Harnessing Neuroplasticity: The Role of Priming in Enhancing Post Stroke Motor Function

Abstract

Stroke remains a leading cause of disability worldwide, highlighting the need for innovative neurorehabilitation strategies to enhance recovery. Recent advancements emphasize neuroplasticity—the brain's ability to reorganize and form new connections—through targeted interventions. Among these, cortical priming has emerged as a promising approach to enhance neuroplasticity and improve motor recovery post-stroke by modulating brain excitability for optimal motor learning. This review explores the role of cortical priming in stroke rehabilitation, highlighting its ability to enhance neural excitability and plasticity in motor-related brain regions. Various priming techniques, including non-invasive brain stimulation (rTMS, tDCS), deep brain stimulation (DBS), vagus nerve stimulation (VNS), brain-computer interfaces (BCIs), movement-based priming, aerobic exercise, and sensory stimulation, are examined. Despite promising findings, challenges remain in optimizing protocols and addressing individual variability. Future directions focus on biomarker-driven rehabilitation, personalized strategies, and large-scale trials to integrate cortical priming into clinical practice.

Keywords

stroke priming neuroplasticity motor recovery

Introduction

Stroke remains a leading cause of disability worldwide, creating the need for effective neurorehabilitation strategies to mitigate long-term disability. The past decade has witnessed significant strides in stroke rehabilitation, ushering in a new era of multimodal therapeutic approaches aimed at improving post-stroke functional recovery (Veerbeek et al., 2014). Stroke neurorehabilitation has evolved to include a range of promising treatments and technologies (O'Dell, 2023). At the core of motor recovery is neuroplasticity—the brain's ability to reorganize itself after injury (Dimyan & Cohen, 2011). While the principles of neuroplasticity are well-established, translating this knowledge into effective stroke rehabilitation remains an ongoing challenge. This review focuses on cortical priming, an approach designed to enhance neuroplasticity by modulating neural excitability to improve outcomes of rehabilitation. While cortical priming itself is not a new concept, the novelty of this review lies in its structured and mechanism-based classification of priming strategies into direct and indirect neuromodulation. This framework moves beyond listing techniques and instead offers a way to understand how different forms of priming interface with neuroplastic processes relevant to stroke recovery. By emphasizing the physiological underpinnings and therapeutic potential of each approach, the review aims to support more thoughtful integration of priming into clinical practice.

Neuroplasticity, in a broader sense, is the capacity of the nervous system to adapt its structure, function, and connections in response to both internal and external stimuli (Kleim & Jones, 2008). This adaptability underpins development, learning, and experiences across the lifespan, and is particularly pronounced post-injury. The major drivers of neuroplastic changes include meaningful behavior and contextual experience, with plasticity observable at various levels ranging from cellular/synaptic modifications to alterations in brain region and network functions, and behavioral shifts such as skill improvement and adaptability (Galván, 2010; Marzola et al., 2023). Despite this extensive capacity for brain plasticity and reorganization, leveraging this knowledge to enhance functional outcomes, particularly post stroke, remains an emerging field. Neuroplastic changes following stroke can be both adaptive and maladaptive, and there is a crucial, yet unfulfilled, need to utilize this period of recovery for improved outcomes (Carey et al., 2019; Dimyan & Cohen, 2011). Neurorehabilitation recognizes the critical role of experience and learning-dependent plasticity (Kleim & Jones, 2008). Understanding the conditions that enhance and consolidate this plasticity is vital for developing neuroscience-based interventions that effectively harness these mechanisms for stroke recovery.

Bridging the concepts of cortical priming and neuroplasticity presents a critical advancement in the realm of stroke neurorehabilitation. Cortical priming, a nonconscious process where exposure to one stimulus influences the brain's response to a subsequent stimulus, has become increasingly relevant in this field (Bjørndal et al., 2024; Lee et al., 2020). This approach, deeply entrenched in psychology and neuroscience,(Horner & Henson, 2008; Schacter et al., 2004) has gained traction in motor control and rehabilitation. Motor priming, a specific type of cortical priming, refers to a process that enhances neural excitability and plasticity in motor-related brain areas, thereby influencing motor performance and learning (Siebner, 2010; Stoykov & Madhavan, 2015). Unlike learning itself, motor priming may not involve direct skill acquisition but instead modulates the brain's neural state to optimize responsiveness to subsequent motor stimuli (Stinear et al., 2014). It acts as a preparatory mechanism that makes the motor system more adaptable to learning and therapeutic interventions. This process has shown to be effective because techniques such as non-invasive brain stimulation, sensorimotor activation, and motor imagery engage neural mechanisms—including Hebbian and other forms of synaptic plasticity—that support motor memory encoding and consolidation. (Bjørndal et al., 2024; Fritsch et al., 2010). Rather than being a form of learning itself, motor priming creates favorable neural conditions that enhance the efficiency of motor rehabilitation. This approach is rooted in the idea that the brain, especially after a stroke, can be conditioned or made more adaptable to relearning and reorganization. Motor priming involves preparing the brain to be more receptive to therapeutic interventions.

In this review, priming refers specifically to interventions that alter cortical excitability or neural responsiveness before a motor task, with the aim of enhancing subsequent learning or recovery. Crucially, priming is not the primary therapy itself, it precedes and conditions it. This distinguishes it from task practice or motor training, which drive plasticity through repetition and learning. While many forms of stimulation or activity can modify brain function, not all qualify as priming. Here, we define priming functionally by its role in modulating the neural state in advance of rehabilitation. This broad, mechanism-informed definition is justified by growing evidence that diverse priming techniques—electrical, sensory, behavioral—can engage shared physiological pathways to support recovery. (Bjørndal et al., 2024; Stoykov & Madhavan, 2015; Takeuchi & Izumi, 2015). Commonly used motor priming techniques include motor and sensory stimulation, movement-based strategies, and task-oriented training, all of which contribute to shaping neuroplastic responses in motor recovery. These motor-specific priming strategies facilitate neuroplastic changes in motor circuits, thereby potentially enhancing the efficacy of rehabilitation exercises and activities. However, given the limited number of studies that focus on priming in stroke rehabilitation, some of the work cited in this review involves priming techniques applied in conjunction with motor training. While these do not meet the strict definition used here, they are included due to their relevance in illustrating the underlying mechanisms and potential benefits of priming. Where possible, this review focuses on the priming component itself, with attention to how it may contribute to observed outcomes.

Priming the brain for plastic changes allows for more effective utilization of rehabilitation therapies, potentially leading to better outcomes in terms of motor and functional recovery (Bolognini et al., 2009; Moriarty et al., 2019; Stoykov & Madhavan, 2015; Stoykov et al., 2017, 2022; Takeuchi & Izumi, 2015). Moreover, this approach recognizes the dynamic and individualized nature of stroke recovery, highlighting the necessity of personalized rehabilitation interventions. As we move forward, the focus is increasingly on biomarker-driven, individualized approaches and large-scale clinical trials to optimize rehabilitation strategies for stroke survivors.

With the understanding that the physiology of stroke neurorehabilitation is a dynamic and evolving field, in this review we will aim to summarize mechanisms of neuroplasticity related to motor recovery and evidence-based neuromodulation techniques and strategies that can leverage cortical priming to advance stroke neurorehabilitation. This review aims to synthesize current knowledge and recent advancements in the area of motor priming, offering insights into the future directions of stroke neurorehabilitation.

Neuroplasticity After Stroke and Physiological Mechanisms

Neuroplasticity post-stroke is characterized by the brain's ability to reorganize and form new neural connections, which is crucial for motor function recovery (Murphy & Corbett, 2009; Nudo, 1997). This reorganization often involves the recruitment of perilesional and remote motor areas, as primary motor areas may be irreversibly damaged (Cramer, 2008). Functional recovery is influenced by both intra-hemispheric reorganization and interhemispheric interactions, with multiple compensatory mechanisms occurring at different recovery stages rather than a singular process (Grefkes & Fink, 2020)

One of the earliest theories of stroke recovery, the Interhemispheric Competition Model, posits that stroke disrupts the balance of inhibitory and excitatory interactions between the hemispheres. (Nowak et al., 2009; Takeuchi & Izumi, 2015). Increased inhibition from the contralesional hemisphere may suppress activity in the affected hemisphere, further impairing motor function (Boddington & Reynolds, 2017; Murase et al., 2004). This has led to neuromodulation strategies such as contralesional inhibitory stimulation (e.g., low-frequency rTMS, cathodal tDCS) to restore interhemispheric balance. (Hummel & Cohen, 2006). The Vicariation Model proposes that the contralesional hemisphere actively supports recovery by taking over motor functions lost due to damage in the ipsilesional hemisphere (Rehme et al., 2011). This model suggests that residual neural networks in the intact hemisphere contribute to compensatory mechanisms, particularly when the damage to the ipsilesional hemisphere is extensive. Some studies indicate that disrupting contralesional activity may hinder functional recovery in certain patients (Lotze et al., 2006; Rehme & Grefkes, 2013) implying that interventions aimed at inhibiting the contralesional hemisphere may not be beneficial for all stroke survivors.

To reconcile these opposing models, Di Pino et al. (2014) introduced the Bimodal-Balance Recovery Model, which proposes that interhemispheric balance and functional compensation occur in parallel, depending on the severity of the stroke. (Di Pino et al., 2014). According to this model, mild to moderate strokes primarily follow the Interhemispheric Competition Model, where reducing contralesional inhibition benefits recovery. Severe strokes align more with the Vicariation Model, where contralesional networks take on a more dominant compensatory role. However, recent evidence complicates this picture, Fokas et al. (2025) found that transcallosal inhibition did not significantly influence motor recovery in individuals with mild-to-moderate stroke during the subacute phase, suggesting that interhemispheric dynamics may not uniformly drive recovery across all stroke profiles (Fokas et al., 2025)

These insights suggest that not one model alone fully explains post-stroke recovery, and instead, an individualized, stratified approach is needed. This highlights the importance of biomarker-driven rehabilitation strategies that adapt to each patient's unique neural reorganization patterns (Di Pino et al., 2014; Grefkes & Fink, 2020). Understanding these models is essential for designing effective cortical priming interventions. Inhibitory priming techniques, such as low-frequency rTMS or cathodal tDCS, aim to reduce excessive contralesional inhibition in mild to moderate strokes. Conversely, excitatory priming techniques (e.g., anodal tDCS, high-frequency rTMS) may be more effective in severe strokes by facilitating recruitment of alternative neural pathways, including perilesional areas, contralesional motor regions, and secondary motor networks such as the premotor cortex or supplementary motor area (Rehme et al., 2011)

Cortical Priming

Cortical priming is a neurophysiological approach aimed at modulating brain excitability to enhance neuroplasticity and optimize motor recovery post-stroke (Bjørndal et al., 2024; Lee et al., 2020). This process temporarily alters the neural state, making the brain more responsive to rehabilitation interventions. The underlying mechanism of cortical priming involves synaptic potentiation and modulation of cortical excitability through Hebbian plasticity principles (Fritsch et al., 2010). Specifically, it enhances long-term potentiation (LTP) or long-term depression (LTD) via increased NMDA receptor activity, calcium-mediated signaling, and neurotrophic factor upregulation. (Abraham, 2008; Hamada et al., 2009). Techniques such as repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), and movement-based priming leverage these physiological pathways to prepare the brain for motor relearning and functional recovery (da Silva et al., 2020). By influencing the balance of excitatory and inhibitory neurotransmission, cortical priming interventions facilitate more efficient recruitment of motor circuits, promoting adaptive synaptic remodeling.

