1
|
Moguilner S, Herzog R, Perl YS, Medel V, Cruzat J, Coronel C, Kringelbach M, Deco G, Ibáñez A, Tagliazucchi E. Biophysical models applied to dementia patients reveal links between geographical origin, gender, disease duration, and loss of neural inhibition. Alzheimers Res Ther 2024; 16:79. [PMID: 38605416 PMCID: PMC11008050 DOI: 10.1186/s13195-024-01449-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 04/02/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND The hypothesis of decreased neural inhibition in dementia has been sparsely studied in functional magnetic resonance imaging (fMRI) data across patients with different dementia subtypes, and the role of social and demographic heterogeneities on this hypothesis remains to be addressed. METHODS We inferred regional inhibition by fitting a biophysical whole-brain model (dynamic mean field model with realistic inter-areal connectivity) to fMRI data from 414 participants, including patients with Alzheimer's disease, behavioral variant frontotemporal dementia, and controls. We then investigated the effect of disease condition, and demographic and clinical variables on the local inhibitory feedback, a variable related to the maintenance of balanced neural excitation/inhibition. RESULTS Decreased local inhibitory feedback was inferred from the biophysical modeling results in dementia patients, specific to brain areas presenting neurodegeneration. This loss of local inhibition correlated positively with years with disease, and showed differences regarding the gender and geographical origin of the patients. The model correctly reproduced known disease-related changes in functional connectivity. CONCLUSIONS Results suggest a critical link between abnormal neural and circuit-level excitability levels, the loss of grey matter observed in dementia, and the reorganization of functional connectivity, while highlighting the sensitivity of the underlying biophysical mechanism to demographic and clinical heterogeneities in the patient population.
Collapse
Affiliation(s)
- Sebastian Moguilner
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), 1207 1651 4th St, 3rd Floor, San Francisco, CA, 94143, USA
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Vito Dumas 284, B1644BID, Buenos Aires, VIC, Argentina
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
- Trinity College Dublin, Lloyd Building Trinity College Dublin, Dublin, D02 PN40, Ireland
| | - Rubén Herzog
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
| | - Yonatan Sanz Perl
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Vito Dumas 284, B1644BID, Buenos Aires, VIC, Argentina
- National Scientific and Technical Research Council (CONICET), Godoy Cruz 2290, CABA, 1425, Argentina
- Institute of Applied and Interdisciplinary Physics and Department of Physics, University of Buenos Aires, Pabellón 1, Ciudad Universitaria, CABA, 1428, Argentina
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Plaça de La Mercè, 10-12, Barcelona, 08002, Spain
| | - Vicente Medel
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
- Centro Interdisciplinario de Neurociencia de Valparaíso (CINV), Universidad de Valparaíso, Harrington 287, Valparaíso, 2381850, Chile
| | - Josefina Cruzat
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
| | - Carlos Coronel
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, St.Cross Rd, Oxford, OX1 3JA, UK
- Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Ln, Headington, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Blvd. 82, Aarhus, 8200, Denmark
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Plaça de La Mercè, 10-12, Barcelona, 08002, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, Leipzig, 04103, Germany
- Institució Catalana de Recerca I Estudis Avancats (ICREA), Passeig de Lluís Companys, 23, Barcelona, 08010, Spain
- Turner Institute for Brain and Mental Health, Monash University, 770 Blackburn Rd,, Clayton, VIC, 3168, Australia
| | - Agustín Ibáñez
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile.
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), 1207 1651 4th St, 3rd Floor, San Francisco, CA, 94143, USA.
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Vito Dumas 284, B1644BID, Buenos Aires, VIC, Argentina.
- Trinity College Institute of Neuroscience, Trinity College Dublin, 152 - 160 Pearse St, Dublin, D02 R590, Ireland.
- Trinity College Dublin, Lloyd Building Trinity College Dublin, Dublin, D02 PN40, Ireland.
| | - Enzo Tagliazucchi
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile.
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Vito Dumas 284, B1644BID, Buenos Aires, VIC, Argentina.
- National Scientific and Technical Research Council (CONICET), Godoy Cruz 2290, CABA, 1425, Argentina.
- Institute of Applied and Interdisciplinary Physics and Department of Physics, University of Buenos Aires, Pabellón 1, Ciudad Universitaria, CABA, 1428, Argentina.
| |
Collapse
|
2
|
Prado P, Medel V, Gonzalez-Gomez R, Sainz-Ballesteros A, Vidal V, Santamaría-García H, Moguilner S, Mejia J, Slachevsky A, Behrens MI, Aguillon D, Lopera F, Parra MA, Matallana D, Maito MA, Garcia AM, Custodio N, Funes AÁ, Piña-Escudero S, Birba A, Fittipaldi S, Legaz A, Ibañez A. The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds. Sci Data 2023; 10:889. [PMID: 38071313 PMCID: PMC10710425 DOI: 10.1038/s41597-023-02806-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 11/30/2023] [Indexed: 12/18/2023] Open
Abstract
The Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD), multiple sclerosis (MS), Parkinson's disease (PD), and 250 healthy controls (HCs). This dataset (62.7 ± 9.5 years, age range 21-89 years) was collected through a multicentric effort across five Latin American countries to address the need for affordable, scalable, and available biomarkers in regions with larger inequities. The BrainLat is the first regional collection of clinical and cognitive assessments, anatomical magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), diffusion-weighted MRI (DWI), and high density resting-state electroencephalography (EEG) in dementia patients. In addition, it includes demographic information about harmonized recruitment and assessment protocols. The dataset is publicly available to encourage further research and development of tools and health applications for neurodegeneration based on multimodal neuroimaging, promoting the assessment of regional variability and inclusion of underrepresented participants in research.
Collapse
Affiliation(s)
- Pavel Prado
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
| | - Vicente Medel
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Raul Gonzalez-Gomez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | | | - Victor Vidal
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Hernando Santamaría-García
- PhD Neuroscience Program, Physiology and Psychiatry Departments, Pontificia Universidad Javeriana, Bogotá, Colombia
- Memory and Cognition Center Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
- Global Brain Health Institute, University of California San Francisco, San Francisco, USA
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Sebastian Moguilner
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés & CONICET, Buenos Aires, Argentina
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jhony Mejia
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Departamento de Ingeniería Biomédica, Universidad de Los Andes, Bogotá, Colombia
- Memory and Aging Clinic, University of California San Francisco, San Francisco, USA
| | - Andrea Slachevsky
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department - Institute of Biomedical Sciences (ICBM), Neurocience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Santiago de Chile, Chile
- Geroscience Center for Brain Health and Metabolism, (GERO), Santiago de Chile, Chile
- Memory and Neuropsychiatric Center (CMYN), Memory Unit - Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, Santiago de Chile, Chile
- Servicio de Neurología, Departamento de Medicina, Clínica Alemana-Universidad del Desarrollo, Santiago de Chile, Chile
| | - Maria Isabel Behrens
- Centro de Investigación Clínica Avanzada (CICA), Facultad de Medicina-Hospital Clínico, Universidad de Chile, Independencia, Santiago, 8380453, Chile
- Departamento de Neurología y Neurocirugía, Hospital Clínico Universidad de Chile, Independencia, Santiago, 8380430, Chile
- Departamento de Neurociencia, Facultad de Medicina, Universidad de Chile, Independencia, Santiago, 8380453, Chile
- Departamento de Neurología y Psiquiatría, Clínica Alemana-Universidad del Desarrollo, Santiago, 8370065, Chile
| | - David Aguillon
- Grupo de Neurociencias de Antioquia de la Universidad de Antioquia, Medellín, Colombia
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia de la Universidad de Antioquia, Medellín, Colombia
| | - Mario A Parra
- School of Psychological Sciences and Health, University of Strathclyde, Glasgow, United Kingdom
| | - Diana Matallana
- PhD Neuroscience Program, Physiology and Psychiatry Departments, Pontificia Universidad Javeriana, Bogotá, Colombia
- Memory and Cognition Center Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
- Mental Health Department, Hospital Universitario Fundación Santa Fe de Bogotá, Memory Clinic, Bogotá, Colombia
| | - Marcelo Adrián Maito
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés & CONICET, Buenos Aires, Argentina
| | - Adolfo M Garcia
- Global Brain Health Institute, University of California San Francisco, San Francisco, USA
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés & CONICET, Buenos Aires, Argentina
- Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - Nilton Custodio
- Unit Cognitive Impairment and Dementia Prevention, Peruvian Institute of Neurosciences, Lima, Peru
| | - Alberto Ávila Funes
- Geriatrics Department, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Stefanie Piña-Escudero
- Global Brain Health Institute, University of California San Francisco, San Francisco, USA
- Memory and Aging Clinic, University of California San Francisco, San Francisco, USA
| | - Agustina Birba
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés & CONICET, Buenos Aires, Argentina
- Instituto Universitario de Neurociencia, Universidad de La Laguna, Tenerife, Spain
- Facultad de Psicología, Universidad de La Laguna, Tenerife, Spain
| | - Sol Fittipaldi
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés & CONICET, Buenos Aires, Argentina
| | - Agustina Legaz
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés & CONICET, Buenos Aires, Argentina
| | - Agustín Ibañez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile.
- Global Brain Health Institute, University of California San Francisco, San Francisco, USA.
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés & CONICET, Buenos Aires, Argentina.
| |
Collapse
|
3
|
Ogonowski N, Santamaria-Garcia H, Baez S, Lopez A, Laserna A, Garcia-Cifuentes E, Ayala-Ramirez P, Zarante I, Suarez-Obando F, Reyes P, Kauffman M, Cochran N, Schulte M, Sirkis DW, Spina S, Yokoyama JS, Miller BL, Kosik KS, Matallana D, Ibáñez A. Frontotemporal dementia presentation in patients with heterozygous p.H157Y variant of TREM2. J Med Genet 2023; 60:894-904. [PMID: 36813542 PMCID: PMC10447405 DOI: 10.1136/jmg-2022-108627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 02/06/2023] [Indexed: 02/24/2023]
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 Alzheimer's 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.
Collapse
Affiliation(s)
- Natalia Ogonowski
- Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Adolfo Ibanez University, Santiago, Chile, Santiago de Chile, Chile
| | - Hernando Santamaria-Garcia
- Global Brain Health Institute (GBHI), University California San Francisco (UCSF), San Francisco, California, USA
- Pontificia Universidad Javeriana. Ph.D Program of Neuroscience, Bogotá, Colombia
- Hospital Universitario San Ignacio. Centro de Memoria y Cognición Intellectus, Bogotá, Colombia
| | | | - Andrea Lopez
- Hospital Universitario de la Fundación Santa Fe de Bogotá, Bogota, Colombia
- Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Andrés Laserna
- Pontificia Universidad Javeriana, Bogota, Colombia
- University of Rochester Medical Center. Department of Anesthesiology and Perioperative Medicine. of Anesthesiology and Perioperative Medicine, Rochester, NY, New York, USA
| | - Elkin Garcia-Cifuentes
- Pontificia Universidad Javeriana, Bogota, Colombia
- Hospital Universitario San Ignacio, Bogotá, Colombia
| | - Paola Ayala-Ramirez
- Human Genomics Institute, Pontificia Universidad Javeriana, Bogota, Colombia
| | | | | | - Pablo Reyes
- Pontificia Universidad Javeriana, Bogota, Colombia
| | - Marcelo Kauffman
- Hospital General de Agudos Jose Maria Ramos Mejia Consultorio y Laboratorio de Neurogenetica, Buenos Aires, Argentina
- Universidad Austral. IIMT-FCB. Conicet, Buenos Aires, Argentina
| | | | | | - Daniel W Sirkis
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
- Weil Institute of Neuroscience, University of California, San Francisco, San Francisco, California, USA
| | - Salvatore Spina
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Jennifer S Yokoyama
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
- Weil Institute of Neuroscience, University of California, San Francisco, San Francisco, California, USA
| | | | - Kenneth S Kosik
- University of California Santa Barbara, Santa Barbara, California, USA
| | - Diana Matallana
- Pontificia Universidad Javeriana, Bogota, Colombia
- Hospital Universitario Fundación Santa Fe, Bogotá, Colombia
| | - Agustín Ibáñez
- Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Adolfo Ibanez University, Santiago, Chile, Santiago de Chile, Chile
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Cognitive Neuroscience Center (CNC), Universidad de San Andres & CONICET, Buenos Aires, Argentina
| |
Collapse
|
4
|
Santamaria-Garcia H, Moguilner S, Rodriguez-Villagra OA, Botero-Rodriguez F, Pina-Escudero SD, O'Donovan G, Albala C, Matallana D, Schulte M, Slachevsky A, Yokoyama JS, Possin K, Ndhlovu LC, Al-Rousan T, Corley MJ, Kosik KS, Muniz-Terrera G, Miranda JJ, Ibanez A. The impacts of social determinants of health and cardiometabolic factors on cognitive and functional aging in Colombian underserved populations. GeroScience 2023; 45:2405-2423. [PMID: 36849677 PMCID: PMC10651610 DOI: 10.1007/s11357-023-00755-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 02/14/2023] [Indexed: 03/01/2023] Open
Abstract
Global initiatives call for further understanding of the impact of inequity on aging across underserved populations. Previous research in low- and middle-income countries (LMICs) presents limitations in assessing combined sources of inequity and outcomes (i.e., cognition and functionality). In this study, we assessed how social determinants of health (SDH), cardiometabolic factors (CMFs), and other medical/social factors predict cognition and functionality in an aging Colombian population. We ran a cross-sectional study that combined theory- (structural equation models) and data-driven (machine learning) approaches in a population-based study (N = 23,694; M = 69.8 years) to assess the best predictors of cognition and functionality. We found that a combination of SDH and CMF accurately predicted cognition and functionality, although SDH was the stronger predictor. Cognition was predicted with the highest accuracy by SDH, followed by demographics, CMF, and other factors. A combination of SDH, age, CMF, and additional physical/psychological factors were the best predictors of functional status. Results highlight the role of inequity in predicting brain health and advancing solutions to reduce the cognitive and functional decline in LMICs.
Collapse
Affiliation(s)
- Hernando Santamaria-Garcia
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA, USA.
- Pontificia Universidad Javeriana (Ph.D. Program in Neuroscience, Department of Psychiatry), Bogotá, Colombia.
