Stroke is a serious health issue that, according to the World Health Organization (WHO), is the second most common cause of death and disability worldwide [1]. In South Korea, the number of stroke patients increased by 7.1% from 634,177 in 2018 to 2022 according to the Health Insurance Review and Assessment Service’s report on cerebrovascular disease treatment status. Despite early and appropriate treatment, many survivors still experience various degrees of disability that impair their quality of life [2]. Stroke patients exhibit impairments in cognitive functions and motor skills such as walking, and these impairments are more pronounced during Dual-task (DT) activities [3-5]. The goal of rehabilitation for stroke patients is to maximize recovery of residual functions to facilitate a return to complex daily activities requiring cognitive, sensory, and physical performance [6].

DT, which involves performing two tasks simultaneously rather than sequentially, typically results in a degradation in the performance of at least one of the tasks due to cognitive-motor interference [7]. This can lead to an increased risk of falls and decreased efficiency in task execution [3]. Despite an increase in prefrontal cortex activation, stroke patients demonstrate a decrease in motor and cognitive abilities during DT performance [8]. This indicates inefficiencies in brain resource utilization and can result in a decline in performance [9, 10]. Therefore, for effective performance in DTs, it is crucial to understand functional connectivity and networks within the brain cortex [11].

Among the existing brain imaging techniques, functional Magnetic Resonance Imaging (fMRI) detects high-resolution cerebral blood flow signals but requires a controlled environment and is unsuitable for patients with metal implants [12]. Electroencephalography (EEG) offers high temporal resolution but low spatial resolution and is susceptible to motion artifacts, making it challenging to apply in dynamic DT training. On the other hand, functional near-infrared spectroscopy (fNIRS), based on the principle of neurovascular coupling that regulates blood flow to meet the energy demands of active neurons [13], allows for the real-time monitoring of hemodynamic changes in the brain during activities and walking without spatial or temporal restrictions [14].

fNIRS provides better resistance to motion artifacts and greater experimental flexibility compared to other neuroimaging methods, making it more suitable for use in neurologic patients [15-17]. However, most prior studies using fNIRS have focused only on activation in the prefrontal cortex[11, 18-22], often overlooking other brain areas such as the premotor cortex (PMC), which is involved in motor planning and preparation, the sensorimotor cortex (SMC), which handles motor output or sensory input, and the posterior parietal cortex (PPC), which is important for sensorimotor integration[19, 23-25]. Therefore, systematic investigations of changes in cortical activity and functional connectivity from single to multiple tasks are necessary beyond the prefrontal cortex [26]. Additionally, the relationship between brain activation and clinical measurements remains unclear [25]. One study reported that poor motor function in stroke patients was associated with increased compensatory prefrontal cortex activation, while lower cognitive function corresponded to reduced activation in the same region [27]. Another study showed a negative correlation between motor status and DT brain activation [28]. Therefore, further research is needed to establish the relationship between clinical measurements and levels of brain activation in stroke patients [26].

In this review, we aim to synthesize studies that have examined changes in cortical excitability during DTs in post-stroke patients using fNIRS, and to analyze and evaluate the comparative effectiveness of different DT protocols and the relationships between the evaluated cortical regions.

Study Design

This study is a systematic literature review conducted to analyze the cortical activation and functional connectivity efficiency of various DT training programs applied to stroke patients with different durations of illness and cognitive and motor functions. It follows the guidelines of the Cochrane Collaboration's handbook for systematic reviews of interventions and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) for reporting available literature. Additionally, the methodological protocol of this systematic review has been registered with the PROSPERO International Prospective Register of Systematic Reviews (CRD42024523192).

Eligibility Criteria

Eligibility criteria were established based on the PICOSD framework, which includes Participants [P], Intervention [I], Comparison [C], Outcomes [O], and Study Design [SD].

Studies were selected following the PRISMA FLOW DIAGRAM guidelines and organized according to the PICOS framework. This study's participants (P) encompass both acute and chronic stroke patients. The intervention (I) involved DT. Comparisons (C) were made with control groups receiving standard interventions excluding DT, selected from studies with homogeneous control groups. The outcomes (O) focused on the measurement of cortical areas' HbO and HbR using fNIRS. Study designs (SD) included all studies that examined changes in fNIRS during DT training in stroke patients. Studies excluded were those only published as abstracts, non-English language studies, studies only presented at academic conferences, and studies that were more than ten years old.

