Publications

Displaying 1 - 5 of 5
  • Carota, F., Schoffelen, J.-M., Oostenveld, R., & Indefrey, P. (2022). The time course of language production as revealed by pattern classification of MEG sensor data. The Journal of Neuroscience, 42(29), 5745-5754. doi:10.1523/JNEUROSCI.1923-21.2022.

    Abstract

    Language production involves a complex set of computations, from conceptualization to articulation, which are thought to engage cascading neural events in the language network. However, recent neuromagnetic evidence suggests simultaneous meaning-to-speech mapping in picture naming tasks, as indexed by early parallel activation of frontotemporal regions to lexical semantic, phonological, and articulatory information. Here we investigate the time course of word production, asking to what extent such “earliness” is a distinctive property of the associated spatiotemporal dynamics. Using MEG, we recorded the neural signals of 34 human subjects (26 males) overtly naming 134 images from four semantic object categories (animals, foods, tools, clothes). Within each category, we covaried word length, as quantified by the number of syllables contained in a word, and phonological neighborhood density to target lexical and post-lexical phonological/phonetic processes. Multivariate pattern analyses searchlights in sensor space distinguished the stimulus-locked spatiotemporal responses to object categories early on, from 150 to 250 ms after picture onset, whereas word length was decoded in left frontotemporal sensors at 250-350 ms, followed by the latency of phonological neighborhood density (350-450 ms). Our results suggest a progression of neural activity from posterior to anterior language regions for the semantic and phonological/phonetic computations preparing overt speech, thus supporting serial cascading models of word production
  • Shebani, Z., Carota, F., Hauk, O., Rowe, J. B., Barsalou, L. W., Tomasello, R., & Pulvermüller, F. (2022). Brain correlates of action word memory revealed by fMRI. Scientific Reports, 12: 16053. doi:10.1038/s41598-022-19416-w.

    Abstract

    Understanding language semantically related to actions activates the motor cortex. This activation is sensitive to semantic information such as the body part used to perform the action (e.g. arm-/leg-related action words). Additionally, motor movements of the hands/feet can have a causal effect on memory maintenance of action words, suggesting that the involvement of motor systems extends to working memory. This study examined brain correlates of verbal memory load for action-related words using event-related fMRI. Seventeen participants saw either four identical or four different words from the same category (arm-/leg-related action words) then performed a nonmatching-to-sample task. Results show that verbal memory maintenance in the high-load condition produced greater activation in left premotor and supplementary motor cortex, along with posterior-parietal areas, indicating that verbal memory circuits for action-related words include the cortical action system. Somatotopic memory load effects of arm- and leg-related words were observed, but only at more anterior cortical regions than was found in earlier studies employing passive reading tasks. These findings support a neurocomputational model of distributed action-perception circuits (APCs), according to which language understanding is manifest as full ignition of APCs, whereas working memory is realized as reverberant activity receding to multimodal prefrontal and lateral temporal areas.

    Additional information

    supplementary figure S1 caption
  • Carota, F., Nili, H., Pulvermüller, F., & Kriegeskorte, N. (2021). Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: Evidence from RSA of BOLD signals. NeuroImage, 224: 117408. doi:10.1016/j.neuroimage.2020.117408.

    Abstract

    A class of semantic theories defines concepts in terms of statistical distributions of lexical items, basing meaning on vectors of word co-occurrence frequencies. A different approach emphasizes abstract hierarchical taxonomic relationships among concepts. However, the functional relevance of these different accounts and how they capture information-encoding of meaning in the brain still remains elusive.

    We investigated to what extent distributional and taxonomic models explained word-elicited neural responses using cross-validated representational similarity analysis (RSA) of functional magnetic resonance imaging (fMRI) and novel model comparisons.

    Our findings show that the brain encodes both types of semantic similarities, but in distinct cortical regions. Posterior middle temporal regions reflected word links based on hierarchical taxonomies, along with the action-relatedness of the semantic word categories. In contrast, distributional semantics best predicted the representational patterns in left inferior frontal gyrus (LIFG, BA 47). Both representations coexisted in angular gyrus supporting semantic binding and integration. These results reveal that neuronal networks with distinct cortical distributions across higher-order association cortex encode different representational properties of word meanings. Taxonomy may shape long-term lexical-semantic representations in memory consistently with sensorimotor details of semantic categories, whilst distributional knowledge in the LIFG (BA 47) enable semantic combinatorics in the context of language use.

    Our approach helps to elucidate the nature of semantic representations essential for understanding human language.
  • Carota, F., Desmurget, M., & Sirigu, A. (2010). Forward Modeling Mediates Motor Awareness. In W. Sinnott-Armstrong, & L. Nadel (Eds.), Conscious Will and Responsibility - A Tribute to Benjamin Libet (pp. 97-108). Oxford: Oxford University Press.

    Abstract

    This chapter focuses on the issue of motor awareness. It addresses three main questions: What exactly are we aware of when making a movement? What is the contribution of afferent and efferent signals to motor awareness? What are the neural bases of motor awareness? It reviews evidence that the motor system is mainly aware of its intention. As long as the goal is achieved, nothing reaches awareness about the kinematic details of the ongoing movements, even when substantial corrections have to be implemented to attain the intended state. The chapter also shows that motor awareness relies mainly on the central predictive computations carried out within the posterior parietal cortex. The outcome of these computations is contrasted with the peripheral reafferent input to build a veridical motor awareness. Some evidence exists that this process involves the premotor areas.
  • Carota, F., Posada, A., Harquel, S., Delpuech, C., Bertrand, O., & Sirigu, A. (2010). Neural dynamics of the intention to speak. Cerebral Cortex, 20(8), 1891-1897. doi:10.1093/cercor/bhp255.

    Abstract

    When we talk we communicate our intentions. Although the origin of intentional action is debated in cognitive neuroscience, the question of how the brain generates the intention in speech remains still open. Using magnetoencephalography, we investigated the cortical dynamics engaged when healthy subjects attended to either their intention to speak or their actual speech. We found that activity in the right and left parietal cortex increased before subjects became aware of intending to speak. Within the time window of parietal activation, we also observed a transient left frontal activity in Broca's area, a crucial region for inner speech. During attention to speech, neural activity was detected in left prefrontal and temporal areas and in the temporoparietal junction. In agreement with previous results, our findings suggest that the parietal cortex plays a multimodal role in monitoring intentional mechanisms in both action and language. The coactivation of parietal regions and Broca's area may constitute the cortical circuit specific for controlling intentional processes during speech.

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