Fig. 5.

Simulated fNIRS activity assuming the true neuronal activity ${\mathrm{H}}_{\text{Neuronal}}$ is a single positive Gaussian patch: $H_{\text{Neuronal}}=e^{-(x^2+y^2)/(2{\sigma }^2)}$, where $\sigma =1\mathrm{cm}$. The global component ${\mathrm{H}}_{\text{Global}}$ is assumed to be constant. The top row shows the simulated spatial pattern of ${\mathrm{H}}_{\text{Neuronal}}$, ${\mathrm{H}}_{\text{Global}}$, and acquired data H. The middle row shows the derived neuronal component ${\mathrm{H}}_{\text{Neuronal}}$ using various spatial filter sizes. The bottom row shows the derived neuronal component ${\mathrm{H}}_{\text{Neuronal}}$ using various coverage sizes with the largest possible filter size. For all panels, each pixel or color block represents a 1-cm square.