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The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The acquisition of multimodal magnetic resonance-based brain development data is central to the studys core protocol. However, application of Magnetic Resonance Imaging (MRI) methods in this population is complicated by technical challenges and difficulties of imaging in early life. Overcoming these challenges requires an innovative and harmonized approach, combining age-appropriate acquisition protocols together with specialized pediatric neuroimaging strategies. The HBCD MRI Working Group aimed to establish a core acquisition protocol for all 27 HBCD Study recruitment sites to measure brain structure, function, microstructure, and metabolites. Acquisition parameters of individual modalities have been matched across MRI scanner platforms for harmonized acquisitions and state-of-the-art technologies are employed to enable faster and motion-robust imaging. Here, we provide an overview of the HBCD MRI protocol, including decisions of individual modalities and preliminary data. The result will be an unparalleled resource for examining early neurodevelopment which enables the larger scientific community to assess normative trajectories from birth through childhood and to examine the genetic, biological, and environmental factors that help shape the developing brain.

Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Sensory deprivation theory is an important hypothesis involving potential pathways between hearing loss and cognitive impairment in patients with presbycusis. The theory suggests that prolonged auditory deprivation in presbycusis, including neural deafferentation, cortical reallocation, and atrophy, causes long‐lasting changes and reorganization in brain structure and function. However, neurophysiological changes underlying the cognition‐ear link have not been explored. In this study, we recruited 98 presbycusis patients and 60 healthy controls and examined the differences between the two groups in gamma‐aminobutyric acid (GABA) and glutamate (Glu) levels in bilateral auditory cortex, excitation–inhibition (E/I) balance (Glu/GABA ratio), dynamic functional network connectivity (dFNC), hearing ability and cognitive performance. Then, correlations with each other were investigated and variables with statistical significance were further analyzed using the PROCESS Macro in SPSS. GABA levels in right auditory cortex and Glu levels in bilateral auditory cortex were lower but E/I balance in right auditory cortex were higher in presbycusis patients compared to healthy controls. Hearing assessments and cognitive performance were worse in presbycusis patients. Three recurring connectivity states were identified after dFNC analysis: State 1 (least frequent, middle‐high dFNC strength with negative functional connectivity), State 2 (high dFNC strength), and State 3 (most frequent, low dFNC strength). The occurrence and dwell time of State 3 were higher, on the other hand, the dwell time of State 2 decreased in patients with presbycusis compared to healthy controls. In patients with presbycusis, worse hearing assessments and cognition were correlated with decreased GABA levels, increased E/I balance, and aberrant dFNC, decreased GABA levels and increased E/I balance were correlated with decreased occurrence and dwell time in State 3. In the mediation model, the fractional windows, as well as dwell time in State 3, mediated the relationship between the E/I balance in right auditory cortex and episodic memory (Auditory Verbal Learning Test, AVLT) in presbycusis. Moreover, in patients with presbycusis, we found that worse hearing loss contribute to lower GABA levels, higher E/I balance, and further impact aberrant dFNC, which caused lower AVLT scores. Overall, the results suggest that a shift in E/I balance in right auditory cortex plays an important role in cognition‐ear link reorganization and provide evidence for sensory deprivation theory, enhancing our understanding the connection between neurophysiological changes and cognitive impairment in presbycusis. In presbycusis patients, E/I balance may serve as a potential neuroimaging marker for exploring and predicting cognitive impairment. [ABSTRACT FROM AUTHOR]

