Intergenerational sustainability is a pressing challenge, which is exacerbated by the fact that the current generation must make sacrifices today to ensure the well-being of future generations. There are large interindividual differences in intergenerational sustainable behavior. However, the neural mechanisms underlying these interindividual differences have remained unexplored. Here, we combined fMRI with a consequential intergenerational sustainability paradigm in a sample of 72 healthy students. Specifically, we analyzed task-dependent functional activity and connectivity during intergenerational sustainable decision-making, focusing on the state-like neurophysiological processes giving rise to behavioral heterogeneity in sustainability. We found that differences in neural communication within and between the mentalizing (TPJ/DMPFC) and cognitive control (ACC/DLPFC) network are related to interindividual differences in intergenerational sustainable behavior. Specifically, the stronger the functional connectivity within and between these networks during decision-making, the more individuals behaved intergenerationally sustainably. Corroborated by mediation analyses, these findings suggest that differences in the engagement of perspective-taking and self-control processes underly interindividual differences in intergenerational sustainable behavior. By answering recent calls for leveraging behavioral and neuroscience for sustainability research, we hope to contribute to interdisciplinary efforts to advance the understanding of interindividual differences in intergenerational sustainability. These challenges include, for example, long-term investments in infrastructure, education, and renewable energy, the reduction of public debt, the provision and maintenance of social insurance systems, and global climate change. Despite widespread awareness and concern regarding these challenges, there is considerable variation in the extent to which individuals behave sustainably5. What mental processes and neural mechanisms drive these interindividual differences in intergenerational behavior, however, has largely remained an open question.Intergenerational sustainability, commonly defined as meeting the needs of the present generation without compromising the ability of future generations to meet their own needs, poses pressing challenges for societies and humanity10. Specifically, neuroscientific methods can provide objective measures that are free from response biases and demand characteristics and allow investigating and distinguishing different decision-making processes driving behavior that are difficult to access by introspection alone. In a recent study, we leveraged neuroscience for examining interindividual differences in intergenerational sustainable behavior11. We found that task-independent (offline) neuroanatomical differences in cortical thickness could act as trait-like neural markers illuminating the sources of behavioral heterogeneity in intergenerational sustainability. Here, we used task-dependent (online) neurophysiological measures of the decision processes during intergenerational sustainable decision-making to identify more proximal mechanisms that give rise to differences in intergenerational sustainability. Specifically, we used fMRI to investigate whether differential patterns of task-dependent functional brain activity and connectivity could explain interindividual differences in intergenerational sustainable behavior.Scholars have increasingly begun to advocate for the integration of neuroscience into sustainability research, as it holds great promise for unlocking a deeper understanding of the complex mental processes and neural mechanisms underlying sustainable decision-making that might not be obtained by behavioral observations or self-reports aloneunidirectionally impact future generations and do not directly benefit or suffer from the delayed consequences of their own actions. This clearly sets intergenerational sustainability dilemmas apart from social dilemmas that occur within a single generation13.The presence of great interindividual variability in sustainable behavior should come as no surprise, considering that intergenerational sustainability poses complex, unique, and challenging dilemmas. These dilemmas force people of the present generation to choose between sacrificing their own benefits to provide benefits for future generations or maximizing their own benefits at the expense of future generations. Importantly, members of the present generation 14. These psychological distances are related to preferential biases in single-generation contexts. In these contexts, people tend to prioritize the benefits of themselves or socially close others rather than socially distant others15, which is known to drive intergroup bias in single-generation social dilemmas16. Moreover, people tend to prefer immediate smaller benefits over later larger benefits, which constitutes temporal discounting in single-generation intertemporal choice tasks17. Yet, the unique interplay of social and temporal dimensions renders intergenerational sustainability dilemmas distinctively more complex than dilemmas only involving a single generation. For example, in sharp contrast to single-generation intertemporal choice tasks, those who forgo immediate benefits  are not the ones who reap the long-term benefits of their behavior  in intergenerational sustainability dilemmas. Thus, the investigation of mental processes and neural mechanisms driving interindividual differences in intergenerational sustainable decision-making might be informed by, but cannot be reduced to, research on single-generation dilemmas. To assess and investigate intergenerational sustainability, research needs to model its unique complexity.Previous work suggests that the challenging nature of intergenerational sustainability dilemmas is rooted in the unique combination of the social and temporal distance between the present and future generationsGennext), the payoff of every participant of the next generation was reduced considerably if the present generation collectively overharvested the pool. In trials affecting the present generation (Genpres), overharvesting reduced the payoff of every participant of the present generation. The difference in extracted points in Gennext minus Genpres served as a measure of interindividual differences in intergenerational sustainable behavior that we labelled extraction score. In this extraction score, values close to zero represent more intergenerational sustainable behavior while higher positive values indicate more intergenerational unsustainable behavior. Thus, this setup allowed us to model the characteristic features and contingencies of real intergenerational sustainable behavior: Participants had to cooperate with anonymous others of the present generation by incurring real costs to benefit other unknown participants of future generations rather than themselves. Additionally, participants of future generations would experience the consequences of present generation participants’ behavior with temporal delay and could not reciprocate .Here we assessed behavior and neural responses during intergenerational sustainable decision-making in a well-controlled laboratory setting. For this purpose, we combined fMRI with an intergenerational sustainability dilemma game, modelling the key features and contingencies of intergenerational behavior, i.e., the social and temporal distance between benefactors and beneficiaries, the temporal delay between actions and consequences, the unidirectionality of interactions, and the absence of reciprocity. In this game, four participants partaking on the same day formed the present generation, whereas four other participants partaking one week later formed the (future) next generation. Participants did not know each other neither within nor across generations. Over several independent trials, each participant could extract points from a common pool shared with the other participants of the present generation. Crucially, overharvesting of the pool either negatively affected the next or the present generation. In trials affecting the next generation  and the temporoparietal junction (TPJ)29. For instance, reduced activity in and connectivity between the DMPFC and TPJ were associated with stronger punishment of norm violating outgroup (vs. ingroup) members in a third-party punishment paradigm30, suggesting that a lack of perspective-taking with outgroup members might drive intergroup bias in these single-generation intergroup situations. Thus, we expected that individuals with greater activity in and connectivity between the TPJ and DMPFC during making decisions affecting the next (vs. present) generation would behave more sustainably.Individuals who engage more in taking the perspective of future others may be better able to cooperate to benefit future generations by bridging the social distance from them. For example, perspective-taking with others is related to cooperation in social dilemmas31. Such cognitive conflicts arise when mutually exclusive goals are simultaneously activated32, as for example when individuals are forced to decide between serving self-interests vs. collective interest, benefitting the ingroup at the expense of the outgroup, or receiving sooner smaller vs. larger later rewards. Thus, cognitive conflicts and their regulation by self-control processes are inherent and common to single-generation social dilemmas, intergroup, and intertemporal choice situations alike. At the neural level, such conflicts and their resolution via self-control are processed in a cognitive control network including the anterior cingulate cortex (ACC) and the dorsolateral prefrontal cortex (DLPFC)34. Regarding the specific functions of these brain regions, evidence suggests that the ACC monitors conflicts based on input it receives from other brain areas and specifies whether and to which extent cognitive control needs to be employed. The ACC then outputs this information to the DLPFC, which implements cognitive control accordingly. In single-generation phenomena related to intergenerational sustainability, greater activity within the cognitive control network during decision-making in social dilemmas, intergroup situations, and intertemporal choice has been associated with more pro-social, less biased and more patient decisions40, whereas disrupting the cognitive control network by inhibitory brain stimulation was found to reduce these decisions43. Based on these findings, we therefore hypothesized that individuals with greater functional activity and connectivity within the cognitive control network and between the mentalizing and the cognitive control network when making decisions affecting the next (vs. present) generation would behave more sustainably.Differences in the processing of cognitive conflicts and the subsequent employment of self-control might be another driver of interindividual variability in intergenerational sustainable behavior. Self-control allows individuals to advance one goal over another goal when these are perceived to be in conflictWe assessed behavioral and brain data of 77 healthy students of the University of Bern. Five participants were excluded because they failed the comprehension check (see game-specific questions). No participant had to be excluded because of movement artifacts, anomalies in the brain data or technical problems. The final sample consisted of 72 participants . The study was conducted according to the principles expressed in the Declaration of Helsinki and was approved by the ethics committee of the canton of Bern (no. 2020–00302). Participants signed informed written consent prior to the participation in the study.11. Please take note that both the structural and functional studies were conducted in parallel, operating independently from one another. The conclusions drawn from the structural study did not inform the hypotheses or analyses