Measuring acute effects of subanesthetic ketamine on cerebrovascular hemodynamics in humans using TD-fNIRS.

Quantifying neural activity in natural conditions (i.e. conditions comparable to the standard clinical patient experience) during the administration of psychedelics may further our scientific understanding of the effects and mechanisms of action. This data may facilitate the discovery of novel biomarkers enabling more personalized treatments and improved patient outcomes. In this single-blind, placebo-controlled study with a non-randomized design, we use time-domain functional near-infrared spectroscopy (TD-fNIRS) to measure acute brain dynamics after intramuscular subanesthetic ketamine (0.75 mg/kg) and placebo (saline) administration in healthy participants (n = 15, 8 females, 7 males, age 32.4 ± 7.5 years) in a clinical setting. We found that the ketamine administration caused an altered state of consciousness and changes in systemic physiology (e.g. increase in pulse rate and electrodermal activity). Furthermore, ketamine led to a brain-wide reduction in the fractional amplitude of low frequency fluctuations, and a decrease in the global brain connectivity of the prefrontal region. Lastly, we provide preliminary evidence that a combination of neural and physiological metrics may serve as predictors of subjective mystical experiences and reductions in depressive symptomatology. Overall, our study demonstrated the successful application of fNIRS neuroimaging to study the physiological effects of the psychoactive substance ketamine in humans, and can be regarded as an important step toward larger scale clinical fNIRS studies that can quantify the impact of psychedelics on the brain in standard clinical settings.

Erratum: Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models: errata.

[This corrects the article on p. 1131 in vol. 13, PMID: 35414976.].

Change in brain asymmetry reflects level of acute alcohol intoxication and impacts on inhibitory control.

Alcohol is one of the most commonly used substances and frequently abused, yet little is known about the neural underpinnings driving variability in inhibitory control performance after ingesting alcohol. This study was a single-blind, placebo-controlled, randomized design with participants (N = 48 healthy, social drinkers) completing three study visits. At each visit participants received one of three alcohol doses; namely, a placebo dose [equivalent Blood Alcohol Concentration (BAC) = 0.00%], a low dose of alcohol (target BAC = 0.04%), or a moderate dose of alcohol (target BAC = 0.08%). To measure inhibitory control, participants completed a Go/No-go task paradigm twice during each study visit, once immediately before dosing and once after, while their brain activity was measured with time-domain functional near-infrared spectroscopy (TD-fNIRS). BAC and subjective effects of alcohol were also assessed. We report decreased behavioral performance for the moderate dose of alcohol, but not the low or placebo doses. We observed right lateralized inhibitory prefrontal activity during go-no-go blocks, consistent with prior literature. Using standard and novel metrics of lateralization, we were able to significantly differentiate between all doses. Lastly, we demonstrate that these metrics are not only related to behavioral performance during inhibitory control, but also provide complementary information to the legal gold standard of intoxication (i.e. BAC).

Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models.

We characterize cerebral sensitivity across the entire adult human head for diffuse correlation spectroscopy, an optical technique increasingly used for bedside cerebral perfusion monitoring. Sixteen subject-specific magnetic resonance imaging-derived head models were used to identify high sensitivity regions by running Monte Carlo light propagation simulations at over eight hundred uniformly distributed locations on the head. Significant spatial variations in cerebral sensitivity, consistent across subjects, were found. We also identified correlates of such differences suitable for real-time assessment. These variations can be largely attributed to changes in extracerebral thickness and should be taken into account to optimize probe placement in experimental settings.

Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system.

SIGNIFICANCE: Time-domain functional near-infrared spectroscopy (TD-fNIRS) has been considered as the gold standard of noninvasive optical brain imaging devices. However, due to the high cost, complexity, and large form factor, it has not been as widely adopted as continuous wave NIRS systems. AIM: Kernel Flow is a TD-fNIRS system that has been designed to break through these limitations by maintaining the performance of a research grade TD-fNIRS system while integrating all of the components into a small modular device. APPROACH: The Kernel Flow modules are built around miniaturized laser drivers, custom integrated circuits, and specialized detectors. The modules can be assembled into a system with dense channel coverage over the entire head. RESULTS: We show performance similar to benchtop systems with our miniaturized device as characterized by standardized tissue and optical phantom protocols for TD-fNIRS and human neuroscience results. CONCLUSIONS: The miniaturized design of the Kernel Flow system allows for broader applications of TD-fNIRS.

