# Near-Infrared Spectroscopy Applied to Complex Systems and Human Hyperscanning Networking
## 6 Optical Imaging and Methods for fNIRS Hyperscanning Applications
By increasing the number of recording channels, it is possible to improve the spatial sampling of hemodynamic changes associated with brain function and, thanks to advanced processing algorithms, even to create 2D or 3D reconstructions of the blood perfusion within the cortex and of associated neural activations. As for time resolutions, latest fNIRS systems allow for recording from multiple channels with a relatively good sampling rate (up to 100 Hz, even if it is typically limited to around 6 or 10 Hz). While the slow nature of measured biosignals limits the time-domain information that can be obtained, advances in signal processing methods and experimental designs might allow for effectively recording informative signal changes in the order of hundreds of milliseconds [48]. It is important to note, however, that such progresses in hemodynamic signal processing and their application to optical imaging are still a matter of limited experimental testing. Given the localized and circumscribed distribution of hemodynamic modulations and the sensitivity of the technique, fNIRS spatial resolution is usually reported in the centimeter range (\(\approx\)1 cm), with a tissue penetration potential of about 2 cm--enough to reach cortical layers [43]. It is, however, worth noting that the actual spatial resolution of an fNIRS recording also depends on specific methodological and technical aspects, such as the recorded scalp/cortical regions that are transilluminated, the source-detectors distance, and settings of the recording system. In order to properly organize, split, and integrate emitted and recaptured light signals, fNIRS systems include a multiplexer. With the increasing complexity of optical imaging systems, such an element became even more important, since it allows for the coordination of data flows from multiple recording channels measuring hemoglobin modulations from multiple points on the scalp (and then different cortical areas) in a single device. Some fNIRS-based hyperscanning studies [4; 30; 31; 49] took advantage of this potential and of technical features of optical imaging systems to overcome two known methodological issues: synchronization of different devices and potential differences in their sensitivity. Since fNIRS recordings are reference-free--contrary to EEG recordings, which require individual isoelectric reference sensors to compute differential waveforms--it is then possible to connect two individuals to the same recording system, by splitting light sources and detectors between them. This solution prevents potential issues concerning the comparability of different systems calibration and the lack of synchrony between the time courses of data recoded from different co-agents. In addition, with respect to EEG, fNIRS can be similarly used in event-related experimental designs, but its measurement benefits from a greater spatial resolution, though limited to cortical structures [36; 44; 45]. Indeed, the recording of electrical biosignals--such as in EEG--is known to be negatively affected by attenuation and smearing. These phenomena are due to the electrical nature of the recorded signals, since electrical activity tends to spread out through conductive medium such as biological tissues. Further, the fact that different biological tissues show different electrical conductivity makes the problem of spatial resolution and the localization of EEG data even more complex. While source localization techniques offer a notable opportunity to locate the source of scalp-recorded EEG data, spatial resolution still strongly depends, even in that case, on the distribution and density of spatial sampling (i.e., the placement and number of recording channels), and localization data represent an estimate of the most probable solution to the inverse problem.