Neuromodulatory Control of Long-Term Behavioral Patterns and Individuality across Development.

Animals generate complex patterns of behavior across development that may be shared or unique to individuals. Here, we examine the contributions of developmental programs and individual variation to behavior by monitoring single Caenorhabditis elegans nematodes over their complete developmental trajectories and quantifying their behavior at high spatiotemporal resolution. These measurements reveal reproducible trajectories of spontaneous foraging behaviors that are stereotyped within and between developmental stages. Dopamine, serotonin, the neuropeptide receptor NPR-1, and the TGF-ß peptide DAF-7 each have stage-specific effects on behavioral trajectories, implying the existence of a modular temporal program controlled by neuromodulators. In addition, a fraction of individuals within isogenic populations raised in controlled environments have consistent, non-genetic behavioral biases that persist across development. Several neuromodulatory systems increase or decrease the degree of non-genetic individuality to shape sustained patterns of behavior across the population.

Interference suppression techniques for OPM-based MEG: Opportunities and challenges.

One of the primary technical challenges facing magnetoencephalography (MEG) is that the magnitude of neuromagnetic fields is several orders of magnitude lower than interfering signals. Recently, a new type of sensor has been developed - the optically pumped magnetometer (OPM). These sensors can be placed directly on the scalp and move with the head during participant movement, making them wearable. This opens up a range of exciting experimental and clinical opportunities for OPM-based MEG experiments, including paediatric studies, and the incorporation of naturalistic movements into neuroimaging paradigms. However, OPMs face some unique challenges in terms of interference suppression, especially in situations involving mobile participants, and when OPMs are integrated with electrical equipment required for naturalistic paradigms, such as motion capture systems. Here we briefly review various hardware solutions for OPM interference suppression. We then outline several signal processing strategies aimed at increasing the signal from neuromagnetic sources. These include regression-based strategies, temporal filtering and spatial filtering approaches. The focus is on the practical application of these signal processing algorithms to OPM data. In a similar vein, we include two worked-through experiments using OPM data collected from a whole-head sensor array. These tutorial-style examples illustrate how the steps for suppressing external interference can be implemented, including the associated data and code so that researchers can try the pipelines for themselves. With the popularity of OPM-based MEG rising, there will be an increasing need to deal with interference suppression. We hope this practical paper provides a resource for OPM-based MEG researchers to build upon.

MESMERISED: Super-accelerating T1 relaxometry and diffusion MRI with STEAM at 7 T for quantitative multi-contrast and diffusion imaging.