Categories of Cortical Priming

Cortical priming represents a frontier in neuroscience and rehabilitation, with ongoing research aimed at identifying the most effective neuromodulation techniques and understanding how these interventions can be best applied to maximize neuroplasticity driven recovery. Few reviews have explored the efficacy of priming in neurorehabilitation, with a specific emphasis on stimulation-based and movement-based priming (Bolognini et al., 2009; Stoykov & Madhavan, 2015; Stoykov et al., 2017). While prior reviews have primarily focused on individual priming techniques, this review provides a structured framework by categorizing them into two broad groups: direct and indirect neuromodulation (Figure 1). We incorporate techniques that have garnered the most evidence while also introducing some that are less studied (Table 1).

Direct Neural Modulation Techniques: This category encompasses techniques that interact directly with the nervous system, specifically targeting cortical and subcortical regions to alter excitability, connectivity, and functional reorganization. Brain stimulation is the primary example in this group. These techniques are characterized by their direct approach, often using electrical, magnetic, or implantable methods to influence neural activity in a precise manner. Each technique has its unique mechanism of action and influence on neural pathways associated with cortical plasticity and they are summarized below:

Repetitive Transcranial Magnetic Stimulation (rTMS): rTMS involves placing a magnetic coil on the scalp directly over the targeted brain region, where it generates brief electromagnetic pulses that induce controlled electric currents in the underlying brain tissue (Hallett, 2007). Depending on the stimulation frequency, this can either excite or inhibit neural activity in specific brain regions. In the context of post-stroke motor recovery, rTMS is often used to modulate the motor cortex, facilitating the reorganization of disrupted motor pathways through mechanisms such as enhancing perilesional cortical activity, strengthening residual corticospinal tract output, recruiting ipsilateral (contralesional) corticospinal projections, and engaging secondary motor areas like the premotor cortex (Bradnam et al., 2013; Grefkes & Fink, 2020; Lotze et al., 2006; Rehme et al., 2011) Lefaucheur et al. (2020) provided expert consensus recommendations after a comprehensive review of studies investigating the effects of rTMS and theta burst stimulation (TBS) on stroke motor rehabilitation (Lefaucheur et al., 2020). Their review along with others (Dionísio et al., 2018; Starosta et al., 2022) underscore the importance of considering patient-specific factors, such as stroke phase, lesion location, and stimulation parameters, when applying rTMS clinically. Most studies have focused on low-frequency (LF) rTMS applied to the contralesional motor cortex (M1) and high-frequency (HF) rTMS or iTBS to the ipsilesional M1, showing beneficial effects for upper limb motor function recovery. (Lefaucheur et al., 2020). A bihemispheric approach, combining contralesional LF-rTMS and ipsilesional HF-rTMS or iTBS, appears to be more effective than either technique alone for improving upper limb motor function (Meng et al., 2020; Tang et al., 2022)Amongst all priming techniques, the mechanisms of rTMS have been most studied. Its primary mechanism involves altering neurotransmitter levels. Specifically, rTMS induces long-term potentiation (LTP) and long-term depression (LTD), critical for altering synaptic strength and fostering neural adaptability, crucial for recovery (Di Lazzaro et al., 2010). These effects are mediated by the activation of NMDA receptors, which facilitate calcium influx pivotal for synaptic plasticity (Fitzgerald et al., 2006). Moreover, rTMS influences gene expression and neurotrophic factors such as BDNF related to neuronal growth and survival, enhancing neurogenesis and potentially aiding in the functional recovery post-stroke. (Sharbafshaaer et al., 2024). Excitatory rTMS, particularly when applied at high frequencies over motor or prefrontal cortical areas, has been shown to influence neurotransmitter systems, including increasing dopamine release in subcortical regions such as the striatum—likely through indirect cortico-subcortical projections rather than direct stimulation of deep structures. (Strafella et al., 2001) rTMS stands as the most thoroughly studied non-invasive priming method for stroke recovery, though its clinical application still requires refinement in terms of individual responsiveness, protocol standardization, and long-term outcomes.

Transcranial Direct Current Stimulation (tDCS): tDCS uses electrodes placed on the scalp to deliver a constant, low-intensity electrical current to the brain (Woods et al., 2016) tDCS influences neuronal excitability by depolarizing or hyperpolarizing neurons, enhancing or reducing their likelihood of firing, respectively (Stagg & Nitsche, 2011). Similar to rTMS, tDCS modifies synaptic plasticity through mechanisms involving long-term potentiation (LTP) and depression (LTD), and the activation of NMDA receptors (Pelletier & Cicchetti, 2014). However, unlike rTMS, which induces action potentials and significantly impacts dopamine levels, tDCS shifts neuronal membrane potentials and affects neurotransmitter systems like GABA and glutamate, thereby impacting both local and long-range functional connectivity within the brain (Stagg & Nitsche, 2011). These characteristics underscore tDCS's unique approach to modulating brain function, focusing on direct electrical influence on neuronal activity and connectivity. For motor recovery, tDCS is typically applied to the motor cortex, where it can enhance neuroplasticity and potentially improve motor skills by priming the neural environment for motor learning and rehabilitation exercises (Lefaucheur et al., 2017; Marquez et al., 2015). Reviews exploring tDCS in combination with task-specific motor training or conventional rehabilitation for stroke recovery have demonstrated varied levels of efficacy on upper limb motor function and mobility. (Madhavan & Shah, 2012; Rodriguez-Huguet et al., 2024; Tedla et al., 2023). This is further informed by recent large-scale findings from the TRANSPORT-2 trial, which demonstrated that while bihemispheric tDCS combined with constraint-induced movement therapy was safe and feasible, it did not produce significantly greater improvements in upper limb motor recovery compared to sham stimulation. (Schlaug et al., 2025). Nonetheless tDCS, particularly anodal stimulation over the affected M1, represents a promising modality in stroke rehabilitation. Longer-term follow-ups, stratified by stroke subtype and severity, as well as deeper investigations into mechanisms are needed to optimize therapeutic strategies (Brunoni et al., 2012)

Deep Brain Stimulation (DBS): DBS involves surgically implanting electrodes in specific brain areas and connecting them to a pulse generator implanted in the chest (Perlmutter & Mink, 2006; Pycroft et al., 2018). DBS modulates brain activity primarily by delivering high-frequency electrical stimulation to specific subcortical targets, with its effects mediated through activation of axonal pathways in proximity to the electrode. This activation may occur at the nodes of Ranvier along axons, where depolarization is most efficiently induced, leading to modulation of downstream circuits involved in motor control (Gilbert et al., 2023). However, unlike tDCS which applies a diffuse electric field across the scalp, DBS provides more precise, localized stimulation. This is akin to the targeted approach of rTMS, but with direct contact and continuous stimulation capable of overriding abnormal neuronal signals. DBS employs anodic break excitation, which involves hyperpolarization followed by a rapid depolarization, triggering action potentials similar to the mechanism induced by rTMS's pulses (Gilbert et al., 2023). Although less commonly used in stroke recovery, DBS could be used to target deep brain structures involved in motor control, potentially aiding in the reorganization of motor pathways and improving motor function (Paro et al., 2023). Research on DBS for stroke recovery is still in the early stages, with most studies being preclinical or involving small clinical trials (Baker et al., 2023; Wathen et al., 2018). The primary focus has been on targeting areas of the brain responsible for motor control, such as the thalamus, basal ganglia, and cerebellum, to improve motor function. While DBS is not traditionally categorized as a priming technique, its ability to modulate neural excitability in motor-related networks suggests potential as a neuromodulatory primer. Recent work by Baker et al. (2023) demonstrated improvements in motor outcomes following cerebellar DBS in chronic stroke patients, indicating that with further development, DBS may be explored as a preparatory intervention to enhance rehabilitation responsiveness. Despite its promise, DBS for stroke recovery faces challenges, including determining optimal stimulation parameters, identifying the most effective brain targets, and understanding the long-term effects of the intervention. Moreover, the invasiveness of the procedure and the associated risks limit its widespread application (Lozano et al., 2019)

Vagus Nerve Stimulation (VNS): VNS typically involves a device implanted under the skin or non-invasively that electrically stimulates the vagus nerve, a critical part of the autonomic nervous system (Yuan & Silberstein, 2016a). This stimulation can have widespread effects on the brain, including the release of neuromodulators and enhanced neuroplasticity, similar to the effects seen in rTMS and tDCS (Andalib et al., 2023). However, VNS achieves these through direct modulation of neurotransmitter release and neuronal firing patterns influenced by its peripheral stimulation (Olsen et al., 2023). This stimulation involves specific pathways like the α7 nicotinic acetylcholine receptor (α7 nAChR), which plays a central role in mediating the anti-inflammatory and neuroprotective effects of VNS (Malley et al., 2024). Unlike rTMS and DBS, which target brain regions more directly and can have immediate and localized effects, VNS influences brain activity through a broader modulation of systemic functions, including the immune system and metabolic processes, by activating neural reflexes that extend from the brain to peripheral organs (Yuan & Silberstein, 2016b). In motor recovery, VNS may be used to augment traditional rehabilitation by enhancing the brain's plastic response to therapy, potentially leading to better motor outcomes (Schambra & Hays, 2025). Several studies have investigated the efficacy of VNS in stroke recovery (Ananda et al., 2023; Dawson et al., 2023; Kimberley et al., 2018, 2023). These studies have shown promising results, with patients undergoing VNS along with rehabilitation demonstrating greater improvements in motor skills compared to those receiving traditional therapy alone. Improvements have been noted in upper limb function, and overall quality of life. Research in this is ongoing, with studies focusing on optimizing stimulation parameters, identifying which patients are most likely to benefit, and understanding the long-term effects of therapy. As technology advances, less invasive methods of stimulating the vagus nerve may also become available, broadening the accessibility of this treatment.

