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The human brain undergoes rapid development during the first years of life. Beginning in utero, a wide array of biological, social, and environmental factors can have lasting impacts on brain structure and function. To understand how prenatal and early life experiences alter neurodevelopmental trajectories and shape health outcomes, several NIH Institutes, Centers, and Offices collaborated to support and launch the HEALthy Brain and Child Development (HBCD) Study. The HBCD Study is a multi-site prospective longitudinal cohort study, that will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. Influenced by the success of the ongoing Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) and in partnership with the NIH Helping to End Addiction Long-term® Initiative, or NIH HEAL Initiative®, the HBCD Study aims to establish a diverse cohort of over 7000 pregnant participants to understand how early life experiences, including prenatal exposure to addictive substances and adverse social environments as well as their interactions with an individual’s genes, can affect neurodevelopmental trajectories and outcomes. Knowledge gained from the HBCD Study will help identify targets for early interventions and inform policies that promote resilience and mitigate the neurodevelopmental effects of adverse childhood experiences and environments.

Abstract The medial entorhinal cortex (MEC) is hypothesized to function as a cognitive map for memory-guided navigation. How this map develops during learning and influences memory remains unclear. By imaging MEC calcium dynamics while mice successfully learned a novel virtual environment over ten days, we discovered that the dynamics gradually became more spatially consistent and then stabilized. Additionally, grid cells in the MEC not only exhibited improved spatial tuning consistency, but also maintained stable phase relationships, suggesting a network mechanism involving synaptic plasticity and rigid recurrent connectivity to shape grid cell activity during learning. Increased c-Fos expression in the MEC in novel environments further supports the induction of synaptic plasticity. Unsuccessful learning lacked these activity features, indicating that a consistent map is specific for effective spatial memory. Finally, optogenetically disrupting spatial consistency of the map impaired memory-guided navigation in a well-learned environment. Thus, we demonstrate that the establishment of a spatially consistent MEC map across learning both correlates with, and is necessary for, successful spatial memory.

Summary: We sought to characterize the unique role of somatostatin (SST) in the prelimbic (PL) cortex in mice. We performed slice electrophysiology in pyramidal and GABAergic neurons to characterize the pharmacological mechanism of SST signaling and fiber photometry of GCaMP6f fluorescent calcium signals from SST neurons to characterize the activity profile of SST neurons during exploration of an elevated plus maze (EPM) and open field test (OFT). We used local delivery of a broad SST receptor (SSTR) agonist and antagonist to test causal effects of SST signaling. SSTR activation hyperpolarizes layer 2/3 pyramidal neurons, an effect that is recapitulated with optogenetic stimulation of SST neurons. SST neurons in PL are activated during EPM and OFT exploration, and SSTR agonist administration directly into the PL enhances open arm exploration in the EPM. This work describes a broad ability for SST peptide signaling to modulate microcircuits within the prefrontal cortex and related exploratory behaviors.

Abstract Background In 2013, a few years after the launch of the National Institute of Mental Health’s Research Domain Criteria (RDoC) initiative, Cuthbert and Insel published a paper titled “Toward the future of psychiatric diagnosis: the seven pillars of RDoC.” The RDoC project is a translational research effort to encourage new ways of studying psychopathology through a focus on disruptions in normal functions (such as reward learning or attention) that are defined jointly by observable behavior and neurobiological measures. The paper outlined the principles of the RDoC research framework, including emphases on research that acquires data from multiple measurement classes to foster integrative analyses, adopts dimensional approaches, and employs novel methods for ascertaining participants and identifying valid subgroups. Discussion To mark the first decade of the RDoC initiative, we revisit the seven pillars and highlight new research findings and updates to the framework that are related to each. This reappraisal emphasizes the flexible nature of the RDoC framework and its application in diverse areas of research, new findings related to the importance of developmental trajectories within and across neurobehavioral domains, and the value of computational approaches for clarifying complex multivariate relations among behavioral and neurobiological systems. Conclusion The seven pillars of RDoC have provided a foundation that has helped to guide a surge of new studies that have examined neurobehavioral domains related to mental disorders, in the service of informing future psychiatric nosology. Building on this footing, future areas of emphasis for the RDoC project will include studying central-peripheral interactions, developing novel approaches to phenotyping for genomic studies, and identifying new targets for clinical trial research to facilitate progress in precision psychiatry.

