Significance: Solutions for group-level analysis of connectivity from fNIRS observations exist, but groupwise explorative analysis with classical solutions is often cumbersome. Manifold-based solutions excel at data exploration, but there are infinite surfaces crossing the observations cloud of points. Aim: We aim to provide a systematic choice of surface for a manifold-based analysis of connectivity at group level with small surface interpolation error. Approach: This research introduces interpolated functional manifold (IFM). IFM builds a manifold from reconstructed changes in concentrations of oxygenated Δ c HbO 2 and reduced Δ c HbR hemoglobin species by means of radial basis functions (RBF). We evaluate the root mean square error (RMSE) associated to four families of RBF. We validated our model against psychophysiological interactions (PPI) analysis using the Jaccard index (JI). We demonstrate the usability in an experimental dataset of surgical neuroergonomics. Results: Lowest interpolation RMSE was 1.26 e - 4 ± 1.32 e - 8 for Δ c HbO 2 [A.U.] and 4.30 e - 7 ± 2.50 e - 13 [A.U.] for Δ c HbR . Agreement with classical group analysis was JI = 0.89 ± 0.01 for Δ c HbO 2 . Agreement with PPI analysis was JI = 0.83 ± 0.07 for Δ c HbO 2 and JI = 0.77 ± 0.06 for Δ c HbR . IFM successfully decoded group differences [ANOVA: Δ cHbO 2 : F ( 2,117 ) = 3.07 ; p < 0.05 ; Δ c HbR : F ( 2,117 ) = 3.35 ; p < 0.05 ]. Conclusions: IFM provides a pragmatic solution to the problem of choosing the manifold associated to a cloud of points, facilitating the use of manifold-based solutions for the group analysis of fNIRS datasets.

Preterm infants born with very low birth weights are at a high risk of brain injury, in part because the premature brain is believed to be prone to periods of low cerebral blood flow (CBF). Tissue damage is likely to occur if reduction in CBF is sufficient to impair cerebral energy metabolism for extended periods. Therefore, a neuromonitoring method that can detect reductions in CBF, large enough to affect metabolism, could alert the neonatal intensive care team before injury occurs. In this report, we present the development of an optical system that combines diffuse correlation spectroscopy (DCS) for monitoring CBF and broadband near-infrared spectroscopy (B-NIRS) for monitoring the oxidation state of cytochrome c oxidase (oxCCO) - a key biomarker of oxidative metabolism. The hybrid instrument includes a multiplexing system to enable concomitant DCS and B-NIRS measurements while avoiding crosstalk between the two subsystems. The ability of the instrument to monitor dynamic changes in CBF and oxCCO was demonstrated in a piglet model of neonatal hypoxia-ischemia (HI). Experiments conducted in eight animals, including two controls, showed that oxCCO exhibited a delayed response to ischemia while CBF and tissue oxygenation (StO2) responses were instantaneous. These findings suggest that simultaneous neuromonitoring of perfusion and metabolism could provide critical information regarding clinically significant hemodynamic events prior to the onset of brain injury.

Significance: With the increasing popularity of functional near-infrared spectroscopy (fNIRS), the need to determine localization of the source and nature of the signals has grown. Aim: We compare strategies for removal of non-neural signals for a finger-thumb tapping task, which shows responses in contralateral motor cortex and a visual checkerboard viewing task that produces activity within the occipital lobe. Approach: We compare temporal regression strategies using short-channel separation to a spatial principal component (PC) filter that removes global signals present in all channels. For short-channel temporal regression, we compare non-neural signal removal using first and combined first and second PCs from a broad distribution of short channels to limited distribution on the forehead. Results: Temporal regression of non-neural information from broadly distributed short channels did not differ from forehead-only distribution. Spatial PC filtering provides results similar to short-channel separation using the temporal domain. Utilizing both first and second PCs from short channels removes additional non-neural information. Conclusions: We conclude that short-channel information in the temporal domain and spatial domain regression filtering methods remove similar non-neural components represented in scalp hemodynamics from fNIRS signals and that either technique is sufficient to remove non-neural components.

