Non-invasive Optical Low-frequency Oscillation Study of the Prefrontal Cortex Based on fNIRS

August 6, 2026 updated by: Ting Li, Peking Union Medical College
The investigators aimed to investigate the effects of different cognitive load tasks (1-back, 2-back, 3-back) on low-frequency oscillations (LFOs) in the prefrontal cortex of healthy young individuals, analyze the relationship between LFO parameters (power, peak amplitude, peak frequency) and behavioral performance (reaction time, accuracy), and validate the feasibility of using LFOs as a quantitative measure of brain resting-state activity and a sensitive indicator of cognitive load.Low-frequency oscillations (LFO, 0.05-0.15 Hz) are a core feature of cerebral hemodynamics and are closely related to neural activity, blood pressure regulation, and metabolic function. Existing studies suggest that LFO may be influenced by cognitive load during mental tasks, but the underlying mechanisms remain unclear. Functional near-infrared spectroscopy (fNIRS), with its advantages of non-invasiveness, portability, and high temporal resolution, enables precise monitoring of hemodynamic parameters in the prefrontal cortex, including changes in oxygenated and deoxygenated hemoglobin concentrations (Δ[oxy-Hb], Δ[deoxy-Hb]). This study combines the N-back working memory task to investigate how cognitive load modulates LFO, offering a novel approach for assessing brain function.In this study, the investigators used a portable 16-channel continuous-wave functional near-infrared spectroscopy (fNIRS) system to measure dynamic changes in prefrontal cortex (PFC) hemodynamic parameters-Δ[oxy-Hb], Δ[deoxy-Hb], and Δ[tot-Hb]-in 48 healthy participants under varying task loads. The investigators then analyzed low-frequency oscillations (LFOs) based on the detected hemodynamic parameter fluctuations, following established methodologies from prior research. Using Welch's method, LFOs were extracted from power spectral density (PSD) of different hemodynamic parameters across three task conditions (1-back, 2-back, and 3-back). The principle of fNIRS relies on near-infrared light penetrating the skull and brain, being absorbed by chromophores [HbO₂] and [Hb] with distinct absorption spectra. Assuming constant scattering and applying the modified Beer-Lambert law during calculations, sensitive light intensity detectors can detect concentration changes of these chromophores within the subject's brain tissue. The experimental setup consisted of a 4.4 cm × 15 cm sensor array distributed across the forehead, a dedicated data acquisition control box with a sampling rate of 3.3 Hz, and a computer for data storage and analysis software. The current flexible sensor comprises four light sources and ten detectors. The light sources include three built-in LEDs with peak wavelengths at 735 nm, 805 nm, and 850 nm, while the detectors are designed to image the sub-frontal cortical regions (dorsolateral and ventromedial prefrontal cortices). The distance between each source and its surrounding detectors is 2.89 cm, enabling hemodynamic measurements at depths of 2-3 cm beneath the scalp, focusing primarily on the cerebral cortex. Each light source is arranged in an X-shape with four adjacent detectors, where the source is centered and detectors positioned at the corners, forming channels connecting each source to individual detectors. The prefrontal cortex is a region strongly associated with cognitive processing and plays a critical role in working memory tasks. Task load was implemented through working memory tasks-a mechanism by which the brain temporarily processes and stores information crucial for handling complex cognitive demands. Understanding how the amplitude of hemodynamic oscillations is modulated by different cognitive loads is significant, as microvascular blood flow is regulated by myogenic mechanisms. These foundational insights will help improve the analysis and interpretation of hemodynamic neuroimaging data. This study employs fNIRS, a non-invasive neuroimaging technique highly sensitive to microvascular activity, to investigate the interactive effects of cognitive load on brain hemodynamic LFOs.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Actual)

47

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Tianjin Municipality
      • Tianjin, Tianjin Municipality, China, 300192
        • 16 channel fNIRS

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

47 right-handed volunteers (23 males and 24 females) were recruited. Their ages ranged from 18 to 23 years, with an average age of 22.1 years for males and 21.5 years for females. The participants were young adults, as the study aimed to investigate the effects of LFO on cognitive activation, which involved a relatively challenging 3-back working memory task. All participants had normal or corrected-to-normal vision. Female participants were excluded if they were within their menstrual cycle, as hormonal fluctuations during this period may affect certain prefrontal cortical functions. None of the participants had a history of neurological or psychiatric disorders, nor were they taking any psychotropic medications. Participants abstained from alcohol, caffeine, and nicotine for at least 24 hours prior to the experiment.

