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• W4385742360 abstract "Full text Figures and data Side by side Abstract Editor's evaluation eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract The human brain supports social cognitive functions, including Theory of Mind, empathy, and compassion, through its intrinsic hierarchical organization. However, it remains unclear how the learning and refinement of social skills shapes brain function and structure. We studied if different types of social mental training induce changes in cortical function and microstructure, investigating 332 healthy adults (197 women, 20–55 years) with repeated multimodal neuroimaging and behavioral testing. Our neuroimaging approach examined longitudinal changes in cortical functional gradients and myelin-sensitive T1 relaxometry, two complementary measures of cortical hierarchical organization. We observed marked changes in intrinsic cortical function and microstructure, which varied as a function of social training content. In particular, cortical function and microstructure changed as a result of attention-mindfulness and socio-cognitive training in regions functionally associated with attention and interoception, including insular and parietal cortices. Conversely, socio-affective and socio-cognitive training resulted in differential microstructural changes in regions classically implicated in interoceptive and emotional processing, including insular and orbitofrontal areas, but did not result in functional reorganization. Notably, longitudinal changes in cortical function and microstructure predicted behavioral change in attention, compassion and perspective-taking. Our work demonstrates functional and microstructural plasticity after the training of social-interoceptive functions, and illustrates the bidirectional relationship between brain organisation and human social skills. Editor's evaluation This important work extensively quantifies changes in cortical hierarchical organization induced by different types of social cognitive training. The evidence supporting this is compelling: the authors employ rigorous and complementary multi-modal neuroimaging assessments in a very large sample, measuring longitudinal changes in functional and structural metrics of cortical hierarchical organization. This work has broad applicability to basic neuroscience, illuminating the link between anatomical and functional hierarchies in the brain and social skills, and is also of interest to clinical psychology audiences due to its relevance to interventions such as mindfulness-based therapies. https://doi.org/10.7554/eLife.85188.sa0 Decision letter eLife's review process eLife digest Navigating daily life requires a number of social skills, such as empathy and understanding other people’s thoughts and feelings. Research has found that specific parts of the brain support these abilities in humans. For instance, the brain areas that support compassion are different from the regions involved in understanding other people’s perspective and thoughts. It is unclear how learning and refining social skills alters the brain. Previous studies have shown that learning new motor skills restructures the areas of the brain that regulate movement. Could acquiring and improving social skills have a similar effect? To investigate, Valk et al. trained more than 300 healthy adults in different social skills over the course of three months as part of the ReSource project. The program was designed to enhance abilities in compassion and perspective through mental exercises and working in pairs. Participants were also trained using different approaches to see whether changes to the brain are influenced by how a skill is learnt. The brains of the participants were repeatedly pictured using magnetic resonance imaging (MRI). This revealed that different types of training caused unique changes in specific parts of the brain. For example, teaching mindfulness made parts of the brain less functionally connected, whereas training to understand other people’s thought increased functional connections between various regions. These functional alterations were paralleled by changes in brain structure. They could also predict improvements in social skills which were measured throughout the study using behavioural tests. These findings suggest that training can help to improve social skills even in adults, which may benefit their quality of life through stronger social connections. Better knowledge of how to develop social skills and their biological basis will help to identify people who need support with these interactions and develop new therapies to nurture their abilities. Introduction Humans unique social skills enhance cooperation and survival (Ochsner and Lieberman, 2001; Dunbar, 1998). Social capacities can be divided into multiple sub-components (Singer, 2006; Schurz et al., 2020; Schurz et al., 2021): (i) socio-affective (or emotional-motivational) abilities