Task-related oxygenation and cerebral blood volume changes estimated from NIRS signals in motor and cognitive tasks

Although functional near-infrared spectroscopy (fNIRS) has an advantage of simultaneously measuring changes in oxy- and deoxy-hemoglobin concentrations (Δ[HbO] and Δ[HbR]), only few analysis approaches exploit this advantage. As an extension of our recently proposed method (task-related component analysis, TRCA), this study proposes a new analysis method that extracts task-related oxygenation and cerebral blood volume (CBV) changes. In the original formulation of TRCA, task-relatedness of a signal is defined as consistent appearance of a same waveform in every task block, thereby constructing task-related components by maximizing inter-block covariance. The new method proposes that, in addition to maximizing inter-block covariance, the covariance between task-related Δ[HbO] and Δ[HbR] is maximized (TRCA^+) or minimized (TRCA^-) so that oxygenation and CBV changes are maximally contrasted. The proposed method (collectively called TRCA^±) was formulated as a matrix eigenvalue problem, which can be solved efficiently with standard numerical methods, and was tested with a synthetic data generated by a balloon model, successfully recovering oxygenation and CBV components. fNIRS data from sensorimotor areas in a finger-tapping task and from prefrontal lobe in a working-memory (WM) task were then analyzed. For both tasks, the time courses and the spatial maps for oxygenation and CBV changes were found to differ consistently, providing certain constraints the parameters of balloon models. In summary. TRCA can estimate task-related oxygenation and CBV changes simultaneously, thereby extending the applicability of fNIRS

Proceedings of the 3rd International Mobile Brain/Body Imaging Conference : Berlin, July 12th to July 14th 2018

The 3rd International Mobile Brain/Body Imaging (MoBI) conference in Berlin 2018 brought together researchers from various disciplines interested in understanding the human brain in its natural environment and during active behavior. MoBI is a new imaging modality, employing mobile brain imaging methods like the electroencephalogram (EEG) or near infrared spectroscopy (NIRS) synchronized to motion capture and other data streams to investigate brain activity while participants actively move in and interact with their environment. Mobile Brain / Body Imaging allows to investigate brain dynamics accompanying more natural cognitive and affective processes as it allows the human to interact with the environment without restriction regarding physical movement. Overcoming the movement restrictions of established imaging modalities like functional magnetic resonance tomography (MRI), MoBI can provide new insights into the human brain function in mobile participants. This imaging approach will lead to new insights into the brain functions underlying active behavior and the impact of behavior on brain dynamics and vice versa, it can be used for the development of more robust human-machine interfaces as well as state assessment in mobile humans.DFG, GR2627/10-1, 3rd International MoBI Conference 201