Brain-Computer Interfaces (BCIs): BCIs work by creating a direct communication link between the brain and external devices to facilitate motor recovery by bypassing damaged neural pathways (Qin et al., 2022). They record brain activity through invasive or non-invasive methods (EEG, MEG, fMRI) and decode signals to infer user intentions, enabling control of assistive devices. Early studies indicate potential benefits in post-stroke cognitive rehabilitation, by targeting the interplay between motor, cognitive, and emotional functions (Mane et al., 2020). BCIs can facilitate the retraining of motor pathways by providing feedback and enabling practice of motor tasks, even in patients with severe impairments especially by integrating exoskeleton robots or functional electrical stimulation (Baniqued et al., 2021; Miao et al., 2020). Recent research highlights BCI's role as a primer by demonstrating that BCI-FES systems can enhance neuroplasticity through repeated activation of motor pathways (Kumari et al., 2025). By detecting movement intent via EEG and triggering functional electrical stimulation in response, BCI primes the nervous system to strengthen connections between motor intention and execution, which is essential for recovery. This process not only facilitates immediate functional improvements but also conditions the brain to relearn motor tasks more efficiently over time, making it a valuable tool for rehabilitation (Biasiucci et al., 2018; Sinha et al.). The field is rapidly evolving, through the integration of immersive technologies like virtual reality and augmented reality (Yang et al., 2021). There is need for further development in BCI technology, including the exploration of bidirectional BCIs for integrated motor and sensory rehabilitation,(Hughes et al., 2020) asynchronous and hybrid BCIs for enhanced control and interaction(Choi et al., 2017), and the improvement of signal acquisition methods (Ghosh et al. 2024)

Indirect Neural Modulation Techniques: Unlike direct methods which target specific brain regions, indirect techniques modulate neural activity through a more global or systemic approach, engaging multiple neural networks and pathways. This section summarizes various indirect neural modulation techniques, their mechanisms of action, and their potential applications in neurorehabilitation.

Movement-based priming : Movement-based priming encompasses the application of any continuous physical activity designed to amplify the impact of a subsequent main therapy (Stoykov et al., 2017). This form of priming can involve movements that are either bilateral or unilateral, active or passive, and involve single or multiple joints. It may also include diverse exercise modalities, such as aerobic exercises, isometric strength training or game-based movements (Byblow et al., 2012; Lehmann et al.; Lim & Madhavan, 2023; Lim et al., 2022; Moriarty et al., 2019; Stinear et al., 2014). The fundamental difference between movement-based priming and motor training lies in their objectives and methods: motor training focuses on goal-oriented training exercises through skill acquisition and refinement through practice, whereas movement-based priming typically consists of short duration repetitive movements focused on enhancing the brain's readiness for motor learning or performance through neural facilitation (Stoykov et al., 2017). Movement-based priming exercises are designed to either directly stimulate the neural circuits involved in the performance of a target motor skill or activate other neural circuits, which can, in turn, facilitate the desired skill. An example of indirectly engaging task-relevant motor circuits would be the use of skilled ankle movements as a priming technique prior to gait training in stroke (Lim et al., 2020; Madhavan et al., 2020). When targeted task-specific movements using the paretic limb is not feasible, an indirect activation approach using the arms or the non-paretic leg may enhance motor performance or learning by engaging related but distinct areas of the motor system. An example illustrating this concept would involve non-paretic leg movements to increase corticomotor excitability of the contralateral untrained paretic leg. (Lim & Madhavan, 2023). Bilateral and unilateral motor priming enhance motor function recovery by modulating neural activity similarly to techniques like rTMS and tDCS. Both bilateral and unilateral movement-based priming have been shown to facilitate interhemispheric balance, although the underlying mechanisms may differ. Bilateral movements may promote interhemispheric coordination and re-engage transcallosal pathways, while unilateral movements often enhance cortical excitability in targeted motor regions through focused activation. (Perez et al., 2004; Stinear et al., 2014)

Aerobic exercise: Although aerobic exercise qualifies as a form of movement-based priming, it warrants separate consideration due to the substantial evidence surrounding its effects. Aerobic exercise has been identified as a significant factor in enhancing neuroplasticity after stroke (Sivaramakrishnan & Subramanian, 2023). Aerobic exercise has shown to promotes brain plasticity through multiple biological mechanisms, particularly in the context of stroke recovery. It enhances the release of neurotrophic factors like BDNF, IGF-1, and VEGF which supports neuronal health, synaptic plasticity, and neurogenesis (Constans et al., 2016; Limaye et al., 2021; Voss et al., 2013). Exercise also improves cerebral blood flow, facilitating nutrient and oxygen delivery to the brain, essential for repair and the formation of new neural connections. (Bliss et al., 2021; Vecchio et al., 2018). Additionally, aerobic activity can lead to the upregulation of molecules involved in synaptic function and plasticity, further contributing to the brain's ability to reorganize and adapt post-stroke (Hill et al., 2023; Hong et al., 2020; Nie & Yang, 2017). The parameters of exercise, including intensity and duration, that best maximize neuroplastic potential remain unknown. The choice between moderate and high-intensity exercise to promote neuroplasticity post-stroke depends on several factors, including the individual's health status and stage of recovery. Both types of exercise have been shown to offer benefits for neuroplasticity, but they may serve different roles in the priming process (Crozier et al., 2018; Hill et al., 2023)

Remote Ischemic conditioning: Remote Ischemic Conditioning (RIC) exploits the body's natural protective responses to brief, controlled episodes of ischemia (restricted blood flow) in a limb to confer protection against ischemic injury in distant organs, such as the brain (Zhao et al., 2023). RIC involves applying a blood pressure cuff to an extremity (arm or leg) and inflating it to a pressure above systolic levels to temporarily restrict blood flow, followed by deflation to allow reperfusion (Alhashimi et al., 2024). This cycle is repeated several times. Some key proposed mechanisms of action include activating systemic protective signaling pathways that cross the blood-brain barrier, modulating inflammatory responses to favor regeneration, promoting angiogenesis and neurogenesis for tissue repair, and improving cerebral blood flow regulation (Yang et al., 2019). RIC has been shown to acutely improve muscle strength and neuromuscular facilitation in the paretic leg of stroke survivors (Hyngstrom et al., 2018). Long term administration has resulted in improvements in walking speed and reduced leg fatigability (Durand et al., 2019). Although RIC is not typically considered as a priming technique, it is included here due to its capacity to modulate systemic and neural responses that may influence motor performance and recovery (Cummings & Madhavan, 2024). Its mechanism of action differs from traditional cortical priming, but its potential to enhance neuromuscular function prior to training warrants consideration as an emerging neuromodulatory strategy.

Sensory stimulation: Sensory priming is grounded in the principle that sensory and motor cortices are interconnected, and enhancing sensory processing can subsequently improve motor outcomes (Stoykov et al., 2022). The use of a sensory stimulus, like peripheral nerve stimulation, vibration, or transient functional deafferentation, targets the somatosensory system to modulate neural pathways and facilitate motor function (Annino et al., 2025; Celnik et al., 2007; Lu et al., 2024; Sens et al., 2012, 2013). A recent review on the effectiveness of sensory-based priming techniques for improving upper limb motor function in persons with stroke concluded that sensory priming, when used prior to or concurrently with motor interventions, significantly enhances motor skill recovery post-stroke (Stoykov et al., 2022). The mechanisms underlying sensory priming are not fully understood, and there is a need for more standardized protocols in this field.

Figure 1.

This Figure Visually Depicts Cortical Priming Modalities Studied in Stroke Rehabilitation, Segmented into two Broad Groups Based on Their Method of Interaction with the Nervous System: Direct Neural Modulation Techniques and Indirect Neural Modulation Techniques. Each Group is Further Subdivided to Highlight Specific Approaches Within These Categories, Showcasing a spectrum of Strategies Ranging from Well-Evidenced to Emerging Technologies in the Field of Neurorehabilitation.

Table 1.

Summary of Evidence-Based Cortical Priming Techniques for Stroke Rehabilitation.

Priming Technique	Mechanism of Action	Level of Clinical Evidence	Key Research Findings	Limitations & Challenges
Direct Techniques
Transcranial Magnetic Stimulation (TMS)	Modulates motor cortex excitability via electromagnetic pulses	Moderate to Strong	Meta-analyses report improved upper limb function, particularly with high-frequency TMS to the ipsilesional hemisphere or low-frequency TMS to the contralesional hemisphere (Lefaucheur et al., 2020)	Variability in response, high cost, optimal stimulation parameters not yet standardized
Transcranial Direct Current Stimulation (tDCS)	Alters neuronal membrane potentials	Moderate	Studies indicate effectiveness for upper motor function improvements, but not walking function(Tedla et al., 2023; Tien et al., 2020)	Inconsistent clinical outcomes, effects influenced by individual variability
Deep Brain Stimulation (DBS)	Modulates deep motor circuits (e.g., basal ganglia, thalamus) via implanted electrodes	Emerging	Small clinical trials show potential benefits, with targeted stimulation improving motor recovery. (Baker et al., 2023; Wathen et al., 2018)	Highly invasive, requires surgery, long-term effects not well studied
Vagus Nerve Stimulation (VNS)	Stimulates the vagus nerve to enhance neuroplasticity through neuromodulator release	Emerging (non-invasive VNS) to Moderate (invasive VNS)	Clinical trials suggest improved upper limb function when paired with rehabilitation, with some patients exhibiting enhanced motor learning (Ananda et al., 2023; Andalib et al., 2023)	Implanted VNS is invasive, costly, patient selection criteria not well established
Brain-Computer Interfaces (BCIs)	Uses real-time brain activity to control external devices, reinforcing motor-intent pathways	Emerging	Studies show potential for improving motor recovery, especially in patients with severe impairments, when combined with robotic exoskeletons or functional electrical stimulation (Mane et al., 2020)	Expensive, requires intensive patient training, not widely available
Indirect Techniques
Movement-Based Priming	Repetitive motor activity before therapy enhances corticospinal excitability	Emerging	Shown to enhance cortical excitability and improve rehabilitation outcomes when combined with motor training. (Lim et al., 2020; Madhavan et al., 2020; Stoykov et al., 2017)	Requires patient participation, less effective in those with severe impairments
Aerobic Exercise	Increases neurotrophic factors (BDNF, IGF-1), improves blood flow to motor regions	Strong	Demonstrated to enhance neuroplasticity and motor learning post-stroke, with effects dependent on intensity and duration (Crozier et al., 2018; Sivaramakrishnan & Subramanian, 2023)	Optimal intensity and timing remain unclear
Remote Ischemic Conditioning (RIC)	Brief cycles of limb ischemia trigger systemic neuroprotective effects	Emerging	Preliminary studies show improved muscle strength and motor function in stroke survivors, potentially via upregulation of neurotrophic factors (Cummings & Madhavan, 2024)	Mechanisms not fully understood, clinical translation is limited
Sensory-Based Priming (e.g., Peripheral Nerve Stimulation, Vibration Therapy)	Enhances sensorimotor integration, improves cortical mapping	Emerging	Evidence suggests improvements in upper limb function when combined with rehabilitation (Stoykov et al., 2022)	Protocol variability, need for standardization

This table summarizes the mechanisms, levels of clinical evidence, key research findings, and limitations of different cortical priming techniques used in stroke rehabilitation. Mechanisms of action describe how each technique influences neuroplasticity. Level of clinical evidence is categorized as Strong, Moderate, or Emerging based on systematic reviews and meta-analyses. Key research findings highlight major study outcomes, while limitations address challenges in clinical implementation. Techniques with “Emerging” evidence require further large-scale trials to establish efficacy.