such as empathy allowing us to share feelings with others, and may give rise to compassion and prosocial motivation (Batson, 2009; Eisenberg and Fabes, 1990; de Vignemont and Singer, 2006); (ii) socio-cognitive abilities gain access to beliefs and intentions of others [also referred to as Theory of Mind (ToM) or mentalizing (Singer, 2006; Frith and Frith, 2006; Saxe and Kanwisher, 2003)]. Finally, interoceptive abilities, attention, and action observation serve as important auxiliary functions of social aptitudes, contributing to self-other distinction and awareness (Tomasello, 1995; Craig, 2009; Kleckner et al., 2017). These capacities combine externally- and internally-oriented cognitive and affective processes and reflect both focused and ongoing thought processes (Chun et al., 2011; Barrett, 2017; Turnbull et al., 2020; Murphy et al., 2019; Sormaz et al., 2018). With increasing progress in task-based functional neuroimaging, we start to have an increasingly precise understanding of brain networks associated with the different processes implicated in social cognition. For example, tasks probing socio-emotional functioning and empathy consistently elicit functional activations in anterior insula, supramarginal gyrus, and midcingulate cortex (Singer, 2006; Singer and Lamm, 2009; Singer et al., 2004), while emotional-motivational processes, such as compassion, implicate insular, and orbitofrontal areas (Lindquist et al., 2012; Singer and Klimecki, 2014). On the other hand, tasks involving socio-cognitive functioning generally activate regions of the human default mode network (DMN), such as medial frontal cortex, temporo-parietal junction, and superior temporal sulcus (Schurz et al., 2020; Saxe and Kanwisher, 2003; Bzdok et al., 2012). Finally, attentional tasks activate inferior parietal and lateral frontal and anterior insular cortices (Trautwein et al., 2016; Corbetta et al., 2008; Corbetta and Shulman, 2002) and interoceptive awareness is linked to anterior insula and cingulate regions (Craig, 2009; Kleckner et al., 2017; Seth and Friston, 2016; Critchley et al., 2003). These findings suggest a potentially dissociable neural basis of different social abilities in the human brain. Despite the progress in the mapping of the functional topography of networks mediating social and interoceptive abilities, the interplay between social behavior and brain organization is less well understood (Paquola et al., 2022). Prior research has shown that cortical function and microstructure follow parallel spatial patterns, notably a sensory-transmodal axis that may support the differentiation of sensory and motor function from higher order cognitive processes, such as social cognition (Valk et al., 2022; Park et al., 2021b; Paquola et al., 2019b; Huntenburg et al., 2017; Goulas et al., 2018). Put differently, a sensory-transmodal framework situates abstract social and interoceptive functions in transmodal anchors, encompassing both heteromodal regions (such as the prefrontal cortex, posterior parietal cortex, lateral temporal cortex, and posterior parahippocampal regions) as well as paralimbic cortices (including orbitofrontal, insular, temporo-polar, cingulate, and parahippocampal regions; Mesulam, 2000). Distant from sensory systems, transmodal cortices take on functions that are only loosely constrained by the immediate environment (Margulies et al., 2016), allowing internal representations to contribute to more abstract, and social cognition and emotion (Paquola et al., 2019b; Huntenburg et al., 2017; Margulies et al., 2016; Huntenburg et al., 2018; Mesulam, 1998; Mesulam, 1994; Salehi et al., 2020; Cole et al., 2013; Beul et al., 2017; Barbas, 2015), thereby enhancing behavioral flexibility (Mesulam, 1998; Murphy et al., 2018). However, despite the presumed link between cortical microstructure and functional processes it may support, whether and how changes in social behavior impact intrinsic function and microstructure it is not known to date. Longitudinal investigations can reveal causal links between behavioral skills and brain organization, for example via targeted mental training studies. A range of prior studies indicated that mental training may alter brain function and gross morphology (Slagter et al., 2007; Hölzel et al., 2011; Lazar et al., 2005; Fox et al., 2016; Fox et al., 2014), but findings do not yet point to a consistent pattern. For example, a randomized controlled trial showed little effect on brain morphology of 8 weeks of mindfulness-based training in healthy adults (Kral et al., 2022). Arguably, sample sizes have been relatively modest and training intervals short. Moreover, few studies have compared different practices or focussed on different social skills, despite different types of mental training likely having unique effects on brain and behavior (Lutz et al., 2021; Klimecki et al., 2014; Singer and Engert, 2019). In a previous study realized in the context of the ReSource project (Singer et al., 2016), our group demonstrated differentiable change in MRI-derived cortical thickness, in support of macrostructural plasticity of the adult brain following the training of social and interoceptive skills (Valk et al., 2017b). As the ReSource project involved a targeted training of attention-mindfulness (Presence training-module, TM), followed by socio-affective (Affect TM) and socio-cognitive/ToM training (Perspective TM) over the course of nine months, this study design can help to dissociate different mental training effects. Whereas Presence aimed at initially stabilizing the mind and nurturing introspective abilities, the Affect and Perspective TMs focussed on nurturing social skills such as empathy, compassion, and perspective taking on self and others. Here, we leverage the ReSource study dataset to assess whether the targeted training of attention-interoception, socio-affective, and socio-cognitive skills can lead to domain-specific reorganization of (i) intrinsic function (as indexed by resting-state fMRI connectivity gradient analysis), and (ii) cortical microstructure as indexed by quantitative T1 relaxometry, probed along the direction of cortical columns (Marques et al., 2010; Paquola et al., 2020; Paquola and Hong, 2023). Such results would be in line with prior observations suggesting coupled change in brain structure and function (Mount and Monje, 2017; de Faria et al., 2021), and would help to gain insights into the association between social skills and models of brain organization. Longitudinal analyses of subjects-specific measures of functional integration and segregation evaluated whether these changes corresponded to corresponding change in intracortical microstructure. We also tested for associations to behavioral change in attention, compassion, and ToM markers using machine learning with cross-validation, to evaluate behavioral relevance at the individual level. Results Embedding of socio-affective and -cognitive functions in cortical brain organization (Fig. 1) Our work examined changes in brain function and microstructure following social and cognitive mental training. We analyzed resting-state functional MRI (fMRI) measures, myelin-sensitive quantitative T1 (qT1) relaxometry, and behavioral data from 332 adults studied in the ReSource Project (Singer et al., 2016). The preregistered trial (https://clinicaltrials.gov/ct2/show/NCT01833104) involved three 3 month long TMs: (i) Presence, targeting interoception and attention, (ii) Affect, targeting empathy and emotion, and (iii) Perspective, targeting ToM. To gain a system-level understanding of brain changes associated with each TM, we took a multi-level approach, combining cortex-wide exploratory analyses of changes in functional and microstructural organization, with an investigation of a-priori defined functional networks hypothesized to be targeted by each TM, behavioral prediction of behaviors implicated in each domain. For a-priori functional localization, we selected meta-analytical functional networks mapping these functions using NeuroSynth (Yarkoni et al., 2011), (Figure 1). To investigate changes in intrinsic functional organization following different types of social and cognitive mental training we focused on changes within a 3D framework of functional axes, explaining in total more than 50% of variance within the functional connectome (Margulies et al., 2016; de Wael et al., 2020; Coifman et al., 2005; Haak and Beckmann, 2020; Bernhardt et al., 2022). These axes differentiate primary from transmodal cortices (sensory/motor versus abstract cognition, principle gradient, G1), and within this axis further differentiation of visual from sensory-motor regions (secondary gradient, G2), and multiple demand and from default networks (tertiary gradient, G3). To synoptically assess changes within this functional framework, we combined the first three gradients into a marker of functional eccentricity, similar to previous work (Park et al., 2021a). Here, regions at either end of the gradient have a high eccentricity, a value based on the average of the three gradients. Following, we investigated gradient-specific effects. Figure 1 Download asset Open asset Study design. (A) Training design of the ReSource study; (B) Training modules; (C) Task-based meta-analytical maps, and a legend of the color-coding of the maps; (D) Functional cortical organization: i. functional connectivity matrix, gradient 1–3, eccentricity metric; ii. task-based network embedding; iii. intracortical microstructure, mean qT1 values as a function of task-based meta-analytical maps and cortical depth and relative values (z-scored per depth-compartment). Gradients of each individual were Procrustes aligned to the mean functional connectome based on the human connectome project sample (Valk et al., 2022; Van Essen et al., 2013), and we calculated region-wise distances to the center of a coordinate system formed by the first