Interplay between salience and default mode network in a socio-cognitive task towards a close other

Universidade do Minho Escola de Psicologia Cátia Daniela Marques Ribeiro Interplay between salience and default mode network in a socio-cognitive task towards a close other junho de 2021 Interplay between salience and default mode network in a socio-cognitive task towards a close other Cátia Daniela Marques Ribeiro UMinho | 2021 Universidade do Minho Escola de Psicologia junho de 2021 Cátia Daniela Marques Ribeiro Interplay between salience and default mode network in a socio-cognitive task towards a close other Dissertação de Mestrado Mestrado Integrado em Psicologia Trabalho efetuado sob a orientação de Professora Doutora Joana Fernandes Coutinho Professor Doutor José Miguel Soares ii DIREITOS DE AUTOR E CONDIÇÕES DE UTILIZAÇÃO DO TRABALHO POR TERCEIROS Este é um trabalho académico que pode ser utilizado por terceiros desde que respeitadas as regras e boas práticas internacionalmente aceites, no que concerne aos direitos de autor e direitos conexos. Assim, o presente trabalho pode ser utilizado nos termos previstos na licença abaixo indicada. Caso o utilizador necessite de permissão para poder fazer um uso do trabalho em condições não previstas no licenciamento indicado, deverá contactar o autor, através do RepositóriUM da Universidade do Minho. Atribuição-NãoComercial-SemDerivações CC BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/ iii Acknowledgments I want to dedicate this work to everyone that somehow have aided me during the last years: To my supervisors, Professor Dr. Joana Fernandes Coutinho and Professor Dr. José Miguel Soares. Thank you, from the bottom of my heart, for the time, support, and unmeasurable help throughout this process. I learned so much from you, and without both your scientific and methodological expertise, this work could never be done. To my dear sisters, Tânia and Vanessa, thank you for all the love, patience and support, in the roughest moments. To my favorite uncle, Tio Carlos, thank you for always believing in me and for pushing me to grow into a better version of myself. Finally, and for most, to the love of my life, Ricardo, thank you for all the love, understanding, and encouragement and for always being there. I also would like to thank all the team from the Psychological Neuroscience Lab, especially Alberto Lema that kindly sent me some essential material. Unfortunately, I didn’t have the chance to spend time at the lab, but I learned a lot from all the excellent presentations and discussions during our weekly neurolab meetings. Additionally, a special thank you to my friends Isabela, Márcia, and Filipa, for all the support, good talks, and for the “ear” to my random lamentations. iv STATEMENT OF INTEGRITY I hereby declare having conducted this academic work with integrity. I confirm that I have not used plagiarism or any form of undue use of information or falsification of results along the process leading to its elaboration. I further declare that I have fully acknowledged the Code of Ethical Conduct of the University of Minho. University of Minho, 02.06.2021. _____________________________________ v Interação entre salience e default mode network numa tarefa de cognição social com um outro significativo Resumo A cognição social - uma competência essencial no contexto das relações interpessoais - depende de dois subsistemas principais para a compreensão dos outros. Estes subsistemas são sustentados por diferentes redes cerebrais: a Default Mode Network (DMN), associada ao subsistema socio-cognitivo (i.e.,Mentalização), e a Salience Network (SN), associada ao subsistema socio-afetivo (i.e., Empatia). Estas correspondem a conhecidas redes cerebrais de descanso, que parecem constituir a base para a performance de tarefas sociais. Este estudo teve como objetivo analisar os mapas de conectividade funcional de ambas as redes na transição do estado de repouso para o desempenho de uma tarefa, utilizando para isso análise de componentes independentes e análise de conetividade baseada em seeds. 