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2. Echofilter: A Deep Learning Segmentation Model Improves the Automation, Standardization, and Timeliness for Post-Processing Echosounder Data in Tidal Energy Streams

Author

Lowe, Scott C., McGarry, Louise P., Douglas, Jessica, Newport, Jason, Oore, Sageev, Whidden, Christopher, and Hasselman, Daniel J.

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Signal Processing
Abstract

Understanding the abundance and distribution of fish in tidal energy streams is important to assess risks presented by introducing tidal energy devices to the habitat. However tidal current flows suitable for tidal energy are often highly turbulent, complicating the interpretation of echosounder data. The portion of the water column contaminated by returns from entrained air must be excluded from data used for biological analyses. Application of a single conventional algorithm to identify the depth-of-penetration of entrained air is insufficient for a boundary that is discontinuous, depth-dynamic, porous, and varies with tidal flow speed. Using a case study at a tidal energy demonstration site in the Bay of Fundy, we describe the development and application of a deep machine learning model with a U-Net based architecture. Our model, Echofilter, was highly responsive to the dynamic range of turbulence conditions and sensitive to the fine-scale nuances in the boundary position, producing an entrained-air boundary line with an average error of 0.33m on mobile downfacing and 0.5-1.0m on stationary upfacing data, less than half that of existing algorithmic solutions. The model's overall annotations had a high level of agreement with the human segmentation, with an intersection-over-union score of 99% for mobile downfacing recordings and 92-95% for stationary upfacing recordings. This resulted in a 50% reduction in the time required for manual edits when compared to the time required to manually edit the line placement produced by the currently available algorithms. Because of the improved initial automated placement, the implementation of the models permits an increase in the standardization and repeatability of line placement.

Published
2022
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3. Intelligence, educational attainment, and brain structure in those at familial high‐risk for schizophrenia or bipolar disorder

Author

Zwarte, Sonja MC, Brouwer, Rachel M, Agartz, Ingrid, Alda, Martin, Alonso‐Lana, Silvia, Bearden, Carrie E, Bertolino, Alessandro, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth EL, Cahn, Wiepke, Canales‐Rodríguez, Erick J, Cannon, Dara M, Cannon, Tyrone D, Caseras, Xavier, Castro‐Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Bonnin, Caterina Mar, Demro, Caroline, Di Giorgio, Annabella, Doucet, Gaelle E, Eker, Mehmet Cagdas, Erk, Susanne, Fatjó‐Vilas, Mar, Fears, Scott C, Foley, Sonya F, Frangou, Sophia, Fullerton, Janice M, Glahn, David C, Goghari, Vina M, Goikolea, Jose M, Goldman, Aaron L, Gonul, Ali Saffet, Gruber, Oliver, Hajek, Tomas, Hawkins, Emma L, Heinz, Andreas, Ongun, Ceren Hidiroglu, Hillegers, Manon HJ, Houenou, Josselin, Pol, Hilleke E Hulshoff, Hultman, Christina M, Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G, Kane, Fergus, Kempton, Matthew J, Koenis, Marinka MG, Kopecek, Miloslav, Krämer, Bernd, Lawrie, Stephen M, Lenroot, Rhoshel K, Marcelis, Machteld, Mattay, Venkata S, McDonald, Colm, Meyer‐Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B, Moreno, Dolores, Murray, Robin M, Mwangi, Benson, Nabulsi, Leila, Newport, Jason, Olman, Cheryl A, Os, Jim, Overs, Bronwyn J, Ozerdem, Aysegul, Pergola, Giulio, Picchioni, Marco M, Piguet, Camille, Pomarol‐Clotet, Edith, Radua, Joaquim, Ramsay, Ian S, Richter, Anja, Roberts, Gloria, Salvador, Raymond, Aydogan, Aybala Saricicek, Sarró, Salvador, Schofield, Peter R, Simsek, Esma M, Simsek, Fatma, Soares, Jair C, Sponheim, Scott R, Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Vieta, Eduard, Walter, Henrik, Weinberger, Daniel R, Whalley, Heather C, Wu, Mon‐Ju, Yalin, Nefize, Andreassen, Ole A, Ching, Christopher RK, Thomopoulos, Sophia I, Erp, Theo GM, Jahanshad, Neda, and Thompson, Paul M

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Bipolar Disorder, Clinical Research, Serious Mental Illness, Neurosciences, Schizophrenia, Mental Health, Aetiology, 2.3 Psychological, social and economic factors, 2.1 Biological and endogenous factors, Mental health, Cognitive Dysfunction, Educational Status, Family, Genetic Predisposition to Disease, Humans, Intelligence, Magnetic Resonance Imaging, Neuroimaging, bipolar disorder, education, intelligence, neuroimaging, relatives, schizophrenia, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.