Exploring the relation between brain response to speech at 6-months and language outcomes at 24-months in infants at high and low risk for autism spectrum disorder: A preliminary functional near-infrared spectroscopy study.

Infants at high familial risk for autism spectrum disorder (ASD) are at increased risk for language impairments. Studies have demonstrated that atypical brain response to speech is related to language impairments in this population, but few have examined this relation longitudinally. We used functional near-infrared spectroscopy (fNIRS) to investigate the neural correlates of speech processing in 6-month-old infants at high (HRA) and low risk (LRA) for autism. We also assessed the relation between brain response to speech at 6-months and verbal developmental quotient (VDQ) scores at 24-months. LRA infants exhibited greater brain response to speech in bilateral anterior regions of interest (ROIs) compared to posterior ROIs, while HRA infants exhibited similar brain response across all ROIs. Compared to LRA infants, HRA+ infants who were later diagnosed with ASD had reduced brain response in bilateral anterior ROIs, while HRA- infants who were not later diagnosed with ASD had increased brain response in right posterior ROI. Greater brain response in left anterior ROI predicted VDQ scores for LRA infants only. Findings highlight the importance of studying HRA+ and HRA- infants separately, and implicate a different, more distributed neural system for speech processing in HRA infants that is not related to language functioning.

Neural responses to happy, fearful and angry faces of varying identities in 5- and 7-month-old infants.

The processing of facial emotion is an important social skill that develops throughout infancy and early childhood. Here we investigate the neural underpinnings of the ability to process facial emotion across changes in facial identity in cross-sectional groups of 5- and 7-month-old infants. We simultaneously measured neural metabolic, behavioral, and autonomic responses to happy, fearful, and angry faces of different female models using functional near-infrared spectroscopy (fNIRS), eye-tracking, and heart rate measures. We observed significant neural activation to these facial emotions in a distributed set of frontal and temporal brain regions, and longer looking to the mouth region of angry faces compared to happy and fearful faces. No differences in looking behavior or neural activations were observed between 5- and 7-month-olds, although several exploratory, age-independent associations between neural activations and looking behavior were noted. Overall, these findings suggest more developmental stability than previously thought in responses to emotional facial expressions of varying identities between 5- and 7-months of age.

The influence of maternal anxiety and depression symptoms on fNIRS brain responses to emotional faces in 5- and 7-month-old infants.

Greater relative right (versus left) frontal cortical activation to emotional faces as measured with alpha power in the electroencephalogram (EEG), has been considered a promising neural marker of increased vulnerability to psychopathology and emotional disorders. We set out to explore multichannel fNIRS as a tool to investigate infants' frontal asymmetry responses (hypothesizing greater right versus left frontal cortex activation) to emotional faces as influenced by maternal anxiety and depression symptoms during the postnatal period. We also explored activation differences in fronto-temporal regions associated with facial emotion processing. Ninety-one typically developing 5- and 7-month-old infants were shown photographs of women portraying happy, fearful and angry expressions. Hemodynamic brain responses were analyzed over two frontopolar and seven bilateral cortical regions subdivided into frontal, temporal and parietal areas, defined by age-appropriate MRI templates. Infants of mothers reporting higher negative affect had greater oxyhemoglobin (oxyHb) activation across all emotions over the left inferior frontal gyrus, a region implicated in emotional communication. Follow-up analyses indicated that associations were driven by maternal depression, but not anxiety symptoms. Overall, we found no support for greater right versus left frontal cortex activation in association with maternal negative affect. Findings point to the potential utility of fNIRS as a method for identifying altered neural substrates associated with exposure to maternal depression in infancy.

Infant brain responses to live face-to-face interaction with their mothers: Combining functional near-infrared spectroscopy (fNIRS) with a modified still-face paradigm.

