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1,026 results on '"Ibáñez, Agustín"'

1. FAST functional connectivity implicates P300 connectivity in working memory deficits in Alzheimer's disease

Author

Roy, Om, Moshfeghi, Yashar, Ibanez, Agustin, Lopera, Francisco, Parra, Mario A, and Smith, Keith M

Subjects
Quantitative Biology - Neurons and Cognition, Electrical Engineering and Systems Science - Signal Processing
Abstract

Measuring transient functional connectivity is an important challenge in Electroencephalogram (EEG) research. Here, the rich potential for insightful, discriminative information of brain activity offered by high temporal resolution is confounded by the inherent noise of the medium and the spurious nature of correlations computed over short temporal windows. We propose a novel methodology to overcome these problems called Filter Average Short-Term (FAST) functional connectivity. First, long-term, stable, functional connectivity is averaged across an entire study cohort for a given pair of Visual Short Term Memory (VSTM) tasks. The resulting average connectivity matrix, containing information on the strongest general connections for the tasks, is used as a filter to analyse the transient high temporal resolution functional connectivity of individual subjects. In simulations, we show that this method accurately discriminates differences in noisy Event-Related Potentials (ERPs) between two conditions where standard connectivity and other comparable methods fail. We then apply this to analyse activity related to visual short-term memory binding deficits in two cohorts of familial and sporadic Alzheimer's disease. Reproducible significant differences were found in the binding task with no significant difference in the shape task in the P300 ERP range. This allows new sensitive measurements of transient functional connectivity, which can be implemented to obtain results of clinical significance., Comment: Published in Network Neuroscience (2024) by MIT Press

Published
2024
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5. Frontotemporal dementia presentation in patients with heterozygous p.H157Y variant of TREM2.

Author

Ogonowski, Natalia, Santamaria-Garcia, Hernando, Baez, Sandra, Lopez, Andrea, Laserna, Andrés, Garcia-Cifuentes, Elkin, Ayala-Ramirez, Paola, Zarante, Ignacio, Suarez-Obando, Fernando, Reyes, Pablo, Kauffman, Marcelo, Cochran, Nick, Schulte, Michael, Kosik, Kenneth, Matallana, Diana, Ibáñez, Agustín, Spina, Salvatore, Miller, Bruce, Yokoyama, Jennifer, and Sirkis, Daniel

Subjects
Genetics, Neurodegenerative Diseases, Neurology, Humans, Frontotemporal Dementia, Alzheimer Disease, Brain, Atrophy, Membrane Glycoproteins, Receptors, Immunologic
Abstract

BACKGROUND: The triggering receptor expressed on myeloid cell 2 (TREM2) is a major regulator of neuroinflammatory processes in neurodegeneration. To date, the p.H157Y variant of TREM2 has been reported only in patients with Alzheimers disease. Here, we report three patients with frontotemporal dementia (FTD) from three unrelated families with heterozygous p.H157Y variant of TREM2: two patients from Colombian families (study 1) and a third Mexican origin case from the USA (study 2). METHODS: To determine if the p.H157Y variant might be associated with a specific FTD presentation, we compared in each study the cases with age-matched, sex-matched and education-matched groups-a healthy control group (HC) and a group with FTD with neither TREM2 mutations nor family antecedents (Ng-FTD and Ng-FTD-MND). RESULTS: The two Colombian cases presented with early behavioural changes, greater impairments in general cognition and executive function compared with both HC and Ng-FTD groups. These patients also exhibited brain atrophy in areas characteristic of FTD. Furthermore, TREM2 cases showed increased atrophy compared with Ng-FTD in frontal, temporal, parietal, precuneus, basal ganglia, parahippocampal/hippocampal and cerebellar regions. The Mexican case presented with FTD and motor neuron disease (MND), showing grey matter reduction in basal ganglia and thalamus, and extensive TDP-43 type B pathology. CONCLUSION: In all TREM2 cases, multiple atrophy peaks overlapped with the maximum peaks of TREM2 gene expression in crucial brain regions including frontal, temporal, thalamic and basal ganglia areas. These results provide the first report of an FTD presentation potentially associated with the p.H157Y variant with exacerbated neurocognitive impairments.