undertaken in the functional study.The present study is part of a larger project investigating brain anatomical and functional correlates of interindividual differences in intergenerational sustainable decision-making and behavior. Here, we focused on task-dependent functional brain activity and connectivity to shed light on the mental processes and neural mechanisms driving interindividual differences in intergenerational sustainable decision-making. Results of a neural trait approach study investigating the anatomical sources of interindividual differences in intergenerational sustainable behavior are reported elsewhereParticipants showed up for one session in which their behavioral and brain data was acquired. Outside of the scanner, participants first read the instructions for the intergenerational sustainability dilemma game, which they then played inside the scanner while undergoing functional MRI. Directly after game completion, participants answered game-specific questions and the comprehension check. Next, participants’ structural MRI was acquired. At the end of the session, participants received their fixed show-up fee of CHF 40. Two weeks after the session, participants received a link to an online questionnaire  and their additional payment, which depended on their own and others’ behavior (see below).44, focusing on the consequences that the behavior of the present generation entails for a future generation. Please note that the same paradigm was used and described in our previous study11. To model the succession of different generations separated by a temporal delay, four participants who completed their session on the same day formed the present generation, while four other participants who would partake about 7 days later constituted the next generation. Like in the seminal work by Hauser and colleagues44 and ensuing studies49, participants were explained in the instructions that the game included a sequence of “groups” separated by a temporal gap and that participants’ behaviors affected the payoff of the “next group” or “present group”. Because the game modeled key features of intergenerational sustainability , the “next group” can be considered as a proxy for a future generation49. By truthfully and transparently communicating all rules of the game to participants, we followed standard principles for the application of behavioral economic games.We aimed at assessing intergenerational sustainable decision-making and behavior independently of any specific sustainability context as, e.g., environmental or climate behavior. Accordingly, we designed a game inspired by the seminal study of Hauser and colleaguesGen) and refer to its two conditions as Genpres for trials affecting the present generation and as Gennext for trials affecting the next generation. Note that Genpres trials served as within-subject control condition for behavioral and brain measures in Gennext trials, which were the main focus of interest. Accordingly, behavioral and brain measures in Gennext trials were analyzed relative to corresponding measures in Genpres trials using difference values .In each of 16 independent trials, participants could extract between 0 and 20 points (in increments of 2 points) from a pool shared with the other three participants of the present generation. Each point was worth 1 CHF. Extraction of points took place under two conditions, which were equally distributed over the 16 trials in a pseudo-randomized order. In eight trials, participants of the present generation were informed that if they collectively extracted more than 40 points, every participant’s payoff of the present generation was reduced by 80% for that trial. In the other eight trials, participants were informed that if the present generation’s collective extraction exceeded 40 points, the payoff of every participant of the next generation would be reduced by 80% in that trial, while the payoffs of the participants of the present generation were not affected. Thus, trials differed in whether the present or the next generation’s payoff was affected if the present generation exceed the threshold of 40 points. Accordingly, we named the experimentally manipulated factor Affected Generation . Then, participants were presented with the decision screen. In the top half of the screen, they saw which generation (present vs. next) would be affected by the present generation’s decision (word frame: “affected group: present” or “affected group: next”) and they were reminded of the collective extraction threshold of 40 points and of the payoff reduction consequences if the threshold was exceeded. After a delay of 5 s, the bottom half of the decision screen was revealed, in which participants saw the question “How many points would you like to extract?”. To give their answer, participants were presented with a horizontal scale ranging from 0 to 20 (in increments of 2) beneath the question. Participants could input their decision by using two navigation buttons and a confirmation button. Navigation consisted of moving a red dot indicating the currently selected option  to the desired scale point. A trial ended when participants confirmed their decision . The intergenerational sustainability dilemma game was programmed in z-tree, which is a software for social interaction experimentsAfter all participants of the present generation had completed their sessions, two trials were selected randomly to be paid out . Participants were then given feedback on their generation’s collective behavior and its consequences for the present and next generation. Two weeks later, participants received the variable amount they earned in the game .Gennext–Genpres). Thus, higher positive values indicated that participants extracted more points if the next compared to the present generation was affected by their decisions. That is, higher positive values indexed more unsustainable behavior towards the next generation . Lower values around zero indicated that participants extracted an equal number of points if the next or the present generation was affected. That is, lower values indexed more sustainable behavior towards the next generation . Negative values indicated that participants extracted less points if the next compared to the present generation was affected. Note that this extraction score served as the main behavioral variable of interest in all subsequent analyses.To index interindividual differences in intergenerational sustainable behavior, we created an extraction score see Fig. A for eac11. In trials affecting the next generation, each of the four participants of the present generation could extract up to 10 points without risking to collectively extract more than 40 points, which would reduce the payoff of the next generation. Thus, 10 points represent a reasonable individual sustainability threshold. Therefore, we categorized participants as sustainable if their median extraction in trials affecting the next generation was lower or equal to 10 points and as unsustainable otherwise. Please note that this procedure is not the same as a median split but a categorization based on the a priori defined sustainability threshold. As visualized in Fig. Genpres vs. Genpres), which facilitated understanding these difference values and their associations. Note, however, that all primary statistical inferences are derived from regression analyses using the full variance of the extraction score. If additional statistical inferences based on the behavioral types are reported, these are of secondary nature and are only intended to ease the understanding of regression findings.To disentangle and better understand the difference values in the extraction score, we categorized participants into behavioral sustainability types by following the same rationale as described in our previous study11. We asked participants to indicate their agreement to specific statements on a scale from 1  to 11 (“completely agree”) directly after game completion. In a first block, participants were presented with the statements that, in Gennext trials, (1) putting themselves in the shoes of members of the next generation and (2) putting themselves in the shoes of members of the present generation influenced their decision. These two statements aimed at assessing participants’ engagement in perspective-taking processes during Gennext trials. Additionally, participants indicated their agreement to the statement that, in Gennext trials, (1) they were tempted to extract more than 10 points and that (2) they tried to resist this temptation. These two statements were designed to reflect that behavior resulting from (failed) self-control processes involves (1) a desire conflicting with a higher-order goal (a temptation) and (2) a (lack of) effort to control this desire (effort to resist the temptation)52. In a second block, participants answered the same statements as in the first block but now concerning Genpres trials. However, they were not asked to indicate the extent to which they took the perspective of members of the next generation because this statement was not sensible in Genpres trials.Our hypotheses focused on perspective-taking and self-control as potential drivers of interindividual differences in intergenerational sustainable behavior. To assess whether participants indeed were engaged in these socio-cognitive processes during the intergenerational sustainability game, we formulated game-specific questions tapping into perspective-taking and self-control. The same questions were used and described in our previous studyGennext trials by taking the difference between perspective-taking with members of the next generation (Target of Perspective-Taking: TPnext) minus perspective-taking with members of the present generation (TPpres). To quantify participants’ differential engagement in self-control, we calculated two difference scores. We (1) took the difference between participants’ temptation in Gennext minus Genpres trials (Δ temptation) and we (2) took the difference between participants’ effort to resist the temptation in Gennext minus Genpres trials (Δ resisttemptation). In statistical analyses (see mediation results), we focused on Δ resisttemptation while entering Δ temptation as a covariate. Because we statistically adjusted for Δ temptation, we considered effects regarding Δ resisttemptation as representing effects concerning differential engagement in self-control52.We calculated participants’ differential engagement in perspective-taking in As a comprehension check, participants had to indicate the average number of points each member of the present generation could extract without reducing the payoff of the next generation. Hence, this question allowed us to ensure that participants did not accidentally behave unsustainably while believing they were behaving sustainably .53 online after the experimental session. They rated how important 16 values were for them as leading principles in life . The SVS is divided into four subscales, which assess altruistic, egoistic, hedonic, and biospheric values. These values have been argued to play crucial roles in pro-environmental53 and intergenerational behavior13. Thus, we tested whether interindividual differences in intergenerational sustainable behavior were associated with differences in these values by regressing the extraction score on the four SVS subscales in a multiple regression.Participants answered the Schwartz Values Scale (SVS)All MRI data were acquired on a Siemens MAGNETOM Prisma 3 Tesla whole-body scanner using a 64-channel head coil. The functional session started off with a localizer scan followed by the intergenerational sustainability game. The game was projected onto a screen that the subjects viewed through an angled mirror mounted to the head coil. Subjects made their responses on a three-button response box in their right hand. While subjects were playing the game, we acquired gradient echo T2*-weighted echoplanar images (EPIs) with blood