Search Strategy

The systematic review were conducted in April 2023 by researchers with experience in systematic review. The search strategy utilized key terms related to Participants, Intervention, and Outcomes, based on MeSH (Medical Subject Heading). Keywords used included combinations of "stroke OR cerebrovascular accident OR cva OR post-stroke OR stroke patients" AND "functional near-infrared spectroscopy OR near-infrared spectroscopy OR hemodynamics" AND "Dual-task OR Dual-task training OR Dual-tasking OR Dual-task performance". Searches were performed across international databases such as the Cumulative Index of Nursing and Allied Health Literature (CINAHL), Excerpta Medica Database (Embase), Medical Literature Analysis and Retrieval System Online (MEDLINE), and Web of Science.

Data Extraction

Data from selected studies were extracted into Microsoft Excel (Microsoft Excel 16.71, Microsoft, USA) to eliminate duplicates. Following PRISMA guidelines, titles and abstracts were initially screened, followed by a detailed review of the full texts for studies that did not meet initial criteria. Selections were based on the defined eligibility criteria, and any disagreements among researchers were resolved through joint review.

Risk of Bias Assessment

Risk of bias for randomized controlled trials was assessed using a tool developed by the Cochrane Bias Method Group, consisting of seven items [29]. Two researchers independently rated the risk of bias as low (＋), high (－), or uncertain (?). Disagreements were settled by jointly revisiting the original texts. Cross-sectional studies were evaluated using the ROBINS-E tool (Risk Of Bias In Non-randomized Studies - of Exposures) [30], where the risk of bias was determined to be critical (I), serious (x), moderate (－), low (＋), and not applicable (Na).

Literature Search and Characteristics of Included Studies

As depicted in Figure 1, a total of 158 studies were initially identified from four international electronic databases and search engines. First, 42 duplicate studies were identified and removed using Excel. Following this, the titles and abstracts were screened by researchers, resulting in the exclusion of 107 studies. Lastly, one study that did not provide data according to the eligibility criteria was also excluded after a full-text review. Ultimately, 8 studies were included for qualitative analysis [31-38].

Risk of Bias of Synthesized Studies

The risk of bias assessment of the eight studies had 100% agreement among researchers. The results of the three RCTs and five other studies are shown in Figure 2.

Cortical Activation Changes between DTs in Stroke Patients.

Recent research on stroke patients highlights that DT compared to single-task significantly increases brain activation, particularly in the prefrontal cortex and other related areas such as the premotor and posterior parietal cortex. This increased activation correlates with greater energy expenditure and improved cognitive and motor function integration. However, excessive activation does not always translate to functional improvements, suggesting a complex interaction between brain activation and motor recovery.

This systematic review elucidates the dynamic interplay between cognitive and motor functionalities in post-stroke patients during DT activities, highlighting the critical role of cortical activations across various regions such as the PFC, PMC, PPC, and SMA. These findings suggest that DT interventions might significantly influence brain activation patterns, promoting better integration of cognitive and motor functions.

Cortical Activation and Functional Outcomes

Increased activation of the PFC during DTs, as noted in multiple studies, underscores its integral role in managing combined cognitive and motor demands [27]. However, enhanced PFC activation does not uniformly translate into improved functional outcomes. This discrepancy suggests that in some instances, increased activation may represent compensatory mechanisms rather than recovery, highlighting a complex relationship between brain activation and actual functional enhancement.

Metabolic Costs and Contralateral Activation

The review corroborates findings that DT markedly increases metabolic demands, evidenced by heightened energy expenditure and corresponding increases in contralateral PFC activation [33]. This response indicates significant neurophysiological adaptation and suggests that the brain's effort to handle multiple tasks can substantially elevate metabolic costs, which could be a consideration in designing rehabilitation programs.

Integration of Cortical Responses

The extensive activation of cortical networks involving the PMC and PPC, in addition to the PFC, suggests an integrated response to increased demands during DT [19, 25]. This broad activation pattern may reflect the brain's strategy to engage multiple networks to preserve task performance under more demanding conditions.

