Conducting Concurrent Electroencephalography and Functional Near-Infrared Spectroscopy Recordings with a Flanker Task
May 24th, 2020
7.4K views
The present protocol describes how to perform concurrent EEG and fNIRS recordings and how to inspect the relationship between the EEG and fNIRS data.
Overview
This study presents a protocol for conducting simultaneous EEG and fNIRS recordings to assess the neuroactivation patterns during a flanker task. By integrating these techniques, the relationship between the activity in the prefrontal cortex and various event-related potentials is examined, providing insights into cognitive processing.
Key Study Components
Area of Science
- Neuroimaging
- Cognitive neuroscience
- Electrophysiology
Background
- fNIRS is primarily used to measure neurovascular activity in the frontal lobe.
- EEG offers high temporal resolution for assessing neural activity.
- The combination of these methods allows for a deeper understanding of brain function.
Purpose of Study
- To develop a protocol that effectively couples EEG and fNIRS measurements.
- To validate the relationship between ERP components and hemodynamic responses during cognitive tasks.
- To improve understanding of neural processes involved in cognitive functions.
Methods Used
- The study utilized concurrent EEG and fNIRS systems.
- Participants underwent a flanker task while undergoing simultaneous neuroimaging.
- Key procedural steps include calibration and validation of equipment to ensure signal quality.
- Data analysis was performed using specialized software to process fNIRS signals.
Main Results
- The integrated fNIRS and EEG approach revealed significant correlations between ERP components and hemodynamic responses.
- Key findings highlight the efficacy of this method in studying the neurocognitive mechanisms involved in the flanker task.
Conclusions
- This study successfully demonstrates a method for concurrent neuroimaging that enhances understanding of cognitive processes.
- The findings provide valuable insights into the relationship between neural and hemodynamic activity, informing future research in cognitive neuroscience.
Frequently Asked Questions
What are the advantages of using concurrent EEG and fNIRS?
Using both methods together provides complementary information on neural activity and vascular responses, allowing for a more comprehensive understanding of brain function.
How is the flanker task implemented in this study?
Participants perform the flanker task while undergoing simultaneous EEG and fNIRS recordings, enabling the assessment of neural responses related to cognitive processes.
What types of data are obtained from this method?
This method yields data on electrical brain activity (EEG) and changes in blood flow (fNIRS), providing insights into cognitive functions.
How can this method be adapted for other cognitive tasks?
The concurrent EEG and fNIRS setup can be applied to various cognitive tasks by adjusting the experimental design and task instructions accordingly.
What are some limitations of EEG and fNIRS?
EEG has limited spatial resolution, while fNIRS has lower temporal resolution. They can complement each other's limitations, but care must be taken during data interpretation.
Executive Industry Relevance
Concurrent EEG and fNIRS recordings provide a multimodal approach to de-risk target validation by linking rapid electrophysiological activity with hemodynamic responses in prefrontal cortex networks. This integrated methodology enhances predictive confidence in early discovery by enabling mechanistic interrogation of cognitive processing pathways relevant to neuropsychiatric and neurodegenerative indications. The protocol supports translational biomarker development through quantifiable neural and vascular correlates of task-evoked brain function.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Scientific Value: Interrogate therapeutic hypotheses by correlating ERP components (e.g., N200) with HbO signals during cognitive control tasks to validate target engagement in prefrontal circuits.
- Operational Value: Enable biological de-risking through simultaneous measurement of neural and vascular responses, reducing ambiguity in target mechanism of action.
- Predictive Value: Support portfolio triage by identifying compounds that modulate correlated EEG-fNIRS signatures, indicating preferential effects on cognitive networks.
Screening & Assay Development
- Scientific Value: Prepare validated biological systems for downstream screening by establishing baseline neurovascular coupling profiles in healthy or disease-relevant models.
- Operational Value: Address assay standardization and reproducibility through hardware/software calibration procedures and signal quality thresholds (e.g., SNR optimization via probe adjustment or intensity tuning).
- Scalability: Highlight platform reuse potential via standardized cap layouts (e.g., 10-20 system) and MNI coordinate registration for cross-study comparability.
Translational & Preclinical Research
- Translational Continuity: Discuss disease relevance by linking flanker-task-induced prefrontal activation to cognitive domains impaired in ADHD, schizophrenia, or traumatic brain injury.
- Preclinical Alignment: Describe continuity from discovery through preclinical validation by using conserved cognitive tasks (e.g., rodent analogues of flanker) to assess target-mediated changes in EEG-fNIRS coupling.
- Risk-Adjusted Advancement: Address go/no-go decisions by establishing quantitative thresholds for significant ERP-HbO correlations (e.g., Pearson r > 0.5, p < 0.05) as pharmacodynamic markers of target modulation.