There is an increasing interest in quantitative imaging of T1, T2 and diffusion contrast in the brain due to greater robustness against bias fields and artifacts, as well as better biophysical interpretability in terms of microstructure. However, acquisition time constraints are a challenge, particularly when multiple quantitative contrasts are desired and when extensive sampling of diffusion directions, high b-values or long diffusion times are needed for multi-compartment microstructure modeling. Although ultra-high fields of 7 T and above have desirable properties for many MR modalities, the shortening T2 and the high specific absorption rate (SAR) of inversion and refocusing pulses bring great challenges to quantitative T1, T2 and diffusion imaging. Here, we present the MESMERISED sequence (Multiplexed Echo Shifted Multiband Excited and Recalled Imaging of STEAM Encoded Diffusion). MESMERISED removes the dead time in Stimulated Echo Acquisition Mode (STEAM) imaging by an echo-shifting mechanism. The echo-shift (ES) factor is independent of multiband (MB) acceleration and allows for very high multiplicative (ESxMB) acceleration factors, particularly under moderate and long mixing times. This results in super-acceleration and high time efficiency at 7 T for quantitative T1 and diffusion imaging, while also retaining the capacity to perform quantitative T2 and B1 mapping. We demonstrate the super-acceleration of MESMERISED for whole-brain T1 relaxometry with total acceleration factors up to 36 at 1.8 mm isotropic resolution, and up to 54 at 1.25 mm resolution qT1 imaging, corresponding to a 6x and 9x speedup, respectively, compared to MB-only accelerated acquisitions. We then demonstrate highly efficient diffusion MRI with high b-values and long diffusion times in two separate cases. First, we show that super-accelerated multi-shell diffusion acquisitions with 370 whole-brain diffusion volumes over 8 b-value shells up to b = 7000 s/mm2 can be generated at 2 mm isotropic in under 8 minutes, a data rate of almost a volume per second, or at 1.8 mm isotropic in under 11 minutes, achieving up to 3.4x speedup compared to MB-only. A comparison of b = 7000 s/mm2 MESMERISED against standard MB pulsed gradient spin echo (PGSE) diffusion imaging shows 70% higher SNR efficiency and greater effectiveness in supporting complex diffusion signal modeling. Second, we demonstrate time-efficient sampling of different diffusion times with 1.8 mm isotropic diffusion data acquired at four diffusion times up to 290 ms, which supports both Diffusion Tensor Imaging (DTI) and Diffusion Kurtosis Imaging (DKI) at each diffusion time. Finally, we demonstrate how adding quantitative T2 and B1+ mapping to super-accelerated qT1 and diffusion imaging enables efficient quantitative multi-contrast mapping with the same MESMERISED sequence and the same readout train. MESMERISED extends possibilities to efficiently probe T1, T2 and diffusion contrast for multi-component modeling of tissue microstructure.

PriMa: A low-cost, modular, open hardware, and 3D-printed fMRI manipulandum.

Motor actions in fMRI settings require specialized hardware to monitor, record, and control the subjects behavior. Commercially available options for such behavior tracking or control are very restricted and costly. We present a novel grasp manipulandum in a modular design, consisting of MRI-compatible, 3D printable buttons and a chassis for mounting. Button presses are detected by the interruption of an optical fiber path, which is digitized by a photodiode and subsequent signal amplification and thresholding. Two feedback devices (manipulanda) are constructed, one for macaques (Macaca mulatta) and one for human use. Both devices have been tested in their specific experimental setting and possible improvements are reported. Design files are shared under an open hardware license.

Bloch modelling enables robust T2 mapping using retrospective proton density and T2-weighted images from different vendors and sites.

T2 quantification is commonly attempted by applying an exponential fit to proton density (PD) and transverse relaxation (T2)-weighted fast spin echo (FSE) images. However, inter-site studies have noted systematic differences between vendors in T2 maps computed via standard exponential fitting due to imperfect slice refocusing, different refocusing angles and transmit field (B1+) inhomogeneity. We examine T2 mapping at 3T across 13 sites and two vendors in healthy volunteers from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using both a standard exponential and a Bloch modelling approach. The standard exponential approach resulted in highly variable T2 values across different sites and vendors. The two-echo fitting method based on Bloch equation modelling of the pulse sequence with prior knowledge of the nominal refocusing angles, slice profiles, and estimated B1+ maps yielded similar T2 values across sites and vendors by accounting for the effects of indirect and stimulated echoes. By modelling the actual refocusing angles used, T2 quantification from PD and T2-weighted images can be applied in studies across multiple sites and vendors.

Comparison of structural MRI brain measures between 1.5 and 3 T: Data from the Lothian Birth Cohort 1936.