Principles of Priming

Drawing on insights provided by the seminal paper by Kleim and colleagues on the principles of neuroplasticity and its implications for rehabilitation post-brain damage, we haveidentified key principles of motor priming for enhancing stroke rehabilitation (Kleim & Jones, 2008). These principles are aimed at enhancing the brain's capacity for recovery by leveraging the underlying mechanisms of plasticity. It is important to acknowledge that while these principles are grounded in theoretical frameworks and emerging evidence, many remain at the forefront of current research and require further empirical validation.

Timing of Priming relevant to Stroke Onset: Initiating priming techniques in the early phase post-stroke can leverage the brain's heightened state of plasticity, optimizing the window for recovery and enhancing the effectiveness of functional exercises (Coleman et al., 2017). While early intervention has been associated with positive outcomes in some cases, evidence suggests that the optimal window for priming is not universally early and may vary depending on the specific recovery goal (Dromerick et al., 2021). Some studies indicate that premature interventions may not always yield the expected benefits (Langhorne et al., 2017; Nave et al., 2019). Thus, rather than a strict emphasis on early intervention, identifying an individualized ‘sweet spot’ for priming may be key to maximizing recovery potential.

Timing of Priming relevant to Motor Practice: In this review, priming is defined as a neuromodulatory intervention applied prior to motor practice to enhance the brain's responsiveness to training. However, some studies have explored the effects of delivering priming during or after rehabilitation, particularly in the context of motor learning and memory consolidation. Evidence suggests that timing influences outcomes, with interventions delivered immediately before or during training often showing the greatest benefits (Byczynski & Vanneste, 2023; Charalambous et al., 2018; Giacobbe et al., 2013; Sriraman et al., 2014; Thomas et al., 2016). These findings underscore the importance of aligning priming with task engagement to optimize plasticity, while still supporting its primary role as a preparatory intervention and aligns with growing calls to increase rehabilitation intensity and dose post-stroke (Lin et al., 2025)

Specificity of Training: Priming activities should facilitate the brain area(s) being targeted for rehabilitation. (Bjørndal et al., 2024). This ensures that the neural circuits activated during priming are the ones most relevant to the desired motor recovery.

Protocol Parameters: The design of each priming session—such as its frequency, duration, and intensity—are critical components that contribute to its effectiveness. For instance, high intensity training is shown to elicit greater neuroplastic responses in stroke survivors than moderate intensity training (Boyne et al., 2019)

Integration of Modalities: A holistic approach, combining various priming techniques can provide a more robust and comprehensive approach to priming, potentially leading to greater improvements in motor recovery. Lima et al. (2023) examined a sequence of treatments that included tDCS, motor imagery based BCI with virtual reality along with task specific training in a person with severe stroke impairment and reported positive trends in improvement of mobility and sensory function (Lima et al., 2023). Aerobic exercise when combined with tDCS, compared to exercise alone, can facilitate descending corticomotor excitability of lower limb M1 in persons post stroke (Sivaramakrishnan & Madhavan, 2021)

Customization and Adaptation: Priming strategies should be tailored to meet the individual needs and progress of each patient, allowing for adjustments based on recovery pace and specific challenges encountered during rehabilitation. For example, cross-training may offer a valuable approach for stroke survivors with severe functional impairment by leveraging the non-paretic limb to promote recovery in the paretic limb, while high intensity aerobic exercise could be particularly beneficial for those with higher functional levels.

Synergy with Rehabilitation: Cortical priming should be viewed as a complement to motor training, not a standalone solution. Its integration into a broader therapeutic regimen can maximize functional outcomes especially in situations where encouraging neuroplasticity is important for motor learning and recovery.

Challenges in Implementation and Future Directions

The application of priming techniques post stroke represents a significant advancement in neurorehabilitation, bridging the gap between traditional therapies and the forefront of personalized medicine. Despite the promising advancements in the understanding and application of neuromodulation in stroke rehabilitation, it is crucial to acknowledge the limitations inherent in the current body of research. A significant proportion of studies in this domain are characterized by small sample sizes, limiting the generalizability of their findings (Dionísio et al., 2018; Elsner et al., 2016). Additionally, many of these investigations feature short follow-up periods, raising questions about the long-term efficacy and stability of the reported outcomes. For instance, while numerous studies highlight the immediate benefits of interventions like rTMS and tDCS, fewer explore the durability of these effects over time. This gap underscores the necessity for future research to not only include larger, more diverse cohorts but also to extend observation periods. Moreover, the priming methodologies and paradigms employed exhibit a high degree of variability, ranging from the selection of neuromodulation techniques to the protocols for administering therapies and to the response elicited in patients (Lefaucheur et al., 2017; Woods et al., 2016). This diversity, while reflective of the field's dynamic nature, complicates the task of synthesizing findings and drawing broad conclusions, further emphasizing the need for standardization and rigorous experimental design in future investigations.

The translation of these modalities into widespread clinical application encounters several barriers. The optimization of priming protocols should be a critical area of focus (Bastani & Jaberzadeh, 2012; Hsu et al., 2012). This involves fine-tuning the timing, frequency, and duration of priming sessions to ensure that patients receive the maximum possible benefit from these interventions. The goal is to establish evidence-based guidelines that can inform clinicians on how best to integrate priming into neurorehabilitation, making it as effective as possible for enhancing neuroplasticity and facilitating recovery.

To achieve this level of precision, a deeper understanding of the underlying mechanisms of action is essential. This means conducting research aimed at uncovering mechanisms of priming at a biological level. Identifying the key circulating factors—such as brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor (VEGF), and inflammatory cytokines—and the neural pathways involved, including cortico-subcortical circuits and sensorimotor networks, which are activated or modulated by priming will provide valuable insights into its therapeutic effects. This knowledge could lead to the development of more targeted and efficient rehabilitation strategies that leverage these biological processes for improved outcomes (Joy & Carmichael, 2021). Another critical aspect of improving priming interventions is patient selection. Not all stroke survivors will respond to priming in the same way, and factors such as the type and severity of the stroke, as well as individual patient characteristics, play a significant role in determining who is most likely to benefit. Developing criteria for selecting appropriate candidates for different types of priming can help ensure that these interventions are used where they are most likely to be effective, thereby optimizing resource use and maximizing patient benefits (Lin et al., 2024). There is a pressing need for more comprehensive data on the long-term effects of priming on stroke recovery. This includes understanding its impact not only on functional recovery but also on the quality of life of stroke survivors. Longitudinal studies and follow-up assessments are essential to gauge the lasting benefits of priming and to assess whether these interventions can contribute to sustained improvements over time.

Furthermore, incorporating the concept of priming into clinical education represents a pivotal step towards enhancing the efficacy of stroke rehabilitation strategies. Education and training programs for rehabilitation professionals must evolve to include the latest advancements in priming techniques. By doing so, we can equip future clinicians with the knowledge and tools needed to apply these cutting-edge strategies effectively within clinical settings. Additionally, fostering interdisciplinary collaboration among healthcare professionals is vital for integrating priming into clinical practice, enabling the creation of patient-specific priming protocols and advancing personalized rehabilitation. The use of technology, such as wearable devices and digital platforms, also plays a key role by providing real-time progress data and enabling remote monitoring, thus broadening the reach of priming therapies beyond conventional settings (Kheirollahzadeh et al., 2025; Maceira-Elvira et al., 2019; Peters et al., 2021)

Conclusion

In conclusion, the exploration of neuroplasticity and cortical priming in stroke neurorehabilitation offers promising avenues for augmenting functional recovery after stroke. By delving into the mechanisms of neuroplasticity and leveraging innovative priming techniques, this review underscores the potential for personalized and effective rehabilitation strategies as the future of stroke rehabilitation. The integration of direct and indirect neuromodulation techniques, alongside traditional therapies, is a viable way to optimize the current standard of practice. The evidence base for several priming strategies, although promising, is not yet conclusive, and these approaches should be considered as suggestions for future research rather than established practices. The complexities of neuroplasticity and individual variability in stroke recovery necessitate a cautious approach when integrating new priming techniques into clinical practice.

Advancing the use of priming in stroke rehabilitation requires a multifaceted approach that encompasses optimizing treatment protocols, gaining deeper mechanistic insights, refining patient selection processes, and conducting thorough evaluations of long-term outcomes. Rigorous clinical trials and systematic reviews are needed to substantiate the effectiveness of these interventions and ensure their safety and efficacy across diverse stroke populations. Through such efforts, the potential of priming to significantly enhance stroke recovery can be more fully realized. As research continues to evolve, it is important that clinical practices adapt to incorporate these evidence-based approaches through interdisciplinary collaborations and technological integration, ensuring that stroke neurorehabilitation is grounded in the latest advances in neuroscience and medicine.

Footnotes

Acknowledgements

I would like to thank Ms. Gina Sawa for assistance with the rendition of the figure. This project was partly funded by the National Institutes of Health [R01HD075777]. Study sponsors had no role in study design, data collection, data analysis, data interpretation, writing the manuscript, or the decision to submit this manuscript for publication.

ORCID iD

Sangeetha Madhavan

Author Contributions

SM conceptualized the review, conducted the literature search, and wrote the manuscript. SM also reviewed and revised the final draft for accuracy and coherence.

