tms.coef: Default TMS regression coefficients

In fernandoPalluzzi/tmsClassifier: Random Forest Classifiers for Transcranial Magnetic Stimulation Data

Description

Data.frame of TMS regression coefficients derived from default TMS data (Benussi, 2017). They include regression coefficients over time (t) for short-interval intracortical inhibition (SICI ~ bs0 + bs*t), intracortical facilitation (ICF ~ bi0 + bi*t), short-latency afferent inhibition (SAI ~ b0 + b1*t + b2*t^2), and long-interval intracortical inhibition (LICI ~ a0 + a1*t).

Usage

tms.coef

Format

"tms.coef" is a data.frame of 649 subjects (rows) and 9 TMS regression coefficients (columns). Subjects are subdivided into 273 Alzheimer's Disease patients (AD), 207 Frontotemporal Dementia patients (FTD), 67 Dementia with Lewy Bodies patients (DLB), and 147 healthy controls (HC).

References

Benussi A, Di Lorenzo F, Dell'Era V, Cosseddu M, Alberici A, Caratozzolo S, Cotelli MS, Micheli A, Rozzini L, Depari A, Flammini A, Ponzo V, Martorana A, Caltagirone C, Padovani A, Koch G, Borroni B. (2017). Transcranial magnetic stimulation distinguishes Alzheimer disease from frontotemporal dementia. Neurology, 89(7):665-672. https://doi.org/10.1212/WNL.0000000000004232

fernandoPalluzzi/tmsClassifier documentation built on Feb. 3, 2021, 12:31 p.m.