oxygenation level dependent (BOLD) contrast , field of view: 235 × 235 × 135 mm, slice thickness: 2.5 mm, no gap, repetition time: 1300 ms, echo time: 30 ms, flip angle 80°). Volumes were acquired in axial orientation at a 15° tilt to the anterior commissure–posterior commissure line. After the functional session, T1-weighted 3D-modified driven equilibrium Fourier transformation (MDEFT) images were acquired from each subject .https://www.fil.ion.ucl.ac.uk/spm/software/spm12/) implemented in Matlab (Version R2020b) was used for preprocessing and statistical analyses. All functional images were realigned and unwarped to the mean EPI image to correct for movement artefacts and susceptibility distortions. We then corrected for time of slice acquisition within a repetition time (reference time: 640 ms), taking into account the parallel acquisition sequence. Realigned and slice time corrected images were then normalized to stereotactic space (3 × 3 × 3 mm3) corresponding to the Montreal Neurological Institute (MNI) with parameters estimated from the co-registered structural image using the segmentation algorithm. Finally, images were smoothed using an 8-mm full-width-at-half-maximum Gaussian kernel.The statistical parametric mapping software  and (2) decisions in trials affecting the present generation (Genpres). Each of these decisions were modeled with durations from the respective onset of the decision screens until the decisions were individually confirmed via button press . Note that a first-level model with additional regressors separately modeling the motor response led to highly similar and statistically undistinguishable findings for the decision phase (which in this case was modelled until the first button press). Please also note that a first-level model with a parametric modulator of extraction behavior is not feasible due to high consistency in the subjects’ decisions . As nuisance regressors, the six motion parameters produced during realignment were included as additional regressors in the SPM analysis to account for residual effects of scan-to-scan motion.The statistical analyses of the fMRI data were also performed in SPM12. We modeled each participants’ BOLD response with a general linear model (GLM) that was estimated using a standard hemodynamic response function and a high-pass filter of 128 Hz, as well as a correction for intrinsic autocorrelations. To increase signal to noise ratio, we minimized global intensity changes by scaling each image to the grand mean. The GLM contained two regressors of interest as boxcar functions: (1) decisions in trials affecting the next generation  on the interindividual differences in extraction score (Gennext–Genpres), i.e., we tested whether differences in functional activity were associated with interindividual differences in intergenerational sustainable behavior.Based on these first-level GLM estimates, we computed the following single-subject contrasts of regression coefficients (beta estimates) for the decision phase: 55. For this purpose, first-level SPM design matrices of each subject (as previously described) and the fully preprocessed functional and anatomical images  were first imported in the CONN toolbox. The seed areas used for functional connectivity analyses were defined as a 5 mm sphere around the peaks identified in other analyses (see Results section for details). Furthermore, an additional denoising process56 recommended for functional connectivity analysis was applied to eliminate confounds of white matter, CSF, subject motion and effects of the task . This procedure allows to remove the temporal timeseries of each confound from functional images and to apply a band-pass filter (0.01 Hz < f < 0.10 Hz) to the residual timeseries. Adding regressors accounting for task effects in this preprocessing step allowed preventing that the main effects of the task drove the estimation of the functional connectivity. First-level functional connectivity for each subject and condition  was computed using weighted bivariate regression coefficients between the seed timeseries  and timeseries from all other voxels in the brain. These first-level condition-specific connectivity estimates were then taken to second-level random effects analyses, in which we regressed the functional connectivity differences between the two conditions (Gennext > Genpres) on the interindividual differences in the extraction score (Gennext–Genpres), i.e., we tested whether differences in functional connectivity between the seed areas  and other areas/voxels in the brain were associated with interindividual differences in intergenerational sustainable behavior.Task-dependent and seed-based functional connectivity was analyzed with the SPM-based connectivity toolbox CONN (version 20b)57. For the definition of the DMPFC and TPJ, we used a meta-analysis on social cognition29 to define peaks in the left TPJ , the right TPJ , and the DMPFC , which consisted of the average coordinates of areas that had consistently been found activated in perspective-taking tasks . Then, we created 20 mm spheres centered on these coordinates by using the WFU Pickatlas toolbox.We looked for functional activity and connectivity effects as a function of intergenerational sustainable behavior across the whole brain as well as across a priori defined regions of interest (see Introduction section) involved in perspective-taking (DMPFC and TPJ) and self-control (ACC and DLPFC). For this purpose, we created a mask consisting of the bilateral ACC, bilateral middle frontal gyrus , the DMPFC and bilateral TPJ. For the definition of the MFG and ACC, we used the automated anatomical labelling atlas as provided in the WFU Pickatlas toolboxp < 0.05 across the whole brain (whole-brain FDR-corrected) or across the small volume mask defined above . For cluster inference, we used a cluster-defining threshold of p < 0.001. For significant activity and connectivity findings , we extracted the contrast estimates (Gennext > Genpres) of the corresponding clusters (thresholded at p < 0.001 or p < 0.005) and used these contrast estimates for creating scatter plots as well as for mediation analyses (see below). Furthermore, we also extracted the activity and connectivity estimates in the significant clusters (again thresholded at p < 0.001 or 0.005) separately for the two conditions  and plotted these values in bar plots, broken down for the two behavioral types . These post-hoc visualizations  using the disentangled activity and connectivity values  helped to better understand what drives the observed effects in the regression analyses. However, we would like to emphasize that the primary statistical inferences are derived from the regression analyses.We considered findings significant if they survived false discovery rate (FDR) correction on peak- or cluster-level at r and r2 for effect sizes by using R’s stats package’s functions lm and cor.test. For secondary analyses, we conducted two-way mixed between-within-subjects analyses of variance (ANOVAs) in R by using the package afex (version 1.2–1). We used Behavioral Type (unsustainable vs. sustainable) as between-subject factor and Affected Generation (Genpres vs. Gennext) or Target of Perspective-Taking in Gennext (TPpres vs. TPnext) as within-subject factors. We used R’s stats package’s function t.test for two-sample t-tests for comparisons of levels of between-subjects factors and paired t-tests for comparisons of levels of within-subjects factors. We considered results significant if p < 0.05 (two-sided). For effect sizes, we reported  η2 as measures of explained variance.For primary analyses, we conducted linear regression analyses and reported Pearson correlation coefficients 58, which is available online (http://processmacro.org/download.html). We modeled ordinary least squares regression path analyses and estimated direct and indirect effects in  mediation analyses with one or two mediating variables. For instance, we investigated whether effects of interindividual differences in functional connectivity (independent variable) on interindividual differences in the extraction score (dependent variable) were mediated by differential engagement in perspective-taking and self-control processes . To test whether the indirect effects through the mediator(s) were statistically significant, we used 5′000 bootstrap samples to generate 95% bootstrap confidence intervals (95%-CIboot) for the indirect effect .To conduct mediation analyses, we used the PROCESS R code (version 4.3)Gennext) compared to trials affecting the present generation (Genpres).The histogram of participants’ extraction scores in Fig. SD = 0.46 ± 1.54) and 36 unsustainable participants (mean extraction score ± SD = 6.70 ± 3.28). Importantly, sustainable and unsustainable participants only differed in their behavior in Gennext but not in Genpres trials, indicating that unsustainable (vs. sustainable) participants’ greater extraction scores were mainly driven by higher extraction behavior in trials affecting the next generation  = −3.11, p = 0.003, ΔR2 = 0.12). None of the other three values was predictive of intergenerational sustainable behavior . Importantly, however, our functional activity and connectivity results (see below) hold when including altruistic values as covariate of no interest , indicating that these neural mechanisms uniquely explained variance in intergenerational sustainable behavior over and above participants’ altruistic values.We additionally tested whether altruistic, egoistic, hedonic, or biospheric values assessed by the SVS were associated with intergenerational sustainable behavior. Note that because one participant did not answer the online questionnaire, analyses regarding SVS values were based on a sample of 71 participants. A multiple regression of the extraction score on these values revealed that the more individuals endorsed altruistic values, the more sustainably they behaved towards the next generation (standardized regression coefficient p < 0.05) that interindividual differences in functional activity and the extraction score were significantly associated in a hypothesized area of the brain, namely the left TPJ . No additional findings emerged by applying a small-volume FWE- or FDR-cluster or -peak correction for bilateral MFG (which the DLPFC is part of), ACC, TPJ, and DMPFC. Contrary to expectations, however, greater left TPJ activity (Gennext > Genpres) was associated with higher extraction scores, that is the higher participants’ left TPJ activity was in trials affecting the next (relative to the present) generation, the more they behaved unsustainably towards the next generation  separately for Gennext and Genpres trials and plotted these extracted values broken down for the two behavioral sustainability types .We found  and of the present (TPpres) generation affected their decisions in Gennext trials (see Methods for details). We conducted a two-way mixed ANOVA of this rated engagement in perspective-taking in Gennext trials on the Target of Perspective-Taking in Gennext (TPpres vs. TPnext) and Behavioral Type (unsustainable vs. sustainable). This analysis showed that the behavioral types did not differ in their overall engagement in taking the perspective of others in trials affecting the next generation  = 3.03, p = 0.086, ηp2 = 0.042), i.e. both types showed similarly strong perspective-taking in trials affecting the next generation. Importantly, however, the behavioral types considerably differed in whose perspective they took in trials affecting the next generation  = 37.11, p < 0.001, ηp2 = 0.346, see Fig. Based on the TPJ’s known function in perspective-taking processes, these results might suggest that in activity or overall engagement in perspective-taking. They differed considerably in whose perspective they took. Thus, we wondered whether the TPJ’s functional connectivity with other areas of the brain would reveal a differential pattern that helps to explain the interindividual