Description

Inclusion Criteria:

  • Aged 18 to 23 years
  • Right-hand
  • Normal or corrected-to-normal vision
  • Willing to abstain from alcohol, caffeine, and nicotine for at least 24 hours prior to the experiment
  • Able to understand the study procedures and provide written informed consent

Exclusion Criteria:

  • History of neurological or psychiatric disorders (e.g., epilepsy, severe insomnia, or anxiety)
  • History of arrhythmia or other severe cardiovascular conditions
  • Current or long-term use of psychotropic medications or other medications affecting the nervous system
  • Contraindications for wearing skin-mounted optical devices
  • Female participants currently in their menstrual cycle (due to potential hormonal effects on prefrontal cortical functions)
  • Inability to follow experimental instructions or complete the testing tasks

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
No category
Device: N-back Visual working memory task
The investigators employed the N-back visual working memory task, a continuous letter task with varying working memory load demands. The task consisted of four fixation blocks and three task blocks, lasting a total of 377 seconds. Each fixation block lasted 20 seconds, during which participants were instructed to fixate their gaze on a central point. The working memory load gradually increased from 1-back to 3-back across the task blocks. Participants were required to determine whether the current letter matched the previous letter (1-back), the letter two positions back (2-back), or the letter three positions back (3-back) in terms of features, responding with one button for "yes" and another for "no."

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Peak Amplitude of Low-Frequency Oscillations (LFO) Measured by functional Near-Infrared Spectroscopy (fNIRS)
Time Frame: Day1, The assessment time point was after the n-back task, with spectral analysis performed on low-frequency oscillation data collected during the 377-second n-back experiment.
  1. The peak amplitude of LFO (0.05-0.15 Hz) will be extracted from the power spectral density (PSD) of the relative changes in oxygenated and deoxygenated hemoglobin concentrations in the prefrontal cortex. This is measured using a 16-channel portable continuous-wave fNIRS system during different cognitive load tasks (1-back, 2-back, and 3-back).
  2. Measurement Tool: 16-channel continuous-wave fNIRS system.
  3. Unit of Measure: Perived from relative hemoglobin concentration changes and after log-transformed-power spectral density (PSD) in certain frequency :lg(μM^2/Hz).
Day1, The assessment time point was after the n-back task, with spectral analysis performed on low-frequency oscillation data collected during the 377-second n-back experiment.
Peak frequency of Low-Frequency Oscillations (LFO) Measured by fNIRS
Time Frame: Day1, The assessment time point was after the n-back task, with spectral analysis performed on low-frequency oscillation data collected during the 377-second n-back experiment.
  1. The frequency at which the maximum power occurs within the low-frequency band (0.05-0.15 Hz) derived from the PSD of prefrontal cortex hemoglobin concentration changes. This assesses the shift in vascular oscillation frequency under varying cognitive loads (1-back, 2-back, 3-back).
  2. Measurement Tool: 16-channel continuous-wave fNIRS system.
  3. Unit of Measure: Hertz (Hz).
Day1, The assessment time point was after the n-back task, with spectral analysis performed on low-frequency oscillation data collected during the 377-second n-back experiment.
Power of Low-Frequency Oscillations (LFO) Measured by fNIRS
Time Frame: Day1, The assessment time point was after the n-back task, with spectral analysis performed on low-frequency oscillation data collected during the 377-second n-back experiment.
  1. The total signal power within the low-frequency band (0.05-0.15 Hz) calculated from the PSD of hemoglobin concentration changes during the working memory tasks. The power spectral data undergoes a logarithmic transformation prior to statistical analysis to ensure normal distribution.
  2. Measurement Tool: 16-channel continuous-wave fNIRS system.
  3. Unit of Measure: derived from relative hemoglobin concentration changes after log-transformed: lg(μM^2)
Day1, The assessment time point was after the n-back task, with spectral analysis performed on low-frequency oscillation data collected during the 377-second n-back experiment.

