Background: FMRI resting state networks (RSNs) are used to characterize brain disorders. They also show extensive heterogeneity across patients. Identifying systematic differences between RSNs in... Show moreBackground: FMRI resting state networks (RSNs) are used to characterize brain disorders. They also show extensive heterogeneity across patients. Identifying systematic differences between RSNs in patients, i.e. discovering neurofunctional subtypes, may further increase our understanding of disease heterogeneity. Currently, no methodology is available to estimate neurofunctional subtypes and their associated RSNs simultaneously. New method: We present an unsupervised learning method for fMRI data, called Clusterwise Independent Component Analysis (C-ICA). This enables the clustering of patients into neurofunctional subtypes based on differences in shared ICA-derived RSNs.The parameters are estimated simultaneously, which leads to an improved estimation of subtypes and their associated RSNs. Results: In five simulation studies, the C-ICA model is successfully validated using both artificially and realistically simulated data (N = 30-40). The successful performance of the C-ICA model is also illustrated on an empirical data set consisting of Alzheimer's disease patients and elderly control subjects (N = 250). C-ICA is able to uncover a meaningful clustering that partially matches (balanced accuracy = .72) the diagnostic labels and identifies differences in RSNs between the Alzheimer and control cluster. Comparison with other methods: Both in the simulation study and the empirical application, C-ICA yields better results compared to competing clustering methods (i.e., a two step clustering procedure based on single subject ICA's and a Group ICA plus dual regression variant thereof) that do not simultaneously estimate a clustering and associated RSNs. Indeed, the overall mean adjusted Rand Index, a measure for cluster recovery, equals 0.65 for C-ICA and ranges from 0.27 to 0.46 for competing methods. Conclusions: The successful performance of C-ICA indicates that it is a promising method to extract neuro-functional subtypes from multi-subject resting state-fMRI data. This method can be applied on fMRI scans of patient groups to study (neurofunctional) subtypes, which may eventually further increase understanding of disease heterogeneity. Show less
This dissertation investigates how sound change is adopted by speakers and listeners, based on a currently-ongoing cluster of changes in Dutch termed the ‘Polder shift’. The main aim of the... Show moreThis dissertation investigates how sound change is adopted by speakers and listeners, based on a currently-ongoing cluster of changes in Dutch termed the ‘Polder shift’. The main aim of the dissertation is to form a bridge between five key areas of linguistics: historical phonology, sociophonetics, psycholinguistics, neurolinguistics, and quantitative linguistics. A unified account of these different angles to the study of sound change is not trivial. This dissertation uses psycholinguistic experiments combined with detailed quantitative analysis to study the contributions of the different components to the adoption of sound change in the medium and long term. The population studied in this dissertation is sociolinguistic migrants: in this case, Flemish speakers of Dutch who have migrated to the Netherlands, and thereby migrated from a non-Polder-shift area to a Polder-shift area. The methods adopted in this dissertation include a corpus study of regional variation, longitudinal psycholinguistic experiments over nine months’ time, cross-sectional psycholinguistic experiments spanning multiple decades of apparent time, and two neurolinguistic studies using EEG. Results show that the sociolinguistic migrants rapidly acquire allophonic variation at the phonological level (albeit not necessarily the associated sociolinguistic knowledge), but that it takes a long time (more than nine months, up to multiple decades) for this to carry forward to their behavioral production and perception, and moreover is subject to significant individual differences. The contributions by this dissertation show how the fundamentally sociolinguistic phenomenon of sound change can be studied empirically using psycho- and neurolinguistics, and profit from recent innovations in statistics. Show less