Purpose: Retrospective frequency‐and‐phase correction (FPC) methods attempt to remove frequency‐and‐phase variations between transients to improve the quality of the averaged MR spectrum. However, traditional FPC methods like spectral registration struggle at low SNR. Here, we propose a method that directly integrates FPC into a 2D linear‐combination model (2D‐LCM) of individual transients ("model‐based FPC"). We investigated how model‐based FPC performs compared to the traditional approach, i.e., spectral registration followed by 1D‐LCM in estimating frequency‐and‐phase drifts and, consequentially, metabolite level estimates. Methods: We created synthetic in‐vivo‐like 64‐transient short‐TE sLASER datasets with 100 noise realizations at 5 SNR levels and added randomly sampled frequency and phase variations. We then used this synthetic dataset to compare the performance of 2D‐LCM with the traditional approach (spectral registration, averaging, then 1D‐LCM). Outcome measures were the frequency/phase/amplitude errors, the SD of those ground‐truth errors, and amplitude Cramér Rao lower bounds (CRLBs). We further tested the proposed method on publicly available in‐vivo short‐TE PRESS data. Results: 2D‐LCM estimates (and accounts for) frequency‐and‐phase variations directly from uncorrected data with equivalent or better fidelity than the conventional approach. Furthermore, 2D‐LCM metabolite amplitude estimates were at least as accurate, precise, and certain as the conventionally derived estimates. 2D‐LCM estimation of FPC and amplitudes performed substantially better at low‐to‐very‐low SNR. Conclusion: Model‐based FPC with 2D linear‐combination modeling is feasible and has great potential to improve metabolite level estimation for conventional and dynamic MRS data, especially for low‐SNR conditions, for example, long TEs or strong diffusion weighting. [ABSTRACT FROM AUTHOR]

Purpose: The J‐difference edited γ‐aminobutyric acid (GABA) signal is contaminated by other co‐edited signals—the largest of which originates from co‐edited macromolecules (MMs)—and is consequently often reported as "GABA+." MM signals are broader and less well‐characterized than the metabolites, and are commonly approximated using a Gaussian model parameterization. Experimentally measured MM signals are a consensus‐recommended alternative to parameterized modeling; however, they are relatively under‐studied in the context of edited MRS. Methods: To address this limitation in the literature, we have acquired GABA‐edited MEGA‐PRESS data with pre‐inversion to null metabolite signals in 13 healthy controls. An experimental MM basis function was derived from the mean across subjects. We further derived a new parameterization of the MM signals from the experimental data, using multiple Gaussians to accurately represent their observed asymmetry. The previous single‐Gaussian parameterization, mean experimental MM spectrum and new multi‐Gaussian parameterization were compared in a three‐way analysis of a public MEGA‐PRESS dataset of 61 healthy participants. Results: Both the experimental MMs and the multi‐Gaussian parameterization exhibited reduced fit residuals compared to the single‐Gaussian approach (p = 0.034 and p = 0.031, respectively), suggesting they better represent the underlying data than the single‐Gaussian parameterization. Furthermore, both experimentally derived models estimated larger MM fractional contribution to the GABA+ signal for the experimental MMs (58%) and multi‐Gaussian parameterization (58%), compared to the single‐Gaussian approach (50%). Conclusions: Our results indicate that single‐Gaussian parameterization of edited MM signals is insufficient and that both experimentally derived GABA+ spectra and their parameterized replicas improve the modeling of GABA+ spectra. [ABSTRACT FROM AUTHOR]

