Abstract Advances in non-invasive monitoring of human brain function under normal and pathological conditions will lead to breakthroughs in our understanding of the brain in health and disease, and lead to the development of devices available for everyday use, with applications such as monitoring patients with brain injuries or neurodegenerative disease, studies of brain function in natural environments, and brain-computer interfaces. Among the various brain imaging techniques, functional near infrared spectroscopy (fNIRS) is an optical method that images the hemodynamic response to brain activation by measuring the oxy-(HbO) and deoxy-(HbR) hemoglobin concentration changes due to brain activation. It is especially useful for populations and for studies for which other imaging modalities are limited, e.g. functional magnetic resonance imaging (fMRI), including for children, infants, and studies that involve motion and interactions or require high temporal resolution. However, fNIRS brain sensitivity in adult humans is typically around 10%, and fNIRS alone does not provide quantitative information about all the hemodynamic parameters as it does not measure changes in cerebral blood flow (CBF). Here, we propose to develop a fiber-based speckle contrast optical spectroscopy (SCOS) system to measure CBF variations due to brain activation in humans. SCOS uses relatively low-cost complementary metal–oxide– semiconductor (CMOS) cameras as detectors. The performance of SCOS can surpass that of existing optical systems for human measurements of CBF in terms of contrast to noise ratio (CNR) by at least one order of magnitude with equal or less cost. The combined SCOS-fNIRS system developed in the UG3 phase will provide measurements of all the hemodynamic parameters associated with brain activation, achieve an up to 3x improvement in brain sensitivity compared with fNIRS alone, and permit estimation of evoked changes in CMRO2. The high-density SCOS-fNIRS system developed in the UH3 phase will provide images of all the hemodynamic parameters with high spatial and temporal resolution. This work will result in a new approach for functional brain imaging and demonstrative results that will motivate adoption by others and future advancements towards wearable devices at a reduced cost.