A Multimodal Exploration of Brain Activation for Language and Cognitive and Linguistic Skills
Poster No:
1021
Submission Type:
Abstract Submission
Authors:
Irene Balboni1,2,3, Alessandra Rampinini3,2, Olga Kepinska4,5, Raphael Berthele1, Narly Golestani4,5,3
Institutions:
1Institute of Multilingualism, University of Fribourg, Fribourg, Switzerland, 2National Centre for Competence in Research Evolving Language, Switzerland, Switzerland, 3Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland, 4Brain and Language Lab, Cognitive Science Hub, University of Vienna, Vienna, Austria, 5Department of Behavioral and Cognitive Biology, Faculty of Life Sciences, University of Vienna, Vienna, Austria
First Author:
Irene Balboni
Institute of Multilingualism, University of Fribourg|National Centre for Competence in Research Evolving Language|Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva
Fribourg, Switzerland|Switzerland, Switzerland|Geneva, Switzerland
Institute of Multilingualism, University of Fribourg|National Centre for Competence in Research Evolving Language|Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva
Fribourg, Switzerland|Switzerland, Switzerland|Geneva, Switzerland
Co-Author(s):
Alessandra Rampinini
Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva|National Centre for Competence in Research Evolving Language
Geneva, Switzerland|Switzerland, Switzerland
Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva|National Centre for Competence in Research Evolving Language
Geneva, Switzerland|Switzerland, Switzerland
Olga Kepinska
Brain and Language Lab, Cognitive Science Hub, University of Vienna|Department of Behavioral and Cognitive Biology, Faculty of Life Sciences, University of Vienna
Vienna, Austria|Vienna, Austria
Brain and Language Lab, Cognitive Science Hub, University of Vienna|Department of Behavioral and Cognitive Biology, Faculty of Life Sciences, University of Vienna
Vienna, Austria|Vienna, Austria
Narly Golestani
Brain and Language Lab, Cognitive Science Hub, University of Vienna|Department of Behavioral and Cognitive Biology, Faculty of Life Sciences, University of Vienna|Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva
Vienna, Austria|Vienna, Austria|Geneva, Switzerland
Brain and Language Lab, Cognitive Science Hub, University of Vienna|Department of Behavioral and Cognitive Biology, Faculty of Life Sciences, University of Vienna|Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva
Vienna, Austria|Vienna, Austria|Geneva, Switzerland
Introduction:
Language learning and use both require a complex set of skills ranging from auditory perception to higher-order syntactic processing. Abilities related to memory, pattern recognition, and motor control are all involved in language functions. The neural underpinnings of language abilities [1]–[3] , language experience [4,5], as well as other language-relevant cognitive skills [6]–[8] have been established by a wealth of publications, and recent work emphasises the importance of multimodal and multivariate analyses of language learning profiles using not only language measures but also domain general cognitive ones [9]
The aim of the present work is to carry out a data-driven investigation of the key dimensions underlying language processing and learning, their subcomponents and their relationship with language-related brain activation.
The aim of the present work is to carry out a data-driven investigation of the key dimensions underlying language processing and learning, their subcomponents and their relationship with language-related brain activation.
Methods:
We obtained behavioural and brain data from 136 participants with a broad multilingual background. A subsample (N=25) had previously been diagnosed with dyslexia. We included general cognitive measures such as fluid intelligence, attention, and memory as well as measures of arithmetic, musicality, and fine motor skills. All the participants were also assessed on language-specific tests, spanning from traditional language aptitude measures to tests used to diagnose dyslexia. The participants also completed questionnaires regarding motivation for language learning and experience, reading history, and musical training.
For each participant, fMRI data were collected using a 3-Tesla Siemens Prisma scanner. Functional activation maps for language were obtained using an adapted version of the AliceLoc localiser from [10]. In the localiser, participants listened to 24 passages (18 s each) from the book 'Alice in Wonderland', read by a female native speaker of their first language (L1). The baseline condition consisted of 24 degraded versions of the passages (procedure from [10]).
The above work has resulted in two types of data: behavioural data, comprising 36 variables derived from the most relevant scores on the tasks and questionnaires, and brain imaging data comprising voxel-wise brain activation for the L1. Partial Least Squares Correlation (PLS; Figure 1) was used to uncover the dimensions commonly underlying the two types of data (henceforth, 'data modalities'). This method allows to first identify the main dimensions explaining the variation within each type of data, and in a second step to uncover multivariate patterns underlying common features between the two data modalities.
For each participant, fMRI data were collected using a 3-Tesla Siemens Prisma scanner. Functional activation maps for language were obtained using an adapted version of the AliceLoc localiser from [10]. In the localiser, participants listened to 24 passages (18 s each) from the book 'Alice in Wonderland', read by a female native speaker of their first language (L1). The baseline condition consisted of 24 degraded versions of the passages (procedure from [10]).
The above work has resulted in two types of data: behavioural data, comprising 36 variables derived from the most relevant scores on the tasks and questionnaires, and brain imaging data comprising voxel-wise brain activation for the L1. Partial Least Squares Correlation (PLS; Figure 1) was used to uncover the dimensions commonly underlying the two types of data (henceforth, 'data modalities'). This method allows to first identify the main dimensions explaining the variation within each type of data, and in a second step to uncover multivariate patterns underlying common features between the two data modalities.
·Figure 1. Schematic representation of the PLS analysis
Results:
The PLS analysis revealed two significant components, together explaining 53% of the variance. The first component was positively correlated with performance on higher-level general cognitive measures as well as with language-specific tasks relying on executive functions. In the neural data, this component was associated with greater brain activation in predominantly bilateral cortical areas involved in higher-level cognitive and linguistic skills. The second component was negatively correlated with both lower- and higher-level linguistic tasks and with motor skills, and was positively correlated with greater activation in predominantly left-lateralised brain regions linked to lower-level phonetic and acoustic processing.
Conclusions:
The present work reveals both associations and dissociations between key dimensions underlying language learning. Higher-level language-related skills and general cognition appear to be associated with activation in brain areas traditionally associated with higher level linguistic skills (i.e. semantic, syntactic processing, and sound-symbol association). We've also identified a complementary pattern of results in a component reflecting skills and brain areas related to lower-level acoustic, phonetic and motor domains.
Higher Cognitive Functions:
Higher Cognitive Functions Other 2
Language:
Speech Perception
Language Other 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Multivariate Approaches
Keywords:
Cognition
FUNCTIONAL MRI
Language
Memory
Multivariate
Other - Multilingualism
1|2Indicates the priority used for review
Provide references using author date format
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