scholarly journals An Overview on Cognitive Function Enhancement through Physical Exercises

2021 ◽  
Vol 11 (10) ◽  
pp. 1289
Author(s):  
Narayanasamy Sai Srinivas ◽  
Vijayaragavan Vimalan ◽  
Parasuraman Padmanabhan ◽  
Balázs Gulyás

This review is extensively focused on the enhancement of cognitive functions while performing physical exercises categorized into cardiovascular exercises, resistance training, martial arts, racquet sports, dancing and mind-body exercises. Imaging modalities, viz. functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), have been included in this review. This review indicates that differences are present in cognitive functioning while changing the type of physical activity performed. This study concludes that employing fNIRS helps overcome certain limitations of fMRI. Further, the effects of physical activity on a diverse variety of the population, from active children to the old people, are discussed.

2021 ◽  
Vol 12 ◽  
Author(s):  
Marcel Simis ◽  
Marta Imamura ◽  
Paulo Sampaio de Melo ◽  
Anna Marduy ◽  
Linamara Battistella ◽  
...  

Background: Brain plasticity is an intrinsic property of the nervous system, which is modified during its lifetime. This is one mechanism of recuperation after injuries with an important role in rehabilitation. Evidence suggests that injuries in the nervous system disturb the stability between inhibition and excitability essential for the recuperation process of neuroplasticity. However, the mechanisms involved in this balance are not completely understood and, besides the advancement in the field, the knowledge has had a low impact on the rehabilitation practice. Therefore, the understanding of the relationship between biomarkers and functional disability may help to optimize and individualize treatments and build consistent studies in the future.Methods: This cohort study, the deficit of inhibition as a marker of neuroplasticity study, will follow four groups (stroke, spinal cord injury, limb amputation, and osteoarthritis) to understand the neuroplasticity mechanisms involved in motor rehabilitation. We will recruit 500 subjects (including 100 age- and sex-matched controls). A battery of neurophysiological assessments, transcranial magnetic stimulation, electroencephalography, functional near-infrared spectroscopy, and magnetic resonance imaging, is going to be used to assess plasticity on the motor cortex before and after rehabilitation. One of the main hypotheses in this cohort is that the level of intracortical inhibition is related to functional deficits. We expect to develop a better understanding of the neuroplasticity mechanisms involved in the rehabilitation, and we expect to build neurophysiological “transdiagnostic” biomarkers, especially the markers of inhibition, which will have great relevance in the scientific and therapeutic improvement in rehabilitation. The relationship between neurophysiological and clinical outcomes will be analyzed using linear and logistic regression models.Discussion: By evaluating the reliability of electroencephalography, functional near-infrared spectroscopy, transcranial magnetic stimulation, and magnetic resonance imaging measures as possible biomarkers for neurologic rehabilitation in different neurologic disorders, this study will aid in the understanding of brain plasticity mechanisms in rehabilitation, allowing more effective approaches and screening methods to take place.


2018 ◽  
Vol 26 (2) ◽  
pp. 79-86 ◽  
Author(s):  
Gihyoun Lee ◽  
Seung Hyun Lee ◽  
Sang Hyeon Jin ◽  
Jinung An

Functional near infrared spectroscopy can measure hemodynamic signals, and the results are similar to functional magnetic resonance imaging of blood-oxygen-level-dependent signals. Thus, functional near infrared spectroscopy can be employed to investigate brain activity by measuring the absorption of near infrared light through an intact skull. Recently, a general linear model, which is a standard method for functional magnetic resonance imaging, was applied to functional near infrared spectroscopy imaging analysis. However, the general linear model fails when functional near infrared spectroscopy signals retain noise, such as that caused by the subject's movement during measurement. Although wavelet-based denoising and hemodynamic response function smoothing are popular denoising methods for functional near infrared spectroscopy signals, these methods do not exhibit impressive performances for very noisy environments and a specific class of noise. Thus, this paper proposes a new denoising algorithm that uses multiple wavelet shrinkage and a multiple threshold function based on a hemodynamic response model. Through the experiments, the performance of the proposed algorithm is verified using graphic results and objective indexes, and it is compared with existing denoising algorithms.


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