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Functional near-infrared spectroscopy (fNIRS) research articles show a large heterogeneity in the analysis approaches and pre-processing procedures. Additionally, there is often a lack of a complete description of the methods applied, necessary for study replication or for results comparison. The aims of this paper were (i) to review and investigate which information is generally included in published fNIRS papers, and (ii) to define a signal pre-processing procedure to set a common ground for standardization guidelines. To this goal, we have reviewed 110 fNIRS articles published in 2016 in the field of cognitive neuroscience, and performed a simulation analysis with synthetic fNIRS data to optimize the signal filtering step before applying the GLM method for statistical inference. Our results highlight the fact that many papers lack important information, and there is a large variability in the filtering methods used. Our simulations demonstrated that the optimal approach to remove noise and recover the hemodynamic response from fNIRS data in a GLM framework is to use a 1000th order band-pass Finite Impulse Response filter. Based on these results, we give preliminary recommendations as to the first step toward improving the analysis of fNIRS data and dissemination of the results.

Inhibitory control develops over time and is linked to fronto-striatal maturation. Traditional computerised assessments often lack ecological validity and are not age appropriate. Here, we developed a naturalistic, age-appropriate paradigm using a cave automatic virtual environment (CAVE) and mobile functional near-infrared spectroscopy (fNIRS) to measure response inhibition in children aged 3–7-years. The new task was validated in adults (N = 24, M age  = 30.38, SD = 10.54), and children (N = 36, M age  = 4.44, SD age  = 1.11 years). Participants completed two Go/No-Go tasks: a standard computer-based version and an adapted CAVE version, while fNIRS recorded brain activity in the bilateral dorsolateral frontal cortices. The aims were to compare behavioural performance in the CAVE and computer tasks, establish if the tasks capture developmental differences in inhibitory control, assess their psychometric properties (convergent and divergent validity), determine the feasibility and acceptability of the multimodal CAVE-fNIRS setup in early childhood, and characterise the neural correlates of response inhibition in both 2D and 3D tasks. Consistent with typical Go/No-Go tasks, we found higher error rates in mixed blocks compared to Go-only blocks. No significant correlations were found between self-reported (adults) or parent-reported (children) inhibition measures and task performance, nor between performance metrics across the CAVE and computer tasks, though children generally exhibited poorer performance across most metrics compared to adults, reflecting the prolonged developmental trajectory of inhibitory control. The novel CAVE task proved feasible and acceptable, with high completion rates and absent or minimal virtual reality-induced symptoms. Specific to the early childhood sample, Go/No-Go blocks in the CAVE task elicited higher activity in the left inferior frontal gyrus. This study shows the brain correlates of response inhibition during unrestricted movement in 2D and 3D settings in young children, integrating age-appropriate fNIRS with an immersive CAVE, opening potential new approaches to studying neurodevelopment.

Functional Near Infrared-Spectroscopy (fNIRS) represents a powerful tool to non-invasively study task-evoked brain activity. fNIRS assessment of cortical activity may suffer for contamination by physiological noises of different origin (e.g. heart beat, respiration, blood pressure, skin blood flow), both task-evoked and spontaneous. Spontaneous changes occur at different time scales and, even if they are not directly elicited by tasks, their amplitude may result task-modulated. In this study, concentration changes of hemoglobin were recorded over the prefrontal cortex while simultaneously recording the facial temperature variations of the participants through functional infrared thermal (fIR) imaging. fIR imaging provides touch-less estimation of the thermal expression of peripheral autonomic. Wavelet analysis revealed task-modulation of the very low frequency (VLF) components of both fNIRS and fIR signals and strong coherence between them. Our results indicate that subjective cognitive and autonomic activities are intimately linked and that the VLF component of the fNIRS signal is affected by the autonomic activity elicited by the cognitive task. Moreover, we showed that task-modulated changes in vascular tone occur both at a superficial and at larger depth in the brain. Combined use of fNIRS and fIR imaging can effectively quantify the impact of VLF autonomic activity on the fNIRS signals.