differences in sustainable behavior and perspective-taking.In sum, we found that functional activity in TPJ was associated with interindividual differences in intergenerational sustainable behavior. However, in trials affecting the next generation, more sustainable and less sustainable participants did not differ in TPJ p < 0.05) that the left TPJ showed increased functional connectivity (Gennext > Genpres) with the DMPFC  between these areas, the more sustainably a participant behaved towards the next generation as indexed by extraction score values near zero  in the significant clusters separately for the two conditions and plotted these values, broken down for the two behavioral types. As can be seen in the bar plots in Fig. Connectivity analyses seeded in the left TPJ  revealed a distinctive connectivity pattern of the left TPJ with four other areas of the brain. More precisely, we found  might demonstrate a condition-specific connectivity pattern with the DLPFC as a function of sustainable behavior. Connectivity analyses seeded in the dorsal ACC revealed (whole-brain FDR-cluster corrected at p < 0.05) an increased functional connectivity (Gennext > Genpres) of the dorsal ACC with an area of the left  DLPFC  between the dorsal ACC and left DLPFC, the more sustainably participants behaved towards the next generation as indexed by extraction score values near zero  in the significant clusters separately for the two conditions and plotted these values, broken down for the two behavioral types. As can be seen in the bar plot in Fig. No other areas in the brain showed a functional connectivity pattern with the left TPJ as a function of sustainable behavior, also not if we apply small-volume corrections for our hypothesized regions of interests. In this regard, it is interesting to note that there seems to be no such functional connectivity pattern between the left TPJ and dorsolateral areas of the prefrontal cortex, as hypothesized. However, as outlined in the introduction, the dorsal ACC and dorsolateral areas of the prefrontal cortex often act together to solve a decision conflict, i.e., the dorsal ACC monitors and signals conflicts and recruits the DLPFC to solve themOur findings revealed that the functional connectivity between key areas involved in perspective-taking (TPJ-DMPFC connectivity) and self-control (ACC-DLPFC connectivity) seem to play an important role in intergenerational sustainability. Thus, in a final set of mediation analyses we tested whether the functional connectivity within these networks indeed affected intergenerational sustainability by influencing social-cognitive and self-control related processes.TPnext) and of the present (TPpres) generation affected their decisions in trials affecting the next generation (see Methods section for details). As illustrated in Fig. Gennext trials . Hence, higher positive values indicated that participants more strongly engaged in taking the perspective of others of the next generation, whereas lower negative values indicated that participants more strongly engaged in taking the perspective of others of the present generation, and values around zero represented that participants engaged in taking the perspective of others of both generations in a balanced way. We ran a mediation analysis to test whether the observed differential engagement in perspective-taking mediated the impact of TPJ-DMPFC connectivity on intergenerational sustainable behavior (measured with the extraction score). We found  predicted more next-generation oriented perspective-taking, which in turn was associated with increased intergenerational sustainable behavior (lower extraction scores). Importantly, all critical paths .Participants indicated to what extent taking the perspective of others of the next . Based on these ratings, we again calculated difference scores (Gennext–Genpres). Hence, higher positive values in differential effort to resist temptation indicated that participants more strongly tried to resist the temptation in Gennext trials, whereas lower negative values indicated that participants more strongly tried to resist the temptation in Genpres trials, and values near zero represented equal efforts to resist temptations irrespective of which generation was affected. In fact, sustainable participants reported an equal (and high) effort to resist temptation in both conditions (Gennext and Genpres), whereas unsustainable participants reported a significantly lower efforts to resist temptation in Gennext (vs. Genpres) trials  predicted higher efforts to resist temptation in trials affecting the next (vs. present) generation, which in turn was associated with increased intergenerational sustainable behavior (lower extraction scores). Importantly, all critical paths . Please note that mediation results hold if efforts to resist temptation only in trials affecting the next generation is used as mediator  and if the mediation is run without differential temptation as covariate . Modeling the critical contingencies of intergenerational sustainability, overharvesting of the pool considerably reduced either the payoff of the next (Gennext) or the present generation . The difference in extracted points in Gennext minus Genpres (labelled extraction score) served as a measure of interindividual differences in intergenerational sustainable behavior. Results showed that differences in the extraction score were associated with differences in activity and connectivity within the mentalizing network , connectivity between the mentalizing and cognitive control network (TPJ-ACC connectivity), and connectivity within the cognitive control network (ACC-DLPFC connectivity).What mental processes and neural mechanisms drive interindividual differences in intergenerational sustainable behavior? Here, we assessed neural responses during decision-making in a consequential intergenerational sustainability dilemma game, in which successive groups of participants  could extract points from a common pool under two experimental conditions  trials was associated with less sustainable behavior. Importantly, however, a closer inspection revealed that this association was driven by unsustainable (vs. sustainable) participants’ reduced TPJ activity in Genpres trials (control condition), whereas no difference in TPJ activity occurred in Gennext trials. This aligns with the finding that unsustainable and sustainable participants did not differ in overall engagement in reported perspective-taking in Gennext trials. However, they differed considerably in whose perspective they took . Unsustainable participants’ perspective-taking was more present-generation oriented, whereas sustainable participants’ perspective-taking was more balanced or next-generation oriented. Yet, these behaviorally relevant interindividual variability in differential engagement in perspective-taking (present- vs. next-generation oriented) seemed not to be encoded in the local activity pattern of the TPJ. Taking the perspective of others is a difficult task, which presumably becomes even more challenging if the targets are unknown, future strangers. Thus, such intergenerational perspective-taking might require a more elaborate communication between multiple nodes of the mentalizing network.The TPJ, a core node of the mentalizing network, is involved in social cognition, including perspective-taking, theory of mind, and self-other distinctionGennext (vs. Genpres) trials was associated with more sustainable behavior and that this effect was mediated by more next-generation oriented perspective-taking. As core nodes of the mentalizing network, the TPJ and DMPFC are known to be tightly interconnected, both structurally and functionally70. Differences in structural and functional TPJ-DMPFC connectivity have been found to drive interindividual differences in perspective-taking related social behaviors in single-generation contexts, including intergroup situations, trust games, and third-party punishment paradigms72. The present findings extend the importance of TPJ-DMPFC connectivity for perspective-taking in single-generation contexts to intergenerational behavior. Based on the known functions of the mentalizing network and on our mediation analysis, we therefore interpret increased TPJ-DMPFC functional connectivity as indexing more elaborate communication within the mentalizing network, enabling individuals to better engage in taking the perspective of future others. This increased intergenerational mentalizing, i.e., thinking about the needs and mental states of others in the future, might activate the goal not to curtail the outcomes of future others, which might ultimately motivate sustainable behavior. Once activated, this goal likely conflicts with the desire to maximize benefits for oneself in the present, a characteristic feature of intergenerational sustainability dilemmas21. Such desire-goal conflicts may manifest in temptations74, which need to be monitored and overcome to behave sustainably. Thus, the question arises: Which neural mechanisms could potentially account for why certain individuals manage to effectively navigate these conflicts, resisting temptations and engaging in sustainable behavior, while others do not?In support of this idea, we found that greater TPJ-DMPFC connectivity in Gennext (vs. Genpres) trials. The ACC and DLPFC are thought to constitute a cognitive control network, in which the ACC monitors conflicts based on inputs it receives from diverse brain areas and sends control signals to the DLPFC, where self-control processes are implemented accordingly78. Functioning of the ACC and DLPFC is known to be crucially involved in a wide range of single-generation contexts requiring self-control, including intertemporal choice, intergroup situations, and social dilemmas84. The TPJ is one of the brain regions providing the ACC with inputs for conflict monitoring through known structural and functional interconnections86. Thus, greater TPJ-ACC connectivity in Gennext (vs. Genpres) trials might suggest heightened communication between the mentalizing and cognitive control network, possibly indexing a more elaborate monitoring and processing of potential conflicts arising from the trade-off between benefitting oneself or future others. Moreover, increased ACC-DLPFC connectivity in Gennext (vs. Genpres) trials might represent greater communication within the cognitive control network, enabling a more intricate engagement in self-control processes  needed to overcome selfish, unsustainable temptations. This interpretation is further substantiated by our finding that the effect of greater ACC-DLPFC connectivity in Gennext (vs. Genpres) trials on more sustainable behavior was mediated by increased reported engagement in self-control  in trials affecting the next (vs. present) generation.We found that more sustainable behavior was associated with increased TPJ‑ACC and ACC‑DLPFC connectivity in 89 and cognitive control95 play important roles in sustainable behavior. Here, we complement and extend this research by assessing neural responses during intergenerational decision-making and providing first evidence that task-dependent neural mechanisms related to perspective-taking and self-control explain interindividual differences in intergenerational sustainability.Cumulatively, these findings integrate into a picture in which differences in the neural communication within and between the mentalizing and cognitive control network drive interindividual differences in intergenerational sustainable behavior. Based on these networks’ known functions and supported by our single mediator and multiple serial mediator analyses, our results speak for a central role of perspective-taking and self-control processes during intergenerational sustainable decision-making. This resonates with and synthesizes theories and behavioral, non-neuroscientific studies suggesting that perspective-taking96, and the HC is known to play a crucial role in prospective