Brain effective connectome based on fMRI and DTI data: Bayesian causal learning and assessment.

Neuroscientific studies aim to find an accurate and reliable brain Effective Connectome (EC). Although current EC discovery methods have contributed to our understanding of brain organization, their performances are severely constrained by the short sample size and poor temporal resolution of fMRI data, and high dimensionality of the brain connectome. By leveraging the DTI data as prior knowledge, we introduce two Bayesian causal discovery frameworks -the Bayesian GOLEM (BGOLEM) and Bayesian FGES (BFGES) methods- that offer significantly more accurate and reliable ECs and address the shortcomings of the existing causal discovery methods in discovering ECs based on only fMRI data.

The variation of functional connectivity and activity before and after thalamotomy surgery (review).

Ablation surgeries are utilized to treat certain brain disorders. Recently, these surgeries have become more prevalent using techniques such as magnetic resonance guided focused ultrasound (MRgFUS) ablation and Gamma knife thalamotomy (GKT). However, as the thalamus plays a critical role in cognitive functions, the potential impact of these surgeries on functional connectivity and cognition is a matter of concern.

Construction of Meta-Thinking Educational Program Based on Mental-Brain Simulation () and Evaluating its Effectiveness on Executive Functions, Emotion Regulation, and Impulsivity in Children With ADHD: A Resting-State Functional MRI Study.

Objective: The aim of present research was to make a Meta-Thinking educational program based on mental-brain simulation and to evaluate its effectiveness on executive functions, emotion regulation and impulsivity in children with ADHD.

Methods: The research method was Embedded Design: Embedded Experimental Model. The research sample included 32 children with ADHD who were randomly assigned to two experimental and control groups.