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See detailMental arithmetic in the bilingual brain: Language matters.
Van Rinsveld, Amandine; Dricot, Laurence; Guillaume, Mathieu UL et al

in Neuropsychologia (2017), 101

How do bilinguals solve arithmetic problems in each of their languages? We investigated this question by exploring the neural substrates of mental arithmetic in bilinguals. Critically, our population was ... [more ▼]

How do bilinguals solve arithmetic problems in each of their languages? We investigated this question by exploring the neural substrates of mental arithmetic in bilinguals. Critically, our population was composed of a homogeneous group of adults who were fluent in both of their instruction languages (i.e., German as first instruction language and French as second instruction language). Twenty bilinguals were scanned with fMRI (3T) while performing mental arithmetic. Both simple and complex problems were presented to disentangle memory retrieval occuring in very simple problems from arithmetic computation occuring in more complex problems. In simple additions, the left temporal regions were more activated in German than in French, whereas no brain regions showed additional activity in the reverse constrast. Complex additions revealed the reverse pattern, since the activations of regions for French surpassed the same computations in German and the extra regions were located predominantly in occipital regions. Our results thus highlight that highly proficient bilinguals rely on differential activation patterns to solve simple and complex additions in each of their languages, suggesting different solving procedures. The present study confirms the critical role of language in arithmetic problem solving and provides novel insights into how highly proficient bilinguals solve arithmetic problems. [less ▲]

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See detailCorrelates of social exclusion in social anxiety Disorder: An fMRI study
Heeren, Alexandre; Dricot, Laurence; Billieux, Joël UL et al

in Scientific Reports (2017), 7

Cognitive models posit that social anxiety disorder (SAD) is maintained by biased informationprocessing vis-à-vis threat of social exclusion. However, uncertainty still abounds regarding the very nature ... [more ▼]

Cognitive models posit that social anxiety disorder (SAD) is maintained by biased informationprocessing vis-à-vis threat of social exclusion. However, uncertainty still abounds regarding the very nature of this sensitivity to social exclusion in SAD. Especially, brain alterations related to social exclusion have not been explored in SAD. Our primary purpose was thus to determine both the selfreport and neural correlates of social exclusion in this population. 23 patients with SAD and 23 matched nonanxious controls played a virtual game (“Cyberball”) during fMRI recording. Participants were frst included by other players, then excluded, and fnally re-included. At the behavioral level, patients with SAD exhibited signifcantly higher levels of social exclusion feelings than nonanxious controls. At the brain level, patients with SAD exhibited signifcantly higher activation within the left inferior frontal gyrus relative to nonanxious controls during the re-inclusion phase. Moreover, self-report of social exclusion correlates with the activity of this cluster among individuals qualifying for SAD diagnosis. Our pattern of fndings lends strong support to the notion that SAD may be better portrayed by a poor ability to recover following social exclusion than during social exclusion per se. These fndings value social neuroscience as an innovative procedure to gain new insight into the underlying mechanisms of SAD. [less ▲]

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See detailFunctional connectivity and structural analyses in the bilingual brain: implications for arithmetic.
Van Rinsveld, Amandine UL; Dricot, Laurence; Guillaume, Mathieu UL et al

Poster (2015, June)

Do bilinguals use the same brain networks than monolinguals when they solve arithmetic problems? We investigated this question by using resting-state functional connectivity and cortical thickness ... [more ▼]