Multi-scanner MRI studies are reliant on understanding the apparent differences in imaging measures between different scanners. We provide a comprehensive analysis of T1 -weighted and diffusion MRI (dMRI) structural brain measures between a 1.5 T GE Signa Horizon HDx and a 3 T Siemens Magnetom Prisma using 91 community-dwelling older participants (aged 82 years). Although we found considerable differences in absolute measurements (global tissue volumes were measured as ~6-11% higher and fractional anisotropy [FA] was 33% higher at 3 T than at 1.5 T), between-scanner consistency was good to excellent for global volumetric and dMRI measures (intraclass correlation coefficient [ICC] range: .612-.993) and fair to good for 68 cortical regions (FreeSurfer) and cortical surface measures (mean ICC: .504-.763). Between-scanner consistency was fair for dMRI measures of 12 major white matter tracts (mean ICC: .475-.564), and the general factors of these tracts provided excellent consistency (ICC ≥ .769). Whole-brain structural networks provided good to excellent consistency for global metrics (ICC ≥ .612). Although consistency was poor for individual network connections (mean ICCs: .275-.280), this was driven by a large difference in network sparsity (.599 vs. .334), and consistency was improved when comparing only the connections present in every participant (mean ICCs: .533-.647). Regression-based k-fold cross-validation showed that, particularly for global volumes, between-scanner differences could be largely eliminated (R2 range .615-.991). We conclude that low granularity measures of brain structure can be reliably matched between the scanners tested, but caution is warranted when combining high granularity information from different scanners.

Comparison of traveling-subject and ComBat harmonization methods for assessing structural brain characteristics.

Multisite magnetic resonance imaging (MRI) is increasingly used in clinical research and development. Measurement biases-caused by site differences in scanner/image-acquisition protocols-negatively influence the reliability and reproducibility of image-analysis methods. Harmonization can reduce bias and improve the reproducibility of multisite datasets. Herein, a traveling-subject (TS) dataset including 56 T1-weighted MRI scans of 20 healthy participants in three different MRI procedures-20, 19, and 17 subjects in Procedures 1, 2, and 3, respectively-was considered to compare the reproducibility of TS-GLM, ComBat, and TS-ComBat harmonization methods. The minimum participant count required for harmonization was determined, and the Cohen's d between different MRI procedures was evaluated as a measurement-bias indicator. The measurement-bias reduction realized with different methods was evaluated by comparing test-retest scans for 20 healthy participants. Moreover, the minimum subject count for harmonization was determined by comparing test-retest datasets. The results revealed that TS-GLM and TS-ComBat reduced measurement bias by up to 85 and 81.3%, respectively. Meanwhile, ComBat showed a reduction of only 59.0%. At least 6 TSs were required to harmonize data obtained from different MRI scanners, complying with the imaging protocol predetermined for multisite investigations and operated with similar scan parameters. The results indicate that TS-based harmonization outperforms ComBat for measurement-bias reduction and is optimal for MRI data in well-prepared multisite investigations. One drawback is the small sample size used, potentially limiting the applicability of ComBat. Investigation on the number of subjects needed for a large-scale study is an interesting future problem.

Super-resolved 3D-STED microscopy identifies a layer-specific increase in excitatory synapses in the hippocampal CA1 region of Neuroligin-3 KO mice.

The chemical synapse is one type of cell-adhesion system that transmits information from a neuron to another neuron in the complex neuronal network in the brain. Synaptic transmission is the rate-limiting step during the information processing in the neuronal network and its plasticity is involved in cognitive functions. Thus, morphological and electrophysiological analyses of synapses are of particular importance in neuroscience research. In the current study, we applied super-resolved three-dimensional stimulated emission depletion (3D-STED) microscopy for the morphological analyses of synapses. This approach allowed us to estimate the precise number of excitatory and inhibitory synapses in the mouse hippocampal tissue. We discovered a region-specific increase in excitatory synapses in a model mouse of autism spectrum disorder, Neuroligin-3 KO, with this method. This type of analysis will open a new field in developmental neuroscience in the future.

Implementation of a dedicated 1.5 T MR scanner for radiotherapy treatment planning featuring a novel high-channel coil setup for brain imaging in treatment position.

