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Arelio, I.

Publications and source records attributed to Arelio, I..

2 recordsLinked to original sources

Development of the Functional Connectome Topology in Adolescence: evidence from Topological Data Analysis

Adolescence is a crucial developmental period in terms of behavior and mental health. Therefore, understanding how the brain develops during this stage is a fundamental challenge for neuroscience. Recent studies have modelled the brain as a network or connectome, mainly applying measures from graph theory, showing a change in its functional organization such as an increase in its segregation and integration. Topological Data Analysis (TDA) complements such modelling by extracting high-dimensional features across the whole range of connectivity values, instead of exploring a fixed set of connections. This study enquiries into the developmental trajectories of such properties using a longitudinal sample of typically developing participants (N = 98; 53/45 F/M; 6.7-18.1 years), applying TDA into their functional connectomes. In addition, we explore the effect of puberty on the individual developmental trajectories. Results showed that compared to random networks, the adolescent brain is more segregated at the global level, but more densely connected at the local level. Furthermore, developmental effects showed nonlinear trajectories for the integration of the whole brain and fronto-parietal networks, with an inflection point and increasing trajectories after puberty onset. These results add to the insights in the development of the functional organization of the adolescent. Significance StatementTopological Data Analysis may be used to explore the topology of the brain along the whole range of connectivity values instead of selecting only a fixed set of connectivity thresholds. Here, we explored some properties of the topology of the brain functional connectome, and how they develop in adolescence. First, we show that developmental trajectories are nonlinear and better explained by the puberty status than chronological age, with an inflection point around the puberty onset. The greatest effect is the increase in functional integration for the whole brain, and particularly for the Fronto-Parietal Network when exploring functional subnetworks.

neuroscience↗

Topological Data Analysis reveals robust alterations in the whole-brain and frontal lobe functional connectomes in Attention-Deficit/Hyperactivity Disorder

The functional organization of the brain network (connectome) has been widely studied as a graph; however, methodological issues may affect the results, such as the brain parcellation scheme or the selection of a proper threshold value. Instead of exploring the brain in terms of a static connectivity threshold, this work explores its algebraic topology as a function of the filtration value (i.e., the connectivity threshold), a process termed the Rips filtration in Topological Data Analysis. Specifically, we characterized the transition from all nodes being isolated to being connected into a single component as a function of the filtration value, in a public dataset of children with attention-deficit/hyperactivity disorder (ADHD) and typically developing children. Results were highly congruent when using four different brain segmentations (atlases), and exhibited significant differences for the brain topology of children with ADHD, both at the whole brain network and at the functional sub-network levels, particularly involving the frontal lobe and the default mode network. Therefore, this approach may contribute to identify the neurophysio-pathology of ADHD, reducing the bias of connectomics-related methods.\n\nHighlightsO_LITopological Data Analysis was implemented in functional connectomes.\nC_LIO_LIBetti curves were assessed based on the area under the curve, slope and kurtosis.\nC_LIO_LIThe explored variables were robust along four different brain atlases.\nC_LIO_LIADHD showed lower areas, suggesting decreased functional segregation.\nC_LIO_LIFrontal and default mode networks showed the greatest differences between groups.\nC_LI\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=168 HEIGHT=200 SRC=\"FIGDIR/small/751008v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (51K):\norg.highwire.dtl.DTLVardef@50e91corg.highwire.dtl.DTLVardef@1f837aforg.highwire.dtl.DTLVardef@10fe920org.highwire.dtl.DTLVardef@1923ead_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