three gradients G1, G2, and G3 for each individual [based on the Schaefer 400 parcellation (Schaefer et al., 2018)]. Such a gradient eccentricity measures captures intrinsic functional integration (low eccentricity) vs segregation (high eccentricity) in a single scalar value (Park et al., 2021a). Highest segregation was observed in visual and sensory-motor networks, while ventral attention and limbic networks were closest to the center of the space. Notably, the a-priori networks showed a unique embedding in 3D gradient space (F(5,394) 8.727, P<0.001), with Affect-associated networks being most integrated while and Perspective-networks were most segregated. Studying cortical microstructure, a marker of structural hierarchical organization, we observed patterns of high microstructural integrity (low qT1) in primary areas and low microstructural integrity (high qT1) in transmodal areas, similar to previous work (Paquola et al., 2019a; Burt et al., 2018). Evaluating a-priori network microstructural integrity, we found that compartment 5:12 showed unique microstructural loadings (F(5,394) >5.760, p<0.001), with the emotion meta-analytical network showing lowest microstructural integrity in deep compartments. Mental training-specific change in functional organization (Fig. 2) We first tracked training-related longitudinal changes in functional organization using a holistic and cortex-wide approach through probing the combination of functional gradients 1–3 in functional eccentricity following the different ReSource TMs. Following, we investigated specificity of effects in terms of functional gradient and a-priori functional networks associated with the TMs. In the Resource study, participants were randomly assigned to two training cohorts (TC1, N=80; TC2, N=81), which each underwent a 9-month training consisting of three sequential TMs (i.e., Presence, Perspective, and Affect) and with weekly group sessions and daily exercises, completed via cell-phone and internet platforms (Figure 1, Tables 1–3, Materials and Methods and Supplementary Materials for details). TC1 and TC2 underwent the latter two TMs in different order (TC1: AffectPerspective; TC2 PerspectiveAffect) to serve as active control groups for each other (Figure 1A). Additionally, a matched test-retest control cohort did not undergo any training (RCC, N=90), but was followed with the same neuroimaging and behavioral measures as TC1 and TC2. All participants were measured at the end of each three-month TM (T1, T2, T3) using 3T MRI and behavioral measures that were identical to the baseline (T0) measures. There was furthermore an active control group (TC3; N=81), which completed three months of Affect training only. In our main analyses, we compared TMs against each other focusing on TMs completed by TC1 and TC2, that is Presence (T0→T1, TC1 and TC2), Affect (T1→T2, TC1 and T2→T3, TC2), Perspective T2→T3, TC1 and T1→T2, TC2 and supplementary investigations including also TC3 that only completed a socio-affective training and retest control cohorts. Table 1 Participant inclusion in resting-state analysis and quantitative T1 analysis. Recruited (N, mean age, % female)T0 (N)T1 (N)T2 (N)T3 (N)Total (N=332)TC1 (N=80; 41.3; 58.8)TC2 (N=81; 41.2; 59.3)RCC (N=90; 40.0; 58.9)TC3 (N=81; 40.4; 60.5)2686967656725965596867182576164184556465 Table 2 Reason for missing data across the study duration. MR incidental findings are based on T0 radiological evaluations; participants who did not survive MRI quality control refers to movement and/or artefacts in the T1-weighted MRI; dropout details can be found in Singer et al., 2016; no MRT: due to illness / scheduling issues / discomfort in scanner; other: non-disclosed; functional MRI missing: no complete functional MRI; functional MRI quality:>0.3 mm movement (low quality in volume +surface). Reason for dropout(TC1, TC2, RCC)T0T1T2T3Structural MR incidental findingStructural MRI quality controlDropoutMedical reasonsOtherFunctional MRI missing/QC qT1 missing572141813(5 based on T0)67 (2 based on T0)7 (1 based on T0)10147(5 based on T0)47 (9 based on T01)7 (8 based on T01)7166(5 based on T0)27 (16 based on T012)(15 based on T012)787 Table 3 Reason for missing data across the study duration. MR incidental findings are based on T0 radiological evaluations; participants who did not survive MRI quality control refers to movement and/or artefacts in the T1-weighted MRI; dropout details can be found in Singer et al., 2016; no MRT: due to illness / scheduling issues / discomfort in scanner; other: non-disclosed. Reason for dropout (TC3)T0T1MR incidental findingMRI quality controlDropoutMedical reasonsOtherFunctional MRI missing/QC qT1 missing3001514(3 based on T0)032330 We evaluated how cortical functional gradients would change following mental training using mixed-effects models (Dale et al., 1999). Excluding participants with missing functional or structural data, or excessive movement, the sample included 109 individuals