PURPOSE: To share our experiences in implementing a dedicated magnetic resonance (MR) scanner for radiotherapy (RT) treatment planning using a novel coil setup for brain imaging in treatment position as well as to present developed core protocols with sequences specifically tuned for brain and prostate RT treatment planning. MATERIALS AND METHODS: Our novel setup consists of two large 18-channel flexible coils and a specifically designed wooden mask holder mounted on a flat tabletop overlay, which allows patients to be measured in treatment position with mask immobilization. The signal-to-noise ratio (SNR) of this setup was compared to the vendor-provided flexible coil RT setup and the standard setup for diagnostic radiology. The occurrence of motion artifacts was quantified. To develop magnetic resonance imaging (MRI) protocols, we formulated site- and disease-specific clinical objectives. RESULTS: Our novel setup showed mean SNR of 163 ± 28 anteriorly, 104 ± 23 centrally, and 78 ± 14 posteriorly compared to 84 ± 8 and 102 ± 22 anteriorly, 68 ± 6 and 95 ± 20 centrally, and 56 ± 7 and 119 ± 23 posteriorly for the vendor-provided and diagnostic setup, respectively. All differences were significant (p > 0.05). Image quality of our novel setup was judged suitable for contouring by expert-based assessment. Motion artifacts were found in 8/60 patients in the diagnostic setup, whereas none were found for patients in the RT setup. Site-specific core protocols were designed to minimize distortions while optimizing tissue contrast and 3D resolution according to indication-specific objectives. CONCLUSION: We present a novel setup for high-quality imaging in treatment position that allows use of several immobilization systems enabling MR-only workflows, which could reduce unnecessary dose and registration inaccuracies.

Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results.

Cross-scanner and cross-protocol variability of diffusion magnetic resonance imaging (dMRI) data are known to be major obstacles in multi-site clinical studies since they limit the ability to aggregate dMRI data and derived measures. Computational algorithms that harmonize the data and minimize such variability are critical to reliably combine datasets acquired from different scanners and/or protocols, thus improving the statistical power and sensitivity of multi-site studies. Different computational approaches have been proposed to harmonize diffusion MRI data or remove scanner-specific differences. To date, these methods have mostly been developed for or evaluated on single b-value diffusion MRI data. In this work, we present the evaluation results of 19 algorithms that are developed to harmonize the cross-scanner and cross-protocol variability of multi-shell diffusion MRI using a benchmark database. The proposed algorithms rely on various signal representation approaches and computational tools, such as rotational invariant spherical harmonics, deep neural networks and hybrid biophysical and statistical approaches. The benchmark database consists of data acquired from the same subjects on two scanners with different maximum gradient strength (80 and 300 â€‹mT/m) and with two protocols. We evaluated the performance of these algorithms for mapping multi-shell diffusion MRI data across scanners and across protocols using several state-of-the-art imaging measures. The results show that data harmonization algorithms can reduce the cross-scanner and cross-protocol variabilities to a similar level as scan-rescan variability using the same scanner and protocol. In particular, the LinearRISH algorithm based on adaptive linear mapping of rotational invariant spherical harmonics features yields the lowest variability for our data in predicting the fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK) and the rotationally invariant spherical harmonic (RISH) features. But other algorithms, such as DIAMOND, SHResNet, DIQT, CMResNet show further improvement in harmonizing the return-to-origin probability (RTOP). The performance of different approaches provides useful guidelines on data harmonization in future multi-site studies.

Microstructural correlates of 23Na relaxation in human brain at 7 Tesla.