thinking98. Thus, these results suggest that differences in processes involving empathy and prospective thinking might be additional drivers of interindividual differences in intergenerational sustainable behavior , which also aligns with research showing the importance of these processes in single-generation intergroup situations102 and sustainable behavior103. Future research focusing on these and other additional potential processes could deepen our understanding of the neural mechanisms driving heterogeneity in intergenerational sustainable behavior.We would like to emphasize that differences in other processes than the ones discussed thus far might also contribute to behavioral heterogeneity in intergenerational sustainability. In fact, we found, beyond the scope of our hypotheses, that greater functional connectivity between the TPJ and anterior insula (aINS) and between the TPJ and the hippocampus (HC) was associated with more sustainable behavior . Together, these results suggest that trait-like structural and state-like functional differences in the same brain regions related to perspective-taking and self-control drive interindividual differences in intergenerational sustainable behavior. This might be interpreted as evidence that both, the general capacity for as well as actual engagement in perspective-taking and self-control processes during decision-making explain interindividual differences in intergenerational sustainability.Our results fit in and substantially extend the few existing neuroscientific studies on intergenerational sustainability. In a recent neural trait study using the same behavioral paradigm as the one deployed here, we found that sustainable participants were marked by greater cortical thickness of the DMPFC and left DLPFC compared to unsustainable participants, and that these effects were mediated by increased next-generation oriented perspective-taking and self-control, respectively49 found that inhibiting the right DLPFC by means of continuous theta-burst transcranial magnetic stimulation (TMS) did not alter behavior in an intergenerational sustainability dilemma game very similar to the one used here. As a potential explanation for this missing effect, the authors discussed that, maybe, not the right, but the left DLPFC is causally involved in self-control related intergenerational sustainable behavior, given evidence that inhibition of the left, but not the right, DLPFC reduces self-control in the context of single-generation intertemporal choice42. In support of this line of thought, we found that functional connectivity between the ACC and the left DLPFC was associated with individual differences in intergenerational sustainable behavior. Second, Langenbach and colleagues48 showed that applying high-definition transcranial direct current stimulation over the TPJ causally enhanced sustainable behavior in the same intergenerational task as in the previous TMS study. At first, this might suggest that local TPJ activity causally induces intergenerational mentalizing giving rise to intergenerational sustainable behavior. However, we find that local activity of a single node of the mentalizing network falls short of explaining behaviorally relevant differences in future-generation oriented perspective-taking. Importantly, brain stimulation techniques are known to alter brain function not only locally but also in distributed networks107, and transcranial magnetic and direct current stimulation of the TPJ has been found to alter TPJ-DMPFC and TPJ-ACC functional connectivity109. Thus, one might speculate that the TPJ stimulation effect reported by Langenbach and colleagues48 might not (solely) be due to the enhancement of local TPJ activity but to increased functional connectivity of the TPJ with other nodes of the mentalizing and cognitive control network. Future studies combining brain stimulation and imaging techniques in sustainability research could enhance our understanding of the neural networks causally involved in intergenerational sustainable behavior.The present study might also shed new light on results from two recent brain stimulation studies on intergenerational sustainable behavior. First, Langenbach and colleagues44 and has since been applied in various behavioral studies47. Similar to these studies, our paradigm consisted of successive groups that were separated by a temporal gap and extracted resources from a common pool, whose overharvesting affected the payoff of the next or present group. Crucially, this paradigm modelled important aspects of intergenerational sustainability dilemmas. These aspects included the social and temporal distance between benefactors and beneficiaries, the temporal delay between actions and consequences, the unidirectional nature of the interactions, and the absence of reciprocity. As argued previously49, incorporating these features allows to consider the “next group” as a valid proxy for a “future generation”, enabling the paradigm to reasonably capture intergenerational contingencies within the confines of a well-controlled laboratory environment. Nevertheless, such paradigms optimized for laboratory settings necessarily remain approximations of real-world intergenerational behaviors. Future studies developing practical solutions for investigating behaviors between real generations could advance sustainability research.We recognize certain limitations of our study that we recommend considering and addressing in future research. In designing our behavioral paradigm, we aimed at capturing the complexity of real intergenerational sustainable behavior. However, mimicking intergenerational behavior between real generations in a controlled setting is extremely challenging, if not practically impossible. To overcome this limitation, researchers have successfully designed paradigms approximating the key features and contingencies of intergenerational behavior. This approach was first introduced in seminal work by Hauser and colleaguesThe present study deliberately focused on the interplay of social and temporal dimensions distinctively characterizing intergenerational sustainable behavior. When viewed in isolation, these dimensions also constitute components of some single-generation dilemmas . It is a different question whether and how behavior and neural processes in these single-generation dilemmas relate to intergenerational sustainability. Future research could investigate such potential relationships by using different designs optimized for these questions. For instance, future studies could employ full factorial designs crossing different levels of social and temporal dimensions, shedding light on the specificity of neural underpinnings of intergenerational sustainability dilemmas compared to single-generation dilemmas.We acknowledge that our functional neuroimaging findings do not definitively distinguish between a capacity-based interpretation and a motivational-based interpretation. This limitation is inherent to many neuroimaging studies and highlights the complexity of interpreting neural activation and connectivity patterns. Our findings demonstrate which specific brain regions are more active or functionally connected when participants make intergenerationally sustainable decisions compared to unsustainable decisions. However, these findings alone do not definitively answer the question of whether unsustainable participants are incapable or unwilling (or both) to behave in an intergenerationally sustainable manner.Our connectivity findings consistently reflect a similar pattern across the reported regions, prompting consideration of the potential influence of a broader network connectivity effect. While the selectivity of our connectivity findings  mitigate the plausibility of such an effect, we recognize that a complete exclusion is difficult. Addressing this uncertainty will require future neuroimaging studies dedicated to exploring intergenerational sustainability.110. Importantly, we view our work as contributing to basic research, and we therefore do not claim that our study has direct policy relevance. The challenge of intergenerational sustainability cannot be solved by neuroscience alone. However, neuroscience can uniquely contribute to the transdisciplinary efforts to advance sustainability research by providing exclusive access to mental processes and neural mechanisms giving rise to intergenerational sustainable behavior and its interindividual differences.In conclusion, the present study identified differences in task-dependent functional activity and connectivity within and between brain networks engaged in perspective-taking and self-control processes as drivers of interindividual differences in intergenerational sustainable behavior. By combining a consequential behavioral task with the assessment of objective neural responses during decision-making, the study answers intensifying calls for measuring actual  behavior and leveraging neuroscience for sustainability researchSupplementary Information.


The incidence of diagnosed massive pulmonary embolism presenting to the EmergencyDepartment is between 3% and 4.5% and it is associated with high mortality ifnot intervened timely. Cardiopulmonary arrest in this subset of patients carriesa very poor prognosis, and various treating pathways have been applied withmodest rate of success. Systemic thrombolysis is an established first line oftreatment, but surgeons are often involved in the decision-making because of theimproving surgical pulmonary embolectomy outcomes. Treating teams can be perplexed about the bestpossible management strategy in crunch time situations of haemodynamic instabilityprogressing to cardiac arrest. Improving surgical outcomes of the index surgery aswell as need for mechanical support devices in these unstable patients bring cardiacsurgeons in the middle of decision making,3. There are numerousunanswered questions in this field when patient is referred with ongoingcardiopulmonary resuscitation (CPR), and there is still no consensus about thestandard pathway to route these patients. Here we present the surgeon’s perspective on this subjectwith the background of our own prior and continuing experience in thisfield,6.Approximately 20% of the patients presenting with pulmonary artery embolus can havemassive pulmonary embolism (MPE), and it has a very high mortality rate in the firsthour of presentation if it is not intervened promptlyA. Do surgeons have any role in the management of MPE?B. If at all, then when to intervene and how to manage thesesick cases?C. Role of venoarterial extracorporeal membrane oxygenation(VA-ECMO).D. Surgical pulmonary embolectomy (SPE) vs.catheter-based thrombolysis.E. How far is too far? Where to stop?A. Clots in the pulmonary arteries do not allow proper forward flow inthe distal pulmonary circulation and eventually reduce left ventricular preload,which may lead to the loss of cardiac output (. The right ventricle (RV) is thinner compared tothe left ventricle, and that is the reason why RV is more sensitive to the acuteafterload changes, and SPE is the swiftest modality to start “reverse remodeling ofthe RV dysfunction” by removing distal obstruction , and the reason behind these better outcomes can be contributed toour early operating policy.Kalra et al. have reported anoverall hospital mortality rate of 26.3%, while in our study, it was 8.54%. But evenin our study, once the patient required preoperative CPR, then mortality rateescalated to 58.34%, and again it reinforces the fact about earlyintervention. Fivesurvivors in our study had cardiopulmonary arrest in the operating room, and CPR wasperformed prior to the sternotomy. Other seven patients went in cardiopulmonaryarrest outside of operating room and could not be saved. Another unique complicationseen among patients who required preoperative CPR was massive pulmonary haemorrhagethrough endotracheal tube (3/12 patients). Potential aetiology might be thepulmonary infarction caused by