Novice teachers need mentoring support from experienced teachers as they prepare to become teachers. Such mentoring support needs to be responsive and adaptive to novice teachers’ learning. Mentor... Show moreNovice teachers need mentoring support from experienced teachers as they prepare to become teachers. Such mentoring support needs to be responsive and adaptive to novice teachers’ learning. Mentor teachers therefore require knowledge of novice teacher learning and of mentoring activities to support this learning. These are critical but underdeveloped components in the knowledge base of mentoring. This thesis draws on mentor teachers’ practical knowledge to inform the knowledge base of mentoring, and focuses on the question: What is the content of mentor teachers’ practical knowledge of adaptive response to their mentee teachers’ learning? Through questionnaires and interviews, the study elicited four components of mentor teachers’ practical knowledge of adaptive mentoring: 1) their mentoring conceptions, 2) their knowledge of mentoring activities, 3) their knowledge of novice teacher learning, and 4) their heuristics for responding to specific mentoring situations. Findings show that adaptive mentors focus on novice teacher construction of practical knowledge of teaching, and that confronting novices with problems is a central activity of adaptive mentoring. The study provides representations of shared mentor teacher knowledge of adaptive mentoring and a component model of mentor practical knowledge of adaptive mentoring, useful for developers of mentor training. Show less
Although many neuroimaging studies have investigated adolescent risk taking, few studies have dissociated between decision-making under risk (known probabilities) and ambiguity (unknown... Show moreAlthough many neuroimaging studies have investigated adolescent risk taking, few studies have dissociated between decision-making under risk (known probabilities) and ambiguity (unknown probabilities). Furthermore, which brain regions are sensitive to individual differences in task-related and self-reported risk taking remains elusive. We presented 198 adolescents (11-24 years, an age-range in which individual differences in risk taking are prominent) with an fMRI paradigm that separated decision-making (choosing to gamble or not) and reward outcome processing (gains, no gains) under risky and ambiguous conditions, and related this to task-related and self-reported risk taking. We observed distinct neural mechanisms underlying risky and ambiguous gambling, with risk more prominently associated with activation in parietal cortex, and ambiguity more prominently with dorsolateral prefrontal cortex (PFC), as well as medial PFC during outcome processing. Individual differences in task-related risk taking were positively associated with ventral striatum activation in the decision phase, specifically for risk, and negatively associated with insula and dorsomedial PFC activation, specifically for ambiguity. Moreover, dorsolateral PFC activation in the outcome phase seemed a prominent marker for individual differences in task-related risk taking under ambiguity as well as self-reported daily-life risk taking, in which greater risk taking was associated with reduced activation in dorsolateral PFC. Together, this study demonstrates the importance of considering multiple risk-taking measures, and contextual moderators, in understanding the neural mechanisms underlying adolescent risk taking. Show less
Aktar, E.; Mandell, D.J.; De Vente, W.; Majdandžić, M.; Raijmakers, M.E.J.; Bögels, S.M. 2016
Between 10 and 14 months, infants gain the ability to learn about unfamiliar stimuli by observing others’ emotional reactions to those stimuli, so called social referencing (SR). Joint processing... Show moreBetween 10 and 14 months, infants gain the ability to learn about unfamiliar stimuli by observing others’ emotional reactions to those stimuli, so called social referencing (SR). Joint processing of emotion and head/gaze direction is essential for SR. This study tested emotion and head/gaze direction effects on infants’ attention via pupillometry in the period following the emergence of SR. Pupil responses of 14-to-17-month-old infants (N = 57) were measured during computerized presentations of unfamiliar objects alone, before-and-after being paired with emotional (happy, sad, fearful vs. neutral) faces gazing towards (vs. away) from objects. Additionally, the associations of infants’ temperament, and parents’ negative affect/depression/anxiety with infants’ pupil responses were explored. Both mothers and fathers of participating infants completed questionnaires about their negative affect, depression and anxiety symptoms and their infants’ negative temperament. Infants allocated more attention (larger pupils) to negative vs. neutral faces when the faces were presented alone, while they allocated less attention to objects paired with emotional vs. neutral faces independent of head/gaze direction. Sad (but not fearful) temperament predicted more attention to emotional faces. Infants’ sad temperament moderated the associations of mothers’ depression (but not anxiety) with infants’ attention to objects. Maternal depression predicted more attention to objects paired with emotional expressions in infants low in sad temperament, while it predicted less attention in infants high in sad temperament. Fathers’ depression (but not anxiety) predicted more attention to objects paired with emotional expressions independent of infants’ temperament. We conclude that infants’ own temperamental dispositions for sadness, and their exposure to mothers’ and fathers’ depressed moods may influence infants’ attention to emotion-object associations in social learning contexts. Show less