42 participantes envolvidos num relacionamento amoroso monogâmico responderam a um questionário de empatia diádica e foram submetidos a um protocolo fMRI, que incluiu uma aquisição de estado de repouso seguida por uma tarefa, na qual os sujeitos assistiam a vídeos com conteúdo emocional do seu parceiro, elaborando sobre a experiência do parceiro (condição other ) ou sobre sua própria experiência (condição self ). Verificámos que algumas regiões da DMN exibiram maior conectividade durante o desempenho da tarefa em comparação com o estado de repouso. A conectividade da SN foi mais limitada na condição other em comparação com as condições de repouso e self. Os resultados revelaram também uma interação entre a DMN e a SN, particularmente evidente durante o desempenho da tarefa social. Palavras-chave: Cognição Social; Default Mode Network ; Other ; Salience Network ; Self . vi Interplay between salience and default mode network in a social-cognitive task towards a close other Abstract Social cognition, an essential ability in the context of interpersonal relationships, relies on two main subsystems to construct the understanding of others. These subsystems are sustained by different brain networks: the Default Mode Network (DMN) associated with the socio-cognitive subsystem (i.e., mentalizing), and the Salience Network (SN) associated with the socio-affective subsystem (i.e., empathy). These are well-known resting state networks that seem to constitute a baseline for the performance of social tasks. The present study aimed to investigate both networks' functional connectivity maps in the transition from rest to task performance, using independent component and seed-based analysis. A sample of 42 participants involved in a monogamous romantic relationship completed a questionnaire of dyadic empathy and underwent an fMRI protocol that included a resting state acquisition, followed by a task in which subjects watched emotional videos of their romantic partner and elaborated on their partner’s (other condition) or on their own experience (self condition). We found that some DMN regions exhibited increased connectivity during task performance in comparison to resting state. The other condition revealed a more limited SN´s connectivity in comparison to the self and rest conditions. Overall, the results showed an interplay between the DMN and SN, particularly in social task performance. Keywords: Social Cognition; Default Mode Network; Other; Salience Network; Self. vii Contents Abbreviations and acronyms ………………………………………………………………………………………………..vii List of figures ……………………………………………………………………………………………………………………viii List of tables ……………………………………………………………………………………………………………………viii Introduction ……………………………………………………………………………………………………………………….9 Method ……………………………………………………………………………………………………………………….….12 Participants ………………………………………………………………………………………………………….12 Self-report measures …………………………………………………………………………………….………..13 Experimental procedure ……………………………………………………………………………….…………14 Image acquisition ……………………………………………………………………………………….………..14 Socio-cognitive task ……………………………………………………………………………………….……..14 Data analysis …………………………………………………………………………………………………………15 Image processing ………………………………………………………………………………………….………15 Independent Component Analysis ………………………………………………………………………….….16 Seed-based analysis ……………………………………………………………………………………………....17 Correlation analysis with IRIC . ………………………………………………………………………………….17 Results ……………………………………………………………………………………………………………………………18 DMN and SN's functional connectivity in Rest, Self, and Other conditions ……………….…….….18 Independent component analysis approach …………………………………………………………….…..18 Seed-based approach ………………………………………………………………………………………….….21 Association between DMN and SN's FC and self-report measures …………………………………..28 Discussion ………………………………………………………………………………………………………………………29 Limitations and future directions … ……………………………………………………………………….…..32 References ……………………………………………………………………………………………………………………..33 Abbreviations and acronyms ACC - anterior middle cingulate cortex AI - anterior insula BOLD - blood oxygen level depend DMN - Default Mode Network EC - dyadic empathic concern subscale FC - functional connectivity SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 14 Experimental procedure After the first screening to assess the inclusion in the study, the goals and procedures were explained to the participants, who signed a written informed consent before the beginning of the experiment. This study belongs to a large research project about social cognition in the context of romantic interaction, which was approved by the Institutional Review Board of University of Minho and complied with the principles expressed in the Declaration of Helsinki (with the amendment of Tokyo 1975, Venice1983, HongKong 1989, Somerset West 1996, Edinburgh 2000). The experiment started with each participant completing a sociodemographic form and the selfreport measures. Then, after assured all the security measures, each participant went on a fMRI scanning session at a clinical hospital in Oporto. While being scanned, the participants performed the social task described below. The total experimental procedure time lasted 45 minutes. Image