Do bilinguals use the same brain networks than monolinguals when they solve arithmetic problems? We investigated this question by using resting-state functional connectivity and cortical thickness measurements. Recent studies highlighted differences of functional connectivity (e.g. Grady et al., 2015) and of brain structure (e.g. Klein et al., 2014) between bilinguals and monolinguals. However, no study so far has linked these differences to arithmetic problem solving, a cognitive skill that may at least partially rely on language processing. Our study population was composed of carefully selected German-French bilinguals (N = 20) who acquired each language at the same age, leading to high proficiency levels in both languages. These bilinguals all attended university in their second language at the time of the experiment, namely French. Therefore we selected a control group of French-speaking monolinguals (N = 12). Structural and functional images of brain activity were collected using a 3T MRI scanner. Functional scans of resting-state were acquired during a 6-minute session, with eyes closed. A 3D T1-weighted data set encompassing the whole brain was acquired to provide detailed anatomy (1 mm3), which was used both for the co-registration of functional data and for morphometric analyses. Prior to the scanning session, all participants took a behavioral test measuring their arithmetic skill. For the resting-state part of the study, we generated spheres based on ROIs reported in the literature as magnitude manipulation- and language-related areas during arithmetic problem solving (Klein et al. 2013), and addition-related areas reported in a recent meta-analysis (Arsalidou & Tayor, 2011). We used these spheres as seed regions for the analyses. We correlated resting activations between these regions and compared these correlations in bilinguals versus monolinguals. Results showed significantly higher correlations between the three seed regions in monolinguals than in bilinguals (all ts > 2.306; ps < .05), suggesting that regions used to solve arithmetic problems form a different network in bilinguals than in monolinguals. To control for general differences between both populations, we also created two spheres in areas not specifically related to neither arithmetic nor language regions. There were no significant differences between groups in terms of correlations of these regions with resting-state activations. These results suggest that the differences observed in arithmetic problem solving regions could not account for by general differences between groups. In the second part of the study, we aimed at verifying whether the differences in functional connectivity we observed between bilinguals and monolinguals coincide with structural brain differences. We measured and compared cortical thickness in both groups. Then we compared the correlations between cortical thickness and arithmetic skill in both groups (considering differences with corrected p < .001). Cortical thickness of areas commonly associated to language or number processing correlated differently with arithmetic skill as a function of the group: Higher cortical thickness of left pars triangularis, bilateral superior parietal gyri and precuneus positively correlated with arithmetic skill in monolinguals but negatively correlated with arithmetic skill in bilinguals. These results highlight that there are different relations between brain structure and arithmetic skills in bilinguals and monolinguals. In conclusion the current study provides new evidence for differences between bilinguals’ and monolinguals’ brain networks engaged in arithmetic problem solving, even without any arithmetic task during the data acquisition. These findings based on functional connectivity and brain structure analyses also reveal the general involvement of language in arithmetic problem solving in bilingual as well as non-bilingual individuals. [less ▲]

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See detailNeural correlates of arithmetic problem solving in bilinguals: an fMRI study.
Van Rinsveld, Amandine UL; Dricot, Laurence; Guillaume, Mathieu UL et al

Poster (2015, May)

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See detailArithmetic in the bilingual brain: an fMRI study
Van Rinsveld, Amandine UL; Dricot, Laurence; Guillaume, Mathieu UL et al

Scientific Conference (2015, March)

Using fMRI we observed that solving addition and multiplication problems induced activation in several fronto-parietal regions in both German-French bilingual and French monolingual adults. However ... [more ▼]

Using fMRI we observed that solving addition and multiplication problems induced activation in several fronto-parietal regions in both German-French bilingual and French monolingual adults. However, during complex addition frontal regions showed systematically higher activation levels in bilinguals than monolinguals, both when bilinguals computed in German (math-acquisition language) and in French. [less ▲]

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See detailArithmetic in the Bilingual Brain: an fMRI study
Van Rinsveld, Amandine UL; Dricot, Laurence; Guillaume, Mathieu UL et al

Scientific Conference (2014, May)

How do bilinguals solve arithmetic problems in their different languages? We investigated this question with functional magnetic resonance imaging (fMRI) by exploring the neural substrates of arithmetic ... [more ▼]

