Development and validation of a brain maturation index using longitudinal neuroanatomical scans

NeuroImage ◽  
2015 ◽  
Vol 117 ◽  
pp. 311-318 ◽  
Author(s):  
Bo Cao ◽  
Benson Mwangi ◽  
Khader M. Hasan ◽  
Sudhakar Selvaraj ◽  
Cristian P. Zeni ◽  
...  
Keyword(s):  
Brain Maturation ◽  
Maturation Index ◽  
Development And Validation

scholarly journals Predicting age and clinical risk from the neonatal connectome

2020 ◽  
Author(s):  
Yassine Taoudi-Benchekroun ◽  
Daan Christiaens ◽  
Irina Grigorescu ◽  
Andreas Schuh ◽  
Maximilian Pietsch ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Brain Connectivity ◽  
Later Life ◽  
Absolute Error ◽  
Brain Maturation ◽  
Preterm Neonates ◽  
Efficient Treatment ◽  
Human Connectome Project ◽  
Maturation Index ◽  
Atypical Development

AbstractThe development of perinatal brain connectivity underpins motor, cognitive and behavioural abilities in later life. With the rise of advanced imaging methods such as diffusion MRI, the study of brain connectivity has emerged as an important tool to understand subtle alterations associated with neurodevelopmental conditions. Brain connectivity derived from diffusion MRI is complex, multi-dimensional and noisy, and hence it can be challenging to interpret on an individual basis. Machine learning methods have proven to be a powerful tool to uncover hidden patterns in such data, thus opening an opportunity for early identification of atypical development and potentially more efficient treatment.In this work, we used Deep Neural Networks and Random Forests to predict neurodevelopmental characteristics from neonatal structural connectomes, in a large sample of neonates (N = 524) derived from the developing Human Connectome Project. We achieved a highly accurate prediction of post menstrual age (PMA) at scan on term-born infants (Mean absolute error (MAE) = 0.72 weeks, r = 0.83, p<<0.001). We also achieved good accuracy when predicting gestational age at birth on a cohort of term and preterm babies scanned at term equivalent age (MAE = 2.21 weeks, r = 0.82, p<<0.001). From our models of PMA at scan for infants born at term, we computed the brain maturation index (i.e. predicted minus actual age) of individual preterm neonates and found significant correlation of this index with motor outcome at 18 months corrected age. Our results suggest that the neural substrate for later neurological functioning is detectable within a few weeks after birth in the structural connectome.

scholarly journals Characterization of late structural maturation with a neuroanatomical marker that considers both cortical thickness and intracortical myelination

2021 ◽  
Author(s):  
Sophie Maingault ◽  
Antonietta Pepe ◽  
Bernard Mazoyer ◽  
Nathalie Tzourio-Mazoyer ◽  
Fabrice Crivello
Keyword(s):  
Cortical Thickness ◽  
Structural Changes ◽  
Right Hemisphere ◽  
Linear Increase ◽  
Brain Maturation ◽  
Linear Component ◽  
Age Related ◽  
Maturation Index ◽  
Cortical Maturation

ABSTRACTThe cortical ribbon changes throughout a person’s lifespan, with the most significant changes occurring during crucial development and aging periods. Changes during adulthood are rarely investigated due to the scarcity of neuroimaging data during this period. After childhood, the brain loses gray matter, which is evidenced by an apparent reduction in cortical thickness (CT); one factor of this thinning process is intense ongoing intracortical myelination (MYEL). Here, we report age-related changes in CT, MYEL, and their ratio in 447 participants aged 18 to 57 years (BIL&GIN cohort). We propose the CT/MYEL ratio to be a multimodal cortical maturation index (MATUR) capable of reflecting 1) stages during which CT and MYEL patterns diverge and 2) the regional differences in cortical maturation that occur in adulthood. Age mainly decreased CT in all cortical regions, with larger reductions occurring in the bilateral insular lobes, temporal and frontal poles, and cingulate cortices. Age led to a linear increase in MYEL in the entire cortex and larger increases in the primary motor, auditory, and visual cortices. The effects of age on the MATUR index were characterized by both linear and quadratic components. The linear component mimicked the pattern found in CT, with 1) a robust amplification of the global and regional effects of age on CT and 2) evidence of new bilateral linear decreases in the frontal and cortical cortices. Most importantly, age exhibited additional large quadratic effects on the MATUR index in the bilateral frontal (more prominent in the right hemisphere), parietal, temporal, and cingulate regions that were not highlighted by the CT metric. Thus, the MATUR index was more sensitive to age-related cortical structural changes during adulthood than was either CT or MYEL alone. As evidenced by the large quadratic component of the effect of age, the newly proposed maturation index dramatically improved the characterization of the regional cortical territories, uncovering the latest brain maturation steps that occur before stabilization and deterioration occur in mid- and late adulthood.