Published
2023

8. Next generation brain health: transforming global research and public health to promote prevention of dementia and reduce its risk in young adult populations

Author

Farina, Francesca R, Bridgeman, Katie, Gregory, Sarah, Crivelli, Lucía, Foote, Isabelle F, Jutila, Otto-Emil I, Kucikova, Ludmila, Mariano, Luciano I, Nguyen, Kim-Huong, Thayanandan, Tony, Akindejoye, Funmi, Butler, Joe, Calandri, Ismael L, Čepukaitytė, Giedrė, Chiesa, Scott T, Dawson, Walter D, Deckers, Kay, Cruz-Góngora, Vanessa De la, Dounavi, Maria-Eleni, Govia, Ishtar, Guzmán-Vélez, Edmarie, Heikal, Shimaa A, Hill-Jarrett, Tanisha G, Ibáñez, Agustín, James, Bryan D, McGlinchey, Eimear, Mullin, Donncha S, Muniz-Terrera, Graciela, Pintado Caipa, Maritza, Qansuwa, Esraa M, Robinson, Louise, Santuccione Chadha, Antonella, Shannon, Oliver M, Su, Li, Weidner, Wendy, and Booi, Laura

Published
2024
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9. The Latin American Brain Health Institute, a regional initiative to reduce the scale and impact of dementia.

Author

Duran-Aniotz, Claudia, Sanhueza, Jorge, Grinberg, Lea T, Slachevsky, Andrea, Valcour, Victor, Robertson, Ian, Lawlor, Brian, Miller, Bruce, and Ibáñez, Agustín

Subjects
Brain, Humans, Dementia, Latin America, brain health, capacity building, dementia, networking, translational research, Aging, Neurodegenerative, Brain Disorders, Neurosciences, Acquired Cognitive Impairment, Neurological, Clinical Sciences, Geriatrics
Abstract

Latin American and Caribbean countries face complex challenges to improve brain health and reduce the impact of dementia. Regional hubs devoted to research, capacity building, implementation science, and education are critically needed. The Latin American Brain Health Institute represent an important step to address many of these needs.

Published
2022

10. Multi-feature computational framework for combined signatures of dementia in underrepresented settings.

Author

Moguilner, Sebastian, Birba, Agustina, Fittipaldi, Sol, Gonzalez-Campo, Cecilia, Tagliazucchi, Enzo, Reyes, Pablo, Matallana, Diana, Parra, Mario, Slachevsky, Andrea, Farías, Gonzalo, Cruzat, Josefina, García, Adolfo, Eyre, Harris, La Joie, Renaud, Rabinovici, Gil, Whelan, Robert, and Ibáñez, Agustín

Subjects
feature selection, harmonization, machine learning, multimodal neuroimaging, neurodegeneration, Alzheimer Disease, Bayes Theorem, Biomarkers, Brain, Frontotemporal Dementia, Humans, Magnetic Resonance Imaging, Neuropsychological Tests
Abstract

Objective.The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimers disease (AD) remains challenging in underrepresented, underdiagnosed groups, including Latinos, as advanced biomarkers are rarely available. Recent guidelines for the study of dementia highlight the critical role of biomarkers. Thus, novel cost-effective complementary approaches are required in clinical settings.Approach. We developed a novel framework based on a gradient boosting machine learning classifier, tuned by Bayesian optimization, on a multi-feature multimodal approach (combining demographic, neuropsychological, magnetic resonance imaging (MRI), and electroencephalography/functional MRI connectivity data) to characterize neurodegeneration using site harmonization and sequential feature selection. We assessed 54 bvFTD and 76 AD patients and 152 healthy controls (HCs) from a Latin American consortium (ReDLat).Main results. The multimodal model yielded high area under the curve classification values (bvFTD patients vs HCs: 0.93 (±0.01); AD patients vs HCs: 0.95 (±0.01); bvFTD vs AD patients: 0.92 (±0.01)). The feature selection approach successfully filtered non-informative multimodal markers (from thousands to dozens).Results. Proved robust against multimodal heterogeneity, sociodemographic variability, and missing data.Significance. The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. This approach, if confirmed and replicated, may potentially complement clinical assessments in developing countries.

