Neuroarchitectural Recovery Model of Post-stroke Patients

A.1. Introduction Between 1990 and 2016, the mean lifetime risk of stroke increased from 23% to 25%.1 Stroke was one disease that resulted in long-term neurological deficits and disabilities1,2, which burden both the family and society. Post-stroke rehabilitation has been designed to promote the regain of daily functions.3 A previous study revealed that the heterogeneity of the neurotrauma due to a stroke, as well as the constraints of neuroplastic responses to clinical interventions, influenced the patient's rehabilitation outcomes.4 For example, substantial variability existed in the gains in motor functions after constraint-induced movement therapy (CIMT). This occurred despite the fact that treatment efficacy had been well established for the intervention.5 High variability in rehabilitation-induced recovery has prompted clinical researchers to develop more efficacious post-stroke rehabilitative interventions.6,7 Other researchers have attempted to derive neurological and clinical biomarkers8-11 for explaining the observed effects of these interventions.

A.2. Neuroplasticity underlying stroke recovery Chan (Co-I) and Pang (Co-I) conducted a few randomized clinical trials to test the efficacy of clinical interventions for augmenting the functional regains of post-stroke patients. Chan and his colleagues designed functional training programs based on the motor relearning theory, which showed significantly better motor functions and a higher level of performance in activities of daily living compared with regular practices.12 The second trial was a six-week intervention involving self-regulatory learning training. Post-stroke patients learned the chunking, mental rehearsal, and self-regulation practices of common daily activities, such as laundry and cooking.13,14 Compared with those who received the usual practices, patients in the self-regulatory learning group showed significantly better performance in both trained and untrained daily tasks. More importantly, the results of the untrained tasks suggested that patients in the experimental group managed to generalize what was learned from the training to the new task context and procedures.15 It is noteworthy that the better daily task performance did not associate with changes in the motor functions among the patients. A recent brain imaging pilot study that Chan (Co-I) and colleagues conducted on the self-regulatory training indicated that post-stroke patients showed significant increases in blood-oxygen-level-dependent (BOLD) signals in the right superior and middle temporal gyri in the untrained task trials, as well as in the left orbital frontal, anterior insular, and anterior temporal regions in the untrained-minus-trained task trials. The results of this pilot study suggested that better task performance after self-regulatory training were associated with decision-making, access to semantic memory, and introspective awareness. Post-stroke functional regain, according to these studies, would go far beyond motor functions and self-regulation, which belongs to the executive function.

Pang (Co-I) conducted a single-blinded randomized controlled study and showed that an intervention for a dual task, which required the performance of mobility and cognitive tasks simultaneously, could improve the outcomes of a patient with chronic stroke, such as dual-task performance and fall incidence.16 A.3. Neuroarchitectural correlates of motor recovery after post-stroke rehabilitation The results of a pilot study that Hui (PI) conducted on 16 post-stroke patients indicate that both functional and structural brain networks are associated with motor recovery. The changes were found to occur during and after the patients underwent a conventional rehabilitation program in a hospital for up to three months. They included one week as well as one, three, and six months after stroke onset. Longitudinal structural changes in connectivity, derived from diffusion tensor imaging, were observed in the ipsilesional supramarginal gyrus, contralesional anterior cingulate gyrus, superior parietal gyrus, and cuneus (Figure 1). Longitudinal functional changes in connectivity, derived from rest-state functional magnetic resonance imaging (MRI), were also observed in the ipsilesional superior temporal gyrus, pallidum, and thalamus, as well as the contralesional superior, middle, and triangularis inferior frontal gyri; mid-cingulate area; putamen; and pallidum (Figure 2). To better comprehend the structural results, the neuroarchitectural method was used to build network models at the whole brain and regional levels17, as well as their rich-club organizations.18 An increase in the density ratio of the structural connections of rich-club regions occurred (Table 1). These connections were meant to reflect increases in neural communication efficiency among the neural substrates. This was followed by the testing of how structural and functional connections might subserve post-stroke functional recovery. At one week, the investigators found the properties significantly associated with patients' functional regain in the local structural brain network of the ipsilesional postcentral gyrus; paracentral lobule; median and anterior cingulate gyri and putamen; and contralesional superior parietal gyrus, precuneus, dorsolateral superior frontal gyrus, and hippocampus (Figure 3). At one month, it was the local functional brain network of the ipsilesional posterior cingulate gyrus, contralesional precuneus, and superior frontal gyrus that is significantly associated with patients' functional regain (Figure 4). The post-treatment functional gains were also correlated with the rich-club organization of the structural brain connections (Table 2). The results of this pilot study inform the setting of hypotheses in this study. The advantage of using the neuroarchitectural method, such as rich-club organization, rather than conventional fractional anisotropy from diffusion tensor imaging to define longitudinal structural and functional changes is that the brain network that ischemic infarct disrupts is attributable to neurological sequelae.19-21 The relationship between brain changes and recovery should therefore be studied from the perspective of the brain as a network, rather than local regional changes.22 In this study, the investigators plan to apply the neuroachitectural method to build a post-stroke brain recovery model.

