Nirs-spm Software

After converting measured near-infrared light changes into oxyhemoglobin and deoxyhemoglobin estimates, NIRS-SPM uses a general linear model to test whether each signal follows the response predicted for the experimental task. The model provides a framework for evaluating task-related changes rather than treating every fluctuation as activation, linking physiological signal estimates to an explicit experimental prediction.

Temporal noise can create fluctuations in oxyhemoglobin and deoxyhemoglobin signals that do not reflect the task-related response. NIRS-SPM accounts for this noise during statistical analysis so that the comparison between the observed signal and the predicted hemodynamic response is more appropriately evaluated. This helps distinguish task-linked patterns from unrelated temporal variation in the recorded data.

Statistical parametric mapping applies statistical testing across the measured data to identify locations where the signal follows the predicted task-related response. In NIRS-SPM, this analysis supports assessment at channel or voxel levels, allowing researchers to examine where cortical hemodynamic changes occur and to quantify spatial patterns rather than relying only on a single overall signal.

A typical workflow first represents changes in near-infrared light as oxyhemoglobin and deoxyhemoglobin concentration estimates. NIRS-SPM then models those signals against the predicted hemodynamic response, accounts for temporal noise, and applies statistical parametric mapping. The resulting tests indicate whether measured changes are consistent with the experimental task at the analyzed channel or voxel locations.

Researchers can apply NIRS-SPM when an experiment examines cortical hemodynamic responses during cognitive, sensory, or motor tasks. The software supports testing whether measured signals follow the expected response for an experimental condition, making it useful for evaluating task-related brain activity and comparing response patterns across the spatial locations represented in the analysis.

NIRS-SPM can provide channel- or voxel-level statistical assessments of task-related cortical hemodynamic changes. These results help researchers determine whether signals match the predicted response, compare patterns between experimental conditions, and quantify the spatial distribution of cortical responses. The analysis therefore connects condition-level comparisons with localized measurements of brain activity.