Priming words with pictures: Neural correlates of semantic associations in a cross‐modal priming task using fMRI

Kircher, Tilo; Saß, Katharina; Sachs, Olga; Krach, Sören

doi:10.1002/hbm.20833

Cited by 42 publications

(31 citation statements)

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“…A rapid event-related fMRI (erfMRI) design was used to present related, unrelated, and nonword trials [Amaro and Barker, 2006;Gold et al, 2006;Kircher et al, 2009;Sass et al, 2009a,b;Whitney et al, 2009]. The idea behind the design was that the presentation of trials from the same condition in a sequence leads to a better sampling of the HRF curve and hence to a better signal.…”

Section: Fmri Proceduresmentioning

confidence: 99%

“…The opposite contrast was calculated to obtain RS. To ensure, that the activations (RS) and deactivation (RE) were a result of the differences between the related and unrelated conditions and to asses only those voxels that are activated or deactivated in both conditions, all contrasts were exclusively masked with the nonword condition [e.g., Bright et al, 2004;Devlin et al, 2002;Kircher et al, 2009]. The mask was thresholded at P < 0.05 uncorrected.…”

Section: Fmri Data Analysismentioning

confidence: 99%

“…different prime-target relations [associative vs. categorical; e.g., Kalenine et al, 2009;Sachs et al, 2008;Sass et al, 2009b;Warrington and Shallice, 1984], different presentation modalities [visual vs. auditory;e.g. Bright et al, 2004;Kircher et al, 2009;Sass et al, 2009a;Vandenberghe et al, 1996], and different semantic distances [direct vs. indirect; e.g., Kuperberg et al, 2008;McNamara and Altarriba, 1988;Sass et al, 2009a;Spitzer et al, 1993]. Beside these different impacts on semantic processing, the context of items also has an influence.…”

Section: Introductionmentioning

confidence: 95%

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The influence of emotional associations on the neural correlates of semantic priming

Saß¹,

Habel²,

Sachs³

et al. 2011

Human Brain Mapping

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Emotions influence our everyday life in several ways. With the present study, we wanted to examine the impact of emotional information on neural correlates of semantic priming, a well-established technique to investigate semantic processing. Stimuli were presented with a short SOA of 200 ms as subjects performed a lexical decision task during fMRI measurement. Seven experimental conditions were compared: positive/negative/neutral related, positive/negative/neutral unrelated, nonwords (all words were nouns). Behavioral data revealed a valence specific semantic priming effect (i.e., unrelated > related) only for neutral and positive related word pairs. On a neural level, the comparison of emotional over neutral relations showed activation in left anterior medial frontal cortex, superior frontal gyrus, and posterior cingulate. Interactions for the different relations were located in left anterior part of the medial frontal cortex, cingulate regions, and right hippocampus ( positive > neutral + negative) and left posterior part of medial frontal cortex (negative > neutral + positive). The results showed that emotional information have an influence on semantic association processes. While positive and neutral information seem to share a semantic network, negative relations might induce compensatory mechanisms that inhibit the spread of activation between related concepts. The neural correlates highlighted a distributed neural network, primarily involving attention, memory and emotion related processing areas in medial fronto-parietal cortices. The differentiation between anterior (positive) and posterior part (negative) of the medial frontal cortex was linked to the type of affective manipulation with more cognitive demands being involved in the automatic processing of negative information

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Section: Fmri Proceduresmentioning

confidence: 99%

Section: Fmri Data Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

See 1 more Smart Citation

The influence of emotional associations on the neural correlates of semantic priming

Saß¹,

Habel²,

Sachs³

et al. 2011

Human Brain Mapping

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“…These studies suggested possible candidate regions for amodal processing of words and pictures, such as the ventral occipitotemporal cortex (Chao et al, 1999;Buckner et al, 2000;Seghier and Price, 2011), the posterior middle temporal gyrus (Chertkow et al, 1997;Vandenbulcke et al, 2007;Kircher et al, 2009), the angular gyrus (Bonner et al, 2013), the anterior temporal pole (Hodges et al, 1992;Vandenberghe et al, 1996;Rogers and McClelland, 2004;Patterson et al, 2007;Binder et al, 2009;Lambon Ralph et al, 2010), the left inferior frontal sulcus (Wagner et al, 1997), the anterior inferior frontal gyrus (Goldberg et al, 2007), and the left middle frontal gyrus (Demb et al, 1995;Vandenberghe et al, 1996;Van Doren et al, 2010). Part of the amodality, especially in left inferior frontal sulcus and ventral occipitotemporal transition zone, may be due to working memory (Badre et al, 2005;Van Doren et al, 2010) or executive control (Whitney et al, 2011) which is required by task regardless of input-modality.…”