Purpose: To develop a 3D, high‐sensitivity CEST mapping technique based on the 3D stack‐of‐spirals (SOS) gradient echo readout, the proposed approach was compared with conventional acquisition techniques and evaluated for its efficacy in concurrently mapping of guanidino (Guan) and amide CEST in human brain at 3 T, leveraging the polynomial Lorentzian line‐shape fitting (PLOF) method. Methods: Saturation time and recovery delay were optimized to achieve maximum CEST time efficiency. The 3DSOS method was compared with segmented 3D EPI (3DEPI), turbo spin echo, and gradient‐ and spin‐echo techniques. Image quality, temporal SNR (tSNR), and test–retest reliability were assessed. Maps of Guan and amide CEST derived from 3DSOS were demonstrated on a low‐grade glioma patient. Results: The optimized recovery delay/saturation time was determined to be 1.4/2 s for Guan and amide CEST. In addition to nearly doubling the slice number, the gradient echo techniques also outperformed spin echo sequences in tSNR: 3DEPI (193.8 ± 6.6), 3DSOS (173.9 ± 5.6), and GRASE (141.0 ± 2.7). 3DSOS, compared with 3DEPI, demonstrated comparable GuanCEST signal in gray matter (GM) (3DSOS: [2.14%–2.59%] vs. 3DEPI: [2.15%–2.61%]), and white matter (WM) (3DSOS: [1.49%–2.11%] vs. 3DEPI: [1.64%–2.09%]). 3DSOS also achieves significantly higher amideCEST in both GM (3DSOS: [2.29%–3.00%] vs. 3DEPI: [2.06%–2.92%]) and WM (3DSOS: [2.23%–2.66%] vs. 3DEPI: [1.95%–2.57%]). 3DSOS outperforms 3DEPI in terms of scan–rescan reliability (correlation coefficient: 3DSOS: 0.58–0.96 vs. 3DEPI: −0.02 to 0.75) and robustness to motion as well. Conclusion: The 3DSOS CEST technique shows promise for whole‐cerebrum CEST imaging, offering uniform contrast and robustness against motion artifacts. [ABSTRACT FROM AUTHOR]

Cognitive flexibility represents the capacity to switch among different mental schemes, providing an adaptive advantage to a changing environment. The neural underpinnings of this executive function have been deeply studied in humans through fMRI, showing that the left inferior frontal cortex (IFC) and the left inferior parietal lobule (IPL) are crucial. Here, we investigated the inhibitory– excitatory balance in these regions by means of γ-aminobutyric acid (GABA+) and glutamate + glutamine (Glx), measured with magnetic resonance spectroscopy, during a cognitive flexibility task and its relationship with the performance level and the local task-induced blood oxygenation level-dependent (BOLD) response in 40 young (18–35 years; 26 female) and 40 older (18–35 years; 21 female) human adults. As the IFC and the IPL are richly connected regions, we also examined whole-brain effects associated with their local metabolic activity. Results did not show absolute metabolic modulations associated with flexibility performance, but the performance level was related to the direction of metabolic modulation in the IPL with opposite patterns in young and older individuals. The individual inhibitory–excitatory balance modulation showed an inverse relationship with the local BOLD response in the IPL. Finally, the modulation of inhibitory–excitatory balance in IPL was related to whole-brain effects only in older individuals. These findings show disparities in the metabolic mechanisms underlying cognitive flexibility in young and older adults and their association with the performance level and BOLD response. Such metabolic differences are likely to play a role in executive functioning during aging and specifically in cognitive flexibility. [ABSTRACT FROM AUTHOR]

Relaxation correction is an integral step in quantifying brain metabolite concentrations measured by in vivo magnetic resonance spectroscopy (MRS). While most quantification routines assume constant T1 relaxation across age, it is possible that aging alters T1 relaxation rates, as is seen for T2 relaxation. Here, we investigate the age dependence of metabolite T1 relaxation times at 3 T in both gray‐ and white‐matter‐rich voxels using publicly available metabolite and metabolite‐nulled (single inversion recovery TI = 600 ms) spectra acquired at 3 T using Point RESolved Spectroscopy (PRESS) localization. Data were acquired from voxels in the posterior cingulate cortex (PCC) and centrum semiovale (CSO) in 102 healthy volunteers across 5 decades of life (aged 20–69 years). All spectra were analyzed in Osprey v.2.4.0. To estimate T1 relaxation times for total N‐acetyl aspartate at 2.0 ppm (tNAA2.0) and total creatine at 3.0 ppm (tCr3.0), the ratio of modeled metabolite residual amplitudes in the metabolite‐nulled spectrum to the full metabolite signal was calculated using the single‐inversion‐recovery signal equation. Correlations between T1 and subject age were evaluated. Spearman correlations revealed that estimated T1 relaxation times of tNAA2.0 (rs = −0.27; p < 0.006) and tCr3.0 (rs = −0.40; p < 0.001) decreased significantly with age in white‐matter‐rich CSO, and less steeply for tNAA2.0 (rs = −0.228; p = 0.005) and (not significantly for) tCr3.0 (rs = −0.13; p = 0.196) in graymatter‐rich PCC. The analysis harnessed a large publicly available cross‐sectional dataset to test an important hypothesis, that metabolite T1 relaxation times change with age. This preliminary study stresses the importance of further work to measure age‐normed metabolite T1 relaxation times for accurate quantification of metabolite levels in studies of aging. [ABSTRACT FROM AUTHOR]