BACKGROUND: Non-invasive imaging techniques, such as fNIRS, allow us to shed light on the neural correlates of infant's social-emotional development within the context of parent-infant interaction. On a behavioral level, numerous studies have investigated parent-infant interaction employing the still-face paradigm and found that the primary caregiver(s), often the mother, is an important coregulator of the infant's physiological and behavioral stress response. However, limited information is available on how the infant's brain reacts to the maternal cues during real-life interaction. METHODS: Therefore, the main aim of the current study was to design a fNIRS paradigm to study live mother-infant interaction and to explore the neural correlates of infant affect regulation during real-life dyadic interaction. To this end, a modified still-face paradigm was designed, which consists of live face-to-face mother-infant, and stranger-infant, interaction episodes, including stressful, "still-face" and non-stressful, "happy-face" interaction blocks, combined with infant fNIRS imaging. RESULTS: Hemodynamic brain responses were collected in n = 10 (6 females, mean age 230.2 ±â€¯17.5 days), typically developing infants using the Hitachi ETG-4000 continuous-wave system (22 channels spanning the frontal cortex; 10 Hz system sampling frequency). Infants with usable data (n = 7) showed negative activations, indicated by a decrease in oxygenated hemoglobin, over the middle frontal gyrus in response to happy-face (reunion) interaction with their mothers compared to a female stranger; suggesting deactivation of brain regions associated with affect regulation. We also explored correlations between infant brain responses to maternal interaction and infant characteristics (temperament) as well as experiential/environmental factors (mothers' self-reported depression symptoms). CONCLUSIONS: Although the current results are very preliminary, they overall suggest that live design in infant populations is doable and offers unique opportunities to study the neural mechanisms underlying early caregiver(s)-child interaction in a more naturalistic context. Restrictions, and implications, of the methodology are critically discussed.

Using functional near-infrared spectroscopy to assess social information processing in poor urban Bangladeshi infants and toddlers.

Children living in low-resource settings are at risk for failing to reach their developmental potential. While the behavioral outcomes of growing up in such settings are well-known, the neural mechanisms underpinning poor outcomes have not been well elucidated, particularly in the context of low- and middle-income countries. In this study, we measure brain metabolic responses to social and nonsocial stimuli in a cohort of 6- and 36-month-old Bangladeshi children. Study participants in both cohorts lived in an urban slum and were exposed to a broad range of adversity early in life including extreme poverty, malnutrition, recurrent infections, and low maternal education. We observed brain regions that responded selectively to social stimuli in both ages indicating that these specialized brain responses are online from an early age. We additionally show that the magnitude of the socially selective response is related to maternal education, maternal stress, and the caregiving environment. Ultimately our results suggest that a variety of psychosocial hazards have a measurable relationship with the developing social brain.

Infant brain responses to social sounds: A longitudinal functional near-infrared spectroscopy study.

Infants are responsive to and show a preference for human vocalizations from very early in development. While previous studies have provided a strong foundation of understanding regarding areas of the infant brain that respond preferentially to social vs. non-social sounds, how the infant brain responds to sounds of varying social significance over time, and how this relates to behavior, is less well understood. The current study uniquely examined longitudinal brain responses to social sounds of differing social-communicative value in infants at 3 and 6 months of age using functional near-infrared spectroscopy (fNIRS). At 3 months, infants showed similar patterns of widespread activation in bilateral temporal cortices to communicative and non-communicative human non-speech vocalizations, while by 6 months infants showed more similar, and focal, responses to social sounds that carried increased social value (infant-directed speech and human non-speech communicative sounds). In addition, we found that brain activity at 3 months of age related to later brain activity and receptive language abilities as measured at 6 months. These findings suggest areas of consistency and change in auditory social perception between 3 and 6 months of age.

Motion correction for infant functional near-infrared spectroscopy with an application to live interaction data.

Correcting for motion is an important consideration in infant functional near-infrared spectroscopy studies. We tested the performance of conventional motion correction methods and compared probe motion and data quality metrics for data collected at different infant ages (5, 7, and 12 months) and during different methods of stimulus presentation (video versus live). While 5-month-olds had slower maximum head speed than 7- or 12-month-olds, data quality metrics and hemodynamic response recovery errors were similar across ages. Data quality was also similar between video and live stimulus presentation. Motion correction algorithms, such as wavelet filtering and targeted principal component analysis, performed well for infant data using infant-specific parameters, and parameters may be used without fine-tuning for infant age or method of stimulus presentation. We recommend using wavelet filtering with [Formula: see text]; however, a range of parameters seemed acceptable. We do not recommend using trial rejection alone, because it did not improve hemodynamic response recovery as compared to no correction at all. Data quality metrics calculated from uncorrected data were associated with hemodynamic response recovery error, indicating that full simulation studies may not be necessary to assess motion correction performance.

The infant brain in the social world: Moving toward interactive social neuroscience with functional near-infrared spectroscopy.