Published
2022

4. The Association Between Familial Risk and Brain Abnormalities Is Disease Specific: An ENIGMA-Relatives Study of Schizophrenia and Bipolar Disorder

Author

de Zwarte, Sonja MC, Brouwer, Rachel M, Agartz, Ingrid, Alda, Martin, Aleman, André, Alpert, Kathryn I, Bearden, Carrie E, Bertolino, Alessandro, Bois, Catherine, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth EL, Cahn, Wiepke, Cannon, Dara M, Cannon, Tyrone D, Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Di Giorgio, Annabella, Doucet, Gaelle E, Eker, Mehmet Cagdas, Erk, Susanne, Fears, Scott C, Foley, Sonya F, Frangou, Sophia, Frankland, Andrew, Fullerton, Janice M, Glahn, David C, Goghari, Vina M, Goldman, Aaron L, Gonul, Ali Saffet, Gruber, Oliver, de Haan, Lieuwe, Hajek, Tomas, Hawkins, Emma L, Heinz, Andreas, Hillegers, Manon HJ, Pol, Hilleke E Hulshoff, Hultman, Christina M, Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G, Kane, Fergus, Kempton, Matthew J, Koenis, Marinka MG, Kopecek, Miloslav, Krabbendam, Lydia, Krämer, Bernd, Lawrie, Stephen M, Lenroot, Rhoshel K, Marcelis, Machteld, Marsman, Jan-Bernard C, Mattay, Venkata S, McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B, Moreno, Dolores, Murray, Robin M, Mwangi, Benson, Najt, Pablo, Neilson, Emma, Newport, Jason, van Os, Jim, Overs, Bronwyn, Ozerdem, Aysegul, Picchioni, Marco M, Richter, Anja, Roberts, Gloria, Aydogan, Aybala Saricicek, Schofield, Peter R, Simsek, Fatma, Soares, Jair C, Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Walter, Henrik, Wang, Lei, Weinberger, Daniel R, Whalley, Heather C, Yalin, Nefize, Andreassen, Ole A, Ching, Christopher RK, van Erp, Theo GM, Turner, Jessica A, Jahanshad, Neda, Thompson, Paul M, Kahn, René S, and van Haren, Neeltje EM

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Mental Health, Brain Disorders, Serious Mental Illness, Schizophrenia, Genetics, Neurosciences, Clinical Research, Bipolar Disorder, 2.3 Psychological, social and economic factors, Aetiology, 2.1 Biological and endogenous factors, Mental health, Adult, Brain, Cohort Studies, Female, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Young Adult, Bipolar disorder, Familial risk, Imaging, Meta-analysis, Neurodevelopment, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundSchizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects.MethodsWe performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects.ResultsFDRs-BD had significantly larger ICV (d = +0.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = -0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d

Published
2019

6. Variable parallelism in the genomic basis of age at maturity across spatial scales in Atlantic Salmon.

Author

Kess, Tony, Lehnert, Sarah J., Bentzen, Paul, Duffy, Steven, Messmer, Amber, Dempson, J. Brian, Newport, Jason, Whidden, Christopher, Robertson, Martha J., Chaput, Gerald, Breau, Cindy, April, Julien, Gillis, Carole‐Anne, Kent, Matthew, Nugent, Cameron M., and Bradbury, Ian R.

Subjects
ATLANTIC salmon, LOCUS (Genetics), MOLECULAR evolution, LIFE history theory, FOCAL adhesions
Abstract

Complex traits often exhibit complex underlying genetic architectures resulting from a combination of evolution from standing variation, hard and soft sweeps, and alleles of varying effect size. Increasingly, studies implicate both large‐effect loci and polygenic patterns underpinning adaptation, but the extent that common genetic architectures are utilized during repeated adaptation is not well understood. Sea age or age at maturation represents a significant life history trait in Atlantic Salmon (Salmo salar), the genetic basis of which has been studied extensively in European Atlantic populations, with repeated identification of large‐effect loci. However, the genetic basis of sea age within North American Atlantic Salmon populations remains unclear, as does the potential for a parallel trans‐Atlantic genomic basis to sea age. Here, we used a large single‐nucleotide polymorphism (SNP) array and low‐coverage whole‐genome resequencing to explore the genomic basis of sea age variation in North American Atlantic Salmon. We found significant associations at the gene and SNP level with a large‐effect locus (vgll3) previously identified in European populations, indicating genetic parallelism, but found that this pattern varied based on both sex and geographic region. We also identified nonrepeated sets of highly predictive loci associated with sea age among populations and sexes within North America, indicating polygenicity and low rates of genomic parallelism. Despite low genome‐wide parallelism, we uncovered a set of conserved molecular pathways associated with sea age that were consistently enriched among comparisons, including calcium signaling, MapK signaling, focal adhesion, and phosphatidylinositol signaling. Together, our results indicate parallelism of the molecular basis of sea age in North American Atlantic Salmon across large‐effect genes and molecular pathways despite population‐specific patterns of polygenicity. These findings reveal roles for both contingency and repeated adaptation at the molecular level in the evolution of life history variation. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Treatment with a GLP−1R agonist over four weeks promotes weight loss-moderated changes in frontal-striatal brain structures in individuals with mood disorders

Author

Mansur, Rodrigo B., Zugman, Andre, Ahmed, Juhie, Cha, Danielle S., Subramaniapillai, Mehala, Lee, Yena, Lovshin, Julie, Lee, Jung G., Lee, Jae-Hon, Drobinin, Vladislav, Newport, Jason, Brietzke, Elisa, Reininghaus, Eva Z., Sim, Kang, Vinberg, Maj, Rasgon, Natalie, Hajek, Tomas, and McIntyre, Roger S.