Acute stress transiently disrupts reward-seeking behaviour and repeated stress exposure produces lasting anhedonia-like behaviour in rodents. Here, the authors show that stress triggers GABAergic activity in the ventral tegmental area which blunts reward-seeking behaviour in mice.

We demonstrate a Rydberg atom-based sensor embedded in a parallel-plate waveguide (PPWG) for amplitude and phase detection of a radio-frequency (RF) electric field. This embedded atomic sensor is also capable of receiving modulated communications signals. In this configuration, the PPWG antenna serves two functions. First, the PPWG antenna acts as a source for a local oscillator (LO) field. The LO is required to use an atomic vapor cell (a glass cell containing a Rydberg atom vapor) as a Rydberg atom-based mixer, which detects the amplitude and phase of a second RF field incident from some remote location. The second function of the PPWG antenna is to capture the RF field arriving from a remote location and concentrate it at the location of the atomic vapor cell for detection. To demonstrate this, we show several examples of phase and amplitude measurements of an RF field with the embedded Rydberg-atom sensor. We also demonstrate the discrimination of the polarization of an RF field and the ability to receive phase-modulated carrier communications signals with this integrated atomic sensor. Embedding the atomic sensor in an antenna allows for the full characterization of a radio frequency field, in that the magnitude, phase, and polarization of an RF field can be measured with one compact integrated quantum-based sensor. Furthermore, the embedded sensor head allows one to easily vary the LO in order to maximize the ability to measure phase and amplitude of the field or modulated signal.

Adolescence is a time of dramatic changes in brain structure and function, and the adolescent brain is highly susceptible to being altered by experiences like substance use. However, there is much we have yet to learn about how these experiences influence brain development, how they promote or interfere with later health outcomes, or even what healthy brain development looks like. A large longitudinal study beginning in early adolescence could help us understand the normal variability in adolescent brain and cognitive development and tease apart the many factors that influence it. Recent advances in neuroimaging, informatics, and genetics technologies have made it feasible to conduct a study of sufficient size and scope to answer many outstanding questions. At the same time, several Institutes across the NIH recognized the value of collaborating in such a project because of its ability to address the role of biological, environmental, and behavioral factors like gender, pubertal hormones, sports participation, and social/economic disparities on brain development as well as their association with the emergence and progression of substance use and mental illness including suicide risk. Thus, the Adolescent Brain Cognitive Development study was created to answer the most pressing public health questions of our day. Keywords: Adolescent, Brain development, Neuroimaging, Longitudinal, Substance use, Mental health

In this work, we present methods allowing parallel, hybrid, and serial manipulators to be analyzed, calibrated, and controlled with the same analytical tools. We introduce a general approach to describe any robotic manipulator using established serial-link representations. We use this framework to generate analytical kinematic and calibration Jacobians for general manipulator constructions using null space constraints and extend the methods to hybrid manipulator types with complex geometry. We leverage the analytical Jacobians to develop detailed expressions for post-calibration pose uncertainties that are applied to describe the relationship between data set size and post-calibration uncertainty. We demonstrate the calibration of a hybrid manipulator assembled from high precision calibrated industrial components resulting in 91.1 μm RMS position error and 71.2 μrad RMS rotation error, representing a 46.7% reduction compared to the baseline calibration of assembly offsets.

Theta- and gamma-frequency oscillatory synchrony correlates with spatial working memory performance. Here the authors report increases in theta-gamma cross-frequency coupling as a compensatory mechism associated with better working memory performance in models of cognitive dysfunction in mice.