How do bilinguals solve arithmetic problems in their different languages? We investigated this question with functional magnetic resonance imaging (fMRI) by exploring the neural substrates of arithmetic processing in bilinguals in comparison to monolinguals. Bilingual participants were highly proficient both in German and French as they attended primary school in German and secondary school and higher education in French. This bilingual combination is particularly interesting because the order of two-digit number words is inversed in these languages: decade-unit in French but unit-decade in German. 21 German-French bilinguals and 12 French-speaking monolinguals were scanned while performing different types of arithmetic problems: additions of different complexity levels (from simple to complex additions) and multiplication facts. We presented different types of operations in order to disentangle arithmetic computation from pure memory retrieval that occurs in very simple additions or multiplications. Arithmetic problems were presented via headsets in a verification paradigm and bilinguals performed the tasks in both languages. Results showed that all arithmetic tasks elicited a broad fronto-parietal network in both groups and for both of bilinguals’ language sessions. However, we observed that complex additions involved more left frontal activity (i.e. inferior frontal gyrus, anterior cingulate gyrus) in bilinguals than in monolinguals. It is important to notice that these frontal activation differences occurred both for the arithmetic acquisition language (i.e. German) and the second language (i.e. French). These BOLD differences between bilingual and monolingual participants were observed despite the fact that both groups solved the arithmetic problems with equivalent accuracy rates. Moreover, localization of the regions activated by complex additions in bilinguals differed from the typical activation pattern reported for mental arithmetic in recent meta-analyses (Arsalidou & Taylor, 2011). Taken together, our results indicate that highly proficient bilinguals rely on differential activation patterns than monolinguals to solve complex additions. The differences in left frontal activations might reflect different degrees of language-related automaticity when computing complex arithmetic problems. Executive functions that are necessary to control language context and access for bilinguals’ respective languages might also play a role. Further insights about the role of language in arithmetic solving process in bilingual and non-bilingual individuals will be discussed. [less ▲]

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See detailCerebral lateralization of the face-cortical network in left-handers: only the FFA does not get it right
Bukowski, Henryk; Rossion, Bruno; Schiltz, Christine UL et al

in Journal of Vision (2010), 10(7),

Face processing is a function that is highly lateralized in humans, as supported by original evidence from brain lesion studies (Hecaen & Anguerlergues, 1962), followed by studies using divided visual ... [more ▼]

Face processing is a function that is highly lateralized in humans, as supported by original evidence from brain lesion studies (Hecaen & Anguerlergues, 1962), followed by studies using divided visual field presentations (Heller & Levy, 1981), neuroimaging (Sergent et al., 1992) and event-related potentials (Bentin et al., 1996). Studies in non-human primates (Perrett et al., 1988; Zangenehpour & Chaudhuri, 2005), or other mammals (Peirce & Kendrick, 2001) support the right lateralization of the function, which may be related to a dominance of the right hemisphere in global visual processing. However, in humans there is evidence that manual preference may shift or qualify the pattern of lateralization for faces in the visual cortex: face recognition impairments following unilateral left hemisphere brain damage have been found only in a few left-handers (e.g., Mattson et al., 1992; Barton, 2009). Here we measured the pattern of lateralization in the entire cortical face network in right and left-handers (12 subjects in each group) using a well-balanced face-localizer block paradigm in fMRI (faces, cars, and their phase-scrambled versions). While the FFA was strongly right lateralized in right-handers, as described previously, it was equally strong in both hemispheres in left-handers. In contrast, other areas of the face-sensitive network (posterior superior temporal sulcus, pSTS; occipital face area, OFA; anterior infero-temporal cortex, AIT; amygdala) remained identically right lateralized in both left- and right-handers. Accordingly, our results strongly suggest that the face-sensitive network is equally lateralized for left- and right-handers, and thus the face processing is not influenced by handedness. However, the FFA is an important exception since it is right-lateralized for right-handers but its recruitment is more balanced between hemispheres for left-handers. These observations carry important theoretical and clinical implications for the aetiology of brain lateralization depending on the left- or right-handedness and the neuropsychological undertaking of prosopagnosic patients. [less ▲]

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See detailCharacterizing the face processing network in the human brain: a large-scale fMRI localizer study
Dricot, Laurence; Hanseeuw, Bernard; Schiltz, Christine UL et al

in Journal of Vision (2010), 10(7),

A whole network of brain areas showing larger response to faces than other visual stimuli has been identified in the human brain using fMRI (Sergent, 1992; Haxby, 2000). Most studies identify only a ... [more ▼]