acquisition Structural (T1) and functional (T2*) images were acquired with a clinically approved 3 Tesla MRI scanner (Siemens Magnetom Skyra, Erlangen, Germany) in one imaging session per participant. Each session included one MPRAGE T1 scan (192 sagittal slices) with the following parameters: repetition time (TR) = 2000 ms; echo time (TE) = 2.33s; flip angle (FA) = 7°; field of view (FoV) = 256 mm; slice gap = 0 mm; pixel size = 0.8 × 0.8 mm2; and slice thickness = 0.8 mm and one functional blood oxygen level depend (BOLD) sensitive echo-planar imaging (EPI) sequence (375 volumes; 39 axial slices) with the subsequent imaging parameters: TR = 2000 ms; TE = 29 ms; FA = 90°; FoV = 1554 mm; matrix size = 64 × 64; pixel size = 3 × 3 mm 2; and slice thickness = 3 mm. During this sequence, the synchronization between the experimental paradigm and the acquisition for each TR was ensured using the Lumina 3G Controller. Additionally, before the experimental task a 7 minutes resting state functional (T2*) scan (210 volumes; 39 axial slices) was acquired following the same EPI parameters. During the resting state/task-free acquisition, participants were instructed to keep their eyes closed, to remain awake but relaxed and motionless as possible, doing nothing in particular during the acquisition. Socio-cognitive task Each participant watched a set of video vignettes (20 seconds) of his/her romantic partner expressing emotional content. While watching the vignettes, participants were asked to either focus on their own experience (self condition) or on their partner's experience (other condition). These videos containing negative and positive emotional content towards the partner were extracted from a previously SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 15 video-recorded interaction task in the lab (details regarding this interaction task can be found in Coutinho et al., 2017; 2018). The task was composed by two blocks, one for each condition, and each block contained 22 trials. Each trial was composed by a fixation cross (during 5 seconds); instructions in accordance with each referent block, for example the instruction for the other block was "In the next video focus on how your partner is feeling."; during (3 seconds); video (during 20 seconds); and behavioral response (during 4 seconds). An example of a trial in the other condition is displayed in Figure 1. In terms of the behavioral response (which essentially aimed to ensure that participants were focusing in their own and on the partner’s experience) it was required to participants to choose among one of three options, dependent on the emotional impact of the video: "Bad" for any kind of negative state or emotion, "Neutral" in the absence of any positive or negative state or emotion; or "Good" for any kind of positive state or emotion. The stimuli were displayed in a pseudo-randomized order. The blocks were also displayed in a randomized order across participants. The total duration of the task was 1364 seconds (24 minutes). More detailed information regarding this task can be found in Esménio et al. (2019; 2020). Figure 1 Example of a trial on the other condition Data analysis Image processing Before data processing, all images were visually inspected to ensure the absence of head motion artifacts and any brain lesion. All imaging were preprocessed using the advanced edition of the Data Processing Assistant for Resting-State fMRI 5.1 (DPARSF; Chao-Gan & Yu-Feng 2010; http://rfmri.org/DPARSF), according to the following steps: removal of the first five volumes (10s), to SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 16 ensure signal stabilization and participants adjustment to scanner noise; slice-timing correction, using the middle slice as reference; motion correction, using rigid body alignment of each volume to the mean image of the acquisition and motion scrubbing (volumes in which FD > .5 and DVARS > .5% change in the BOLD signal were “scrubbed,” or removed entirely from the data), to correct for movement artifacts and related susceptibility artifacts; rigid-body registration of the mean functional image to the T1 and segment using Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL; Ashburner, 2007); normalization to the Montreal Neurological Institute (MNI) space by DARTEL; smoothing with a Gaussian kernel of 8 mm full-width at half-maximum to decrease spatial noise; and band-pass temporal filtering (0.01-0.08 Hz), applied to the resting state functional images, and high-pass temporal filtering (128s) applied to the images acquired during task performance, to remove lowfrequency noise from the data. The final