Section: Introductionmentioning

confidence: 97%

Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

et al. 2015

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This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Neuropsychologia following peer review. The definitive publisher-authenticated version (Liuzzi A.G., Bruffaerts R., Dupont P., Adamczuk K., Peeters R., De Deyne S., Storms G., Vandenberghe R. AbstractLeft perirhinal cortex has been previously implicated in associative coding. According to a recent experiment, the similarity of perirhinal fMRI response patterns to written concrete words is higher for words which are more similar in their meaning. If left perirhinal cortex functions as an amodal semantic hub, one would predict that this semantic similarity effect would extend to the spoken modality. We conducted an event-related fMRI experiment and evaluated whether a same semantic similarity effect could be obtained for spoken as for written words. Twenty healthy subjects performed a property verification task in either the written or the spoken modality. Words corresponded to concrete animate entities for which extensive feature generation was available from more than 1000 subjects. From these feature generation data, a concept-feature matrix was derived which formed the basis of a cosine similarity matrix between the entities reflecting their similarity in meaning (called the "semantic cossimilarity matrix"). Independently, we calculated a cosine similarity matrix between the left perirhinal fMRI activity patterns evoked by the words (called the "fMRI cossimilarity matrix"). Next, the similarity was determined between the semantic cossimilarity matrix and the fMRI cossimilarity matrix. This was done for written and spoken words pooled, for written words only, for spoken words only, as well as for crossmodal pairs. Only for written words did the fMRI cossimilarity matrix correlate with the semantic cossimilarity matrix. Contrary to our prediction, we did not find any such effect for auditory word input nor did we find cross-modal effects in perirhinal cortex between written and auditory words. Our findings situate the contribution of left perirhinal cortex to word processing at the top of the visual processing pathway, rather than at an amodal stage where visual and auditory word processing pathways have already converged.

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“…In some cases, participants classified pairs of concepts as being taxonomically related, thematically related, or unrelated (Kriukova, Bridger, & Mecklinger, 2013;Maguire, Brier, & Ferree, 2010). In others, participants rated on a 7-point Likert scale the extent to which each pair is linked together in a common scenario or in a functional relationship (Jones & Golonka, 2012;Kalénine et al, 2012;Kircher, Sass, Sachs, & Krach, 2009). A slightly different validation approach was taken by Lin and Murphy (2001), who asked participants to write a sentence describing how two given concepts go together to form a category, and, then, on the basis of these responses, the authors categorized the pairs of concepts as thematic or taxonomic.…”

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confidence: 99%

Thematic relatedness production norms for 100 object concepts

Jouravlev

Masamune

2015

Behav Res

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Knowledge of thematic relations is an area of increased interest in semantic memory research because it is crucial to many cognitive processes. One methodological issue that researchers face is how to identify pairs of thematically related concepts that are well-established in semantic memory for most people. In this article, we review existing methods of assessing thematic relatedness and provide thematic relatedness production norming data for 100 object concepts. In addition, 1,174 related concept pairs obtained from the production norms were classified as reflecting one of the five subtypes of relations: attributive, argument, coordinate, locative, and temporal. The database and methodology will be useful for researchers interested in the effects of thematic knowledge on language processing, analogical reasoning, similarity judgments, and memory. These data will also benefit researchers interested in investigating potential processing differences among the five types of semantic relations.

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Priming words with pictures: Neural correlates of semantic associations in a cross‐modal priming task using fMRI

Cited by 42 publications

References 65 publications

The influence of emotional associations on the neural correlates of semantic priming

The influence of emotional associations on the neural correlates of semantic priming

Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

Thematic relatedness production norms for 100 object concepts

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