SYNAPTIC PLASTICITY IN THE INJURED BRAIN DEPENDS ON THE TEMPORAL PATTERN OF STIMULATION.

Neurostimulation protocols are increasingly used as therapeutic interventions, including for brain injury. In addition to the direct activation of neurons, these stimulation protocols are also likely to have downstream effects on those neurons' synaptic outputs. It is well known that alterations in the strength of synaptic connections (long-term potentiation, LTP; long-term depression, LTD) are sensitive to the frequency of stimulation used for induction, however little is known about the contribution of the temporal pattern of stimulation to the downstream synaptic plasticity that may be induced by neurostimulation in the injured brain. We explored interactions of the temporal pattern and frequency of neurostimulation in the normal cerebral cortex and after mild traumatic brain injury (mTBI), to inform therapies to strengthen or weaken neural circuits in injured brains, as well as to better understand the role of these factors in normal brain plasticity. Whole-cell (WC) patch-clamp recordings of evoked postsynaptic potentials (PSPs) in individual neurons, as well as field potential (FP) recordings, were made from layer 2/3 of visual cortex in response to stimulation of layer 4, in acute slices from control (naïve), sham operated, and mTBI rats. We compared synaptic plasticity induced by different stimulation protocols, each consisting of a specific frequency (1 Hz, 10 Hz, or 100 Hz), continuity (continuous or discontinuous), and temporal pattern (perfectly regular, slightly irregular, or highly irregular). At the individual neuron level, dramatic differences in plasticity outcome occurred when the highly irregular stimulation protocol was used at 1 Hz or 10 Hz, producing an overall LTD in controls and shams, but a robust overall LTP after mTBI. Consistent with the individual neuron results, the plasticity outcomes for simultaneous FP recordings were similar, indicative of our results generalizing to a larger scale synaptic network than can be sampled by individual WC recordings alone. In addition to the differences in plasticity outcome between control (naïve or sham) and injured brains, the dynamics of the changes in synaptic responses that developed during stimulation were predictive of the final plasticity outcome. Our results demonstrate that the temporal pattern of stimulation plays a role in the polarity and magnitude of synaptic plasticity induced in the cerebral cortex while highlighting differences between normal and injured brain responses. Moreover, these results may be useful for optimization of neurostimulation therapies to treat mTBI and other brain disorders, in addition to providing new insights into downstream plasticity signaling mechanisms in the normal brain.

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks.

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3-20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks.

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3 - 20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

Community recommendations on cryoEM data archiving and validation.

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for the deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and the resulting consensus recommendations. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.

Overcoming resolution attenuation during tilted cryo-EM data collection.

Structural biology efforts using cryogenic electron microscopy are frequently stifled by specimens adopting "preferred orientations" on grids, leading to anisotropic map resolution and impeding structure determination. Tilting the specimen stage during data collection is a generalizable solution but has historically led to substantial resolution attenuation. Here, we develop updated data collection and image processing workflows and demonstrate, using multiple specimens, that resolution attenuation is negligible or significantly reduced across tilt angles. Reconstructions with and without the stage tilted as high as 60° are virtually indistinguishable. These strategies allowed the reconstruction to 3 Å resolution of a bacterial RNA polymerase with preferred orientation, containing an unnatural nucleotide for studying novel base pair recognition. Furthermore, we present a quantitative framework that allows cryo-EM practitioners to define an optimal tilt angle during data acquisition. These results reinforce the utility of employing stage tilt for data collection and provide quantitative metrics to obtain isotropic maps.

Community recommendations on cryoEM data archiving and validation: Outcomes of a wwPDB/EMDB workshop on cryoEM data management, deposition and validation.

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and consensus recommendations resulting from the workshop. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.

Transformations between rotational and translational invariants formulated in reciprocal spaces.