dislodgement of the clots from main pulmonaryarteries into the distal circulation during cardiac massage  patients withMPE is another debatable field, where there are no perfect answers. Multiple factorsplay important role in the decision making and outcome, like duration ofcardiopulmonary arrest, effectiveness of CPR, return of spontaneous cardiacactivity, associated primary pathology, and the time before reaching to theEmergency Department. Early riskstratification is the key for good outcomes and, therefore, it is important to havequick tests, like serum lactate level, to triage high-risk cases and interveneearly,11. Our protocol is to insert arterial pressure lineduring CPR to assess cardiac output and effectiveness of the cardiac compressions.Patients presented with prolonged, unwitnessed, and ineffective resuscitation areruled out for any surgical intervention and managed with systemic thrombolysis only.On contrary to previous reports, recent literature is suggesting improvement in thesurvival with the use of systemic thrombolysis during the resuscitation, and thesefindings further escalate the complexity in the decision making.C. Although the results of VA-ECMO in MPE with cardiogenic shock areencouraging, overall outcomes of VA-ECMO during CPR are still poor, with reportedin-hospital mortality of around 75%,13. Around 4-5% ofthe patients with MPE also have clots in the right atrium, RV (clots in transit),and acutely create instability by obliterating inflow and outflow valve. Duringongoing CPR, establishing prompt CPB or VA-ECMO flows are paramount, but theseintracardiac clots might get sucked in the venous cannula and cause distension ofthe heart by poor venous drainage. Various groups are recognising the importance ofearly haemodynamic stabilization by instituting VA-ECMO and managing patients eitherwith thrombolysis or emergency SPE. VA-ECMO insertion gives time for the patient transfer to theoperating rooms with sustaining sufficient cardiac output. But “only VA-ECMO”support group has 2-3-fold higher mortality rate compared to the patients in whomVA-ECMO was followed by SPE,15.D. Systemic thrombolysis and catheter-based therapies (CBT) continue tobe the class I indication in the management of MPE, while SPE is ofered in selectedunstable cases, but thorough review of the contemporary literature gives interestinginsight on this subject. Arecently published systemic review of 1,650 patients, who either underwent CBT or SPE , presented similar in-hospital mortality ifCBT or SPE was performed before cardiopulmonary arrest, but the advantages of SPEwas complete clearance of the clots and more defnitive treatment in the long-termfollow-up. Comparingoutcomes among these treatment modalities are not straightforward as SPE cases aresicker (21.4% had prior CPR) and have higher clot burden compared to CBT patients.Keeling et al. have reported amulticentre series and again reinforced that if SPE is performed timely, then goodearly outcomes can be achieved with low in-hospital mortality, but if the patient ishaving ongoing CPR, then mortality rate is 32.1%. Lee et al. have reported thatoverall use of thrombolysis and SPE in the management of pulmonary embolism (PE) isaround 1% and 0.4%, respectively, and both modalities give similar earlyoutcomes. They havereported that patients in the SPE group had lower associated risks of early stroke,reintervention, and late recurrent PE compared with those in the thrombolysis group,and they have advocated SPE as it reduces future recurrence of PE.E. It is mandatory to make notes of the duration of the haemodynamicinstability with serum markers’ levels , failureof the systemic thrombolysis, and duration of CPR before deciding the treatmentmodality. These are extremely relevant variables to decide whether to use“minimalistic approach” (VA-ECMO) or to perform index SPE surgery, with or withoutVA-ECMO support. Duration of the CPR makes big impact on the outcomes and that isthe reason why in patients with OOHCA or in-hospital cardiac arrest where downtimeis prolonged (30 minutes), surgeons have to critically analyse the situation andtake consensual decision involving different treating teams. George et al. have reported in theirretrospective analysis that three groups where ECMO consistently gives poor outcomesare patients with malignancy, cardiac arrest prior to initiation of ECMO, andpatients with serum lactate > 6 mmol/l. Although there are no randomized trialsto support, ECMO-facilitated resuscitation has been increasingly used to assistearly return of perfusion and support further resuscitation in order to mitigate themulti-organ dysfunction. But ECMO-assisted CPR should be used judiciously and mostoften attempted in cases with potentially reversible clinical conditions with leastcomorbidities.All available evidence supports prompt “risk stratification” and triage for thedefnite treatment in patients with MPE. But, with the paucity of large randomizedclinical trials, management of MPE with cardiopulmonary arrest is still an opendebate with various choices. SPE can be a good option in these unstable patients,with centrally located massive clot with right ventricular strain and dilatation onechocardiography. Surgical outcomes are very poor in patients with OOHCA andin-hospital cardiac arrest (outside of operating room) and should be deferred in thefavour of systemic thrombolysis with or without VA-ECMO support.


Islet transplantation (IT) offers the potential to restore euglycemia for patients with type 1 diabetes mellitus (T1DM). Despite improvements in islet isolation techniques and immunosuppressive regimes, outcomes remain suboptimal with UK five-year graft survivals (5YGS) of 55% and most patients still requiring exogenous insulin after multiple islet infusions. Native islets have a significant non-endocrine component with dense extra-cellular matrix (ECM), important for islet development, cell survival and function. Collagenase isolation necessarily disrupts this complex islet microenvironment, leaving islets devoid of a supporting framework and increasing vulnerability of transplanted islets. Following portal venous transplantation, a liver injury response is potentially induced, which typically results in inflammation and ECM deposition from liver specific myofibroblasts. The impact of this response may have important impact on islet survival and function. A fibroblast response and ECM deposition at the kidney capsule and eye chamber alongside other implantation sites have been shown to be beneficial for survival and function. Investigating the implantation site microenvironment and the interactions of transplanted islets with ECM proteins may reveal therapeutic interventions to improve IT and stem-cell derived beta-cell therapy. A patient with T1DM administers 65,000 injections and checks their blood glucose levels 80,000 times during their lifetime . WorldwiBeta-cell replacement strategies seek to restore insulin production capabilities thereby reducing exogenous insulin requirements. Pancreas transplant (PT) outcomes have steadily improved , but devIT is employed to reduce the burden of T1DM and is indicated in the UK for patients with T1DM suffering from episodes of hypoglycaemic unawareness or extremely labile glucose control . In the For UK clinical use, islet preparations must achieve a minimum yield of 250,000 Islet Equivalents (IEQ), with purity of over 50% endocrine tissue, determined by dithizone (DTZ) staining and 70% viability. In addition, for a first transplant in the UK, the yield must be sufficient to achieved 5000 IEQ/Kg for the designated recipient or 10000 IEQ/Kg if to be used for a supplementary islet transplant . UK reciPurity in islet preparations is considered a marker of successful islet isolation and predictive of graft success. However, there is evidence to suggest that long term functionality is not determined by endocrine content alone. It has been shown that long term glycaemic control is superior in recipients with islet infusions with <50% purity compared to >50% with similar islet viability and total islet mass . In thesDespite the promise of IT, graft longevity remains elusive. Analysis of outcomes of a Swiss-French islet network demonstrated that insulin independence persisted in only 1 of 21 patients at 10 years follow-up, whilst 73% remained free of severe hypoglycaemic episodes . AnotherThe great progress in IT has only accentuated the lack of donor islets and the need to understand why islet loss continues post-transplantation. The mechanism for islet loss cannot be solely attributed to ongoing autoimmunity or allogeneity as loss follows transplantation for other forms of pancreatic disease and in syngeneic models of islet transplantation –42. LossNon-endocrine cell types are important to islet function; predominantly endothelial cells which are a component of the network of intra-islet microvasculature which is five times denser than the exocrine pancreas alongside dendritic cells and nerve fibres . In humaNative islet ECM producing cells are not well characterised, but evidence is emerging for the role of islet stellate cells (ISCs). Similar, but distinct from pancreatic stellate cell population, which are implicated in pancreatic fibrosis and exocrine disease, they possess a quiescent and activated state in which they are thought responsible for excessive ECM deposition and implicated in Type 2 Diabetes Mellitus (T2DM) , 52. HowThe extra-cellular matrix (ECM) is a complex environment, composed of multiple proteins, glycoproteins and proteoglycans. These networks, which are found across tissue types, can bind with cell surface receptors to influence cell differentiation, survival and function. This can be achieved via integrin receptors and through mechano-sensing of transmitted loads through frequency and intensity of cell-ECM interactions. The cytoplasmic tails of integrin receptors bind with the intra-cellular actin cytoskeleton and activate pathways involved with cell survival and function and allow bi-directional communication with the local micro-environment .1 and integrin β1 subunits reduce cell adhesion and migration of foetal and adult human islets in vitro  are also thought to impact survival and function. FN is a key component of developing islets and activates integrin αve cells . Whilst ve cells . For exave cells . FGFs acve cells . Of noteve cells . Appraisve cells .in vitro, leading to cell death (in vitro and increased islet index (IEQ/islet number) positively correlates with stimulated C-peptide 3 months following simultaneous islet-kidney transplant  is required to facilitate successful islet isolation . Consequll death . Interesansplant . Hypoxiaansplant .To achieve function after IT, revascularisation is a necessary requirement for successful islet engraftment. New intra-islet vasculature is derived from both recipient and donor endothelium , 72. AngMorphological analysis of autopsy specimens in long term functioning islet transplants (>10 years) with positive serum C-peptide has revealed extensive capillary networks positively staining for CD31, with comparable vascular density, size of vessel and distribution to those seen on histological analysis of biopsy tissue from native pancreas . ElsewheTo achieve successful islet isolation, destruction of the supporting framework of extra-cellular matrix vasculature is required Figure 1in vitro insulin dynamics, with superior glucose stimulated insulin secretion and reduced apoptosis in extended culture. Transcriptomic analysis demonstrated increased expression of regulatory pathways associated with cell adhesion, ECM organisation and responses to external stimuli when compared to culture in suspension (Native pancreatic ECM is composed of both interstitial matrix and basement membrane, which is predominantly laminin, fibronectin alongside collagen IV and V . Islet ispension .Avenues to improve engraftment include increasing selectivity of collagenase digestion, promoting neovascularisation