Published
2017
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8. Parallel genomic basis of age at maturity across spatial scales in Atlantic Salmon

Author

Kess, Tony, primary, Lehnert, Sarah J., additional, Bentzen, Paul, additional, Duffy, Steven, additional, Messmer, Amber, additional, Dempson, J. Brian, additional, Newport, Jason, additional, Whidden, Christopher, additional, Robertson, Martha J., additional, Chaput, Gerald, additional, Breau, Cindy, additional, April, Julien, additional, Gillis, Carole-Anne, additional, Kent, Matthew, additional, Nugent, Cameron M., additional, and Bradbury, Ian R., additional

Published
2022
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10. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

Author

de Zwarte, Sonja MC, de Zwarte, Sonja MC, Brouwer, Rachel M, Agartz, Ingrid, Alda, Martin, Alonso-Lana, Silvia, Bearden, Carrie E, Bertolino, Alessandro, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth EL, Cahn, Wiepke, Canales-Rodríguez, Erick J, Cannon, Dara M, Cannon, Tyrone D, Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Del Mar Bonnin, Caterina, Demro, Caroline, Di Giorgio, Annabella, Doucet, Gaelle E, Eker, Mehmet Cagdas, Erk, Susanne, Fatjó-Vilas, Mar, Fears, Scott C, Foley, Sonya F, Frangou, Sophia, Fullerton, Janice M, Glahn, David C, Goghari, Vina M, Goikolea, Jose M, Goldman, Aaron L, Gonul, Ali Saffet, Gruber, Oliver, Hajek, Tomas, Hawkins, Emma L, Heinz, Andreas, Hidiroglu Ongun, Ceren, Hillegers, Manon HJ, Houenou, Josselin, Hulshoff Pol, Hilleke E, Hultman, Christina M, Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G, Kane, Fergus, Kempton, Matthew J, Koenis, Marinka MG, Kopecek, Miloslav, Krämer, Bernd, Lawrie, Stephen M, Lenroot, Rhoshel K, Marcelis, Machteld, Mattay, Venkata S, McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B, Moreno, Dolores, Murray, Robin M, Mwangi, Benson, Nabulsi, Leila, Newport, Jason, Olman, Cheryl A, van Os, Jim, Overs, Bronwyn J, Ozerdem, Aysegul, Pergola, Giulio, Picchioni, Marco M, Piguet, Camille, Pomarol-Clotet, Edith, Radua, Joaquim, Ramsay, Ian S, Richter, Anja, Roberts, Gloria, Salvador, Raymond, Saricicek Aydogan, Aybala, Sarró, Salvador, Schofield, Peter R, Simsek, Esma M, Simsek, Fatma, Soares, Jair C, Sponheim, Scott R, Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Vieta, Eduard, Walter, Henrik, Weinberger, Daniel R, Whalley, Heather C, Wu, Mon-Ju, Yalin, Nefize, Andreassen, Ole A, Ching, Christopher RK, Thomopoulos, Sophia I, van Erp, Theo GM, Jahanshad, Neda, Thompson, Paul M, de Zwarte, Sonja MC, de Zwarte, Sonja MC, Brouwer, Rachel M, Agartz, Ingrid, Alda, Martin, Alonso-Lana, Silvia, Bearden, Carrie E, Bertolino, Alessandro, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth EL, Cahn, Wiepke, Canales-Rodríguez, Erick J, Cannon, Dara M, Cannon, Tyrone D, Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Del Mar Bonnin, Caterina, Demro, Caroline, Di Giorgio, Annabella, Doucet, Gaelle E, Eker, Mehmet Cagdas, Erk, Susanne, Fatjó-Vilas, Mar, Fears, Scott C, Foley, Sonya F, Frangou, Sophia, Fullerton, Janice M, Glahn, David C, Goghari, Vina M, Goikolea, Jose M, Goldman, Aaron L, Gonul, Ali Saffet, Gruber, Oliver, Hajek, Tomas, Hawkins, Emma L, Heinz, Andreas, Hidiroglu Ongun, Ceren, Hillegers, Manon HJ, Houenou, Josselin, Hulshoff Pol, Hilleke E, Hultman, Christina M, Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G, Kane, Fergus, Kempton, Matthew J, Koenis, Marinka MG, Kopecek, Miloslav, Krämer, Bernd, Lawrie, Stephen M, Lenroot, Rhoshel K, Marcelis, Machteld, Mattay, Venkata S, McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B, Moreno, Dolores, Murray, Robin M, Mwangi, Benson, Nabulsi, Leila, Newport, Jason, Olman, Cheryl A, van Os, Jim, Overs, Bronwyn J, Ozerdem, Aysegul, Pergola, Giulio, Picchioni, Marco M, Piguet, Camille, Pomarol-Clotet, Edith, Radua, Joaquim, Ramsay, Ian S, Richter, Anja, Roberts, Gloria, Salvador, Raymond, Saricicek Aydogan, Aybala, Sarró, Salvador, Schofield, Peter R, Simsek, Esma M, Simsek, Fatma, Soares, Jair C, Sponheim, Scott R, Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Vieta, Eduard, Walter, Henrik, Weinberger, Daniel R, Whalley, Heather C, Wu, Mon-Ju, Yalin, Nefize, Andreassen, Ole A, Ching, Christopher RK, Thomopoulos, Sophia I, van Erp, Theo GM, Jahanshad, Neda, and Thompson, Paul M

Abstract

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.

Published
2022

11. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder

Author

de Zwarte, Sonja M. C., Brouwer, Rachel M., Agartz, Ingrid, Alda, Martin, Alonso-Lana, Silvia, Bearden, Carrie E., Bertolino, Alessandro, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth E. L., Cahn, Wiepke, Canales-Rodríguez, Erick J., Cannon, Dara M., Cannon, Tyrone D., Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Del Mar Bonnin, Caterina, Demro, Caroline, Di Giorgio, Annabella, Doucet, Gaelle E., Eker, Mehmet Cagdas, Erk, Susanne, Fatjó-Vilas, Mar, Fears, Scott C., Foley, Sonya F., Frangou, Sophia, Fullerton, Janice M., Glahn, David C., Goghari, Vina M., Goikolea, Jose M., Goldman, Aaron L., Gonul, Ali Saffet, Gruber, Oliver, Hajek, Tomas, Hawkins, Emma L., Heinz, Andreas, Hidiroglu Ongun, Ceren, Hillegers, Manon H.J., Houenou, Josselin, Hulshoff Pol, Hilleke E., Hultman, Christina M., Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G., Kane, Fergus, Kempton, Matthew J., Koenis, Marinka M. G., Kopecek, Miloslav, Krämer, Bernd, Lawrie, Stephen M., Lenroot, Rhoshel K., Marcelis, Machteld, Mattay, Venkata S., McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B., Moreno, Dolores, Murray, Robin M., Mwangi, Benson, Nabulsi, Leila, Newport, Jason, Olman, Cheryl A., van Os, Jim, Overs, Bronwyn J., Ozerdem, Aysegul, Pergola, Giulio, Picchioni, Marco M., Piguet, Camille, Pomarol-Clotet, Edith, Radua, Joaquim, Ramsay, Ian S., Richter, Anja, Roberts, Gloria, Salvador, Raymond, Saricicek Aydogan, Aybala, Sarró, Salvador, Schofield, Peter R., Simsek, Esma M., Simsek, Fatma, Soares, Jair C., Sponheim, Scott R., Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Vieta, Eduard, Walter, Henrik, Weinberger, Daniel R., Whalley, Heather C., Wu, Mon-Ju, Yalin, Nefize, Andreassen, Ole A., Ching, Christopher R. K., Thomopoulos, Sophia I., van Erp, Theo G. M., Jahanshad, Neda, Thompson, Paul M., Kahn, René S., van Haren, Neeltje E. M., de Zwarte, Sonja M. C., Brouwer, Rachel M., Agartz, Ingrid, Alda, Martin, Alonso-Lana, Silvia, Bearden, Carrie E., Bertolino, Alessandro, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth E. L., Cahn, Wiepke, Canales-Rodríguez, Erick J., Cannon, Dara M., Cannon, Tyrone D., Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Del Mar Bonnin, Caterina, Demro, Caroline, Di Giorgio, Annabella, Doucet, Gaelle E., Eker, Mehmet Cagdas, Erk, Susanne, Fatjó-Vilas, Mar, Fears, Scott C., Foley, Sonya F., Frangou, Sophia, Fullerton, Janice M., Glahn, David C., Goghari, Vina M., Goikolea, Jose M., Goldman, Aaron L., Gonul, Ali Saffet, Gruber, Oliver, Hajek, Tomas, Hawkins, Emma L., Heinz, Andreas, Hidiroglu Ongun, Ceren, Hillegers, Manon H.J., Houenou, Josselin, Hulshoff Pol, Hilleke E., Hultman, Christina M., Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G., Kane, Fergus, Kempton, Matthew J., Koenis, Marinka M. G., Kopecek, Miloslav, Krämer, Bernd, Lawrie, Stephen M., Lenroot, Rhoshel K., Marcelis, Machteld, Mattay, Venkata S., McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B., Moreno, Dolores, Murray, Robin M., Mwangi, Benson, Nabulsi, Leila, Newport, Jason, Olman, Cheryl A., van Os, Jim, Overs, Bronwyn J., Ozerdem, Aysegul, Pergola, Giulio, Picchioni, Marco M., Piguet, Camille, Pomarol-Clotet, Edith, Radua, Joaquim, Ramsay, Ian S., Richter, Anja, Roberts, Gloria, Salvador, Raymond, Saricicek Aydogan, Aybala, Sarró, Salvador, Schofield, Peter R., Simsek, Esma M., Simsek, Fatma, Soares, Jair C., Sponheim, Scott R., Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Vieta, Eduard, Walter, Henrik, Weinberger, Daniel R., Whalley, Heather C., Wu, Mon-Ju, Yalin, Nefize, Andreassen, Ole A., Ching, Christopher R. K., Thomopoulos, Sophia I., van Erp, Theo G. M., Jahanshad, Neda, Thompson, Paul M., Kahn, René S., and van Haren, Neeltje E. M.

Abstract

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.

Published
2022
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12. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder

Author

de Zwarte, Sonja M.C., Brouwer, Rachel M., Agartz, Ingrid, Alda, Martin, Alonso-Lana, Silvia, Bearden, Carrie E., Bertolino, Alessandro, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth E.L., Cahn, Wiepke, Canales-Rodríguez, Erick J., Cannon, Dara M., Cannon, Tyrone D., Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, del Mar Bonnin, Caterina, Demro, Caroline, Di Giorgio, Annabella, Doucet, Gaelle E., Eker, Mehmet Cagdas, Erk, Susanne, Fatjó-Vilas, Mar, Fears, Scott C., Foley, Sonya F., Frangou, Sophia, Fullerton, Janice M., Glahn, David C., Goghari, Vina M., Goikolea, Jose M., Goldman, Aaron L., Gonul, Ali Saffet, Gruber, Oliver, Hajek, Tomas, Hawkins, Emma L., Heinz, Andreas, Hidiroglu Ongun, Ceren, Hillegers, Manon H.J., Houenou, Josselin, Hulshoff Pol, Hilleke E., Hultman, Christina M., Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G., Kane, Fergus, Kempton, Matthew J., Koenis, Marinka M.G., Kopecek, Miloslav, Krämer, Bernd, Lawrie, Stephen M., Lenroot, Rhoshel K., Marcelis, Machteld, Mattay, Venkata S., McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B., Moreno, Dolores, Murray, Robin M., Mwangi, Benson, Nabulsi, Leila, Newport, Jason, Olman, Cheryl A., van Os, Jim, Overs, Bronwyn J., Ozerdem, Aysegul, Pergola, Giulio, Picchioni, Marco M., Piguet, Camille, Pomarol-Clotet, Edith, Radua, Joaquim, Ramsay, Ian S., Richter, Anja, Roberts, Gloria, Salvador, Raymond, Saricicek Aydogan, Aybala, Sarró, Salvador, Schofield, Peter R., Simsek, Esma M., Simsek, Fatma, Soares, Jair C., Sponheim, Scott R., Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Vieta, Eduard, Walter, Henrik, Weinberger, Daniel R., Whalley, Heather C., Wu, Mon Ju, Yalin, Nefize, Andreassen, Ole A., Ching, Christopher R.K., Thomopoulos, Sophia I., van Erp, Theo G.M., Jahanshad, Neda, Thompson, Paul M., Kahn, René S., van Haren, Neeltje E.M., de Zwarte, Sonja M.C., Brouwer, Rachel M., Agartz, Ingrid, Alda, Martin, Alonso-Lana, Silvia, Bearden, Carrie E., Bertolino, Alessandro, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth E.L., Cahn, Wiepke, Canales-Rodríguez, Erick J., Cannon, Dara M., Cannon, Tyrone D., Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, del Mar Bonnin, Caterina, Demro, Caroline, Di Giorgio, Annabella, Doucet, Gaelle E., Eker, Mehmet Cagdas, Erk, Susanne, Fatjó-Vilas, Mar, Fears, Scott C., Foley, Sonya F., Frangou, Sophia, Fullerton, Janice M., Glahn, David C., Goghari, Vina M., Goikolea, Jose M., Goldman, Aaron L., Gonul, Ali Saffet, Gruber, Oliver, Hajek, Tomas, Hawkins, Emma L., Heinz, Andreas, Hidiroglu Ongun, Ceren, Hillegers, Manon H.J., Houenou, Josselin, Hulshoff Pol, Hilleke E., Hultman, Christina M., Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G., Kane, Fergus, Kempton, Matthew J., Koenis, Marinka M.G., Kopecek, Miloslav, Krämer, Bernd, Lawrie, Stephen M., Lenroot, Rhoshel K., Marcelis, Machteld, Mattay, Venkata S., McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B., Moreno, Dolores, Murray, Robin M., Mwangi, Benson, Nabulsi, Leila, Newport, Jason, Olman, Cheryl A., van Os, Jim, Overs, Bronwyn J., Ozerdem, Aysegul, Pergola, Giulio, Picchioni, Marco M., Piguet, Camille, Pomarol-Clotet, Edith, Radua, Joaquim, Ramsay, Ian S., Richter, Anja, Roberts, Gloria, Salvador, Raymond, Saricicek Aydogan, Aybala, Sarró, Salvador, Schofield, Peter R., Simsek, Esma M., Simsek, Fatma, Soares, Jair C., Sponheim, Scott R., Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Vieta, Eduard, Walter, Henrik, Weinberger, Daniel R., Whalley, Heather C., Wu, Mon Ju, Yalin, Nefize, Andreassen, Ole A., Ching, Christopher R.K., Thomopoulos, Sophia I., van Erp, Theo G.M., Jahanshad, Neda, Thompson, Paul M., Kahn, René S., and van Haren, Neeltje E.M.

Abstract

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = −0.42, p = 3 × 10−5), with weak evidence of IQ reductions among BD-FDRs (d = −0.23, p =.045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.

Published
2022

13. Intelligence, educational attainment, and brain structure in those at familial high‐risk for schizophrenia or bipolar disorder

Author

Zwarte, Sonja M. C., primary, Brouwer, Rachel M., additional, Agartz, Ingrid, additional, Alda, Martin, additional, Alonso‐Lana, Silvia, additional, Bearden, Carrie E., additional, Bertolino, Alessandro, additional, Bonvino, Aurora, additional, Bramon, Elvira, additional, Buimer, Elizabeth E. L., additional, Cahn, Wiepke, additional, Canales‐Rodríguez, Erick J., additional, Cannon, Dara M., additional, Cannon, Tyrone D., additional, Caseras, Xavier, additional, Castro‐Fornieles, Josefina, additional, Chen, Qiang, additional, Chung, Yoonho, additional, De la Serna, Elena, additional, Mar Bonnin, Caterina, additional, Demro, Caroline, additional, Di Giorgio, Annabella, additional, Doucet, Gaelle E., additional, Eker, Mehmet Cagdas, additional, Erk, Susanne, additional, Fatjó‐Vilas, Mar, additional, Fears, Scott C., additional, Foley, Sonya F., additional, Frangou, Sophia, additional, Fullerton, Janice M., additional, Glahn, David C., additional, Goghari, Vina M., additional, Goikolea, Jose M., additional, Goldman, Aaron L., additional, Gonul, Ali Saffet, additional, Gruber, Oliver, additional, Hajek, Tomas, additional, Hawkins, Emma L., additional, Heinz, Andreas, additional, Hidiroglu Ongun, Ceren, additional, Hillegers, Manon H. J., additional, Houenou, Josselin, additional, Hulshoff Pol, Hilleke E., additional, Hultman, Christina M., additional, Ingvar, Martin, additional, Johansson, Viktoria, additional, Jönsson, Erik G., additional, Kane, Fergus, additional, Kempton, Matthew J., additional, Koenis, Marinka M. G., additional, Kopecek, Miloslav, additional, Krämer, Bernd, additional, Lawrie, Stephen M., additional, Lenroot, Rhoshel K., additional, Marcelis, Machteld, additional, Mattay, Venkata S., additional, McDonald, Colm, additional, Meyer‐Lindenberg, Andreas, additional, Michielse, Stijn, additional, Mitchell, Philip B., additional, Moreno, Dolores, additional, Murray, Robin M., additional, Mwangi, Benson, additional, Nabulsi, Leila, additional, Newport, Jason, additional, Olman, Cheryl A., additional, Os, Jim, additional, Overs, Bronwyn J., additional, Ozerdem, Aysegul, additional, Pergola, Giulio, additional, Picchioni, Marco M., additional, Piguet, Camille, additional, Pomarol‐Clotet, Edith, additional, Radua, Joaquim, additional, Ramsay, Ian S., additional, Richter, Anja, additional, Roberts, Gloria, additional, Salvador, Raymond, additional, Saricicek Aydogan, Aybala, additional, Sarró, Salvador, additional, Schofield, Peter R., additional, Simsek, Esma M., additional, Simsek, Fatma, additional, Soares, Jair C., additional, Sponheim, Scott R., additional, Sugranyes, Gisela, additional, Toulopoulou, Timothea, additional, Tronchin, Giulia, additional, Vieta, Eduard, additional, Walter, Henrik, additional, Weinberger, Daniel R., additional, Whalley, Heather C., additional, Wu, Mon‐Ju, additional, Yalin, Nefize, additional, Andreassen, Ole A., additional, Ching, Christopher R. K., additional, Thomopoulos, Sophia I., additional, Erp, Theo G. M., additional, Jahanshad, Neda, additional, Thompson, Paul M., additional, Kahn, René S., additional, and Haren, Neeltje E. M., additional

Published
2020
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14. The association between familial risk and brain abnormalities is disease specific : an ENIGMA-relatives study of schizophrenia and bipolar disorder

Author

de Zwarte, Sonja M. C., Brouwer, Rachel M., Agartz, Ingrid, Alda, Martin, Aleman, André, Alpert, Kathryn I., Bearden, Carrie E., Bertolino, Alessandro, Bois, Catherine, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth E. L., Cahn, Wiepke, Cannon, Dara M., Cannon, Tyrone D., Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Di Giorgio, Annabella, Doucet, Gaelle E., Eker, Mehmet Cagdas, Erk, Susanne, Fears, Scott C., Foley, Sonya F., Frangou, Sophia, Frankland, Andrew, Fullerton, Janice M., Glahn, David C., Goghari, Vina M., Goldman, Aaron L., Gonul, Ali Saffet, Gruber, Oliver, de Haan, Lieuwe, Hajek, Tomas, Hawkins, Emma L., Heinz, Andreas, Hillegers, Manon H. J., Hulshoff Pol, Hilleke E., Hultman, Christina M., Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G., Kane, Fergus, Kempton, Matthew J., Koenis, Marinka M. G., Kopecek, Miloslav, Krabbendam, Lydia, Krämer, Bernd, Lawrie, Stephen M., Lenroot, Rhoshel K., Marcelis, Machteld, Marsman, Jan-Bernard C., Mattay, Venkata S., McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B., Moreno, Dolores, Murray, Robin M., Mwangi, Benson, Najt, Pablo, Neilson, Emma, Newport, Jason, van Os, Jim, Overs, Bronwyn, Ozerdem, Aysegul, Picchioni, Marco M., Richter, Anja, Roberts, Gloria, Aydogan, Aybala Saricicek, Schofield, Peter R., Simsek, Fatma, Soares, Jair C., Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Walter, Henrik, Wang, Lei, Weinberger, Daniel R., Whalley, Heather C., Yalin, Nefize, Andreassen, Ole A., Ching, Christopher R. K., van Erp, Theo G. M., Turner, Jessica A., Jahanshad, Neda, Thompson, Paul M., Kahn, René S., van Haren, Neeltje E. M., de Zwarte, Sonja M. C., Brouwer, Rachel M., Agartz, Ingrid, Alda, Martin, Aleman, André, Alpert, Kathryn I., Bearden, Carrie E., Bertolino, Alessandro, Bois, Catherine, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth E. L., Cahn, Wiepke, Cannon, Dara M., Cannon, Tyrone D., Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Di Giorgio, Annabella, Doucet, Gaelle E., Eker, Mehmet Cagdas, Erk, Susanne, Fears, Scott C., Foley, Sonya F., Frangou, Sophia, Frankland, Andrew, Fullerton, Janice M., Glahn, David C., Goghari, Vina M., Goldman, Aaron L., Gonul, Ali Saffet, Gruber, Oliver, de Haan, Lieuwe, Hajek, Tomas, Hawkins, Emma L., Heinz, Andreas, Hillegers, Manon H. J., Hulshoff Pol, Hilleke E., Hultman, Christina M., Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G., Kane, Fergus, Kempton, Matthew J., Koenis, Marinka M. G., Kopecek, Miloslav, Krabbendam, Lydia, Krämer, Bernd, Lawrie, Stephen M., Lenroot, Rhoshel K., Marcelis, Machteld, Marsman, Jan-Bernard C., Mattay, Venkata S., McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B., Moreno, Dolores, Murray, Robin M., Mwangi, Benson, Najt, Pablo, Neilson, Emma, Newport, Jason, van Os, Jim, Overs, Bronwyn, Ozerdem, Aysegul, Picchioni, Marco M., Richter, Anja, Roberts, Gloria, Aydogan, Aybala Saricicek, Schofield, Peter R., Simsek, Fatma, Soares, Jair C., Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Walter, Henrik, Wang, Lei, Weinberger, Daniel R., Whalley, Heather C., Yalin, Nefize, Andreassen, Ole A., Ching, Christopher R. K., van Erp, Theo G. M., Turner, Jessica A., Jahanshad, Neda, Thompson, Paul M., Kahn, René S., and van Haren, Neeltje E. M.

Abstract

BACKGROUND: Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. METHODS: We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. RESULTS: FDRs-BD had significantly larger ICV (d = +0.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = -0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < -0.09, q < .05 corrected); and third ventricle was larger (d = +0.15, q < .05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. CONCLUSIONS: Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.

Published
2019
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15. IDENTIFICATION OF PERIODIC FISH TAGS WITH DEEP LEARNING.

Author

Medisetty, Santosh, Ouellette, Dave, Smith, Frank, Richard, Matthew, Johnston, Sam, Quirion, Jean, Newport, Jason, Whidden, Christopher, and Kirsebom, Oliver

Subjects
IDENTIFICATION of fishes, ANIMAL mechanics, MACHINE learning, MARINE animals, DEEP learning, DATA analysis
Abstract

Acoustic tags are increasingly being used in research to track movements of marine animals, generating large, complex datasets which require automated analysis methods. In this work, we explore the use of modern machine learning methods to automate the analysis of data from acoustic tags with a novel encoding developed for the study of large numbers of fish in noisy environments. These tags emit pulses at a configurable interval but without any other encoded identification message. This reduces power usage and enables continuous tracking but the challenge is that tags must be identified based on the transmission rate and the position reconstructed by triangulating detections by at least three independent receivers. Utilizing a visual representation of the time series data generated by the tag, we adapt a deep neural network architecture known as U-Net to the task of identifying individual acoustic tag transmissions. Testing our model on unseen data, we achieve an accuracy of 97%, outperforming the solution currently in use, which achieves an accuracy of 41%. Our model shows significant promise and represents the first step towards enabling the large-scale application of this new acoustic tracking technology to fisheries operations. [ABSTRACT FROM AUTHOR]

Published
2021

16. A MACHINE LEARNING REDUNDANCY MODEL FOR THE HERRING COVE SMART BUOY.

Author

Fasuyi, Jesuseyi Will, Newport, Jason, and Whidden, Chris

Subjects
MACHINE learning, RANDOM forest algorithms, MARITIME shipping, WIND speed, BUOYS
Abstract

Sensor buoys provide crucial decision-making infrastructure but are often a single point of failure. For example, the Smart Atlantic Herring Cove buoy (SMA-H Buoy) is owned by the Centre for Ocean Ventures and Entrepreneurship and used by the Port of Halifax and Atlantic Pilotage Authority to support operational efficiency, safety, and situational awareness for marine transportation. We developed a proof of concept machine learning model to determine if wind speed and wave height measurements from the SMA-H Buoy could be predicted using measurements from the Environment and Climate Change Canada Buoy (ECCC Buoy) located 13 km away in the open ocean. We combined data from both buoys which required a series of nontrivial alignment, filtering, and matching steps. Of the three machine learning models tested, the random forest algorithm performed best for both wind speed and significant wave height predictions with mean errors of 0.17 m and 1.11 m/s, respectively. This project demonstrates that a machine learning model can provide relatively reliable predictions of wind speed and wave height even from a single alternative measurement source when the primary source is unavailable due to maintenance or malfunction. [ABSTRACT FROM AUTHOR]

Published
2020

17. Treatment with a GLP-1R agonist over four weeks promotes weight loss-moderated changes in frontal-striatal brain structures in individuals with mood disorders

Author

Mansur, Rodrigo B, Zugman, Andre, Ahmed, Juhie, Cha, Danielle S, Subramaniapillai, Mehala, Lee, Yena, Lovshin, Julie, Lee, Jung G, Lee, Jae-Hon, Drobinin, Vladislav, Newport, Jason, Brietzke, Elisa, Reininghaus, Eva Z, Sim, Kang, Vinberg, Maj, Rasgon, Natalie, Hajek, Tomas, McIntyre, Roger S, Mansur, Rodrigo B, Zugman, Andre, Ahmed, Juhie, Cha, Danielle S, Subramaniapillai, Mehala, Lee, Yena, Lovshin, Julie, Lee, Jung G, Lee, Jae-Hon, Drobinin, Vladislav, Newport, Jason, Brietzke, Elisa, Reininghaus, Eva Z, Sim, Kang, Vinberg, Maj, Rasgon, Natalie, Hajek, Tomas, and McIntyre, Roger S

