Pretherapeutic Motor Thalamus Resting-State Functional Connectivity with Visual Areas Predicts Tremor Arrest After Thalamotomy for Essential Tremor: Tracing the Cerebello-thalamo-visuo-motor Network

We previously demonstrated that network level functional connectivity in the human brain could be related to levels of inhibition in a major network node at baseline (<xref ref-type="bibr" rid="bib24">Stagg et al., 2014</xref>). In this study, we build upon this finding to directly investigate the effects of perturbing M1 GABA and resting state functional connectivity using transcranial direct current stimulation (tDCS), a neuromodulatory approach that has previously been demonstrated to modulate both metrics. FMRI data and GABA levels, as assessed by Magnetic Resonance Spectroscopy, were measured before and after 20 min of 1 mA anodal or sham tDCS. In line with previous studies, baseline GABA levels were negatively correlated with the strength of functional connectivity within the resting motor network. However, although we confirm the previously reported findings that anodal tDCS reduces GABA concentration and increases functional connectivity in the stimulated motor cortex; these changes are not correlated, suggesting they may be driven by distinct underlying mechanisms.

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Functional connectivity between somatosensory and motor brain areas predicts individual differences in motor learning by observing

Journal of Neurophysiology ◽

10.1152/jn.00275.2017 ◽

2017 ◽

Vol 118 (2) ◽

pp. 1235-1243 ◽

Cited By ~ 15

Author(s):

Heather R. McGregor ◽

Paul L. Gribble

Keyword(s):

Individual Differences ◽

Functional Connectivity ◽

Motor Learning ◽

Resting State ◽

Brain Function ◽

Motor Recovery ◽

Resting State Functional Connectivity ◽

Brain Areas ◽

Motor Network ◽

Sensory Motor

We show that individual differences in preobservation brain function can predict subsequent observation-related gains in motor learning. Preobservation resting-state functional connectivity within a sensory-motor network may be used as a biomarker for the extent to which observation promotes motor learning. This kind of information may be useful if observation is to be used as a way to boost neuroplasticity and sensory-motor recovery for patients undergoing rehabilitation for diseases that impair movement such as stroke.

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CHANGES OF RESTING-STATE FUNCTIONAL CONNECTIVITY AFTER DUAL-SITE TRANCSCRAINAL DIRECT CURRENT STIMULATION FOR ENHANCING NEURAL PLASTICITY OF GAIT-RELATED MOTOR NETWORK IN STROKE PATIENTS: AN FNIRS STUDY

10.26226/morressier.5cd45409190f54d9a4ac3e20 ◽

2019 ◽

Author(s):

Yun-Hee Kim

Keyword(s):

Functional Connectivity ◽

Direct Current ◽

Neural Plasticity ◽

Resting State ◽

Resting State Functional Connectivity ◽

Stroke Patients ◽

Direct Current Stimulation ◽

Motor Network ◽

Dual Site

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Abstract 6: Resting-state Functional Connectivity Changes After Stroke Rehabilitation Using Closed Loop Neurofeedback

Stroke ◽

10.1161/str.46.suppl_1.6 ◽

2015 ◽

Vol 46 (suppl_1) ◽

Author(s):

Veena A Nair ◽

Brittany M Young ◽

Zack Nigogosyan ◽

Alex Remsick ◽

Sonya Weber ◽

...

Keyword(s):

Functional Connectivity ◽

Upper Extremity ◽

Resting State ◽

Primary Motor Cortex ◽

Seed Region ◽

Resting State Functional Connectivity ◽

Stroke Patients ◽

Motor Network ◽

Brain Changes ◽

Left And Right

Introduction: Brain-computer interface (BCI)-EEG is a promising intervention for improving motor function after stroke. However, brain changes following intervention on a BCI-EEG system are not yet fully understood. We examined changes in resting state functional connectivity (RSFC) MRI in the motor network defined by 6 key regions in the left and right primary motor cortex (M1), left and right supplementary motor area (SMA), and left and right premotor cortex (PMC). Additionally, we investigated brain-behavior correlation between rsFC and a battery of outcome measures including the Barthel Index (BI), the Stroke Impact Scale(SIS), and the Action Research Arm Test (ARAT). Methods: Fifteen stroke patients with persistent mild to severe upper extremity impairment following ischemic stroke received intervention using BCI-EEG and were tested before (T1) and at 2-3 weeks (T2) mid intervention. 11 of these patients were also tested a third time at 4-6 weeks at the end of intervention (T3). Eyes closed, 10 minute resting fMRI and anatomical scans were acquired on a GE 3T MRI scanner. Right hemisphere stroke patients’ scans were flipped so that as a group the lesion was in the left (L) hemisphere and the impaired limb right (R). Seed region based connectivity analyses were performed to examine changes in RSFC over time and in inter-hemispheric and intra-hemispheric connectivity, and correlations between brain changes and behavioral changes were investigated. Results: BCI-EEG intervention led to significant increase in intra-hemispheric connectivity (p = .03) from T1 to T3. Inter-hemispheric connectivity increased from T1 to T3, trending towards significance (p = .06). Significant positive correlations were observed between changes in RSFC (L.M1 and L.PMC, L.M1 and R.PMC, L.SMA and R.PMC, and R.PMC and R.SMA) and change in upper extremity BI score (p ranging from .01 to .001); changes in RSFC between L.PMC and R.PMC correlated with hand strength on the SIS (p = .03). A trend was observed between increase in RSFC (L.M1 and R.PMC) and increase in total ARAT score but this was not significant. Conclusions: Results suggest that BCI-EEG intervention facilitate changes in RSFC in the motor network in stroke patients and these changes are associated with improved outcomes.

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