through manipulation of islets, co-culture with ECM components, non-endocrine cells and promoting islet-ECM interaction post-transplant should be investigated to improve cellular therapies , 85.The liver has many metabolic, digestive, and endocrine functions with complex micro-anatomical arrangement. The hepatic parenchyma receives dual blood supply from the portal venous system and hepatic arterial tree. Histologically, structures are arranged surrounding portal triads of portal venous sinusoids, arterial capillaries and bile duct branches with corresponding central veins which form the vascular outflow tract.Following IT via the portal vein in man and primate models, islets will be spread amongst the liver with the majority sited within the venous lumen or closely related to it whilst only a minority become embedded within hepatic parenchyma , 76. WheIntra-portal IT initiates the instant blood mediated immune response and triggers a response from the hepatic parenchyma . EmbolicHSC activation in progressive fibrosis is detrimental to tissue function, their presence and matrix deposition surrounding intra-portally transplanted islets may influence islet survival and function. This local microfibrosis may interfere with diffusion of insulin, increasing distances to capillary perfusion and paracrine activity and after islet isolation, which destroys native islet ECM, this post-transplant matrix deposition may result in abnormal matrix-cell signalling, which may contribute to impaired beta-cell function and survival. Of note, streptozotocin induced hyerglycaemic mice fed a high fat diet to induce steatohepatitis, have significantly lower rates of euglycaemia after intra-portal IT with significantly higher non-fasting capillary glucose readings compared to controls .It may be that in some scenarios, HSC induced matrix deposition helps to restore the islet-ECM signalling necessary for function. The nature of this consequent post-transplant matrix deposition needs to be investigated, as when isolated HSCs are co-transplanted with islets under the mouse kidney capsule, improved glycaemic control is demonstrated through increased duration of graft function and superior islet dynamics assessed with intra-peritoneal glucose tolerance testing. Histological analysis reveals HSCs are sited surrounding islet clusters in this setting, which was also associated with increased islet insulin expression on immunofluorescent staining compared to solitary islet transplant controls . In micein vitro with a combination of insulin and 15 mM glucose for 24 hours (in vitro; culture with IGF-1 also promoted collagen-1 accumulation in media (Transplanted islets may also influence their microenvironment through paracrine activity. Local hepatic histological changes have been noted in an early cohort of IT recipients and focal peri-portal steatosis has been demonstrated by magnetic resonance imaging and on histology , 95. Pre24 hours . In addiin media . This deAlternative sites for IT away from the hostile hepatic parenchyma have been studied, with few being used outside of clinical trials with portal venous infusion continuing to be the imperfect gold standard , 98. InvThe complexity of the relationship between the local tissue response and transplanted islets persists away from the hepatic parenchyma. When human and mouse islets are infused into the anterior eye chamber of syngeneic or immunodeficient mice, the islet BM which is destroyed during isolation is progressively reconstituted . Islets Subcutaneous tissue responses have been recruited against foreign bodies to create a collagen reaction surrounding an angiogram catheter, upon which islets can be placed. Islets can then be placed into the void created when the device is retrieved. This technique improves glycaemic control and graft survival in mouse syngeneic and allogeneic transplant models and when human islets are transplanted into an immunodeficient mouse model. Islet grafts are surrounded by a collagen capsule with evidence of neovascularisation within the graft . This prMore recently, immature pancreatic endocrine progenitors within an encapsulation device have been sited within the subcutaneous space with some success. Retrieved grafts have stained positive for insulin producing cells and recipients have had detectable levels of serum C-peptide. Histological analysis of explanted devices has demonstrated an influx of fibroblasts stained for alpha-smooth muscle actin, although quantitative analysis of this infiltrate relative to function has not been established; in areas of dense fibroblast infiltrate, there was minimal engraftment , 18. TheIT has the potential to provide insulin independence and reduction in mortality and morbidity induced by T1DM. But despite improvements in islet isolation techniques and immunosuppressive regimes, outcomes remain suboptimal. To improve duration and quality of glycaemic control after IT, it is important to examine the post-transplant microenvironment to understand the two-way relationship between transplanted islet cells and the hepatic parenchyma via paracrine and direct cell-to-cell and cell-ECM signalling. This will allow targeted improvements in islet isolation techniques and shed light on mechanisms for manipulation of the implantation microenvironment. This is an important area for improvements in both IT and stem-cell derived beta-cell therapies, for the benefit of patients living with DM.The article concept was produced by DTD, HAK, DvD, REJ, and KPH. The initial version was produced by DTD. All authors contributed to the article and approved the submitted version.


To understand how pharmacological interventions can exert their powerful effects on brain function, we need to understand how they engage the brain’s rich neurotransmitter landscape. Here, we bridge microscale molecular chemoarchitecture and pharmacologically induced macroscale functional reorganization, by relating the regional distribution of 19 neurotransmitter receptors and transporters obtained from positron emission tomography, and the regional changes in functional magnetic resonance imaging connectivity induced by 10 different mind-altering drugs: propofol, sevoflurane, ketamine, lysergic acid diethylamide (LSD), psilocybin, N,N-Dimethyltryptamine (DMT), ayahuasca, 3,4-methylenedioxymethamphetamine (MDMA), modafinil, and methylphenidate. Our results reveal a many-to-many mapping between psychoactive drugs’ effects on brain function and multiple neurotransmitter systems. The effects of both anesthetics and psychedelics on brain function are organized along hierarchical gradients of brain structure and function. Last, we show that regional co-susceptibility to pharmacological interventions recapitulates co-susceptibility to disorder-induced structural alterations. Collectively, these results highlight rich statistical patterns relating molecular chemoarchitecture and drug-induced reorganization of the brain’s functional architecture. Anaesthetics and psychedelics systematically engage diverse neurotransmitter systems to perturb consciousness. Understanding how the brain orchestrates complex signals across spatial and temporal scales to support cognition and consciousness is a fundamental challenge of contemporary neuroscience. By inducing profound but reversible alterations of brain function, psychoactive compounds provide neuroscientists with the means to manipulate the brain without requiring surgical intervention. In combination with noninvasive brain imaging techniques such as functional magnetic resonance imaging (fMRI), acute pharmacological interventions have therefore emerged as a prominent tool for causal investigation of the relationship between brain and cognitive function in healthy humans  receptors, with additional attenuation of glutamatergic synaptic signaling [mediated by both AMPA and N-methyl-d-aspartate (NMDA) receptors] . To do so, we leveraged two unique datasets: (i) a recently assembled collection of in vivo maps of regional expression from 19 different receptors and transporters, obtained from positron emission tomography (PET) scanning of more than 1200 total individuals, providing the most detailed information about neuromodulators and their spatial distribution available to date , in terms of their effects of FC. There have been other studies looking at the relationships between brain changes induced by one or few psychoactive drugs, and one or few neurotransmitter systems  and sevoflurane; the cognitive enhancers modafinil and methylphenidate; ketamine, acting as both atypical psychedelic (at subanesthetic doses) and as a dissociative anesthetic . For sevA), histamine (H3), cannabinoid (CB1), and opioid (MOR)   (23). BoReceptors and transporters shape the way that neurons respond to neurotransmission and neuromodulatory influences. In turn, psychoactive drugs exert their effects (primarily) by acting on neurotransmitters and neuromodulators. Therefore, we reasoned that everything else being equal, regions that express similar patterns of receptors and transporters should exhibit similar patterns of susceptibility to drug-induced functional reorganization.To address this question, we computed matrices of pharmacological co-susceptibility and neurotransmitter coexpression between pairs of regions, by correlating respectively the regional patterns of drug-induced FC changes  and the regional patterns of neurotransmitter expression . To account for spatial autocorrelation in molecular and FC attributes, we regressed out from both matrices the exponential trend with Euclidean distance .This analysis indicated the presence of two statistically significant latent variables  relating pharmacologically induced functional reorganization to neurotransmitter profiles, together accounting for nearly 85% of covariance. Significance was assessed against autocorrelation-preserving spin-based null models, embodying the null hypothesis that drug effects and neurotransmitters are spatially correlated with each other purely because of inherent spatial autocorrelation . The firFor each latent variable, each brain region is associated with a neurotransmitter and drug score. In turn, neurotransmitter (drug) loadings are defined as the correlation between the PLS-derived score pattern and each neurotransmitter’s density of expression  across brain regions. Taking into account the first latent variable (PLS1), drug loadings showed a distinction of pharmacological effects into two groups, with all anesthetics (except ketamine) on one side, and both ketamine datasets dominating the opposite side, together with LSD, ayahuasca, and modafinil . NeurotrPertaining to the second latent variable (PLS2), neurotransmitter loadings mainly identified a monoamine-rich end (with dopamine and serotonin), although 5-HT1b occupied the opposite end. However, the drug loadings were less clearly discernible, with modafinil alone at one end, and a mixture of propofol, psychedelics, and both ketamine datasets at the other end. Both neurotransmitter and drug scores markedly separated dorsal and ventral aspects of the brain for this second latent variable .Neurotransmitter and drug scores  provide information about the regional distribution of neurotransmitter-drug associations. Neurotransmitters and drugs whose regional distribution correlates positively with the score pattern covary with one another in the positively scored regions, and vice versa for negatively scored regions.PLS1 scores correspond to the main axis of covariance between neurotransmitter expression and pharmacologically induced functional reorganization. For both drug and receptor scores, we observed that their regional distribution reflected the brain’s organization into intrinsic resting-state networks (RSNs)  and 4. IPspin = 0.056) (P > 0.05 against spin-based null models). As an alternative avenue to characterize this second, nonhierarchical cortical pattern, we quantified its spatial similarity with 123 brain maps pertaining