Ultrashort echo time brain imaging links myelin content to cognitive flexibility
Poster No:
924
Submission Type:
Abstract Submission
Authors:
Liz Lee1, Chie Takahashi1, Katharina Zühlsdorff1, Onur Ozyurt1, Diana Rotaru1, Zhen Jiang2, Humberto Monsivais2, Guy B. Williams1, Uzay Emir2, Zoe Kourtzi1
Institutions:
1University of Cambridge, Cambridge, United Kingdom, 2Purdue University, West Lafayette, Indiana
First Author:
Co-Author(s):
Introduction:
Flexibly adapting to new situations and changes in dynamic environments is a key ability known as cognitive flexibility (Kupis and Uddin, 2023). Cognitive flexibility is typically studied using tasks that require switching between rules (e.g. Wisconsin Card Sorting Test, WCST; probabilistic reversal learning, PRL). Previous work has implicated dorsolateral prefrontal cortex (DLPFC) (Kim et al., 2011) and hippocampus (Rubin et al., 2014) in adopting new probabilistic rules and forming relational memory representations, respectively. Most brain imaging studies of cognitive flexibility have focused on functional activity and connectivity as measured by fMRI. However, the role of myelination - the process of forming myelin to enhance neural information transmission - in cognitive flexibility remains largely unknown.
Here, we test the role of myelination in DLPFC and hippocampus in cognitive flexibility. We employ cutting-edge ultrashort echo time (UTE) and ultrashort echo time magnetization transfer (UTE-MT) sequences to extract magnetisation transfer ratio (MTR). MTR is known to significantly correlate with myelin content as measured by histopathology (Guglielmetti et al., 2020). Yet, conventional MRI measures of myelination are confounded by iron concentration. Due to the specific chemical environment of the bilayer-bound protons, 80% of the myelin lipid 1H protons have T2* values well below 1 ms (Baadsvik et al., 2023). As their signal decays too fast to be captured by conventional MRI techniques with TEs in milliseconds or longer in "multiple gradient/spin echo imaging", UTE provides a promising method for direct measurement of myelin (Wilhelm et al., 2012).
Here, we test the role of myelination in DLPFC and hippocampus in cognitive flexibility. We employ cutting-edge ultrashort echo time (UTE) and ultrashort echo time magnetization transfer (UTE-MT) sequences to extract magnetisation transfer ratio (MTR). MTR is known to significantly correlate with myelin content as measured by histopathology (Guglielmetti et al., 2020). Yet, conventional MRI measures of myelination are confounded by iron concentration. Due to the specific chemical environment of the bilayer-bound protons, 80% of the myelin lipid 1H protons have T2* values well below 1 ms (Baadsvik et al., 2023). As their signal decays too fast to be captured by conventional MRI techniques with TEs in milliseconds or longer in "multiple gradient/spin echo imaging", UTE provides a promising method for direct measurement of myelin (Wilhelm et al., 2012).
Methods:
Fifty-four participants (26 female, age 43±6.6) from NIHR BioResource completed one behavioral and one MRI session. In the behavioural session, we measured cognitive flexibility using WCST and PRL tasks. In the MRI session (3T), we used UTE to estimate iron concentration (Shen et al., 2023) and UTE-MT to estimate (Guglielmetti et al., 2020). Image reconstruction was performed with ESPIRiT calibration using the Berkeley Advanced Reconstruction Toolbox and non-uniform fast Fourier transform. Image preprocessing was performed with FSL (coregistration,brain extraction), AFNI (bias correction), and SPM (Figure 1). We extracted ROI-based MTR and iron concentrations (Brainnetome atlas) (Fan et al., 2016) in DLPFC (Brodmann areas 8, 9, 46) (Sanches et al., 2009) and hippocampus. For iron concentration we regressed out age and sex. To control for iron contribution to myelin content, we regressed out iron concentration in addition to age, sex.
Results:
We observed a significant negative correlation of myelin content in DLPFC with PRL perseverative errors (Figure 2A; r = -0.30, p = .046). In contrast, iron concentration in DLPFC did not correlate significantly with perseverative errors (r = - 0.18, p = .232), suggesting that higher myelin content - rather than iron concentration - in DLPFC is associated with stronger flexibility in adopting new rules. Further, we observed a significant positive correlation of myelin content in the hippocampus with WCST perseverative errors (Figure 2B; r = 0.28, p = .042). In contrast, iron concentration in the hippocampus negatively correlated with WCST perseverative errors (r = -0.28, p = .041). Note that correlations of MTR without regressing out iron with perseverative errors were not significant (PRL, DLPFC, r = -0.19, p = .209; WCST, hippocampus, r = 0.265, p = .053), consistent with a confounding effect of iron in myelin measurements.
Conclusions:
Our results suggest that myelin content in the frontal and hippocampal regions relates to our ability to learn new rules in the context of cognitive flexibility tasks. Employing UTE and UTE-MT sequences, we control for the confounding effect of iron concentration in MTR measurements, providing new insights into the role of myelin in adaptive behaviour and cognitive flexibility.
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making 1
Novel Imaging Acquisition Methods:
Anatomical MRI 2
Keywords:
Cognition
Myelin
STRUCTURAL MRI
1|2Indicates the priority used for review
Provide references using author date format
Fan, L. et al. (2016) ‘The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture’, Cerebral Cortex, 26(8), pp. 3508–3526.
Guglielmetti, C. et al. (2020) ‘Longitudinal evaluation of demyelinated lesions in a multiple sclerosis model using ultrashort echo time magnetization transfer (UTE-MT) imaging’, NeuroImage, 208, p. 116415.
Kim, C. et al. (2011) ‘Common and Distinct Mechanisms of Cognitive Flexibility in Prefrontal Cortex’, The Journal of Neuroscience, 31(13), pp. 4771–4779.
Kupis, L.B. and Uddin, L.Q. (2023) ‘Developmental Neuroimaging of Cognitive Flexibility: Update and Future Directions’, Annual Review of Developmental Psychology, 5(1).
Rubin, R.D. et al. (2014) ‘The role of the hippocampus in flexible cognition and social behavior’, Frontiers in Human Neuroscience, 8.
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