WashU weekly Neuroscience publications

The community structure of functional brain networks exhibits scale-specific patterns of inter- and intra-subject variability
(2019) NeuroImage, 202, art. no. 115990, . 

Betzel, R.F.^{a b c} , Bertolero, M.A.^a , Gordon, E.M.^{d e} , Gratton, C.^{f g} , Dosenbach, N.U.F.^{f h i} , Bassett, D.S.^{a j k l m n}

^a Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States
^b Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47401, United States
^c Cognitive Science Program, Indiana University, Bloomington, IN 47401, United States
^d VISN 17 Center of Excellence for Research on Returning War Veterans, Waco, TX 76711, United States
^e Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235, United States
^f Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
^g Department of Psychology, Northwestern University, Evanston, IL 60208, United States
^h Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States
ⁱ Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
^j Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States
^k Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
^l Department of Physics & Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States
^m Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
ⁿ Santa Fe Institute, 1399 Hyde Park Rd, Santa Fe, NM 87501, United States

Abstract
The network organization of the human brain varies across individuals, changes with development and aging, and differs in disease. Discovering the major dimensions along which this variability is displayed remains a central goal of both neuroscience and clinical medicine. Such efforts can be usefully framed within the context of the brain’s modular network organization, which can be assessed quantitatively using computational techniques and extended for the purposes of multi-scale analysis, dimensionality reduction, and biomarker generation. Although the concept of modularity and its utility in describing brain network organization is clear, principled methods for comparing multi-scale communities across individuals and time are surprisingly lacking. Here, we present a method that uses multi-layer networks to simultaneously discover the modular structure of many subjects at once. This method builds upon the well-known multi-layer modularity maximization technique, and provides a viable and principled tool for studying differences in network communities across individuals and within individuals across time. We test this method on two datasets and identify consistent patterns of inter-subject community variability, demonstrating that this variability – which would be undetectable using past approaches – is associated with measures of cognitive performance. In general, the multi-layer, multi-subject framework proposed here represents an advance over current approaches by straighforwardly mapping community assignments across subjects and holds promise for future investigations of inter-subject community variation in clinical populations or as a result of task constraints. © 2019 The Authors

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

An ethnographic decision model of the initiation of gabapentin misuse among prescription and/or illicit opioid (mis)user
(2019) Drug and Alcohol Dependence, 204, art. no. 107554, . 

Buttram, M.E.^a , Kurtz, S.P.^a , Cicero, T.J.^b , Havens, J.R.^c

^a ARSH: Center for Applied Research on Substance Use and Health Disparities, Nova Southeastern University, 7255 NE 4th Ave., Suite 112, Miami, FL 33138, United States
^b Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave., Box 8134, St. Louis, MO 63110, United States
^c Department of Behavioral Science, University of Kentucky, 333 Waller Ave., Suite 480, Lexington, KY 40504, United States

Abstract
Aims: Gabapentin is used in the treatment of seizures and neuralgia, and it is prescribed off-label to treat substance use disorders and withdrawal symptoms. Recent research documents misuse of gabapentin, especially among prescription opioid misusers. The present study contributes to this literature by examining the initiation of gabapentin misuse. Methods: Qualitative interviews were conducted with prescription and/or illicit opioid (mis)users who reported a history of gabapentin misuse (N = 62) and who did not (N = 29). During semi-structured interviews, respondents provided descriptions of the first time they misused gabapentin. An ethnographic decision model was constructed to illustrate the factors that influence the initiation decision. Results: Multiple individual, social, and environmental factors influence the decision to initiate gabapentin misuse. Respondents described the initiation decision related to: a) wanting to feel a psychoactive high during times of limited access to one’s preferred drug because of institutional barriers (e.g., substance abuse treatment; jail; transitional living facility; N = 18); b) the desire to use multiple drugs, including for experimentation or to potentiate another substance (N = 18); and c) the need to self-treat withdrawal symptoms during periods of opioid nonuse or when opioids were unavailable (N = 16). Respondents also initiated gabapentin misuse to self-treat physical pain (N = 10). Conclusions: Multiple approaches are needed to mitigate gabapentin misuse, including limiting availability in institutional settings and informal channels as well as addressing the needs of drug users who experience physical pain and withdrawal symptoms. Continued research is needed to examine therapeutic uses of gabapentin and behaviors related to misuse. © 2019

Author Keywords
Gabapentin;  Opioid;  Qualitative

Document Type: Article
Publication Stage: Final
Source: Scopus

How old is your brain?
(2019) Nature Neuroscience, 22 (10), pp. 1611-1612. 

Bijsterbosch, J.

Department of Radiology, Washington University Medical School, Saint Louis, Missouri, USA

Document Type: Article
Publication Stage: Final
Source: Scopus

Common brain disorders are associated with heritable patterns of apparent aging of the brain
(2019) Nature Neuroscience, 22 (10), pp. 1617-1623. 

Kaufmann, T.^a , van der Meer, D.^{a b} , Doan, N.T.^a , Schwarz, E.^c , Lund, M.J.^a , Agartz, I.^{a d e} , Alnæs, D.^a , Barch, D.M.^{f g h} , Baur-Streubel, R.ⁱ , Bertolino, A.^{j k} , Bettella, F.^a , Beyer, M.K.^{l m} , Bøen, E.^{d n} , Borgwardt, S.^{o p q} , Brandt, C.L.^a , Buitelaar, J.^{r s} , Celius, E.G.^{l t} , Cervenka, S.^e , Conzelmann, A.^u , Córdova-Palomera, A.^a , Dale, A.M.^{v w x y} , de Quervain, D.J.F.^{z aa} , Carlo, P.^k , Djurovic, S.^{ab ac} , Dørum, E.S.^{a ad ae} , Eisenacher, S.^c , Elvsåshagen, T.^{a l t} , Espeseth, T.^ad , Fatouros-Bergman, H.^e , Flyckt, L.^e , Franke, B.^af , Frei, O.^a , Haatveit, B.^{a ad} , Håberg, A.K.^{ag ah} , Harbo, H.F.^{l t} , Hartman, C.A.^ai , Heslenfeld, D.^{aj ak} , Hoekstra, P.J.^al , Høgestøl, E.A.^{l t} , Jernigan, T.L.^{am an ao} , Jonassen, R.^ap , Jönsson, E.G.^{a e} , Kirsch, P.^{aq ar} , Kłoszewska, I.^as , Kolskår, K.K.^{a ad ae} , Landrø, N.I.^{d ad} , Hellard, S.^ac , Lesch, K.-P.^{at au av} , Lovestone, S.^aw , Lundervold, A.^{ax ay} , Lundervold, A.J.^az , Maglanoc, L.A.^{a ad} , Malt, U.F.^{l ba} , Mecocci, P.^bb , Melle, I.^a , Meyer-Lindenberg, A.^c , Moberget, T.^a , Norbom, L.B.^{a ad} , Nordvik, J.E.^bc , Nyberg, L.^bd , Oosterlaan, J.^{aj be} , Papalino, M.^k , Papassotiropoulos, A.^{z bf bg} , Pauli, P.ⁱ , Pergola, G.^k , Persson, K.^{bh bi} , Richard, G.^{a ad ae} , Rokicki, J.^{a ad} , Sanders, A.-M.^{a ad ae} , Selbæk, G.^{l bh bi} , Shadrin, A.A.^a , Smeland, O.B.^a , Soininen, H.^{bj bk} , Sowa, P.^m , Steen, V.M.^{ac bl} , Tsolaki, M.^bm , Ulrichsen, K.M.^{a ad ae} , Vellas, B.^bn , Wang, L.^bo , Westman, E.^{p bp} , Ziegler, G.C.^at , Zink, M.^{c bq} , Andreassen, O.A.^a , Westlye, L.T.^{a ad} , Karolinska Schizophrenia Project (KaSP)^br

^a NORMENT, Division of Mental Health and Addiction Oslo University Hospital & Institute of Clinical Medicine, University of OsloOslo, Norway
^b School of Mental Health and Neuroscience Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
^c Department of Psychiatry and Psychotherapy Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
^d Department of Psychiatry Diakonhjemmet HospitalOslo, Norway
^e Centre for Psychiatry Research, Department of Clinical Neuroscience Karolinska Institutet & Stockholm Health Care Services, Stockholm County CouncilStockholm, Sweden
^f Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, United States
^g Department of Psychiatry Washington, University in St. Louis, St. Louis, United States
^h Department of Radiology Washington, University in St. Louis, St. Louis, United States
ⁱ Department of Psychology I, University of Würzburg, Würzburg, Germany
^j Institute of Psychiatry Bari University HospitalBari, Italy
^k Department of Basic Medical Science, Neuroscience and Sense Organs University of BariBari, Italy
^l Institute of Clinical Medicine, University of OsloOslo, Norway
^m Division of Radiology and Nuclear Medicine, Section of Neuroradiology Oslo University HospitalOslo, Norway
ⁿ Psychosomatic and CL Psychiatry, Division of Mental Health and Addiction, Oslo University HospitalOslo, Norway
^o Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
^p Department of Psychiatry, Psychosomatics and Psychotherapy University of Lübeck, Lübeck, Germany
^q Institute of Psychiatry King’s College, London, United Kingdom
^r Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour Radboud University Medical Center, Nijmegen, Netherlands
^s Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, Netherlands
^t Department of Neurology, Oslo University HospitalOslo, Norway
^u Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy University of Tübingen, Tübingen, Germany
^v Center for Multimodal Imaging and Genetics, University of California at San Diego, La Jolla, CA, United States
^w Department of Radiology, University of California, San Diego, La Jolla, CA, USA
^x Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
^y Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
^z Division of Cognitive Neuroscience, University of Basel, Basel, Switzerland
^aa Transfaculty Research Platform Molecular and Cognitive Neurosciences University of Basel, Basel, Switzerland
^ab Department of Medical Genetics, Oslo University HospitalOslo, Norway
^ac NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
^ad Department of Psychology, University of OsloOslo, Norway
^ae Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
^af Departments of Human Genetics and Psychiatry, Donders Institute for Brain, Cognition and Behaviour Radboud University Medical Center, Nijmegen, Netherlands
^ag Department of Neuromedicine and Movement Science Norwegian, University of Science and Technology, Trondheim, Norway
^ah Department of Radiology and Nuclear Medicine St. Olavs Hospital, Trondheim, Norway
^ai Department of Psychiatry, University of Groningen, University Medical Center GroningenGroningen, Netherlands
^aj Clinical Neuropsychology section Vrije Universiteit Amsterdam, Amsterdam, Netherlands
^ak Department of Cognitive Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
^al Department of Child and Adolescent Psychiatry, University Medical Center Groningen, University of GroningenGroningen, Netherlands
^am Center for Human Development, University of California, San Diego, United States
^an Department of Cognitive Science, University of California, San Diego, United States
^ao Departments of Psychiatry and Radiology, University of California, San Diego, United States
^ap Faculty of Health Sciences, Oslo Metropolitan UniversityOslo, Norway
^aq Department of Clinical Psychology Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
^ar Bernstein Center for Computational Neuroscience Heidelberg/Mannheim, Mannheim, Germany
^as Department of Old Age Psychiatry and Psychotic Disorders Medical University of Lodz, Lodz, Poland
^at Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany
^au Laboratory of Psychiatric Neurobiology, Institute of Molecular Medicine Sechenov First Moscow State Medical UniversityMoscow, Russian Federation
^av Department of Neuroscience, School for Mental Health and Neuroscience (MHeNS) Maastricht University, Maastricht, Netherlands
^aw Department of Psychiatry, Warneford Hospital University of Oxford, Oxford, United Kingdom
^ax Department of Biomedicine, University of Bergen, Bergen, Norway
^ay Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
^az Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
^ba Department of Research and Education, Oslo University HospitalOslo, Norway
^bb Institute of Gerontology and Geriatrics, University of Perugia, Perugia, Italy
^bc CatoSenteret Rehabilitation Center SonOslo, Norway
^bd Departments of Radiation Sciences and Integrative Medical Biology, Umeå Center for Functional Brain Imaging Umeå University, Umeå, Sweden
^be Emma Children’s Hospital, Amsterdam UMC University of Amsterdam and Vrije Universiteit Amsterdam, Emma Neuroscience Group, Department of Pediatrics, Amsterdam Reproduction & Development, Amsterdam, Netherlands
^bf Division of Molecular Neuroscience University of Basel, Basel, Switzerland
^bg Life Sciences Training Facility, Department Biozentrum University of Basel, Basel, Switzerland
^bh Department of Geriatric Medicine, Oslo University HospitalOslo, Norway
^bi Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Norway
^bj Department of Neurology, Institute of Clinical Medicine University of Eastern Finland, Kuopio, Finland
^bk Neurocenter, Neurology Kuopio University Hospital, Kuopio, Finland
^bl Dr. E. Martens Research Group for Biological Psychiatry, Department of Medical Genetics Haukeland University Hospital, Bergen, Norway
^bm 1st Department of Neurology Aristotle University of Thessaloniki, Thessaloniki, Greece
^bn UMR Inserm 1027, CHU Toulouse, UPS, Toulouse, France
^bo Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, United States
^bp Department of Neurobiology Care Sciences and Society, Karolinska InstituteStockholm, Sweden
^bq District hospital Ansbach, Ansbach, Germany

Abstract
Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.

Document Type: Article
Publication Stage: Final
Source: Scopus

Fragmented mitochondria released from microglia trigger A1 astrocytic response and propagate inflammatory neurodegeneration
(2019) Nature Neuroscience, 22 (10), pp. 1635-1648. 

Joshi, A.U.^a , Minhas, P.S.^b , Liddelow, S.A.^{c d e} , Haileselassie, B.^{a f} , Andreasson, K.I.^b , Dorn, G.W., 2nd^g , Mochly-Rosen, D.^h

^a Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
^b Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
^c Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
^d Department of Neuroscience and Physiology and Neuroscience Institute, New York University Langone Medical Center, NY, NY, United States
^e Department of Pharmacology and Therapeutics, University of Melbourne, Melbourne, VIC, Australia
^f Department of Pediatrics Division of Critical Care Medicine, Stanford University School of Medicine, Stanford, CA, USA
^g Center for Pharmacogenomics, Department of Internal Medicine, Washington University School of Medicine, St Louis, MO, USA
^h Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA. mochly@stanford.edu

Abstract
In neurodegenerative diseases, debris of dead neurons are thought to trigger glia-mediated neuroinflammation, thus increasing neuronal death. Here we show that the expression of neurotoxic proteins associated with these diseases in microglia alone is sufficient to directly trigger death of naive neurons and to propagate neuronal death through activation of naive astrocytes to the A1 state. Injury propagation is mediated, in great part, by the release of fragmented and dysfunctional microglial mitochondria into the neuronal milieu. The amount of damaged mitochondria released from microglia relative to functional mitochondria and the consequent neuronal injury are determined by Fis1-mediated mitochondrial fragmentation within the glial cells. The propagation of the inflammatory response and neuronal cell death by extracellular dysfunctional mitochondria suggests a potential new intervention for neurodegeneration-one that inhibits mitochondrial fragmentation in microglia, thus inhibiting the release of dysfunctional mitochondria into the extracellular milieu of the brain, without affecting the release of healthy neuroprotective mitochondria.

Document Type: Article
Publication Stage: Final
Source: Scopus

Medication-Assisted Treatment for Opioid-Use Disorder
(2019) Mayo Clinic Proceedings, 94 (10), pp. 2072-2086. 

Oesterle, T.S.^a , Thusius, N.J.^a , Rummans, T.A.^{a b} , Gold, M.S.^c

^a Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
^b Mayo Clinic, Jacksonville, FL, United States
^c Washington University School of Medicine, Department of Psychiatry, and National Council, Washington University in St. Louis, Institute for Public Health, St. Louis, MO, United States

Abstract
The United States is in the midst of a national opioid epidemic. Physicians are encouraged both to prevent and treat opioid-use disorders (OUDs). Although there are 3 Food and Drug Administration-approved medications to treat OUD (methadone, buprenorphine, and naltrexone) and there is ample evidence of their efficacy, they are not used as often as they should. We provide a brief review of the 3 primary medications used in the treatment of OUD. Using data from available medical literature, we synthesize existing knowledge and provide a framework for how to determine the optimal approach for outpatient management of OUD with medication-assisted treatments. © 2019 Mayo Foundation for Medical Education and Research

Document Type: Review
Publication Stage: Final
Source: Scopus

School-based programs for Supporting the mental health and psychosocial wellbeing of adolescent forced migrants in high-income countries: A scoping review
(2019) Social Science and Medicine, 239, art. no. 112558, . 

Bennouna, C.^a , Khauli, N.^b , Basir, M.^c , Allaf, C.^d , Wessells, M.^c , Stark, L.^e

^a Department of Political Science, Brown University, United States
^b Department of Psychiatry, Columbia University Medical Center, United States
^c Mailman School of Public Health, Columbia University, United States
^d Qatar Foundation International, United States
^e Brown School at Washington University in St. Louis, United States

Abstract
As communities around the world continue to receive record-setting numbers of newcomers fleeing armed conflict, schools play a central role in supporting these families through the challenges of adjustment. Policymakers and educators in several high-income countries have begun to invest in efforts to support these young forced migrants not only academically, but also socially and emotionally. This study reviews the published and grey literature on 20 school-based programs aimed at improving the mental health and psychosocial wellbeing of adolescent forced migrants in high-income countries from 2000 to 2019. This review seeks to inform a more comprehensive and detailed understanding of the types of program options available to schools, while also identifying gaps in the current literature related to factors influencing program implementation. We find several common approaches and challenges to supporting adolescent forced migrants, as well as their families, communities, schools, and service providers. The reviewed programs faced recurring challenges related to intercultural exchange, gaining access to communities, promoting care-seeking, school capacity limitations, and sustainability. The lessons learned from these programs indicate that several steps can be taken to mitigate these challenges, including adapting services to individuals and their contexts, taking a multi-layered approach that addresses multiple levels of young people’s social ecologies, and building trusting, collaborative partnerships with schools, communities, and students. © 2019

Author Keywords
Armed conflict;  Mental health and psychosocial support (MHPSS);  Refugee;  School;  Social and emotional learning

Document Type: Review
Publication Stage: Final
Source: Scopus

Nmnat restores neuronal integrity by neutralizing mutant Huntingtin aggregate-induced progressive toxicity
(2019) Proceedings of the National Academy of Sciences of the United States of America, 116 (38), pp. 19165-19175. 

Zhu, Y.^a , Li, C.^{a b} , Tao, X.^a , Brazill, J.M.^{a c} , Park, J.^a , Diaz-Perez, Z.^a , Grace Zhai, R.^a

^a Department of Molecular and Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, United States
^b Institute of Molecular Biotechnology, Austrian Academy of Sciences (IMBA), Vienna, 1030, Austria
^c Department of Medicine, Division of Bone and Mineral Diseases, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States

Abstract
Accumulative aggregation of mutant Huntingtin (Htt) is a primary neuropathological hallmark of Huntington’s disease (HD). Currently, mechanistic understanding of the cytotoxicity of mutant Htt aggregates remains limited, and neuroprotective strategies combating mutant Htt-induced neurodegeneration are lacking. Here, we show that in Drosophila models of HD, neuronal compartment-specific accumulation of mutant Htt aggregates causes neurodegenerative phenotypes. In addition to the increase in the number and size, we discovered an age-dependent acquisition of thioflavin S+, amyloid-like adhesive properties of mutant Htt aggregates and a concomitant progressive clustering of aggregates with mitochondria and synaptic proteins, indicating that the amyloid-like adhesive property underlies the neurotoxicity of mutant Htt aggregation. Importantly, nicotinamide mononucleotide adenylyltransferase (NMNAT), an evolutionarily conserved nicotinamide adenine dinucleotide (NAD+) synthase and neuroprotective factor, significantly mitigates mutant Htt-induced neurodegeneration by reducing mutant Htt aggregation through promoting autophagic clearance. Additionally, Nmnat overexpression reduces progressive accumulation of amyloid-like Htt aggregates, neutralizes adhesiveness, and inhibits the clustering of mutant Htt with mitochondria and synaptic proteins, thereby restoring neuronal function. Conversely, partial loss of endogenous Nmnat exacerbates mutant Htt-induced neurodegeneration through enhancing mutant Htt aggregation and adhesive property. Finally, conditional expression of Nmnat after the onset of degenerative phenotypes significantly delays the progression of neurodegeneration, revealing the therapeutic potential of Nmnat-mediated neuroprotection at advanced stages of HD. Our study uncovers essential mechanistic insights to the neurotoxicity of mutant Htt aggregation and describes the molecular basis of Nmnat-mediated neuroprotection in HD. © 2019 National Academy of Sciences. All rights reserved.

Author Keywords
Aggregate;  Amyloid;  Huntington’s disease;  Mitochondria;  Nmnat

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Multispectral tracing in densely labeled mouse brain with nTracer
(2019) Bioinformatics (Oxford, England), 35 (18), pp. 3544-3546. 

Roossien, D.H.^a , Sadis, B.V.^a , Yan, Y.^a , Webb, J.M.^b , Min, L.Y.^{a c d} , Dizaji, A.S.^a , Bogart, L.J.^e , Mazuski, C.^b , Huth, R.S.^a , Stecher, J.S.^a , Akula, S.^a , Shen, F.^a , Li, Y.^a , Xiao, T.^f , Vandenbrink, M.^a , Lichtman, J.W.^{g h} , Hensch, T.K.^{e g h} , Herzog, E.D.^b , Cai, D.^a

^a Department of Cell and Developmental Biology, University of Michigan Medical School, MI, Ann Arbor, United States
^b Department of Biology, Washington University in St. Louis, St. Louis, MO, USA
^c Life Sciences Institute, University of Michigan, MI, Ann Arbor, United States
^d School of Art and Design, University of Michigan, MI, Ann Arbor, United States
^e Department of Neurology, Boston Children’s Hospital, Harvard Medical School, MA, Boston, United States
^f Department of Biology, University of Toronto, ON, Toronto, Canada
^g Department of Molecular and Cellular Biology Cambridge, MA, United States
^h Center for Brain Science, Harvard University, MA, Cambridge, United States

Abstract
SUMMARY: This note describes nTracer, an ImageJ plug-in for user-guided, semi-automated tracing of multispectral fluorescent tissue samples. This approach allows for rapid and accurate reconstruction of whole cell morphology of large neuronal populations in densely labeled brains. AVAILABILITY AND IMPLEMENTATION: nTracer was written as a plug-in for the open source image processing software ImageJ. The software, instructional documentation, tutorial videos, sample image and sample tracing results are available at https://www.cai-lab.org/ntracer-tutorial. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. © The Author(s) 2019. Published by Oxford University Press.

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Association of Timing of Adverse Childhood Experiences and Caregiver Support With Regionally Specific Brain Development in Adolescents
(2019) JAMA Network Open, 2 (9), p. e1911426. 

Luby, J.L.^a , Tillman, R.^b , Barch, D.M.^{b c}

^a Department of Psychiatry (Child), School of Medicine, Washington University in St Louis, St Louis, MO, United States
^b Department of Psychiatry, School of Medicine, Washington University in St Louis, St Louis, MO, United States
^c Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO, United States

Abstract
Importance: Few data are available to inform the associations and timing of the associations between adversity, caregiver support, and brain outcomes. Consideration of timing has important public health implications to inform more precise prevention strategies. Objective: To evaluate the timing and regional specificity of the association between adverse childhood experiences (ACEs) and caregiver support to structural development of limbic and striatal brain regions in middle childhood and adolescence. Design, Setting, and Participants: This 15-year developmental, neuroimaging cohort study included 211 children and their caregivers screened from day care centers and preschools in the St Louis, Missouri, metropolitan area during the preschool period, with an additional 4 waves of neuroimaging at school age through adolescence from November 14, 2007, to August 29, 2017. The cohort was oversampled for preschoolers with elevated symptoms of depression using a brief screener. Data analysis was performed from March 19, 2019, to July 26, 2019. Main Outcomes and Measures: Volumes in adolescence and developmental trajectories of volumes of the amygdala, hippocampus, caudate, subgenual cingulate, and insula during 4 waves of scanning; ACEs and observed caregiver support at preschool and school age; and volumes of amygdala, hippocampus, insula, and subgenual cingulate during 4 waves of scanning. Results: A total of 211 children (107 [50.7%] male) completed at least 1 scan. At preschool (mean [SD] age, 5.5 [0.8] years), ACE data were available for 164 children (84 [51.2%] male) and maternal support data for 155 children; at school age (mean [SD], 8.3 [1.2] years), ACE data were available for 172 children and maternal support data for 146 children. Unique patterns of the association between ACEs and support were found, with an association between the interaction of preschool ACEs and school-age support and the development of the hippocampus (t = -2.27; P = .02) and amygdala (t = -2.12; P = .04). A buffering hypothesis was not confirmed because high caregiver support was more strongly associated with the development of these regions only in the context of low ACEs. In contrast, preschool ACEs (t = -2.30; P = .02) and support (t = 2.59; P = .01) had independent associations with the development of the caudate. Conclusions and Relevance: The findings suggest that there are unique regional associations of support and adversity with key brain structures important for emotional regulation. Results may inform the timing and potential targets of preventive action for the range of poor developmental outcomes.

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

Steady-state activation and modulation of the synaptic-type α1β2γ2L GABAA receptor by combinations of physiological and clinical ligands
(2019) Physiological Reports, 7 (18), p. e14230. 

Germann, A.L.^a , Pierce, S.R.^a , Senneff, T.C.^a , Burbridge, A.B.^a , Steinbach, J.H.^{a b} , Akk, G.^{a b}

^a Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO, United States
^b Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, MO, United States

Abstract
The synaptic α1β2γ2 GABAA receptor is activated phasically by presynaptically released GABA. The receptor is considered to be inactive between synaptic events when exposed to ambient GABA because of its low resting affinity to the transmitter. We tested the hypothesis that a combination of physiological and/or clinical positive allosteric modulators of the GABAA receptor with ambient GABA generates measurable steady-state activity. Recombinant α1β2γ2L GABAA receptors were expressed in Xenopus oocytes and activated by combinations of low concentrations of orthosteric (GABA, taurine) and allosteric (the steroid allopregnanolone, the anesthetic propofol) agonists, in the absence and presence of the inhibitory steroid pregnenolone sulfate. Steady-state activity was analyzed using the three-state cyclic Resting-Active-Desensitized model. We estimate that the steady-state open probability of the synaptic α1β2γ2L GABAA receptor in the presence of ambient GABA (1 μmol/L), taurine (10 μmol/L), and physiological levels of allopregnanolone (0.01 μmol/L) and pregnenolone sulfate (0.1 μmol/L) is 0.008. Coapplication of a clinical concentration of propofol (1 μmol/L) increases the steady-state open probability to 0.03. Comparison of total charge transfer for phasic and tonic activity indicates that steady-state activity can contribute strongly (~20 to >99%) to integrated activity from the synaptic GABAA receptor. © 2019 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.

Author Keywords
Anesthetics;  electrophysiology;  GABAA receptors;  neurosteroids

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

High-density functional diffuse optical tomography based on frequency-domain measurements improves image quality and spatial resolution
(2019) Neurophotonics, 6 (3), art. no. 035007, . 

Doulgerakis, M.^a , Eggebrecht, A.T.^b , Dehghani, H.^a

^a University of Birmingham, School of Computer Science, Birmingham, United Kingdom
^b Washington University, School of Medicine, Mallinckrodt Institute of Radiology, St. Louis, MO, United States

Abstract
Measurements of dynamic near-infrared (NIR) light attenuation across the human head together with model-based image reconstruction algorithms allow the recovery of three-dimensional spatial brain activation maps. Previous studies using high-density diffuse optical tomography (HD-DOT) systems have reported improved image quality over sparse arrays. These HD-DOT systems incorporated multidistance overlapping continuous wave measurements that only recover differential intensity attenuation. We investigate the potential improvement in reconstructed image quality due to the additional incorporation of phase shift measurements, which reflect the time-of-flight of the measured NIR light, within the tomographic reconstruction from high-density measurements. To evaluate image reconstruction with and without the additional phase information, we simulated point spread functions across a whole-scalp field of view in 24 subject-specific anatomical models using an experimentally derived noise model. The addition of phase information improves the image quality by reducing localization error by up to 59% and effective resolution by up to 21% as compared to using the intensity attenuation measurements alone. Furthermore, we demonstrate that the phase data enable images to be resolved at deeper brain regions where intensity data fail, which is further supported by utilizing experimental data from a single subject measurement during a retinotopic experiment. © The Authors.

Author Keywords
Frequency domain;  Functional near-infrared imaging;  High density diffuse optical tomography

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

A learning framework for controlling spiking neural networks
(2019) Proceedings of the American Control Conference, 2019-July, art. no. 8815197, pp. 211-216. 

Narayanan, V.^a , Ritt, J.T.^b , Li, J.-S.^{a c} , Ching, S.^{a c}

^a Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, United States
^b Department of Biomedical Engineering, Boston University, Boston, MA, United States
^c Department of Biomedical Engineering, Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, MO, United States

Abstract
Controlling a population of interconnected neurons using extrinsic stimulation is a challenging problem. The challenges are due to the inherent nonlinear neuronal dynamics, the highly complex structure of underlying neuronal networks, the underactuated nature of the control problem, and adding to these is the binary nature of the observation/feedback. To meet these challenges, adaptive, learning-based approaches using deep neural networks and reinforcement learning are potentially useful strategies. In this paper, we propose an approximation based learning framework in which a model for approximating the input-output relationship in a spiking neuron is developed. We then present a reinforcement learning scheme to approximate the solution for the Bellman equation, and to design the control sequence to achieve a desired spike pattern. The proposed strategy, by integrating the reinforcement learning and system theoretic approaches, provides a tractable framework to design a learning control network, and to select the hyper parameters in deep learning architectures. We demonstrate the feasibility of the proposed approach using numerical simulations. © 2019 American Automatic Control Council.

Document Type: Conference Paper
Publication Stage: Final
Source: Scopus

Defining information-based functional objectives for neurostimulation and control
(2019) Proceedings of the American Control Conference, 2019-July, art. no. 8814601, pp. 866-871. 

Ghazizadeh, E., Yi, P., Ching, S.

Department of Electrical and Systems Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, MO 63130, United States

Abstract
Neurostimulation – the practice of applying exogenous excitation, e.g., via electrical current, to the brain – has been used for decades in clinical applications such as the treatment of motor disorders and neuropsychiatric illnesses. Over the past several years, more emphasis has been placed on understanding and designing neurostimulation from a systems-theoretic perspective, so as to better optimize its use. Particular questions of interest have included designing stimulation waveforms that best induce certain patterns of brain activity while minimizing expenditure of stimulus power. The pursuit of these designs faces a fundamental conundrum, insofar as they presume that the desired pattern (e.g., desyn-chronization of a neural population) is known a priori. In this paper, we present an alternative paradigm wherein the goal of the stimulation is not to induce a prescribed pattern, but rather to simply improve the functionality of the stimulated circuit/system. Here, the notion of functionality is defined in terms of an information-theoretic objective. Specifically, we seek closed loop control designs that maximize the ability of a controlled circuit to encode an afferent ‘hidden input,’ without prescription of dynamics or output. In this way, the control attempts only to make the system ‘effective’ without knowing beforehand the dynamics that are needed to be induced. We devote most of our effort to defining this framework mathematically, providing algorithmic procedures that demonstrate its solution and interpreting the results of this procedure for simple, prototypical dynamical systems. Simulation results are provided for more complex models, including an example involving control of a canonical neural mass model. © 2019 American Automatic Control Council.

Document Type: Conference Paper
Publication Stage: Final
Source: Scopus

Behavioral analyses of animal models of intellectual and developmental disabilities
(2019) Neurobiology of Learning and Memory, art. no. 107087, . 

Crawley, J.N.^a , Fagiolini, M.^b , Harrison, F.E.^c , Samaco, R.^d , Wozniak, D.F.^e , Robinson, M.B.^f

^a MIND Institute, Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95821, United States
^b Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Boston, MA 02459, United States
^c Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37323, United States
^d Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, United States
^e Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
^f Departments of Pediatrics and Systems Pharmacology & Translational Therapeutics, Children’s Hospital of Philadelphia/University of Pennsylvania, Philadelphia, PA 19104, United States

Abstract
Intellectual and developmental disabilities (IDDs) are a common group of disorders that frequently share overlapping symptoms, including cognitive deficits, altered attention, seizures, impaired social interactions, and anxiety. The causes of these disorders are varied ranging from early prenatal/postnatal insults to genetic variants that either cause or are associated with an increased likelihood of an IDD. As many of the symptoms observed in individuals with IDDs are a manifestation of altered nervous system function resulting in altered behaviors, it should not be surprising that the field is very dependent upon in vivo model systems. This special issue of Neurobiology of Learning and Memory is focused on the methods and approaches that are being used to model and understand these disorders in mammals. While surveys by the Pew Foundation continue to find a high degree of confidence/trust in scientists by the public, several recent studies have documented issues with reproducibility in scientific publications. This special issue includes both primary research articles and review articles in which careful attention has been made to transparently report methods and use rigorous approaches to ensure reproducibility. Although there have been and will continue to be remarkable advances for treatment of subset of IDDs, it is clear that this field is still in its early stages. There is no doubt that the strategies being used to model IDDs will continue to evolve. We hope this special issue will support this evolution so that we can maintain the trust of the public and elected officials, and continue developing evidence-based approaches to new therapeutics. © 2019 Elsevier Inc.

Document Type: Editorial
Publication Stage: Article in Press
Source: Scopus

Stroke Factors Associated with Thrombolysis Use in Hospitals in Singapore and US: A Cross-Registry Comparative Study
(2019) Cerebrovascular diseases (Basel, Switzerland), 47 (5-6), pp. 291-298. 

Ng, S.H.-X.^a , Wong, A.W.K.^b , Chen, C.H.^a , Tan, C.S.^a , Müller-Riemenschneider, F.^{a c} , Chan, B.P.L.^d , Baum, M.C.^b , Lee, J.-M.^e , Venketasubramanian, N.^f , Koh, G.C.-H.^g

^a Saw Swee Hock School of Public Health, National University Health System, Singapore
^b Department of Neurology, Program in Occupational Therapy, Washington University in St Louis, St. Louis, MO, United States
^c Institute for Social Medicine, Epidemiology and Health Economics, Charite University Medical CentreBerlin, Germany
^d Division of Neurology, National University Hospital, National University Health System, Singapore
^e Department of Neurology, Washington University in St Louis, St. Louis, MO, United States
^f Raffles Neuroscience Centre, Raffles Hospital, Singapore
^g Saw Swee Hock School of Public Health, National University Health System, Singapore

Abstract
BACKGROUND AND OBJECTIVES: This paper aims to describe and compare the characteristics of 2 stroke populations in Singapore and in St. Louis, USA, and to document thrombolysis rates and contrast factors associated with its uptake in both populations. METHODS: The stroke populations described were from the Singapore Stroke Registry (SSR) in -Singapore and the Cognitive Rehabilitation Research Group Stroke Registry (CRRGSR) in St. Louis, MO, USA. The registries were compared in terms of demographics and stroke risk factor history. Logistic regression was used to determine factors associated with thrombolysis uptake. RESULTS: A total of 39,323 and 8,106 episodes were recorded in SSR and CRRGSR, respectively, from 2005 to 2012. Compared to CRRGSR, patients in SSR were older, male, and from the ethnic majority. Thrombolysis rates in SSR and CRRGSR were 2.5 and 8.2%, respectively, for the study period. History of ischemic heart disease or atrial fibrillation was associated with increased uptake in both populations, while history of stroke was associated with lower uptake. For SSR, younger age and males were associated with increased uptake, while having a history of smoking or diabetes was associated with decreased uptake. For CRRGSR, ethnic minority status was associated with decreased uptake. CONCLUSIONS: The comparison of stroke populations in Singapore and St Louis revealed distinct differences in clinicodemographics of the 2 groups. Thrombolysis uptake was driven by nonethnicity demographics in Singapore. Ethnicity was the only demographic driver of uptake in the CRRGSR population, highlighting the need to target ethnic minorities in increasing access to thrombolysis. © 2019 S. Karger AG, Basel.

Author Keywords
International comparison;  Stroke;  Thrombolysis;  Treatment

Document Type: Article
Publication Stage: Final
Source: Scopus

Younger Patients Are Differentially Affected by Stiffness-Related Disability Following Adult Spinal Deformity Surgery
(2019) World Neurosurgery, . 

Durand, W.M.^b , Daniels, A.H.^a , Hamilton, D.K.^c , Passias, P.G.^d , Kim, H.J.^e , Protopsaltis, T.^d , Lafage, V.^e , Smith, J.S.^f , Shaffrey, C.^g , Gupta, M.^h , Kelly, M.P.^h , Klineberg, E.ⁱ , Schwab, F.^e , Burton, D.^j , Bess, S.^k , Ames, C.^l , Hart, R.^m , International Spine Study Groupⁿ

^a Department of Orthopaedics, Warren Alpert Medical School of Brown University, Providence, RI, United States
^b Warren Alpert Medical School of Brown University, Providence, RI, United States
^c Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, United States
^d Department of Orthopedics, NYU Langone Orthopedic Hospital, New York, NY, United States
^e Department of Orthopedic Surgery, Hospital for Special Surgery, New York, NY, United States
^f Department of Neurological Surgery, University of Virginia Health System, Charlottesville, VA, United States
^g Spine Division, Duke University, Durham, NC, United States
^h Department of Orthopedic Surgery, Washington University, St. Louis, MO, United States
ⁱ Department of Orthopedic Surgery, University of California, Davis, Sacramento, CA, United States
^j Department of Orthopedic Surgery, University of Kansas Hospital, Kansas City, KS, United States
^k Department of Orthopedic Surgery, Denver International Spine Center, Denver, CO, United States
^l Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
^m Department of Orthopedic Surgery, Swedish Neuroscience Institute, Seattle, WA, United States

Abstract
Objective: The Lumbar Stiffness Disability Index (LSDI) assesses impact of lumbar stiffness on activities of daily living. We hypothesized that patients <60 years old would perceive greater lumbar stiffness–related functional limitation following fusion for adult spinal deformity. Methods: Patients completed the LSDI and Scoliosis Research Society 22 Questionnaire, Revised (SRS-22r) preoperatively and at 2 years postoperatively. The primary independent variable was patient age <60 versus ≥60. Multivariable regression analyses were used. Results: Analysis included 267 patients. Patients <60 years old (51.3%) and ≥60 years old (48.7%) were evenly represented. In bivariable analysis, patients age <60 exhibited lower LSDI at baseline versus patients age ≥60 (25.7 vs. 35.5, β −9.8, P < 0.0001), but a directionally smaller difference at 2 years (26.4 vs. 32.3, β −5.8, P = 0.0147). LSDI was associated with lower SRS-22r total score among both age groups at baseline and 2 years (all P < 0.0001); the association was stronger among patients age <60 versus ≥60 at 2 years. LSDI was associated with SRS-22r satisfaction scores at 2 years among patients age <60 (P < 0.0001), but not patients age ≥60 (P = 0.2250). The difference in SRS-22r satisfaction per unit LSDI between patients <60 years old and ≥60 years old was significant (P = 0.0021). Conclusions: Among patients with adult spinal deformity managed operatively, higher LSDI was associated with inferior SRS-22r total score and satisfaction at 2 years postoperatively. The association between increased LSDI and worse patient-reported outcome measures was greater among patients age <60 versus ≥60. Preoperative counseling is needed for patients age <60 undergoing adult spinal deformity surgery regarding effects that lumbar stiffness may have on postoperative function and satisfaction. © 2019 Elsevier Inc.

Author Keywords
Adult spinal deformity;  HRQOL;  Lumbar spine stiffness

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Factors Associated with Frequent Opioid Use in Children with Acute Recurrent and Chronic Pancreatitis
(2019) Journal of Pediatric Gastroenterology and Nutrition, . 

Perito, E.R.^a , Palermo, T.M.^b , Pohl, J.F.^c , Mascarenhas, M.^d , Abu-El-Haija, M.^e , Barth, B.^f , Bellin, M.D.^g , Fishman, D.S.^h , Freedman, S.ⁱ , Gariepy, C.^j , Giefer, M.^b , Gonska, T.^k , Heyman, M.B.^a , Himes, R.W.^h , Husain, S.Z.^l , Lin, T.^e , Liu, Q.^m , Maqbool, A.^d , McFerron, B.ⁿ , Morinville, V.D.^o , Nathan, J.D.^p , Ooi, C.Y.^q , Rhee, S.^a , Schwarzenberg, S.J.^g , Shah, U.^r , Troendle, D.M.^f , Werlin, S.^s , Wilschanski, M.^t , Zheng, Y.^u , Zimmerman, M.B.^v , Lowe, M.^w , Uc, A.^x

^a Department of Pediatrics, University of California San Francisco, San Francisco, CA, United States
^b Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, United States
^c Department of Pediatrics, University of Utah, Salt Lake City, UT, United States
^d Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
^e Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
^f Department of Pediatrics, University of Texas Southwestern, Dallas, TX, United States
^g Department of Pediatrics, University of Minnesota, Minneapolis, MN, United States
^h Department of Pediatrics, Texas Children’s Hospital, Houston, TX, United States
ⁱ Harvard University, Boston, MA, United States
^j Department of Pediatrics, Nationwide Children’s Hospital, Columbus, OH, United States
^k Department of Pediatrics, Sick Kids Hospital, University of Toronto, Toronto, ON, Canada
^l Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, United States
^m Department of Pediatrics, Cedars-Sinai, Los Angeles, CA, United States
ⁿ Department of Pediatrics, Indiana University, Indianapolis, IN, United States
^o Department of Pediatrics, Montreal Children’s Hospital, McGill University, Montreal, QC, Canada
^p Department of Pediatric General and Thoracic Surgery, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
^q School of Women’s and Children’s Health, Medicine, University of New South Wales, Sydney, NSW, Australia
^r Department of Pediatrics, Massachusetts General Hospital, Boston, MA, United States
^s Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, United States
^t Hadassah University, Jerusalem, Israel
^u Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, CA, United States
^v Department of Biostatistics, University of Iowa, Iowa City, IA, United States
^w Department of Pediatrics, Washington University, St. Louis, MO, United States
^x Stead Family Department of Pediatrics, University of Iowa, Iowa City, IA, United States

Abstract
The aim of the study was to understand the association of frequent opioid use with disease phenotype and pain pattern and burden in children and adolescents with acute recurrent (ARP) or chronic pancreatitis (CP). Methods: Cross-sectional study of children <19 years with ARP or CP, at enrollment into the INSPPIRE cohort. We categorized patients as opioid “frequent use” (daily/weekly) or “nonfrequent use” (monthly or less, or no opioids), based on patient and parent self-report. Results: Of 427 children with ARP or CP, 17% reported frequent opioid use. More children with CP (65%) reported frequent opioid use than with ARP (41%, P = 0.0002). In multivariate analysis, frequent opioid use was associated with older age at diagnosis (odds ratio [OR] 1.67 per 5 years, 95% confidence interval [CI] 1.13-2.47, P = 0.01), exocrine insufficiency (OR 2.44, 95% CI 1.13-5.24, P = 0.02), constant/severe pain (OR 4.14, 95% CI 2.06-8.34, P < 0.0001), and higher average pain impact score across all 6 functional domains (OR 1.62 per 1-point increase, 95% CI 1.28-2.06, P < 0.0001). Children with frequent opioid use also reported more missed school days, hospitalizations, and emergency room visits in the past year than children with no frequent use (P < 0.0002 for each). Participants in the US West and Midwest accounted for 83% of frequent opioid users but only 56% of the total cohort. Conclusions: In children with CP or ARP, frequent opioid use is associated with constant pain, more healthcare use, and higher levels of pain interference with functioning. Longitudinal and prospective research is needed to identify risk factors for frequent opioid use and to evaluate nonopioid interventions for reducing pain and disability in these children. © ESPGHAN and NASPGHAN. All rights reserved.

Author Keywords
chronic pain;  opioids;  pain medication;  pancreatitis;  pediatric

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

A Human Depression Circuit Derived From Focal Brain Lesions
(2019) Biological Psychiatry, . 

Padmanabhan, J.L.^{a b c} , Cooke, D.^b , Joutsa, J.^{b e f} , Siddiqi, S.H.^{a b c d g} , Ferguson, M.^b , Darby, R.R.^h , Soussand, L.^b , Horn, A.ⁱ , Kim, N.Y.^{b j} , Voss, J.L.^{k l} , Naidech, A.M.^{k l} , Brodtmann, A.^{o p} , Egorova, N.^{o p} , Gozzi, S.^{q r} , Phan, T.G.^{q r} , Corbetta, M.^{s t} , Grafman, J.^{m n} , Fox, M.D.^{b c}

^a Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
^b Berenson-Allen Center for Non-Invasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
^c Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
^d Division of Neurotherapeutics, McLean Hospital, Harvard Medical School, Boston, MA, United States
^e Department of Neurology, University of Turku, Turku, Finland
^f Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland
^g Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
^h Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
ⁱ Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité—University Medicine Berlin, Berlin, Germany
^j Department and Research Institute of Rehabilitation Medicine, Yonsei University College of Medicine, Seoul, South Korea
^k Ken and Ruth Davee Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
^l Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
^m Psychiatry and Behavioral Sciences and Cognitive Neurology/Alzheimer’s Disease Research Center, Feinberg School of Medicine and Department of Psychology, Northwestern University, Chicago, IL, United States
ⁿ Shirley Ryan AbilityLab, Chicago, IL, United States
^o Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
^p Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Victoria, Australia
^q School of Psychological Sciences, Department of Medicine, Monash University, Melbourne, Victoria, Australia
^r Stroke and Aging Research Group, School of Clinical Sciences, Department of Medicine, Monash University and Stroke Unit, Monash Medical Centre, Melbourne, Victoria, Australia
^s Department of Neuroscience, University of Padova and Padova Neuroscience Center, Padova, Italy
^t Departments of Neurology, Radiology, Bioengineering, and Neuroscience, Washington University School of Medicine, Saint Louis, MO, United States

Abstract
Background: Focal brain lesions can lend insight into the causal neuroanatomical substrate of depression in the human brain. However, studies of lesion location have led to inconsistent results. Methods: Five independent datasets with different lesion etiologies and measures of postlesion depression were collated (N = 461). Each 3-dimensional lesion location was mapped to a common brain atlas. We used voxel lesion symptom mapping to test for associations between depression and lesion locations. Next, we computed the network of regions functionally connected to each lesion location using a large normative connectome dataset (N = 1000). We used these lesion network maps to test for associations between depression and connected brain circuits. Reproducibility was assessed using a rigorous leave-one-dataset-out validation. Finally, we tested whether lesion locations associated with depression fell within the same circuit as brain stimulation sites that were effective for improving poststroke depression. Results: Lesion locations associated with depression were highly heterogeneous, and no single brain region was consistently implicated. However, these same lesion locations mapped to a connected brain circuit, centered on the left dorsolateral prefrontal cortex. Results were robust to leave-one-dataset-out cross-validation. Finally, our depression circuit derived from brain lesions aligned with brain stimulation sites that were effective for improving poststroke depression. Conclusions: Lesion locations associated with depression fail to map to a specific brain region but do map to a specific brain circuit. This circuit may have prognostic utility in identifying patients at risk for poststroke depression and therapeutic utility in refining brain stimulation targets. © 2019 Society of Biological Psychiatry

Author Keywords
Depression;  Functional connectivity;  Functional MRI;  Imaging;  Lesion;  Network;  Stroke

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

Preimplant hearing aid fittings and aided audibility for pediatric cochlear implant recipients
(2019) Journal of the American Academy of Audiology, 30 (8), pp. 703-711. 

Nickerson, A.^a , Davidson, L.S.^{b c d} , Uchanski, R.M.^{b c}

^a Department of Speech and Hearing Science, University of Illinois, Champaign, IL, United States
^b Program in Audiology and Communication Science, St. Louis, MO, United States
^c Department of Otolaryngology, Washington University School of Medicine, St. Louis, MO, United States
^d Central Institute for the Deaf, St. Louis, MO, United States

Abstract
Background: Audibility of speech for children with hearing loss (HL) depends on the degree of HL and the fitting of the hearing aids (HAs) themselves. Many studies on cochlear implant (CI) users have demonstrated that preimplant hearing is associated with postimplant outcomes, but there have been very few reports on the fitting of HAs before surgery. Purpose: The aims of this study were to characterize HA fittings and aided audibility of speech for pediatric HA users with severe to profound HL and to examine the relation between preimplant aided audibility and postimplant speech perception. Research Design: A descriptive/observational and correlational study. Audiologic records of pediatric CI participants involved in a larger study examining the effects of early acoustic hearing were analyzed retrospectively; when available, these records included HA verification and speech recognition performance. Study Sample: The CI participants were enrolled in audiology centers and oral schools for the deaf across the United States. Data Collection and Analysis: To determine whether deviations from prescribed DSL target were significantly greater than zero, 95% confidence intervals of the mean deviation were calculated for each frequency (250, 500, 1000, 2000, and 4000 Hz). Correlational analyses were used to examine the relationship between preimplant aided Speech Intelligibility Indices (SIIs) and postimplant speech perception in noise. Correlational analyses were also used to explore the relationship between preimplant aided SIIs and demographic data. T-tests were used to compare preimplant-aided SIIs of HAs of listeners who later became users of either sequential CIs, simultaneous CIs, or bimodal devices. Results: Preimplant fittings of HAs were generally very close to prescriptive targets, except at 4000 Hz for those HAs with active frequency-lowering processing, and preimplant SIIs, albeit low, were correlated with postimplant speech recognition performance in noise. These results suggest that aided audibility should be maximized throughout the HA trial for later speech recognition purposes. Conclusions: It is recommended that HA fittings be optimized to support speech audibility even when considering implantation. In addition to the age at which HA use begins, the aided audibility itself is important in determining CI candidacy and decisions regarding bimodal HA use. © 2019 American Academy of Audiology. All rights reserved.

Author Keywords
Cochlear implants;  Hearing AIDS;  Hearing loss;  Pediatric;  SII;  Verification

Document Type: Article
Publication Stage: Final
Source: Scopus

Developing a pain intensity measure for persons with dementia: Initial construction and testing
(2019) Pain Medicine (United States), 20 (6), pp. 1078-1092. Cited 1 time.

Ersek, M.^{a b} , Herr, K.^c , Hilgeman, M.M.^{d e f} , Neradilek, M.B.^g , Polissar, N.^g , Cook, K.F.^h , Nash, P.^d , Snow, A.L.^{d e} , McDarby, M.ⁱ , Nelson, F.X.^a

^a Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, United States
^b University of Pennsylvania School of Nursing, Philadelphia, PA, United States
^c University of Iowa College of Nursing, Iowa City, IA, United States
^d Tuscaloosa VA Medical Center, Tuscaloosa, AL, United States
^e Alabama Research Institute on Aging, Department of Psychology, University of Alabama, Tuscaloosa, AL, United States
^f Division of Gerontology, Geriatrics, and Palliative Care, University of Alabama at Birmingham, Birmingham, AL, United States
^g Mountain-Whisper-Light Statistics, Seattle, WA, United States
^h Northwestern University Feinberg School of Medicine, Chicago, IL, United States
ⁱ Washington University, St. Louis, MO, United States

Abstract
Objective. The goal of this study was to identify a limited set of pain indicators that were most predicive of physical pain. We began with 140 items culled from existing pain observation tools and used a modified Delphi approach followed by statistical analyses to reduce the item pool. Methods. Through the Delphi Method, we created a candidate item set of behavioral indicators. Next, trained staff observed nursing home residents and rated the items on scales of behavior intensity and frequency. We evaluated associations among the items and expert clinicians’ assessment of pain intensity. Setting. Four government-owned nursing homes and 12 community nursing homes in Alabama and Southeastern Pennsylvania. Participants. Ninety-five residents (mean age ¼ 84.9 years) with moderate to severe cognitive impairment. Results. Using the least absolute shrinkage and selection operator model, we identified seven items that best predicted clinicians’ evaluations of pain intensity. These items were rigid/stiff body or body parts, bracing, complaining, expressive eyes, grimacing, frowning, and sighing. We also found that a model based on ratings of frequency of behaviors did not have better predictive ability than a model based on ratings of intensity of behaviors. Conclusions. We used two complementary approaches—expert opinion and statistical analysis—to reduce a large pool of behavioral indicators to a parsimonious set of items to predict pain intensity in persons with dementia. Future studies are needed to examine the psychometric properties of this scale, which is called the Pain Intensity Measure for Persons with Dementia. © 2019 Oxford University Press. All rights reserved.

Author Keywords
Delphi method;  Dementia;  Nursing homes;  Pain assessment;  Pain measurement

Document Type: Article
Publication Stage: Final
Source: Scopus

Cerebellar Ataxia With Neuropathy and Vestibular Areflexia Syndrome Presenting With Neurotrophic Keratopathy
(2018) Journal of Neuro-Ophthalmology : the Official Journal of the North American Neuro-Ophthalmology Society, 38 (3), pp. 342-343. 

Paley, G.L., Kung, N.H., Bucelli, R.C., Margolis, T.P., Van Stavern, G.P.

Department of Ophthalmology and Visual Sciences (GLP, NHK, TPM, GPVS), Washington University in St. Louis, St. Louis, Missouri; and Department of Neurology (RCB, GPVS), Washington University in St. Louis, St. Louis, Missouri

Document Type: Letter
Publication Stage: Final
Source: Scopus