Abstract
In this paper we investigate the changes in the functional connectivity intensity, and some related properties, in healthy people, across the life span and at resting state. For the explicit computation of the functional connectivity we exploit a recently proposed model, that bases not only on the correlations data provided by the acquisition equipment, but also on different parameters, such as the anatomical distances between nodes and their degrees. The leading purpose of the paper is to show that the proposed approach is able to recover the main aspects of resting state condition known from the available literature, as well as to suggest new insights, perspectives and speculations from a neurobiological point of view. Our study involves 133 subjects, both males and females of different ages, with no evidence of neurological diseases or systemic disorders. First, we show how the model applies to the sample, where the subjects are grouped into 28 different groups (14 of males and 14 of females), according to their age. This leads to the construction of two graphs (one for males and one for females), that can be realistically interpreted as representative of the neural network during the resting state. Second, following the idea that the brain network is better understood by focusing on specific nodes having a kind of centrality, we refine the two output graphs by introducing a new metric that favours the selection of nodes having higher degrees. As a third step, we extensively comment and discuss the obtained results. In particular, it is remarkable that, despite a great overlapping exists between the outcomes concerning males and females, some intriguing differences appear. This motivates a deeper local investigation, which represents the fourth part of the paper, carried out through a thorough statistical analysis. As a result, we are enabled to support that, for two special age groups, a few links contribute in differentiating the behaviour of males and females. In addition, we performed an average-based comparison between the proposed model and the traditional statistical correlation-based approach, then discussing and commenting the main outlined discrepancies.
Highlights
Functional magnetic resonance in neuroscienceUndoubtedly, the functional magnetic resonance imaging constitutes a fundamental technique to examine brain function by using blood oxygen level–dependent (BOLD) contrast
In this paper we have investigated the functional connectivity” (FC) intensity changes, and some related invariant properties, in healthy people across the life span and at resting state
We have exploited the recently proposed FD model [20], and we have applied it to a sample of 133 healthy participants, with age distributed throughout the lifespan
Summary
Functional magnetic resonance in neuroscienceUndoubtedly, the functional magnetic resonance imaging (fMRI) constitutes a fundamental technique to examine brain function by using blood oxygen level–dependent (BOLD) contrast. While BOLD contrast has been used for nearly 3 decades to localize the neuronal activity associated with a specific task or stimulus, it is established that, even at rest, the BOLD signal exhibits low-frequency spontaneous fluctuations These oscillations are characterized by temporal correlations across spatially distinct brain regions and are believed to reflect the degree of “functional connectivity” (FC) (see for example [1]). Since our aim was to focus on the links having strongest intensities, we defined data-depending thresholds that select, for each one of the 133 distributions, a suitable neighbor of interest (NOI) [23] This is done by fixing a q-quantiles partition of each distribution, and by considering, for each k 2 {1, . We recall that this implies that the (100(q-qk)/q)% of the data of the k-th distribution contributes to the corresponding NOI
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