Peer Review #1 of "Effective connectivity differences in motor network during passive movement of paretic and non-paretic ankles in subacute stroke patients (v0.1)"

Background: A better understanding of the neural changes associated with paresis in stroke patients could have important implications for therapeutic approaches.Dynamic Causal Modeling (DCM) for functional magnetic resonance imaging (fMRI) is commonly used for analyzing effective connectivity patterns of brain networks due to its significant property of modeling neural states behind fMRI signals.We applied this technique to analyze the differences between motor networks (MNW) activated by continuous passive movement (CPM) of paretic and non-paretic ankles in subacute stroke patients.This study aimed to identify CPM induced connectivity characteristics of the primary sensory area (S1) and the differences in extrinsic directed connections of the MNW and to explain the hemodynamic differences of brain regions of MNW.Methods: For the network analysis, we used ten stroke patients' task fMRI data collected under CPMs of both ankles.Regions for the MNW, the primary motor cortex (M1), the premotor cortex (PM), the supplementary motor area (SMA) and the S1 were defined in a data-driven way, by independent component analysis.For the network analysis of both CPMs, we compared twelve models organized into two model-families, depending on the S1 connections and input stimulus modelling.Using DCM, we evaluated the extrinsic connectivity strengths and hemodynamic parameters of both stimulations of all patients.Results: After a statistical comparison of the extrinsic connections and their modulations of the "best model", we concluded that three contralateral self-inhibitions (cM1, cS1, and cSMA), one contralateral inter-regional connection (cSMA→cM1), and one interhemispheric connection (cM1→iM1) were significantly different.Our research shows that hemodynamic parameters can be