23Na provides the second strongest MR-observable signal in biological tissue and exhibits bi-exponential T2∗ relaxation in micro-environments such as the brain. There is significant interest in developing 23Na biomarkers for neurological diseases that are associated with sodium channel dysfunction such as multiple sclerosis and epilepsy. We have previously reported methods for acquisition of multi-echo sodium MRI and continuous distribution modelling of sodium relaxation properties as surrogate markers of brain microstructure. This study aimed to compare 23Na T2∗ relaxation times to more established measures of tissue microstructure derived from advanced diffusion MRI at 7 â€‹T. Six healthy volunteers were scanned using a 3D multi-echo radial ultra-short TE sequence using a dual-tuned 1H/23Na birdcage coil, and a high-resolution multi-shell, high angular resolution diffusion imaging sequence using a 32-channel 1H receive coil. 23Na T2∗ relaxation parameters [mean T2∗ (T2∗mean) and fast relaxation fraction (T2∗ff)] were calculated from a voxel-wise continuous gamma distribution signal model. White matter (restricted anisotropic diffusion) and grey matter (restricted isotropic diffusion) density were calculated from multi-shell multi-tissue constrained spherical deconvolution. Sodium parameters were compared with white and grey matter diffusion properties. Sodium T2∗mean and T2∗ff showed little variation across a range of white matter axonal fibre and grey matter densities. We conclude that sodium T2∗ relaxation parameters are not greatly influenced by relative differences in intra- and extracellular partial volumes. We suggest that care be taken when interpreting sodium relaxation changes in terms of tissue microstructure in healthy tissue.

Denoising scanner effects from multimodal MRI data using linked independent component analysis.

Pooling magnetic resonance imaging (MRI) data across research studies, or utilizing shared data from imaging repositories, presents exceptional opportunities to advance and enhance reproducibility of neuroscience research. However, scanner confounds hinder pooling data collected on different scanners or across software and hardware upgrades on the same scanner, even when all acquisition protocols are harmonized. These confounds reduce power and can lead to spurious findings. Unfortunately, methods to address this problem are scant. In this study, we propose a novel denoising approach that implements a data-driven linked independent component analysis (LICA) to identify scanner-related effects for removal from multimodal MRI to denoise scanner effects. We utilized multi-study data to test our proposed method that were collected on a single 3T scanner, pre- and post-software and major hardware upgrades and using different acquisition parameters. Our proposed denoising method shows a greater reduction of scanner-related variance compared with standard GLM confound regression or ICA-based single-modality denoising. Although we did not test it here, for combining data across different scanners, LICA should prove even better at identifying scanner effects as between-scanner variability is generally much larger than within-scanner variability. Our method has great promise for denoising scanner effects in multi-study and in large-scale multi-site studies that may be confounded by scanner differences.

Portable, field-based neuroimaging using high-density diffuse optical tomography.

Behavioral and cognitive tests in individuals who were malnourished as children have revealed malnutrition-related deficits that persist throughout the lifespan. These findings have motivated recent neuroimaging investigations that use highly portable functional near-infrared spectroscopy (fNIRS) instruments to meet the demands of brain imaging experiments in low-resource environments and enable longitudinal investigations of brain function in the context of long-term malnutrition. However, recent studies in healthy subjects have demonstrated that high-density diffuse optical tomography (HD-DOT) can significantly improve image quality over that obtained with sparse fNIRS imaging arrays. In studies of both task activations and resting state functional connectivity, HD-DOT is beginning to approach the data quality of fMRI for superficial cortical regions. In this work, we developed a customized HD-DOT system for use in malnutrition studies in Cali, Colombia. Our results evaluate the performance of the HD-DOT instrument for assessing brain function in a cohort of malnourished children. In addition to demonstrating portability and wearability, we show the HD-DOT instrument's sensitivity to distributed brain responses using a sensory processing task and measurements of homotopic functional connectivity. Task-evoked responses to the passive word listening task produce activations localized to bilateral superior temporal gyrus, replicating previously published work using this paradigm. Evaluating this localization performance across sparse and dense reconstruction schemes indicates that greater localization consistency is associated with a dense array of overlapping optical measurements. These results provide a foundation for additional avenues of investigation, including identifying and characterizing a child's individual malnutrition burden and eventually contributing to intervention development.

Optical imaging reveals functional domains in primate sensorimotor cortex.

