Prefiltering based on experimental paradigm for analysis of fMRI complex brain networks

PLOS ONE RESEARCH ARTICLE Prefiltering based on experimental paradigm for analysis of fMRI complex brain networks Salvador Jiménez1*, Laura Rotger3, Carlos Aguirre2, Alberto Muñoz3, Sergio Granados4, Jesús Tornero ID4* 1 Dept. Matemática Aplicada a las TIC, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain, 2 GNB, EPS, Universidad Autónoma de Madrid, Madrid, Spain, 3 Departamento de Radiologı́a, Universidad Complutense de Madrid, Madrid, Spain, 4 Unidad de Diagnóstico por Imagen, Hospital Los Madroños, Madrid, Spain a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Jiménez S, Rotger L, Aguirre C, Muñoz A, Granados S, Tornero J (2020) Prefiltering based on experimental paradigm for analysis of fMRI complex brain networks. PLoS ONE 15(10): e0238994. https://doi.org/10.1371/journal. pone.0238994 Editor: Hocine Cherifi, Unviersity of Burgundy, FRANCE Received: March 9, 2020 Accepted: August 24, 2020 * (SJ); (JT) Abstract Brain networks offers a new insight about connections between function and anatomical regions of human brain. We present results from brain networks built from functional magnetic resonance images during finger tapping paradigm. Pearson voxel-voxel correlation in time and frequency domains were performed for all subjects. Besides this standard framework we have implemented a new approach consisting in filtering the data with respect to the fMRI paradigm (finger tapping) in order to obtain a better understanding of the network involved in the execution of the task. The main topological graph measures have been compared in both cases: voxel-voxel correlation and voxel-paradigm filtering plus voxel-voxel correlation. With the standard voxel-voxel correlation a clearly free-scale network was obtained. On the other hand, when we prefiltered the paradigm we obtained two different kind of networks: 1) free-scale; 2) random-like. To our best knowledge, this behaviour is reported here for first time for brain networks. We suggest that paradigm signal prefiltering can provide more infomation about the brain networks. Published: October 14, 2020 Copyright: © 2020 Jiménez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: CA is supported by MINECO/FEDER, under grant PGC2018-095895-B-I00. Ministerio de Asuntos Económicos y Transformación Digital. https:\\www.mineco.gob.es. SJ is partially supported by MINECO under grant MTM201567396-P. Ministerio de Asuntos Económicos y Transformación Digital. https:\\www.mineco.gob. es. The funders had no role in study design, data Introduction It is known, since the nineteenth century, that the brain constitutes a huge and complicated structural network [1]. The latest advances in the study of complex systems have motivated new approaches and interpretations applied to brain structural and functional characterization [2, 3]. Functional brain networks can be studied with fMRI [4]. One of the first studies where functional magnetic resonance imaging was used to extract functional networks connecting correlated human structural images of brain was performed by Eguı́luz et al. [5]. In this work they reconstructed correlation matrices of BOLD signals from all MRI voxels during different finger tapping tasks for seven healthy subjects. The resulting functional networks showed small-world behaviour [6] with large clustering coefficients, from 0.14 to 0.15 for a threshold ranging from rc = 0.6 up to 0.8, a short path length, and a probability of a functional connection between any two nodes (degree distribution), scaled as a power law P(k) / k−γ [7]. Their PLOS ONE | https://doi.org/10.1371/journal.pone.0238994 October 14, 2020 1 / 13 PLOS ONE collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Prefiltering based on experimental paradigm for analysis of fMRI complex brain networks computations showed clearly scale-free degree distributions with a scaling exponent γ close to 2, a value that was identified as independent of the threshold value rc. A similar dependence of the functional connectivity was found by Salvador et al. [8]. Resting-state functional connectivity in the human brain was studied by van den Heuvel et al. where both patterns, the smallworld configuration as well as the power law degree distribution with a scaling exponent around 2, were confirmed [9], regardless of the threshold. In all mentioned works the authors identified clearly scale-free degree distributions and compared them to random-like distributions with a marked different behaviour. Following the approach of Eguı́luz et al., in this work we have studied voxel-voxel correlation matrices of BOLD signals which were extracted from fMRI studies and we have constructed and analyzed the corresponding graphs. Besides this standard framework, we have implemented a new approach consisting in a previous filtering of the data with respect to the fMRI paradigm in order to obtain a better understanding of the network involved in the execution of the task. The main topological graph measures have been compared in the two cases: voxel-voxel correlation and voxel-paradigm filtering plus voxel-voxel correlation. We illustrate the process in Fig 1. The pre-filtering is justified since it is aimed at selecting the nodes related to the task in order to enhance the effect under study. We understand that no meaningful information related to the task is removed since pre-filtering is based on correlations with the paradigm. Higher order structural properties may be eliminated by applying pre-filtering, in fact if these higher order structural properties are not related to the task we understand that they should be removed. Materials and methods MRI protocol Five volunteers all right-handed, 4 males, 1 female, mean age 38, were recruited at Hospital Los Madroños in Madrid, Spain. A previous questionnaire, a general medical and neurological examination were performed for volunteer selection. Those volunteers were taken from a previous unpublished study (Tractografı́a Funcional de Imagen de Resonancia Magnética) whose protocol was previously approved from the Local Ethics Committee. As the current individuals have been selected from the former study, Los Madroños Board of Director waived any new requirement for the current study. The study was performed using a Siemens-Avanto 1.5 Tesla imaging system with a 12-element head matrix coil. The finger-tapping test (FTT) is a neuropsychological test that examines motor functioning, specifically, motor speed and lateralized coordination. Subjects, while (...truncated)