Layer-specific myeloarchitecture of human S1 hand area in younger and older adults at 7T-MRI

Poster No:

1389 

Submission Type:

Abstract Submission 

Authors:

Juliane Doehler1, Alicia Northall2, Alessio Fracasso3, Gabriele Lohmann4, Pierre-Louis Bazin5, Daniel Haenelt6, Thomas Wolbers7, Esther Kuehn8,9,10

Institutions:

1Otto-von-Guericke University (OvGU), Magdeburg, Germany, 2Otto-von-Guericke University (OVGU), Magdeburg, Germany, 3Glasgow University, Glasgow, Scotland, 4Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 5University of Amsterdam, Amsterdam, Netherlands, 6Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 7German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany, 8Otto-von-Guericke University Magdeburg, Magdeburg, Germany, 9German Center for Neurodegenerative Diseases, Magdeburg, Germany, 10Center for Behavioral Brain Sciences, Magdeburg, Germany

First Author:

Juliane Doehler  
Otto-von-Guericke University (OvGU)
Magdeburg, Germany

Co-Author(s):

Alicia Northall  
Otto-von-Guericke University (OVGU)
Magdeburg, Germany
Alessio Fracasso  
Glasgow University
Glasgow, Scotland
Gabriele Lohmann, PhD  
Max Planck Institute for Biological Cybernetics
Tübingen, Germany
Pierre-Louis Bazin  
University of Amsterdam
Amsterdam, Netherlands
Daniel Haenelt  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Thomas Wolbers, Prof. Dr.  
German Center for Neurodegenerative Diseases (DZNE)
Magdeburg, Germany
Esther Kuehn, PhD  
Otto-von-Guericke University Magdeburg|German Center for Neurodegenerative Diseases|Center for Behavioral Brain Sciences
Magdeburg, Germany|Magdeburg, Germany|Magdeburg, Germany

Introduction:

The sense of touch is fundamental to our perception of reality. Critically, with advancing age, tactile abilities adapt. Lately, healthy aging has been linked to cortical myelin plasticity (Callaghan 2014, Grydeland 2019), but little is known on how this relates to functional cortex organization (e.g., body topography, resting-state connectivity) and tactile behavior. It has been suggested that layer-specific variation in myelin reflects functional specializations of the local cortical architecture (Nieuwenhuys 2013). However, prior in-vivo studies on age-related myeloarchitecture mainly described the cortex as a two-dimensional sheet. Recent advances in magnetic resonance imaging at 7 Tesla (7T-MRI) offer the possibility to study layer-specific myeloarchitecture in humans in-vivo (Kuehn 2017). Here, we targeted the questions of how myeloarchitecture of the human primary somatosensory cortex (S1) hand area varies with respect to cortical layers and age and how variation in layer-specific myelin relates to resting-state connectivity and tactile behavior.

Methods:

24 healthy, right-handed volunteers (n=12 younger: mean age 24 years, 7 females; n=12 older: mean age 71 years, 6 females) underwent 7T-MRI and tactile testing of index finger performance (see fig. 1). Quantitative T1 (qT1, 0.5 mm isotropic), used as myelin proxy (Stueber 2014), and EPI images (0.5 mm isotropic) of S1 (slab) were acquired. During functional scanning, vibro-tactile stimulation was applied to the fingertips of the right hand (localizer in S1, see fig. 1). A 5-minute resting-state scan was recorded. qT1 values were estimated using the equivolume model (Waehnert 2014). S1 was defined using anatomical landmarks (Yousry 1997). Eigenvector Centrality (EC) maps were calculated for n=20 participants (n=9 younger) using rectified linear unit correlation (Lohmann 2018). A mixed effects ANOVA was applied to qT1 (dependent: finger, cortical depth; independent: age group) and EC values (dependent: finger; independent: age group). Age effects on tactile behavior were tested with t-tests. Pearson correlations were calculated.
Supporting Image: OHBM_2021_Doehler_figure_1.png
 

