QUANTITATIVE PSYCHOLOGY

Principal Investigators

Joan Guardia-Olmos

Full professor

Quantitative neuroscience

Research team

 

Maribel Pero

Full Professor

 

Vicenç Quera

Full Professor

 

Francesc Salvador

Full Professor

 

Antonio Solanas

Full Professor

 

Sonia Benitez

Associate Professor

 

Laia Farras

Associate Professor

 

David Leiva

Associate Professor

 

Rumen Rumenov

Associate Professor

 

Maria Carbo

Associate Professor

 

Ruth Dolado

Lecturer

 

Cristina Castañe

Early Stage Researcher

 

Elisabet Gimeno

Early Stage Researcher

 

Nuria Mancho

Early Stage Researcher

 

Marc Montala

Early Stage Researcher

Research Interest

 

The study of brain connectivity is one of the main challenges when studying the active brain. Brain connectivity is operationally defined as the estimation of the relation between brain areas (regions of interest, ROIs, or Volumes of interest, VOIs); these relations are established when a specific cognitive task is being solved or when resting. In order to estimate the connectivity, different brain signals can be used, each of which has different neurofucntional properties. One of the signals showing great ability to represent the active brain is the BOLD signal, obtained when using functional magnetic resonance imaging (fMRI). What is registered is the modification of the magnetic field that takes place due to the increment of the presence of oxygen is certain brain areas when these are activated during a cognitive task. When the brain is resting, the signal shows the basal state used as a reference.

Technologies & Methods

 

  • Generation of statistical advanced models applied to the big data structures and brain signal
  • Psychometric technology
  • Advanced Multivariate Analysis

Featured Projects

 

    • Impact of diet and physical activity on cognitive reserve and quality of life in persons with down syndrome. Ministerio de Economia y Competitividad. EIN2019-103265. Joan Guardia-Olmos

 

    • Indicadores estadísticos para el estudio de redes de conectividad cerebral en registros de resonancia magnética funcional (FMRI) y su aplicación para el diagnostico del deterioro cognitivo. Ministerio de Ciencia, Innovación y Universidades. PGC2018-095829-B-I00. Joan Guardia-Olmos

Featured Publications

 

    • Figueroa-Jimenez, M. D., Carbó-Carreté, M., Cañete-Massé, C., Zarabozo-Hurtado, D., Peró-Cebollero, M., Salazar-Estrada, J. G., & Guàrdia-Olmos, J. (2021). Complexity Analysis of the Default Mode Network Using Resting-State fMRI in Down Syndrome: Relationships Highlighted by a Neuropsychological Assessment. Brain Sciences, 11(3), 311. https://doi.org/10.3390/brainsci11030311

 

    • Gudayol-Ferré, E., Duarte-Rosas, P., Peró-Cebollero, M., & Guàrdia-Olmos, J. (2021). The effect of second-generation antidepressant treatment on the executive functions of patients with major depressive disorder: a meta-analysis study with structural equation models. Psychiatry Research, 296, 113690. https://doi.org/https://doi.org/10.1016/j.psychres.2020.113690

 

    • Dolado, R., Gimeno, E., Meunier, H., & Beltran, F. S. (2021). Modeling social styles in macaque societies applied to a semi-free-ranging group of Macaca tonkeana. Behavioral Ecology and Sociobiology, 75(3), 53. https://doi.org/10.1007/s00265-021-02965-x

 

    • Figueroa-Jimenez, M. D., Cañete-Massé, C., Carbó-Carreté, M., Zarabozo-Hurtado, D., Peró-Cebollero, M., Salazar-Estrada, J. G., & Guàrdia-Olmos, J. (2021). Resting-state default mode network connectivity in young individuals with Down syndrome. Brain and Behavior, 11(1), e01905. https://doi.org/10.1002/brb3.1905

 

    • Figueroa-Jiménez, M. D., Cañete-Massé, C., Carbó-Carreté, M., Zarabozo-Hurtado, D., & Guàrdia-Olmos, J. (2021). Structural equation models to estimate dynamic effective connectivity networks in resting fMRI. A comparison between individuals with Down syndrome and controls. Behavioural Brain Research, 405, 113188. https://doi.org/https://doi.org/10.1016/j.bbr.2021.113188

 

    • Manolov, R., Solanas, A., & Sierra, V. (2020). Changing Criterion Designs: Integrating Methodological and Data Analysis Recommendations. Journal of Experimental Education, 88(2), 335–350. https://doi.org/10.1080/00220973.2018.1553838

 

    • Carbó-Carreté, M., Cañete-Massé, C., Peró-Cebollero, M., & Guàrdia-Olmos, J. (2020). Eliminate the effect of severity of the Personal Outcomes Scale: Linear regression in persons with intellectual disability. Psicothema, 32(3), 420–428. https://doi.org/10.7334/psicothema2019.353

 

    • Pedersini, C. A., Guàrdia-Olmos, J., Montalà-Flaquer, M., Cardobi, N., Sanchez-Lopez, J., Parisi, G., Savazzi, S., & Marzi, C. A. (2020). Functional interactions in patients with hemianopia: A graph theory-based connectivity study of resting fMRI signal. PLOS ONE, 15(1), e0226816. https://doi.org/10.1371/journal.pone.0226816

 

    • Carbó-Carreté, M., Cañete-Massé, C., Figueroa-Jiménez, M. D., Peró-Cebollero, M., & Guàrdia-Olmos, J. (2020). Relationship between Quality of Life and the Complexity of Default Mode Network in Resting State Functional Magnetic Resonance Image in Down Syndrome. International Journal of Environmental Research and Public Health, 17(19), 7127. https://www.mdpi.com/1660-4601/17/19/7127

 

    • Mancho-Fora, N., Montalà-Flaquer, M., Farràs-Permanyer, L., Bartrés-Faz, D., Vaqué-Alcázar, L., Peró-Cebollero, M., & Guàrdia-Olmos, J. (2020). Resting-State Functional Connectivity Dynamics in Healthy Aging: An Approach Through Network Change Point Detection. Brain Connectivity, 10(3), 134–142. https://doi.org/10.1089/brain.2019.0735

 

    • Carbó-Carreté, M., Cañete-Massé, C., Peró-Cebollero, M., & Guàrdia-Olmos, J. (2020). Using fMRI to Assess Brain Activity in People With Down Syndrome: A Systematic Review. Frontiers in Human Neuroscience, 14, 147. https://doi.org/10.3389/fnhum.2020.00147

 

    • Quera, V., Gimeno, E., Beltran, F. S., & Dolado, R. (2019). Local interaction rules and collective motion in black neon tetra (Hyphessobrycon herbertaxelrodi) and zebrafish (Danio rerio). Journal of Comparative Psychology (Washington, D.C. : 1983), 133(2), 143–155. https://doi.org/10.1037/com0000172