Neuroplasticity Following Stroke from a Functional Laterality Perspective: A fNIRS Study

Song, Ying; Sun, ZhiFang; Wei⁃zhen, SUN; Luo, MeiLing; Du, YiJun; Jing, Jing; Wang, Yonghui

doi:10.1007/s10548-023-00946-z

Cited by 3 publications

(2 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Baskett et al (1996) noted sensorimotor impairments on the unaffected side in patients with right-lesion strokes, indicating compensatory adaptations associated with S1–M1 coupling in the affected hemisphere—observations that are consistent with our own findings [ 48 ]. In addition, Ying et al (2023) observed a negative correlation between motor function and the resting-state functional connectivity strength of the left S1 and M1 [ 49 ], further supporting the notion that improved motor function corresponds with reduced dependence on these brain areas. These examples highlighted the complex neural adaptations during stroke recovery, where decreased activation in specific regions indicated effective adaptation and rehabilitation.…”

Section: Discussionmentioning

confidence: 88%

Use of cortical hemodynamic responses in digital therapeutics for upper limb rehabilitation in patients with stroke

Kim,

Lee

et al. 2024

J NeuroEngineering Rehabil

View full text Add to dashboard Cite

Background Stroke causes long-term disabilities, highlighting the need for innovative rehabilitation strategies for reducing residual impairments. This study explored the potential of functional near-infrared spectroscopy (fNIRS) for monitoring cortical activation during rehabilitation using digital therapeutics. Methods This cross-sectional study included 18 patients with chronic stroke, of whom 13 were men. The mean age of the patients was 67.0 ± 7.1 years. Motor function was evaluated through various tests, including the Fugl–Meyer assessment for upper extremity (FMA-UE), grip and pinch strength test, and box and block test. All the patients completed the digital rehabilitation program (MotoCog®, Cybermedic Co., Ltd., Republic of Korea) while being monitored using fNIRS (NIRScout®, NIRx Inc., Germany). Statistical parametric mapping (SPM) was employed to analyze the cortical activation patterns from the fNIRS data. Furthermore, the K-nearest neighbor (K-NN) algorithm was used to analyze task performance and fNIRS data to classify the severity of motor impairment. Results The participants showed diverse task performances in the digital rehabilitation program, demonstrating distinct patterns of cortical activation that correlated with different motor function levels. Significant activation was observed in the ipsilesional primary motor area (M1), primary somatosensory area (S1), and contralateral prefrontal cortex. The activation patterns varied according to the FMA-UE scores. Positive correlations were observed between the FMA-UE scores and SPM t-values in the ipsilesional M1, whereas negative correlations were observed in the ipsilesional S1, frontal lobe, and parietal lobe. The incorporation of cortical hemodynamic responses with task scores in a digital rehabilitation program substantially improves the accuracy of the K-NN algorithm in classifying upper limb functional levels in patients with stroke. The accuracy for tasks, such as the gas stove-operation task, increased from 44.4% using only task scores to 83.3% when these scores were combined with oxy-Hb t-values from the ipsilesional M1. Conclusions The results advocated the development of tailored digital rehabilitation strategies by combining the behavioral and cerebral hemodynamic data of patients with stroke. This approach aligns with the evolving paradigm of personalized rehabilitation in stroke recovery, highlighting the need for further extensive research to optimize rehabilitation outcomes.

show abstract

Section: Discussionmentioning

confidence: 88%

Use of cortical hemodynamic responses in digital therapeutics for upper limb rehabilitation in patients with stroke

Kim,

Lee

et al. 2024

J NeuroEngineering Rehabil

View full text Add to dashboard Cite

show abstract

“…Tras la repetición de una tarea motora específica se activan estructuras subcorticales que consiguen la mejora del movimiento y de la realización de la misma. Por lo que el aprendizaje motor implica cambios en la neuroplasticidad tanto a nivel cortical como subcortical que dependen del entrenamiento en la rehabilitación [210,211]. Así mismo, el aprendizaje motor interactúa con otros procesos además de los motores, como los cognitivos, sensoriales, perceptivo y/o emocionales.…”

Section: Neurorehabilitación Del Paciente Post-ictusunclassified

Efectos de la Terapia en Espejo vs. Ejercicio Terapéutico Cognoscitivo en la mejora de las funciones del miembro superior en pacientes con ictus

Fernández Solana

View full text Add to dashboard Cite

Current implications of EEG and fNIRS as functional neuroimaging techniques for motor recovery after stroke

Sun,

Dai,

et al. 2024

Medical Review

View full text Add to dashboard Cite

Persistent motor deficits are highly prevalent among post-stroke survivors, contributing significantly to disability. Despite the prevalence of these deficits, the precise mechanisms underlying motor recovery after stroke remain largely elusive. The exploration of motor system reorganization using functional neuroimaging techniques represents a compelling yet challenging avenue of research. Quantitative electroencephalography (qEEG) parameters, including the power ratio index, brain symmetry index, and phase synchrony index, have emerged as potential prognostic markers for overall motor recovery post-stroke. Current evidence suggests a correlation between qEEG parameters and functional motor outcomes in stroke recovery. However, accurately identifying the source activity poses a challenge, prompting the integration of EEG with other neuroimaging modalities, such as functional near-infrared spectroscopy (fNIRS). fNIRS is nowadays widely employed to investigate brain function, revealing disruptions in the functional motor network induced by stroke. Combining these two methods, referred to as integrated fNIRS-EEG, neural activity and hemodynamics signals can be pooled out and offer new types of neurovascular coupling-related features, which may be more accurate than the individual modality alone. By harnessing integrated fNIRS-EEG source localization, brain connectivity analysis could be applied to characterize cortical reorganization associated with stroke, providing valuable insights into the assessment and treatment of post-stroke motor recovery.

show abstract

Neuroplasticity Following Stroke from a Functional Laterality Perspective: A fNIRS Study

Cited by 3 publications

References 46 publications

Use of cortical hemodynamic responses in digital therapeutics for upper limb rehabilitation in patients with stroke

Use of cortical hemodynamic responses in digital therapeutics for upper limb rehabilitation in patients with stroke

Efectos de la Terapia en Espejo vs. Ejercicio Terapéutico Cognoscitivo en la mejora de las funciones del miembro superior en pacientes con ictus

Current implications of EEG and fNIRS as functional neuroimaging techniques for motor recovery after stroke

Contact Info

Product

Resources

About