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Reaction Time Assessed by N-back Behavioral Task System
Time Frame: Day1, The assessment time point was after the n-back task, analyzing behavioral reaction times during the 377-second n-back experiment.
  1. The average time participants take to make a judgment (via button press) on whether the currently displayed letter matches the target letter during the 1-back, 2-back, and 3-back working memory task blocks.
  2. Measurement Tool: Computerized N-back visual working memory task software.
Day1, The assessment time point was after the n-back task, analyzing behavioral reaction times during the 377-second n-back experiment.
Accuracy Rate Assessed by N-back Behavioral Task System
Time Frame: Day 1, the assessment time point was after the n-back task, analyzing behavioral accuracy rate during the 377-second n-back experiment.
  1. The percentage of correct button press responses made by the participant across the 30 randomly presented letters within each N-back task block (1-back, 2-back, 3-back).
  2. Measurement Tool: Computerized N-back visual working memory task software.
  3. Unit of Measure: Percentage (%).
Day 1, the assessment time point was after the n-back task, analyzing behavioral accuracy rate during the 377-second n-back experiment.
Correlation Between LFO Parameters and Task Behavioral Performance
Time Frame: Day 1, the assessment time point was after the n-back task, analyzing behavioral correlation between low frequency oscillation parameters and task behavioral performance during the 377-second n-back experiment.
  1. The statistical correlation evaluating the relationship between the fNIRS-derived LFO parameters (peak amplitude, peak frequency, log-transformed power) and the behavioral performance metrics (reaction time and accuracy) across different cognitive loads. This directly evaluates the feasibility of using LFO as a quantitative indicator of cognitive load.
  2. Measurement Tool: Statistical correlation analysis (e.g., Pearson or Spearman correlation coefficient).
  3. Unit of Measure: Correlation coefficient (r-value)
Day 1, the assessment time point was after the n-back task, analyzing behavioral correlation between low frequency oscillation parameters and task behavioral performance during the 377-second n-back experiment.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Peking Union Medical College

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

  • [1] Biswal B, Zerrin Yetkin F, Haughton V M, et al. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI[J]. Magnetic resonance in medicine, 1995, 34(4): 537-541. [2] Tong Y, Hocke L M, Licata S C, et al. Low-frequency oscillations measured in the periphery with near-infrared spectroscopy are strongly correlated with blood oxygen level-dependent functional magnetic resonance imaging signals[J]. Journal of biomedical optics, 2012, 17(10): 106004-106004. [3] Auer D P. Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the 'resting'brain[J]. Magnetic resonance imaging, 2008, 26(7): 1055-1064. [4] Morita Y, Hardebo J E, Bouskela E. Influence of cerebrovascular sympathetic, parasympathetic, and sensory nerves on autoregulation and spontaneous vasomotion[J]. Acta physiologica scandinavica, 1995, 154(2): 121-130 [5] Vern B A, Schuette W H, Leheta B, et al. Low-frequency oscillations of cortical oxidative metabolism in waking and sleep[J]. Journal of Cerebral Blood Flow & Metabolism, 1988, 8(2): 215-226. [6] Lin PY, Roche-Labarbe N, Dehaes M, Carp S, Fenoglio A, Barbieri B, Hagan K, Grant PE, Franceschini MA. Non-invasive optical measurement of cerebral metabolism and hemodynamics in infants. J Vis Exp. 2013 Mar 14;(73):e4379. [7] Diehl R R, Linden D, Lücke D, et al. Spontaneous blood pressure oscillations and cerebral autoregulation[J]. Clinical Autonomic Research, 1998, 8(1): 7-12. [8] Katura T, Tanaka N, Obata A, et al. Quantitative evaluation of interrelations between spontaneous low-frequency oscillations in cerebral hemodynamics and systemic cardiovascular dynamics[J]. Neuroimage, 2006, 31(4): 1592-1600. [9] Cui X, Bray S, Bryant DM, Glover GH, Reiss AL. A quantitative comparison of NIRS and fMRI across multiple cognitive tasks. Neuroimage. 2011 Feb 14;54(4):2808-21. [10] Biswal B B, Kylen J V, Hyde J S. Simultaneous assessment of flow and BOLD signals in resting-state fu

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 1, 2025

Primary Completion (Actual)

July 1, 2025

Study Completion (Actual)

October 1, 2025

Study Registration Dates

First Submitted

June 24, 2026

First Submitted That Met QC Criteria

August 6, 2026

First Posted (Actual)

August 12, 2026

Study Record Updates

Last Update Posted (Actual)

August 12, 2026

Last Update Submitted That Met QC Criteria

August 6, 2026

Last Verified

August 1, 2026

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • 2025(I)-203-01

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Protection of personal information and privacy of participants

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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