Recent technological advances have allowed the development of portable functional Near-Infrared Spectroscopy (fNIRS) devices that can be used to perform neuroimaging in the real-world. However, as real-world experiments are designed to mimic everyday life situations, the identification of event onsets can be extremely challenging and time-consuming. Here, we present a novel analysis method based on the general linear model (GLM) least square fit analysis for the Automatic IDentification of functional Events (or AIDE) directly from real-world fNIRS neuroimaging data. In order to investigate the accuracy and feasibility of this method, as a proof-of-principle we applied the algorithm to (i) synthetic fNIRS data simulating both block-, event-related and mixed-design experiments and (ii) experimental fNIRS data recorded during a conventional lab-based task (involving maths). AIDE was able to recover functional events from simulated fNIRS data with an accuracy of 89%, 97% and 91% for the simulated block-, event-related and mixed-design experiments respectively. For the lab-based experiment, AIDE recovered more than the 66.7% of the functional events from the fNIRS experimental measured data. To illustrate the strength of this method, we then applied AIDE to fNIRS data recorded by a wearable system on one participant during a complex real-world prospective memory experiment conducted outside the lab. As part of the experiment, there were four and six events (actions where participants had to interact with a target) for the two different conditions respectively (condition 1: social-interact with a person; condition 2: non-social-interact with an object). AIDE managed to recover 3/4 events and 3/6 events for conditions 1 and 2 respectively. The identified functional events were then corresponded to behavioural data from the video recordings of the movements and actions of the participant. Our results suggest that “brain-first” rather than “behaviour-first” analysis is possible and that the present method can provide a novel solution to analyse real-world fNIRS data, filling the gap between real-life testing and functional neuroimaging. •A novel GLM-based method to recover the timing of functional events from fNIRS data.•The method showed high specificity and sensitivity in synthetic and real data.•The method is applied to fNIRS data conducted outdoor on a freely moving participant.

•Neuroimaging of people while walking around London, England.•Greater activation in prefrontal cortex when maintaining social future intentions.•A brain-first analysis approach provided additional explanatory power.•Functional neural events in prefrontal cortex occurred at different locations on the street. . Rostral PFC (area 10) activation is common during prospective memory (PM) tasks. But it is not clear what mental processes these activations index. Three candidate explanations from cognitive neuroscience theory are: (i) monitoring of the environment; (ii) spontaneous intention retrieval; (iii) a combination of the two. These explanations make different predictions about the temporal and spatial patterns of activation that would be seen in rostral PFC in naturalistic settings. Accordingly, we plotted functional events in PFC using portable fNIRS while people were carrying out a PM task outside the lab and responding to cues when they were encountered, to decide between these explanations. Nineteen people were asked to walk around a street in London, U.K. and perform various tasks while also remembering to respond to prospective memory (PM) cues when they detected them. The prospective memory cues could be either social (involving greeting a person) or non-social (interacting with a parking meter) in nature. There were also a number of contrast conditions which allowed us to determine activation specifically related to the prospective memory components of the tasks. We found that maintaining both social and non-social intentions was associated with widespread activation within medial and right hemisphere rostral prefrontal cortex (BA 10), in agreement with numerous previous lab-based fMRI studies of prospective memory. In addition, increased activation was found within lateral prefrontal cortex (BA 45 and 46) when people were maintaining a social intention compared to a non-social one. The data were then subjected to a GLM-based method for automatic identification of functional events (AIDE), and the position of the participants at the time of the activation events were located on a map of the physical space. The results showed that the spatial and temporal distribution of these events was not random, but aggregated around areas in which the participants appeared to retrieve their future intentions (i.e., where they saw intentional cues), as well as where they executed them. Functional events were detected most frequently in BA 10 during the PM conditions compared to other regions and tasks. Mobile fNIRS can be used to measure higher cognitive functions of the prefrontal cortex in “real world” situations outside the laboratory in freely ambulant individuals. The addition of a “brain-first” approach to the data permits the experimenter to determine not only when haemodynamic changes occur, but also where the participant was when it happened. This can be extremely valuable when trying to link brain and cognition.

The specialised regional functionality of the mature human cortex partly emerges through experience-dependent specialisation during early development. Our existing understanding of functional specialisation in the infant brain is based on evidence from unitary imaging modalities and has thus focused on isolated estimates of spatial or temporal selectivity of neural or haemodynamic activation, giving an incomplete picture. We speculate that functional specialisation will be underpinned by better coordinated haemodynamic and metabolic changes in a broadly orchestrated physiological response. To enable researchers to track this process through development, we develop new tools that allow the simultaneous measurement of coordinated neural activity (EEG), metabolic rate, and oxygenated blood supply (broadband near-infrared spectroscopy) in the awake infant. In 4- to 7-month-old infants, we use these new tools to show that social processing is accompanied by spatially and temporally specific increases in coupled activation in the temporal-parietal junction, a core hub region of the adult social brain. During non-social processing, coupled activation decreased in the same region, indicating specificity to social processing. Coupling was strongest with high-frequency brain activity (beta and gamma), consistent with the greater energetic requirements and more localised action of high-frequency brain activity. The development of simultaneous multimodal neural measures will enable future researchers to open new vistas in understanding functional specialisation of the brain.