Correlation functions play an important role in the theoretical underpinnings of many disparate areas of the physical sciences: in particular, scattering theory. More recently, they have become useful in the classification of objects in areas such as computer vision and our area of cryoEM. Our primary classification scheme in the cryoEM image processing system, EMAN2, is now based on third order invariants formulated in Fourier space. This allows a factor of 8 speed up in the two classification procedures inherent in our software pipeline, because it allows for classification without the need for computationally costly alignment procedures. In this work, we address several formal and practical aspects of such multispectral invariants. We show that we can formulate such invariants in the representation in which the original signal is most compact. We explicitly construct transformations between invariants in different orientations for arbitrary order of correlation functions and dimension. We demonstrate that third order invariants distinguish 2D mirrored patterns (unlike the radial power spectrum), which is a fundamental aspects of its classification efficacy. We show the limitations of 3rd order invariants also, by giving an example of a wide family of patterns with identical (vanishing) set of 3rd order invariants. For sufficiently rich patterns, the third order invariants should distinguish typical images, textures and patterns.

Overcoming Resolution Attenuation During Tilted Cryo-EM Data Collection.

Structural biology efforts using cryogenic electron microscopy are frequently stifled by specimens adopting "preferred orientations" on grids, leading to anisotropic map resolution and impeding structure determination. Tilting the specimen stage during data collection is a generalizable solution but has historically led to substantial resolution attenuation. Here, we develop updated data collection and image processing workflows and demonstrate, using multiple specimens, that resolution attenuation is negligible or significantly reduced across tilt angles. Reconstructions with and without the stage tilted as high as 60° are virtually indistinguishable. These strategies allowed the reconstruction to 3 Å resolution of a bacterial RNA polymerase with preferred orientation. Furthermore, we present a quantitative framework that allows cryo-EM practitioners to define an optimal tilt angle for dataset acquisition. These data reinforce the utility of employing stage tilt for data collection and provide quantitative metrics to obtain isotropic maps.

Tools for visualizing and analyzing Fourier space sampling in Cryo-EM.

A complete understanding of how an orientation distribution contributes to a cryo-EM reconstruction remains lacking. It is necessary to begin critically assessing the set of views to gain an understanding of its effect on experimental reconstructions. Toward that end, we recently suggested that the type of orientation distribution may alter resolution measures in a systematic manner. We introduced the sampling compensation factor (SCF), which incorporates how the collection geometry might change the spectral signal-to-noise ratio (SSNR), irrespective of the other experimental aspects. We show here that knowledge of the sampling restricted to spherical surfaces of sufficiently large radii in Fourier space is equivalent to knowledge of the set of projection views. Moreover, the SCF geometrical factor may be calculated from one such surface. To aid cryo-EM practitioners, we developed a graphical user interface (GUI) tool that evaluates experimental orientation distributions. The GUI returns plots of projection directions, sampling constrained to the surface of a sphere, the SCF value, the fraction of the empty region of Fourier space, and a histogram of the sampling values over the points on a sphere. Finally, a fixed tilt angle may be incorporated to determine how tilting the grid during collection may improve the distribution of views and Fourier space sampling. We advocate this simple conception of sampling and the use of such tools as a complement to the distribution of views to capture the different aspects of the effect of projection directions on cryo-EM reconstructions.

Non-uniformity of projection distributions attenuates resolution in Cryo-EM.

Virtually all single-particle cryo-EM experiments currently suffer from specimen adherence to the air-water interface, leading to a non-uniform distribution in the set of projection views. Whereas it is well accepted that uniform projection distributions can lead to high-resolution reconstructions, non-uniform (anisotropic) distributions can negatively affect map quality, elongate structural features, and in some cases, prohibit interpretation altogether. Although some consequences of non-uniform sampling have been described qualitatively, we know little about how sampling quantitatively affects resolution in cryo-EM. Here, we show how inhomogeneity in any projection distribution scheme attenuates the global Fourier Shell Correlation (FSC) in relation to the number of particles and a single geometrical parameter, which we term the sampling compensation factor (SCF). The reciprocal of the SCF is defined as the average over Fourier shells of the reciprocal of the per-particle sampling and normalized to unity for uniform distributions. The SCF therefore ranges from one to zero, with values close to the latter implying large regions of poorly sampled or completely missing data in Fourier space. Using two synthetic test cases, influenza hemagglutinin and human apoferritin, we demonstrate how any amount of sampling inhomogeneity always attenuates the FSC compared to a uniform distribution. We advocate quantitative evaluation of the SCF criterion to approximate the effect of non-uniform sampling on resolution within experimental single-particle cryo-EM reconstructions.

