Objectives: To investigate the effects of different forms (physical and mental, aerobic and resistance) of single exercise on the cognitive flexibility and brain functional connectivity of elderly individuals with cognitive impairment. Clinical trail Methods: This study employed a single-blind, multi-center randomized controlled trial. Sixty elderly individuals with cognitive impairment were recruited and randomly divided into the Qigong group (15 participants), the brisk walking group (15 participants), the elastic band group (15 participants), and the control group (15 participants). Before and after the intervention, 5-minute resting-state electroencephalogram signals were collected and cognitive flexibility tests were conducted. The Qigong group, the brisk walking group, and the elastic band group received single sessions of Qigong, brisk walking, and elastic band exercises respectively, while the control group received health education. The exercise intensity was moderate (target heart rate was 64%-76% of the maximum heart rate), and the exercise duration was 30 minutes.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Enrollment
60
exercise programm
health education materials
Shanghai University of Sport
Shanghai, China
Cognitive flexibility
Cognitive flexibility was assessed using the More-odd-shifting task paradigm, which was designed with E-prime software. The testing environment was quiet, well ventilated and moderately lit. The stimuli used in the More-odd-shifting task were red or green Arabic numerals from 1 to 9, excluding 5. Participants were required to make key-press responses according to the task instructions when the stimuli appeared. The More-odd-shifting task consisted of three conditions: Condition 1, judgment of numerical magnitude; Condition 2, judgment of parity; and Condition 3, mixed judgment of numerical magnitude and parity.
Time frame: A total of 8 months from the beginning to the end
Brain functional connectivity
Brain functional connectivity analysis was performed using MATLAB scripts, and graph-theoretical analysis was carried out using the BrainNet Viewer toolbox. Phase locking value (PLV) was used, and brain functional connectivity was evaluated from two dimensions: connectivity strength and density. In this study, PLV was calculated for the δ, θ, α1, α2, β1 and β2 bands of resting-state EEG using MATLAB, and the formula is shown in Equation (1). Here, i is the imaginary unit, Δt is the time interval between two consecutive samples, and N is the total number of samples. PLV is an index used to quantify phase synchrony in EEG signals and assesses whether two signals maintain a relatively stable phase relationship over time. Its value ranges from 0 to 1, where 1 indicates complete synchrony and 0 indicates no synchrony. PLV is commonly used to investigate phase synchrony between different brain regions, particularly functional connectivity related to neural oscillations.
Time frame: A total of 8 months from the beginning to the end
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