiment we compared neural activity in cortical regions commonly associated with linguistic processing and visual perceptual processing to determine to what extent symbolic and embodied accounts of cognition applied. Participants were asked to determine the semantic relationship of word pairs (e.g., sky – ground) or to determine their iconic relationship (i.e., if the presentation of the pair matched their expected physical relationship). A linguistic bias was found toward the semantic judgment task and a perceptual bias was found toward the iconicity judgment task. More importantly, conceptual processing involved activation in brain regions associated with both linguistic and perceptual processes. When comparing the relative activation of linguistic cortical regions with perceptual cortical regions, the effect sizes for linguistic cortical regions were larger than those for the perceptual cortical regions early in a trial with the reverse being true later in a trial. These results map upon findings from other experimental literature and provide further evidence that processing of concept words relies both on language statistics and on perceptual simulations, whereby linguistic processes precede perceptual simulation processes.

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“…We can only speculate. On the basis of the connectivity of the OpPMF, a lesion specific to this fascicle might lead to a pure "naked" Broca's aphasia (an isolated loss of word production), or semantic errors (De Carli et al, 2007; Glasser & Rilling, 2008). Another term for this fascicle might be the "premotor connection", because the OpPMF makes a strong, well organized, and direct connection between the pars opercularis and the premotor cortex.…”

Section: Discussionmentioning

confidence: 99%

Extended Broca’s Area in the Functional Connectome of Language in Adults: Combined Cortical and Subcortical Single-Subject Analysis Using fMRI and DTI Tractography

et al. 2012

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Traditional models of the human language circuitry encompass three cortical areas, Broca's, Geschwind's and Wernicke's, and their connectivity. In an effort to expand current knowledge, we used diffusion tensor imaging (DTI) to explore subject-specific structural macroscopic connectivity, focusing on Broca’s area. Fascicles were studied using diffusion tensor imaging fiber tracking seeded from volumes placed manually within the white matter. White matter fascicles were co-registered with 3-D renderings of the brain in 12 healthy subjects. We discovered a connectome divisible into three systems --anterior, superior and inferior-- around the insula, more complex than previously thought. The extended Broca’s area involves two new fascicles: the operculo-premotor fascicle comprised of well-organized U-shaped fibers that connect the pars opercularis with the premotor region; and (2) the triangulo-orbitaris system comprised of intermingled U-shaped fibers that connect the pars triangularis with the pars orbitaris. The findings enhance our understanding of human language.

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Identification of activated regions during a language task

Cited by 38 publications

References 32 publications

Brain Signature of Working Memory for Sentence Structure: Enriched Encoding and Facilitated Maintenance

Brain Signature of Working Memory for Sentence Structure: Enriched Encoding and Facilitated Maintenance

Neurological Evidence Linguistic Processes Precede Perceptual Simulation in Conceptual Processing

Extended Broca’s Area in the Functional Connectome of Language in Adults: Combined Cortical and Subcortical Single-Subject Analysis Using fMRI and DTI Tractography

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