Unit of quantitative                                   neurocience

We study statistical models for the complex representation of the behavior of brain signal registers in Functional Magnetic Resonance imaging ( fMRI ) paradigms . We have focused on the generation of statistical, computational and mathematical models for the estimation of functional and effective connectivity behavior.

General Objective 1

Continue to work on connectivity networks in people with a diagnosis of Mild Cognitive Disorder (MCI), comparing them with those presenting people of normal aging and in the absence of cognitive pathology. The first results (2016 and 2017) indicate that the complexity of the networks and their properties can differentiate clinically defined groups. The work that marks a benchmark in this area is, for example:

FARRÀS, L., GUÀRDIA, J. & PERÓ, M. (2015). Mild cognitive impairment and fMRI studies of brain functional connectivity: The state of the art. Frontiers in Psychology, 6. doi: 10.3389/fpsyg.2015.01095

General Objective 2

We have launched a protocol to study the behavior of connectivity networks in subjects diagnosed with Major Depressive Disorder (MDD). This is a protocol with which we have already done some pilot tests and will be in force from the fall of 2017, so that these data must already complement some already published works, such as:

GUDAYOL, E.; PERÓ, M.; GONZÁLEZ, A. & GUÀRDIA, J. (2015). Changes in brain connectivity related to the treatment of depression measured through fMRI: A systematic review. Frontiers in Human Neuroscience, 9, 582. doi: 10.3389/fnhum.2015.00582

General Objective 3

We want to study the brain connectivity networks with fMRI in people with Down syndrome. The challenge is to take advantage of the longevity of these people to study the cognitive aspects, because presenting the same amyloid (21) affected by the Dementia Type Alzheimer’s (DTA), allows us to study differences in the construction of a network in a resting situation ( resting state ) that lately gives us interesting data beyond the designs with stimulation presentation. The same approach with other pathologies can be found in:

GUÀRDIA, J., GALLARDO, G.B., GUDAYOL, E., PERÓ, M., & GONZÁLEZ, A.A. (2017). Effect of verbal task complexity in a working memory paradigm in patients with type 1 diabetes. A fMRI study. PloS One, 12(6), e0178172. doi: 10.1371/journal.pone.0178172

In summary we can identify the following specific objectives:

Specific objective 1: Simulation studies on Bayesian parameter estimation techniques in structural equation models (SEM), following the guidelines of the PSI2013-41400-P project.

Specific objective 2: Simulation studies to assess the goodness of the different indicators of adjustment of structural equation models based on the number of variables involved in the analysis and the number of paths .

Specific objective 3: Study of the cerebral signal to the depressive depressive disorder. Based on the applied research lines of the group and the doctoral studies carried out in recent years.

Specific objective 4: Study of the cerebral signal applied to populations of special interest (Down Syndrome) for the study of connectivity networks