It has been 20 years since functional near-infrared spectroscopy (fNIRS) was first used to investigate the evoked hemodynamic response to a stimulus in newborns. The hemodynamic response to functional activation is well-established in adults, with an observed increase in concentration change of oxygenated hemoglobin (Δ[HbO2]) and decrease in deoxygenated hemoglobin (Δ[HHb]). However, functional studies in newborns have revealed a mixed response, particularly with Δ[HHb] where an inconsistent change in direction is observed. The reason for this heterogeneity is unknown, with potential explanations arising from differing physiology in the developing brain, or differences in instrumentation or methodology. The aim of this review is to collate the findings from studies that have employed fNIRS to monitor cerebral hemodynamics in term newborn infants aged 1 day-1 month. A total of 46 eligible studies were identified; some studies investigated more than one stimulus type, resulting in a total of 51 reported results. The NIRS parameters reported varied across studies with 50/51 cases reporting Δ[HbO2], 39/51 reporting Δ[HHb], and 13/51 reporting total hemoglobin concentration Δ[HbT] (Δ[HbO2] + Δ[HHb]). However, of the 39 cases reporting Δ[HHb] in graphs or tables, only 24 studies explicitly discussed the response (i.e., direction of change) of this variable. In the studies where the fNIRS responses were discussed, 46/51 cases observed an increase in Δ[HbO2], 7/51 observed an increase or varied Δ[HHb], and 2/51 reported a varied or negative Δ[HbT]. An increase in Δ[HbO2] and decrease or no change in Δ[HHb] was observed in 15 studies. By reviewing this body of literature, we have identified that the majority of research articles reported an increase in Δ[HbO2] across various functional tasks and did not report the response of Δ[HHb]. Confirming the normal, healthy hemodynamic response in newborns will allow identification of unhealthy patterns and their association to normal neurodevelopment.

We describe the development of a miniaturized broadband near-infrared spectroscopy system (bNIRS), which measures changes in cerebral tissue oxyhemoglobin ( [ HbO 2 ] ) and deoxyhemoglobin ([HHb]) plus tissue metabolism via changes in the oxidation state of cytochrome-c-oxidase ([oxCCO]). The system is based on a small light source and a customized mini-spectrometer. We assessed the instrument in a preclinical study in 27 newborn piglets undergoing transient cerebral hypoxia-ischemia (HI). We aimed to quantify the recovery of the HI insult and estimate the severity of the injury. The recovery in brain oxygenation ( Δ [ HbDiff ] = Δ [ HbO 2 ] - Δ [ HHb ] ), blood volume ( Δ [ HbT ] = Δ [ HbO 2 ] + Δ [ HHb ] ), and metabolism ( Δ [ oxCCO ] ) for up to 30 min after the end of HI were quantified in percentages using the recovery fraction (RF) algorithm, which quantifies the recovery of a signal with respect to baseline. The receiver operating characteristic analysis was performed on bNIRS-RF measurements compared to proton ( H 1 ) magnetic resonance spectroscopic (MRS)-derived thalamic lactate/N-acetylaspartate (Lac/NAA) measured at 24-h post HI insult; Lac/NAA peak area ratio is an accurate surrogate marker of neurodevelopmental outcome in babies with neonatal HI encephalopathy. The Δ [ oxCCO ] -RF cut-off threshold of 79% within 30 min of HI predicted injury severity based on Lac/NAA with high sensitivity (100%) and specificity (93%). A significant difference in thalamic Lac/NAA was noticed ( p < 0.0001 ) between the two groups based on this cut-off threshold of 79% Δ [ oxCCO ] -RF. The severe injury group ( n = 13 ) had ∼ 30 % smaller recovery in Δ [ HbDiff ] -RF ( p = 0.0001 ) and no significant difference was observed in Δ [ HbT ] -RF between groups. At 48 h post HI, significantly higher P 31 -MRS-measured inorganic phosphate/exchangeable phosphate pool (epp) ( p = 0.01 ) and reduced phosphocreatine/epp ( p = 0.003 ) were observed in the severe injury group indicating persistent cerebral energy depletion. Based on these results, the bNIRS measurement of the oxCCO recovery fraction offers a noninvasive real-time biomarker of brain injury severity within 30 min following HI insult.

