Martin Havlicek

TL;DR: A multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing is introduced and is demonstrated by identifying the effects of age and gender on the resting-state networks of 603 healthy adolescents and adults.

TL;DR: This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art Kalman filtering, which promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous input.

TL;DR: A new fMRI model inspired by experimental observations about the physiological underpinnings of the BOLD signal is introduced and it is demonstrated using experimental data that it is necessary to take into account both neuronal and vascular transients to accurately model the signal dynamics of fMRI data.

TL;DR: This work proposes an approach to dynamic Granger causality in the frequency domain for evaluating functional network connectivity in fMRI data and demonstrates the effectiveness and robustness of the dynamic approach, significantly improved by combining a forward and backward Kalman filter that improved estimates compared to the standard time-invariant MAR modeling.

TL;DR: The results suggest that performing an active task like AOD may be facilitated by recruiting more neurons and higher activation of related networks rather than collaboration among different brain networks.