Neuroplasticity and Functional Improvement

The potential for DT to enhance neuroefficiency offers promising avenues for rehabilitation. Mechanisms that potentially accelerate oxygen supply to the PFC might optimize neuronal response times, enhancing cognitive processing speed and overall task performance [31, 38].

Hemispheric Activation Patterns

Findings from Nosaka, et al., 2023 [37] highlight that DT conditions lead to the highest levels of PFC activation, suggesting robust adaptive neuroplastic changes that extend beyond the affected hemisphere. This bilateral engagement might be pivotal in harnessing the full potential of the brain's adaptive capacity post-stroke.

Consideration through Synthesized Results

The prefrontal cortex (PFC) is crucial for the demand of cognitive and executive control resources, supporting functions such as attention, working memory, motor planning, and task switching. In the context of dual-task performance, when cognitive function is insufficient, it may reach what is termed the "ceiling effect." This is where the maximum recruitment of brain resources is achieved, indicating that the recruitment of the prefrontal cortex may be inadequate. Higher recruitment is considered beneficial when there is a greater availability of cognitive resource reserves [32, 39, 40]. Furthermore, "compensatory recruitment" occurs when the recruitment of basic brain areas or networks is inadequate to support task performance. In stroke patients with severe mobility or motor deficits, there is compensatory recruitment of executive control resources to compensate for the loss of automatic or healthy control mechanisms [33, 41, 42]. Additionally, the "neural mechanisms contributing to brain over-recruitment" involve inefficient processing that requires increased brain recruitment to achieve a specific level of task performance, poor specificity in recruiting specialized networks leading to widespread recruitment, and reactive recruitment in response to subpar task performance, as a means to enhance performance [31, 43].

Limitations and Future Research

This review reveals several limitations affecting the interpretation of findings and future research design. The heterogeneity in study designs, participant demographics, and intervention types challenges the generalizability of results. Many studies use retrospective designs, which may introduce selection and reporting biases and limit causal inferences. Additionally, the small number of studies included may not fully represent the variability in stroke rehabilitation research, reducing the statistical power and robustness of conclusions. There is also a quantitative imbalance, with a predominance of qualitative over quantitative research, which could skew results towards observational insights rather than measurable outcomes. Moreover, the use of fNIRS for measuring cortical activity, despite its non-invasiveness and suitability for dynamic settings, lacks the spatial resolution of techniques like fMRI, which could compromise the precision of brain activation localization and the accuracy of correlating neural changes with functional outcomes.

To address the limitations noted in this review, future research should incorporate prospective studies to better understand the long-term effects and causal relationships of DT interventions in stroke recovery. Expanding the scope and diversity of studies will improve the reliability and applicability of findings. A balanced mix of qualitative and quantitative research will offer a comprehensive view of intervention effectiveness. Additionally, correlating specific brain activation patterns with functional outcomes using standardized measures will enable the development of targeted rehabilitation strategies. Integrating advanced imaging techniques like fMRI with fNIRS will provide more detailed insights into spatial brain activity, enhancing the understanding of recovery processes and their clinical implications. These steps will help develop more effective, tailored rehabilitation protocols for stroke survivors, potentially transforming stroke rehabilitation practices.

Clinical Implications

Clinically, these insights underscore the need for personalized DT rehabilitation programs that consider individual differences in neurophysiological responses and functional capacities. Rehabilitation specialists should consider the metabolic costs and potential for compensatory mechanisms when designing interventions. Optimizing DT interventions may involve varying the complexity and nature of tasks to maximize patient engagement and neuroplastic potential.

Overall, this review suggests that tailored dual-task interventions could optimize recovery and enhance functional independence in stroke patients by leveraging the intrinsic capabilities of the brain's motor and cognitive networks. This necessitates a nuanced approach that considers individual variability in response to dual-task conditions, paving the way for more effective post-stroke rehabilitation strategies. Further exploration into the relationship between cortical activation patterns observed during dual-task and clinical outcomes is essential to refine these therapeutic interventions.

The authors declare no conflict of interest.