Funding

The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partly supported by the National Institutes of Health [R01HD075777].

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability

No data was used in the writing of this review

References

Abraham

W. C.

(2008). Metaplasticity: Tuning synapses and networks for plasticity. Nature Reviews: Neuroscience, 9(5), 387. https://doi.org/10.1038/nrn2356

Alhashimi

Kamarova

Baig

S. S.

Nair

K. P. S.

Wang

Redgrave

Majid

Ali

A. N.

(2024). Remote ischaemic conditioning for neurological disorders—a systematic review and narrative synthesis. Systematic Reviews, 13(1), 308. https://doi.org/10.1186/s13643-024-02725-8

Ananda

Roslan

M. H. B.

Wong

L. L.

Botross

N. P.

Ngim

C. F.

Mariapun

(2023). Efficacy and safety of Vagus nerve stimulation in stroke rehabilitation: A systematic review and meta-analysis. Cerebrovascular Diseases, 52(3), 239–250. https://doi.org/10.1159/000526470

Andalib

Divani

A. A.

Ayata

Baig

Arsava

E. M.

Topcuoglu

M. A.

Cáceres

E. L.

Parikh

Desai

M. J.

Majid

Girolami

Di Napoli

(2023). Vagus nerve stimulation in ischemic stroke. Current Neurology and Neuroscience Reports, 23(12), 947–962. https://doi.org/10.1007/s11910-023-01323-w

Annino

Alashram

A. R.

Romagnoli

Iovane

Youssef

T. M.

Tancredi

Padua

Mercuri

N. B.

(2025). Efficacy of localized muscle vibration on lower extremity functional ability in patients with stroke: A randomized controlled trial. Journal of Bodywork and Movement Therapies, 42, 769–776. https://doi.org/10.1016/j.jbmt.2025.02.004

Baker

K. B.

Plow

E. B.

Nagel

Rosenfeldt

A. B.

Gopalakrishnan

Clark

Wyant

Schroedel

Ozinga

IV Davidson

Hogue

Floden

Chen

Ford

P. J.

Sankary

Huang

Cunningham

D. A.

DiFilippo

…, Machado, A. G. (2023). Cerebellar deep brain stimulation for chronic post-stroke motor rehabilitation: A phase I trial. Nature Medicine, 29(9), 2366–2374. https://doi.org/10.1038/s41591-023-02507-0

Baniqued

P. D. E.

Stanyer

E. C.

Awais

Alazmani

Jackson

A. E.

Mon-Williams

M. A.

Mushtaq

Holt

R. J.

(2021). Brain-computer interface robotics for hand rehabilitation after stroke: A systematic review. Journal of Neuroengineering and Rehabilitation, 18(1), 15. https://doi.org/10.1186/s12984-021-00820-8

Bastani

Jaberzadeh

(2012). Does anodal transcranial direct current stimulation enhance excitability of the motor cortex and motor function in healthy individuals and subjects with stroke: A systematic review and meta-analysis. Clinical Neurophysiology, 123(4), 644–657. https://doi.org/10.1016/j.clinph.2011.08.029

Biasiucci

Leeb

Iturrate

Perdikis

Al-Khodairy

Corbet

Schnider

Schmidlin

Zhang

Bassolino

Viceic

Vuadens

Guggisberg

A. G.

Millán

J. D. R.

(2018). Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke. Nat Commun, 9(1), 2421. https://doi.org/10.1038/s41467-018-04673-z

10.

Bjørndal

J. R.

Beck

M. M.

Jespersen

Christiansen

Lundbye-Jensen

(2024). Hebbian priming of human motor learning. Nat Commun, 15(1), 5126. https://doi.org/10.1038/s41467-024-49478-5

11.

Bliss

E. S.

Wong

R. H.

Howe

P. R.

Mills

D. E.

(2021). Benefits of exercise training on cerebrovascular and cognitive function in ageing. Journal of Cerebral Blood Flow and Metabolism, 41(3), 447–470. https://doi.org/10.1177/0271678X20957807

12.

Boddington

L. J.

Reynolds

J. N. J.

(2017). Targeting interhemispheric inhibition with neuromodulation to enhance stroke rehabilitation. Brain Stimul, 10(2), 214–222. https://doi.org/10.1016/j.brs.2017.01.006

13.

Bolognini

Pascual-Leone

Fregni

(2009). Using non-invasive brain stimulation to augment motor training-induced plasticity. Journal of Neuroengineering and Rehabilitation, 6, 8. https://doi.org/10.1186/1743-0003-6-8

14.

Boyne

Meyrose

Westover

Whitesel

Hatter

Reisman

D.S.

Cunningham

Carl

Jansen

Khoury

J.C.

Gerson

(2019). Exercise intensity affects acute neurotrophic and neurophysiological responses poststroke. J Appl Physiol (1985), 126(2), 431–443. https://doi.org/10.1152/japplphysiol.00594.2018

15.

Bradnam

L. V.

Stinear

C. M.

Byblow

W. D.

(2013). Ipsilateral motor pathways after stroke: Implications for non-invasive brain stimulation. Frontiers in Human Neuroscience, 7, 184. https://doi.org/10.3389/fnhum.2013.00184

16.

Brunoni

A. R.

Nitsche

M. A.

Bolognini

Bikson

Wagner

Merabet

Edwards

D. J.

Valero-Cabré

Rotenberg

Pascual-Leone

Ferrucci

Priori

Boggio

P. S.

Fregni

(2012). Clinical research with transcranial direct current stimulation (tDCS): Challenges and future directions. Brain Stimul, 5(3), 175–195. https://doi.org/10.1016/j.brs.2011.03.002

17.

Byblow

W. D.

Stinear

C. M.

Smith

M. C.

Bjerre

Flaskager

B. K.

McCambridge

A. B.

(2012). Mirror symmetric bimanual movement priming can increase corticomotor excitability and enhance motor learning. PloS One, 7(3), e33882. https://doi.org/10.1371/journal.pone.0033882

18.

Byczynski

Vanneste

(2023). Modulating motor learning with brain stimulation: Stage-specific perspectives for transcranial and transcutaneous delivery. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 125, 110766. https://doi.org/10.1016/j.pnpbp.2023.110766

19.

Carey

Walsh

Adikari

Goodin

Alahakoon

De Silva

Ong

K.-L.

Nilsson

Boyd

(2019). Finding the intersection of neuroplasticity, stroke recovery, and learning: Scope and contributions to stroke rehabilitation. Neural Plasticity, 2019, Article 5232374. https://doi.org/10.1155/2019/5232374

20.

Celnik

Hummel

Harris-Love

Wolk

Cohen

L. G.

(2007). Somatosensory stimulation enhances the effects of training functional hand tasks in patients with chronic stroke. Archives of Physical Medicine and Rehabilitation, 88(11), 1369–1376. https://doi.org/10.1016/j.apmr.2007.08.001

21.

Charalambous

C. C.

Alcantara

C. C.

French

M. A.

Matt

K. S.

Kim

H. E.

Morton

S. M.

Reisman

D. S.

(2018). A single exercise bout and locomotor learning after stroke: Physiological, behavioural, and computational outcomes. Journal of Physiology, 596(10), 1999–2016. https://doi.org/10.1113/JP275881

22.

Choi

Rhiu

Lee

Yun

M. H.

Nam

C. S.

(2017). A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives. PloS One, 12(4), e0176674. https://doi.org/10.1371/journal.pone.0176674

23.

Cochrane Stroke Group Qin

Shi

Cui

Zhao

Yang

(2022). Brain-computer interface training for motor recovery after stroke. Cochrane Database Syst Rev, 2022(6). https://doi.org/10.1002/14651858.cd015065

24.

Coleman

E. R.

Moudgal

Lang

Hyacinth

H. I.

Awosika

O. O.

Kissela

B. M.

Feng

(2017). Early rehabilitation after stroke: A narrative review. Curr Atheroscler Rep, 19(12), 59. https://doi.org/10.1007/s11883-017-0686-6

25.

Constans

Pin-barre

Temprado

J.-J.

Decherchi

Laurin

(2016). Influence of aerobic training and combinations of interventions on cognition and neuroplasticity after stroke. Frontiers in Aging Neuroscience, 8, 2016. https://doi.org/10.3389/fnagi.2016.00164

26.

Cramer

S. C.

(2008). Repairing the human brain after stroke: I. Mechanisms of spontaneous recovery. Annals of Neurology, 63(3), 272–287. https://doi.org/10.1002/ana.21393

27.

Crozier

Roig

Eng

J. J.

MacKay-Lyons

Fung

Ploughman

Bailey

D. M.

Sweet

S. N.

Giacomantonio

Thiel

Trivino

Tang

(2018). High-Intensity interval training after stroke: An opportunity to promote functional recovery, cardiovascular health, and neuroplasticity. Neurorehabilitation and Neural Repair, 32(6–7), 543–556. https://doi.org/10.1177/1545968318766663

28.

Cummings

Madhavan

(2024). Blood flow modulation to improve motor and neurophysiological outcomes in individuals with stroke: A scoping review. Experimental Brain Research, 242(12), 2665–2676. https://doi.org/10.1007/s00221-024-06941-5

29.

da Silva

E. S. M.

Ocamoto

G. N.

Santos-Maia

G. L. D.

de Fatima Carreira Moreira Padovez

Trevisan

de Noronha

M. A.

Russo

T. L.

(2020). The effect of priming on outcomes of task-oriented training for the upper extremity in chronic stroke: A systematic review and meta-analysis. Neurorehabilitation and Neural Repair, 34(6), 479–504. https://doi.org/10.1177/1545968320912760

30.

Dawson

Engineer

N. D.

Cramer

S. C.

Wolf

S. L.

Ali

O'Dell

M. W.

Kimberley

T. J.

(2023). Vagus nerve stimulation paired with rehabilitation for upper limb motor impairment and function after chronic ischemic stroke: Subgroup analysis of the randomized, blinded, pivotal, VNS-REHAB device trial. Neurorehabilitation and Neural Repair, 37(6), 367–373. https://doi.org/10.1177/15459683221129274

31.

Di Lazzaro

Profice

Pilato

Dileone

Oliviero

Ziemann

(2010). The effects of motor cortex rTMS on corticospinal descending activity. Clinical Neurophysiology, 121(4), 464–473. https://doi.org/10.1016/j.clinph.2009.11.007

32.

Dimyan

M. A.

Cohen

L. G.

(2011). Neuroplasticity in the context of motor rehabilitation after stroke. Nature Reviews: Neurology, 7(2), 76–85. https://doi.org/10.1038/nrneurol.2010.200

33.