images were visually inspected and eight participants were excluded: one due to head motion higher than 2 mm in translation and 2° in rotation; two due to anatomical abnormalities; four due to technical problems during the acquisition; and one due to abnormal activation patterns/noise during task performance. Independent Component Analysis Group spatial independent component analysis (ICA) was carried out to search for common spatial patterns among subjects, both during resting state and during task performance, using the Group ICA v4.0c of fMRI Toolbox (GIFT; http://mialab.mrn.org/software/gift/). The ICA analysis consisted in extracting the individual spatial independent maps and their related time courses (Beckmann et al., 2005). The dimensionality reduction of the functional data and computational load was performed with principal component analysis (PCA). The estimated number of independent components (IC) was 20, for each subject, based on a good trade-off between preserving the information in the data while reducing its size (Calhoun et al., 2001; Beckmann et al., 2005). ICA calculation was then performed using the iterative Infomax algorithm (Bell & Sejnowski, 1995). The ICASSO tool was used to control the ICA reliability. Twenty computational runs were made on the dataset, during which the components were being recomputed and compared across runs and the robustness of the results was ensured (Himberg et al., 2004). The IC were obtained and each voxel of the spatial map was expressed as a t statistic map, which was finally converted to a z statistic that characterizes the degree of correlation of the voxel signal with the component time course, providing a measure of the FC within each network. Then, the IC were sorted, SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 17 visually inspected and spatially matched using the DMN and SN templates, provided by FIND Lab (http://findlab.stanford.edu/functional_ROIs.html). We selected the IC that showed the highest spatial overlap with the provided templates, to represent each network. For the group analysis (second-level analyses), the General Linear Model (GLM) from Statistical Parametric Mapping 12.0 (SPM12; Wellcome Department of Cognitive Neurology, London, UK; http://www.fil.ion.ucl.ac.uk) was used. The individual DMN and SN’s z maps, were included in the same group and a one-sample t test ( p < .05 FWE corrected and extent threshold k = 10 voxels) was performed to study the global pattern of activation of the DMN and SN. The resulting statistical maps were masked using the DMN and SN templates, respectively. Only the typical DMN and SN regions were reported and anatomical labeling was assigned by a combination of visual inspection and Anatomical Automatic Labeling atlas (AAL; Tzourio-Mazoyer et al., 2002). Seed-based analysis For the seed-based functional connectivity analysis, we used a priori defined ROIs, based on MNI coordinates reported by previous fMRI studies. Thus, for the DMN we selected the ventral MPFC (x = 1, y = 55, z = -3) following the coordinates proposed by Di & Biswal (2014) and Knyazev et al. (2020). As seed for the SN, we used the right AI (x = 36, y = 18, z = 4) following the coordinates proposed by Menon (2015) and Alcalá-López et al. (2018) using a 8 mm radius sphere in both cases. The correlation maps for these seed regions were produced by computing correlation coefficients between the mean time series of each ROI and the time series of all other voxels in the brain for each participant. Correlation coefficients were converted to z -values using Fisher's transform to improve normality. Then, the individual participant’s z maps from each seed were used to perform second-level analyses, following the same procedure described above, in the ICA section. To study the interplay between the DMN and SN, we used the same individual z maps from each seed, including it in the same group and performed a one-sample t test ( p < .05 FWE corrected and extent threshold k = 10 voxels), masking the resulting statistical map of the MPFC’s seed with the template of the SN, and masking resulting statistical map of the rAI’s seed with the template of the DMN. Only the typical DMN and SN regions were reported and anatomical labeling was assigned by a combination of visual inspection and AAL. Correlation analysis with IRIC SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 18 The multiple regression (with positive and negative correlations) was performed to identify which areas of the DMN and SN were associated with IRIC total, cognitive and affective scores. Results were considered significant at p < .05 corrected