Riemannian geometry boosts functional near-infrared spectroscopy-based brain-state classification accuracy.

ABSTRACT:

Background

Functional near-infrared spectroscopy (fNIRS) has recently gained momentum as a reliable and accurate tool for assessing brain states based on the vascular response to neural activity. This increase in popularity is due to its robustness to movement, non-invasive nature, portability, and user-friendly application. However, compared with other hemodynamic functional brain-imaging methods such as functional magnetic resonance imaging (fMRI), fNIRS is constrained by its limited spatial resolution and coverage with a particularly limited penetration depth. In addition, due to comparatively fewer methodological advancements, the performance of fNIRS-based brain-state classification still lags behind more prevalent methods such as fMRI.

Methods

We introduce a classifica

SUBMITTER: Naher T 

PROVIDER: S-EPMC12523035 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature