Characterizing dynamically evolving functional networks in humans with application to speech

Understanding how communication between brain areas evolves to support dynamic function remains a fundamental challenge in neuroscience. One approach to this question is functional connectivity analysis, in which statistical coupling measures are employed to detect signatures of interactions between brain regions. Because the brain uses multiple communication mechanisms at different temporal and spatial scales, and because the neuronal signatures of communication are often weak, powerful connectivity inference methodologies require continued development specific to these challenges. Here we address the challenge of inferring task-related functional connectivity in brain voltage recordings. We first develop a framework for detecting changes in statistical coupling that occur reliably in a task relative to a baseline period. The framework characterizes the dynamics of connectivity changes, allows inference on multiple spatial scales, and assesses statistical uncertainty. This general framework is modular and applicable to a wide range of tasks and research questions. We demonstrate the flexibility of the framework in the second part of this thesis, in which we refine the coupling statistics and hypothesis tests to improve statistical power and test different proposed connectivity mechanisms. In particular, we introduce frequency domain coupling measures and define test statistics that exploit theoretical properties and capture known sampling variability. The resulting test statistics use correlation, coherence, canonical correlation, and canonical coherence to infer task-related changes in coupling. Because canonical correlation and canonical coherence are not commonly used in functional connectivity analyses, we derive the theoretical values and statistical estimators for these measures. In the third part of this thesis, we present a sample application of these techniques to electrocorticography data collected during an overt reading task. We discuss the challenges that arise with task-related human data, which is often noisy and underpowered, and present functional connectivity results in the context of traditional and contemporary within-electrode analytics. In two of nine subjects we observe time-domain and frequency-domain network changes that accord with theoretical models of information routing during motor processing. Taken together, this work contributes a methodological framework for inferring task-related functional connectivity across spatial and temporal scales, and supports insight into the rapid, dynamic functional coupling of human speech

Degeneracy between mass and spin in black-hole-binary waveforms

We explore the degeneracy between mass and spin in gravitational waveforms emitted by black-hole binary coalescences. We focus on spin-aligned waveforms and obtain our results using phenomenological models that were tuned to numerical-relativity simulations. A degeneracy is known for low-mass binaries (particularly neutron-star binaries), where gravitational-wave detectors are sensitive to only the inspiral phase, and the waveform can be modelled by post-Newtonian theory. Here, we consider black-hole binaries, where detectors will also be sensitive to the merger and ringdown, and demonstrate that the degeneracy persists across a broad mass range. At low masses, the degeneracy is between mass ratio and total spin, with chirp mass accurately determined. At higher masses, the degeneracy persists but is not so clearly characterised by constant chirp mass as the merger and ringdown become more significant. We consider the importance of this degeneracy both for performing searches (including searches where only non-spinning templates are used) and in parameter extraction from observed systems. We compare observational capabilities between the early (~2015) and final (2018 onwards) versions of the Advanced LIGO detector.Comment: 11 pages, 9 figure

Interfacing Microbial Styrene Production with a Biocompatible Cyclopropanation Reaction

Introducing new reactivity into living organisms is a major challenge in synthetic biology. Despite an increasing interest in both developing aqueous-compatible small molecule catalysts and engineering enzymes to perform new chemistry in vitro, the integration of non-native reactivity into metabolic pathways for small molecule production has been underexplored. Herein we report a biocompatible iron(III) phthalocyanine catalyst capable of efficient olefin cyclopropanation in the presence of a living microorganism. By interfacing this catalyst with E. coli engineered to produce styrene, we synthesize non-natural phenyl cyclopropanes directly from D-glucose in single-vessel fermentations. This process represents the first combination of non-biological carbene-transfer reactivity with cellular metabolism for small molecule production.Chemistry and Chemical Biolog

Using Non-Enzymatic Chemistry to Influence Microbial Metabolism

The structural manipulation of small molecule metabolites occurs in all organisms and plays a fundamental role in essentially all biological processes. Despite an increasing interest in developing new, non-enzymatic chemical reactions capable of functioning in the presence of living organisms, the ability of such transformations to interface with cellular metabolism and influence biological function is a comparatively underexplored area of research. This review will discuss efforts to combine non-enzymatic chemistry with microbial metabolism. We will highlight recent and historical uses of non-biological reactions to study microbial growth and function, the use of non-enzymatic transformations to rescue auxotrophic microorganisms, and the combination of engineered microbial metabolism and biocompatible chemical reactions for organic synthesis.Chemistry and Chemical Biolog

It\u27s way more than just writing a prescription : A qualitative study of preferences for integrated versus non-integrated treatment models among individuals with opioid use disorder

BACKGROUND: Increasingly, treatment for opioid use disorder (OUD) is offered in integrated treatment models addressing both substance use and other health conditions within the same system. This often includes offering medications for OUD in general medical settings. It remains uncertain whether integrated OUD treatment models are preferred to non-integrated models, where treatment is provided within a distinct treatment system. This study aimed to explore preferences for integrated versus non-integrated treatment models among people with OUD and examine what factors may influence preferences. METHODS: This qualitative study recruited participants (n = 40) through Craigslist advertisements and flyers posted in treatment programs across the United States. Participants were 18 years of age or older and scored a two or higher on the heroin or opioid pain reliever sections of the Tobacco, Alcohol, Prescription Medications, and Other Substances (TAPS) Tool. Each participant completed a demographic survey and a telephone interview. The interviews were coded and content analyzed. RESULTS: While some participants preferred receiving OUD treatment from an integrated model in a general medical setting, the majority preferred non-integrated models. Some participants preferred integrated models in theory but expressed concerns about stigma and a lack of psychosocial services. Tradeoffs between integrated and non-integrated models were centered around patient values (desire for anonymity and personalization, fear of consequences), the characteristics of the provider and setting (convenience, perceived treatment effectiveness, access to services), and the patient-provider relationship (disclosure, trust, comfort, stigma). CONCLUSIONS: Among this sample of primarily White adults, preferences for non-integrated versus integrated OUD treatment were mixed. Perceived benefits of integrated models included convenience, potential for treatment personalization, and opportunity to extend established relationships with medical providers. Recommendations to make integrated treatment more patient-centered include facilitating access to psychosocial services, educating patients on privacy, individualizing treatment, and prioritizing the patient-provider relationship. This sample included very few minorities and thus findings may not be fully generalizable to the larger population of persons with OUD. Nonetheless, results suggest a need for expansion of both OUD treatment in specialty and general medical settings to ensure access to preferred treatment for all

“It’s way more than just writing a prescription”: A qualitative study of preferences for integrated versus non-integrated treatment models among individuals with opioid use disorder

Background: Increasingly, treatment for opioid use disorder (OUD) is offered in integrated treatment models addressing both substance use and other health conditions within the same system. This often includes offering medications for OUD in general medical settings. It remains uncertain whether integrated OUD treatment models are preferred to non-integrated models, where treatment is provided within a distinct treatment system. This study aimed to explore preferences for integrated versus non-integrated treatment models among people with OUD and examine what factors may influence preferences. Methods: This qualitative study recruited participants (n = 40) through Craigslist advertisements and flyers posted in treatment programs across the United States. Participants were 18 years of age or older and scored a two or higher on the heroin or opioid pain reliever sections of the Tobacco, Alcohol, Prescription Medications, and Other Substances (TAPS) Tool. Each participant completed a demographic survey and a telephone interview. The interviews were coded and content analyzed. Results: While some participants preferred receiving OUD treatment from an integrated model in a general medical setting, the majority preferred non-integrated models. Some participants preferred integrated models in theory but expressed concerns about stigma and a lack of psychosocial services. Tradeoffs between integrated and non-integrated models were centered around patient values (desire for anonymity and personalization, fear of consequences), the characteristics of the provider and setting (convenience, perceived treatment effectiveness, access to services), and the patient-provider relationship (disclosure, trust, comfort, stigma). Conclusions: Among this sample of primarily White adults, preferences for non-integrated versus integrated OUD treatment were mixed. Perceived benefits of integrated models included convenience, potential for treatment personalization, and opportunity to extend established relationships with medical providers. Recommendations to make integrated treatment more patient-centered include facilitating access to psychosocial services, educating patients on privacy, individualizing treatment, and prioritizing the patient-provider relationship. This sample included very few minorities and thus findings may not be fully generalizable to the larger population of persons with OUD. Nonetheless, results suggest a need for expansion of both OUD treatment in specialty and general medical settings to ensure access to preferred treatment for all

Natural climate solutions

Our thanks for inputs by L. Almond, A. Baccini, A. Bowman, S. CookPatton, J. Evans, K. Holl, R. Lalasz, A. Nassikas, M. Spalding, M. Wolosin, and expert elicitation respondents. Our thanks for datasets developed by the Hansen lab and the NESCent grasslands working group (C. Lehmann, D. Griffith, T. M. Anderson, D. J. Beerling, W. Bond, E. Denton, E. Edwards, E. Forrestel, D. Fox, W. Hoffmann, R. Hyde, T. Kluyver, L. Mucina, B. Passey, S. Pau, J. Ratnam, N. Salamin, B. Santini, K. Simpson, M. Smith, B. Spriggs, C. Still, C. Strömberg, and C. P. Osborne). This study was made possible by funding from the Doris Duke Charitable Foundation. Woodbury was supported in part by USDA-NIFA Project 2011-67003-30205 Data deposition: A global spatial dataset of reforestation opportunities has been deposited on Zenodo (https://zenodo.org/record/883444). This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1710465114/-/DCSupplemental.Peer reviewedPublisher PD

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function.

BACKGROUND: Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function. METHODS: We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis. RESULTS: The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10(-7)). In addition, meta-analysis using the five cohorts with ≥3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10(-8)) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively. CONCLUSIONS: In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function