No other neurophysiological measure (MEP, SICI, ICF, sICF) showed a significant correlation with micro-online or micro-offline learning¶

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Apart from the LICI–micro-offline-T correlation, Bayesian Pearson correlations between the TMS indices (MEP, SICI, ICF, sICF) and the behavioral measures were not significant. → Pasquale Cardellicchio & Sara Borgomaneri 2025

Evidence¶

Pasquale Cardellicchio & Sara Borgomaneri 2025¶

Pasquale Cardellicchio & Sara Borgomaneri. (2025). Level of M1 GABAB predicts micro offline consolidation of motor learning during wakefulness. npj Science of Learning 10:10. https://doi.org/10.1038/s41539-025-00299-1

q2 · i? · associational · r1

Bayesian Pearson correlation matrix (Table 1) covering MEP, SICI, ICF and sICF against micro-online-T, micro-offline-T, learning-rate parameters K1–K3, Block-T and tapping speed in the same 16-participant experiment; no effect sizes are printed for these null findings, so no equivalence claim is made.

"No other significant correlation was reported (see Table1)."

Discussion¶

Related Claims¶

• In a Bayesian linear regression, micro-offline-T learning explains a moderate proportion of variance in LICI (R² = 0.69), with moderate evidence for its inclusion — related
• Lower resting GABAB-mediated inhibition in M1 (measured as LICI) is strongly negatively associated with micro-offline motor consolidation gains during early learning — related
• The GABAB–micro-offline correlation is significantly stronger than the corresponding GABAA (SICI) correlation — related