Typically developing infants rapidly acquire a sophisticated array of social skills within the first year of life. These social skills are largely learned within the context of day-to-day interactions with caregivers. While social neuroscience has made great gains in our knowledge of the underlying neural circuitry of social cognition and behavior, much of this work has focused on experiments that sacrifice ecological validity for experimental control. Functional near-infrared spectroscopy (fNIRS) is a promising methodology for measuring brain activity in the context of naturalistic social interactions. Here, we review what we have learned from fNIRS studies that have used traditional experimental stimuli to study social development during infancy. We then discuss recent infant fNIRS studies that have utilized more naturalistic social stimuli, followed by a discussion of applications of this methodology to the study of atypical social development, with a focus on infants at risk for autism spectrum disorder. We end with recommendations for applying fNIRS to studies of typically developing and at-risk infants in naturalistic social situations.

Differing Developmental Trajectories in Heart Rate Responses to Speech Stimuli in Infants at High and Low Risk for Autism Spectrum Disorder.

We investigated heart rate (HR) in infants at 3, 6, 9, and 12 months of age, at high (HRA) and low (LRC) familial risk for ASD, to identify potential endophenotypes of ASD risk related to attentional responses. HR was extracted from functional near-infrared spectroscopy recordings while infants listened to speech stimuli. Longitudinal analysis revealed that HRA infants and males generally had lower baseline HR than LRC infants and females. HRA infants showed decreased HR responses to early trials over development, while LRC infants showed increased responses. These findings suggest altered developmental trajectories in physiological responses to speech stimuli over the first year of life, with HRA infants showing less social orienting over time.

Infants' neural responses to facial emotion in the prefrontal cortex are correlated with temperament: a functional near-infrared spectroscopy study.

Accurate decoding of facial expressions is critical for human communication, particularly during infancy, before formal language has developed. Different facial emotions elicit distinct neural responses within the first months of life. However, there are broad individual differences in such responses, so that the same emotional expression can elicit different brain responses in different infants. In this study, we sought to investigate such differences in the processing of emotional faces by analyzing infants's cortical metabolic responses to face stimuli and examining whether individual differences in these responses might vary as a function of infant temperament. Seven-month-old infants (N = 24) were shown photographs of women portraying happy expressions, and neural activity was recorded using functional near-infrared spectroscopy (fNIRS). Temperament data were collected using the Revised Infant Behavior Questionnaire Short Form, which assesses the broad temperament factors of Surgency/Extraversion (S/E), Negative Emotionality (NE), and Orienting/Regulation (O/R). We observed that oxyhemoglobin (oxyHb) responses to happy face stimuli were negatively correlated with infant temperament factors in channels over the left prefrontal cortex (uncorrected for multiple comparisons). To investigate the brain activity underlying this association, and to explore the use of fNIRS in measuring cortical asymmetry, we analyzed hemispheric asymmetry with respect to temperament groups. Results showed preferential activation of the left hemisphere in low-NE infants in response to smiling faces. These results suggest that individual differences in temperament are associated with differential prefrontal oxyHb responses to faces. Overall, these analyses contribute to our current understanding of face processing during infancy, demonstrate the use of fNIRS in measuring prefrontal asymmetry, and illuminate the neural correlates of face processing as modulated by temperament.

Extraction of heart rate from functional near-infrared spectroscopy in infants.

Changes in heart rate are a useful physiological measure in infant studies. We present an algorithm for calculating the heart rate (HR) from oxyhemoglobin pulsation in functional near-infrared spectroscopy (fNIRS) signals. The algorithm is applied to data collected from 10 infants, and the HR derived from the fNIRS signals is compared against the HR as calculated by electrocardiography. We show high agreement between the two HR signals for all infants (r > 0.90), and also compare stimulus-related HR responses as measured by the two methods and find good agreement despite high levels of movement in the infants. This algorithm can be used to measure changes in HR in infants participating in fNIRS studies without the need for additional HR sensors.

Algorithm to find high density EEG scalp coordinates and analysis of their correspondence to structural and functional regions of the brain.