- Center of Memory and Cognition Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia.
| | - Sebastian Moguilner
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Chile
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, and CONICET, Buenos Aires, Argentina
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Felipe Botero-Rodriguez
- Pontificia Universidad Javeriana (Ph.D. Program in Neuroscience, Department of Psychiatry), Bogotá, Colombia
| | - Stefanie Danielle Pina-Escudero
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA, USA
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Gary O'Donovan
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Chile
- Facultad de Medicina, Universidad de los Andes, Bogotá, Colombia
| | - Cecilia Albala
- Instituto de Nutrición Y Tecnología de los Alimentos, Universidad de Chile, Avenida El Líbano 5524, Macul, Santiago, Chile
| | - Diana Matallana
- Pontificia Universidad Javeriana (Ph.D. Program in Neuroscience, Department of Psychiatry), Bogotá, Colombia
- Center of Memory and Cognition Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
- Mental Health Department, Hospital Universitario Fundación Santa Fe de Bogotá, Memory Clinic, Bogotá, Colombia
| | - Michael Schulte
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Chile
| | - Andrea Slachevsky
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department - Institute of Biomedical Sciences (ICBM), Neurocience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Santiago de Chile, Chile
- Geroscience Center for Brain Health and Metabolism, (GERO), Santiago de Chile, Chile
- Memory and Neuropsychiatric Center (CMYN), Memory Unit - Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, Santiago de Chile, Chile
- Servicio de Neurología, Departamento de Medicina, Clínica Alemana-Universidad del Desarrollo, Santiago de Chile, Chile
| | - Jennifer S Yokoyama
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA, USA
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Katherine Possin
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA, USA
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Lishomwa C Ndhlovu
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York, NY, USA
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Tala Al-Rousan
- Herbert Wertheim School of Public Health, University of California San Diego, La Jolla, CA, USA
| | - Michael J Corley
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York, NY, USA
| | - Kenneth S Kosik
- Neuroscience Research Institute. Department of Molecular Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, USA
| | - Graciela Muniz-Terrera
- Edinburgh Dementia Prevention, University of Edinburgh, Edinburgh, UK
- Department of Primary Care, Ohio University, Athens, USA
| | - J Jaime Miranda
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru
- Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
- The George Institute for Global Health, UNSW, Sydney, Australia
| | - Agustin Ibanez
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA, USA.
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Chile.
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, and CONICET, Buenos Aires, Argentina.
- Trinity College Dublin (TCD), Dublin, Ireland.
| |
Collapse
|
5
|
Perl YS, Zamora-Lopez G, Montbrió E, Monge-Asensio M, Vohryzek J, Fittipaldi S, Campo CG, Moguilner S, Ibañez A, Tagliazucchi E, Yeo BTT, Kringelbach ML, Deco G. The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations. Netw Neurosci 2023; 7:632-660. [PMID: 37397876 PMCID: PMC10312285 DOI: 10.1162/netn_a_00299] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 12/02/2022] [Indexed: 12/25/2023] Open
Abstract
Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontaneous brain activity. In particular, biophysically grounded mean-field whole-brain models in the asynchronous regime were used to demonstrate the dynamical consequences of including regional variability. Nevertheless, the role of heterogeneities when brain dynamics are supported by synchronous oscillating state, which is a ubiquitous phenomenon in brain, remains poorly understood. Here, we implemented two models capable of presenting oscillatory behavior with different levels of abstraction: a phenomenological Stuart-Landau model and an exact mean-field model. The fit of these models informed by structural- to functional-weighted MRI signal (T1w/T2w) allowed us to explore the implication of the inclusion of heterogeneities for modeling resting-state fMRI recordings from healthy participants. We found that disease-specific regional functional heterogeneity imposed dynamical consequences within the oscillatory regime in fMRI recordings from neurodegeneration with specific impacts on brain atrophy/structure (Alzheimer's patients). Overall, we found that models with oscillations perform better when structural and functional regional heterogeneities are considered, showing that phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.
Collapse
Affiliation(s)
- Yonatan Sanz Perl
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Gorka Zamora-Lopez
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Ernest Montbrió
- Neuronal Dynamics Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Martí Monge-Asensio
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Jakub Vohryzek
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom
| | - Sol Fittipaldi
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, CA, USA; and Trinity College Dublin, Dublin, Ireland
| | - Cecilia González Campo
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - Sebastián Moguilner
- Global Brain Health Institute, University of California, San Francisco, CA, USA; and Trinity College Dublin, Dublin, Ireland
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Agustín Ibañez
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, CA, USA; and Trinity College Dublin, Dublin, Ireland
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Trinity College Institute of Neuroscience (TCIN), Trinity College Dublin, Dublin, Ireland
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - B. T. Thomas Yeo
- Centre for Sleep and Cognition, Centre for Translational MR Research, Department of Electrical and Computer Engineering, N.1 Institute for Health and Institute for Digital Medicine, National University of Singapore, Singapore
| | - Morten L. Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avancats (ICREA), Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Australia
| |
Collapse
|
6
|
Sanz Perl Y, Fittipaldi S, Gonzalez Campo C, Moguilner S, Cruzat J, Fraile-Vazquez ME, Herzog R, Kringelbach ML, Deco G, Prado P, Ibanez A, Tagliazucchi E. Model-based whole-brain perturbational landscape of neurodegenerative diseases. eLife 2023; 12:e83970. [PMID: 36995213 PMCID: PMC10063230 DOI: 10.7554/elife.83970] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 03/15/2023] [Indexed: 03/31/2023] Open
Abstract
The treatment of neurodegenerative diseases is hindered by lack of interventions capable of steering multimodal whole-brain dynamics towards patterns indicative of preserved brain health. To address this problem, we combined deep learning with a model capable of reproducing whole-brain functional connectivity in patients diagnosed with Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD). These models included disease-specific atrophy maps as priors to modulate local parameters, revealing increased stability of hippocampal and insular dynamics as signatures of brain atrophy in AD and bvFTD, respectively. Using variational autoencoders, we visualized different pathologies and their severity as the evolution of trajectories in a low-dimensional latent space. Finally, we perturbed the model to reveal key AD- and bvFTD-specific regions to induce transitions from pathological to healthy brain states. Overall, we obtained novel insights on disease progression and control by means of external stimulation, while identifying dynamical mechanisms that underlie functional alterations in neurodegeneration.
Collapse
Affiliation(s)
- Yonatan Sanz Perl
- Department of Physics, University of Buenos AiresBuenos AiresArgentina
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu FabraBarcelonaSpain
| | - Sol Fittipaldi
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
| | - Cecilia Gonzalez Campo
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
| | - Sebastián Moguilner
- Global Brain Health Institute, University of California, San FranciscoSan FranciscoUnited States
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
| | - Josephine Cruzat
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu FabraBarcelonaSpain
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
| | | | - Rubén Herzog
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
| | - Morten L Kringelbach
- Department of Psychiatry, University of OxfordOxfordUnited Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus UniversityÅrhusDenmark
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of MinhoBragaPortugal
- Centre for Eudaimonia and Human Flourishing, University of OxfordOxfordUnited Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu FabraBarcelonaSpain
- Department of Information and Communication Technologies, Universitat Pompeu FabraBarcelonaSpain
- Institució Catalana de la Recerca i Estudis Avancats (ICREA)BarcelonaSpain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- School of Psychological Sciences, Monash UniversityClaytonAustralia
| | - Pavel Prado
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
- Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San SebastiánSantiagoChile
| | - Agustin Ibanez
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
- Global Brain Health Institute, University of California, San FranciscoSan FranciscoUnited States
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
- Trinity College Institute of Neuroscience (TCIN), Trinity College DublinDublinIreland
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos AiresBuenos AiresArgentina
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
| |
Collapse
|
7
|
Cruzat J, Herzog R, Prado P, Sanz-Perl Y, Gonzalez-Gomez R, Moguilner S, Kringelbach ML, Deco G, Tagliazucchi E, Ibañez A. Temporal Irreversibility of Large-Scale Brain Dynamics in Alzheimer's Disease. J Neurosci 2023; 43:1643-1656. [PMID: 36732071 PMCID: PMC10008060 DOI: 10.1523/jneurosci.1312-22.2022] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 12/12/2022] [Accepted: 12/25/2022] [Indexed: 02/04/2023] Open
Abstract
Healthy brain dynamics can be understood as the emergence of a complex system far from thermodynamic equilibrium. Brain dynamics are temporally irreversible and thus establish a preferred direction in time (i.e., arrow of time). However, little is known about how the time-reversal symmetry of spontaneous brain activity is affected by Alzheimer's disease (AD). We hypothesized that the level of irreversibility would be compromised in AD, signaling a fundamental shift in the collective properties of brain activity toward equilibrium dynamics. We investigated the irreversibility from resting-state fMRI and EEG data in male and female human patients with AD and elderly healthy control subjects (HCs). We quantified the level of irreversibility and, thus, proximity to nonequilibrium dynamics by comparing forward and backward time series through time-shifted correlations. AD was associated with a breakdown of temporal irreversibility at the global, local, and network levels, and at multiple oscillatory frequency bands. At the local level, temporoparietal and frontal regions were affected by AD. The limbic, frontoparietal, default mode, and salience networks were the most compromised at the network level. The temporal reversibility was associated with cognitive decline in AD and gray matter volume in HCs. The irreversibility of brain dynamics provided higher accuracy and more distinctive information than classical neurocognitive measures when differentiating AD from control subjects. Findings were validated using an out-of-sample cohort. Present results offer new evidence regarding pathophysiological links between the entropy generation rate of brain dynamics and the clinical presentation of AD, opening new avenues for dementia characterization at different levels.SIGNIFICANCE STATEMENT By assessing the irreversibility of large-scale dynamics across multiple brain signals, we provide a precise signature capable of distinguishing Alzheimer's disease (AD) at the global, local, and network levels and different oscillatory regimes. Irreversibility of limbic, frontoparietal, default-mode, and salience networks was the most compromised by AD compared with more sensory-motor networks. Moreover, the time-irreversibility properties associated with cognitive decline and atrophy outperformed and complemented classical neurocognitive markers of AD in predictive classification performance. Findings were generalized and replicated with an out-of-sample validation procedure. We provide novel multilevel evidence of reduced irreversibility in AD brain dynamics that has the potential to open new avenues for understating neurodegeneration in terms of the temporal asymmetry of brain dynamics.
Collapse
Affiliation(s)
- Josephine Cruzat
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Fundación para el Estudio de la Conciencia Humana (ECoH), 7550000, Santiago, Chile
| | - Ruben Herzog
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Fundación para el Estudio de la Conciencia Humana (ECoH), 7550000, Santiago, Chile
| | - Pavel Prado
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
| | - Yonatan Sanz-Perl
- Department of Physics, University of Buenos Aires, C1428EGA, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), C1033AAJ, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, C116ABJ, Buenos Aires, Argentina
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, 08005 Barcelona, Spain
| | - Raul Gonzalez-Gomez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
| | - Sebastian Moguilner
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Global Brain Health Institute, University of California, San Francisco, San Francisco, California 94143
- Global Brain Health Institute, Trinity College, Dublin 2, Ireland
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, 8000 Århus, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford OX3 9BX, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, 08005 Barcelona, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avancats (ICREA), 08010 Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, D-04303 Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne 3168, Australia
| | - Enzo Tagliazucchi
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Department of Physics, University of Buenos Aires, C1428EGA, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), C1033AAJ, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, C116ABJ, Buenos Aires, Argentina
| | - Agustín Ibañez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- National Scientific and Technical Research Council (CONICET), C1033AAJ, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, C116ABJ, Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, San Francisco, California 94143
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
| |
Collapse
|
8
|
Castro Martínez JC, Santamaría-García H. Understanding mental health through computers: An introduction to computational psychiatry. Front Psychiatry 2023; 14:1092471. [PMID: 36824671 PMCID: PMC9941647 DOI: 10.3389/fpsyt.2023.1092471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 01/16/2023] [Indexed: 02/10/2023] Open
Abstract
Computational psychiatry recently established itself as a new tool in the study of mental disorders and problems. Integration of different levels of analysis is creating computational phenotypes with clinical and research values, and constructing a way to arrive at precision psychiatry are part of this new branch. It conceptualizes the brain as a computational organ that receives from the environment parameters to respond to challenges through calculations and algorithms in continuous feedback and feedforward loops with a permanent degree of uncertainty. Through this conception, one can seize an understanding of the cerebral and mental processes in the form of theories or hypotheses based on data. Using these approximations, a better understanding of the disorder and its different determinant factors facilitates the diagnostics and treatment by having an individual, ecologic, and holistic approach. It is a tool that can be used to homologate and integrate multiple sources of information given by several theoretical models. In conclusion, it helps psychiatry achieve precision and reproducibility, which can help the mental health field achieve significant advancement. This article is a narrative review of the basis of the functioning of computational psychiatry with a critical analysis of its concepts.
Collapse
Affiliation(s)
- Juan Camilo Castro Martínez
- Departamento de Psiquiatría y Salud Mental, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Hernando Santamaría-García
- Ph.D. Programa de Neurociencias, Departamento de Psiquiatría y Salud Mental, Pontificia Universidad Javeriana, Bogotá, Colombia
- Centro de Memoria y Cognición Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
- Global Brain Health Institute, University of California, San Francisco – Trinity College Dublin, San Francisco, CA, United States
| |
Collapse
|
9
|
Maito MA, Santamaría-García H, Moguilner S, Possin KL, Godoy ME, Avila-Funes JA, Behrens MI, Brusco IL, Bruno MA, Cardona JF, Custodio N, García AM, Javandel S, Lopera F, Matallana DL, Miller B, Okada de Oliveira M, Pina-Escudero SD, Slachevsky A, Sosa Ortiz AL, Takada LT, Tagliazuchi E, Valcour V, Yokoyama JS, Ibañez A. Classification of Alzheimer's disease and frontotemporal dementia using routine clinical and cognitive measures across multicentric underrepresented samples: A cross sectional observational study. LANCET REGIONAL HEALTH. AMERICAS 2023; 17:100387. [PMID: 36583137 PMCID: PMC9794191 DOI: 10.1016/j.lana.2022.100387] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 09/20/2022] [Accepted: 10/14/2022] [Indexed: 11/06/2022]
Abstract
Background Global brain health initiatives call for improving methods for the diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD) in underrepresented populations. However, diagnostic procedures in upper-middle-income countries (UMICs) and lower-middle income countries (LMICs), such as Latin American countries (LAC), face multiple challenges. These include the heterogeneity in diagnostic methods, lack of clinical harmonisation, and limited access to biomarkers. Methods This cross-sectional observational study aimed to identify the best combination of predictors to discriminate between AD and FTD using demographic, clinical and cognitive data among 1794 participants [904 diagnosed with AD, 282 diagnosed with FTD, and 606 healthy controls (HCs)] collected in 11 clinical centres across five LAC (ReDLat cohort). Findings A fully automated computational approach included classical statistical methods, support vector machine procedures, and machine learning techniques (random forest and sequential feature selection procedures). Results demonstrated an accurate classification of patients with AD and FTD and HCs. A machine learning model produced the best values to differentiate AD from FTD patients with an accuracy = 0.91. The top features included social cognition, neuropsychiatric symptoms, executive functioning performance, and cognitive screening; with secondary contributions from age, educational attainment, and sex. Interpretation Results demonstrate that data-driven techniques applied in archival clinical datasets could enhance diagnostic procedures in regions with limited resources. These results also suggest specific fine-grained cognitive and behavioural measures may aid in the diagnosis of AD and FTD in LAC. Moreover, our results highlight an opportunity for harmonisation of clinical tools for dementia diagnosis in the region. Funding This work was supported by the Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat), funded by NIA/NIH (R01AG057234), Alzheimer's Association (SG-20-725707-ReDLat), Rainwater Foundation, Takeda (CW2680521), Global Brain Health Institute; as well as CONICET; FONCYT-PICT (2017-1818, 2017-1820); PIIECC, Facultad de Humanidades, Usach; Sistema General de Regalías de Colombia (BPIN2018000100059), Universidad del Valle (CI 5316); ANID/FONDECYT Regular (1210195, 1210176, 1210176); ANID/FONDAP (15150012); ANID/PIA/ANILLOS ACT210096; and Alzheimer's Association GBHI ALZ UK-22-865742.
