Interhemispheric Connectivity Characterizes Cortical Reorganization in Motor-Related Networks After Cerebellar Lesions

Abstract

Although cerebellar-cortical interactions have been studied extensively in animal models and humans using modern neuroimaging techniques, the effects of cerebellar stroke and focal lesions on cerebral cortical processing remain unknown. In the present study, we analyzed the large-scale functional connectivity at the cortical level by combining high-density electroencephalography (EEG) and source imaging techniques to evaluate and quantify the compensatory reorganization of brain networks after cerebellar damage. The experimental protocol comprised a repetitive finger extension task by 10 patients with unilateral focal cerebellar lesions and 10 matched healthy controls. A graph theoretical approach was used to investigate the functional reorganization of cortical networks. Our patients, compared with controls, exhibited significant differences at global and local topological level of their brain networks. An abnormal rise in small-world network efficiency was observed in the gamma band (30-40 Hz) during execution of the task, paralleled by increased long-range connectivity between cortical hemispheres. Our findings show that a pervasive reorganization of the brain network is associated with cerebellar focal damage and support the idea that the cerebellum boosts or refines cortical functions. Clinically, these results suggest that cortical changes after cerebellar damage are achieved through an increase in the interactions between remote cortical areas and that rehabilitation should aim to reshape functional activation patterns. Future studies should determine whether these hypotheses are limited to motor tasks or if they also apply to cerebro-cerebellar dysfunction in general.

Network interactions underlying mirror feedback in stroke: A dynamic causal modeling study

“…Our investigation revealed MVF-related parietal-to-M1 coupling. Weakened parietal-to-M1 interactions (Grefkes and Fink, 2011, Takeuchi et al, 2012) have been previously identified in stroke, and restoring functional interactions among this network has been positively correlated with good recovery (Carter et al, 2010, van Meer et al, 2010, Wang et al, 2010, Grefkes and Fink, 2011, Rehme et al, 2011, Rehme et al, 2012, van Meer et al, 2012, De Vico Fallani et al, 2016). Mirror feedback, therefore, may be a useful clinical tool, as it has been shown to improve some outcomes in moderately to severely impaired patients (Thieme et al, 2012, Thieme et al, 2013, Pollock et al, 2014), and to activate specific networks that may favor recovery, particularly in patients who cannot otherwise engage their paretic hand in exercise.…”

“…Empirical evidence suggests that the activation of these regions (Grefkes and Fink, 2011, Rehme et al, 2011, Rehme et al, 2012), and restored interactions between these regions measured as functional and effective connectivity are important predictors of recovery (He et al, 2007, Carter et al, 2010, Wang et al, 2010, van Meer et al, 2012, De Vico Fallani et al, 2016). Therefore, understanding the MVF network interactions may unveil if mirror feedback has the potential to engage circuits in a manner that may be favorable for recovery.…”

The Implementation of Predictions During Sequencing

“…This s-MMN paradigm was studied in subjects with unilateral cerebellar lesions to exploit the possibility of testing cortical responses with and without cerebellar processing in the same subject. Because of the well-known crossed organization of cerebro-cerebellar circuits, unilateral cerebellar damage will affect only the cerebral cortex of the contralateral hemisphere (Di Lazzaro et al, 1994a, b, 1995; De Vico Fallani et al, 2016).…”

Compressibility of High-Density EEG Signals in Stroke Patients

“…Only Zeng et al [14] and Caliandro et al [15] compared the features of the EEGs collected at the impaired zones with the those recorded at the healthy zones: Caliandro et al [15] observed no difference between the two hemispheres of the same subject, whereas Zeng et al [14] claimed that the method they proposed needed to be further validated on EEG time series. As regards high-density EEG studies, De Vico Fallani et al [18] applied source imaging to HD-EEG to evaluate the compensatory reorganization of brain networks after cerebellar damage during a finger extension task. Sixty-four-channel EEGs were acquired during alternating movement tasks.…”