Motor cortex (M1) and somatosensory cortex (S1) are central to arm and hand control. Efforts to understand encoding in M1 and S1 have focused on temporal relationships between neural activity and movement features. However, it remains unclear how the neural activity is spatially organized within M1 and S1. Optical imaging methods are well-suited for revealing the spatio-temporal organization of cortical activity, but their application is sparse in monkey sensorimotor cortex. Here, we investigate the effectiveness of intrinsic signal optical imaging (ISOI) for measuring cortical activity that supports arm and hand control in a macaque monkey. ISOI revealed spatial domains that were active in M1 and S1 in response to instructed reaching and grasping. The lateral M1 domains overlapped the hand representation and contained a population of neurons with peak firing during grasping. In contrast, the medial M1 domain overlapped the arm representation and a population of neurons with peak firing during reaching. The S1 domain overlapped the hand representations of areas 1 and 2 and a population of neurons with peak firing upon hand contact with the target. Our single unit recordings indicate that ISOI domains report the locations of spatial clusters of functionally related neurons. ISOI is therefore an effective tool for surveilling the neocortex for "hot zones" of activity that supports movement. Combining the strengths of ISOI with other imaging modalities (e.g., fMRI, 2-photon) and with electrophysiological methods can open new frontiers in understanding the spatio-temporal organization of cortical signals involved in movement control.

Anterior fissure, central canal, posterior septum and more: New insights into the cervical spinal cord gray and white matter regional organization using T1 mapping at 7T.

T1 mapping lacks specificity toward a single particular biological feature, however it has the potential to discriminate spinal cord regional tissue organization and characterize tissue microstructural impairments occurring in neurodegenerative pathologies. In this exploratory work, T1 mapping of the cervical spinal cord with a 300-µm in-plane resolution was performed on fourteen healthy subjects at 7T, using the MP2RAGE sequence. Individual images from C1 to C7 vertebral levels provided a clear delineation of spinal cord anatomical details and substructures including motor columns within gray matter (GM) horns, anterior median fissure, central canal, ventral, lateral and dorsal white matter (WM) fasciculi, and posterior median septum. Group studies highlighted regional T1 differences between regions of interest so far hardly visible at lower spatial resolution. Two-dimensional averaged T1 maps and manual parcellation of GM and WM substructures were built based on these data. Benefiting from the very high spatial resolution achievable at ultra-high field for T1 mapping, this work contributes to improve the in vivo characterization of the cervical spinal cord. By allowing investigation within a wider range of functional regions, it also opens new perspectives for pathology diagnosis such as motor neuron disease, neuropathic pain or refined investigation of neurodegeneration.

Test-retest reliability and sample size estimates after MRI scanner relocation.