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.

Anterior prefrontal cortex (PFC, Brodmann area 10) activations are often, but not always, found in neuroimaging studies investigating deception, and the precise role of this area remains unclear. To explore the role of the PFC in face-to-face deception, we invited pairs of participants to play a card game involving lying and lie detection while we used functional near infrared spectroscopy (fNIRS) to record brain activity in the PFC. Participants could win points for successfully lying about the value of their cards or for detecting lies. We contrasted patterns of brain activation when the participants either told the truth or lied, when they were either forced into this or did so voluntarily and when they either succeeded or failed to detect a lie. Activation in the anterior PFC was found in both lie production and detection, unrelated to reward. Analysis of cross-brain activation patterns between participants identified areas of the PFC where the lead player's brain activity synchronized their partner's later brain activity. These results suggest that during situations that involve close interpersonal interaction, the anterior PFC supports processing widely involved in deception, possibly relating to the demands of monitoring one's own and other people's behaviour.

People with a depressed mood tend to perform poorly on executive function tasks, which require much of the prefrontal cortex (PFC), an area of the brain which has also been shown to be hypo-active in this population. Recent research has suggested that these aspects of cognition might be improved through physical activity and cognitive training. However, whether the acute effects of exercise on PFC activation during executive function tasks vary with depressive symptoms remains unclear. To investigate these effects, 106 participants were given a cardiopulmonary exercise test (CPET) and were administered a set of executive function tests directly before and after the CPET assessment. The composite effects of exercise on the PFC (all experimental blocks) showed bilateral activation changes in dorsolateral (BA46/9) and ventrolateral (BA44/45) PFC, with the greatest changes occurring in rostral PFC (BA10). The effects observed in right ventrolateral PFC varied depending on level of depressive symptoms (13% variance explained); the changes in activation were less for higher levels. There was also a positive relationship between CPET scores (VO2peak) and right rostral PFC, in that greater activation changes in right BA10 were predictive of higher levels of aerobic fitness (9% variance explained). Since acute exercise ipsilaterally affected this PFC subregion and the inferior frontal gyrus during executive function tasks, this suggests physical activity might benefit the executive functions these subregions support. And because physical fitness and depressive symptoms explained some degree of cerebral upregulation to these subregions, physical activity might more specifically facilitate the engagement of executive functions that are typically associated with hypoactivation in depressed populations. Future research might investigate this possibility in clinical populations, particularly the neural effects of physical activity used in combination with mental health interventions.

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.

We present and validate a multi-wavelength time-domain near-infrared spectroscopy (TD-NIRS) system that avoids switching wavelengths and instead exploits the full capability of a supercontinuum light source by emitting and acquiring signals for the whole chosen range of wavelengths. The system was designed for muscle and brain oxygenation monitoring in a clinical environment. A pulsed supercontinuum laser emits broadband light and each of two detection modules acquires the distributions of times of flight of photons (DTOFs) for 16 spectral channels (used width 12.5 nm / channel), providing a total of 32 DTOFs at up to 3 Hz. Two emitting fibers and two detection fiber bundles allow simultaneous measurements at two positions on the tissue or at two source-detector separations. Three established protocols (BIP, MEDPHOT, and nEUROPt) were used to quantitatively assess the system's performance, including linearity, coupling, accuracy, and depth sensitivity. Measurements were performed on 32 homogeneous phantoms and two inhomogeneous phantoms (solid and liquid). Furthermore, measurements on two blood-lipid phantoms with a varied amount of blood and Intralipid provide the strongest validation for accurate tissue oximetry. The retrieved hemoglobin concentrations and oxygen saturation match well with the reference values that were obtained using a commercially available NIRS system (OxiplexTS) and a blood gas analyzer (ABL90 FLEX), except a discrepancy occurs for the lowest amount of Intralipid. In-vivo measurements on the forearm of three healthy volunteers during arterial (250 mmHg) and venous (60 mmHg) cuff occlusions provide an example of tissue monitoring during the expected hemodynamic changes that follow previously well-described physiologies. All results, including quantitative parameters, can be compared to other systems that report similar tests. Overall, the presented TD-NIRS system has an exemplary performance evaluated with state-of-the-art performance assessment methods.