for multiple comparisons using the Monte Carlo correction (combined height threshold p = .05 and a minimum cluster size = 54 for the DMN and 35 for the SN determined by Monte Carlo simulation program, AlphaSim). The resulting statistical maps were, also, presented using the DMN and SN’s templates as masks, and only the typical network regions were reported and anatomical labeling was assigned by a combination of visual inspection and AAL. Results DMN and SN's functional connectivity in Res, Self and Other conditions Independent component analysis approach DMN's functional connectivity At a group level the DMN's spatial maps activated the traditional regions associated with this network, in the three conditions, as can be observed in table 2. We found that the DMN's connectivity pattern changed from resting state to self and other processing, with some regions exhibiting increased FC during the social task performance, in comparison to resting state as can also be observed in table 2 and figure 2. Moreover, we observed a higher FC in anterior regions of the DMN, namely in left superior medial frontal gyrus (SMFG) and ventral ACC both in rest and self conditions, and higher FC on posterior regions in the other condition, namely in PCC/precuneus. SN's functional connectivity Regarding the SN's connectivity, we found that the spatial maps also evidenced the traditional regions associated with this network, in the three conditions, as can be seen in table 3. The overall network's FC pattern changed between conditions, with the other condition revealing a more limited SN´s connectivity in comparison to the self and rest conditions. For instance, the other condition presented a lower FC in the dorsal ACC - a SN's key region - and showed a reduced connectivity in the AI, as illustrated in figure 2. SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 19 Table 2 DMN’s functional connectivity in the three conditions MNI Coordinates MNI Coordinates MNI Coordinates Region of interest x y z T k Region of interest x y z T k Region of interest x y z T k DMN Resting Self Other L Superior medial frontal -6 51 15 29.11 1038 L Ventral anterior cingulate -3 45 15 45.09 1218 R Precuneus 6 -57 18 40.31 469 R Ventral anterior cingulate 6 48 18 28.51 R Ventral anterior cingulate 9 45 18 44.54 L Posterior cingulate 0 -42 30 38.44 R Posterior cingulate 3 -48 27 19.05 347 L Precuneus -3 -57 18 38.34 469 L Precuneus -6 -54 18 37.47 L Posterior cingulate -6 -51 27 18.27 R Precuneus 6 -57 18 37.30 R Ventral anterior cingulate 6 39 12 39.47 1189 L Angular /TPJ -48 -66 33 15.64 22 R Posterior cingulate 6 -42 21 31.64 L Ventral anterior cingulate -3 42 9 38.89 R Superior frontal 15 36 51 14.97 40 L Angular/TPJ -42 -66 33 29.07 22 L Angular/TPJ -42 -66 33 30.21 22 R Angular/TPJ 51 -63 27 13.55 13 R Angular/TPJ 51 -63 27 23.30 13 R Angular/TPJ 48 -60 30 27.04 13 R Middle cingulate 3 -15 39 17.42 33 L Middle cingulate 0 -21 39 17.46 33 L Parahippocampal -24 -30 -12 16.49 79 R Superior frontal 18 42 39 13.75 31 R Superior frontal 15 33 51 15.45 39 L Superior medial frontal -3 51 15 13.46 446 L Middle cingulate 0 -21 39 14.84 29 L Frontal medial orbital 0 51 -3 13.07 L Superior medial frontal -3 60 12 14.02 547 R Middle cingulate 3 -15 39 13.17 32 L Middle frontal -24 30 48 10.69 43 L Lingual -15 -33 -3 12.69 74 L Thalamus -6 -3 6 10.09 66 L Parahippocampal -21 -24 -12 11.50 R Thalamus 6 -6 3 9.94 L Middle frontal -24 30 48 11.28 79 L Thalamus -6 0 0 7.70 40 R Thalamus 6 -15 3 7.49 Note. p<. 05 FWE corrected, extent threshold k=10 voxels; k = cluster size; L = left, R = right; TPJ = temporoparietal junction. SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 20 Table 3 SN’s functional connectivity in the three conditions MNI Coordinates MNI Coordinates MNI Coordinates Region of interest x y z T k Region of interest x y z T k Region of interest x y z T k SN Resting Self Other L Supplementary motor area -6 15 54 23.61 819 L Middle frontal -30 39 24 21.84 168 R Supplementary motor area 9 9 54 27.46 715 R Anterior middle/ dorsal anterior cingulate 3 18 39 20.13 L Anterior middle/ dorsal anterior cingulate -9 18 33 21.60 447 L Supplementary motor area -6 9 57 25.07 L Anterior insula -39 18 -9 18.38 98 R Anterior middle/dorsal anterior cingulate 9 21 36 19.25 L Middle frontal -33 39 27 14.80 125 R Anterior insula 45 18 -6 15.65 95 R Superior frontal 27 45 24 17.71 133 R Middle frontal 30 45 21 13.51 106 L Superior frontal -27 51 24 12.60 148 L Anterior Insula -33 15 -3 14.63 94 L Anterior Insula -30 24 3 10.45 16 R Superior frontal 27 45 24 11.55 106 R Supplementary motor area 15 9 63 13.11 78 L Supplementary motor area -15 6 63 12.82 42 R Anterior Insula 42 12 -3 12.46 96 Note. p<. 