Taken A.2 and A.3 together, our research work offers insights into the notion that neural substrates beyond the sensorimotor cortices should play important roles in post-stroke recovery. However, they have not been emphasized in previous post-stroke recovery model studies. The investigators also demonstrate the advantages of using the neuroachitectural method, which accounts for longitudinal changes in the brain in terms of structural and functional features, as well as their relationships, at various levels of the brain.

The joint characterization of the spatiotemporal changes in structural and functional brain networks would fill a critical knowledge gap regarding the mechanisms underlying post-stroke recovery in response to clinical intervention. This is particularly true for the role that non-sensorimotor cortices would play a role in the recovery process. Furthermore, the knowledge would help to provide a better understanding of the relationships by means of the network coupling strength23 between the dynamic functional and static structural connections in the plastic brain. This claim is supported by our pilot results showing that both types of brain networks were correlated with the rehabilitation-induced recovery and hence their underpinning of responses to post-stroke rehabilitation. The reason for employing network coupling strength in this proposed study is because previous studies showed that its value increased with age24 and decreased with schizophrenia,25 idiopathic generalized epilepsy,23 and small vessel disease with a high white matter lesional load.26 More importantly, the network coupling strength was also found to be correlated with the clinical symptoms,25 the duration23 of the disease, executive function, and memory performance.26 A.4. Neurophysiological correlates of rehabilitation-induced recovery CIMT involves the forced use of the paretic upper limb followed by bilateral upper limb functional training.27 A large number of studies have reported the efficacy of CIMT on improving the motor abilities and daily functions of post-stroke patients.28-30 For instance, a comprehensive review published in 2015 concluded that the clinical effects of CIMT can be supported by the motor learning principles of task- and context-specific and repetitive training.30 However, despite the clinical benefits of CIMT, the neural mechanisms underlying CIMT-induced recovery have not yet been clarified.30 For instance, it is still unclear why improvement in the quality of hand functions involved the recruitment of the ipsilesional superior temporal gyrus after CIMT,31 a neural substrate not directly related to motor functions.

The majority of brain imaging studies on CIMT have revealed that post-treatment functional regains were associated with changes in the motor cortices. CIMT-indicated functional regain was correlated with an increase in the size of the ipsilesional motor cortex32,33, as well as activations in the primary sensorimotor5,34-37, supplementary motor5, premotor cortex31, and secondary somatosensory31 cortices. The structural changes associated with the functional regains included an increase in gray matter density in the bilateral sensorimotor cortices and hippocampi,38 as well as bilateral cerebral peduncles and pons.39 Another study revealed structural integrity of the posterior limb of the internal capsule of the cortico-spinal track (CST) relating to CIMT treatment effects.40 One study indicated that the extent of ischemic injury to the CST was a better predictor of CIMT effects compared with infarct volume.41 In this study, CIMT will be used as the intervention for inducing functional improvements in a group of chronic post-stroke patients based on which the recovery model is to be constructed.

A.5. Hypothesis and significance

The investigators propose constructing a basic brain recovery model for a detailed account of the functional and structural brain changes in a group of chronic stroke patients during the course of CIMT. Two objectives are set for achieving this goal:

OBJECTIVE 1: To characterize the longitudinal changes in functional and structural brain networks that would differentiate the rate of changes in these networks.

Rationale. Considering that the brain is in continuous interactive states,42 a comprehensive account of the neuroplastic changes that occur over the course of CIMT-induced recovery would be meaningful only when both the structural and functional brain networks are to be jointly modeled in the same stereotactic "framework" (i.e., the same brain template). To achieve this, changes in functional brain networks will be measured using the resting state rather than task-based functional MRI. The main reason is that rest-state data would be less biased by the participants' specific task-taking behaviors, such as motivation, level of attention, compliance, and infarct location.43-46 Resting-state data also require a shorter scanning time and are easier to acquired than task-based data are.47 These advantages are helpful for lowering the potential attrition rate due to the repeated scanning required for the participants. Previous studies on robotic therapy reported significant functional connectivities between the ipsilesional and contralesional motor cortices associated with better therapy-induced functional gains among a group of subacute or chronic post-stroke patients.48,49 Hypothesis 1. Longitudinal changes will take place in the functional and structural connections in the sensorimotor and non-