Arginina

Although there are a large number of different fNIR devices, they share some fundamental similarities in their design. The main part of an fNIR device is the sensor pad, which is placed onto the head of the participants. This part contains the light sources (e.g. LEDs) and the light detectors. Light is emitted from the light sources and is assumed to follows a ‘banana’ shaped path to the detectors as it is reflected back by the tissue (Okada et al., 1997). Photons emitted from a light source follow this path through tissue back to a detector located on the same approximate plane as the source. Most of the light is scattered or absorbed but a certain amount reaches the sensors. The light that reaches the sensors is encoded with the spectroscopic signatures of the molecules it has passed through.

By choosing the right wavelengths of light, it is possible to capture the spectroscopic signatures of Hb and HbO2. As with other neuroimaging methods, fNIR is susceptible to noise, particularly from the physiological functions of the body (e.g. respiration). As a result of this, fNIR devices provide automatic noise cancelling such as independent and principal component analysis, and optimal filtering (Izzetoglu et al. 2005; Ayaz et al., 2011). The sensor pad is connected to a computer, which analyses and stores the data collected by the sensor pad.

The number of light sources and detectors determines the number of channels an fNIR device has (i.e. the number of measurement locations). Each distance between a light source and a detector corresponds to a recording channel (or an optode). For example, an fNIR device with one light source and four sensors would have 4 recording channels. The area between the light sources and the detectors are the areas that haemodynamic activity is recorded from (also known as the measurement volume). The depth of this measurement volume from the surface (i.e. the skin) is a function of the distance between the light source and

the detector, corresponding to roughly half the distance between the light source and the detector (Gefen, Ayaz and Onaral, 2014). As a result, the further the light source and the sensor are from one another, the deeper measurements can be taken from. The number of light sources, detectors and channels is dependent on the specific fNIR device, with some devices having 16 channels and some having as many as 64 (Ferrari and Quaresima, 2012). fNIR devices with smaller number of channels are used to record activity in single areas of the brain (e.g. the frontal lobes), while devices with a larger number of channels can record neural activity from multiple areas of the brain (e.g. the frontal, parietal lobes and occipital lobes).

The sampling rate of fNIR ranges from 100Hz to less than 10Hz, while spatial resolution is in the region of 1cm (Ferrari and Quaresima, 2012).

The methods described so far in this chapter largely relate to the most commonly used form of fNIR, continuous wave (CW) fNIR. However, a number fNIR devices have been developed over the years that utilise slightly different technologies and allow for different measurements (see Elwell and Cooper (2011) for an in-depth review on this subject). These devices can be split into one of several general categories depending on the technologies they use: continuous wave, frequency-domain and time-domain. (Other near-infrared spectroscopy methods exist, such as spatially resolved and diffuse correlation spectroscopy.

However, these have not yet been used extensively for functional imaging and have instead focused on tissue oximetry.)

4.3.4.1 Continuous Wave Spectroscopy

CW spectroscopy uses light sources (usually LEDs) at two wavelengths with a constant amplitude and frequency. CW devices are not capable of determining photon path lengths. As a result they are not able to measure absolute concentrations in Hb and HbO2, only relative changes. It is sometimes possible to calculate absolute concentrations by simulating (through a Monte Carlo simulation) or assuming the photon path-lengths (Scholkmann et al., 2014). From the changes in Hb and HbO2 it is possible to calculate other values such as the change in blood volume (BF) and the change in blood oxygenation (HbO2 – Hb).

The sampling rate and of these devices can be as high as 100Hz, while their depth penetration is limited to a few cm (Ferrari and Quaresima, 2012). Due to its

relative simplicity, low cost and portability, CW is the most commonly used form of fNIR. However the cost is largely related to the number of channels, meaning that costs can increase significantly for devices with a large number of channels.

4.3.4.2 Frequency Domain fNIR Spectroscopy

Frequency domain (FD) spectroscopy also light at two wavelengths, however the light is produced by lasers and the amplitude of the light is modulated by a frequency of 100MHz or more (Torricelli et al., 2014). Changes in the amplitude and phase of the light recorded at the detectors provide direct measurements of the absorption coefficients at the two wavelengths, as well as the scattering coefficient. This removes the need to know the photon path-lengths, which allows for the calculation of the absolute values of Hb and HbO2

concentrations. This in turn allows for the calculation of values such as the absolute tissue oxygen saturation (SO2) and total haemoglobin concentration (HbT). FD fNIR devices also have the benefit of greater penetration depth for the light sources used (Ferrari and Quaresima, 2012). There are however a number of drawbacks to this methodology. Their sampling rate/temporal resolution is lower than that of CW devices (Ferrari and Quaresima, 2012) and they have a less favourable signal-to-noise ratio than CW devices (Elwell and Cooper 2011). The significantly more complex nature of these systems also makes them much more expensive and less portable (Ferrari and Quaresima, 2012).

4.3.4.3 Time Domain Spectroscopy

Time domain (TD) spectroscopy is a time of flight method that uses a light source (usually a laser) to provide light pulses with duration of a few picoseconds.

Due to these extremely fast pulses of light, detection equipment with a temporal resolution in the sub-nanosecond scale is required (Torricelli et al., 2014). TD spectroscopy relies on the measurement of the photon distribution time-of-flight in a diffuse medium (e.g. human tissue) using these extremely fast pulses of light.

By comparing the time taken for the light to travel through the tissue with a reference time from the speed of the light it is possible to calculate the absorption and scattering coefficients. This allows for the calculation of absolute values of

Hb and HbO2 concentrations. As with FD spectroscopy, TD allows for greater depth sensitivity (Ferrari and Quaresima, 2012). However the drawbacks of a lower sampling rate/temporal resolution (Ferrari and Quaresima, 2012) and inferior signal-to-noise ratio are present (Elwell and Cooper 2011). The high-speed emitters and detectors make TD systems the most expensive and complex available (Ferrari and Quaresima, 2012).