Dionísio

Duarte

I. C.

Patrício

Castelo-Branco

(2018). The use of repetitive transcranial magnetic stimulation for stroke rehabilitation: A systematic review. Journal of Stroke and Cerebrovascular Diseases, 27(1), 1–31. https://doi.org/10.1016/j.jstrokecerebrovasdis.2017.09.008

34.

Di Pino

Pellegrino

Assenza

Capone

Ferreri

Formica

Di Lazzaro

(2014). Modulation of brain plasticity in stroke: A novel model for neurorehabilitation. Nature Reviews: Neurology, 10(10), 597–608. https://doi.org/10.1038/nrneurol.2014.162

35.

Dromerick

A. W.

Geed

Barth

Brady

K. P.

Giannetti

M. L.

Mitchell

Edwards

M. A.

Tan

M. T.

Zhou

Newport

E. L.

Edwards

D. F.

(2021). Critical Period After Stroke Study (CPASS): A phase II clinical trial testing an optimal time for motor recovery after stroke in humans. Proceedings of the National Academy of Sciences of the United States of America, 118(39). https://doi.org/10.1073/pnas.2026676118

36.

Durand

M. J.

Boerger

T. F.

Nguyen

J. N.

Alqahtani

S. Z.

Wright

M. T.

Schmit

B. D.

Hyngstrom

A. S.

(2019). Two weeks of ischemic conditioning improves walking speed and reduces neuromuscular fatigability in chronic stroke survivors. J Appl Physiol (1985), 126(3), 755–763. https://doi.org/10.1152/japplphysiol.00772.2018

37.

Elsner

Kugler

Pohl

Mehrholz

(2016). Transcranial direct current stimulation (tDCS) for improving activities of daily living, and physical and cognitive functioning, in people after stroke. Cochrane Database Syst Rev, 3, Cd009645. https://doi.org/10.1002/14651858.CD009645.pub3

38.

Fitzgerald

P. B.

Fountain

Daskalakis

Z. J.

(2006). A comprehensive review of the effects of rTMS on motor cortical excitability and inhibition. Clinical Neurophysiology, 117(12), 2584–2596. https://doi.org/10.1016/j.clinph.2006.06.712

39.

Fokas

Taga

Hayes

Charalambous

C. C.

Raju

Wang

Schambra

(2025). Transcallosal inhibition does not influence subacute motor recovery in mild-to-moderate stroke. Brain. https://doi.org/10.1093/brain/awaf095

40.

Fritsch

Reis

Martinowich

Schambra

H. M.

Cohen

L. G.

(2010). Direct current stimulation promotes BDNF-dependent synaptic plasticity: Potential implications for motor learning. Neuron, 66(2), 198–204. https://doi.org/10.1016/j.neuron.2010.03.035

41.

Galván

(2010). Neural plasticity of development and learning. Human Brain Mapping, 31(6), 879–890. https://doi.org/10.1002/hbm.21029

42.

Ghosh

Máthé

Harishita

P. B.

Sankarapillai

Mohan

Bhuvanakantham

Padmanabhan

(2024). Review of Multimodal Data Acquisition Approaches for Brain–Computer Interfaces. Biomedicine, 4(4), 548–587. https://doi.org/10.3390/biomed4040041

43.

Giacobbe

Krebs

H. I.

Volpe

B. T.

Pascual-Leone

Rykman

Zeiarati

Edwards

D. J.

(2013). Transcranial direct current stimulation (tDCS) and robotic practice in chronic stroke: The dimension of timing. NeuroRehabilitation, 33(1), 49–56. https://doi.org/10.3233/NRE-130927

44.

Gilbert

Mason

Sebastian

Tang

A. M.

Martin Del Campo-Vera

Chen

K. H.

Lee

(2023). A review of neurophysiological effects and efficiency of waveform parameters in deep brain stimulation. Clinical Neurophysiology, 152, 93–111. https://doi.org/10.1016/j.clinph.2023.04.007

45.

Grefkes

Fink

G. R.

(2020). Recovery from stroke: Current concepts and future perspectives. Neurol Res Pract, 2, 17. https://doi.org/10.1186/s42466-020-00060-6

46.

Hallett

(2007). Transcranial magnetic stimulation: A primer. Neuron, 55(2), 187–199. https://doi.org/10.1016/j.neuron.2007.06.026

47.

Hamada

Hanajima

Terao

Okabe

Nakatani-Enomoto

Furubayashi

Ugawa

(2009). Primary motor cortical metaplasticity induced by priming over the supplementary motor area. Journal of Physiology, 587(Pt 20), 4845–4862. https://doi.org/10.1113/jphysiol.2009.179101

48.

Hill

Johnson

Serrada

Benyamin

Van Den Berg

Hordacre

(2023). Moderate intensity aerobic exercise may enhance neuroplasticity of the contralesional hemisphere after stroke: A randomised controlled study. Scientific Reports, 13(1), 14440. https://doi.org/10.1038/s41598-023-40902-2

49.

Hong

Kim

T. W.

Park

S. S.

Kim

M. K.

Park

Y. H.

Shin

M. S.

(2020). Treadmill exercise improves motor function and short-term memory by enhancing synaptic plasticity and neurogenesis in photothrombotic stroke mice. International Neurourology Journal, 24(Suppl 1), S28–S38. https://doi.org/10.5213/inj.2040158.079

50.

Horner

A. J.

Henson

R. N.

(2008). Priming, response learning and repetition suppression. Neuropsychologia, 46(7), 1979–1991. https://doi.org/10.1016/j.neuropsychologia.2008.01.018

51.

Hsu

W.-Y.

Cheng

C.-H.

Liao

K.-K.

Lee

I. H.

Lin

Y.-Y.

(2012). Effects of repetitive transcranial magnetic stimulation on motor functions in patients with stroke. Stroke, 43(7), 1849–1857. https://doi.org/10.1161/STROKEAHA.111.649756

52.

Hughes

Herrera

Gaunt

Collinger

(2020). Bidirectional brain-computer interfaces. Handbook of Clinical Neurology, 168, 163–181. https://doi.org/10.1016/B978-0-444-63934-9.00013-5

53.

Hummel

F. C.

Cohen

L. G.

(2006). Non-invasive brain stimulation: A new strategy to improve neurorehabilitation after stroke? Lancet Neurology, 5(8), 708–712. https://doi.org/S1474-4422(06)70525-7https://doi.org/ [pii] 10.1016/S1474-4422(06)70525-7

54.

Hyngstrom

A. S.

Murphy

S. A.

Nguyen

Schmit

B. D.

Negro

Gutterman

D. D.

Durand

M. J.

(2018). Ischemic conditioning increases strength and volitional activation of paretic muscle in chronic stroke: A pilot study. J Appl Physiol (1985), 124(5), 1140–1147. https://doi.org/10.1152/japplphysiol.01072.2017

55.

Joy

M. T.

Carmichael

S. T.

(2021). Encouraging an excitable brain state: Mechanisms of brain repair in stroke. Nature Reviews: Neuroscience, 22(1), 38–53. https://doi.org/10.1038/s41583-020-00396-7

56.

Kheirollahzadeh

Sarvghadi

Bani Hani

Azizkhani

Monnin

Choukou

M.-A.

(2025). Digital health technologies to support at-home recovery of people with stroke: A scoping review. Applied Sciences, 15(10), 5335. https://www.mdpi.com/2076-3417/15/10/5335 https://doi.org/10.3390/app15105335

57.

Kimberley

T. J.

Pierce

Prudente

C. N.

Francisco

G. E.

Yozbatiran

Smith

Dawson

(2018). Vagus nerve stimulation paired with upper limb rehabilitation after chronic stroke. Stroke, 49(11), 2789–2792. https://doi.org/10.1161/STROKEAHA.118.022279

58.

Kimberley

T. J.

Prudente

C. N.

Engineer

N. D.

Dickie

D. A.

Bisson

T. A.

Van de Winckel

(2023). Vagus Nerve Stimulation Paired With Mobility Training in Chronic Ischemic Stroke: A Case Report. Physical Therapy, 103(12). https://doi.org/10.1093/ptj/pzad097

59.

Kleim

J. A.

Jones

T. A.

(2008). Principles of experience-dependent neural plasticity: Implications for rehabilitation after brain damage. Journal of Speech, Language, and Hearing Research, 51(1), S225–S239. https://doi.org/10.1044/1092-4388(2008/018)

60.

Kumari

Dybus

Purcell

Vučković

(2025). Motor priming to enhance the effect of physical therapy in people with spinal cord injury. Journal of Spinal Cord Medicine, 48(2), 312–326. https://doi.org/10.1080/10790268.2024.2317011

61.

Langhorne

Rodgers

Ashburn

Bernhardt

(2017). A very early rehabilitation trial after stroke (AVERT): A phase III, multicentre, randomised controlled trial. Health Technology Assessment, 21(54), 1–120. https://doi.org/10.3310/hta21540

62.

Lee

S. M.

Henson

R. N.

Lin

C. Y.

(2020). Neural correlates of repetition priming: A coordinate-based meta-analysis of fMRI studies. Frontiers in Human Neuroscience, 14, 565114. https://doi.org/10.3389/fnhum.2020.565114

63.

Lefaucheur

J. P.

Aleman

Baeken

Benninger

D. H.

Brunelin

Di Lazzaro

Filipović

S. R.

Grefkes

Hasan

Hummel

F. C.

Jääskeläinen

S. K.

Langguth

Leocani

Londero

Nardone

Nguyen

J. P.

Nyffeler

Oliveira-Maia

A. J.

Oliviero

… Ziemann

(2020). Evidence-based guidelines on the therapeutic use of repetitive transcranial magnetic stimulation (rTMS): An update (2014-2018). Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 131(2), 474–528. https://doi.org/10.1016/j.clinph.2019.11.002

64.

Lefaucheur

J. P.

Antal

Ayache

S. S.

Benninger

D. H.

Brunelin

Cogiamanian

Paulus

(2017). Evidence-based guidelines on the therapeutic use of transcranial direct current stimulation (tDCS). Clinical Neurophysiology, 128(1), 56–92. https://doi.org/10.1016/j.clinph.2016.10.087

65.

Lehmann

Villringer

Taubert

Priming cardiovascular exercise improves complex motor skill learning by affecting the trajectory of learning-related brain plasticity.

66.

Lim

Iyer

P. C.

Luciano

Madhavan

(2020). Game-based movement facilitates acute priming effect in stroke. Somatosensory and Motor Research, 1–7. https://doi.org/10.1080/08990220.2020.1846513

67.