Collapse
Affiliation(s)
- Marcelo Adrián Maito
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - Hernando Santamaría-García
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Ph.D Program of Neuroscience, Psychiatry Department, Pontificia Universidad Javeriana, Bogotá, Colombia
- Center for Memory and Cognition Intellectus, Hospital San Ignacio, Bogotá, Colombia
| | - Sebastián Moguilner
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - Katherine L. Possin
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - María E. Godoy
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - José Alberto Avila-Funes
- Geriatrics Department, Instituto Nacional de Ciencias médicas y nutrición Salvador Zubirán, Mexico City, Mexico
- Centre de Recherche Inserm, U897, Brodeaux, France
- University Victor Segalen Bourdeaux 2, Bordeaux, France
| | - María I. Behrens
- Centro de Investigación Clínica Avanzada (CICA) Hospital Clínico Universidad de Chile, Departamento de Neurología y Neurocirugía, Hospital Clínico Universidad de Chile, Departamento de Neurociencia, Facultad de medicina Universidad de Chile and Departamento de Neurología y Psiquiatría, Clínica Alemana-Universidad del Desarrollo, Santiago, Chile
| | - Ignacio L. Brusco
- Universidad Buenos Aires & Consejo Nacional de Investigaciones Científicas y técnicas (CONICET), Argentina
| | - Martín A. Bruno
- Instituto de Ciencias Biomédicas de la Universidad Católica de Cuyo & Consejo Nacional de Investigaciones Científicas y técnicas (CONICET), Argentina
| | | | - Nilton Custodio
- Unit Cognitive Impairment and Dementia Prevention, Peruvian Institute of Neurosciences, Lima, Peru
| | - Adolfo M. García
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - Shireen Javandel
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Francisco Lopera
- Neuroscience Research Group, Universidad de Antioquia, Medellín, Colombia
| | - Diana L. Matallana
- PhD Program of Neuroscience, Aging Institute, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Bruce Miller
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Maira Okada de Oliveira
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Hospital Santa Marcelina, São Paulo, SP, Brazil
- University of São Paulo, São Paulo, SP, Brazil
| | - Stefanie D. Pina-Escudero
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Andrea Slachevsky
- Neurology Department, Geroscience Center for Brain Health and Metabolism, Santiago, Chile
- Laboratory of Neuropsychology and Clinical Neuroscience (LANNEC), Physiopathology Program ICBM, East Neurologic and Neurosciences Departments, Faculty of Medicine, Hospital del Salvador and Faculty of Medicine, University of Chile, Santiago, Chile
- Servicio de Neurología, Departamento de Medicina, Clínica Alemana, Universidad del Desarrollo, University of Chile, Neuropsychiatry and Memory Disorders clinic (CMYN), Santiago, Chile
| | - Ana L. Sosa Ortiz
- Instituto Nacional de Neurología y neurocirugía, Ciudad de México, Mexico
| | - Leonel T. Takada
- Hospital de Clinicas, University of Sao Paulo Medical School, Brazil
| | - Enzo Tagliazuchi
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Chile
- Departamento de Física, Universidad de Buenos Aires & Instituto de Física de Buenos Aires (FIBA – CONICET), Buenos Aires, Argentina
| | - Victor Valcour
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Ph.D Program of Neuroscience, Psychiatry Department; Memory and Aging Center, Department of Neurology, University of California, San Francisco, USA
| | - Jennifer S. Yokoyama
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Agustín Ibañez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Chile
- Universidad de San Andrés & Consejo Nacional de Investigaciones Científicas y técnicas (CONICET), Argentina
- Global Brain Health Institute (GBHI), Trinity College Dublin, (TCD), Ireland
| |
Collapse
|
10
|
Díaz-Rivera MN, Birba A, Fittipaldi S, Mola D, Morera Y, de Vega M, Moguilner S, Lillo P, Slachevsky A, González Campo C, Ibáñez A, García AM. Multidimensional inhibitory signatures of sentential negation in behavioral variant frontotemporal dementia. Cereb Cortex 2022; 33:403-420. [PMID: 35253864 PMCID: PMC9837611 DOI: 10.1093/cercor/bhac074] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/31/2022] [Accepted: 02/07/2022] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Processing of linguistic negation has been associated to inhibitory brain mechanisms. However, no study has tapped this link via multimodal measures in patients with core inhibitory alterations, a critical approach to reveal direct neural correlates and potential disease markers. METHODS Here we examined oscillatory, neuroanatomical, and functional connectivity signatures of a recently reported Go/No-go negation task in healthy controls and behavioral variant frontotemporal dementia (bvFTD) patients, typified by primary and generalized inhibitory disruptions. To test for specificity, we also recruited persons with Alzheimer's disease (AD), a disease involving frequent but nonprimary inhibitory deficits. RESULTS In controls, negative sentences in the No-go condition distinctly involved frontocentral delta (2-3 Hz) suppression, a canonical inhibitory marker. In bvFTD patients, this modulation was selectively abolished and significantly correlated with the volume and functional connectivity of regions supporting inhibition (e.g. precentral gyrus, caudate nucleus, and cerebellum). Such canonical delta suppression was preserved in the AD group and associated with widespread anatomo-functional patterns across non-inhibitory regions. DISCUSSION These findings suggest that negation hinges on the integrity and interaction of spatiotemporal inhibitory mechanisms. Moreover, our results reveal potential neurocognitive markers of bvFTD, opening a new agenda at the crossing of cognitive neuroscience and behavioral neurology.
Collapse
Affiliation(s)
- Mariano N Díaz-Rivera
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT), C1425FQD, Godoy Cruz 2370, Buenos Aires, Argentina
| | - Agustina Birba
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina
| | - Sol Fittipaldi
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina
| | - Débora Mola
- Instituto de Investigaciones Psicológicas, CONICET, 5000, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Yurena Morera
- Instituto Universitario de Neurociencia (IUNE), Universidad de La Laguna, Campus de Guajara, 38205 La Laguna, Santa Cruz de Tenerife, Spain
| | - Manuel de Vega
- Instituto Universitario de Neurociencia (IUNE), Universidad de La Laguna, Campus de Guajara, 38205 La Laguna, Santa Cruz de Tenerife, Spain
| | - Sebastian Moguilner
- Global Brain Health Institute, University of California, San Francisco, CA94158, US; and Trinity College, Dublin D02DP21, , Ireland.,Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, 8320000, Santiago, Chile
| | - Patricia Lillo
- Departamento de Neurología Sur, Facultad de Medicina, Universidad de Chile, 8380000, Santiago, Chile.,Unidad de Neurología, Hospital San José, 8380000, Santiago, Chile.,Geroscience Center for Brain Health and Metabolism (GERO), 7800003, Santiago, Chile
| | - Andrea Slachevsky
- Geroscience Center for Brain Health and Metabolism (GERO), 7800003, Santiago, Chile.,Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department, Neuroscience and East Neuroscience Departments, Faculty of Medicine, Institute of Biomedical Sciences (ICBM), University of Chile, 8380000, Santiago, Chile.,Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, 7500000, Santiago, Chile.,Departamento de Medicina, Servicio de Neurología, Clínica Alemana-Universidad del Desarrollo, 7550000, Santiago, Chile
| | - Cecilia González Campo
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina
| | - Agustín Ibáñez
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina.,Global Brain Health Institute, University of California, San Francisco, CA94158, US; and Trinity College, Dublin D02DP21, , Ireland.,Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, 8320000, Santiago, Chile
| | - Adolfo M García
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina.,Global Brain Health Institute, University of California, San Francisco, CA94158, US; and Trinity College, Dublin D02DP21, , Ireland.,Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, 7550000, Santiago, Chile
| |
Collapse
|
11
|
Ferreira LK, Lindberg O, Santillo AF, Wahlund LO. Functional connectivity in behavioral variant frontotemporal dementia. Brain Behav 2022; 12:e2790. [PMID: 36306386 PMCID: PMC9759144 DOI: 10.1002/brb3.2790] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 09/13/2022] [Accepted: 09/24/2022] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION Functional connectivity (FC)-which reflects relationships between neural activity in different brain regions-has been used to explore the functional architecture of the brain in neurodegenerative disorders. Although an increasing number of studies have explored FC changes in behavioral variant frontotemporal dementia (bvFTD), there is no focused, in-depth review about FC in bvFTD. METHODS Comprehensive literature search and narrative review to summarize the current field of FC in bvFTD. RESULTS (1) Decreased FC within the salience network (SN) is the most consistent finding in bvFTD; (2) FC changes extend beyond the SN and affect the interplay between networks; (3) results within the Default Mode Network are mixed; (4) the brain as a network is less interconnected and less efficient in bvFTD; (5) symptoms, functional impairment, and cognition are associated with FC; and (6) the functional architecture resembles patterns of neuropathological spread. CONCLUSIONS FC has potential as a biomarker, and future studies are expected to advance the field with multicentric initiatives, longitudinal designs, and methodological advances.
Collapse
Affiliation(s)
- Luiz Kobuti Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Stockholm, Sweden
| | - Olof Lindberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Alexander F Santillo
- Clinical Memory Research Unit and Psychiatry, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Lars-Olof Wahlund
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|
12
|
Moguilner S, Birba A, Fittipaldi S, Gonzalez-Campo C, Tagliazucchi E, Reyes P, Matallana D, Parra MA, Slachevsky A, Farías G, Cruzat J, García A, Eyre HA, La Joie R, Rabinovici G, Whelan R, Ibáñez A. Multi-feature computational framework for combined signatures of dementia in underrepresented settings. J Neural Eng 2022; 19:046048. [PMID: 35940105 DOI: 10.1088/1741-2552/ac87d0] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 08/08/2022] [Indexed: 11/11/2022]
Abstract
Objective.The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's 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.
Collapse
Affiliation(s)
- Sebastian Moguilner
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, United States of America
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Trinity College Dublin, Dublin, Ireland
| | - Agustina Birba
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Sol Fittipaldi
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | | | - Enzo Tagliazucchi
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
| | - Pablo Reyes
- Medical School, Aging Institute, Psychiatry and Mental Health, Pontificia Universidad Javeriana, Bogota, Colombia
| | - Diana Matallana
- Medical School, Aging Institute, Psychiatry and Mental Health, Pontificia Universidad Javeriana, Bogota, Colombia
| | - Mario A Parra
- MAP: School of Psychological Sciences and Health, University of Strathclyde, Glasgow, United Kingdom
| | - Andrea Slachevsky
- Gerosciences Center for Brain Health and Metabolism, Santiago, Chile
- Faculty of Medicine, University of Chile, Santiago, Chile
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital del Salvador and University of Chile, Santiago, Chile
- Servicio de Neurología, Departamento de Medicina, Clínica Alemana-Universidad del Desarrollo, Santiago de Chile, Chile
| | - Gonzalo Farías
- Faculty of Medicine, University of Chile, Santiago, Chile
| | - Josefina Cruzat
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Adolfo García
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, United States of America
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
- Trinity College Dublin, Dublin, Ireland
| | - Harris A Eyre
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, United States of America
- Neuroscience-Inspired Policy Initiative, Organisation for Economic Co-operation and Development and PRODEO Institute, Paris, France
- IMPACT, The Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, Victoria, Australia
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States of America
- Trinity College Dublin, Dublin, Ireland
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States of America
| | - Gil Rabinovici
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, United States of America
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States of America
- Trinity College Dublin, Dublin, Ireland
| | - Robert Whelan
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, United States of America
- Trinity College Dublin, Dublin, Ireland
| | - Agustín Ibáñez
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, United States of America
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Trinity College Dublin, Dublin, Ireland
| |
Collapse
|
13
|
Birba A, Santamaría-García H, Prado P, Cruzat J, Ballesteros AS, Legaz A, Fittipaldi S, Duran-Aniotz C, Slachevsky A, Santibañez R, Sigman M, García AM, Whelan R, Moguilner S, Ibáñez A. Allostatic-Interoceptive Overload in Frontotemporal Dementia. Biol Psychiatry 2022; 92:54-67. [PMID: 35491275 DOI: 10.1016/j.biopsych.2022.02.955] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 01/28/2022] [Accepted: 02/16/2022] [Indexed: 12/22/2022]
Abstract
BACKGROUND The predictive coding theory of allostatic-interoceptive load states that brain networks mediating autonomic regulation and interoceptive-exteroceptive balance regulate the internal milieu to anticipate future needs and environmental demands. These functions seem to be distinctly compromised in behavioral variant frontotemporal dementia (bvFTD), including alterations of the allostatic-interoceptive network (AIN). Here, we hypothesize that bvFTD is typified by an allostatic-interoceptive overload. METHODS We assessed resting-state heartbeat evoked potential (rsHEP) modulation as well as its behavioral and multimodal neuroimaging correlates in patients with bvFTD relative to healthy control subjects and patients with Alzheimer's disease (N = 94). We measured 1) resting-state electroencephalography (to assess the rsHEP, prompted by visceral inputs and modulated by internal body sensing), 2) associations between rsHEP and its neural generators (source location), 3) cognitive disturbances (cognitive state, executive functions, facial emotion recognition), 4) brain atrophy, and 5) resting-state functional magnetic resonance imaging functional connectivity (AIN vs. control networks). RESULTS Relative to healthy control subjects and patients with Alzheimer's disease, patients with bvFTD presented more negative rsHEP amplitudes with sources in critical hubs of the AIN (insula, amygdala, somatosensory cortex, hippocampus, anterior cingulate cortex). This exacerbated rsHEP modulation selectively predicted the patients' cognitive profile (including cognitive decline, executive dysfunction, and emotional impairments). In addition, increased rsHEP modulation in bvFTD was associated with decreased brain volume and connectivity of the AIN. Machine learning results confirmed AIN specificity in predicting the bvFTD group. CONCLUSIONS Altogether, these results suggest that bvFTD may be characterized by an allostatic-interoceptive overload manifested in ongoing electrophysiological markers, brain atrophy, functional networks, and cognition.