for Presence, 104 individuals for Affect, 96 individuals for Perspective, 168 retest controls and 60 active controls (Affect) with functional and structural change scores. At the whole-cortex level, we observed marked gradient eccentricity changes following Presence and Perspective (Figure 2, descriptive statistics: Supplementary file 1a-e). Presence training resulted in increased eccentricity of bilateral temporal and right superior parietal areas (FDRq <0.05), indicative of increased segregation. Perspective training resulted in decreased eccentricity of right temporal regions, together with left insular cortices (FDRq <0.05). We observed no eccentricity change following Affect training. Post-hoc analysis indicated changes between Presence and Perspective were underlying eccentricity change were most marked in G2 (t=–4.647, p<0.001, d=−0.403), dissociating sensory-motor from visual systems, but not G1 (t=–1.495, p>0.05, d=−0.130) or G3 (t=–0.493, p>0.05, d=−0.043) gradient. Focussing on a-priori networks, in particular attention (t=2.842, p=0.005, d=0.247) and interoception (t=2.765, p=0.006, d=0.240) networks showed alterations in Presence-vs-Perspective, (Table 4, Figure 2 and Figure 2—figure supplement 1). Although effects varied, they were also observed after Global Signal Regression (GSR) control, in TC1 and TC2, and versus RCC (Supplementary file 1f-j). Evaluating gradient-specific alterations per a-priori network we observed a link between Presence versus Affect in the empathy-network along G2 (t=3.215, p<0.002; Supplementary file 1k-m, Figure 2—figure supplements 2–4). Findings were robust when controlling for previously reported cortical thickness change (Valk et al., 2017b), Supplementary file 1n. We did not find evidence for overall effects of training on functional eccentricity relative to RCC (Supplementary file 1o). Table 4 TM-specific changes in eccentricity per a priori networks. Presence (n=109) vs Perspective (n=96)Presence (n=109) vs Affect (n=104)Perspective (n=96)vs Affect (n=104)Attentiont=2.842, p=0.005*, d=0.247t=1.458, p>0.05, d=0.127t=−1.692, p>0.05, d=−0.147Interoceptiont=2.765, p=0.006*, d=0.240t=1.043, p>0.05, d=0.091t=−2.008, p=0.045, d=−0.174Emotiont=0.387, p>0.05, d=0.035t=−0.135, p>0.05, d=−0.011t=−0.552, p>0.05, d=−0.048Empathyt=2.218, p=0.027, d=193t=0.879, p>0.05, d=0.076t=−1.569, p>0.05, d=−0.136Theory of Mindt=1.721, p>0.05, d=0.149t=1.324, p>0.05, d=0.115t=−0.601, p>0.05, d=−0.052 * signifies FDR corrected differences. Figure 2 with 4 supplements see all Download asset Open asset Training-induced changes in cortical functional organization. (A) upper: T-maps of TM-specific changes in functional eccentricity; lower: TM-specific change in functional eccentricity, p<0.01, FDRq <0.05 outlined in black, below: alterations of eccentricity in the FDRq <0.05 regions, right: mean changes in FDRq <0.05 eccentricity regions as a function of G1-G2-G3; (B) A-priori network functional eccentricity change in networks that showed TM-specific change. Overall training effects in microstructure as a function of cortical depth (Fig. 3) Having established alterations in integration and segregation of a-priori networks, we evaluated the neurobiological relevance of these alterations. We investigated changes in cortical microstructure as a function of cortical depth, motivated by the idea that intrinsic functional changes may be anchored in microstructural plasticity that occurs in a depth-varying manner (Paquola et al., 2022). Overall, ReSource training led to decreased qT1 values, i.e. increased myelination, in both TC1 and TC2 relative to RCC over the nine months training time, in all a-priori functional networks in particular in deeper compartment microstructure, whereas RCC showed subtle increases of qT1, suggesting decreased myelination (Figure 3, Supplementary file 1p, Figure 3—figure supplement 1). Studying training-specific effects, we observed marked changes in cortical microstructure following 3-month-long mental training across domains (all FDRq <0.05). Presence showed marked increases in qT1 in posterior areas in superficial depth compartments, and marked decreases in qT1 in prefrontal and occipital regions that showed increased spatial extent as a function of cortical depth. Conversely, Affect resulted in extended decreases in qT1 in mid and deep depth compartments, in particular in bilateral frontal areas extending to parietal lobe, bilateral posterior cingulate, left fusiform gyrus and right insula. Perspective showed largely decreases in qT1 in superficial depths in parietal-temporal, precuneus, and sensory-motor areas, and an increase in qT1 in left prefrontal regions. Patterns were similar when comparing the TMs against each other, highlighting the differentiation between superficial and deep depth-varying changes between Perspective and Affect and medial prefrontal qT1 decrease following Presence relative to Perspective and Affect as well as Affect TC3 and