This article provides an illustrative treatment of psychiatric morbidity that offers an alternative to the standard nosological model in psychiatry. It considers what would happen if we treated diagnostic categories not as causes of signs and symptoms, but as diagnostic consequences of psychopathology and pathophysiology. This reformulation (of the standard nosological model) opens the door to a more natural description of how patients present—and of their likely responses to therapeutic interventions. In brief, we describe a model that generates symptoms, signs, and diagnostic outcomes from latent psychopathological states. In turn, psychopathology is caused by pathophysiological processes that are perturbed by (etiological) causes such as predisposing factors, life events, and therapeutic interventions. The key advantages of this nosological formulation include (i) the formal integration of diagnostic (e.g., DSM) categories and latent psychopathological constructs (e.g., the dimensions of the Research Domain Criteria); (ii) the provision of a hypothesis or model space that accommodates formal, evidence-based hypothesis testing (using Bayesian model comparison); and (iii) the ability to predict therapeutic responses (using a posterior predictive density), as in precision medicine. These and other advantages are largely promissory at present: The purpose of this article is to show what might be possible, through the use of idealized simulations.

Rydberg atoms have been used for measuring radio-frequency (RF) electric (E)-fields due to their strong dipole moments over the frequency range of 500 MHz-1 THz. For this, electromagnetically induced transparency (EIT) within the Autler-Townes (AT) regime is used such that the detected E-field is proportional to AT splitting. However, for weak E-fields AT peak separation becomes unresolvable thus limiting the minimum detectable E-field. Here, we demonstrate using the Rydberg atoms as an RF mixer for weak E-field detection well below the AT regime with frequency discrimination better than 1 Hz resolution. A heterodyne detection scenario with two E-fields incident on a vapor cell filled with cesium atoms is used. One E-field at 19.626000 GHz drives the 34D5/2 → 35P3/2 Rydberg transition and acts as a local oscillator (LO) and a second signal E-field (Sig) of interest is at 19.626090 GHz. In the presence of the LO, the Rydberg atoms naturally down convert the Sig field to a 90 kHz intermediate frequency (IF) signal. This IF signal manifests as an oscillation in the probe laser intensity through the Rydberg vapor and is easily detected with a photodiode and lock-in amplifier. In the configuration used here, E-field strength down to ≈ 46 μV/m ± 2 μV/m were detected with a sensitivity of ≈ 79 μVm−1Hz−1/2. Furthermore, neighboring fields 0.1 Hz away and equal in strength to Sig could be discriminated without any leakage into the lock-in signal. For signals 1 Hz away and as high as +60 dB above Sig, leakage into the lock-in signal could be kept below -3 dB.

Proline dehydrogenase (PRODH), which degrades L-proline, resides within the schizophrenia-linked 22q11.2 deletion suggesting a role in disease. Supporting this, elevated L-proline levels have been shown to increase risk for psychotic disorders. Despite the strength of data linking PRODH and L-proline to neuropsychiatric diseases, targets of disease-relevant concentrations of L-proline have not been convincingly described. Here, we show that Prodh-deficient mice with elevated CNS L-proline display specific deficits in high-frequency GABA-ergic transmission and gamma-band oscillations. We find that L-proline is a GABA-mimetic and can act at multiple GABA-ergic targets. However, at disease-relevant concentrations, GABA-mimesis is limited to competitive blockade of glutamate decarboxylase leading to reduced GABA production. Significantly, deficits in GABA-ergic transmission are reversed by enhancing net GABA production with the clinically relevant compound vigabatrin. These findings indicate that accumulation of a neuroactive metabolite can lead to molecular and synaptic dysfunction and help to understand mechanisms underlying neuropsychiatric disease.

Despite the increasing use of optogenetics in vivo, the effects of direct light exposure to brain tissue are understudied. Of particular concern is the potential for heat induced by prolonged optical stimulation. We demonstrate that high-intensity light, delivered through an optical fiber, is capable of elevating firing rate locally, even in the absence of opsin expression. Predicting the severity and spatial extent of any temperature increase during optogenetic stimulation is therefore of considerable importance. Here, we describe a realistic model that simulates light and heat propagation during optogenetic experiments. We validated the model by comparing predicted and measured temperature changes in vivo. We further demonstrate the utility of this model by comparing predictions for various wavelengths of light and fiber sizes, as well as testing methods for reducing heat effects on neural targets in vivo.