Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Aug 14:13:841.
doi: 10.3389/fnins.2019.00841. eCollection 2019.

Determinants of Inter-Individual Variability in Corticomotor Excitability Induced by Paired Associative Stimulation

Lora Minkova  1   2   3 , Jessica Peter  1 , Ahmed Abdulkadir  1 , Lena V Schumacher  4 , Christoph P Kaller  3   5 , Christoph Nissen  2   6   7 , Stefan Klöppel  1   8 , Jacob Lahr  2   3
Affiliations

Determinants of Inter-Individual Variability in Corticomotor Excitability Induced by Paired Associative Stimulation

Lora Minkova et al. Front Neurosci. .

Abstract

Transcranial magnetic stimulation (TMS) is a well-established tool in probing cortical plasticity in vivo. Changes in corticomotor excitability can be induced using paired associative stimulation (PAS) protocol, in which TMS over the primary motor cortex is conditioned with an electrical peripheral nerve stimulation of the contralateral hand. PAS with an inter-stimulus interval of 25 ms induces long-term potentiation (LTP)-like effects in cortical excitability. However, the response to a PAS protocol tends to vary substantially across individuals. In this study, we used univariate and multivariate data-driven methods to investigate various previously proposed determinants of inter-individual variability in PAS efficacy, such as demographic, cognitive, clinical, neurophysiological, and neuroimaging measures. Forty-one right-handed participants, comprising 22 patients with amnestic mild cognitive impairment (MCI) and 19 healthy controls (HC), underwent the PAS protocol. Prior to stimulation, demographic, genetic, clinical, as well as structural and resting-state functional MRI data were acquired. The two groups did not differ in any of the variables, except by global cognitive status. Univariate analysis showed that only 61% of all participants were classified as PAS responders, irrespective of group membership. Higher PAS response was associated with lower TMS intensity and with higher resting-state connectivity within the sensorimotor network, but only in responders, as opposed to non-responders. We also found an overall positive correlation between PAS response and structural connectivity within the corticospinal tract, which did not differ between groups. A multivariate random forest (RF) model identified age, gender, education, IQ, global cognitive status, sleep quality, alertness, TMS intensity, genetic factors, and neuroimaging measures (functional and structural connectivity, gray matter (GM) volume, and cortical thickness as poor predictors of PAS response. The model resulted in low accuracy of the RF classifier (58%; 95% CI: 42 - 74%), with a higher relative importance of brain connectivity measures compared to the other variables. We conclude that PAS variability in our sample was not well explained by factors known to influence PAS efficacy, emphasizing the need for future replication studies.

Keywords: DTI; TMS; corticospinal tract; paired associative stimulation; random forest; resting-state fMRI; sensorimotor network.

PubMed Disclaimer

Figures

FIGURE 1
FIGURE 1
TMS results: (A) Correlational analysis between TMS intensity and PAS response, divided into responders and non-responders. (B) An exemplary TMS-induced field distribution from the simulation computed in SimNIBS.
FIGURE 2
FIGURE 2
Resting-state fMRI results: (A) Average functional connectivity map of the sensorimotor network with the TMS hotspot as a seed (p–FDR < 0.05). The color bar represents T-values. (B) Correlation analysis between PAS response and functional connectivity between primary motor cortex (M1) and primary somatosensory cortex (S1).
FIGURE 3
FIGURE 3
DTI results: (A) Probabilistic fiber tractography of the corticospinal tract (CST). (B) Correlation analysis between PAS response and average fractional anisotropy (FA) of the CST.
FIGURE 4
FIGURE 4
Random forest analysis: (A) Receiver operating characteristic (ROC) curves for the RF model with 19 features (AUC 0.49). (B) Importance of single variables.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Alagona G., Bella R., Ferri R., Carnemolla A., Pappalardo A., Costanzo E., et al. (2001). Transcranial magnetic stimulation in Alzheimer disease: motor cortex excitability and cognitive severity. Neurosci. Lett. 314 57–60. 10.1016/S0304-3940(01)02288-1 - DOI - PubMed
    1. Albert M. S., DeKosky S. T., Dickson D., Dubois B., Feldman H. H., Fox N. C., et al. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the national institute on aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 7 270–279. 10.1016/j.jalz.2011.03.008 - DOI - PMC - PubMed
    1. Antonenko D., Nierhaus T., Meinzer M., Prehn K., Thielscher A., Ittermann B., et al. (2018). Age-dependent effects of brain stimulation on network centrality. NeuroImage 176 71–82. 10.1016/j.neuroimage.2018.04.038 - DOI - PubMed
    1. Arai N., Müller-Dahlhaus F., Murakami T., Bliem B., Lu M.-K., Ugawa Y., et al. (2011). State-dependent and timing-dependent bidirectional associative plasticity in the human SMA-M1 network. J. Neurosci. 31 15376–15383. 10.1523/JNEUROSCI.2271-11.2011 - DOI - PMC - PubMed
    1. Ashburner J. (2007). A fast diffeomorphic image registration algorithm. NeuroImage, 38 95–113. 10.1016/j.neuroimage.2007.07.007 - DOI - PubMed