RCC (in particular in case of TC1, Figure 3—figure supplement 2). Figure 3 with 2 supplements see all Download asset Open asset Changes in depth-varying microstructure as a function of TM. (A). Change in cortical microstructure, per TM, red indicates positive change in qT1, blue negative change. FDRq <0.05 findings are outlined in black on top of t-values per parcel; (B) TM specific change in cortical microstructure. Red indicates positive change in qT1, blue negative change. FDRq <0.05 findings are outlined in black in combination with semi-transparent trends (p<0.01). Corresponding changes in functional organization and intra-cortical microstructure (Fig. 4) Having shown alterations in functional and microstructural organization following social mental training, we evaluated corresponding changes in cortical microstructure. A multilevel approach was chosen. First, we evaluated whether the regions observed in functional reorganization in Presence versus Perspective would also show microstructural change. Second, we studied training-specific microstructural alterations in a-priori functional networks. Third, we evaluated the spatial correlation between functional and structural organization as a function of cortical depth. To do so, we sampled qT1 relaxometry values across 12 equidistant intracortical surfaces between the pial and the white matter (Paquola et al., 2019b; Figure 4). Regions with low mean qT1 were located in sensory-motor and visual regions, regions known to have a high myelin content (Dinse et al., 2015; Sanides and Hoffmann, 1969). On the other hand, regions with high mean qT1 and thus low myelin content were located in transmodal areas, as previously shown (Paquola et al., 2020). We then examined how intra-cortical microstructural organization mirrored observed changes in functional eccentricity in clusters showing differential change during Presence vs Perspective. We observed a correspondence (FDRq <0.05) between functional eccentricity and upper layer microstructural compartments (1st: t=3.167 p=0.002, d=0.275; 2nd compartment: t=2.911, p=0.004, d=0.253) in regions showing differences in eccentricity between Presence and Perspective. Following, assessing TM-specific effects in microstructure in a-priori task-based functional networks through comparing all TMs, we found all but the emotion network to show increases in qT1 of Presence versus Affect and Perspective in the upper compartments, extending to deeper compartments when comparing Presence and Affect (FDRq <0.05). Conversely, in deeper compartments, near the GM/WM boundary, we observed decreases of Affect relative to Perspective in interoception and emotion-related networks (descriptive statistics: Supplementary file 1q-u, Figure 4—figure supplement 1, Supplementary file 1v-x). Findings were largely consistent across the different training cohorts, yet weak relative to retest controls (Supplementary file 1y-zl, Figure 4—figure supplement 2). As for the functional change, findings were also observed when controlling for cortical thickness (Supplementary file 1: zm-zo), indicating that microstructural change goes above and beyond previously reported morphological change (Valk et al., 2017b). Exploring correspondence between functional and microstructural change within TMs, rather than by contrasting TMs, we observed a spatial correlation between functional change in eccentricity and G2 in upper and middle compartment microstructure in Presence and overall correspondence with G3 changes, correcting for spatial autocorrelation (pspin <0.05), whereas microstructural alterations in mid- and deeper compartments showed correspondence to eccentricity and G2 in Affect (pspin <0.05). Figure 4 with 2 supplements see all Download asset Open asset Dissociable microstructural alterations following mental training. (A).TM-specific changes in cortical microstructure; qT1 in regions showing eccentricity change (y-axis: depth, x-axis: qT1 change); (B) Network-specific change in cortical microstructure as a function of depth, mean change per TM, pFDR <0.05 have black outline (y-axis: depth, x-axis: qT1 change). The boxes on the right of each plot display the statistics (t-values) of the respective difference between TM, with the contrast color coded as upper minus lower TM (defined by color); (C) Correspondence of functional versus microstructural change; i. Spatial correlation of mean alterations in each TM, black outline indicates pspin <0.05, as a function of cortical depth. Functional eccentricity and intracortical microstructure predict social cognitive performance (Fig. 5) Last, we evaluated whether alterations in cortical microstructure and function following mental training could" @default.
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• W4385742360 title "Decision letter: Functional and microstructural plasticity following social and interoceptive mental training" @default.
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