OBJECTIVE: Many factors can contribute to the reliability and robustness of MRI-derived metrics. In this study, we assessed the reliability and reproducibility of three MRI modalities after an MRI scanner was relocated to a new hospital facility. METHODS: Twenty healthy volunteers (12 females, mean age (standard deviation) â€‹= â€‹41 (11) years, age range [25-66]) completed three MRI sessions. The first session (S1) was one week prior to the 3T GE HDxt scanner relocation. The second (S2) occurred nine weeks after S1 and at the new location; a third session (S3) was acquired 4 weeks after S2. At each session, we acquired structural T1-weighted, pseudo-continuous arterial spin labelled, and diffusion tensor imaging sequences. We used longitudinal processing streams to create 12 summary MRI metrics, including total gray matter (GM), cortical GM, subcortical GM, white matter (WM), and lateral ventricle volume; mean cortical thickness; total surface area; average gray matter perfusion, and average diffusion tensor metrics along principal white matter pathways. We compared mean MRI values and variance at the old scanner location to multiple sessions at the new location using Bayesian multi-level regression models. K-fold cross validation allowed identification of important predictors. Whole-brain analyses were used to investigate any regional differences. Furthermore, we calculated within-subject coefficient of variation (wsCV), intraclass correlation coefficient (ICC), and dice similarity index (SI) of cortical segmentations across scanner relocation and within-site. Additionally, we estimated sample sizes required to robustly detect a 4% difference between two groups across MRI metrics. RESULTS: All global MRI metrics exhibited little mean difference and small variability (bar cortical gray matter perfusion) both across scanner relocation and within-site repeat. T1- and DTI-derived tissue metrics showed â€‹< â€‹|0.3|% mean difference and <1.2% variance across scanner location and <|0.4|% mean difference and <0.8% variance within the new location, with between-site intraclass correlation coefficient (ICC) â€‹> â€‹0.80 and within-subject coefficient of variation (wsCV) â€‹< â€‹1.4%. Mean cortical gray matter perfusion had the highest between-session variability (6.7% [0.3, 16.7], estimate [95% uncertainty interval]), and hence the smallest ICC (0.71 [0.44,0.92]) and largest wsCV (13.4% [5.4, 18.1]). No global metric exhibited evidence of a meaningful mean difference between scanner locations. However, surface area showed evidence of a mean difference within-site repeat (between S2 and S3). Whole-brain analyses revealed no significant areas of difference between scanner relocation or within-site. For all metrics, we found no support for a systematic difference in variance across relocation sites compared to within-site test-retest reliability. Necessary sample sizes to detect a 4% difference between two independent groups varied from a maximum of n â€‹= â€‹362 per group (cortical gray matter perfusion), to total gray matter volume (n â€‹= â€‹114), average fractional anisotropy (n â€‹= â€‹23), total gray matter volume normalized by intracranial volume (n â€‹= â€‹19), and axial diffusivity (n â€‹= â€‹3 per group). CONCLUSION: Cortical gray matter perfusion was the most variable metric investigated (necessitating large sample sizes to identify group differences), with other metrics showing substantially less variability. Scanner relocation appeared to have a negligible effect on variability of the global MRI metrics tested. This manuscript reports within-site test-retest variability to act as a tool for calculating sample size in future investigations. Our results suggest that when all other parameters are held constant (e.g., sequence parameters and MRI processing), the effect of scanner relocation is indistinguishable from within-site variability, but may need to be considered depending on the question being investigated.

Neurovascular coupling in the developing neonatal brain at rest.

The neonatal brain is an extremely dynamic organization undergoing essential development in terms of connectivity and function. Several functional imaging investigations of the developing brain have found neurovascular coupling (NVC) patterns that contrast with those observed in adults. These discrepancies are partly due to that NVC is still developing in the neonatal brain. To characterize the vascular response to spontaneous neuronal activations, a multiscale multimodal noninvasive approach combining simultaneous electrical, hemodynamic, and metabolic recordings has been developed for preterm infants. Our results demonstrate that the immature vascular network does not adopt a unique strategy to respond to spontaneous cortical activations. NVC takes on different forms in the same preterm infant during the same recording session in response to very similar types of neural activation. This includes (a) positive stereotyped hemodynamic responses (increases in HbO, decreases in HbR together with increases in rCBF and rCMRO2), (b) negative hemodynamic responses (increases in HbR, decreases in HbO together with decreases in rCBF and rCMRO2), and (c) Increases and decreases in both HbO-HbR and rCMRO2 together with no changes in rCBF. Age-related NVC maturation is demonstrated in preterm infants, which can contribute to a better understanding/prevention of cerebral hemodynamic risks in these infants.

Potential of on-scalp MEG: Robust detection of human visual gamma-band responses.

Electrophysiological signals recorded intracranially show rich frequency content spanning from near-DC to hundreds of hertz. Noninvasive electromagnetic signals measured with electroencephalography (EEG) or magnetoencephalography (MEG) typically contain less signal power in high frequencies than invasive recordings. Particularly, noninvasive detection of gamma-band activity (>30 Hz) is challenging since coherently active source areas are small at such frequencies and the available imaging methods have limited spatial resolution. Compared to EEG and conventional SQUID-based MEG, on-scalp MEG should provide substantially improved spatial resolution, making it an attractive method for detecting gamma-band activity. Using an on-scalp array comprised of eight optically pumped magnetometers (OPMs) and a conventional whole-head SQUID array, we measured responses to a dynamic visual stimulus known to elicit strong gamma-band responses. OPMs had substantially higher signal power than SQUIDs, and had a slightly larger relative gamma-power increase over the baseline. With only eight OPMs, we could obtain gamma-activity source estimates comparable to those of SQUIDs at the group level. Our results show the feasibility of OPMs to measure gamma-band activity. To further facilitate the noninvasive detection of gamma-band activity, the on-scalp OPM arrays should be optimized with respect to sensor noise, the number of sensors and intersensor spacing.