05 FWE corrected, extent threshold k=10 voxels; k = cluster size; L = left, R = right. SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 21 Figure 2 Group-level spatial patterns of the DMN and SN in the three conditions Note. p <.05 FWE corrected, extent threshold k=10 voxels. Seed-based approach MPFC's functional connectivity with overall DMN We found that the MPFC, the selected DMN´s seed region , showed significant FC with the other traditional regions of the DMN, in the three conditions, as shown in table 4, however it appeared to be relatively stronger in the rest condition in comparison with the self and other conditions. rAI’s functional connectivity with overall SN We found that the rAI, the selected SN's seed region, was also functionally connected with the other traditional regions of the SN, in the three conditions, as can be observed in table 5. Additionally, this seed region also exhibited increased FC with the left cerebellum in the three conditions. SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 22 Table 4 MPFC's functional connectivity with overall DMN MNI Coordinates MNI Coordinates MNI Coordinates Seed Connected region x y z T k Connected region x y z T k Connected region x y z T k MPFC Resting Self Other L Frontal medial orbital 0 54 -3 561.28 1559 L Frontal medial orbital 0 54 -3 385.68 1563 L Frontal medial orbital -3 54 -3 330 1528 L Superior frontal -18 39 48 17.13 R Ventral anterior cingulate 6 27 18 17.09 R Ventral anterior cingulate 6 27 18 14.4 L Posterior cingulate -6 -48 30 25.00 469 L Middle frontal -24 30 48 14.57 L Middle frontal -24 27 51 12.8 L Precuneus -3 -60 15 24.53 L Angular/TPJ -39 -66 33 15.46 25 R Precuneus 6 -63 21 17.4 469 L Angular/TPJ -45 -66 33 22.96 25 R Precuneus 9 -51 36 15.29 469 R Posterior cingulate 6 -48 30 17.1 R Angular/TPJ 51 -60 30 20.21 13 R Posterior cingulate 3 -42 21 14.69 L Angular/TPJ -39 -69 33 15.5 25 L Middle cingulate 0 -21 36 17.97 34 L Cuneus -9 -63 24 14.69 R Angular/TPJ 48 -63 33 14.5 13 L Hippocampus -24 -24 -12 16.23 115 R Superior frontal 15 33 51 13.94 40 R Middle cingulate 3 -21 39 12.4 34 L Thalamus -15 -33 3 15.70 R Middle cingulate 3 -21 39 13.32 34 L Middle cingulate 0 -9 36 11.4 R Superior frontal 18 42 45 14.50 40 R Angular/TPJ 48 -63 30 12.78 13 R Thalamus 6 -6 9 11.9 65 R Parahippocampal 30 -27 -12 13.79 42 L Thalamus -6 0 0 12.50 67 L Thalamus -3 -9 9 11.3 R Thalamus 6 -6 9 9.62 67 R Thalamus 6 -6 9 10.38 R Superior frontal 15 33 51 11.5 40 L Parahippocampal -24 -24 -18 10.55 115 R Parahippocampal 27 -18 -18 10.1 42 R Parahippocampal 27 -21 -18 9.01 41 L Parahippocampal -21 -24 -12 8.90 116 Note. p<. 05 FWE corrected, extent threshold k=10 voxels; k=cluster size; L = left, R = right; TPJ = temporoparietal junction. a SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 23 Table 5 Right AI’s functional connectivity with overall SN MNI Coordinates MNI Coordinates MNI Coordinates Seed Connected region x y z T k Connected region x y z T k Connected region x y z T k R AI Resting Self Other R Anterior insula 36 21 3 577.8 101 R Anterior insula 36 18 3 549.27 101 R Anterior insula 36 18 3 589 101 R Anterior middle/ dorsal anterior cingulate 6 18 36 69.26 865 L Anterior insula -33 18 6 69.64 98 L Anterior insula -36 12 6 73.4 98 L Anterior middle/ dorsal anterior cingulate -6 12 39 53.45 R Middle frontal 33 39 27 46.13 142 L Middle frontal -39 45 15 33.6 181 R Supplementary motor area 3 0 60 44.38 R Anterior middle/ dorsal anterior cingulate 6 12 45 36.26 864 R Middle frontal 36 39 27 32.5 142 L Anterior insula -30 21 3 48.76 98 L Supplementary motor area -3 3 51 34.00 L Supplementary motor area -3 3 51 30 855 R Middle frontal 33 42 24 40.39 142 L Middle frontal -33 39 33 32.76 181 R Supplementary motor area 3 0 57 29.3 L Middle frontal -36 42 24 33.37 181 L Cerebellum -30 -54 -30 11.89 27 L Cerebellum -33 -54 -30 11.50 27 L Cerebellum -36 -54 -30 12.71 27 Note. p<. 