Collapse
Affiliation(s)
- Agustina Birba
- Latin American Brain Health Institute, Universidad Adolfo Ibáñez, Santiago, Chile; National Scientific and Technical Research Council, Buenos Aires, Argentina; Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
| | - Hernando Santamaría-García
- PhD Neuroscience Program, Physiology and Psychiatry Departments, Pontificia Universidad Javeriana, Bogotá, Colombia; Memory and Cognition Center Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia; Global Brain Health Institute, University of California San Francisco, San Francisco, California, and Trinity College Dublin, Dublin, Ireland
| | - Pavel Prado
- Latin American Brain Health Institute, Universidad Adolfo Ibáñez, Santiago, Chile
| | - Josefina Cruzat
- Latin American Brain Health Institute, Universidad Adolfo Ibáñez, Santiago, Chile
| | | | - Agustina Legaz
- National Scientific and Technical Research Council, Buenos Aires, Argentina; Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
| | - Sol Fittipaldi
- National Scientific and Technical Research Council, Buenos Aires, Argentina; Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
| | - Claudia Duran-Aniotz
- Latin American Brain Health Institute, Universidad Adolfo Ibáñez, Santiago, Chile; Center for Social and Cognitive Neuroscience, School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile
| | - Andrea Slachevsky
- Center for Geroscience, Brain Health and Metabolism, Santiago, Chile; Neuropsychology and Clinical Neuroscience Laboratory, Physiopathology Department, Institute of Biomedical Sciences, Santiago, Chile; Memory and Neuropsychiatric Clinic, Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, Santiago, Chile; Servicio de Neurología, Departamento de Medicina, Clínica Alemana-Universidad del Desarrollo, Santiago, Chile
| | - Rodrigo Santibañez
- Neurology Service, Hospital Dr. Sótero del Río, Santiago, Chile; Neurology Department, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Mariano Sigman
- National Scientific and Technical Research Council, Buenos Aires, Argentina; Laboratorio de Neurociencia, Universidad Torcuato Di Tella, Buenos Aires, Argentina; Facultad de Lenguas y Educación, Universidad Nebrija, Madrid, Spain
| | - Adolfo M García
- Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile; National Scientific and Technical Research Council, Buenos Aires, Argentina; Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina; Global Brain Health Institute, University of California San Francisco, San Francisco, California, and Trinity College Dublin, Dublin, Ireland
| | - Robert Whelan
- Global Brain Health Institute, University of California San Francisco, San Francisco, California, and Trinity College Dublin, Dublin, Ireland; Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sebastián Moguilner
- Latin American Brain Health Institute, Universidad Adolfo Ibáñez, Santiago, Chile; National Scientific and Technical Research Council, Buenos Aires, Argentina; Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina; Global Brain Health Institute, University of California San Francisco, San Francisco, California, and Trinity College Dublin, Dublin, Ireland; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Agustín Ibáñez
- Latin American Brain Health Institute, Universidad Adolfo Ibáñez, Santiago, Chile; National Scientific and Technical Research Council, Buenos Aires, Argentina; Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina; Global Brain Health Institute, University of California San Francisco, San Francisco, California, and Trinity College Dublin, Dublin, Ireland; Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
| |
Collapse
|
14
|
McKenna MC, Murad A, Huynh W, Lope J, Bede P. The changing landscape of neuroimaging in frontotemporal lobar degeneration: from group-level observations to single-subject data interpretation. Expert Rev Neurother 2022; 22:179-207. [PMID: 35227146 DOI: 10.1080/14737175.2022.2048648] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION While the imaging signatures of frontotemporal lobar degeneration (FTLD) phenotypes and genotypes are well-characterised based on group-level descriptive analyses, the meaningful interpretation of single MRI scans remains challenging. Single-subject MRI classification frameworks rely on complex computational models and large training datasets to categorise individual patients into diagnostic subgroups based on distinguishing imaging features. Reliable individual subject data interpretation is hugely important in the clinical setting to expedite the diagnosis and classify individuals into relevant prognostic categories. AREAS COVERED This article reviews (1) the neuroimaging studies that propose single-subject MRI classification strategies in symptomatic and pre-symptomatic FTLD, (2) potential practical implications and (3) the limitations of current single-subject data interpretation models. EXPERT OPINION Classification studies in FTLD have demonstrated the feasibility of categorising individual subjects into diagnostic groups based on multiparametric imaging data. Preliminary data indicate that pre-symptomatic FTLD mutation carriers may also be reliably distinguished from controls. Despite momentous advances in the field, significant further improvements are needed before these models can be developed into viable clinical applications.
Collapse
Affiliation(s)
| | - Aizuri Murad
- Computational Neuroimaging Group, Trinity College Dublin, Ireland
| | - William Huynh
- Brain and Mind Centre, University of Sydney, Australia
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity College Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Ireland.,Pitié-Salpêtrière University Hospital, Sorbonne University, France
| |
Collapse
|
15
|
Díaz-Álvarez J, Matias-Guiu JA, Cabrera-Martín MN, Pytel V, Segovia-Ríos I, García-Gutiérrez F, Hernández-Lorenzo L, Matias-Guiu J, Carreras JL, Ayala JL. Genetic Algorithms for Optimized Diagnosis of Alzheimer's Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging. Front Aging Neurosci 2022; 13:708932. [PMID: 35185510 PMCID: PMC8851241 DOI: 10.3389/fnagi.2021.708932] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 12/20/2021] [Indexed: 11/13/2022] Open
Abstract
Genetic algorithms have a proven capability to explore a large space of solutions, and deal with very large numbers of input features. We hypothesized that the application of these algorithms to 18F-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) may help in diagnosis of Alzheimer's disease (AD) and Frontotemporal Dementia (FTD) by selecting the most meaningful features and automating diagnosis. We aimed to develop algorithms for the three main issues in the diagnosis: discrimination between patients with AD or FTD and healthy controls (HC), differential diagnosis between behavioral FTD (bvFTD) and AD, and differential diagnosis between primary progressive aphasia (PPA) variants. Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). K-fold cross validation within the same sample and external validation with ADNI-3 samples were performed. External validation was performed for the algorithms distinguishing AD and HC. Our study supports the use of FDG-PET imaging, which allowed a very high accuracy rate for the diagnosis of AD, FTD, and related disorders. Genetic algorithms identified the most meaningful features with the minimum set of features, which may be relevant for automated assessment of brain FDG-PET images. Overall, our study contributes to the development of an automated, and optimized diagnosis of neurodegenerative disorders using brain metabolism.
Collapse
Affiliation(s)
- Josefa Díaz-Álvarez
- Department of Computer Architecture and Communications, Centro Universitario de Mérida, Universidad de Extremadura, Badajoz, Spain
| | - Jordi A. Matias-Guiu
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - María Nieves Cabrera-Martín
- Department of Nuclear Medicine, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - Vanesa Pytel
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - Ignacio Segovia-Ríos
- Department of Computer Architecture and Communications, Centro Universitario de Mérida, Universidad de Extremadura, Badajoz, Spain
| | - Fernando García-Gutiérrez
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
| | - Laura Hernández-Lorenzo
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
| | - Jorge Matias-Guiu
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - José Luis Carreras
- Department of Nuclear Medicine, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - José L. Ayala
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
| | | |
Collapse
|
16
|
McKenna MC, Tahedl M, Murad A, Lope J, Hardiman O, Hutchinson S, Bede P. White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation. Brain Behav 2022; 12:e2500. [PMID: 35072974 PMCID: PMC8865163 DOI: 10.1002/brb3.2500] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/22/2021] [Accepted: 01/01/2022] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Frontotemporal dementias (FTD) include a genetically heterogeneous group of conditions with distinctive molecular, radiological and clinical features. The majority of radiology studies in FTD compare FTD subgroups to healthy controls to describe phenotype- or genotype-associated imaging signatures. While the characterization of group-specific imaging traits is academically important, the priority of clinical imaging is the meaningful interpretation of individual datasets. METHODS To demonstrate the feasibility of single-subject magnetic resonance imaging (MRI) interpretation, we have evaluated the white matter profile of 60 patients across the clinical spectrum of FTD. A z-score-based approach was implemented, where the diffusivity metrics of individual patients were appraised with reference to demographically matched healthy controls. Fifty white matter tracts were systematically evaluated in each subject with reference to normative data. RESULTS The z-score-based approach successfully detected white matter pathology in single subjects, and group-level inferences were analogous to the outputs of standard track-based spatial statistics. CONCLUSIONS Our findings suggest that it is possible to meaningfully evaluate the diffusion profile of single FTD patients if large normative datasets are available. In contrast to the visual review of FLAIR and T2-weighted images, computational imaging offers objective, quantitative insights into white matter integrity changes even at single-subject level.
Collapse
Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Marlene Tahedl
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Aizuri Murad
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | | | - Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
| |
Collapse
|
17
|
Garcia-Gutierrez F, Delgado-Alvarez A, Delgado-Alonso C, Díaz-Álvarez J, Pytel V, Valles-Salgado M, Gil MJ, Hernández-Lorenzo L, Matías-Guiu J, Ayala JL, Matias-Guiu JA. Diagnosis of Alzheimer's disease and behavioural variant frontotemporal dementia with machine learning-aided neuropsychological assessment using feature engineering and genetic algorithms. Int J Geriatr Psychiatry 2021; 37. [PMID: 34894410 DOI: 10.1002/gps.5667] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 12/08/2021] [Indexed: 11/09/2022]
Abstract
BACKGROUND Neuropsychological assessment is considered a valid tool in the diagnosis of neurodegenerative disorders. However, there is an important overlap in cognitive profiles between Alzheimer's disease (AD) and behavioural variant frontotemporal dementia (bvFTD), and the usefulness in diagnosis is uncertain. We aimed to develop machine learning-based models for the diagnosis using cognitive tests. METHODS Three hundred and twenty-nine participants (170 AD, 72 bvFTD, 87 healthy control [HC]) were enrolled. Evolutionary algorithms, inspired by the process of natural selection, were applied for both mono-objective and multi-objective classification and feature selection. Classical algorithms (NativeBayes, Support Vector Machines, among others) were also used, and a meta-model strategy. RESULTS Accuracies for the diagnosis of AD, bvFTD and the differential diagnosis between them were higher than 84%. Algorithms were able to significantly reduce the number of tests and scores needed. Free and Cued Selective Reminding Test, verbal fluency and Addenbrooke's Cognitive Examination were amongst the most meaningful tests. CONCLUSIONS Our study found high levels of accuracy for diagnosis using exclusively neuropsychological tests, which supports the usefulness of cognitive assessment in diagnosis. Machine learning may have a role in improving the interpretation and test selection.
Collapse
Affiliation(s)
- Fernando Garcia-Gutierrez
- Department of Neurology, Hospital Clínico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
| | - Alfonso Delgado-Alvarez
- Department of Neurology, Hospital Clínico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - Cristina Delgado-Alonso
- Department of Neurology, Hospital Clínico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - Josefa Díaz-Álvarez
- Department of Computer Architecture and Communications, Centro Universitario de Mérida, Universidad de Extremadura, Merida, Spain
| | - Vanesa Pytel
- Department of Neurology, Hospital Clínico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - Maria Valles-Salgado
- Department of Neurology, Hospital Clínico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - María Jose Gil
- Department of Neurology, Hospital Clínico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - Laura Hernández-Lorenzo
- Department of Neurology, Hospital Clínico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
| | - Jorge Matías-Guiu
- Department of Neurology, Hospital Clínico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - José L Ayala
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
| | - Jordi A Matias-Guiu
- Department of Neurology, Hospital Clínico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| |
Collapse
|
18
|
Legaz A, Abrevaya S, Dottori M, Campo CG, Birba A, Caro MM, Aguirre J, Slachevsky A, Aranguiz R, Serrano C, Gillan CM, Leroi I, García AM, Fittipaldi S, Ibañez A. Multimodal mechanisms of human socially reinforced learning across neurodegenerative diseases. Brain 2021; 145:1052-1068. [PMID: 34529034 PMCID: PMC9128375 DOI: 10.1093/brain/awab345] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/17/2021] [Accepted: 09/06/2021] [Indexed: 11/13/2022] Open
Abstract
Social feedback can selectively enhance learning in diverse domains. Relevant
neurocognitive mechanisms have been studied mainly in healthy persons, yielding
correlational findings. Neurodegenerative lesion models, coupled with multimodal
brain measures, can complement standard approaches by revealing direct
multidimensional correlates of the phenomenon. To this end, we assessed socially reinforced and non-socially reinforced learning
in 40 healthy participants as well as persons with behavioural variant
frontotemporal dementia (n = 21), Parkinson’s
disease (n = 31) and Alzheimer’s disease
(n = 20). These conditions are typified by
predominant deficits in social cognition, feedback-based learning and
associative learning, respectively, although all three domains may be partly
compromised in the other conditions. We combined a validated behavioural task
with ongoing EEG signatures of implicit learning (medial frontal negativity) and
offline MRI measures (voxel-based morphometry). In healthy participants, learning was facilitated by social feedback relative to
non-social feedback. In comparison with controls, this effect was specifically
impaired in behavioural variant frontotemporal dementia and Parkinson’s
disease, while unspecific learning deficits (across social and non-social
conditions) were observed in Alzheimer’s disease. EEG results showed
increased medial frontal negativity in healthy controls during social feedback
and learning. Such a modulation was selectively disrupted in behavioural variant
frontotemporal dementia. Neuroanatomical results revealed extended
temporo-parietal and fronto-limbic correlates of socially reinforced learning,
with specific temporo-parietal associations in behavioural variant
frontotemporal dementia and predominantly fronto-limbic regions in
Alzheimer’s disease. In contrast, non-socially reinforced learning was
consistently linked to medial temporal/hippocampal regions. No associations with
cortical volume were found in Parkinson’s disease. Results are consistent
with core social deficits in behavioural variant frontotemporal dementia, subtle
disruptions in ongoing feedback-mechanisms and social processes in
Parkinson’s disease and generalized learning alterations in
Alzheimer’s disease. This multimodal approach highlights the impact of
different neurodegenerative profiles on learning and social feedback. Our findings inform a promising theoretical and clinical agenda in the fields of
social learning, socially reinforced learning and neurodegeneration.
Collapse
Affiliation(s)
- Agustina Legaz
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Universidad Nacional de Córdoba. Facultad de Psicología, Córdoba, CU320, Argentina
| | - Sofía Abrevaya
- National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, CONICET, Buenos Aires, C1021, Argentina
| | - Martín Dottori
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina
| | - Cecilia González Campo
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina
| | - Agustina Birba
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina
| | - Miguel Martorell Caro
- National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, CONICET, Buenos Aires, C1021, Argentina
| | - Julieta Aguirre
- Instituto de Investigaciones Psicológicas (IIPsi), CONICET, Universidad Nacional de Córdoba, Córdoba, CB5000, Argentina
| | - Andrea Slachevsky
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital delSalvador, SSMO & Faculty of Medicine, University of Chile, Santiago, Chile.,Gerosciences Center for Brain Health and Metabolism, Santiago, Chile.,Neuropsychology and Clinical Neuroscience Laboratory, Physiopathology Department, ICBM, Neurosciences Department, Faculty of Medicine, University of Chile, Chile.,Servicio de Neurología, Departamento de Medicina, Clínica Alemana-Universidad del Desarrollo, Chile
| | | | - Cecilia Serrano
- Neurología Cognitiva, Hospital Cesar Milstein, Buenos Aires, C1221, Argentina
| | - Claire M Gillan
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA 94158, USA.,Department of Psychology, Trinity College Dublin, Dublin, Ireland.,Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Iracema Leroi
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA 94158, USA
| | - Adolfo M García
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA 94158, USA.,Global Brain Health Institute (GBHI), Trinity College Dublin (TCD), Dublin, Dublin 2, Ireland.,Faculty of Education, National University of Cuyo, Mendoza, M5502JMA, Argentina.,Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - Sol Fittipaldi
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Universidad Nacional de Córdoba. Facultad de Psicología, Córdoba, CU320, Argentina
| | - Agustín Ibañez
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, C1011ACC, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina.,Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA 94158, USA.,Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| |
Collapse
|
19
|
Llibre-Guerra JJ, Behrens MI, Hosogi ML, Montero L, Torralva T, Custodio N, Longoria-Ibarrola EM, Giraldo-Chica M, Aguillón D, Hardi A, Maestre GE, Contreras V, Doldan C, Duque-Peñailillo L, Hesse H, Roman N, Santana-Trinidad DA, Schenk C, Ocampo-Barba N, López-Contreras R, Nitrini R. Frontotemporal Dementias in Latin America: History, Epidemiology, Genetics, and Clinical Research. Front Neurol 2021; 12:710332. [PMID: 34552552 PMCID: PMC8450529 DOI: 10.3389/fneur.2021.710332] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Accepted: 07/19/2021] [Indexed: 01/08/2023] Open
Abstract
Introduction: The historical development, frequency, and impact of frontotemporal dementia (FTD) are less clear in Latin America than in high-income countries. Although there is a growing number of dementia studies in Latin America, little is known collectively about FTD prevalence studies by country, clinical heterogeneity, risk factors, and genetics in Latin American countries. Methods: A systematic review was completed, aimed at identifying the frequency, clinical heterogeneity, and genetics studies of FTD in Latin American populations. The search strategies used a combination of standardized terms for FTD and related disorders. In addition, at least one author per Latin American country summarized the available literature. Collaborative or regional studies were reviewed during consensus meetings. Results: The first FTD reports published in Latin America were mostly case reports. The last two decades marked a substantial increase in the number of FTD research in Latin American countries. Brazil (165), Argentina (84), Colombia (26), and Chile (23) are the countries with the larger numbers of FTD published studies. Most of the research has focused on clinical and neuropsychological features (n = 247), including the local adaptation of neuropsychological and behavioral assessment batteries. However, there are little to no large studies on prevalence (n = 4), biomarkers (n = 9), or neuropathology (n = 3) of FTD. Conclusions: Future FTD studies will be required in Latin America, albeit with a greater emphasis on clinical diagnosis, genetics, biomarkers, and neuropathological studies. Regional and country-level efforts should seek better estimations of the prevalence, incidence, and economic impact of FTD syndromes.
Collapse
Affiliation(s)
- Jorge J. Llibre-Guerra
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Maria Isabel Behrens
- Departamento de Neurología y Neurocirugía Hospital Clínico Universidad de Chile, Departamento de Neurociencia, Centro de Investigación Clínica Avanzada (CICA), Facultad de Medicina, Universidad de Chile, Santiago de Chile, Chile
- Departamento de Psiquiatría y Neurología, Clínica Alemana de Santiago, Universidad del Desarrollo, Santiago, Chile
| | - Mirna Lie Hosogi
- Departmento de Neurologia, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Lucia Montero
- Laboratory of Neuropsychology (LNPS), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina
| | - Teresa Torralva
- Laboratory of Neuropsychology (LNPS), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina
| | - Nilton Custodio
- Unidad de Diagnóstico de Deterioro Cognitivo y Prevención de Demencia, Instituto Peruano de Neurociencias, Lima, Peru
| | | | - Margarita Giraldo-Chica
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia
| | - David Aguillón
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia
| | - Angela Hardi
- Becker Medical Library, Washington University School of Medicine, St. Louis, MO, United States
| | - Gladys E. Maestre
- Departament of Neurosciences and Alzheimer's Disease Resource Center for Minority Aging Research, University of Texas Rio Grande Valley, Brownsville, TX, United States
| | - Valeria Contreras
- Departamento de Neuropsicología, Hospital de Clínicas Dr Manuel Quintela, Universidad de la República, Montevideo, Uruguay
| | - Celeste Doldan
- Departamento de Neuropsicología Cognitiva, Clínica Especializada en Neurociencias Física y Cognitiva CEFYC, Asunción, Paraguay
| | | | - Heike Hesse
- Observatorio COVID-19, Universidad Tecnológica Centroamericana, Tegucigalpa, Honduras
| | - Norbel Roman
- Hospital Social Security of Costa Rica, Universidad de Costa Rica, San Jose, Costa Rica
| | | | - Christian Schenk
- Sección de Neurología, Dept. de Medicina. Recinto de Ciencias Médicas- Universidad de Puerto Rico, San Juan, Puerto Rico
| | - Ninoska Ocampo-Barba
- Instituto Boliviano de Neurociencia Cognitiva, Universidad Autónoma Gabriel René Moreno, Santa Cruz de la Sierra, Bolivia
| | - Ricardo López-Contreras
- Clínica de Memoria, Servicio de Neurología, Instituto Salvadoreño del Seguro Social, San Salvador, El Salvador
| | - Ricardo Nitrini
- Departmento de Neurologia, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| |
Collapse
|
20
|
Ibanez A, Parra MA, Butler C. The Latin America and the Caribbean Consortium on Dementia (LAC-CD): From Networking to Research to Implementation Science. J Alzheimers Dis 2021; 82:S379-S394. [PMID: 33492297 PMCID: PMC8293660 DOI: 10.3233/jad-201384] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
In comparison with other regions, dementia prevalence in Latin America is growing rapidly, along with the consequent clinical, social, and economic burden upon patients and their families. The combination of fragile health care systems, large social inequalities, and isolated clinical and research initiatives makes the coordination of efforts imperative. The Latin America and the Caribbean Consortium on Dementia (LAC-CD) is a regional organization overseeing and promoting clinical and research activities on dementia. Here, we first provide an overview of the consortium, highlighting the antecedents and current mission. Then, we present the consortium’s regional research, including the multi-partner consortium to expand dementia research in Latin America (ReDLat), which aims to identify the unique genetic, social, and economic factors that drive Alzheimer’s and frontotemporal dementia presentation in LAC relative to the US. We describe an extension of ReDLat which aims to develop affordable markers of disease subtype and severity using high density EEG. We introduce current initiatives promoting regional diagnosis, visibility, and capacity, including the forthcoming launch of the Latin American Brain Health Institute (BrainLat). We discuss LAC-CD-led advances in brain health diplomacy, including an assessment of responses to the impact of COVID-19 on people with dementia and examining the knowledge of public policies among experts in the region. Finally, we present the current knowledge-to-action framework, which paves the way for a future regional action plan. Coordinated actions are crucial to forging strong regional bonds, supporting the implementation of regional dementia plans, improving health systems, and expanding research collaborations across Latin America.
Collapse
Affiliation(s)
- Agustin Ibanez
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA, USA.,Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.,Universidad Autónoma del Caribe, Barranquilla, Barranquilla, Colombia.,Latin American Institute for Brain Health (BrainLat), Center for Social and Cognitive Neuroscience (CSCN), Universidad Adolfo Ibanez, Santiago de Chile, Chile
| | - Mario A Parra
- Universidad Autónoma del Caribe, Barranquilla, Barranquilla, Colombia.,School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK
| | - Christopher Butler
- Department of Brain Sciences, Imperial College London, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Instituto de Neurología Cognitiva, Buenos Aires, Argentina.,Departamento de Neurología, Pontificia Universidad de Chile, Santiago, Chile
| | | |
Collapse
|
21
|
Salamone PC, Legaz A, Sedeño L, Moguilner S, Fraile-Vazquez M, Campo CG, Fittipaldi S, Yoris A, Miranda M, Birba A, Galiani A, Abrevaya S, Neely A, Caro MM, Alifano F, Villagra R, Anunziata F, Okada de Oliveira M, Pautassi RM, Slachevsky A, Serrano C, García AM, Ibañez A. Interoception Primes Emotional Processing: Multimodal Evidence from Neurodegeneration. J Neurosci 2021; 41:4276-4292. [PMID: 33827935 PMCID: PMC8143206 DOI: 10.1523/jneurosci.2578-20.2021] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 03/17/2021] [Accepted: 03/18/2021] [Indexed: 12/15/2022] Open
Abstract
Recent frameworks in cognitive neuroscience and behavioral neurology underscore interoceptive priors as core modulators of negative emotions. However, the field lacks experimental designs manipulating the priming of emotions via interoception and exploring their multimodal signatures in neurodegenerative models. Here, we designed a novel task that involves interoceptive and control-exteroceptive priming conditions followed by post-interoception and post-exteroception facial emotion recognition (FER). We recruited 114 participants, including healthy controls (HCs) as well as patients with behavioral variant frontotemporal dementia (bvFTD), Parkinson's disease (PD), and Alzheimer's disease (AD). We measured online EEG modulations of the heart-evoked potential (HEP), and associations with both brain structural and resting-state functional connectivity patterns. Behaviorally, post-interoception negative FER was enhanced in HCs but selectively disrupted in bvFTD and PD, with AD presenting generalized disruptions across emotion types. Only bvFTD presented impaired interoceptive accuracy. Increased HEP modulations during post-interoception negative FER was observed in HCs and AD, but not in bvFTD or PD patients. Across all groups, post-interoception negative FER correlated with the volume of the insula and the ACC. Also, negative FER was associated with functional connectivity along the (a) salience network in the post-interoception condition, and along the (b) executive network in the post-exteroception condition. These patterns were selectively disrupted in bvFTD (a) and PD (b), respectively. Our approach underscores the multidimensional impact of interoception on emotion, while revealing a specific pathophysiological marker of bvFTD. These findings inform a promising theoretical and clinical agenda in the fields of nteroception, emotion, allostasis, and neurodegeneration.SIGNIFICANCE STATEMENT We examined whether and how emotions are primed by interoceptive states combining multimodal measures in healthy controls and neurodegenerative models. In controls, negative emotion recognition and ongoing HEP modulations were increased after interoception. These patterns were selectively disrupted in patients with atrophy across key interoceptive-emotional regions (e.g., the insula and the cingulate in frontotemporal dementia, frontostriatal networks in Parkinson's disease), whereas persons with Alzheimer's disease presented generalized emotional processing abnormalities with preserved interoceptive mechanisms. The integration of both domains was associated with the volume and connectivity (salience network) of canonical interoceptive-emotional hubs, critically involving the insula and the anterior cingulate. Our study reveals multimodal markers of interoceptive-emotional priming, laying the groundwork for new agendas in cognitive neuroscience and behavioral neurology.
Collapse
Affiliation(s)
- Paula C Salamone
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Agustina Legaz
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Lucas Sedeño
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Sebastián Moguilner
- Global Brain Health Institute, University of California-San Francisco, San Francisco, California, and Trinity College Dublin, Dublin, Ireland
- Nuclear Medicine School Foundation, National Commission of Atomic Energy, Mendoza, Argentina
| | | | - Cecilia Gonzalez Campo
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Sol Fittipaldi
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Adrián Yoris
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, CONICET, Buenos Aires, Argentina
| | - Magdalena Miranda
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, CONICET, Buenos Aires, Argentina
| | - Agustina Birba
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Agostina Galiani
- Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, CONICET, Buenos Aires, Argentina
| | - Sofía Abrevaya
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, CONICET, Buenos Aires, Argentina
| | - Alejandra Neely
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Miguel Martorell Caro
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, CONICET, Buenos Aires, Argentina
| | - Florencia Alifano
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, CONICET, Buenos Aires, Argentina
| | - Roque Villagra
- Memory and Neuropsychiatric Clinic, Neurology Department, Hospital del Salvador, SSMO & Faculty of Medicine, University of Chile, Santiago, Chile
| | - Florencia Anunziata
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina
- Instituto de Investigación Médica M. y M. Ferreyra, INIMEC-CONICET-UNC, Córdoba, Argentina
| | - Maira Okada de Oliveira
- Global Brain Health Institute, University of California-San Francisco, San Francisco, California, and Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP Brazil
- Department of Neurology, Hospital Santa Marcelina, Sao Paulo, SP Brazil
| | - Ricardo M Pautassi
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina
- Instituto de Investigación Médica M. y M. Ferreyra, INIMEC-CONICET-UNC, Córdoba, Argentina
| | - Andrea Slachevsky
- Memory and Neuropsychiatric Clinic, Neurology Department, Hospital del Salvador, SSMO & Faculty of Medicine, University of Chile, Santiago, Chile
- Gerosciences Center for Brain Health and Metabolism, Santiago, Chile
- Neuropsychology and Clinical Neuroscience Laboratory, Physiopathology Department, ICBM, Neurosciences Department, Faculty of Medicine, University of Chile, Santiago, Chile
- Servicio de Neurología, Departamento de Medicina, Clínica Alemana-Universidad del Desarrollo, Santiago, Chile
| | - Cecilia Serrano
- Neurología Cognitiva, Hospital Cesar Milstein, Buenos Aires, Argentina
| | - Adolfo M García
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Global Brain Health Institute, University of California-San Francisco, San Francisco, California, and Trinity College Dublin, Dublin, Ireland
- Faculty of Education, National University of Cuyo, Mendoza, M5502JMA, Argentina
- Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - Agustín Ibañez
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Global Brain Health Institute, University of California-San Francisco, San Francisco, California, and Trinity College Dublin, Dublin, Ireland
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| |
Collapse
|
22
|
Ibanez A, Yokoyama JS, Possin KL, Matallana D, Lopera F, Nitrini R, Takada LT, Custodio N, Sosa Ortiz AL, Avila-Funes JA, Behrens MI, Slachevsky A, Myers RM, Cochran JN, Brusco LI, Bruno MA, Brucki SMD, Pina-Escudero SD, Okada de Oliveira M, Donnelly Kehoe P, Garcia AM, Cardona JF, Santamaria-Garcia H, Moguilner S, Duran-Aniotz C, Tagliazucchi E, Maito M, Longoria Ibarrola EM, Pintado-Caipa M, Godoy ME, Bakman V, Javandel S, Kosik KS, Valcour V, Miller BL. The Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat): Driving Multicentric Research and Implementation Science. Front Neurol 2021; 12:631722. [PMID: 33776890 PMCID: PMC7992978 DOI: 10.3389/fneur.2021.631722] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 02/15/2021] [Indexed: 12/17/2022] Open
Abstract
Dementia is becoming increasingly prevalent in Latin America, contrasting with stable or declining rates in North America and Europe. This scenario places unprecedented clinical, social, and economic burden upon patients, families, and health systems. The challenges prove particularly pressing for conditions with highly specific diagnostic and management demands, such as frontotemporal dementia. Here we introduce a research and networking initiative designed to tackle these ensuing hurdles, the Multi-partner consortium to expand dementia research in Latin America (ReDLat). First, we present ReDLat's regional research framework, aimed at identifying the unique genetic, social, and economic factors driving the presentation of frontotemporal dementia and Alzheimer's disease in Latin America relative to the US. We describe ongoing ReDLat studies in various fields and ongoing research extensions. Then, we introduce actions coordinated by ReDLat and the Latin America and Caribbean Consortium on Dementia (LAC-CD) to develop culturally appropriate diagnostic tools, regional visibility and capacity building, diplomatic coordination in local priority areas, and a knowledge-to-action framework toward a regional action plan. Together, these research and networking initiatives will help to establish strong cross-national bonds, support the implementation of regional dementia plans, enhance health systems' infrastructure, and increase translational research collaborations across the continent.