Pipeline & Workflow Integration
Position the method within the discovery continuum from hypothesis testing in early discovery to lead optimization, where multimodal neuroimaging supports mechanism-of-action confirmation and biomarker qualification.
- Discovery Biology: Explain how the method supports hypothesis testing by detecting significant correlations between event-related potentials (e.g., N200 incongruent condition) and hemodynamic responses (HbO) during cognitive conflict processing.
- Screening: Describe assay readiness through reproducible signal acquisition protocols, including warm-up periods (30 min for fNIRS lasers), gel-based electrode preparation, and optical probe placement validated via 3D digitization.
- Analytics: Highlight measurements such as peak HbO values, ERP amplitude microvolt ranges (±100 µV rejection threshold), and Pearson correlation outputs that enable cross-condition comparisons (congruent vs. incongruent flanker trials).
- Translational Research: Connect the method to preclinical continuity by using the flanker task as a translatable paradigm for assessing prefrontal-dependent cognitive control across species.
- Enterprise Reuse: Frame the method as a reusable capability via standardized software pipelines (EEGLAB, ERPLAB, Homer2, fNIRS SPM) and portable hardware configurations adaptable to various cognitive paradigms.
Operational & Enterprise Impact
- Scientific Value: Predictive confidence through mechanistic de-risking of prefrontal targets via correlated electrophysiological and hemodynamic signatures.
- Operational Value: Standardization via 10-20 electrode system, fixed source-detector distance (3 cm), and reproducible signal quality controls.
- Strategic Value: Better go/no-go decisions by identifying early-stage compounds that normalize aberrant EEG-fNIRS coupling in cognitive task models.
- Portfolio Impact: Risk-adjusted prioritization based on dose-dependent modulation of correlated neural-vascular responses, reducing late-stage attrition due to insufficient target engagement.
Implementation Considerations
- Required scientific expertise in electrophysiology, neurovascular coupling, and multimodal signal processing.
- Instrumentation needs include simultaneous EEG/fNIRS acquisition systems, 3D digitizer for optode localization, and stimulus presentation hardware (e.g., for flanker task).
- Cross-team standardization requires shared protocols for electrode/optode placement, signal quality thresholds (SNR-based probe adjustment), and synchronized event marking (e.g., via parallel/serial ports).
- Adaptation considerations across model systems involve scaling cap dimensions, adjusting source-detector distances for smaller cortices, and validating task analogues (e.g., rodent touchscreen flanker).
- Practical limitations include fNIRS sensitivity to motion artifacts requiring correction algorithms and EEG susceptibility to ocular artifacts necessitating ICA-based rejection.
Biopharma FAQs
Why does null hypothesis testing matter for ERP-HbO correlation in target validation?
Null hypothesis testing determines whether observed correlations between EEG components (e.g., N200) and fNIRS signals (HbO) during flanker task performance exceed chance levels, providing statistical confidence in target-mediated effects on prefrontal neurovascular coupling.
How does isolating independent variables (e.g., congruent vs. incongruent flanker conditions) support discovery pipeline decisions?
Isolating experimental conditions enables attribution of specific ERP and HbO signal changes to cognitive control processes, allowing researchers to quantify target-dependent modulation of neural-vascular coupling during task performance.
What quantitative dependent variable measurements (e.g., peak HbO, ERP amplitude) enable go/no-go decisions in preclinical screening?
Peak HbO concentrations and ERP microvolt amplitudes serve as quantifiable endpoints; significant condition-dependent changes (e.g., incongruent > congruent) indicate target engagement in prefrontal circuits, informing compound advancement criteria.
Why do replication requirements (e.g., minimum 100% registration probability in fNIRS SPM) matter for cross-functional collaboration?
Reproducible optode localization via 3D digitization and strict registration thresholds ensure consistent spatial mapping of fNIRS channels across studies, enabling reliable comparison of hemodynamic responses between laboratories and experimental groups.
What statistical analysis capabilities (e.g., Pearson correlation, IIR filtering) are required before implementing concurrent EEG-fNIRS in target validation workflows?
Preprocessing steps including bandpass filtering (0.015–0.2 Hz for fNIRS, IIR for EEG), artifact correction (motion and ocular), and correlation analysis (Pearson r) are essential to isolate true neurovascular coupling signals from noise before assessing target effects.
Chapters in this video
0:00
Introduction
2:31
Hardware and Software Setting for Concurrent EEG and fNIRS Recordings
4:05
Preparation before the Experiment
6:47
Run the Experiment
7:09
Measurement of 3D MNI Coordinates of fNIRS Optodes with 3D Digitizer
7:47
Data Analysis
10:55
Results
11:37
Conclusion