05 FWE corrected, extent threshold k=10 voxels; k=cluster size; L = left, R = right. SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 30 (2018) in which an increase in the strength of DMN´s intra-network connectivity in task performance compared to resting state had also been reported. In the same line, a recent work by Wang and colleagues (2021) on the structural and functional connectome of the social mentalizing network reported an increase in the FC of areas such as the dorsal MPFC, ventral MPFC, TPJ, and precuneus with the augmented demands of the mentalizing task. Thus, these results confirm the well-known relationship between the DMN, as the mentalizing system in SC, and our ability to infer internal states, either ours or the ones of others (Knyazev et al., 2020). Moreover, during both rest and self conditions, we observed relatively higher connectivity in anterior regions of the DMN, namely in ventral ACC and left SMFG, whereas in the other condition the higher connectivity was observed in posterior regions, namely in PCC/precuneus. This finding is consistent with the evidence for an anterior-posterior dissociation of the DMN, found in previous research (Coutinho et al., 2015b), pointing to a functional specialization within the network, with the anterior portions more involved in self-referential processes and the posterior areas involved in episodic memory and perceptual processing. Similarly, Murray and colleagues (2015) refer to the pregenual ACC as the seed node for a conceptual self network and the PCC/precuneus as the seed for a conceptual other network. In respect to the SN, the network also presented its typical FC pattern across the three conditions. The observed main difference, however, suggested a more limited FC in key nodes, such as the dACC and AI in the other condition compared to rest and self. This suggests that when left to think freely or explicitly told to think about their internal states, subjects tended to recruit to a greater extent the emotional circuits subserved by the SN. Furthermore, this finding aligns with our hypothesis and the wellknown association between the SN and self-referential interoceptive processes (Timmers et al., 2018). Similar evidence was reported by Cheng et al. (2010), in which subjects watched painful situations and had to imagine them from a self, loved-one, and stranger perspective. Although the three perspectives were related to a neural network of pain processing, activation in the AI and ACC showed a gradient decline from the self, to close other, and to the stranger (Cheng et al. 2010). Having characterized the functional architecture of each network, we proceeded to the analysis of the interplay between them. Using a seed-based approach to see how the DMN interacts with the SN, we intended to better understand the integration between cognitive and emotional dimensions of SC both during rest and during the task performance. As hypothesized, our results pointed to an interplay between the two networks in the three conditions. Importantly, both self and other conditions showed a higher FC between the MPFC (the SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 31 selected DMN seed region) and the nodes of the SN - AI and dACC - pointing to increased functional interaction between both networks when the subjects were actively involved in a social task. This suggests greater integration between affective, or bottom-up, and cognitive, or top-down, dimensions during the socio-processing. Likewise, in a review on the types of brain network organization that occurs in the context of SC, Schurz et al. (2021) concluded that increased network integration indicated more effortful and controlled processing. Shine and collaborators (2016) also reported that network integration increased in a theory of mind task compared to passive rest, leading the authors to conclude that in response to task complexity, large-scale brain networks increase their integration as a response to task complexity (Shine & Poldrack, 2018). Interestingly, we only observed FC between the MPFC and cerebellum during task performance, which is in line with the documented role of the cerebellum for SC, supported by results of cerebellar activation during empathy and mentalizing tasks (Jackson et al., 2005; Moriguchi et al., 2007) and by evidence from lesions studies!showing that cerebellar damage results in deficits in theory of mind (Clausi et al., 2019; Gerschcovich et al., 2011). When using the right AI as the seed region, we replicated the coupling between the SN and the DMN across conditions. This is not surprising due to the role of the AI in coordinating the switching between large scale networks, namely the DMN and the central executive network (Menon & Uddin, 2010). Moreover, we observed that the increased connectivity between the SN and the DMN was more evident with posterior nodes of the DMN, namely the lingual/parahippocampal/hippocampus, PCC/precuneus, and MCC. The connection with hippocampal regions during task performance may reflect the retrieval of memories of past experiences (Aminoff et al., 2013; Laurita et al. 2017), needed for this task in which subjects may have evoked specific episodic memories related to the content depicted in the videos. Notably, it was only in the task-dependent