Published
2022

12. Unveiling Trail Making Test: Visual and manual trajectories indexing multiple executive processes

Author

Linari, Ignacio, Juantorena, Gustavo, Ibañez, Agustin, Petroni, Agustin, and Kamienkowski, Juan E.

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

The Trail Making Test (TMT) is one of the most popular neuropsychological tests in the clinical assessment of executive functions (EF) and research in a wide range of clinical conditions. In addition to its sensitivity to executive dysfunction, the TMT presents several strengths: it is simple and intuitive, it is easy to understand for patients, and has a short administration. However, it has important limitations. First, the underlying EFs articulated during the task are not well discriminated, which makes it a test with low specificity. Second, the traditional pen-and-paper version presents one trial per condition which introduces high variability. Third, only the total time is quantified, which does not allow for a detailed analysis. Fourth, it has a fixed spatial configuration per condition. In the present study we designed a computerized version of the TMT (cTMT) to overcome its main limitations. Eye and hand positions are simultaneously measured with high resolution, several trials are acquired, and spatial configuration of the targets is controlled. Our results showed a very similar performance profile compared to the traditional TMT. Moreover, it revealed similarities and differences in eye movements between the two parts of the task. Most importantly, we found an internal working memory measure of the cTMT based on hand and eye movements that showed an association to a validated working memory task. Additionally, we found another internal measure of the TMT, also based on hand and eye movements, that we propose as a potential marker of inhibitory control. Our results showed that executive functions can be studied in more detail using traditional tests combined with powerful digital setups. Finally, our study paved the way for a detailed analysis of other complex tasks used for clinical evaluation, providing a deeper understanding of the processes underlying its resolution.

Published
2021

13. Brain health in diverse settings: How age, demographics and cognition shape brain function

Author

Hernandez, Hernan, Baez, Sandra, Medel, Vicente, Moguilner, Sebastian, Cuadros, Jhosmary, Santamaria-Garcia, Hernando, Tagliazucchi, Enzo, Valdes-Sosa, Pedro A., Lopera, Francisco, OchoaGómez, John Fredy, González-Hernández, Alfredis, Bonilla-Santos, Jasmin, Gonzalez-Montealegre, Rodrigo A., Aktürk, Tuba, Yıldırım, Ebru, Anghinah, Renato, Legaz, Agustina, Fittipaldi, Sol, Yener, Görsev G., Escudero, Javier, Babiloni, Claudio, Lopez, Susanna, Whelan, Robert, Lucas, Alberto A Fernández, García, Adolfo M., Huepe, David, Caterina, Gaetano Di, Soto-Añari, Marcio, Birba, Agustina, Sainz-Ballesteros, Agustin, Coronel, Carlos, Herrera, Eduar, Abasolo, Daniel, Kilborn, Kerry, Rubido, Nicolás, Clark, Ruaridh, Herzog, Ruben, Yerlikaya, Deniz, Güntekin, Bahar, Parra, Mario A., Prado, Pavel, and Ibanez, Agustin

Published
2024
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16. Allostasis, health, and development in Latin America

Author

Migeot, Joaquín, Panesso, Carolina, Duran-Aniotz, Claudia, Ávila-Rincón, Cristian, Ochoa, Carolina, Huepe, David, Santamaría-García, Hernando, Miranda, J. Jaime, Escobar, María Josefina, Pina-Escudero, Stefanie, Romero-Ortuno, Roman, Lawlor, Brian, Ibáñez, Agustín, and Lipina, Sebastián

Published
2024
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18. A pre-registered, multi-lab non-replication of the action-sentence compatibility effect (ACE)

Author

Morey, Richard D, Kaschak, Michael P, Díez-Álamo, Antonio M, Glenberg, Arthur M, Zwaan, Rolf A, Lakens, Daniël, Ibáñez, Agustín, García, Adolfo, Gianelli, Claudia, Jones, John L, Madden, Julie, Alifano, Florencia, Bergen, Benjamin, Bloxsom, Nicholas G, Bub, Daniel N, Cai, Zhenguang G, Chartier, Christopher R, Chatterjee, Anjan, Conwell, Erin, Cook, Susan Wagner, Davis, Joshua D, Evers, Ellen RK, Girard, Sandrine, Harter, Derek, Hartung, Franziska, Herrera, Eduar, Huettig, Falk, Humphries, Stacey, Juanchich, Marie, Kühne, Katharina, Lu, Shulan, Lynes, Tom, Masson, Michael EJ, Ostarek, Markus, Pessers, Sebastiaan, Reglin, Rebecca, Steegen, Sara, Thiessen, Erik D, Thomas, Laura E, Trott, Sean, Vandekerckhove, Joachim, Vanpaemel, Wolf, Vlachou, Maria, Williams, Kristina, and Ziv-Crispel, Noam

Subjects
Behavioral and Social Science, Basic Behavioral and Social Science, Comprehension, Humans, Language, Movement, Reaction Time, Embodied cognition, Action-sentence compatibility effect, Psychology, Cognitive Sciences, Experimental Psychology
Abstract

The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre-registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.

Published
2022

19. Automated text-level semantic markers of Alzheimers disease.

Author

Sanz, Camila, Carrillo, Facundo, Slachevsky, Andrea, Forno, Gonzalo, Gorno Tempini, Maria, Villagra, Roque, Ibáñez, Agustín, Tagliazucchi, Enzo, and García, Adolfo

Subjects
Alzheimers disease dementia, Parkinsons disease, automated speech analysis, semantic granularity, semantic variability
Abstract

INTRODUCTION: Automated speech analysis has emerged as a scalable, cost-effective tool to identify persons with Alzheimers disease dementia (ADD). Yet, most research is undermined by low interpretability and specificity. METHODS: Combining statistical and machine learning analyses of natural speech data, we aimed to discriminate ADD patients from healthy controls (HCs) based on automated measures of domains typically affected in ADD: semantic granularity (coarseness of concepts) and ongoing semantic variability (conceptual closeness of successive words). To test for specificity, we replicated the analyses on Parkinsons disease (PD) patients. RESULTS: Relative to controls, ADD (but not PD) patients exhibited significant differences in both measures. Also, these features robustly discriminated between ADD patients and HC, while yielding near-chance classification between PD patients and HCs. DISCUSSION: Automated discourse-level semantic analyses can reveal objective, interpretable, and specific markers of ADD, bridging well-established neuropsychological targets with digital assessment tools.

Published
2022

20. Chronic neuropsychiatric sequelae of SARS‐CoV‐2: Protocol and methods from the Alzheimer's Association Global Consortium

Author

Erausquin, Gabriel A, Snyder, Heather, Brugha, Traolach S, Seshadri, Sudha, Carrillo, Maria, Sagar, Rajesh, Huang, Yueqin, Newton, Charles, Tartaglia, Carmela, Teunissen, Charlotte, Håkanson, Krister, Akinyemi, Rufus, Prasad, Kameshwar, D'Avossa, Giovanni, Gonzalez‐Aleman, Gabriela, Hosseini, Akram, Vavougios, George D, Sachdev, Perminder, Bankart, John, Mors, Niels Peter Ole, Lipton, Richard, Katz, Mindy, Fox, Peter T, Katshu, Mohammad Zia, Iyengar, M Sriram, Weinstein, Galit, Sohrabi, Hamid R, Jenkins, Rachel, Stein, Dan J, Hugon, Jacques, Mavreas, Venetsanos, Blangero, John, Cruchaga, Carlos, Krishna, Murali, Wadoo, Ovais, Becerra, Rodrigo, Zwir, Igor, Longstreth, William T, Kroenenberg, Golo, Edison, Paul, Mukaetova‐Ladinska, Elizabeta, Staufenberg, Ekkehart, Figueredo‐Aguiar, Mariana, Yécora, Agustín, Vaca, Fabiana, Zamponi, Hernan P, Re, Vincenzina Lo, Majid, Abdul, Sundarakumar, Jonas, Gonzalez, Hector M, Geerlings, Mirjam I, Skoog, Ingmar, Salmoiraghi, Alberto, Boneschi, Filippo Martinelli, Patel, Vibuthi N, Santos, Juan M, Arroyo, Guillermo Rivera, Moreno, Antonio Caballero, Felix, Pascal, Gallo, Carla, Arai, Hidenori, Yamada, Masahito, Iwatsubo, Takeshi, Sharma, Malveeka, Chakraborty, Nandini, Ferreccio, Catterina, Akena, Dickens, Brayne, Carol, Maestre, Gladys, Blangero, Sarah Williams, Brusco, Luis I, Siddarth, Prabha, Hughes, Timothy M, Zuñiga, Alfredo Ramírez, Kambeitz, Joseph, Laza, Agustin Ruiz, Allen, Norrina, Panos, Stella, Merrill, David, Ibáñez, Agustín, Tsuang, Debby, Valishvili, Nino, Shrestha, Srishti, Wang, Sophia, Padma, Vasantha, Anstey, Kaarin J, Ravindrdanath, Vijayalakshmi, Blennow, Kaj, Mullins, Paul, Łojek, Emilia, Pria, Anand, Mosley, Thomas H, Gowland, Penny, Girard, Timothy D, Bowtell, Richard, and Vahidy, Farhaan S

Subjects
Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Alzheimer's Disease, Infectious Diseases, Emerging Infectious Diseases, Clinical Research, Dementia, Neurodegenerative, Prevention, Acquired Cognitive Impairment, Aging, Aetiology, 2.1 Biological and endogenous factors, Neurological, Good Health and Well Being, cognitive impairment, dementia, neuropsychiatric sequelae, predictors, SARS-CoV-2, SARS‐CoV‐2
Abstract

IntroductionCoronavirus disease 2019 (COVID-19) has caused >3.5 million deaths worldwide and affected >160 million people. At least twice as many have been infected but remained asymptomatic or minimally symptomatic. COVID-19 includes central nervous system manifestations mediated by inflammation and cerebrovascular, anoxic, and/or viral neurotoxicity mechanisms. More than one third of patients with COVID-19 develop neurologic problems during the acute phase of the illness, including loss of sense of smell or taste, seizures, and stroke. Damage or functional changes to the brain may result in chronic sequelae. The risk of incident cognitive and neuropsychiatric complications appears independent from the severity of the original pulmonary illness. It behooves the scientific and medical community to attempt to understand the molecular and/or systemic factors linking COVID-19 to neurologic illness, both short and long term.MethodsThis article describes what is known so far in terms of links among COVID-19, the brain, neurological symptoms, and Alzheimer's disease (AD) and related dementias. We focus on risk factors and possible molecular, inflammatory, and viral mechanisms underlying neurological injury. We also provide a comprehensive description of the Alzheimer's Association Consortium on Chronic Neuropsychiatric Sequelae of SARS-CoV-2 infection (CNS SC2) harmonized methodology to address these questions using a worldwide network of researchers and institutions.ResultsSuccessful harmonization of designs and methods was achieved through a consensus process initially fragmented by specific interest groups (epidemiology, clinical assessments, cognitive evaluation, biomarkers, and neuroimaging). Conclusions from subcommittees were presented to the whole group and discussed extensively. Presently data collection is ongoing at 19 sites in 12 countries representing Asia, Africa, the Americas, and Europe.DiscussionThe Alzheimer's Association Global Consortium harmonized methodology is proposed as a model to study long-term neurocognitive sequelae of SARS-CoV-2 infection.Key pointsThe following review describes what is known so far in terms of molecular and epidemiological links among COVID-19, the brain, neurological symptoms, and AD and related dementias (ADRD)The primary objective of this large-scale collaboration is to clarify the pathogenesis of ADRD and to advance our understanding of the impact of a neurotropic virus on the long-term risk of cognitive decline and other CNS sequelae. No available evidence supports the notion that cognitive impairment after SARS-CoV-2 infection is a form of dementia (ADRD or otherwise). The longitudinal methodologies espoused by the consortium are intended to provide data to answer this question as clearly as possible controlling for possible confounders. Our specific hypothesis is that SARS-CoV-2 triggers ADRD-like pathology following the extended olfactory cortical network (EOCN) in older individuals with specific genetic susceptibility.The proposed harmonization strategies and flexible study designs offer the possibility to include large samples of under-represented racial and ethnic groups, creating a rich set of harmonized cohorts for future studies of the pathophysiology, determinants, long-term consequences, and trends in cognitive aging, ADRD, and vascular disease.We provide a framework for current and future studies to be carried out within the Consortium. and offers a "green paper" to the research community with a very broad, global base of support, on tools suitable for low- and middle-income countries aimed to compare and combine future longitudinal data on the topic.The Consortium proposes a combination of design and statistical methods as a means of approaching causal inference of the COVID-19 neuropsychiatric sequelae. We expect that deep phenotyping of neuropsychiatric sequelae may provide a series of candidate syndromes with phenomenological and biological characterization that can be further explored. By generating high-quality harmonized data across sites we aim to capture both descriptive and, where possible, causal associations.

Published
2022

22. The Human Affectome

Author

Schiller, Daniela, Yu, Alessandra N.C., Alia-Klein, Nelly, Becker, Susanne, Cromwell, Howard C., Dolcos, Florin, Eslinger, Paul J., Frewen, Paul, Kemp, Andrew H., Pace-Schott, Edward F., Raber, Jacob, Silton, Rebecca L., Stefanova, Elka, Williams, Justin H.G., Abe, Nobuhito, Aghajani, Moji, Albrecht, Franziska, Alexander, Rebecca, Anders, Silke, Aragón, Oriana R., Arias, Juan A., Arzy, Shahar, Aue, Tatjana, Baez, Sandra, Balconi, Michela, Ballarini, Tommaso, Bannister, Scott, Banta, Marlissa C., Barrett, Karen Caplovitz, Belzung, Catherine, Bensafi, Moustafa, Booij, Linda, Bookwala, Jamila, Boulanger-Bertolus, Julie, Boutros, Sydney Weber, Bräscher, Anne-Kathrin, Bruno, Antonio, Busatto, Geraldo, Bylsma, Lauren M., Caldwell-Harris, Catherine, Chan, Raymond C.K., Cherbuin, Nicolas, Chiarella, Julian, Cipresso, Pietro, Critchley, Hugo, Croote, Denise E., Demaree, Heath A., Denson, Thomas F., Depue, Brendan, Derntl, Birgit, Dickson, Joanne M., Dolcos, Sanda, Drach-Zahavy, Anat, Dubljević, Olga, Eerola, Tuomas, Ellingsen, Dan-Mikael, Fairfield, Beth, Ferdenzi, Camille, Friedman, Bruce H., Fu, Cynthia H.Y., Gatt, Justine M., de Gelder, Beatrice, Gendolla, Guido H.E., Gilam, Gadi, Goldblatt, Hadass, Gooding, Anne Elizabeth Kotynski, Gosseries, Olivia, Hamm, Alfons O., Hanson, Jamie L., Hendler, Talma, Herbert, Cornelia, Hofmann, Stefan G., Ibanez, Agustin, Joffily, Mateus, Jovanovic, Tanja, Kahrilas, Ian J., Kangas, Maria, Katsumi, Yuta, Kensinger, Elizabeth, Kirby, Lauren A.J., Koncz, Rebecca, Koster, Ernst H.W., Kozlowska, Kasia, Krach, Sören, Kret, Mariska E., Krippl, Martin, Kusi-Mensah, Kwabena, Ladouceur, Cecile D., Laureys, Steven, Lawrence, Alistair, Li, Chiang-shan R., Liddell, Belinda J., Lidhar, Navdeep K., Lowry, Christopher A., Magee, Kelsey, Marin, Marie-France, Mariotti, Veronica, Martin, Loren J., Marusak, Hilary A., Mayer, Annalina V., Merner, Amanda R., Minnier, Jessica, Moll, Jorge, Morrison, Robert G., Moore, Matthew, Mouly, Anne-Marie, Mueller, Sven C., Mühlberger, Andreas, Murphy, Nora A., Muscatello, Maria Rosaria Anna, Musser, Erica D., Newton, Tamara L., Noll-Hussong, Michael, Norrholm, Seth Davin, Northoff, Georg, Nusslock, Robin, Okon-Singer, Hadas, Olino, Thomas M., Ortner, Catherine, Owolabi, Mayowa, Padulo, Caterina, Palermo, Romina, Palumbo, Rocco, Palumbo, Sara, Papadelis, Christos, Pegna, Alan J., Pellegrini, Silvia, Peltonen, Kirsi, Penninx, Brenda W.J.H., Pietrini, Pietro, Pinna, Graziano, Lobo, Rosario Pintos, Polnaszek, Kelly L., Polyakova, Maryna, Rabinak, Christine, Helene Richter, S., Richter, Thalia, Riva, Giuseppe, Rizzo, Amelia, Robinson, Jennifer L., Rosa, Pedro, Sachdev, Perminder S., Sato, Wataru, Schroeter, Matthias L., Schweizer, Susanne, Shiban, Youssef, Siddharthan, Advaith, Siedlecka, Ewa, Smith, Robert C., Soreq, Hermona, Spangler, Derek P., Stern, Emily R., Styliadis, Charis, Sullivan, Gavin B., Swain, James E., Urben, Sébastien, Van den Stock, Jan, vander Kooij, Michael A., van Overveld, Mark, Van Rheenen, Tamsyn E., VanElzakker, Michael B., Ventura-Bort, Carlos, Verona, Edelyn, Volk, Tyler, Wang, Yi, Weingast, Leah T., Weymar, Mathias, Williams, Claire, Willis, Megan L., Yamashita, Paula, Zahn, Roland, Zupan, Barbra, and Lowe, Leroy

