No evidence for motor recovery-related cortical connectivity changes after stroke using resting-state fMRI

Investigating functional connectivity related to stroke recovery: A systematic review

INTRODUCTION

Stroke recovery is a complex process influenced by various factors, including specific neural reorganization. The objective of this systematic review was to identify important functional connectivity (FC) changes in resting-state fMRI data that were often correlated with motor, emotional, and cognitive outcome improvement.

METHOD

A systematic search using PubMed and SCOPUS databases was conducted to identify relevant studies published between 2010 and 2023.

RESULTS

A total of 766 studies were identified, of which 20 studies (602 S individuals) met the inclusion criteria. Fourteen studies focussed on motor recovery while six on cognitive recovery. All studies reported interhemispheric FC to be strongly associated with motor and cognitive recovery. The preservation and changes of M1-M1 (eight incidences) and M1-SMA (nine incidences) FC were found to be strongly correlated with motor function improvement. For cognitive recovery, restoration and preservation of FC with and between default mode network (DMN)-related regions were important for the process.

CONCLUSIONS

This review identified specific patterns of FC that were consistently reported with recovery of motor and cognitive function. The findings may serve in refining future management strategies to enhance patient outcomes.

Effect of transcranial direct current stimulation in the initial weeks post-stroke: a pilot randomized study

OBJECTIVE

This study aimed at assessing the alterations in upper limb motor impairment and connectivity between motor areas following the post-stroke delivery of cathodal transcranial direct current stimulation sessions.

METHODS

Modifications in the Fugl-Meyer Assessment scores, connectivity between the primary motor cortex of the unaffected and affected hemispheres, and between the primary motor and premotor cortices of the unaffected hemisphere were compared prior to and following six sessions of cathodal transcranial direct current stimulation application in 13 patients (active = 6; sham = 7); this modality targets the primary motor cortex of the unaffected hemisphere early after a stroke.

RESULTS

Clinically relevant distinctions in Fugl-Meyer Assessment scores (≥9 points) were observed more frequently in the Sham Group than in the Active Group. Between-group differences in the alterations in Fugl-Meyer Assessment scores were not statistically significant (Mann-Whitney test, p=0.133). ROI-to-ROI correlations between the primary motor cortices of the affected and unaffected hemispheres post-therapeutically increased in 5/6 and 2/7 participants in the Active and Sham Groups, respectively. Between-group differences in modifications in connectivity between the aforementioned areas were not statistically significant. Motor performance enhancements were more frequent in the Sham Group compared to the Active Group.

CONCLUSION

The results of this hypothesis-generating investigation suggest that heightened connectivity may not translate into early clinical benefits following a stroke and will be crucial in designing larger cohort studies to explore mechanisms underlying the impacts of this intervention. ClinicalTrials.gov Identifier: NCT02455427.

Finite sample corrections for average equivalence testing

Average (bio)equivalence tests are used to assess if a parameter, like the mean difference in treatment response between two conditions for example, lies within a given equivalence interval, hence allowing to conclude that the conditions have "equivalent" means. The two one-sided tests (TOST) procedure, consisting in testing whether the target parameter is respectively significantly greater and lower than some pre-defined lower and upper equivalence limits, is typically used in this context, usually by checking whether the confidence interval for the target parameter lies within these limits. This intuitive and visual procedure is however known to be conservative, especially in the case of highly variable drugs, where it shows a rapid power loss, often reaching zero, hence making it impossible to conclude for equivalence when it is actually true. Here, we propose a finite sample correction of the TOST procedure, theα $$ \alpha $$ -TOST, which consists in a correction of the significance level of the TOST allowing to guarantee a test size (or type-I error rate) ofα $$ \alpha $$ . This new procedure essentially corresponds to a finite sample and variability correction of the TOST procedure. We show that this procedure is uniformly more powerful than the TOST, easy to compute, and that its operating characteristics outperform the ones of its competitors. A case study about econazole nitrate deposition in porcine skin is used to illustrate the benefits of the proposed method and its advantages compared to other available procedures.

Against cortical reorganisation

Neurological insults, such as congenital blindness, deafness, amputation, and stroke, often result in surprising and impressive behavioural changes. Cortical reorganisation, which refers to preserved brain tissue taking on a new functional role, is often invoked to account for these behavioural changes. Here, we revisit many of the classical animal and patient cortical remapping studies that spawned this notion of reorganisation. We highlight empirical, methodological, and conceptual problems that call this notion into doubt. We argue that appeal to the idea of reorganisation is attributable in part to the way that cortical maps are empirically derived. Specifically, cortical maps are often defined based on oversimplified assumptions of 'winner-takes-all', which in turn leads to an erroneous interpretation of what it means when these maps appear to change. Conceptually, remapping is interpreted as a circuit receiving novel input and processing it in a way unrelated to its original function. This implies that neurons are either pluripotent enough to change what they are tuned to or that a circuit can change what it computes. Instead of reorganisation, we argue that remapping is more likely to occur due to potentiation of pre-existing architecture that already has the requisite representational and computational capacity pre-injury. This architecture can be facilitated via Hebbian and homeostatic plasticity mechanisms. Crucially, our revised framework proposes that opportunities for functional change are constrained throughout the lifespan by the underlying structural 'blueprint'. At no period, including early in development, does the cortex offer structural opportunities for functional pluripotency. We conclude that reorganisation as a distinct form of cortical plasticity, ubiquitously evoked with words such as 'take-over'' and 'rewiring', does not exist.

Connectomics underlying motor functional outcomes in the acute period following stroke

Objective

Stroke remains the number one cause of morbidity in many developing countries, and while effective neurorehabilitation strategies exist, it remains difficult to predict the individual trajectories of patients in the acute period, making personalized therapies difficult. Sophisticated and data-driven methods are necessary to identify markers of functional outcomes.

Methods

Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI (rsfMRI), and diffusion weighted scans were obtained from 79 patients following stroke. Sixteen models were constructed to predict performance across six tests of motor impairment, spasticity, and activities of daily living, using either whole-brain structural or functional connectivity. Feature importance analysis was also performed to identify brain regions and networks associated with performance in each test.

Results

The area under the receiver operating characteristic curve ranged from 0.650 to 0.868. Models utilizing functional connectivity tended to have better performance than those utilizing structural connectivity. The Dorsal and Ventral Attention Networks were among the top three features in several structural and functional models, while the Language and Accessory Language Networks were most commonly implicated in structural models.

Conclusions

Our study highlights the potential of machine learning methods combined with connectivity analysis in predicting outcomes in neurorehabilitation and disentangling the neural correlates of functional impairments, though further longitudinal studies are necessary.