conditions that the rAI increased its connectivity with regions such as the angular gyrus/TPJ, which correspond to DMN’s areas involved in the cognitive representation of both self and other´s internal states and self-other distinction (Eddy, 2016; Santiesteban et al., 2012). As suggested by Qin et al. (2020), connectivity between the insula and TPJ could serve the association between internal and external aspects of the self, which could serve as the basis for further co-representation of social information pertaining to both self and other. In a study where subjects observed strangers and close others experiencing painful stimulus, Cheng et al. (2010) found that the closer the relationship between the observer and the target, the greater the right TPJ deactivation and the higher the activation in the AI. According to the authors, this TPJ SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 32 deactivation may reflect the increased self-other blending that characterizes empathic processes towards close others. The same process of inclusion the other in the self may have influenced our results in which the target was an intimate other. This leads us to infer that if we had included another experimental condition in which the target was a distant or non-familiar other, we would find a higher FC with the TPJ and this difference would be more pronounced for the distant other compared to the self or close other condition. Finally, the greater involvement of the DMN in the cognitive route and of the SN in the affective route of SC was confirmed by the results from the correlational analysis between their FC pattern at rest and self-perceived empathic abilities. While the DMN was positively associated with IRIC cognitive scores and negatively associated with affective scores, the SN was negatively associated with cognitive IRIC scores. This adds to previous work of our research team (Oliveira-Silva et al., 2018), in which the superior MPFC, was positively associated with higher scores in the cognitive domain, and negatively associated with higher scores in the affective domain. In summary, this study provided some insight into the configuration of two key social networks across different brain states. Taken together our findings showed that intra and inter-network connectivity increased from resting to task, supporting the need for a higher integration between different social brain areas during the active processing of social information. On the other hand, the focus on the other "s experience seems to have increased the recruitment of posterior areas, with the connectivity within the DMN being higher in posterior nodes such as the PCC/precuneus, and the connectivity within key SN nodes such as the AI being also relatively lower in the other condition. Finally, the AI was more connected with DMN posterior nodes and the recruitment of the cerebellum was more evident in the other. Limitations and future directions The present work used FC methods to describe the relationship between nodes of the DMN and SN. FC methods are based on the correlations between brain regions’ BOLD signal fluctuations over time, and despite its utility and extensive use in the literature, they can be complemented by other approaches. One of those complementary methods is dynamic functional connectivity, which contrarily to FC that is based on the assumption of stationarity, addresses the temporal component (fluctuations) of spontaneous BOLD signals (Cabral et al., 2011; Soares et al., 2016) On the other hand, despite its utility and ability to detect consistent spatiotemporal relationships between different brain regions, they don´t assess the directed influence that one brain area exerts over another. Thus, this can be accomplished through effective connectivity analyses (Friston, 1994) which, SALIENCE AND DEFAULT NETWORK IN SOCIAL COGNITION 33 as showed in previous work (Esménio et al., 2020), considers how the information flows through brain regions of a given network as well as between networks (Friston, 2011). For instance, the knowledge of the information flow between socio-affective and socio-cognitive networks will clarify if they are hierarchically related, with the ability to abstract mental state attributions being dependent on the ability to simulate the other state. The relative homogeneity of our sample in terms of age, relationship duration, and marital functioning may also be seen as a possible limitation of the present work, which restricts the generalization of our findings to similar samples of relatively young and healthy couples. 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