In this study, we used broadband near-infrared spectroscopy, a non-invasive optical technique, to investigate in real time the possible role of neuroglobin in retinal hemodynamics and metabolism.

Opportunities for adjunct therapies with cooling in neonatal encephalopathy are imminent; however, robust biomarkers of early assessment are lacking. Using an optical platform of broadband near-infrared spectroscopy and diffuse correlation spectroscopy to directly measure mitochondrial metabolism (oxCCO), oxygenation (HbD), cerebral blood flow (CBF), we hypothesised optical indices early (1-h post insult) after hypoxia-ischaemia (HI) predicts insult severity and outcome.

With the rapid growth of optical-based neuroimaging to explore human brain functioning, our research group has been developing broadband Near Infrared Spectroscopy (bNIRS) instruments, a technological extension to functional Near Infrared Spectroscopy (fNIRS). bNIRS has the unique capacity of monitoring brain haemodynamics/oxygenation (measuring oxygenated and deoxygenated haemoglobin), and metabolism (measuring the changes in the redox state of cytochrome-c-oxidase). When combined with electroencephalography (EEG), bNIRS provides a unique neuromonitoring platform to explore neurovascular coupling mechanisms. In this paper, we present a novel pipeline for the integrated analysis of bNIRS and EEG signals, and demonstrate its use on multi-channel bNIRS data recorded with concurrent EEG on healthy adults during a visual stimulation task. We introduce the use of the Finite Impulse Response functions within the General Linear Model for bNIRS and show its feasibility to statistically localize the haemodynamic and metabolic activity in the occipital cortex. Moreover, our results suggest that the fusion of haemodynamic and metabolic measures unveils additional information on brain functioning over haemodynamic imaging alone. The cross-correlation-based analysis of interrelationships between electrical (EEG) and haemodynamic/metabolic (bNIRS) activity revealed that the bNIRS metabolic signal offers a unique marker of brain activity, being more closely coupled to the neuronal EEG response.

Artefacts are a common and unwanted aspect of any measurement process, especially in a clinical environment, with multiple causes such as environmental changes or motion. In near-infrared spectroscopy (NIRS), there are several existing methods that can be used to identify and remove artefacts to improve the quality of collected data.We have developed a novel Automatic Broadband Artefact Detection (ABroAD) process, using machine learning methods alongside broadband NIRS data to detect common measurement artefacts using the broadband intensity spectrum. Data were collected from eight subjects, using a broadband NIRS monitoring over the frontal lobe with two sensors. Six different artificial artefacts - vertical head movement, horizontal head movement, frowning, pressure, ambient light, torch light - were simulated using movement and light changes on eight subjects in a block test design. It was possible to identify both light artefacts to a good degree, as well as pressure artefacts. This is promising and, by expanding this work to larger datasets, it may be possible to create and train a machine learning pipeline to automate the detection of various artefacts, making the analysis of collected data more reliable.

Perinatal hypoxic ischaemic encephalopathy (HIE) is associated with severe neurodevelopmental problems and mortality. There is a clinical need for techniques to provide cotside assessment of the injury extent. This study aims to use non-invasive cerebral broadband near-infrared spectroscopy (NIRS) in combination with systemic physiology to assess the severity of HIE injury. Broadband NIRS is used to measure the changes in haemodynamics, oxygenation and the oxidation state of cytochrome c oxidase (oxCCO). We used canonical correlation analysis (CCA), a multivariate statistical technique, to measure the relationship between cerebral broadband NIRS measurements and systemic physiology. A strong relationship between the metabolic marker, oxCCO, and systemic changes indicated severe brain injury; if more than 60 % of the oxCCO signal could be explained by the systemic variations, then the neurodevelopmental outcome was poor. This boundary has high sensitivity and specificity (100 and 83 %, respectively). Broadband NIRS measured concentration changes of the oxidation state of cytochrome c oxidase has the potential to become a useful cotside tool for assessment of injury severity following hypoxic ischaemic brain injury.