Abstract

Cognitive deficits are a core feature across psychiatric disorders. Emerging evidence indicates that metabolic pathways are highly relevant for the substrates and phenomenology of the cognitive domain. Herein, we aimed to determine the effects of liraglutide, a GLP-1R agonist, on brain structural/volumetric parameters in adults with a mood disorder. This is the secondary analysis of a 4-week, pilot, proof-of-concept, open-label study. Participants (N=19) exhibiting impairments in executive function with either major depressive disorder (MDD) or bipolar disorder (BD) were recruited. Liraglutide 1.8mg/day was added as an adjunct to existing pharmacotherapy. Structural magnetic resonance imaging (MRI) scanning was obtained at baseline and endpoint. Results showed that at endpoint there was significant weight loss (mean: 3.15%; p<0.001). Changes in frontal and striatal volumes were significantly correlated with changes in body mass index (BMI), indicating the weight loss was associated with volume increase in most regions (e.g. r=-0.561, p=0.042 in the left superior frontal area). After adjusting for intracranial volume, age, gender, and BMI, we observed significant changes from baseline to endpoint in multiple regions (e.g. RR: 1.011, p=0.049 in the left rostral middle frontal area). Changes in regional volumes were associated with improvement in executive function (e.g. r=0.698, p=0.003 for the right superior frontal area). Adjunctive liraglutide results in clinically significant weight loss, with corresponding improvement in cognitive function; changes in cognitive function were partially moderated by changes in brain morphometry, underscoring the interrelationship between weight and brain structure/function.

Published
2017

20. Solutions to the nonlinear Schrodinger equation with Dirac mass initial data

Author

Newport, Jason

Abstract

We study the Nonlinear Schrodinger Equation Dirac mass initial data. We use scattering and inverse scattering theory to pose a Riemann Hilbert problem with a regularized reflection coefficient. We study the asymptotic behaviour of this RHP as the regularizing parameter tends to zero. We also establish asymptotic descriptions of solutions for sequences of initial data that converge to a Dirac mass, using a connection to previously known long time asymptotics.

Published
2008
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21. Deep Learning and Fish Tags.

Author

Medisetty, Santosh, Ouellette, Dave, Smith, Frank, Richard, Matthew, Johnston, Sam, Quirion, Jean, Newport, Jason, Whidden, Christopher, and Kirsebom, Oliver

Subjects
DEEP learning, IMAGE analysis, FISHERIES, IMAGE segmentation, MACHINE learning, FISH habitats
Published
2021

22. ON LETTING GO.

Author

NEWPORT, JASON

Subjects
HIGH school students' conduct of life, DECISION making, LIFE
Published
2015

23. Spare Change.

Author

Newport, Jason

Subjects
SPARE Change (Short story), NEWPORT, Jason
Abstract

Presents the short story "Spare Change," by Jason Newport.

Published
2005

24. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

Author

de Zwarte SMC, Brouwer RM, Agartz I, Alda M, Alonso-Lana S, Bearden CE, Bertolino A, Bonvino A, Bramon E, Buimer EEL, Cahn W, Canales-Rodríguez EJ, Cannon DM, Cannon TD, Caseras X, Castro-Fornieles J, Chen Q, Chung Y, De la Serna E, Del Mar Bonnin C, Demro C, Di Giorgio A, Doucet GE, Eker MC, Erk S, Fatjó-Vilas M, Fears SC, Foley SF, Frangou S, Fullerton JM, Glahn DC, Goghari VM, Goikolea JM, Goldman AL, Gonul AS, Gruber O, Hajek T, Hawkins EL, Heinz A, Hidiroglu Ongun C, Hillegers MHJ, Houenou J, Hulshoff Pol HE, Hultman CM, Ingvar M, Johansson V, Jönsson EG, Kane F, Kempton MJ, Koenis MMG, Kopecek M, Krämer B, Lawrie SM, Lenroot RK, Marcelis M, Mattay VS, McDonald C, Meyer-Lindenberg A, Michielse S, Mitchell PB, Moreno D, Murray RM, Mwangi B, Nabulsi L, Newport J, Olman CA, van Os J, Overs BJ, Ozerdem A, Pergola G, Picchioni MM, Piguet C, Pomarol-Clotet E, Radua J, Ramsay IS, Richter A, Roberts G, Salvador R, Saricicek Aydogan A, Sarró S, Schofield PR, Simsek EM, Simsek F, Soares JC, Sponheim SR, Sugranyes G, Toulopoulou T, Tronchin G, Vieta E, Walter H, Weinberger DR, Whalley HC, Wu MJ, Yalin N, Andreassen OA, Ching CRK, Thomopoulos SI, van Erp TGM, Jahanshad N, Thompson PM, Kahn RS, and van Haren NEM

Subjects
Bipolar Disorder complications, Bipolar Disorder diagnostic imaging, Cognitive Dysfunction diagnostic imaging, Family, Humans, Magnetic Resonance Imaging, Schizophrenia complications, Schizophrenia diagnostic imaging, Schizophrenia etiology, Bipolar Disorder pathology, Cognitive Dysfunction pathology, Educational Status, Genetic Predisposition to Disease, Intelligence physiology, Neuroimaging, Schizophrenia pathology
Abstract

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10 -5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Published
2022
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