BACKGROUND: Interpretation and analysis of electroencephalography (EEG) measurements relies on the correspondence of electrode scalp coordinates to structural and functional regions of the brain. NEW METHOD: An algorithm is introduced for automatic calculation of the International 10-20, 10-10, and 10-5 scalp coordinates of EEG electrodes on a boundary element mesh of a human head. The EEG electrode positions are then used to generate parcellation regions of the cerebral cortex based on proximity to the EEG electrodes. RESULTS: The scalp electrode calculation method presented in this study effectively and efficiently identifies EEG locations without prior digitization of coordinates. The average of electrode proximity parcellations of the cortex were tabulated with respect to structural and functional regions of the brain in a population of 20 adult subjects. COMPARISON WITH EXISTING METHODS: Parcellations based on electrode proximity and EEG sensitivity were compared. The parcellation regions based on sensitivity and proximity were found to have 44.0 ± 11.3% agreement when demarcated by the International 10-20, 32.4 ± 12.6% by the 10-10, and 24.7 ± 16.3% by the 10-5 electrode positioning system. CONCLUSIONS: The EEG positioning algorithm is a fast and easy method of locating EEG scalp coordinates without the need for digitized electrode positions. The parcellation method presented summarizes the EEG scalp locations with respect to brain regions without computation of a full EEG forward model solution. The reference table of electrode proximity versus cortical regions may be used by experimenters to select electrodes that correspond to anatomical and functional regions of interest.

T1 magnetic resonance imaging head segmentation for diffuse optical tomography and electroencephalography.

Accurate segmentation of structural magnetic resonance images is critical for creating subject-specific forward models for functional neuroimaging source localization. In this work, we present an innovative segmentation algorithm that generates accurate head tissue layer thicknesses that are needed for diffuse optical tomography (DOT) data analysis. The presented algorithm is compared against other publicly available head segmentation methods. The proposed algorithm has a root mean square scalp thickness error of 1.60 mm, skull thickness error of 1.96 mm, and summed scalp and skull error of 1.49 mm. We also introduce a segmentation evaluation metric that evaluates the accuracy of tissue layer thicknesses in regions of the head where optodes are typically placed. The presented segmentation algorithm and evaluation metric are tools for improving the localization accuracy of neuroimaging with DOT, and also multimodal neuroimaging such as combined electroencephalography and DOT.

A graphical user interface for infant ERP analysis.

Recording of event-related potentials (ERPs) is one of the best-suited technologies for examining brain function in human infants. Yet the existing software packages are not optimized for the unique requirements of analyzing artifact-prone ERP data from infants. We developed a new graphical user interface that enables an efficient implementation of a two-stage approach to the analysis of infant ERPs. In the first stage, video records of infant behavior are synchronized with ERPs at the level of individual trials to reject epochs with noncompliant behavior and other artifacts. In the second stage, the interface calls MATLAB and EEGLAB (Delorme & Makeig, Journal of Neuroscience Methods 134(1):9-21, 2004) functions for further preprocessing of the ERP signal itself (i.e., filtering, artifact removal, interpolation, and rereferencing). Finally, methods are included for data visualization and analysis by using bootstrapped group averages. Analyses of simulated and real EEG data demonstrated that the proposed approach can be effectively used to establish task compliance, remove various types of artifacts, and perform representative visualizations and statistical comparisons of ERPs. The interface is available for download from http://www.uta.fi/med/icl/methods/eeg.html in a format that is widely applicable to ERP studies with special populations and open for further editing by users.

Effects of spatial pattern scale of brain activity on the sensitivity of DOT, fMRI, EEG and MEG.

The objective of this work is to quantify how patterns of cortical activity at different spatial scales are measured by noninvasive functional neuroimaging sensors. We simulated cortical activation patterns at nine different spatial scales in a realistic head model and propagated this activity to magnetoencephalography (MEG), electroencephalography (EEG), diffuse optical tomography (DOT), and functional magnetic resonance imaging (fMRI) sensors in arrangements that are typically used in functional neuroimaging studies. We estimated contrast transfer functions (CTF), correlation distances in sensor space, and the minimum resolvable spatial scale of cortical activity for each modality. We found that CTF decreases as the spatial extent of cortical activity decreases, and that correlations between nearby sensors depend on the spatial extent of cortical activity. For cortical activity on the intermediate spatial scale of 6.7 cm(2), the correlation distances (r>0.5) were 1.0 cm for fMRI, 2.0 cm for DOT, 12.8 for EEG, 9.5 cm for MEG magnetometers and 9.7 cm for MEG gradiometers. The resolvable spatial pattern scale was found to be 1.43 cm(2) for MEG magnetometers, 0.88 cm(2) for MEG gradiometers, 376 cm(2) for EEG, 0.75 cm(2) for DOT, and 0.072 cm(2) for fMRI. These findings show that sensitivity to cortical activity varies substantially as a function of spatial scale within and between the different imaging modalities. This information should be taken into account when interpreting neuroimaging data and when choosing the number of nodes for network analyses in sensor space.