The habenula as a novel link between the homeostatic and hedonic pathways in cancer-associated weight loss: a pilot study.

BACKGROUND: Little is known about the brain mechanisms underlying cancer-associated weight loss (C-WL) in humans despite this condition negatively affecting their quality of life and survival. We tested the hypothesis that patients with C-WL have abnormal connectivity in homeostatic and hedonic brain pathways together with altered brain activity during food reward. METHODS: In 12 patients with cancer and 12 healthy controls, resting-state functional connectivity (RSFC, resting brain activity observed through changes in blood flow in the brain which creates a blood oxygen level-dependent signal that can be measured using functional magnetic resonance imaging) was used to compare three brain regions hypothesized to play a role in C-WL: the hypothalamus (homeostatic), the nucleus accumbens (hedonic), and the habenula (an important regulator of reward). In addition, the brain reward response to juice was studied. Participants included 12 patients with histological diagnosis of incurable cancer (solid tumours), a European Cooperative Oncology Group performance status of 0-2, and a ≥5% involuntary body weight loss from pre-illness over the previous 6 months and 12 non-cancer controls matched for age, sex, and race. RSFC between the hypothalamus, nucleus accumbens, and habenula and brain striatum activity as measured by functional MRI during juice reward delivery events were the main outcome measures. RESULTS: After adjusting for BMI and compared with matched controls, patients with C-WL were found to have reduced RSFC between the habenula and hypothalamus (P = 0.04) and between the habenula and nucleus accumbens (P = 0.014). Patients with C-WL also had reduced juice reward responses in the striatum compared with controls. CONCLUSIONS: In patients with C-WL, reduced connectivity between both homeostatic and hedonic brain regions and the habenula and reduced juice reward were observed. Further research is needed to establish the relevance of the habenula and striatum in C-WL.

Amygdala-frontal connectivity predicts internalizing symptom recovery among inpatient adolescents.

BACKGROUND: The possibility of using biological measures to predict the trajectory of symptoms among adolescent psychiatric inpatients has important implications. This study aimed to examine emotion regulation ability (measured via self-report) and a hypothesized proxy in resting-state functional connectivity [RSFC] between the amygdala and frontal brain regions as baseline predictors of internalizing symptom recovery during inpatient care. METHODS: 196 adolescents (61% female; Mage = 15.20; SD = 1.48) completed the Achenbach Brief Problem Monitor (BPM) each week during their inpatient care. RSFC (n = 45) and self-report data of emotion regulation (n = 196) were collected at baseline. RESULTS: The average internalizing symptom score at admission was high (α0 = 66.52), exceeding the BPM's clinical cut off score of 65. On average, internalizing symptom scores declined significantly, by 0.40 points per week (p = 0.004). While self-reported emotion regulation was associated with admission levels of internalizing problems, it did not predict change in symptoms. RSFC between left amygdala and left superior frontal gyrus was significantly associated with the intercept-higher connectivity was associated with higher internalizing at admission-and the slope- higher connectivity was associated with a more positive slope (i.e., less decline in symptoms). RSFC between the right amygdala and the left superior frontal gyrus was significantly, positively correlated with the slope parameter. CONCLUSIONS: Results indicate the potential of biologically-based measures that can be developed further for personalized care in adolescent psychiatry.

Big data in cryoEM: automated collection, processing and accessibility of EM data.

