Mental arithmetic in the bilingual brain: Language matters.

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 ▲]

Functional connectivity and structural analyses in the bilingual brain: implications for arithmetic.

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 ▲]

Arithmetic in the bilingual brain: an fMRI study

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 ▲]

Characterizing the face processing network in the human brain: a large-scale fMRI localizer study

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 ▲]

Holistic perception of individual faces in the right middle fusiform gyrus as evidenced by the composite face illusion

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 ▲]

Evidence for individual face discrimination in non-face selective areas of the visual cortex in acquired prosopagnosia

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 ▲]