to cognitive and psychological processes, obtained from NeuroSynth. Significant FDR-corrected correlations (assessed against spin-based null models) were observed for both PLS2 drug and neurotransmitter scores, in particular pertaining to emotion-related terms  on the positive end—consistent with the involvement of limbic and salience networks in PLS2 (fig. S4).We observed significant correlations (assessed against spin-based null models and corrected for multiple comparisons) between each cortical hierarchy and both neurotransmitter and drug scores for PLS1  . The scoBy comparing the score pattern to multiple cortical hierarchies, we demonstrate that the relationship between psychoactive drug effects and neurotransmitter receptor densities fits into the broader sensory-association hierarchy of the cortex  . As alreLast, we wondered if the functional co-susceptibility of different regions to transient pharmacological perturbations may provide a functional proxy for their co-susceptibility to structural perturbations resulting from different neurological, neurodevelopmental, and psychiatric disorders. To this end, we combined 11 spatial maps of cortical thickness abnormalities made available by the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium (P < 0.001 after regressing out the effect of Euclidean distance)  . This reHaving ascertained that susceptibility to pharmacological and pathological alterations is positively correlated, we next sought to identify a low-dimensional representation of this joint co-susceptibility. Whereas the aim of PLS analysis is to enable a many-to-many mapping between variables , we also repeated our analysis after implementing three different strategies for further controlling the potential confounding effects of motion. First, we regressed the FC change at each region observed in each dataset, against the standardized difference in mean framewise displacement observed for that dataset, as a way of further controlling for any differences in motion across datasets that may be confounding our analysis. The resulting PLS1 also primarily separated anesthetics from other psychoactive substances and neurotransmitter receptors versus transporters, as observed in our main analysis, with transporters covarying with cognitive enhancers and most psychedelics in primary sensory and motor regions, and receptors primarily covarying with traditional anesthetics in transmodal association cortices (fig. S12). PLS1 scores also remained significantly aligned with the cortical hierarchy after motion regression (fig. S13). Second, we replicated our results with low-motion subjects only. We show that analogous hierarchically organized mappings between different drug types and receptors versus transporters can be observed when any subjects with mean framewise displacement greater than 0.3 in either baseline or drug scan are excluded from the analysis (fig. S14). Third, we further show that our main results are replicated if we only include datasets for which the difference in mean framewise displacement between baseline and drug scans is not statistically significant (table S2), namely, the Cambridge propofol dataset, the Cambridge propofol recovery dataset, the psychedelic ketamine dataset, modafinil, methylphenidate, ayahuasca, MDMA, and psilocybin . Again, we find that our results replicate what we observed in our main analysis, with a principal latent variable organized along the unimodal-transmodal axis separating receptors and transporters (fig. S15). The convergence of these three distinct approaches to motion correction in replicating the results of our main analysis demonstrates that our results are robust to the potential confounding effects of motion and remain stable even under conservative strategies for motion correction.To further ensure the robustness of our main results, we also replicated them using different cortical parcellations: the anatomically defined Lausanne-114 (fig. S16) . Such multifaceted results can emerge from numerous biological mechanisms. Not only are many of the drugs that we considered known to have varied molecular targets, beyond the primary ones through which they exert their effects; in addition, even when a drug has low affinity for a given receptor when considered in isolation, it may still indirectly engage the corresponding neurotransmitter system through complex downstream effects, which abound in the brain. In addition, the highest alignment with GABAA receptor expression was found for the lowest dose of anesthetics—possibly suggesting that, as the dose increases, secondary and downstream targets may begin to exert more prominent effects, thereby contributing to a more diffuse mapping onto the full set of neurotransmitters. As a data-driven technique designed to identify many-to-many mappings rather than focusing on individual ones . Last, another feature differentiating unimodal from transmodal cortices is that the latter have higher neuron and synapse density . In other words, drugs whose effects on FC are less selective for higher versus lower ends of the cortical hierarchy may simply be less likely to exert mind-altering effects of the kind that we chose to focus on in this work.More broadly, we found that pairs of regions that are more similar in terms of their susceptibility to pharmacologically induced FC changes are also more similar in their susceptibility to cortical alterations associated with a variety of neuropsychiatric disorders. This observation suggests a broader pattern of both pharmacological (acute) and neuroanatomical (chronic) susceptibility across regions. We speculate that this joint susceptibility may be related to regional relevance for cognitive function: We found that this joint vulnerability can be understood in terms of two multimodal principal gradients of variation over the cortex: one of them resembling the principal gradient of FC  and the other anchored in the dorsolateral prefrontal cortex at one end, and ventromedial and temporal cortex at the other. The first, hierarchically organized gradient of association between disorder co-susceptibility and co-susceptibility to pharmacologically induced functional reorganization sheds light on recent evidence, which indicated that the principal gradient of neurotransmitter expression is particularly relevant for predicting a wide spectrum of disease-specific cortical morphology , reminiscent of the evidence that ketamine can have “psychoto-mimetic” effects , the present work did not seek to provide a direct link between drugs, their molecular targets in the brain, and their behavioral effects. Experimental interventions will be required to conclusively demonstrate causal involvement and elucidate the underlying neurobiological pathways from receptors to behavior. However, we emphasize that our results generate empirically testable hypotheses about which neurotransmitters may be involved with the macroscale effects of different drugs on brain function. These hypotheses may be tested experimentally, but also in silico: Whole-brain computational modeling is becoming increasingly prominent as a tool to investigate the causal mechanisms that drive brain activity and organization in healthy and pathological conditions  into orthogonal sets of latent variables with maximum covariance, which are linear combinations of the original data  represent the degree to which each neurotransmitter contributes to the latent variable and demonstrate the extracted association between neurotransmitter density and drug-induced FC changes (neurotransmitter weights). The right singular vectors  represent the degree to which the FC changes contribute to the same latent variable (term weights). Positively weighed neurotransmitters covary with positively weighed drug-induced changes, and negatively weighed neurotransmitters covary with negatively weighed drug-induced changes.This is achieved by Scores at each brain region for each latent variable can be computed by projecting the original data onto the singular vector weights. Positively scored brain regions are regions that demonstrate the covariance between the prevalence of positively weighted neurotransmitters and positively weighted drug-induced effects (and vice versa for negatively scored brain regions). Loadings for each variable were computed as Pearson’s correlation between each individual variable’s regional distribution (neurotransmitter density and drug-induced FC changes) and the PLS analysis–derived neurotransmitter score pattern. Squaring the loading (a correlation) equals the percentage of variance shared between an original variable and the PLS analysis–derived latent variable. Variables with high absolute loadings are highly correlated to the score pattern, indicating a large amount of shared variance between the individual variable and the latent variable. We confirmed that PLS1 explained the largest amount of variance by testing across a range of PLS components (between 1 and 15) and quantifying the relative variance explained by each component.z-scored separately before being combined for the PLS analysis, due to the well-documented differences in PET radioligand uptake between cortical and subcortical structures (For each subject at each condition (drug and baseline), the denoised regional blood oxygen level–dependent (BOLD) signals from fMRI  were parcellated into 100 cortical regions according to the local-global functional parcellation of Schaefer and colleagues . We alsoA), histamine (H3), cannabinoid (CB1), and opioid (MOR). Volumetric PET images were registered to the MNI-ICBM 152 nonlinear 2009  template, averaged across participants within each study, then parcellated, and receptors/transporters with more than one mean image of the same tracer  were combined using a weighted average. See the dedicated article by Hansen et al. , referred to as “AHBA PC1”  derived from multimodal neuroimaging. We considered the anatomical gradient of intracortical myelination obtained from T1w/T2w MRI ratio   segmentations, are fully validated and allow maximal uniformity and comparability across sites. Together, more than 17,000 patients were scanned across the 13 disorders, against almost 22,000 controls. The values for each map are z-scored effect sizes (Cohen’s d) of cortical thickness in patient populations versus healthy controls. Imaging and processing protocols can be found at http://enigma.ini.usc.edu/protocols/.Patterns of cortical thickness were collected for the available 11 neurological, neurodevelopmental, and psychiatric disorders from the ENIGMA consortium and the For every brain region, we constructed an 11-element vector of disorder abnormality, where each element represents a disorder’s cortical abnormality at the region. For every pair of brain regions, we correlated the abnormality vectors to quantify how similarly two brain regions are affected across disorders. This results in a region-by-region matrix of “disorder co-susceptibility”  (2R) of the multiple linear regression model (p − 1 submodels for a model with p being the predictors). Total dominance is defined as the average of the relative increase in 2R when adding a single predictor of interest to a submodel, across all 2p − 1 submodels. The sum of the dominance of all input variables is equal to the total adjusted 2R of the complete model, from which a percentage of relative importance is obtained by partitioning the total effect size accounted for by each predictor. Therefore, unlike other methods of assessing predictor importance, such as methods based on regression coefficients or univariate correlations, dominance analysis accounts for predictor-predictor interactions and is interpretable.When considering multiple cortical hierarchies, we also applied dominance analysis to evaluate their relative contribution to our latent variable scores. Dominance analysis seeks to determine the relative contribution (“dominance”) of each independent variable to the overall fit (adjusted