Prefrontal Cerebral Oxygenated Hemoglobin Concentration during the Category Fluency and Finger-Tapping Tasks in Adults with and without Mild Cognitive Impairment: A Near-Infrared Spectroscopy Study

Abstract

Mild cognitive impairment (MCI) is considered to be the limit between the cognitive changes of aging and early dementia; thus, discriminating between participants with and without MCI is important. In the present study, we aimed to examine the differences in the cerebral oxyhemoglobin signal between individuals with and without MCI. The cerebral oxyhemoglobin signal was measured when the participants (young and elderly controls as well as patients with MCI) performed category fluency, finger tapping, and dual tasks using head-mounted near-infrared spectroscopy; the results were compared between the groups. The cerebral oxyhemoglobin signal trended toward the highest values during the category fluency task in young participants and during the finger-tapping task in elderly participants regardless of the MCI status. The area under the curve was approximately 0.5, indicating a low discrimination ability between elderly participants with and without MCI. The measurement of the blood flow in the prefrontal cortex may not accurately quantify cognitive and motor performance to detect MCI. Finger tapping may increase cerebral blood flow in individuals with and without MCI during the task.

Construction and evaluation of a neurofeedback system using finger tapping and near-infrared spectroscopy

“…However, the areas that control finger movement traditionally include the primary motor cortex (BA4), premotor cortex, supplementary motor area (BA6) (Sugioka et al, 2022 ), primary sensorimotor cortex, and the cerebellum (Turesky et al, 2018 ). Activation in prefrontal regions during alternating finger tapping has not been confirmed in young individuals (Takahashi et al, 2022 ). In our paradigm of finger tapping with neurofeedback, the concentration of oxygenated hemoglobin increased, which may also be due to the effect of this system.…”

“…The NIRS signal was then normalized using a z-score transformation for inter-participant comparison (Megumi et al, 2023 ); for the z-score, the signal at each time point was divided by the mean value during the 10 s before the first task and then by the standard deviation during the 10 s before the task. Values outside ±2 times the standard deviation of the mean were excluded as outliers (Takahashi et al, 2022 ). To evaluate prefrontal activation, channels (CH)10–13 were analyzed as right PFC, CH16–19 as middle PFC, and CH22–25 as left PFC.…”

“…Patients with orthopedic, cerebrovascular, neurologic, motor, limb or finger disorders were also considered for exclusion; however, no participants were excluded. Based on the results of previous studies, a sample size of at least 15 participants was required (Takahashi et al, 2018(Takahashi et al, , 2022. This sample size could not be met for the older population.…”