Collapse
Affiliation(s)
- Agustin Ibanez
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- School of Psychology, Center for Social and Cognitive Neuroscience, Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Adolfo Ibanez University, Santiago, Chile
| | - Jennifer S. Yokoyama
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Katherine L. Possin
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Diana Matallana
- Psychiatry Department, School of Medicine, Aging Institute, Pontificia Universidad Javeriana, Bogotá, Colombia
- Memory and Cognition Clinic, Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
- Mental Health Unit, Hospital Universitario Santa Fe de Bogotá, Bogotá, Colombia
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellín, Colombia
| | - Ricardo Nitrini
- Cognitive and Behavioral Neurology Unit, Hospital das Clinicas, University of São Paulo Medical School, São Paulo, Brazil
| | - Leonel T. Takada
- Cognitive and Behavioral Neurology Unit, Hospital das Clinicas, University of São Paulo Medical School, São Paulo, Brazil
| | - Nilton Custodio
- Unit Cognitive Impairment and Dementia Prevention, Cognitive Neurology Center, Peruvian Institute of Neurosciences, Lima, Perú
| | - Ana Luisa Sosa Ortiz
- Instituto Nacional de Neurologia y Neurocirugia MVS, Universidad Nacional Autonoma de Mexico, Mexico, Mexico
| | - José Alberto Avila-Funes
- Department of Geriatrics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico, Mexico
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, Bordeaux, France
| | - Maria Isabel Behrens
- Centro de Investigación Clínica Avanzada, Hospital Clínico, Facultad de Medicina Universidad de Chile, Santiago, Chile
- Departamento de Neurología y Neurocirugía, Hospital Clínico Universidad de Chile, Santiago, Chile
- Departamento de Neurociencia, Facultad de Medicina Universidad de Chile, Santiago, Chile
- Clínica Alemana Santiago, Universidad del Desarrollo, Santiago, Chile
| | - Andrea Slachevsky
- Clínica Alemana Santiago, Universidad del Desarrollo, Santiago, Chile
- Geroscience Center for Brain Health and Metabolism (GERO), Santiago, Chile
- Neuropsychology and Clinical Neuroscience Laboratory, Physiopathology Department, Institute of Biomedical Sciences, Neuroscience and East Neuroscience, Santiago, Chile
- Faculty of Medicine, University of Chile, Santiago, Chile
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Faculty of Medicine, Hospital del Salvador, University of Chile, Santiago, Chile
| | - Richard M. Myers
- Hudson Alpha Institute for Biotechnology, Huntsville, AL, United States
| | | | - Luis Ignacio Brusco
- Facultad de Medicina, Universidad de Buenos Aires, Buenos Aires, Argentina
- ALZAR – Alzheimer, Buenos Aires, Argentina
| | - Martin A. Bruno
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Facultad Ciencias Médicas, Instituto Ciencias Biomédicas, Universidad Católica de Cuyo, San Juan, Argentina
| | - Sonia M. D. Brucki
- Cognitive and Behavioral Neurology Unit, Hospital das Clinicas, University of São Paulo Medical School, São Paulo, Brazil
- Hospital Santa Marcelina, São Paulo, São Paulo, Brazil
| | - Stefanie Danielle Pina-Escudero
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Maira Okada de Oliveira
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Cognitive and Behavioral Neurology Unit, Hospital das Clinicas, University of São Paulo Medical School, São Paulo, Brazil
- Hospital Santa Marcelina, São Paulo, São Paulo, Brazil
| | - Patricio Donnelly Kehoe
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Multimedia Signal Processing Group - Neuroimage Division, French-Argentine International Center for Information and Systems Sciences, Rosario, Argentina
| | - Adolfo M. Garcia
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Faculty of Education, National University of Cuyo, Mendoza, Argentina
| | | | - Hernando Santamaria-Garcia
- Memory and Cognition Clinic, Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
- Ph.D. Program in Neuroscience, Department of Psychiatry, Physiology, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Sebastian Moguilner
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Claudia Duran-Aniotz
- School of Psychology, Center for Social and Cognitive Neuroscience, Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Adolfo Ibanez University, Santiago, Chile
| | - Enzo Tagliazucchi
- Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Marcelo Maito
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
| | | | - Maritza Pintado-Caipa
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Unit Cognitive Impairment and Dementia Prevention, Cognitive Neurology Center, Peruvian Institute of Neurosciences, Lima, Perú
| | - Maria Eugenia Godoy
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
| | - Vera Bakman
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Shireen Javandel
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Kenneth S. Kosik
- Department of Molecular, Cellular, and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - Victor Valcour
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Bruce L. Miller
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| |
Collapse
|
23
|
Princich JP, Donnelly-Kehoe PA, Deleglise A, Vallejo-Azar MN, Pascariello GO, Seoane P, Veron Do Santos JG, Collavini S, Nasimbera AH, Kochen S. Diagnostic Performance of MRI Volumetry in Epilepsy Patients With Hippocampal Sclerosis Supported Through a Random Forest Automatic Classification Algorithm. Front Neurol 2021; 12:613967. [PMID: 33692740 PMCID: PMC7937810 DOI: 10.3389/fneur.2021.613967] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 01/18/2021] [Indexed: 01/07/2023] Open
Abstract
Introduction: Several methods offer free volumetry services for MR data that adequately quantify volume differences in the hippocampus and its subregions. These methods are frequently used to assist in clinical diagnosis of suspected hippocampal sclerosis in temporal lobe epilepsy. A strong association between severity of histopathological anomalies and hippocampal volumes was reported using MR volumetry with a higher diagnostic yield than visual examination alone. Interpretation of volumetry results is challenging due to inherent methodological differences and to the reported variability of hippocampal volume. Furthermore, normal morphometric differences are recognized in diverse populations that may need consideration. To address this concern, we highlighted procedural discrepancies including atlas definition and computation of total intracranial volume that may impact volumetry results. We aimed to quantify diagnostic performance and to propose reference values for hippocampal volume from two well-established techniques: FreeSurfer v.06 and volBrain-HIPS. Methods: Volumetry measures were calculated using clinical T1 MRI from a local population of 61 healthy controls and 57 epilepsy patients with confirmed unilateral hippocampal sclerosis. We further validated the results by a state-of-the-art machine learning classification algorithm (Random Forest) computing accuracy and feature relevance to distinguish between patients and controls. This validation process was performed using the FreeSurfer dataset alone, considering morphometric values not only from the hippocampus but also from additional non-hippocampal brain regions that could be potentially relevant for group classification. Mean reference values and 95% confidence intervals were calculated for left and right hippocampi along with hippocampal asymmetry degree to test diagnostic accuracy. Results: Both methods showed excellent classification performance (AUC:> 0.914) with noticeable differences in absolute (cm3) and normalized volumes. Hippocampal asymmetry was the most accurate discriminator from all estimates (AUC:1~0.97). Similar results were achieved in the validation test with an automatic classifier (AUC:>0.960), disclosing hippocampal structures as the most relevant features for group differentiation among other brain regions. Conclusion: We calculated reference volumetry values from two commonly used methods to accurately identify patients with temporal epilepsy and hippocampal sclerosis. Validation with an automatic classifier confirmed the principal role of the hippocampus and its subregions for diagnosis.
Collapse
Affiliation(s)
- Juan Pablo Princich
- ENyS (Estudios en Neurociencias y Sistemas Complejos), Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional Arturo Jauretche y Hospital El Cruce, Florencio Varela, Argentina.,Hospital de Pediatría J.P Garrahan, Departamento de Neuroimágenes, Buenos Aires, Argentina
| | - Patricio Andres Donnelly-Kehoe
- Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas (CIFASIS) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Grupo de Procesamiento de Señales Multimedia - División Neuroimágenes, Universidad Nacional de Rosario, Rosario, Argentina
| | - Alvaro Deleglise
- Instituto de Fisiología y Biofísica B. Houssay (IFIBIO), Consejo Nacional de Investigaciones Científicas y Técnicas, Departamento de Fisiología y Biofísica, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Mariana Nahir Vallejo-Azar
- ENyS (Estudios en Neurociencias y Sistemas Complejos), Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional Arturo Jauretche y Hospital El Cruce, Florencio Varela, Argentina
| | - Guido Orlando Pascariello
- Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas (CIFASIS) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Grupo de Procesamiento de Señales Multimedia - División Neuroimágenes, Universidad Nacional de Rosario, Rosario, Argentina
| | - Pablo Seoane
- ENyS (Estudios en Neurociencias y Sistemas Complejos), Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional Arturo Jauretche y Hospital El Cruce, Florencio Varela, Argentina.,Hospital J.M Ramos Mejía, Centro de Epilepsia, Buenos Aires, Argentina
| | - Jose Gabriel Veron Do Santos
- ENyS (Estudios en Neurociencias y Sistemas Complejos), Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional Arturo Jauretche y Hospital El Cruce, Florencio Varela, Argentina
| | - Santiago Collavini
- ENyS (Estudios en Neurociencias y Sistemas Complejos), Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional Arturo Jauretche y Hospital El Cruce, Florencio Varela, Argentina.,Instituto de investigación en Electrónica, Control y Procesamiento de Señales (LEICI), Universidad Nacional de La Plata-Consejo Nacional de Investigaciones Científicas y Técnicas, La Plata, Argentina.,Instituto de Ingeniería y Agronomía, Universidad Nacional Arturo Jauretche, Florencio Varela, Argentina
| | - Alejandro Hugo Nasimbera
- ENyS (Estudios en Neurociencias y Sistemas Complejos), Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional Arturo Jauretche y Hospital El Cruce, Florencio Varela, Argentina.,Hospital J.M Ramos Mejía, Centro de Epilepsia, Buenos Aires, Argentina
| | - Silvia Kochen
- ENyS (Estudios en Neurociencias y Sistemas Complejos), Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional Arturo Jauretche y Hospital El Cruce, Florencio Varela, Argentina
| |
Collapse
|
24
|
Santamaría-García H, Baez S, Aponte-Canencio DM, Pasciarello GO, Donnelly-Kehoe PA, Maggiotti G, Matallana D, Hesse E, Neely A, Zapata JG, Chiong W, Levy J, Decety J, Ibáñez A. Uncovering social-contextual and individual mental health factors associated with violence via computational inference. PATTERNS (NEW YORK, N.Y.) 2021; 2:100176. [PMID: 33659906 PMCID: PMC7892360 DOI: 10.1016/j.patter.2020.100176] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 10/21/2020] [Accepted: 11/30/2020] [Indexed: 01/13/2023]
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.
Collapse
Affiliation(s)
- Hernando Santamaría-García
- Doctorado de Neurociencias, Departamentos de Psiquiatría y Fisiología, Pontificia Universidad Javeriana, Bogotá, Colombia
- Centro de Memoria y Cognición Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
| | | | - Diego Mauricio Aponte-Canencio
- Universidad Externado de Colombia, Bogotá, Colombia
- Agencia para la Reincorporación y la Normalización (ARN), Bogotá, Colombia
- Department of Neuroscience and Biomedical Engineering, Aalto University, Finland
| | - Guido Orlando Pasciarello
- Multimedia Signal Processing Group–Neuroimage Division, French-Argentine International Center for Information and Systems Sciences (CIFASIS)–National Scientific and Technical Research Council (CONICET), Rosario, Argentina
- Laboratory of Neuroimaging and Neuroscience (LANEN), INECO Foundation Rosario, Rosario, Argentina
| | - Patricio Andrés Donnelly-Kehoe
- Multimedia Signal Processing Group–Neuroimage Division, French-Argentine International Center for Information and Systems Sciences (CIFASIS)–National Scientific and Technical Research Council (CONICET), Rosario, Argentina
- Laboratory of Neuroimaging and Neuroscience (LANEN), INECO Foundation Rosario, Rosario, Argentina
| | | | - Diana Matallana
- Doctorado de Neurociencias, Departamentos de Psiquiatría y Fisiología, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Eugenia Hesse
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Argentina
| | - Alejandra Neely
- Latin American Institute for Brain Health (BrainLat), Center for Social and Cognitive Neuroscience (CSCN), Universidad Adolfo Ibáñez, Santiago de Chile, Chile
| | | | - Winston Chiong
- UCSF Weill Institute for Neurosciences, San Francisco, CA, USA
| | - Jonathan Levy
- Baruch Ivcher School of Psychology, Interdisciplinary Center Herzliya (IDC), Israel
- Department of Neuroscience and Biomedical Engineering, Aalto University, Finland
| | | | - Agustín Ibáñez
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Argentina
- Latin American Institute for Brain Health (BrainLat), Center for Social and Cognitive Neuroscience (CSCN), Universidad Adolfo Ibáñez, Santiago de Chile, Chile
- Universidad Autónoma del Caribe, Barranquilla, Colombia
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA, USA
| |
Collapse
|
25
|
Parra MA, Baez S, Sedeño L, Gonzalez Campo C, Santamaría‐García H, Aprahamian I, Bertolucci PHF, Bustin J, Camargos Bicalho MA, Cano‐Gutierrez C, Caramelli P, Chaves MLF, Cogram P, Beber BC, Court FA, de Souza LC, Custodio N, Damian A, de la Cruz M, Diehl Rodriguez R, Brucki SMD, Fajersztajn L, Farías GA, De Felice FG, Ferrari R, de Oliveira FF, Ferreira ST, Ferretti C, Figueredo Balthazar ML, Ferreira Frota NA, Fuentes P, García AM, Garcia PJ, de Gobbi Porto FH, Duque Peñailillo L, Engler HW, Maier I, Mata IF, Gonzalez‐Billault C, Lopez OL, Morelli L, Nitrini R, Quiroz YT, Guerrero Barragan A, Huepe D, Pio FJ, Suemoto CK, Kochhann R, Kochen S, Kumfor F, Lanata S, Miller B, Mansur LL, Hosogi ML, Lillo P, Llibre Guerra J, Lira D, Lopera F, Comas A, Avila‐Funes JA, Sosa AL, Ramos C, Resende EDPF, Snyder HM, Tarnanas I, Yokoyama J, Llibre J, Cardona JF, Possin K, Kosik KS, Montesinos R, Moguilner S, Solis PCL, Ferretti‐Rebustini REDL, Ramirez JM, Matallana D, Mbakile‐Mahlanza L, Marques Ton AM, Tavares RM, Miotto EC, Muniz‐Terrera G, Muñoz‐Nevárez LA, Orozco D, Okada de Oliveira M, Piguet O, Pintado Caipa M, Piña Escudero SD, Schilling LP, Rodrigues Palmeira AL, Yassuda MS, Santacruz‐Escudero JM, Serafim RB, Smid J, Slachevsky A, Serrano C, Soto‐Añari M, Takada LT, Grinberg LT, Teixeira AL, Barbosa MT, Trépel D, Ibanez A. Dementia in Latin America: Paving the way toward a regional action plan. Alzheimers Dement 2021; 17:295-313. [PMID: 33634602 PMCID: PMC7984223 DOI: 10.1002/alz.12202] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 08/28/2020] [Accepted: 08/30/2020] [Indexed: 12/12/2022]
Abstract
Across Latin American and Caribbean countries (LACs), the fight against dementia faces pressing challenges, such as heterogeneity, diversity, political instability, and socioeconomic disparities. These can be addressed more effectively in a collaborative setting that fosters open exchange of knowledge. In this work, the Latin American and Caribbean Consortium on Dementia (LAC-CD) proposes an agenda for integration to deliver a Knowledge to Action Framework (KtAF). First, we summarize evidence-based strategies (epidemiology, genetics, biomarkers, clinical trials, nonpharmacological interventions, networking, and translational research) and align them to current global strategies to translate regional knowledge into transformative actions. Then we characterize key sources of complexity (genetic isolates, admixture in populations, environmental factors, and barriers to effective interventions), map them to the above challenges, and provide the basic mosaics of knowledge toward a KtAF. Finally, we describe strategies supporting the knowledge creation stage that underpins the translational impact of KtAF.
Collapse
Affiliation(s)
- Mario Alfredo Parra
- School of Psychological Sciences and HealthGraham Hills BuildingGlasgow, G1 1QE, UK, Universidad Autónoma del CaribePrograma de PsicologíaUniversity of StrathclydeBarranquillaColombia
| | | | - Lucas Sedeño
- Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET)Buenos AiresArgentina
| | - Cecilia Gonzalez Campo
- Cognitive Neuroscience Center (CNC)Universidad de San AndresConsejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET)Buenos AiresArgentina
| | - Hernando Santamaría‐García
- Pontificia Universidad JaverianaMedical School, Physiology and Psychiatry DepartmentsMemory and Cognition Center IntellectusHospital Universitario San IgnacioBogotáColombia
| | - Ivan Aprahamian
- Department of Internal MedicineFaculty of Medicine of JundiaíGroup of Investigation on Multimorbidity and Mental Health in Aging (GIMMA)JundiaíState of São PauloBrazil
| | - Paulo HF Bertolucci
- Department of Neurology and NeurosurgeryEscola Paulista de MedicinaFederal University of São Paulo ‐ UNIFESPSão PauloBrazil
| | - Julian Bustin
- INECO FoundationInstitute of Cognitive and Translational Neuroscience (INCYT)Favaloro UniversityBuenos AiresArgentina
| | | | - Carlos Cano‐Gutierrez
- Medical SchoolGeriatric Unit, Memory and Cognition Center‐IntellectusAging InstituteHospital Universitario San IgnacioPontificia Universidad JaverianaBogotáColombia
| | - Paulo Caramelli
- Faculdade de MedicinaUniversidade Federal de Minas GeraisBelo HorizonteBrazil
| | - Marcia L. F. Chaves
- Neurology ServiceHospital de Clínicas de Porto Alegre e Universidade Federal do Rio Grande do SulBrazil
| | - Patricia Cogram
- Laboratory of Molecular NeuropsychiatryINECO FoundationNational Scientific and Technical Research CouncilInstitute of Cognitive and Translational Neuroscience (INCyT)Favaloro UniversityBuenos AiresArgentina
| | - Bárbara Costa Beber
- Department of Speech and Language PathologyAtlantic Fellow for Equity in Brain HealthFederal University of Health Sciences of Porto Alegre (UFCSPA)Porto AlegreBrazil
| | - Felipe A. Court
- Center for Integrative BiologyFaculty of SciencesFONDAP Center for GeroscienceBrain Health and Metabolism, Santiago, Chile, The Buck Institute for Research on AgingUniversidad Mayor, ChileNovatoCAUSA
| | | | - Nilton Custodio
- Unit Cognitive Impairment and Dementia PreventionCognitive Neurology CenterPeruvian Institute of NeurosciencesLimaPerú
| | - Andres Damian
- Centro Uruguayo de Imagenología Molecular (CUDIM)Centro de Medicina Nuclear e Imagenología MolecularHospital de ClínicasUniversidad de la RepúblicaMontevideoUruguay
| | - Myriam de la Cruz
- Global Brain Health Institute, University of CaliforniaSan FranciscoUSA
| | - Roberta Diehl Rodriguez
- Behavioral and Cognitive Neurology UnitDepartment of Neurology and LIM 22University of São PauloSão PauloBrazil
| | | | - Lais Fajersztajn
- Laboratory of Experimental Air Pollution (LIM05)Department of PathologySchool of MedicineGlobal Brain Health Institute, University of CaliforniaSan Francisco (UCSF)University of São PauloSão PauloSao PauloBrazil
| | - Gonzalo A. Farías
- Department Neurology and Neurosurgery North/Department of NeurosciencesCenter for Advanced Clinical Research (CICA)Faculty of MedicineUniversidad de ChileSantiagoChile
| | | | - Raffaele Ferrari
- Department of Neurodegenerative DiseaseUniversity College LondonLondonESUK
| | - Fabricio Ferreira de Oliveira
- Department of Neurology and NeurosurgeryEscola Paulista de MedicinaFederal University of São Paulo ‐ UNIFESPSão PauloBrazil
| | - Sergio T. Ferreira
- Institute of Medical Biochemistry Leopoldo de Meis & Institute of Biophysics Carlos Chagas FilhoFederal University of Rio de JaneiroRio de JaneiroRJBrazil
| | - Ceres Ferretti
- Division of NeurologyUniversity of São PauloSão PauloBrazil
| | | | | | - Patricio Fuentes
- Geriatrics Section Clinical Hospital University of Chile, Santos Dumont 999 IndependenciaSantiagoChile
| | - Adolfo M. García
- Cognitive Neuroscience Center (CNC)Faculty of EducationNational University of Cuyo (UNCuyo)Universidad de San Andres. National Scientific and Technical Research Council (CONICET)MendozaArgentina
| | | | - Fábio Henrique de Gobbi Porto
- Laboratory of Psychiatric Neuroimaging (LIM‐21)Instituto de PsiquiatriaHospital das Clinicas HCFMUSPFaculdade de MedicinaUniversidade de Sao PauloSao PauloSao PauloBrazil
| | | | | | | | - Ignacio F. Mata
- Department of Genomic MedicineLerner Research InstituteCleveland ClinicOHUSA
| | - Christian Gonzalez‐Billault
- Center for GeroscienceBrain Health and Metabolism (GERO), Santiago, Chile, and Department of Biology, Faculty of SciencesUniversity of ChileSantiagoChile
| | - Oscar L. Lopez
- Alzheimer's Disease Research CenterUniversity of PittsburghPittsburghPAUSA
| | - Laura Morelli
- Fundacion Instituto Leloir‐IIBBA‐CONICET. AveArgentina
| | - Ricardo Nitrini
- Department of NeurologyUniversity of São Paulo Medical SchoolSão PauloBrazil
| | | | - Alejandra Guerrero Barragan
- Trinity College Dublin, Dublin, Departamento de Neurologia Hospital Occidente de KennedyGlobal Brain Health InstituteUniversidad de la SabanaBogotaColombia
| | - David Huepe
- Center for Social and Cognitive Neuroscience (CSCN)School of PsychologyUniversidad Adolfo IbañezSantiagoChile
| | - Fabricio Joao Pio
- Department of NeurologyHospital Governador Celso RamosFlorianopolisBrazil
| | | | - Renata Kochhann
- Graduate Program in PsychologySchool of Health SciencesHospital Moinhos de VentoPontifical Catholic University of Rio Grande do Sul—PUCRS and Researcher OfficePorto AlegreBrazil
| | - Silvia Kochen
- Neurosciences and Complex Systems Unit (EnyS), CONICET, Hosp, El Cruce “N. Kirchner”, Univ. National A, Jauretche (UNAJ), F. Varela, Prov. Buenos Aires. Fac. MedicineUniv Nacional de Buenos Aires (UBA)Buenos AiresArgentina
| | - Fiona Kumfor
- Brain and Mind Centre and School of PsychologyUniversity of SydneySydneyNSWAustralia
| | - Serggio Lanata
- UCSF Department of NeurologyMemory and Aging CenterUCSFSan FranciscoCaliforniaUS
| | - Bruce Miller
- UCSF Department of NeurologyMemory and Aging CenterUCSFSan FranciscoCaliforniaUS
| | | | - Mirna Lie Hosogi
- Behavioral and Cognitive Unit of Department of NeurologyUniversity of São Paulo School of MedicineSao PauloBrazil
| | - Patricia Lillo
- Geroscience Center for Brain Health and Metabolism, Santiago, Chile, Departamento de Neurología Sur/Departamento de Neurociencia, Facultad de MedicinaUniversidad de ChileSantiagoChile
| | | | - David Lira
- Unit Cognitive Impairment and Dementia PreventionCognitive Neurology CenterPeruvian Institute of NeurosciencesLimaPerú
| | - Francisco Lopera
- Neuroscience Research GroupUniversidad de AntioquiaMedellínColombia
| | - Adelina Comas
- Department of Health Policy at the London School of Economics and Political ScienceLondonUK
| | | | - Ana Luisa Sosa
- Instituto Nacional de Neurología y NeurocirugíaCiudad de MéxicoMéxico
| | - Claudia Ramos
- Global Brain Health Institute, University of California, San Francisco (UCSF)San FranciscoUSA
| | | | | | - Ioannis Tarnanas
- Global Brain Health Institute, University of CaliforniaSan FranciscoUSA
- Altoida Inc.HoustonTexasUSA
| | - Jenifer Yokoyama
- UCSF Department of NeurologyMemory and Aging CenterUCSFSan FranciscoCaliforniaUS
| | | | | | - Kate Possin
- UCSF Department of NeurologyMemory and Aging CenterUCSFSan FranciscoCaliforniaUS
| | - Kenneth S. Kosik
- Neuroscience Research Institute and Dept of Molecular Cellular and Developmental BiologyUniversity of California SantaBarbaraCaliforniaUSA
| | - Rosa Montesinos
- Unit Cognitive Impairment and Dementia PreventionCognitive Neurology CenterPeruvian Institute of NeurosciencesLimaPerú
| | - Sebastian Moguilner
- Global Brain Health Institute, University of California, San Francisco (UCSF)San FranciscoUSA
| | - Patricia Cristina Lourdes Solis
- Neurosciences and Complex Systems Unit (EnyS), CONICET, Hosp, El Cruce “N. Kirchner”, Univ. National A, Jauretche (UNAJ), F. Varela, Prov. Buenos Aires. Fac. MedicineUniv Nacional de Buenos Aires (UBA)Buenos AiresArgentina
| | | | - Jeronimo Martin Ramirez
- Departamen de Admision Continua Adultos Hospital General La Raza Instituto Mexicano del Seguro SocialGlobal Brain Health Institute, Trinity College Dublin, DublinCiudad de MexicoMexico
| | - Diana Matallana
- Medical SchoolAging Institute and Psychiatry DepartmentPontificia Universidad Javeriana. Memory and Cognition Center‐IntellectusHospital Universitario San IgnacioBogotáColombia
| | - Lingani Mbakile‐Mahlanza
- Global Brain Health InstituteUniversity of California San Francisco, University of BotswanaGaboroneBotswana
| | | | | | - Eliane C Miotto
- Department of NeurologyUniversity of Sao PauloSao PauloBrazil
| | | | | | - David Orozco
- Cognitive Neuroscience Development LaboratoryAxis NeurocienciasUniversidad Nacional del Sur, Cognitive Impairment and Behavior Disorders UnitBahía BlancaArgentina
| | - Maira Okada de Oliveira
- Global Brain Health Institute, University of California, San Francisco (UCSF)San FranciscoUSA
| | - Olivier Piguet
- School of Psychology and Brain and Mind CentreUniversity of SydneyCamperdownNSWAustralia
| | - Maritza Pintado Caipa
- Global Brain Health Institute, University of California, San Francisco (UCSF)San FranciscoUSA
| | | | - Lucas Porcello Schilling
- Department of NeurologyPontificia Universidade Catolica do Rio Grande do Sul (PUCRS)Porto AlegreBrazil
| | - André Luiz Rodrigues Palmeira
- Santa Casa de Misericórdia de Porto Alegre, Serviço de Neurologia, Porto Alegre, BrazilHospital Ernesto DornellesServiço de Neurologia e NeurocirurgiaPorto AlegreBrazil
| | | | - Jose Manuel Santacruz‐Escudero
- Medical School and Psychiatry DepartmentMemory and Cognition Center‐ IntellectusPontificia Universidad JaverianaHospital Universitario San IgnacioBogotáColombia
| | | | - Jerusa Smid
- Department of NeurologyUniversity of Sao PauloSão PauloBrazil
| | - Andrea Slachevsky
- Neurology DepartmentGeroscience Center for Brain Health and Metabolism, Santiago, Chile, Laboratory of Neuropsychology and Clinical Neuroscience (LANNEC), Physiopathology Program‐ICBM, East Neurologic and Neurosciences Departments, Faculty of MedicineHospital del Salvador and Faculty of Medicine University of Chile. Servicio de NeurologíaDepartamento de MedicinaClínica Alemana—Universidad del DesarrolloUniversity of Chile, Neuropsychiatry and Memory Disorders clinic (CMYN)SantiagoChile
| | | | | | | | - Lea Tenenholz Grinberg
- Departments of NeurologyPathology and Global Brain Health InstituteUCSF ‐ USA, Department of PathologyUniversity of São Paulo Medical SchoolSão PauloBrazil
| | - Antonio Lucio Teixeira
- Laboratório Interdisciplinar de Investigação MédicaFaculdade de MedicinaAv. Alfredo Balena, 110Universidade Federal de Minas GeraisBelo HorizonteBrazil
| | - Maira Tonidandel Barbosa
- Faculdade de Medicina da Universidade Federal de Minas Gerais e Faculdade deCiências Médicas de Minas GeraisBelo HorizonteBrazil
| | - Dominic Trépel
- Global Brain Health Institute (GBHI)Trinity College DublinDublin
| | - Agustin Ibanez
- Cognitive Neuroscience Center (CNC) Buenos Aires, Argentina; Universidad Autonoma del Caribe, Barranquilla, Colombia; Global Brain Health Institute (GBHI), USUniversidad de San AndresCONICETUniversidad Autonoma del CaribeUniversidad Adolfo IbanezUCSFUSA
| |
Collapse
|
26
|
Garcia-Cordero I, Migeot J, Fittipaldi S, Aquino A, Campo CG, García A, Ibáñez A. Metacognition of emotion recognition across neurodegenerative diseases. Cortex 2021; 137:93-107. [PMID: 33609899 DOI: 10.1016/j.cortex.2020.12.023] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/18/2020] [Accepted: 12/24/2020] [Indexed: 12/12/2022]
Abstract
Metacognition (monitoring) of emotion recognition is fundamental for social interactions. Correct recognition of and confidence in the emotional meaning inferred from others' faces are fundamental for guiding and adjusting interpersonal behavior. Yet, although emotion recognition impairments are well documented across neurodegenerative diseases, the role of metacognition in this domain remains poorly understood. Here, we evaluate multimodal neurocognitive markers of metacognition in 83 subjects, encompassing patients with behavioral variant frontotemporal dementia [bvFTD, n = 18], Alzheimer's disease [AD, n = 27], and demographically-matched controls (n = 38). Participants performed a classical facial emotion recognition task and, after each trial, they rated their confidence in their performance. We examined two measures of metacognition: (i) calibration: how well confidence tracks accuracy; and (ii) a metacognitive index (MI) capturing the magnitude of the difference between confidence and accuracy. Then, whole-brain grey matter volume and fMRI-derived resting-state functional connectivity were analyzed to track associations with metacognition. Results showed that metacognition deficits were linked to basic emotion recognition. Metacognition of negative emotions was compromised in patients, especially disgust in bvFTD as well as sadness in AD. Metacognition impairments were associated with reduced volume of fronto-temporo-insular and subcortical areas in bvFTD and fronto-parietal regions in AD. Metacognition deficits were associated with disconnection of large-scale fronto-posterior networks for both groups. This study reveals a link between emotion recognition and metacognition in neurodegenerative diseases. The characterization of metacognitive impairments in bvFTD and AD would be relevant for understanding patients' daily life changes in social behavior.
Collapse
Affiliation(s)
- Indira Garcia-Cordero
- Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Joaquín Migeot
- Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago de Chile, Chile
| | - Sol Fittipaldi
- Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | | | - Cecilia Gonzalez Campo
- Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Adolfo García
- Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Faculty of Education, National University of Cuyo, Mendoza, Argentina; Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile; Global Brain Health Institute, University of California, San Francisco, USA
| | - Agustín Ibáñez
- Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago de Chile, Chile; Global Brain Health Institute, University of California, San Francisco, USA.
| |
Collapse
|
27
|
Moguilner S, García AM, Perl YS, Tagliazucchi E, Piguet O, Kumfor F, Reyes P, Matallana D, Sedeño L, Ibáñez A. Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes: A multicenter study. Neuroimage 2021; 225:117522. [PMID: 33144220 PMCID: PMC7832160 DOI: 10.1016/j.neuroimage.2020.117522] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 10/14/2020] [Accepted: 10/27/2020] [Indexed: 02/07/2023] Open
Abstract
From molecular mechanisms to global brain networks, atypical fluctuations are the hallmark of neurodegeneration. Yet, traditional fMRI research on resting-state networks (RSNs) has favored static and average connectivity methods, which by overlooking the fluctuation dynamics triggered by neurodegeneration, have yielded inconsistent results. The present multicenter study introduces a data-driven machine learning pipeline based on dynamic connectivity fluctuation analysis (DCFA) on RS-fMRI data from 300 participants belonging to three groups: behavioral variant frontotemporal dementia (bvFTD) patients, Alzheimer's disease (AD) patients, and healthy controls. We considered non-linear oscillatory patterns across combined and individual resting-state networks (RSNs), namely: the salience network (SN), mostly affected in bvFTD; the default mode network (DMN), mostly affected in AD; the executive network (EN), partially compromised in both conditions; the motor network (MN); and the visual network (VN). These RSNs were entered as features for dementia classification using a recent robust machine learning approach (a Bayesian hyperparameter tuned Gradient Boosting Machines (GBM) algorithm), across four independent datasets with different MR scanners and recording parameters. The machine learning classification accuracy analysis revealed a systematic and unique tailored architecture of RSN disruption. The classification accuracy ranking showed that the most affected networks for bvFTD were the SN + EN network pair (mean accuracy = 86.43%, AUC = 0.91, sensitivity = 86.45%, specificity = 87.54%); for AD, the DMN + EN network pair (mean accuracy = 86.63%, AUC = 0.89, sensitivity = 88.37%, specificity = 84.62%); and for the bvFTD vs. AD classification, the DMN + SN network pair (mean accuracy = 82.67%, AUC = 0.86, sensitivity = 81.27%, specificity = 83.01%). Moreover, the DFCA classification systematically outperformed canonical connectivity approaches (including both static and linear dynamic connectivity). Our findings suggest that non-linear dynamical fluctuations surpass two traditional seed-based functional connectivity approaches and provide a pathophysiological characterization of global brain networks in neurodegenerative conditions (AD and bvFTD) across multicenter data.
Collapse
Affiliation(s)
- Sebastian Moguilner
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), California, US; & Trinity College Dublin, Dublin, Ireland; Fundación Escuela de Medicina Nuclear (FUESMEN) and Comisión Nacional de Energía Atómica (CNEA), Buenos Aires, Argentina
| | - Adolfo M García
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), California, US; & Trinity College Dublin, Dublin, Ireland; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Universidad de San Andrés, Buenos Aires, Argentina; Faculty of Education, National University of Cuyo (UNCuyo), Mendoza, Argentina
| | - Yonatan Sanz Perl
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Universidad de San Andrés, Buenos Aires, Argentina; Department of Physics, University of Buenos Aires, Argentina
| | - Enzo Tagliazucchi
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Department of Physics, University of Buenos Aires, Argentina
| | - Olivier Piguet
- School of Psychology and Brain and Mind Centre, The University of Sydney, Sydney, Australia
| | - Fiona Kumfor
- School of Psychology and Brain and Mind Centre, The University of Sydney, Sydney, Australia
| | - Pablo Reyes
- Medical School, Aging Institute, Psychiatry and Mental Health, Pontificia Universidad Javeriana; Mental Health Unit, Hospital Universitario Fundación Santa Fe, Bogotá, Colombia, Hospital Universitario San Ignacio. Bogotá, Colombia
| | - Diana Matallana
- Medical School, Aging Institute, Psychiatry and Mental Health, Pontificia Universidad Javeriana; Mental Health Unit, Hospital Universitario Fundación Santa Fe, Bogotá, Colombia, Hospital Universitario San Ignacio. Bogotá, Colombia
| | - Lucas Sedeño
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.
| | - Agustín Ibáñez
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), California, US; & Trinity College Dublin, Dublin, Ireland; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Universidad de San Andrés, Buenos Aires, Argentina; Universidad Autónoma del Caribe, Barranquilla, Colombia; Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago de Chile, Chile.
| |
Collapse
|
28
|
Ibañez A, Fittipaldi S, Trujillo C, Jaramillo T, Torres A, Cardona JF, Rivera R, Slachevsky A, García A, Bertoux M, Baez S. Predicting and Characterizing Neurodegenerative Subtypes with Multimodal Neurocognitive Signatures of Social and Cognitive Processes. J Alzheimers Dis 2021; 83:227-248. [PMID: 34275897 PMCID: PMC8461708 DOI: 10.3233/jad-210163] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/11/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Social cognition is critically compromised across neurodegenerative diseases, including the behavioral variant frontotemporal dementia (bvFTD), Alzheimer's disease (AD), and Parkinson's disease (PD). However, no previous study has used social cognition and other cognitive tasks to predict diagnoses of these conditions, let alone reporting the brain correlates of prediction outcomes. OBJECTIVE We performed a diagnostic classification analysis using social cognition, cognitive screening (CS), and executive function (EF) measures, and explored which anatomical and functional networks were associated with main predictors. METHODS Multiple group discriminant function analyses (MDAs) and ROC analyses of social cognition (facial emotional recognition, theory of mind), CS, and EF were implemented in 223 participants (bvFTD, AD, PD, controls). Gray matter volume and functional connectivity correlates of top discriminant scores were investigated. RESULTS Although all patient groups revealed deficits in social cognition, CS, and EF, our classification approach provided robust discriminatory characterizations. Regarding controls, probabilistic social cognition outcomes provided the best characterization for bvFTD (together with CS) and PD, but not AD (for which CS alone was the best predictor). Within patient groups, the best MDA probabilities scores yielded high classification rates for bvFTD versus PD (98.3%, social cognition), AD versus PD (98.6%, social cognition + CS), and bvFTD versus AD (71.7%, social cognition + CS). Top MDA scores were associated with specific patterns of atrophy and functional networks across neurodegenerative conditions. CONCLUSION Standardized validated measures of social cognition, in combination with CS, can provide a dimensional classification with specific pathophysiological markers of neurodegeneration diagnoses.
Collapse
Affiliation(s)
- Agustín Ibañez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Global Brain Health Institute, Trinity College Dublin (TCD), Dublin, Ireland
| | - Sol Fittipaldi
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina
| | | | - Tania Jaramillo
- Instituto de Psicología, Universidad del Valle, Cali, Colombia
| | | | - Juan F. Cardona
- Instituto de Psicología, Universidad del Valle, Cali, Colombia
| | - Rodrigo Rivera
- Neuroradiology Department, Instituto de Neurocirugia, Universidad de Chile, Santiago, Chile
| | - Andrea Slachevsky
- Geroscience Center for Brain Health and Metabolism (GERO), Faculty of Medicine, University of Chile, Santiago, Chile
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department - ICBM, Neuroscience and East Neuroscience Departments, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Adolfo García
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, CA, USA
- Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - Maxime Bertoux
- Lille Center of Excellence for Neurodegenerative Disorders (LICEND), CHU Lille, U1172 - Lille Neurosciences & Cognition, Université de Lille, Inserm, Lille, France
| | | |
Collapse
|
29
|
Fittipaldi S, Abrevaya S, Fuente ADL, Pascariello GO, Hesse E, Birba A, Salamone P, Hildebrandt M, Martí SA, Pautassi RM, Huepe D, Martorell MM, Yoris A, Roca M, García AM, Sedeño L, Ibáñez A. A multidimensional and multi-feature framework for cardiac interoception. Neuroimage 2020; 212:116677. [PMID: 32101777 DOI: 10.1016/j.neuroimage.2020.116677] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 02/04/2020] [Accepted: 02/21/2020] [Indexed: 11/18/2022] Open
Abstract
Interoception (the sensing of inner-body signals) is a multi-faceted construct with major relevance for basic and clinical neuroscience research. However, the neurocognitive signatures of this domain (cutting across behavioral, electrophysiological, and fMRI connectivity levels) are rarely reported in convergent or systematic fashion. Additionally, various controversies in the field might reflect the caveats of standard interoceptive accuracy (IA) indexes, mainly based on heartbeat detection (HBD) tasks. Here we profit from a novel IA index (md) to provide a convergent multidimensional and multi-feature approach to cardiac interoception. We found that outcomes from our IA-md index are associated with -and predicted by- canonical markers of interoception, including the hd-EEG-derived heart-evoked potential (HEP), fMRI functional connectivity within interoceptive hubs (insular, somatosensory, and frontal networks), and socio-emotional skills. Importantly, these associations proved more robust than those involving current IA indexes. Furthermore, this pattern of results persisted when taking into consideration confounding variables (gender, age, years of education, and executive functioning). This work has relevant theoretical and clinical implications concerning the characterization of cardiac interoception and its assessment in heterogeneous samples, such as those composed of neuropsychiatric patients.
Collapse
Affiliation(s)
- Sol Fittipaldi
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina
| | - Sofía Abrevaya
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina
| | - Alethia de la Fuente
- National Scientific and Technical Research Council (CONICET), Argentina; Buenos Aires Physics Institute (IFIBA) and Physics Department, University of Buenos Aires, Buenos Aires, Argentina; Laboratory of Neuropsychology (LNPS), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina
| | - Guido Orlando Pascariello
- National Scientific and Technical Research Council (CONICET), Argentina; Multimedia Signal Processing Group - Neuroimage Division, French-Argentine International Center for Information and Systems Sciences (CIFASIS), National Scientific and Technical Research Council (CONICET), Argentina; Laboratory of Neuroimaging and Neuroscience (LANEN), INECO Foundation Rosario, Argentina
| | - Eugenia Hesse
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina; Departamento de Matemática y Ciencias, Universidad de San Andrés, Buenos Aires, Argentina
| | - Agustina Birba
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina
| | - Paula Salamone
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina
| | - Malin Hildebrandt
- Chair for Addiction Research, Institute for Clinical Psychology and Psychotherapy, Dresden, Germany
| | - Sofía Alarco Martí
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina
| | - Ricardo Marcos Pautassi
- Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina; Instituto de Investigación Médica M. y M. Ferreyra, INIMEC-CONICET-UNC, Córdoba, Argentina
| | - David Huepe
- Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile
| | - Miquel Martorell Martorell
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina
| | - Adrián Yoris
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina
| | - María Roca
- National Scientific and Technical Research Council (CONICET), Argentina; Laboratory of Neuropsychology (LNPS), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina
| | - Adolfo M García
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina; Faculty of Education, National University of Cuyo (UNCuyo), Mendoza, Argentina
| | - Lucas Sedeño
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina
| | - Agustín Ibáñez
- Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCYT), INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Argentina; Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile; Universidad Autónoma Del Caribe, Barranquilla, Colombia; ARC Excellence Center of Cognition and its Disorders, Sydney, Australia.
| |
Collapse
|