Neurophysiological biomarkers of motor improvement from Constraint-Induced Movement Therapy and Robot-Assisted Therapy in participants with stroke.

Background: The mechanism of stroke recovery is related to the reorganization of cerebral activity that can be enhanced by rehabilitation therapy. Two well established treatments are Robot-Assisted Therapy (RT) and Constraint-Induced Movement Therapy (CIMT), however, it is unknown whether there is a difference in the neuroplastic changes induced by these therapies, and if the modifications are related to motor improvement. Therefore, this study aims to identify neurophysiological biomarkers related to motor improvement of participants with chronic stroke that received RT or CIMT, and to test whether there is a difference in neuronal changes induced by these two therapies. Methods: This study included participants with chronic stroke that took part in a pilot experiment to compare CIMT vs. RT. Neurophysiological evaluations were performed with electroencephalography (EEG) and transcranial magnetic stimulation (TMS), pre and post rehabilitation therapy. Motor function was measured by the Wolf Motor Function Test (WMFT) and Fugl-Meyer Assessment Upper Limb (FMA-UL). Results: Twenty-seven participants with chronic stroke completed the present study [mean age of 58.8 years (SD ± 13.6), mean time since stroke of 18.2 months (SD ± 9.6)]. We found that changes in motor threshold (MT) and motor evoked potential (MEP) in the lesioned hemisphere have a positive and negative correlation with WMFT improvement, respectively. The absolute change in alpha peak in the unlesioned hemisphere and the absolute change of the alpha ratio (unlesioned/lesioned hemisphere) is negatively correlated with WMFT improvement. The decrease of EEG power ratio (increase in the lesioned hemisphere and decrease in the unlesioned hemisphere) for high alpha bandwidths is correlated with better improvement in WMFT. The variable "type of treatment (RT or CIMT)" was not significant in the models. Conclusion: Our results suggest that distinct treatments (RT and CIMT) have similar neuroplastic mechanisms of recovery. Moreover, motor improvements in participants with chronic stroke are related to decreases of cortical excitability in the lesioned hemisphere measured with TMS. Furthermore, the balance of both EEG power and EEG alpha peak frequency in the lesioned hemisphere is related to motor improvement.

Beta-band oscillations as a biomarker of gait recovery in spinal cord injury patients: A quantitative electroencephalography analysis.

OBJECTIVE: The gait recovery in spinal cord injury (SCI) seems to be partially related to the reorganization of cerebral function; however, the neural mechanisms and the respective biomarkers are not well known. This study tested the hypothesis that enhanced beta-band oscillations may be a marker of compensatory neural plasticity during the recovery period in SCI. We tested this hypothesis at baseline in SCI subjects and also in response to cortical stimulation with transcranial direct current stimulation (tDCS) combined with robotic-assisted gait training (RAGT). METHODS: In this neurophysiological analysis of a randomized controlled trial, thirty-nine patients with incomplete SCI were included. They received 30 sessions of either active or sham anodal tDCS over the primary motor area for 20 min combined with RAGT. We analyzed the Electroencephalography (EEG) power spectrum and task-related power modulation of EEG oscillations, and their association with gait function indexed by Walk Index for Spinal Cord Injury (WISCI-II). Univariate and multivariate linear/logistic regression analyses were performed to identify the predictors of gait function and recovery. RESULTS: Consistent with our hypothesis, we found that in the sensorimotor area: (1) Anodal tDCS combined with RAGT can modulate high-beta EEG oscillations power and enhance gait recovery; (2) higher high-beta EEG oscillations power at baseline can predict baseline gait function; (3) high-beta EEG oscillations power at baseline can predict gait recovery - the higher power at baseline, the better gait recovery; (4) decreases in relative high-beta power and increases in beta power decrease during walking are associated with gait recovery. CONCLUSIONS: Enhanced EEG beta oscillations in the sensorimotor area in SCI subjects may be part of a compensatory mechanism to enhance local plasticity. Our results point to the direction that interventions enhancing local plasticity such as tDCS combined with robotic training also lead to an immediate increase in sensorimotor cortex activation, improvement in gait recovery, and subsequent decrease in high-beta power. These findings suggest that beta-band oscillations may be potential biomarkers of gait function and recovery in SCI. SIGNIFICANCE: These findings are significant for rehabilitation in SCI patients, and as EEG is a portable, inexpensive, and easy-to-apply system, the clinical translation is feasible to follow better the recovery process and to help to individualize rehabilitation therapies of SCI patients.

Hidden diversity in the Andes: comparison of species delimitation methods in montane marsupials.

Cryptic genetic diversity is a significant challenge for systematists faced with ever-increasing amounts of DNA sequence data. Computationally intensive coalescent-based analyses involving multiple unlinked loci are the only currently viable methods by which to assess the extent to which phenotypically similar populations (or metapopulations) are genetically distinct lineages. Although coalescent-based approaches have been tested extensively via simulations, few empirical studies have examined the impact of prior assumptions and dataset size on the ability to assess genetic isolation (evolutionary independence) using molecular data alone. Here, we consider the efficacy of two coalescent-based approaches (BPP and SpeDeSTEM) for testing the evolutionary independence of cryptic mtDNA haplogroups within three morphologically diagnosable species of Andean mouse opossums (Thylamys pallidior, T. sponsorius, and T. venustus). Fourteen anonymous nuclear loci, one X-linked nuclear intron, and one mitochondrial gene were analyzed for multiple individuals within each haplogroup of interest. We inferred individual gene trees for each locus and considered all of the nuclear loci jointly in a species-tree analysis. Using only the nuclear loci, we performed "species validation" tests for the cryptic mitochondrial lineages in SpeDeSTEM and BPP. For BPP, we also tested a wide range of prior assumptions, assessed performance of the rjMCMC algorithm, and examined how many loci were necessary to confidently delimit lineages. Results from BPP provided strong support for two independent evolutionary lineages each within T. pallidior, T. sponsorius, and T. venustus, whereas SpeDeSTEM results did not support splitting out mtDNA haplogroups as distinct evolutionary units. For most tests, BPP was robust to prior assumptions, although priors were shown to have an effect on both the strength of lineage recognition among T. venustus haplotypes and on the efficiency of the rjMCMC algorithm. Comparisons of results from datasets with different numbers of loci revealed that some cryptic lineages could be confidently delimited with as few as two loci.

Critical interpretation of Cochran's Q test depends on power and prior assumptions about heterogeneity.

We describe how an appropriate interpretation of the Q-test depends on its power to detect a given typical amount of between-study variance (τ(2)) as well as prior beliefs on heterogeneity. We illustrate these concepts in an evaluation of 1011 meta-analyses of clinical trials with ⩾4 studies and binary outcomes. These concepts can be seen as an application of the Bayes theorem. Across the 1011 meta-analyses, power to detect typical heterogeneity was low in most situations. Thus, usually a non-significant Q test did not change perceptibly prior convictions on heterogeneity. Conversely, significant results for the Q test typically augmented considerably the probability of heterogeneity. The posterior probability of heterogeneity depends on what τ(2) we want to detect. With the same approach, one may also estimate the posterior probability for the presence of heterogeneity that is large enough to annul statistically significant summary effects; that is half the average within-study variance of the combined studies; and that is able to change the summary effect estimate of the meta-analysis by 20%. The discussed analyses are exploratory, and may depend heavily on prior assumptions when power for the Q-test is low. Statistical heterogeneity in meta-analyses should be cautiously interpreted considering the power to detect a specific τ(2) and prior assumptions about the presence of heterogeneity. Copyright © 2010 John Wiley & Sons, Ltd.