Lim

Madhavan

(2023). Non-paretic leg movements can facilitate cortical drive to the paretic leg in individuals post stroke with severe motor impairment: Implications for motor priming. European Journal of Neuroscience, 58(3), 2853–2867. https://doi.org/10.1111/ejn.16069

68.

Lim

Marjanovic

Luciano

Madhavan

(2022). Feasibility and acceptability of game-based cortical priming and functional lower limb training in a remotely supervised home setting for chronic stroke: A case series. Front Rehabil Sci, 3, 775496. https://doi.org/10.3389/fresc.2022.775496

69.

Lima

J. P. S.

Silva

L. A.

Delisle-Rodriguez

Cardoso

V. F.

Nakamura-Palacios

E. M.

Bastos-Filho

T. F.

(2023). Unraveling Transformative Effects after tDCS and BCI Intervention in Chronic Post-Stroke Patient Rehabilitation-An Alternative Treatment Design Study. Sensors (Basel), 23(23). https://doi.org/10.3390/s23239302

70.

Limaye

N. S.

Carvalho

L. B.

Kramer

(2021). Effects of aerobic exercise on Serum biomarkers of neuroplasticity and brain repair in stroke: A systematic review. Archives of Physical Medicine and Rehabilitation, 102(8), 1633–1644. https://doi.org/10.1016/j.apmr.2021.04.010

71.

Lin

D. J.

Backus

Chakraborty

Liew

S. L.

Valero-Cuevas

F. J.

Patten

Cotton

R. J.

(2024). Transforming modeling in neurorehabilitation: Clinical insights for personalized rehabilitation. Journal of Neuroengineering and Rehabilitation, 21(1), 18. https://doi.org/10.1186/s12984-024-01309-w

72.

Lin

D. J.

Cramer

S. C.

Boyne

Khatri

Krakauer

J. W.

(2025). High-Dose, high-intensity stroke rehabilitation: Why aren't we giving it? Stroke, 56(5), 1351–1364. https://doi.org/10.1161/strokeaha.124.043650

73.

Lotze

Markert

Sauseng

Hoppe

Plewnia

Gerloff

(2006). The role of multiple contralesional motor areas for complex hand movements after internal capsular lesion. Journal of Neuroscience, 26(22), 6096–6102. https://doi.org/26/22/6096https://doi.org/ [pii] 10.1523/JNEUROSCI.4564-05.2006

74.

Lozano

A. M.

Lipsman

Bergman

Brown

Chabardes

Chang

J. W.

Krauss

J. K.

(2019). Deep brain stimulation: Current challenges and future directions. Nature Reviews: Neurology, 15(3), 148–160. https://doi.org/10.1038/s41582-018-0128-2

75.

Y. H.

Chen

H. J.

Liao

C. D.

Chen

P. J.

Wang

X. M.

C. H.

Lin

C. H.

(2024). Upper extremity function and disability recovery with vibration therapy after stroke: A systematic review and meta-analysis of RCTs. Journal of Neuroengineering and Rehabilitation, 21(1), 221. https://doi.org/10.1186/s12984-024-01515-6

76.

Maceira-Elvira

Popa

Schmid

A.-C.

Hummel

F. C.

(2019). Wearable technology in stroke rehabilitation: Towards improved diagnosis and treatment of upper-limb motor impairment. Journal of Neuroengineering and Rehabilitation, 16(1), 142. https://doi.org/10.1186/s12984-019-0612-y

77.

Madhavan

Cleland

B. T.

Sivaramakrishnan

Freels

Lim

Testai

F. D.

Corcos

D. M.

(2020). Cortical priming strategies for gait training after stroke: A controlled, stratified trial. Journal of Neuroengineering and Rehabilitation, 17(1), 111. https://doi.org/10.1186/s12984-020-00744-9

78.

Madhavan

Shah

(2012). Enhancing motor skill learning with transcranial direct current stimulation – a concise review with applications to stroke. Front Psychiatry, 3, 66. https://doi.org/10.3389/fpsyt.2012.00066

79.

Malley

K. M.

Ruiz

A. D.

Darrow

M. J.

Danaphongse

Shiers

Ahmad

F. N.

Beltran

C. M.

Stanislav

B. T.

Price

Rennaker

R. L.

II Kilgard

M. P.

Hays

S. A.

(2024). Neural mechanisms responsible for vagus nerve stimulation–dependent enhancement of somatosensory recovery. Research Square. https://doi.org/10.21203/rs.3.rs-3873435/v1

80.

Mane

Chouhan

Guan

(2020). BCI For stroke rehabilitation: Motor and beyond. J Neural Eng, 17(4), 041001. https://doi.org/10.1088/1741-2552/aba162

81.

Marquez

van Vliet

McElduff

Lagopoulos

Parsons

(2015). Transcranial direct current stimulation (tDCS): Does it have merit in stroke rehabilitation? A systematic review. International Journal of Stroke, 10(3), 306–316. https://doi.org/10.1111/ijs.12169

82.

Marzola

Melzer

Pavesi

Gil-Mohapel

Brocardo

P. S.

(2023). Exploring the Role of Neuroplasticity in Development, Aging, and Neurodegeneration. Brain Sci, 13(12). https://doi.org/10.3390/brainsci13121610

83.

Meng

Zhang

Hai

Zhao

Y. Y.

Y. W.

(2020). Efficacy of coupling intermittent theta-burst stimulation and 1Hz repetitive transcranial magnetic stimulation to enhance upper limb motor recovery in subacute stroke patients: A randomized controlled trial. Restorative Neurology and Neuroscience, 38(1), 109–118. https://doi.org/10.3233/RNN-190953

84.

Miao

Chen

Zhang

Jin

Daly

Jia

Wang

Cichocki

Jung

T. P.

(2020). BCI-Based Rehabilitation on the stroke in sequela stage. Neural Plasticity, 2020, 8882764. https://doi.org/10.1155/2020/8882764

85.

Moriarty

T. A.

Mermier

Kravitz

Gibson

Beltz

Zuhl

(2019). Acute aerobic exercise based cognitive and motor priming: Practical applications and mechanisms. Frontiers in Psychology, 10, 2790. https://doi.org/10.3389/fpsyg.2019.02790

86.

Murase

Duque

Mazzocchio

Cohen

L. G.

(2004). Influence of interhemispheric interactions on motor function in chronic stroke. Annals of Neurology, 55(3), 400–409. https://doi.org/10.1002/ana.10848

87.

Murphy

T. H.

Corbett

(2009). Plasticity during stroke recovery: From synapse to behaviour. Nature Reviews: Neuroscience, 10(12), 861–872. https://doi.org/10.1038/nrn2735

88.

Nave

A. H.

Rackoll

Grittner

Bläsing

Gorsler

Nabavi

D.G.

Audebert

H. J.

Klostermann

Müller-Werdan

Steinhagen-Thiessen

Meisel

(2019). Physical fitness training in patients with subacute stroke (PHYS-STROKE): Multicentre, randomised controlled, endpoint blinded trial. BMJ, 366, l5101. https://doi.org/10.1136/bmj.l5101

89.

Nie

Yang

(2017). Modulation of synaptic plasticity by exercise training as a basis for ischemic stroke rehabilitation. Cellular and Molecular Neurobiology, 37(1), 5–16. https://doi.org/10.1007/s10571-016-0348-1

90.

Nowak

D. A.

Grefkes

Ameli

Fink

G. R.

(2009). Interhemispheric competition after stroke: Brain stimulation to enhance recovery of function of the affected hand. Neurorehabilitation and Neural Repair, 23(7), 641–656. https://doi.org/10.1177/1545968309336661

91.

Nudo

R. J.

(1997). Remodeling of cortical motor representations after stroke: Implications for recovery from brain damage. Molecular Psychiatry, 2(3), 188–191. https://doi.org/10.1038/sj.mp.4000188

92.

O'Dell

M. W.

(2023). Stroke rehabilitation and motor recovery. Continuum (Minneap Minn), 29(2), 605–627. https://doi.org/10.1212/con.0000000000001218

93.

Olsen

L. K.

Solis

Jr. McIntire

L. K.

Hatcher-Solis

C. N.

(2023). Vagus nerve stimulation: Mechanisms and factors involved in memory enhancement. Frontiers in Human Neuroscience, 17, 1152064. https://doi.org/10.3389/fnhum.2023.1152064

94.

Paro

M. R.

Dyrda

Ramanan

Wadman

Burke

S. A.

Cipollone

Bosworth

Zurek

Senatus

P.B.

(2023). Deep brain stimulation for movement disorders after stroke: A systematic review of the literature. Journal of Neurosurgery, 138(6), 1688–1701. https://doi.org/10.3171/2022.8.JNS221334

95.

Pelletier

S. J.

Cicchetti

(2014). Cellular and molecular mechanisms of action of transcranial direct current stimulation: evidence from in vitro and in vivo models. International Journal of Neuropsychopharmacology, 18(2). https://doi.org/10.1093/ijnp/pyu047

96.

Perez

M. A.

Lungholt

B. K.

Nyborg

Nielsen

J. B.

(2004). Motor skill training induces changes in the excitability of the leg cortical area in healthy humans. Experimental Brain Research, 159(2), 197–205. https://doi.org/10.1007/s00221-004-1947-5

97.

Perlmutter

J. S.

Mink

J. W.

(2006). Deep brain stimulation. Annual Review of Neuroscience, 29, 229–257. https://doi.org/10.1146/annurev.neuro.29.051605.112824

98.

Peters

D. M.

O'Brien

E. S.

Kamrud

K. E.

Roberts

S. M.

Rooney

T. A.

Thibodeau

K. P.

Balakrishnan

Gell

Mohapatra

(2021). Utilization of wearable technology to assess gait and mobility post-stroke: A systematic review. Journal of Neuroengineering and Rehabilitation, 18(1), 67. https://doi.org/10.1186/s12984-021-00863-x

99.

Pycroft

Stein

Aziz

(2018). Deep brain stimulation: An overview of history, methods, and future developments. Brain Neurosci Adv, 2, 2398212818816017. https://doi.org/10.1177/2398212818816017

100.

Rehme

A. K.

Eickhoff

S. B.

Wang

L. E.

Fink

G. R.

Grefkes

(2011). Dynamic causal modeling of cortical activity from the acute to the chronic stage after stroke. Neuroimage, 55(3), 1147–1158. https://doi.org/10.1016/j.neuroimage.2011.01.014

101.

Rehme

A. K.

Grefkes

(2013). Cerebral network disorders after stroke: Evidence from imaging-based connectivity analyses of active and resting brain states in humans. Journal of Physiology, 591(1), 17–31. https://doi.org/10.1113/jphysiol.2012.243469

102.