The scope and complexity of cryogenic electron microscopy (cryoEM) data has greatly increased, and will continue to do so, due to recent and ongoing technical breakthroughs that have led to much improved resolutions for macromolecular structures solved using this method. This big data explosion includes single particle data as well as tomographic tilt series, both generally acquired as direct detector movies of ∼10-100 frames per image or per tilt-series. We provide a brief survey of the developments leading to the current status, and describe existing cryoEM pipelines, with an emphasis on the scope of data acquisition, methods for automation, and use of cloud storage and computing.

Prefrontal Connectivity and Glutamate Transmission: Relevance to Depression Pathophysiology and Ketamine Treatment.

BACKGROUND: Prefrontal global brain connectivity with global signal regression (GBCr) was proposed as a robust biomarker of depression, and was associated with ketamine's mechanism of action. Here, we investigated prefrontal GBCr in treatment-resistant depression (TRD) at baseline and following treatment. Then, we conducted a set of pharmacological challenges in healthy subjects to investigate the glutamate neurotransmission correlates of GBCr. METHODS: In study A, we used functional magnetic resonance imaging (fMRI) to compare GBCr between 22 TRD and 29 healthy control. Then, we examined the effects of ketamine and midazolam on GBCr in TRD patients 24h post-treatment. In study B, we acquired repeated fMRI in 18 healthy subjects to determine the effects of lamotrigine (a glutamate release inhibitor), ketamine, and lamotrigine-by-ketamine interaction. RESULTS: In study A, TRD patients showed significant reduction in dorsomedial and dorsolateral prefrontal GBCr compared to healthy control. In TRD patients, GBCr in the altered clusters significantly increased 24h following ketamine (effect size = 1.0 [0.3 1.8]), but not midazolam (effect size = 0.5 [-0.6 1.3]). In study B, oral lamotrigine reduced GBCr 2h post-administration, while ketamine increased medial prefrontal GBCr during infusion. Lamotrigine significantly reduced the ketamine-induced GBCr surge. Exploratory analyses showed elevated ventral prefrontal GBCr in TRD and significant reduction of ventral prefrontal GBCr during ketamine infusion in healthy subjects. CONCLUSIONS: This study provides first replication of the ability of ketamine to normalize depression-related prefrontal dysconnectivity. It also provides indirect evidence that these effects may be triggered by the capacity of ketamine to enhance glutamate neurotransmission.

Genome-wide imaging association study implicates functional activity and glial homeostasis of the caudate in smoking addiction.

BACKGROUND: Nearly 6 million deaths and over a half trillion dollars in healthcare costs worldwide are attributed to tobacco smoking each year. Extensive research efforts have been pursued to elucidate the molecular underpinnings of smoking addiction and facilitate cessation. In this study, we genotyped and obtained both resting state and task-based functional magnetic resonance imaging from 64 non-smokers and 42 smokers. Smokers were imaged after having smoked normally ("sated") and after having not smoked for at least 12 h ("abstinent"). RESULTS: While abstinent smokers did not differ from non-smokers with respect to pairwise resting state functional connectivities (RSFCs) between 12 brain regions of interest, RSFCs involving the caudate and putamen of sated smokers significantly differed from those of non-smokers (P < 0.01). Further analyses of caudate and putamen activity during elicited experiences of reward and disappointment show that caudate activity during reward (CR) correlated with smoking status (P = 0.015). Moreover, abstinent smokers with lower CR experienced greater withdrawal symptoms (P = 0.024), which suggests CR may be related to smoking urges. Associations between genetic variants and CR, adjusted for smoking status, were identified by genome-wide association study (GWAS). Genes containing or exhibiting caudate-specific expression regulation by these variants were enriched within Gene Ontology terms that describe cytoskeleton functions, synaptic organization, and injury response (P < 0.001, FDR < 0.05). CONCLUSIONS: By integrating genomic and imaging data, novel insights into potential mechanisms of caudate activation and homeostasis are revealed that may guide new directions of research toward improving our understanding of addiction pathology.

