Hierarchical Dynamic Causal Modeling of Resting-State fMRI Reveals Longitudinal Changes in Effective Connectivity in the Motor System after Thalamotomy for Essential Tremor.

Hae-Jeong Park,Peter Zeidman,Chongwon Pae,Jin Woo Chang,Karl Friston,Adeel Razi,Changwon Jang,Won Seok Chang

doi:10.3389/fneur.2017.00346

Abstract

Thalamotomy at the ventralis intermedius nucleus for essential tremor is known to cause changes in motor circuitry, but how a focal lesion leads to progressive changes in connectivity is not clear. To understand the mechanisms by which thalamotomy exerts enduring effects on motor circuitry, a quantitative analysis of directed or effective connectivity among motor-related areas is required. We characterized changes in effective connectivity of the motor system following thalamotomy using (spectral) dynamic causal modeling (spDCM) for resting-state fMRI. To differentiate long-lasting treatment effects from transient effects, and to identify symptom-related changes in effective connectivity, we subject longitudinal resting-state fMRI data to spDCM, acquired 1 day prior to, and 1 day, 7 days, and 3 months after thalamotomy using a non-cranium-opening MRI-guided focused ultrasound ablation technique. For the group-level (between subject) analysis of longitudinal (between-session) effects, we introduce a multilevel parametric empirical Bayes (PEB) analysis for spDCM. We found remarkably selective and consistent changes in effective connectivity from the ventrolateral nuclei and the supplementary motor area to the contralateral dentate nucleus after thalamotomy, which may be mediated via a polysynaptic thalamic–cortical–cerebellar motor loop. Crucially, changes in effective connectivity predicted changes in clinical motor-symptom scores after thalamotomy. This study speaks to the efficacy of thalamotomy in regulating the dentate nucleus in the context of treating essential tremor. Furthermore, it illustrates the utility of PEB for group-level analysis of dynamic causal modeling in quantifying longitudinal changes in effective connectivity; i.e., measuring long-term plasticity in human subjects non-invasively.

Highlights

Thalamotomy at the ventralis intermedius nucleus (Vim) is an effective treatment for essential tremor [1,2,3]
We applied spectral DCM (spDCM) for resting-state functional magnetic resonance imaging (rs-fMRI) to characterize the longitudinal changes in intrinsic effective connectivity after focal lesions of the thalamus in patients with essential tremors
We have introduced a simple and efficient way to analyze longitudinal spDCM at the group level using a multilevel parametric empirical Bayes (PEB)

Summary

Introduction

Thalamotomy at the ventralis intermedius nucleus (Vim) is an effective treatment for essential tremor [1,2,3]. A focal lesion of the Vim by thalamotomy is known to induce progressive changes at the circuit level of the motor system These progressive changes have been detected, in structural connectivity at remote regions—measured with diffusion tensor imaging (DTI) [4]—and in the inter-regional temporal synchrony (i.e., functional connectivity) of resting-state functional magnetic resonance imaging (rs-fMRI) signals [5]. Jang and colleagues [5] have shown thalamotomy-induced longitudinal changes of restingstate functional connectivity in both the whole brain network and at the level of the motor circuit. They suggested that alterations of resting-state functional connectivity over time involve a mixture of symptom-related (sustained) treatment effects and non-symptom-related (or indirectly related) transient effects. Effective connectivity refers to the causal influence that one neural system exerts over another, either at a synaptic or population level [7]

Methods

Results

Conclusion