The retina has the greatest metabolic demand in the body particularly in dark adaptation when its sensitivity is enhanced. This requires elevated level of perfusion to sustain mitochondrial activity. However, mitochondrial performance declines with age leading to reduced adaptive ability. We assessed human retina metabolism in vivo using broad band near-infrared spectroscopy (bNIRS), which records colour changes in mitochondria and blood as retinal metabolism shifts in response to changes in environmental luminance. We demonstrate a significant sustained rise in mitochondrial oxidative metabolism in the first 3 min of darkness in subjects under 50 years old. This was not seen in those over 50 years. Choroidal oxygenation declines in < 50 s as mitochondrial metabolism increases, but gradually rises in the > 50 s. Significant group differences in blood oxygenation are apparent in the first 6 min, consistent with mitochondrial demand leading hemodynamic changes. A greater coupling between mitochondrial oxidative metabolism with hemodynamics is revealed in subjects older than 50, possibly due to reduced capacity in the older retina. Rapid in vivo assessment of retinal metabolism with bNIRS provides a route to understanding fundamental physiology and early identification of retinal disease before pathology is established.

Tissue oximetry with near-infrared spectroscopy (NIRS) is a technique for the measurement of absolute tissue oxygen saturation (StO2). Offering a real-time and non-invasive assessment of brain oxygenation and haemodynamics, StO2 has potential to be used for the assessment of newborn brain injury. Multiple algorithms have been developed to measure StO2, however, issues with low measurement accuracy or extracranial tissue signal contamination remain. In this work, we present a novel algorithm to recover StO2 in the neonate, broadband multidistance oximetry (BRUNO), based on a measurement of the gradient of attenuation against distance measured with broadband NIRS. The performance of the algorithm was compared to two other published algorithms, broadband fitting (BF) and spatially resolved spectroscopy (SRS). The median error when recovering StO2 in light transport simulations on a neonatal head mesh was 0.4% with BRUNO, 4.2% with BF and 9.5% with SRS. BRUNO was more sensitive to brain tissue oxygenation changes, shown in layered head model simulations. Comparison of algorithm performance during full oxygenation-deoxygenation cycles in a homogeneous dynamic blood phantom showed significant differences in the dynamic range of the algorithms; BRUNO recovered StO2 over 0-100%, BF over 0-90% and SRS over 39-80%. Recovering StO2 from data collected in a neonate treated at the neonatal intensive care showed different baseline values; mean StO2 was 64.9% with BRUNO, 67.2% with BF and 73.2% with SRS. These findings highlight the effect of StO2 algorithm selection on oxygenation recovery; applying BRUNO in the clinical care setting could reveal further insight into complex haemodynamic processes occurring during neonatal brain injury.

Multimodal monitoring of brain state is important both for the investigation of healthy cerebral physiology and to inform clinical decision making in conditions of injury and disease. Near-infrared spectroscopy is an instrument modality that allows non-invasive measurement of several physiological variables of clinical interest, notably haemoglobin oxygenation and the redox state of the metabolic enzyme cytochrome c oxidase. Interpreting such measurements requires the integration of multiple signals from different sources to try to understand the physiological states giving rise to them. We have previously published several computational models to assist with such interpretation. Like many models in the realm of Systems Biology, these are complex and dependent on many parameters that can be difficult or impossible to measure precisely. Taking one such model, BrainSignals, as a starting point, we have developed several variant models in which specific regions of complexity are substituted with much simpler linear approximations. We demonstrate that model behaviour can be maintained whilst achieving a significant reduction in complexity, provided that the linearity assumptions hold. The simplified models have been tested for applicability with simulated data and experimental data from healthy adults undergoing a hypercapnia challenge, but relevance to different physiological and pathophysiological conditions will require specific testing. In conditions where the simplified models are applicable, their greater efficiency has potential to allow their use at the bedside to help interpret clinical data in near real-time.

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.

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.