Increased habenular connectivity in opioid users is associated with an α5 subunit nicotinic receptor genetic variant.

BACKGROUND AND OBJECTIVES: Opioid use disorder (OUD) is a chronic disorder with relapse based on both desire for reinforcement (craving) and avoidance of withdrawal. The aversive aspect of dependence and relapse has been associated with a small brain structure called the habenula, which expresses large numbers of both opioid and nicotinic receptors. Additionally, opioid withdrawal symptoms can be induced in opioid-treated rodents by blocking not only opioid, but also nicotinic receptors. This receptor co-localization and cross-induction of withdrawal therefore might lead to genetic variation in the nicotinic receptor influencing development of human opioid dependence through its impact on the aversive components of opioid dependence. METHODS: We studied habenular resting state functional connectivity with related brain structures, specifically the striatum. We compared abstinent psychiatric patients who use opioids (N = 51) to psychiatric patients who do not (N = 254) to identify an endophenotype of opioid use that focused on withdrawal avoidance and aversion rather than the more commonly examined craving aspects of relapse. RESULTS: We found that habenula-striatal connectivity was stronger in opioid-using patients. Increased habenula-striatum connectivity was observed in opioid-using patients with the low risk rs16969968 GG genotype, but not in patients carrying the high risk AG or AA genotypes. CONCLUSIONS: We propose that increased habenula-striatum functional connectivity may be modulated by the nicotinic receptor variant rs16969968 and may lead to increased opioid use. SCIENTIFIC SIGNIFICANCE: Our data uncovered a promising brain target for development of novel anti-addiction therapies and may help the development of personalized therapies against opioid abuse. (Am J Addict 2017;26:751-759).

Addressing preferred specimen orientation in single-particle cryo-EM through tilting.

We present a strategy for tackling preferred specimen orientation in single-particle cryogenic electron microscopy by employing tilts during data collection. We also describe a tool to quantify the resulting directional resolution using 3D Fourier shell correlation volumes. We applied these methods to determine the structures at near-atomic resolution of the influenza hemagglutinin trimer, which adopts a highly preferred specimen orientation, and of ribosomal biogenesis intermediates, which adopt moderately preferred orientations.

A Novel Approach to Identifying a Neuroimaging Biomarker for Patients With Serious Mental Illness.

Serious mental illness (SMI) is disabling, and current interventions are ineffective for many. This exploratory study sought to demonstrate the feasibility of applying topological data analysis (TDA) to resting-state functional connectivity data obtained from a heterogeneous sample of 235 adult inpatients to identify a biomarker of treatment response. TDA identified two groups based on connectivity between the prefrontal cortex and striatal regions: patients admitted with greater functional connectivity between these regions evidenced less improvement from admission to discharge than patients with lesser connectivity between them. TDA identified a potential biomarker of an attenuated treatment response among inpatients with SMI. Insofar as the observed pattern of resting-state functional connectivity collected early during treatment is replicable, this potential biomarker may indicate the need to modify standard of care for a small, albeit meaningful, percentage of patients.

Real time functional MRI training to decrease motion in imaging studies: Lack of significant improvement.

Functional magnetic resonance imaging (fMRI) is widely used to study brain circuitry in healthy controls and in psychiatry. A major problem of fMRI studies is motion, which affects the quality of images, is a major source of noise, and can confound data if, for example, the experimental groups move differently. Despite continual reminders to experimental subjects about keeping still, however, movement in the scanner remains a problem. The authors hypothesized that showing head movement during a scanning session may help subjects learn how to keep their head still. The authors scanned subjects and displayed in real time a plot of head movement that had three regions. The authors found, in a limited sample, that the improvements were marginal and inconsistent. Thus, they concluded that this strategy, even if likely to work for some people, is probably not sufficiently successful to be implemented at this time.