Multi sequence average templates for aging and neurodegenerative disease populations

Dadar, Mahsa; Camicioli, Richard; Duchesne, Simon

doi:10.1038/s41597-022-01341-2

Cited by 8 publications

(3 citation statements)

References 38 publications

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“…We used the MNI-152 brain as a commonly utilized template, but there may be closer matching composite MRI scans depending on the population of interest. For instance, if a researcher wanted to investigate the group-level E-fields in an aging population could consider using more specific age-matched ( Fillmore et al, 2015 ) or diagnosis-matched ( Dadar et al, 2022 ) templates for potentially more accurate simulations. While we used bilateral electrode placements (i.e., C3-C4 and F3-F4) instead of other common electrode placements (e.g., C3-SO and F3-SO), prior large-scale findings have shown that there are no significant differences in E-field magnitudes between C3-C4 and C3-SO ( Caulfield and George, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Template MRI scans reliably approximate individual and group-level tES and TMS electric fields induced in motor and prefrontal circuits

Cho,

Van Hoornweder,

Sege

et al. 2023

Front. Neural Circuits

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BackgroundElectric field (E-field) modeling is a valuable method of elucidating the cortical target engagement from transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES), but it is typically dependent on individual MRI scans. In this study, we systematically tested whether E-field models in template MNI-152 and Ernie scans can reliably approximate group-level E-fields induced in N = 195 individuals across 5 diagnoses (healthy, alcohol use disorder, tobacco use disorder, anxiety, depression).MethodsWe computed 788 E-field models using the CHARM–SimNIBS 4.0.0 pipeline with 4 E-field models per participant (motor and prefrontal targets for TMS and tES). We additionally calculated permutation analyses to determine the point of stability of E-fields to assess whether the 152 brains represented in the MNI-152 template is sufficient.ResultsGroup-level E-fields did not significantly differ between the individual vs. MNI-152 template and Ernie scans for any stimulation modality or location (p > 0.05). However, TMS-induced E-field magnitudes significantly varied by diagnosis; individuals with generalized anxiety had significantly higher prefrontal and motor E-field magnitudes than healthy controls and those with alcohol use disorder and depression (p < 0.001). The point of stability for group-level E-field magnitudes ranged from 42 (motor tES) to 52 participants (prefrontal TMS).ConclusionMNI-152 and Ernie models reliably estimate group-average TMS and tES-induced E-fields transdiagnostically. The MNI-152 template includes sufficient scans to control for interindividual anatomical differences (i.e., above the point of stability). Taken together, using the MNI-152 and Ernie brains to approximate group-level E-fields is a valid and reliable approach.

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Section: Discussionmentioning

confidence: 99%

Template MRI scans reliably approximate individual and group-level tES and TMS electric fields induced in motor and prefrontal circuits

Cho,

Van Hoornweder,

Sege

et al. 2023

Front. Neural Circuits

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“…missing slices, incomplete field of view), as well as linear and nonlinear alignment of the images with the outline of the MNI-ICBM152-2009c average template (Manera et al, 2020). Registration QC was conducted following the protocols outlined in Dadar et al 2018, 2022 (Dadar et al, 2022, 2018). Each image in the two datasets underwent these steps, and quality ratings were recorded.…”

