HRF in Resting State fMRI: Methodology and Applications from OHBM 2014

A poster from the OHBM 2014 conference describes a methodology for retrieving the hemodynamic response function (HRF) from resting state fMRI data. The work by Daniele Marinazzo examines modifications to HRF parameters induced by physiological states like eyes closed versus eyes open and propofol-induced loss of consciousness. The dataset likely contains time-series neuroimaging data used to derive these HRF parameters.

Use Cases

• Method validation for HRF estimation based on the described retrieval methodology
• Comparative analysis of neural activity under different physiological states based on the eyes open/closed and anesthesia conditions mentioned
• Modeling the hemodynamic response in resting-state networks based on the inferred fMRI time-series data

Strengths

• Methodology is associated with a peer-reviewed academic conference (OHBM 2014)
• The dataset is derived from a described experimental design comparing specific physiological states

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Last update date is unknown; freshness unverified

Provenance

Source

Daniele Marinazzo

Collection Method

Methodology presented in an academic poster; data collection method for the underlying fMRI scans is not specified.