The simple act of watching another person can change a person’s behaviour in subtle but important ways; the individual being watched is now capable of signalling to the watcher, and may use this opportunity to communicate to the watcher. Recent data shows that people will spontaneously imitate more when being watched. Here, we examine the neural and cognitive mechanisms of being watched during spontaneous social imitation in autistic and neurotypical adults using fNIRS brain imaging. Participants (n = 44) took part in a block-moving task where they were instructed only to copy the block sequence which people normally do using a straight low action trajectory. Here, the demonstrator sometimes used an atypical ‘high’ action trajectory, giving participants the opportunity to spontaneously copy the high trajectory even if this slowed their performance. The confederate who demonstrated each block sequence could watch the participant’s actions or close her eyes, giving a factorial design with factors of trajectory (high/low) and watched (watched/unwatched). Throughout the task, brain signals were captured from bilateral temporal/parietal/occipital cortex using fNIRS. We found that all participants performed higher actions when being watched by the confederate than when not being watched, with no differences between autistic and neurotypical participants. The unwatched conditions were associated with higher activity of the right inferior parietal lobule in all participants and also engagement of left STS only in autistic participants. These findings are consistent with the claim that people engage different neural mechanisms when watched and unwatched and that participants with autism may engage additional brain mechanisms to match neurotypical behaviour and compensate for social difficulties. However, further studies will be needed to replicate these results in a larger sample of participants.

Metabolic pathways underlying brain function remain largely unexplored during neurodevelopment, predominantly due to the lack of feasible techniques for use with awake infants. Broadband near-infrared spectroscopy (bNIRS) provides the opportunity to explore the relationship between cerebral energy metabolism and blood oxygenation/haemodynamics through the measurement of changes in the oxidation state of mitochondrial respiratory chain enzyme cytochrome-c-oxidase (ΔoxCCO) alongside haemodynamic changes. We used a bNIRS system to measure ΔoxCCO and haemodynamics during functional activation in a group of 42 typically developing infants aged between 4 and 7 months. bNIRS measurements were made over the right hemisphere over temporal, parietal and central cortical regions, in response to social and non-social visual and auditory stimuli. Both ΔoxCCO and Δ[HbO2] displayed larger activation for the social condition in comparison to the non-social condition. Integration of haemodynamic and metabolic signals revealed networks of stimulus-selective cortical regions that were not apparent from analysis of the individual bNIRS signals. These results provide the first spatially resolved measures of cerebral metabolic activity alongside haemodynamics during functional activation in infants. Measuring synchronised changes in metabolism and haemodynamics have the potential for uncovering the development of cortical specialisation in early infancy.

Significance: There is a longstanding recommendation within the field of fNIRS to use oxygenated (HbO2) and deoxygenated (HHb) hemoglobin when analyzing and interpreting results. Despite this, many fNIRS studies do focus on HbO2 only. Previous work has shown that HbO2 on its own is susceptible to systemic interference and results may mostly reflect that rather than functional activation. Studies using both HbO2 and HHb to draw their conclusions do so with varying methods and can lead to discrepancies between studies. The combination of HbO2 and HHb has been recommended as a method to utilize both signals in analysis. Aim: We present the development of the hemodynamic phase correlation (HPC) signal to combine HbO2 and HHb as recommended to utilize both signals in the analysis. We use synthetic and experimental data to evaluate how the HPC and current signals used for fNIRS analysis compare. Approach: About 18 synthetic datasets were formed using resting-state fNIRS data acquired from 16 channels over the frontal lobe. To simulate fNIRS data for a block-design task, we superimposed a synthetic task-related hemodynamic response to the resting state data. This data was used to develop an HPC-general linear model (GLM) framework. Experiments were conducted to investigate the performance of each signal at different SNR and to investigate the effect of false positives on the data. Performance was based on each signal’s mean T-value across channels. Experimental data recorded from 128 participants across 134 channels during a finger-tapping task were used to investigate the performance of multiple signals [HbO2, HHb, HbT, HbD, correlation-based signal improvement (CBSI), and HPC] on real data. Signal performance was evaluated on its ability to localize activation to a specific region of interest. Results: Results from varying the SNR show that the HPC signal has the highest performance for high SNRs. The CBSI performed the best for medium-low SNR. The next analysis evaluated how false positives affect the signals. The analyses evaluating the effect of false positives showed that the HPC and CBSI signals reflect the effect of false positives on HbO2 and HHb. The analysis of real experimental data revealed that the HPC and HHb signals provide localization to the primary motor cortex with the highest accuracy. Conclusions: We developed a new hemodynamic signal (HPC) with the potential to overcome the current limitations of using HbO2 and HHb separately. Our results suggest that the HPC signal provides comparable accuracy to HHb to localize functional activation while at the same time being more robust against false positives.

Recent progress in optoelectronics has made wearable and high-density functional near-infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) technologies possible for the first time. These technologies have the potential to open new fields of real-world neuroscience by enabling functional neuroimaging of the human cortex at a resolution comparable to fMRI in almost any environment and population. In this perspective article, we provide a brief overview of the history and the current status of wearable high-density fNIRS and DOT approaches, discuss the greatest ongoing challenges, and provide our thoughts on the future of this remarkable technology.