White matter microstructural changes in short-term learning of a continuous visuomotor sequence

Tremblay, Stéfanie; Jäger, Anna‐Thekla; Huck, Julia; Giacosa, Chiara; Beram, Stephanie; Schneider, Uta; Grahl, Sophia; Villringer, Arno; Tardif, Christine; Bazin, Pierre‐Louis; Steele, Christopher; Gauthier, Claudine

doi:10.1007/s00429-021-02267-y

Cited by 9 publications

(7 citation statements)

References 129 publications

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“…Our previous study (Jäger et al, 2022) found the right SMA to be relevant for sequence-specific learning using EC, as supported by structural data from the same cohort (Tremblay et al, 2021). The current results showed HE decreases in left SMA with the identified cluster spanning across both hemispheres, extending our findings to this region, which has been found relevant for right-hand tasks in prior studies.…”

Section: Discussionsupporting

confidence: 88%

“…Whole brain HE maps were computed before (on day 1) and after learning the task (on day 5) as well as 12 days after no additional training took place. The present data has been published in previous studies, which focused on measures of functional connectivity and white matter changes, respectively (Jäger et al, 2022 ; Tremblay et al, 2021 ). The majority of the methods have previously been described in detail in (Jäger et al, 2022 ) and will briefly be presented here.…”

Section: Methodsmentioning

confidence: 66%

“…The present data has been published in previous studies, which focused on measures of functional connectivity and white matter changes, respectively (Jäger et al, 2022;Tremblay et al, 2021). The majority of the methods have previously been described in detail in (Jäger et al, 2022) and will briefly be presented here.…”

Section: Methodsmentioning

confidence: 99%

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Decreased long‐range temporal correlations in the resting‐state functional magnetic resonance imaging blood‐oxygen‐level‐dependent signal reflect motor sequence learning up to 2 weeks following training

Jäger,

Bailey,

Huntenburg

et al. 2023

Human Brain Mapping

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Decreased long‐range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long‐range temporal memory within resting‐state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel‐wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well‐known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting‐state and suggests that a cortical subset of sequence‐specific regions may continue to represent a functional signature of learning reflected in decreased long‐range temporal dependence after a period of inactivity.

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Section: Discussionsupporting

confidence: 88%

Section: Methodsmentioning

confidence: 66%

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Decreased long‐range temporal correlations in the resting‐state functional magnetic resonance imaging blood‐oxygen‐level‐dependent signal reflect motor sequence learning up to 2 weeks following training

Jäger,

Bailey,

Huntenburg

et al. 2023

Human Brain Mapping

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“…The dataset was acquired in the context of a longitudinal study, where the participants learned to perform a motor sequence. Descriptions of this data have previously been published (Huck et al, 2019;Jäger et al, 2021;Tremblay et al, 2021). Briefly, participants were trained on a motor task over a time period of 17 days.…”

Section: Scanning Protocolmentioning

confidence: 99%

Modeling venous bias in resting state functional MRI metrics

Huck

Jäger

Schneider

et al. 2023

Human Brain Mapping

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Resting‐state (rs) functional magnetic resonance imaging (fMRI) is used to detect low‐frequency fluctuations in the blood oxygen‐level dependent (BOLD) signal across brain regions. Correlations between temporal BOLD signal fluctuations are commonly used to infer functional connectivity. However, because BOLD is based on the dilution of deoxyhemoglobin, it is sensitive to veins of all sizes, and its amplitude is biased by draining veins. These biases affect local BOLD signal location and amplitude, and may also influence BOLD‐derived connectivity measures, but the magnitude of this venous bias and its relation to vein size and proximity is unknown. Here, veins were identified using high‐resolution quantitative susceptibility maps and utilized in a biophysical model to investigate systematic venous biases on common local rsfMRI‐derived measures. Specifically, we studied the impact of vein diameter and distance to veins on the amplitude of low‐frequency fluctuations (ALFF), fractional ALFF (fALFF), Hurst exponent (HE), regional homogeneity (ReHo), and eigenvector centrality values in the grey matter. Values were higher across all distances in smaller veins, and decreased with increasing vein diameter. Additionally, rsfMRI values associated with larger veins decrease with increasing distance from the veins. ALFF and ReHo were the most biased by veins, while HE and fALFF exhibited the smallest bias. Across all metrics, the amplitude of the bias was limited in voxel‐wise data, confirming that venous structure is not the dominant source of contrast in these rsfMRI metrics. Finally, the models presented can be used to correct this venous bias in rsfMRI metrics.

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“…One hour of neurofeedback training with motor imagery was associated with increased fractional anisotropy in the sensorimotor segment of the corpus callosum [ 95 ]. Learning a complex visuomotor sequence over five consecutive days came along with changes of WM microstructure in the tracts underlying the sensorimotor cortices [ 96 ].…”

Section: How Best Can the Motor Reserve Be Quantified?mentioning

confidence: 99%

Considering the response in addition to the challenge – a narrative review in appraisal of a motor reserve framework

Zeller,

Hiew,

Odorfer

et al. 2024

Aging

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The remarkable increase in human life expectancy over the past century has been achieved at the expense of the risk of age-related impairment and disease. Neurodegeneration, be it part of normal aging or due to neurodegenerative disorders, is characterized by loss of specific neuronal populations, leading to increasing clinical impairment. The individual course may be described as balance between aging- or disease-related pathology and intrinsic mechanisms of adaptation. There is plenty of evidence that the human brain is provided with exhaustible resources to maintain function in the face of adverse conditions. While a reserve concept has mainly been coined in cognitive neuroscience, emerging evidence suggests similar mechanisms to underlie individual differences of adaptive capacity within the motor system. In this narrative review, we summarize what has been proposed to date about a motor reserve (mR) framework. We present current evidence from research in aging subjects and people with neurological conditions, followed by a description of what is known about potential neuronal substrates of mR so far. As there is no gold standard of mR quantification, we outline current approaches which describe various indicators of mR. We conclude by sketching out potential future directions of research. Expediting our understanding of differences in individual motor resilience towards aging and disease will eventually contribute to new, individually tailored therapeutic strategies. Provided early diagnosis, enhancing the individual mR may be suited to postpone disease onset by years and may be an efficacious contribution towards healthy aging, with an increased quality of life for the elderly.

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White matter microstructural changes in short-term learning of a continuous visuomotor sequence

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Cited by 9 publications

References 129 publications

Decreased long‐range temporal correlations in the resting‐state functional magnetic resonance imaging blood‐oxygen‐level‐dependent signal reflect motor sequence learning up to 2 weeks following training

Decreased long‐range temporal correlations in the resting‐state functional magnetic resonance imaging blood‐oxygen‐level‐dependent signal reflect motor sequence learning up to 2 weeks following training

Modeling venous bias in resting state functional MRI metrics

Considering the response in addition to the challenge – a narrative review in appraisal of a motor reserve framework

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