Published
2024
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30. Life-Course Brain Health as a Determinant of Late-Life Mental Health: American Association for Geriatric Psychiatry Expert Panel Recommendations

Author

Eyre, Harris A., Stirland, Lucy E., Jeste, Dilip V., Reynolds, Charles F., III, Berk, Michael, Ibanez, Agustin, Dawson, Walter D., Lawlor, Brian, Leroi, Iracema, Yaffe, Kristine, Gatchel, Jennifer R., Karp, Jordan F., Newhouse, Paul, Rosand, Jonathan, Letourneau, Nicole, Bayen, Eleonore, Farina, Francesca, Booi, Laura, Devanand, Devangere P., Mintzer, Jacobo, Madigan, Sheri, Jayapurwala, Inez, Wong, Stephen T.C., Falcoa, Veronica Podence, Cummings, Jeffrey L., Reichman, William, Lock, Sarah Lenz, Bennett, Marc, Ahuja, Rajiv, Steffens, David C., Elkind, Mitchell S.V., and Lavretsky, Helen

Published
2023
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32. Uncovering social-contextual and individual mental health factors associated with violence via computational inference.

Author

Santamaría-García, Hernando, Baez, Sandra, Aponte-Canencio, Diego Mauricio, Pasciarello, Guido Orlando, Donnelly-Kehoe, Patricio Andrés, Maggiotti, Gabriel, Matallana, Diana, Hesse, Eugenia, Neely, Alejandra, Zapata, José Gabriel, Chiong, Winston, Levy, Jonathan, Decety, Jean, and Ibáñez, Agustín

Subjects
deep neural networks, ex-members of illegal armed groups, machine learning methods, mental disorders, mental health, personality traits, social adversity, social resources, violence
Abstract

The identification of human violence determinants has sparked multiple questions from different academic fields. Innovative methodological assessments of the weight and interaction of multiple determinants are still required. Here, we examine multiple features potentially associated with confessed acts of violence in ex-members of illegal armed groups in Colombia (N = 26,349) through deep learning and feature-derived machine learning. We assessed 162 social-contextual and individual mental health potential predictors of historical data regarding consequentialist, appetitive, retaliative, and reactive domains of violence. Deep learning yields high accuracy using the full set of determinants. Progressive feature elimination revealed that contextual factors were more important than individual factors. Combined social network adversities, membership identification, and normalization of violence were among the more accurate social-contextual factors. To a lesser extent the best individual factors were personality traits (borderline, paranoid, and antisocial) and psychiatric symptoms. The results provide a population-based computational classification regarding historical assessments of violence in vulnerable populations.

Published
2021

34. Modeling the relationship between regional activation and functional connectivity during wakefulness and sleep

Author

Ipiña, Ignacio Perez, Kehoe, Patricio Donnelly, Kringelbach, Morten, Laufs, Helmut, Ibañez, Agustín, Deco, Gustavo, Perl, Yonatan Sanz, and Tagliazucchi, Enzo

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Global brain activity self-organizes into discrete patterns characterized by distinct behavioral observables and modes of information processing. The human thalamocortical system is a densely connected network where local neural activation reciprocally influences coordinated collective dynamics. We introduce a semi-empirical model to investigate the relationship between regional activation and long-range functional connectivity in the different brain states visited during the natural wake-sleep cycle. Our model combines functional magnetic resonance imaging (fMRI) data, in vivo estimates of structural connectivity, and anatomically-informed priors that constrain the independent variation of regional activation. As expected, priors based on functionally coherent networks resulted in the best fit between empirical and simulated brain activity. We show that sleep progressively divided the cortex into regions presenting opposite dynamical behavior: frontoparietal regions approached a bifurcation towards local oscillatory dynamics, while sensorimotor regions presented stable dynamics governed by noise. In agreement with human electrophysiological experiments, sleep onset induced subcortical deactivation and uncoupling, which was subsequently reversed for deeper stages. Finally, we introduced external forcing of variable intensity to simulate external perturbations, and identifiedthe key regionsespecially relevant for the recovery of wakefulness from deep sleep. Our model represents sleep as a state where long-range decoupling and regional deactivation coexist with the latent capacity for a rapid transition towards wakefulness. The mechanistic insights provided by our simulations allow the in silico parametric exploration of such transitions in terms of external perturbations, with potential applications for the control of physiological and pathological brain states.

Published
2019

36. Exchanging screen for non-screen sitting time or physical activity might attenuate depression and anxiety: A cross-sectional isotemporal analysis during early pandemics in South America

Author

Sadarangani, Kabir P., Schuch, Felipe Barreto, De Roia, Gabriela, Martínez-Gomez, David, Chávez, Róbinson, Lobo, Pablo, Cristi-Montero, Carlos, Werneck, André O., Alzahrani, Hosam, Ferrari, Gerson, Ibanez, Agustin, Silva, Danilo R., Von Oetinger, Astrid, Matias, Thiago S., Grabovac, Igor, and Meyer, Jacob

Published
2023
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48. Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

Author

Yener, Görsev, Hünerli-Gündüz, Duygu, Yıldırım, Ebru, Aktürk, Tuba, Başar-Eroğlu, Canan, Bonanni, Laura, Del Percio, Claudio, Farina, Francesca, Ferri, Raffaele, Güntekin, Bahar, Hajós, Mihály, Ibáñez, Agustín, Jiang, Yang, Lizio, Roberta, Lopez, Susanna, Noce, Giuseppe, Parra, Mario A, Randall, Fiona, Stocchi, Fabrizio, and Babiloni, Claudio

Published
2022
Full Text
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49. Allostatic-Interoceptive Overload in Frontotemporal Dementia

Author

Birba, Agustina, Santamaría-García, Hernando, Prado, Pavel, Cruzat, Josefina, Ballesteros, Agustín Sainz, Legaz, Agustina, Fittipaldi, Sol, Duran-Aniotz, Claudia, Slachevsky, Andrea, Santibañez, Rodrigo, Sigman, Mariano, García, Adolfo M., Whelan, Robert, Moguilner, Sebastián, and Ibáñez, Agustín

Published
2022
Full Text
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