Hemodynamic Signal Data from an N-Back Task with PCA Threshold Optimization

A 1.9 MB PDF document authored by Wakana Kawai and last updated on 2026-04-22. The study presents a method for optimizing the threshold in principal component analysis to separate cortical and extracerebral hemodynamic signals, using data from older participants performing a verbal n-back task.

Use Cases

• Benchmarking PCA-based signal separation methods based on the described threshold optimization technique.
• Analyzing hemodynamic responses to cognitive load based on the n-back task paradigm mentioned in the description.
• Comparing the effectiveness of short-separation regression versus PCA correction for extracerebral signal removal.
• Evaluating inter-individual variability in hemodynamic signals using Bayesian statistical tests as described.

Strengths

• Dataset is associated with a specific methodological study on threshold optimization for PCA.
• Data was collected from a defined population (older participants) performing a standardized cognitive task (verbal n-back).
• The work is openly shared under a CC-BY-4.0 license.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The primary data file is a 1.9 MB PDF, which may require extraction of underlying numerical data.

Provenance

Source

figshare, author Wakana Kawai.

Collection Method

Data was gathered from older participants performing a verbal n-back task, as described in the methods section.

Time Range

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Freshness

Last updated 2026-04-22 05:34:55; freshness should be verified.

Geography

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