Peripheral nerve stimulation limits of a high amplitude and slew rate magnetic field gradient coil for neuroimaging.

PURPOSE: To establish peripheral nerve stimulation (PNS) thresholds for an ultra-high performance magnetic field gradient subsystem (simultaneous 200-mT/m gradient amplitude and 500-T/m/s gradient slew rate; 1 MVA per axis [MAGNUS]) designed for neuroimaging with asymmetric transverse gradients and 42-cm inner diameter, and to determine PNS threshold dependencies on gender, age, patient positioning within the gradient subsystem, and anatomical landmarks. METHODS: The MAGNUS head gradient was installed in a whole-body 3T scanner with a custom 16-rung bird-cage transmit/receive RF coil compatible with phased-array receiver brain coils. Twenty adult subjects (10 male, mean ± SD age = 40.4 ± 11.1 years) underwent the imaging and PNS study. The tests were repeated by displacing subject positions by 2-4 cm in the superior-inferior and anterior-posterior directions. RESULTS: The x-axis (left-right) yielded mostly facial stimulation, with mean ΔGmin = 111 ± 6 mT/m, chronaxie = 766 ± 76 µsec. The z-axis (superior-inferior) yielded mostly chest/shoulder stimulation (123 ± 7 mT/m, 620 ± 62 µsec). Y-axis (anterior-posterior) stimulation was negligible. X-axis and z-axis thresholds tended to increase with age, and there was negligible dependency with gender. Translation in the inferior and posterior directions tended to increase the x-axis and z-axis thresholds, respectively. Electric field simulations showed good agreement with the PNS results. Imaging at MAGNUS gradient performance with increased PNS threshold provided a 35% reduction in noise-to-diffusion contrast as compared with whole-body performance (80 mT/m gradient amplitude, 200 T/m/sec gradient slew rate). CONCLUSION: The PNS threshold of MAGNUS is significantly higher than that for whole-body gradients, which allows for diffusion gradients with short rise times (under 1 msec), important for interrogating brain microstructure length scales.

Evaluation of neurocognitive function of prefrontal cortex in ornithine transcarbamylase deficiency.

Hyperammonia due to ornithine transcarbamylase deficiency (OTCD) can cause a range of deficiencies in domains of executive function and working memory. Only a few fMRI studies have focused on neuroimaging data in a population with OTCD. Yet, there is a need for monitoring the disease progression and neurocognitive function in this population. In this study, we used a non-invasive neuroimaging technique, functional Near Infrared Spectroscopy (fNIRS), to examine the hemodynamics of prefrontal cortex (PFC) based on neural activation in an OTCD population. Using fNIRS, we measured the activation in PFC of the participants while performing the Stroop task. Behavioral assessment such as reaction time and correct response were recorded. We investigated the difference in behavioral measures as well as brain activation in left and right PFC in patients with OTCD and controls. Results revealed a distinction in left PFC activation between controls and patients with OTCD, where control subjects showed higher task related activation increase. Subjects with OTCD also exhibited bilateral increase in PFC activation. There was no significant difference in response time or correct response between the two groups. Our findings suggest the alterations in neurocognitive function of PFC in OTCD compared to the controls despite the behavioral profiles exhibiting no such differences. This is a first study using fNIRS to examine a neurocognitive function in OTCD population and can provide a novel insight into the screening of OTCD progression and examining neurocognitive changes.