Background: The neurobiological underpinnings of Autism Spectrum Disorder (ASD) are diverse and likely multifactorial. One possible mechanism is increased oxidative stress leading to altered neurodevelopment and brain function. However, this hypothesis has mostly been tested in post-mortem studies. So far, available in vivo studies in autistic individuals have reported no differences in glutathione (GSH) levels in frontal, occipital, and subcortical regions. However, these studies were limited by the technically challenging quantification of GSH, the main brain antioxidant molecule. This study aimed to overcome previous studies' limitations by using a GSH-tailored spectroscopy sequence and optimised quantification methodology to provide clarity on GSH levels in autistic adults. Methods: We used spectral editing proton-magnetic resonance spectroscopy (1H-MRS) combined with linear combination model fitting to quantify GSH in the dorsomedial prefrontal cortex (DMPFC) and medial occipital cortex (mOCC) of autistic and non-autistic adults (male and female). We compared GSH levels between groups. We also examined correlations between GSH and current autism symptoms, measured using the Autism Quotient (AQ). Results: Data were available from 31 adult autistic participants (24 males, 7 females) and 40 non-autistic participants (21 males, 16 females); the largest sample to date. The GSH levels did not differ between groups in either region. No correlations with AQ were observed. Conclusion: GSH levels as measured using 1H-MRS are unaltered in the DMPFC and mOCC regions of autistic adults, suggesting that oxidative stress in these cortical regions is not a marked neurobiological signature of ASD. [ABSTRACT FROM AUTHOR]

Alterations in the structure, function, and microcirculation of the thalamus, a key brain region involved in pain pathways, have previously been demonstrated in patients with painless and painful diabetic peripheral neuropathy (DPN). However, thalamic neurotransmitter levels including γ-aminobutyric acid (GABA) (inhibitory neurotransmitter) and glutamate (excitatory neurotransmitter) in different DPN phenotypes are not known. We performed a magnetic resonance spectroscopy study and quantified GABA and glutamate levels within the thalamus, in a carefully characterized cohort of participants with painless and painful DPN. Participants with DPN (painful and painless combined) had a significantly lower GABA:H2O ratio compared with those without DPN (healthy volunteers [HV] and participants with diabetes without DPN [no DPN]). Participants with painless DPN had the lowest GABA:H2O ratio, which reached significance compared with HV and no DPN, but not painful DPN. There was no difference in GABA:H2O in painful DPN compared with all other groups. A significant correlation with GABA:H2O and neuropathy severity was also seen. This study demonstrates that lower levels of thalamic GABA in participants with painless DPN may reflect neuroplasticity due to reduced afferent pain impulses, whereas partially preserved levels of GABA in painful DPN may indicate that central GABAergic pathways are involved in the mechanisms of neuropathic pain in diabetes. Article Highlights: The thalamus has been shown to play a key role in the cerebral mechanisms of diabetic peripheral neuropathy (DPN), but neurotransmitter levels have not been explored. We sought to determine the levels of excitatory (glutamate) and inhibitory (γ-aminobutyric acid [GABA]) neurotransmitter levels in the thalamus in participants with painful and painless DPN. Thalamic GABA levels were reduced in participants with painless DPN, with partially preserved levels seen in painful DPN. Alterations of thalamic GABAergic pathways could be involved in the central mechanisms of both painful and painless DPN. [ABSTRACT FROM AUTHOR]