Results:

qT1 values were extracted from finger representations (d1-d5) of contralateral S1 at different cortical depths (see fig. 2A). A 3-way mixed-effects ANOVA revealed a significant main effect of cortical depth (F(1.19,26.24)=390.86, p<.0001, ηG²=0.74) with decreasing qT1 values (increasing myelin levels) from superficial to deep cortical depth (see fig. 2A) as well as trends towards a main effect of finger (F(2.62,57.65)=2.29, p=.096, ηG²=0.01, see fig. 2A) and an interaction between cortical depth and age group (F(1.19,26.24)=3.34, p=.073, ηG²=0.02, see fig. 2A). A 2-way mixed-effects ANOVA revealed a significant main effect of finger (F(4,72)=3.60, p<.05, ηG²=0.06) and a trend towards a main effect of age (F(1,18)=4.09, p=.058, ηG²=0.13) with lower EC values in older adults. Across fingers, qT1 values were significantly correlated with EC values at superficial cortical depth in younger adults (see fig. 2B). Older compared to younger adults showed higher discrimination thresholds (t(14.38)=5.76, p<0.0001, r=0.84), lower precision grip accuracy (t(18.70)=-4.29, p<0.001, r=0.70) and higher detection thresholds (t(17.95)=3.67, p<.01, r=0.66). There was a negative correlation trend of deep qT1 and precision grip accuracy for d2 in younger adults (see fig. 2C).
Supporting Image: OHBM_2021_Doehler_figure_2.png
 

Conclusions:

Layer-specific qT1 mapping in younger and older adults suggests that myeloarchitecture of the S1 hand area is inhomogeneous and varies with respect to cortical depth and functional topography (independent of age). Particularly, the index finger appears to have a special role, most likely being preserved in older age. Our data also indicate that layer-specific myelin variation is related to distinctive widespread resting-state connectivity (related to superficial qT1) and phenotypes of behavior involving precise sensorimotor control (related to deep qT1).

Lifespan Development:

Aging 1

Neuroanatomy, Physiology, Metabolism and Neurotransmission:

Cortical Anatomy and Brain Mapping
Cortical Cyto- and Myeloarchitecture 2

Perception, Attention and Motor Behavior:

Perception: Tactile/Somatosensory

Keywords:

Aging
Cortical Layers
HIGH FIELD MR
Myelin
Somatosensory
Touch

1|2Indicates the priority used for review

My abstract is being submitted as a Software Demonstration.

No

Please indicate below if your study was a "resting state" or "task-activation” study.

Other
Resting state
Task-activation

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Healthy subjects

Was any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Yes

Was any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Functional MRI
Structural MRI
Behavior

For human MRI, what field strength scanner do you use?

7T

Which processing packages did you use for your study?

SPM
Other, Please list  -   MIPAV, cbstools, ITK-Snap, Matlab, R

Provide references using author date format

Callaghan, M. F. (2014), ‘Widespread age-related differences in the human brain microstructure revealed by quantitative magnetic resonance imaging’, Neurobiology of Aging, 35(8):1862–1872. doi:10.1016/j.neurobiolaging.2014.02.008.

Grydeland, H. (2019), 'Waves of Maturation and Senescence in Micro-structural MRI Markers of Human Cortical Myelination over the Lifespan', Cerebral Cortex, 29(3):1369-1381. doi: 10.1093/cercor/bhy330.

Kuehn, E. (2017), ‘Body Topography Parcellates Human Sensory and Motor Cortex’, Cerebral Cortex, 27(7):3790-3805. doi:10.1093/cercor/bhx026.

Lohmann, G. (2018), ‘Eigenvector centrality mapping for ultrahigh resolution fMRI data of the human brain’, biorxiv, 494732. https://doi.org/10.1101/494732.

Nieuwenhuys, R. (2013). ‘The myeloarchitectonic studies on the human cerebral cortex of the vogt–vogt school, and their significance for the interpretation of functional neuroimaging data’, Brain Structure and Function, 218(2):303–352. doi:10.1007/s00429-012-0460-z.

Stüber, C. (2014), ‘Myelin and iron concentration in the human brain: A quantitative study of mri contrast’, NeuroImage, 93():95–106. https://doi.org/10.1016/j.neuroimage.2014.02.026.

Waehnert, M. (2014), ‘Anatomically motivated modeling of cortical laminae’, NeuroImage, 93(2):210-220. doi:10.1016/j.neuroimage.2013.03.078.

Yousry, T. A. (1997), ‘Localization of the motor hand area to a knob on the precentral gyrus. A new landmark’, Brain, 120(1):141–157. https://doi.org/10.1093/brain/120.1.141.