A whole network of brain areas showing larger response to faces than other visual stimuli has been identified in the human brain using fMRI (Sergent, 1992; Haxby, 2000). Most studies identify only a subset of this network, by comparing the presentation of face pictures to all kinds of object categories mixed up (e.g., Kanwisher, 1997), or to scrambled faces (e.g., Ishaï, 2005), using different statistical thresholds. Given these differences of approaches, the (sub)cortical face network can be artificially overextended (Downing & Wiggett, 2008), or minimized in different studies, both at the local (size of regions) and global (number of regions) levels. Here we conducted an analysis of a large set of right-handed subjects (40), tested with a new whole-brain localizer to control for both high-level and low-level differences between faces and objects. Pictures of faces, cars and their phase-scrambled counterparts were used in a 2x2 block design. Group-level (random effect) and single subject (ROI) analyses were made. A conjunction of two contrasts (F-SF and F-C) identified 6 regions: FFA, OFA, amygdala, pSTS, AIT and thalamus. All these regions but the amygdala showed clear right lateralization. Interestingly, the FFA showed the least face-selective response among the cortical face network: it presented a significantly larger response to pictures of cars than scrambled cars [t=9.3, much more than amygdala (t=2.6), AIT (t=2.1) and other regions (NS)], and was also sensitive to low-level properties of faces [SF - SO; t=5.1; NS in other areas]. These observations suggest that, contrary to other areas of the network, including the OFA, the FFA is a region that may contain populations of neurons that are specific to faces intermixed with populations responding more generally to object categories. More generally, this study helps understanding the extent and specificity of the network of (sub)cortical areas particularly involved in face processing. [less ▲]

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See detailHolistic perception of individual faces in the right middle fusiform gyrus as evidenced by the composite face illusion
Schiltz, Christine UL; Dricot, Laurence; Goebel, Rainer et al

in Journal of Vision (2010), 10(2), 1-16

The perception of a facial feature (e.g., the eyes) is influenced by the position and identity of other features (e.g., the mouth) supporting an integrated, or holistic, representation of individual faces ... [more ▼]

The perception of a facial feature (e.g., the eyes) is influenced by the position and identity of other features (e.g., the mouth) supporting an integrated, or holistic, representation of individual faces in the human brain. Here we used an event-related adaptation paradigm in functional magnetic resonance imaging (fMRI) to clarify the regions representing faces holistically across the whole brain. In each trial, observers performed the same/different task on top halves (aligned or misaligned) of two faces presented sequentially. For each face pair, the identity of top and bottom parts could be both identical, both different, or different only for the bottom half. The latter manipulation resulted in a composite face illusion, i.e., the erroneous perception of identical top parts as being different, only for aligned faces. Release from adaptation in this condition was found in two sub-areas of the right middle fusiform gyrus responding preferentially to faces, including the “fusiform face area” (“FFA”). There were no significant effects in homologous regions of the left hemisphere or in the inferior occipital cortex. Altogether, these observations indicate that face-sensitive populations of neurons in the right middle fusiform gyrus are optimally tuned to represent individual exemplars of faces holistically. [less ▲]

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See detailThe roles of "face" and "non-face" areas during individual face perception: Evidence by fmri adaptation in a brain-damaged prosopagnosic patient
Dricot, Laurence; Sorger, Bettina; Schiltz, Christine UL et al

in NeuroImage (2008), 40(1), 318-332

Two regions in the human occipito-temporal cortex respond preferentially to faces: 'the fusiform face area' ('FFA') and the 'occipital face area' ('OFA'). Whether these areas have a dominant or exclusive ... [more ▼]