Rodriguez-Huguet

Ayala-Martinez

Vinolo-Gil

M. J.

Gongora-Rodriguez

Martin-Valero

Gongora-Rodriguez

(2024). Transcranial direct current stimulation in physical therapy treatment for adults after stroke: A systematic review. NeuroRehabilitation, 54(2), 171–183. https://doi.org/10.3233/NRE-230213

103.

Schacter

D. L.

Dobbins

I. G.

Schnyer

D. M.

(2004). Specificity of priming: A cognitive neuroscience perspective. Nature Reviews: Neuroscience, 5(11), 853–862. https://doi.org/10.1038/nrn1534

104.

Schambra

H. M.

Hays

S. A.

(2025). Vagus nerve stimulation for stroke rehabilitation: Neural substrates, neuromodulatory effects and therapeutic implications. Journal of Physiology, 603(3), 723–735. https://doi.org/10.1113/JP285566

105.

Schlaug

Cassarly

Feld

J. A.

Wolf

S. L.

Rowe

V. T.

Fritz

Chhatbar

P. Y.

Shinde

Broderick

J. P.

Zorowitz

Awosika

Edwards

Lin

Franciso

G. E.

Wittenberg

G. F.

Pundik

Gregory

Borich

M. R.

Ramakrishnan

Feng

(2025). Safety and efficacy of transcranial direct current stimulation in addition to constraint-induced movement therapy for post-stroke motor recovery (TRANSPORT2): A phase 2, multicentre, randomised, sham-controlled triple-blind trial. The Lancet. Neurology, 24(5), 400–412. https://doi.org/10.1016/S1474-4422(25)00044-4

106.

Sens

Knorr

Preul

Meissner

Witte

O. W.

Miltner

W. H.

Weiss

(2013). Differences in somatosensory and motor improvement during temporary functional deafferentation in stroke patients and healthy subjects. Behavioural Brain Research, 252, 110–116. https://doi.org/10.1016/j.bbr.2013.05.048

107.

Sens

Teschner

Meissner

Preul

Huonker

Witte

O. W.

Miltner

W. H.

Weiss

(2012). Effects of temporary functional deafferentation on the brain, sensation, and behavior of stroke patients. Journal of Neuroscience, 32(34), 11773–11779. https://doi.org/10.1523/JNEUROSCI.5912-11.2012

108.

Sharbafshaaer

Cirillo

Esposito

Tedeschi

Trojsi

(2024). Harnessing Brain Plasticity: The Therapeutic Power of Repetitive Transcranial Magnetic Stimulation (rTMS) and Theta Burst Stimulation (TBS) in Neurotransmitter Modulation, Receptor Dynamics, and Neuroimaging for Neurological Innovations. Biomedicines, 12(11). https://doi.org/10.3390/biomedicines12112506

109.

Siebner

H. R.

(2010). A primer on priming the human motor cortex. Clinical Neurophysiology, 121(4), 461–463. https://doi.org/10.1016/j.clinph.2009.12.009

110.

Sinha

A. M.

Nair

V. A.

Prabhakaran

Brain-Computer Interface Training With Functional Electrical Stimulation: Facilitating Changes in Interhemispheric Functional Connectivity and Motor Outcomes Post-stroke.

111.

Sivaramakrishnan

Madhavan

(2021). Combining transcranial direct current stimulation with aerobic exercise to optimize cortical priming in stroke. Applied Physiology, Nutrition, and Metabolism. Physiologie Appliquée, Nutrition et Métabolisme, 46(5), 426–435. https://doi.org/10.1139/apnm-2020-0677

112.

Sivaramakrishnan

Subramanian

S. K.

(2023). A systematic review on the effects of acute aerobic exercise on neurophysiological, molecular, and behavioral measures in chronic stroke. Neurorehabilitation and Neural Repair, 37(2-3), 151–164. https://doi.org/10.1177/15459683221146996

113.

Sriraman

Oishi

Madhavan

(2014). Timing-dependent priming effects of tDCS on ankle motor skill learning. Brain Research, 1581, 23–29. https://doi.org/10.1016/j.brainres.2014.07.021

114.

Stagg

C. J.

Nitsche

M. A.

(2011). Physiological basis of transcranial direct current stimulation. Neuroscientist, 17(1), 37–53. https://doi.org/10.1177/1073858410386614

115.

Starosta

Cichon

Saluk-Bijak

Miller

(2022). Benefits from Repetitive Transcranial Magnetic Stimulation in Post-Stroke Rehabilitation. J Clin Med, 11(8). https://doi.org/10.3390/jcm11082149

116.

Stinear

C. M.

Petoe

M. A.

Anwar

Barber

P. A.

Byblow

W. D.

(2014). Bilateral priming accelerates recovery of upper limb function after stroke: A randomized controlled trial. Stroke, 45(1), 205–210. https://doi.org/10.1161/strokeaha.113.003537

117.

Stoykov

M. E.

Corcos

D. M.

Madhavan

(2017). Movement-Based priming: Clinical applications and neural mechanisms. J Mot Behav, 49(1), 88–97. https://doi.org/10.1080/00222895.2016.1250716

118.

Stoykov

M. E.

Heidle

Kang

Lodesky

Maccary

L. E.

Madhavan

(2022). Sensory-Based priming for upper extremity hemiparesis after stroke: A scoping review. OTJR (Thorofare N J), 42(1), 65–78. https://doi.org/10.1177/15394492211032606

119.

Stoykov

M. E.

Madhavan

(2015). Motor priming in neurorehabilitation. Journal of Neurologic Physical Therapy, 39(1), 33–42. https://doi.org/10.1097/npt.0000000000000065

120.

Strafella

A. P.

Paus

Barrett

Dagher

(2001). Repetitive transcranial magnetic stimulation of the human prefrontal cortex induces dopamine release in the caudate nucleus. Journal of Neuroscience, 21(15), RC157. https://doi.org/10.1523/JNEUROSCI.21-15-j0003.2001

121.

Takeuchi

Izumi

(2015). Combinations of stroke neurorehabilitation to facilitate motor recovery: Perspectives on hebbian plasticity and homeostatic metaplasticity. Frontiers in Human Neuroscience, 9, 349. https://doi.org/10.3389/fnhum.2015.00349

122.

Tang

Han

Wang

Zhang

(2022). Excitatory repetitive transcranial magnetic stimulation over the ipsilesional hemisphere for upper limb motor function after stroke: A systematic review and meta-analysis. Frontiers in Neurology, 13, 918597. https://doi.org/10.3389/fneur.2022.918597

123.

Tedla

J. S.

Sangadala

D. R.

Reddy

R. S.

Gular

Kakaraparthi

V. N.

Asiri

(2023). Transcranial direct current stimulation (tDCS) effects on upper limb motor function in stroke: An overview review of the systematic reviews. Brain Injury, 37(2), 122–133. https://doi.org/10.1080/02699052.2022.2163289

124.

Thomas

Beck

M. M.

Lind

R. R.

Korsgaard Johnsen

Geertsen

S. S.

Christiansen

Ritz

Roig

Lundbye-Jensen

(2016). Acute exercise and motor memory consolidation: The role of exercise timing. Neural Plasticity, 2016, 6205452. https://doi.org/10.1155/2016/6205452

125.

Tien

H. H.

Liu

W. Y.

Chen

Y. L.

Y. C.

(2020). Transcranial direct current stimulation for improving ambulation after stroke: a systematic review and meta-analysis. International Journal of Rehabilitation Research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue Internationale de Recherches de Readaptation, 43, 299–309. https://doi.org/10.1097/MRR.0000000000000427

126.

Vecchio

L. M.

Meng

Xhima

Lipsman

Hamani

Aubert

(2018). The neuroprotective effects of exercise: Maintaining a healthy brain throughout aging. Brain Plast, 4(1), 17–52. https://doi.org/10.3233/BPL-180069

127.

Veerbeek

J. M.

van Wegen

van Peppen

van der Wees

P. J.

Hendriks

Rietberg

Kwakkel

(2014). What is the evidence for physical therapy poststroke? A systematic review and meta-analysis. PloS One, 9(2), e87987. https://doi.org/10.1371/journal.pone.0087987

128.

Voss

M. W.

Erickson

K. I.

Prakash

R. S.

Chaddock

Kim

J. S.

Alves

Szabo

Phillips

S. M.

Wójcicki

T. R.

Mailey

E. L.

Olson

E. A.

(2013). Neurobiological markers of exercise-related brain plasticity in older adults. Brain, Behavior, and Immunity, 28, 90–99. https://doi.org/10.1016/j.bbi.2012.10.021

129.

Wathen

C. A.

Frizon

L. A.

Maiti

T. K.

Baker

K. B.

Machado

A. G.

(2018). Deep brain stimulation of the cerebellum for poststroke motor rehabilitation: From laboratory to clinical trial. Neurosurgical Focus, 45(2), E13. https://doi.org/10.3171/2018.5.FOCUS18164

130.

Woods

A. J.

Antal

Bikson

Boggio

P. S.

Brunoni

A. R.

Celnik

Cohen

L.G.

Fregni

Herrmann

C. S.

Kappenman

E. S.

Knotkova

(2016). A technical guide to tDCS, and related non-invasive brain stimulation tools. Clinical Neurophysiology, 127(2), 1031–1048. https://doi.org/10.1016/j.clinph.2015.11.012

131.

Yang

Shi

Wang

Yang

Sun

(2021). Exploring the use of brain-computer interfaces in stroke neurorehabilitation. Biomed Res Int, 2021, 9967348. https://doi.org/10.1155/2021/9967348

132.

Yang

Shakil

Cho

(2019). Peripheral mechanisms of remote ischemic conditioning. Cond Med, 2(2), 61–68. https://www.ncbi.nlm.nih.gov/pubmed/32313875

133.

Yuan

Silberstein

S. D.

(2016a). Vagus nerve and Vagus nerve stimulation, a comprehensive review: Part I. Headache, 56(1), 71–78. https://doi.org/10.1111/head.12647

134.

Yuan

Silberstein

S. D.

(2016b). Vagus nerve and Vagus nerve stimulation, a comprehensive review: Part II. Headache, 56(2), 259–266. https://doi.org/10.1111/head.12650

135.

Zhao

Hausenloy

D. J.

Hess

D. C.

Yellon

D. M.

(2023). Remote ischemic conditioning: Challenges and opportunities. Stroke, 54(8), 2204–2207. https://doi.org/10.1161/STROKEAHA.123.043279