scholarly journals Development and Validation of a Semiquantitative Brain Maturation Score on Fetal MR Images: Initial Results

Radiology ◽  
2013 ◽  
Vol 268 (1) ◽  
pp. 200-207 ◽  
Author(s):  
Arastoo Vossough ◽  
Catherine Limperopoulos ◽  
Mary E. Putt ◽  
Adre J. du Plessis ◽  
Peter J. Schwab ◽  
...  
Keyword(s):  
Brain Maturation ◽  
Mr Images ◽  
Development And Validation ◽  
Initial Results ◽  
Fetal Mr

Brain Maturation in Children With Cochlear Implants

ASHA Leader ◽  
2009 ◽  
Vol 14 (5) ◽  
pp. 14-17 ◽  
Author(s):  
Anu Sharma ◽  
Amy Nash
Keyword(s):  
Cochlear Implants ◽  
Brain Maturation

18: Measuring Quality-of-Life after Surgery: Development and Validation of the Convalescence and Recovery Evaluation (CARE)

2007 ◽  
Vol 177 (4S) ◽  
pp. 7-7
Author(s):  
Brent K. Hollenbeck ◽  
J. Stuart Wolf ◽  
Rodney L. Dunn ◽  
Martin G. Sanda ◽  
David P. Wood ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Development And Validation

Development of the Teacher Attitudes Towards Self-Regulated Learning Scale

2018 ◽  
Vol 34 (3) ◽  
pp. 193-205 ◽  
Author(s):  
Julia Steinbach ◽  
Heidrun Stoeger
Keyword(s):  
Factor Analysis ◽  
Primary School ◽  
Factor Structure ◽  
Concurrent Validity ◽  
Binary Logistic Regression ◽  
Affective Component ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Teachers Attitudes ◽  
Development And Validation

Abstract. We describe the development and validation of an instrument for measuring the affective component of primary school teachers’ attitudes towards self-regulated learning. The questionnaire assesses the affective component towards those cognitive and metacognitive strategies that are especially effective in primary school. In a first study (n = 230), the factor structure was verified via an exploratory factor analysis. A confirmatory factor analysis with data from a second study (n = 400) indicated that the theoretical factor structure is appropriate. A comparison with four alternative models identified the theoretically derived factor structure as the most appropriate. Concurrent validity was demonstrated by correlations with a scale that measures the degree to which teachers create learning environments that enable students to self-regulate their learning. Retrospective validity was demonstrated by correlations with a scale that measures teachers’ experiences with self-regulated learning. In a third study (n = 47), the scale’s concurrent validity was tested with scales measuring teachers’ evaluation of the desirability of different aspects of self-regulated learning in class. Additionally, predictive validity was demonstrated via a binary logistic regression, with teachers attitudes as predictor on their registration for a workshop on self-regulated learning and their willingness to implement a seven-week training program on self-regulated learning.

Development and Validation of a German Language Unit-Level Organizational Citizenship Behavior (OCB) Scale

2020 ◽  
Vol 36 (5) ◽  
pp. 852-863 ◽  
Author(s):  
George Gunnesch-Luca ◽  
Klaus Moser
Keyword(s):  
Factor Analysis ◽  
Organizational Citizenship ◽  
Organizational Citizenship Behavior ◽  
Helping Behavior ◽  
Citizenship Behavior ◽  
German Language ◽  
Individual Level ◽  
Unit Level ◽  
Confirmatory Factor ◽  
Development And Validation

Abstract. The current paper presents the development and validation of a unit-level Organizational Citizenship Behavior (OCB) scale based on the Referent-Shift Consensus Model (RSCM). In Study 1, with 124 individuals measured twice, both an Exploratory Factor Analysis (EFA) and a Confirmatory Factor Analysis (CFA) established and confirmed a five-factor solution (helping behavior, sportsmanship, loyalty, civic virtue, and conscientiousness). Test–retest reliabilities at a 2-month interval were high (between .59 and .79 for the subscales, .83 for the total scale). In Study 2, unit-level OCB was analyzed in a sample of 129 work teams. Both Interrater Reliability (IRR) measures and Interrater Agreement (IRA) values provided support for RSCM requirements. Finally, unit-level OCB was associated with group task interdependence and was more predictable (by job satisfaction and integrity of the supervisor) than individual-level OCB in previous research.

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