Section: Methodsmentioning

confidence: 99%

Investigating the impact of motion in the scanner on brain age predictions

Moqadam

Dadar

Zeighami

2023

Preprint

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Introduction: Brain Age Gap (BAG) is defined as the difference between the brain's predicted age and the chronological age of an individual. Magnetic resonance imaging (MRI)-based BAG can quantify acceleration of brain aging, and is used to measure brain health as aging and disease interact. Motion in the scanner is a common occurrence that can affect the acquired MRI data and act as a major confound in the derived models. As such, age related changes in head motion may impact the observed age-related differences. However, the relationship between head motion and BAG has not been directly examined. The aim of this study is to assess the impact of motion on voxel-based morphometry (VBM) based BAG. Methods: Data were obtained from two sources: i) T1-weighted (T1w) MRIs from the Cambridge Centre for Ageing and Neuroscience (CamCAN) were used to train the brain age prediction model, and ii) T1w MRIs from the Movement-related artifacts (MR-ART) dataset were used to assess the impact of motion on BAG. MR-ART includes one motion-free and two motion-affected (one low and one high) 3D T1w MRIs. We also visually rated the motion levels of the MR-ART MRIs from 0 to 5, with 0 meaning no motion and 5 high motion levels. All images were pre-processed through a standard VBM pipeline. GM density across cortical and subcortical regions were then used to train the brain age prediction model and assess the relationship between BAG and MRI motion. Principal component analysis was used to perform dimension reduction and extract the VBM-based features. BAG was estimated by regressing out the portion of delta age explained by chronological age. Linear mixed effects models were used to investigate the relationship between BAG and motion session as well as motion severity, including participant IDs as random effects. Results: In contrast with the session with no induced motion, predicted delta age was significantly higher for high motion sessions (t-value = 5.06, p < 0.0001), with marginal effect for low motion sessions (t-value = 1.95, p = 0.051). In addition, delta age was significantly associated with motion severity as evaluated by visual rating (t = 4.46, p < 0.0001). Conclusion: Motion in the scanner can significantly impact brain age estimates, and needs to be accounted for as a confound, particularly when studying populations that are known to have higher levels of motion in the scanner. These results have significant implications for brain age studies in aging and neurodegeneration. Based on these findings, we recommend assessment and inclusion of visual motion ratings in such studies.

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“…To facilitate comparisons across subjects, data from each subject should be registered to a template. Moreover, templates based on multiple subjects are optimal for group-level analyses because they possess features that are more representative of the population's "average" brain anatomy which offers higher cross-subject validity (Dadar et al, 2022;Evans et al, 2012;Fonov et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

MEBRAINS 1.0: a new population-based macaque atlas

Balan,

Zhu,

et al. 2023

Preprint

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Due to their fundamental relevance, the number of anatomical macaque brain templates is constantly growing. Novel templates aim to alleviate limitations of previously published atlases and offer the foundation to integrate multiscale multimodal data. Typical limitations of existing templates include their reliance on one subject, their unimodality (usually only T1 or histological images), or lack of anatomical details. The MEBRAINS template overcomes these limitations by using a combination of T1 and T2 images, from the same 10 animals (Macaca mulatta), which are averaged by the multi-brain toolbox for diffeomorphic registration and segmentation. The resulting volumetric T1 and T2 templates are supplemented with high quality white and gray matter surfaces built with FreeSurfer. Human-curated segmentations of pial surface, white/gray matter interface and major subcortical nuclei were used to analyse the relative quality of the MEBRAINS template. Recently published 3D maps of the macaque inferior parietal lobe and (pre)motor cortex were warped to the MEBRAINS surface template, thus populating it with a parcellation scheme based on cyto- and receptor architectonic analyses. Finally, 9 CT scans of the same monkeys were registered to the T1 modality and co-registered to the template. Through its main features (multi-subject, multi-modal, volume-and-surface, traditional and deep learning-based segmentations), MEBRAINS aims to improve integration of multi-modal multi-scale macaque data and is quantitatively equal or better compared to currently widely used macaque templates. The template is integrated in the EBRAINS and Scalable Brain Atlas web-based infrastructures, each of which comes with its own suite of spatial registration tools.

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Multi sequence average templates for aging and neurodegenerative disease populations

Cited by 8 publications

References 38 publications

Template MRI scans reliably approximate individual and group-level tES and TMS electric fields induced in motor and prefrontal circuits

Template MRI scans reliably approximate individual and group-level tES and TMS electric fields induced in motor and prefrontal circuits

Investigating the impact of motion in the scanner on brain age predictions

MEBRAINS 1.0: a new population-based macaque atlas

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