Two regions in the human occipito-temporal cortex respond preferentially to faces: 'the fusiform face area' ('FFA') and the 'occipital face area' ('OFA'). Whether these areas have a dominant or exclusive role in face perception, or if sub-maximal responses in other visual areas such as the lateral occipital complex (LOC) are also involved, is currently debated. To shed light on this issue, we tested normal participants and PS, a well-known brain-damaged patient presenting a face-selective perception deficit (prosopagnosia) [Rossion, B., Caldara, R., Seghier, M., Schuller, A. M., Lazeyras, F., Mayer, E. (2003). A network of occipito-temporal face-sensitive areas besides the right middle fusiform gyrus is necessary for normal face processing. Brain 126 2381-2395.], with functional magnetic resonance imaging (fMRI). Of particular interest, the right hemisphere lesion of the patient PS encompasses the 'OFA' but preserves the 'FFA' and LOC [Sorger, B., Goebel, R., Schiltz, C., Rossion, B. (2007). Understanding the functional neuroanatomy of acquired prosopagnosia. NeuroImage 35, 836-852.]. Using fMRI-adaptation, we found a dissociation between the coding of individual exemplars in the structurally intact 'FFA', which was impaired for faces but preserved for objects in the patient PS's brain. Most importantly, a larger response to different faces than repeated faces was found in the ventral part of the LOC both for normals and the patient, next to the right hemisphere lesion. Thus, following prosopagnosia, areas that do not respond preferentially to faces such as the ventral part of the LOC (vLOC) may still be recruited for compensatory or residual individual face perception. Overall, these observations indicate that several high-level visual areas in the human brain contribute to individual face perception. However, a subset of these areas in the right hemisphere, those responding preferentially to faces ('FFA' and 'OFA'), appear to be critical for this function. [less ▲]

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See detailEvidence for individual face discrimination in non-face selective areas of the visual cortex in acquired prosopagnosia
Dricot, Laurence; Sorger, Bettina; Schiltz, Christine UL et al

in Behavioral Neurology (2008), 19(1-2), 75-79

Two areas in the human occipito-temporal cortex respond preferentially to faces: 'the fusiform face area' ('FFA') and the 'occipital face area' ('OFA'). However, it is unclear whether these areas have an ... [more ▼]

Two areas in the human occipito-temporal cortex respond preferentially to faces: 'the fusiform face area' ('FFA') and the 'occipital face area' ('OFA'). However, it is unclear whether these areas have an exclusive role in processing faces, or if sub-maximal responses in other visual areas such as the lateral occipital complex (LOC) are also involved. To clarify this issue, we tested a brain-damaged patient (PS) presenting a face-selective impairment with functional magnetic resonance imaging (fMRI). The right hemisphere lesion of the prosopagnosic patient encompasses the 'OFA' but preserves the 'FFA' and LOC. Using fMRI-adaptation, we found a larger response to different faces than repeated faces in the ventral part of the LOC both for normals and the patient, next to her right hemisphere lesion. This observation indicates that following prosopagnosia, areas that do not respond preferentially to faces such as the ventral part of the LOC (vLOC) may still be recruited to subtend residual perception of individual faces. [less ▲]

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See detailFmri evidence for multiple face processing pathways in the human brain
Dricot, Laurence; Schiltz, Christine UL; Sorger, Bettina et al

Poster (2007, May)

Two regions in the occipito-temporal cortex respond more strongly to faces than to objects and are thought to be important for face perception: ‘the fusiform face area’ (‘FFA’) and the ‘occipital face ... [more ▼]

Two regions in the occipito-temporal cortex respond more strongly to faces than to objects and are thought to be important for face perception: ‘the fusiform face area’ (‘FFA’) and the ‘occipital face area’ (‘OFA’). Whether these areas responding preferentially to faces play a dominant or exclusive role in face processing or if sub-maximal responses in other areas of the ventral stream such as the lateral occipital complex (LOC) are also involved is currently debated. To clarify this issue, we tested a brain-damaged patient presenting a face-selective deficit, prosopagnosia, with functional magnetic resonance imaging (fMRI). Using fMRI-adaptation, we found a dissociation between the coding of identity in the structurally intact ‘FFA’, which was impaired for faces but preserved for objects. This observation complements recent fMRI findings that the ‘FFA’ reflects averaging of heterogeneous highly selective neural populations for faces and objects, by showing here that the responses of these populations can be functionally independent. Most importantly, a larger response to different faces than repeated faces was found in the ventral part of the LOC both for normals and the patient, next to the right hemisphere lesion. Following prosopagnosia, areas that do not respond preferentially to faces such as the ventral part of the LOC (vLOC) may still be recruited to subtend residual individual face discrimination. Overall, these observations indicate that faces are processed through a network of visual areas in the human brain, with a subset of these areas responding preferentially to faces being critical for efficient face recognition. [less ▲]

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