(C) PLOS One
This story was originally published by PLOS One and is unaltered.
 . . . . . . . . . .



Social interactions between people of same and different generations shape longitudinal changes in interpersonal neural synchrony, loneliness, and social connection [1]

['Ryssa Moffat', 'Social Brain Sciences Lab', 'Eth Zurich', 'Zurich', 'Guillaume Dumas', 'Chu Sainte-Justine Azrieli Research Center', 'Department Of Psychiatry', 'University Of Montreal', 'Montréal', 'Quebec']

Date: 2026-08 

Loneliness is globally acknowledged as a severe and burgeoning health risk, fueling interest in helping people of all ages form meaningful social connections. One promising approach consists of intergenerational social programs. While behavioral and qualitative evidence derived from such programs promise health and wellbeing benefits, the physiological consequences of repeated intergenerational encounters remain unknown. Insight into physiological changes will shed light on the mechanisms of social connection. We charted longitudinal changes in interpersonal neural synchrony (INS) in 31 intergenerational (older/younger adult) and 30 same-generation (younger adult) dyads across a six-session creative drawing program. At each session, dyads completed self-report measures, drew together and alone, and had their cortical activation recorded with fNIRS. In both groups, INS was greater while dyads drew together than alone. Across sessions, intergenerational dyads’ INS decreased and same-generation dyads’ INS increased. INS in RIFG~RTPJ and RIFG~RIFG were predictive of loneliness levels and feelings of social closeness, respectively. This exploratory longitudinal research reinforces the multi-faceted nature of INS dynamics as social connections are forged.

Funding: Two Cortivision Photon Cap devices were provided to RM through the Cortivision Pathfinder Program (grant number CPP-2023/09/01 to RM). https://www.cortivision.com GD was in part supported by the Institute for Data Valorization (Award Number: CF00137433 to GD). https://ivado.ca/en/ GD was in supported by the Fonds de recherche du Québec (Award Number; 285289 to GD). https://frq.gouv.qc.ca/ GD was in part supported by the Natural Sciences and Engineering Research Council of Canada (Award Number: DGECR-2023-00089 to GD). https://www.nserc-crsng.gc.ca/ Oil pastels were provided to RM by Caran D’Ache (agreement number 712517 to RM). https://www.carandache.com/ RM and ESC were supported by and receive salaries from the Social Brain Sciences Lab at ETH Zurich. https://sbs.ethz.ch/ With the exception of the Social Brain Sciences Lab at ETH Zurich, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Prof. ESC leads the Social Brain Sciences Lab at ETH Zurich.

Data Availability: These data were collected after the submission of the following preregistration: https://osf.io/hz6tm . All of the data collected and analysed for this study, as well as all of our code, can be found in our repository entitled ‘Longitudinal perspectives on intergenerational inter-brain synchrony’ on OSF: https://osf.io/xcgp6/ .

To achieve these aims, we recruited 31 intergenerational and 30 same-generation dyads to complete a six-session creative drawing program. At each session, we collected measures of participants’ loneliness and attitudes toward other generations, then recorded dyads’ brain activity using fNIRS while they drew independently and collaboratively with oil pastels. Participants then reported how socially close they felt to their drawing partner. We calculated INS using wavelet transform coherence (WTC) for all pairs of four regions of interest (ROIs), which were the bilateral IFG and TPJ. According to fNIRS best practices, we report both fNIRS signals (oxygenated hemoglobin [HbO] and deoxygenated hemoglobin [HbR]), with HbO results presented in the main manuscript and HbR results presented in the S1 Appendix in S1 File . We employed a Bayesian estimation (as opposed to hypothesis testing) approach [ 89 – 92 ]. Specifically, we built hierarchical models to estimate the magnitude and uncertainty of estimates using posterior predictive distributions. We summarize the distributions of model parameters and contrasts using point estimates and 95% credible intervals called 95% HPDs (highest posterior density regions). We use this estimation approach to assess the sign, magnitude and uncertainty of parameter estimates from our models and to assess the extent to which values of interest (e.g., 0, reflecting the absence of differences between groups or drawing conditions) are among the most credible values in a distribution [ 89 ]. For example, if we compute a contrast between drawing alone and together, we obtain a distribution of the predicted difference between conditions. If the 95% HPD for this distribution excludes 0, we infer a difference between conditions. Aligned with the estimation approach [ 89 – 92 ], we do not compute Bayes factors. Further methodological details are presented in Methods, as well as S2 and S4 Appendices in S1 File . Detailed results tables with point estimates and 95% HPD are presented in S3, S5, and S6 Appendices in S1 File , separately from the results text for ease of reading.

Considered together, these studies suggest that when dyads made up of strangers meet for the first time and engage in a creative, unconstrained activity, such as drawing, INS is likely to be low. Across repeated encounters, INS levels are likely to increase. Drawing on Dikker’s model simulating intergenerational INS, one would expect that generational constellations may impact INS levels and may interact with the trajectory of INS as dyads become socially closer.

Other cross-sectional hyperscanning studies provide evidence that social closeness can shape the arousal that people experience while interacting, as well as INS. In a conversation study, Long and colleagues [ 87 ] recorded brain activity with fNIRS while participants engaged in supportive and conflictual conversations. The authors observed that romantic couples showed greater INS than control dyads when engaging in debate. INS was associated with dyads’ arousal ratings, suggesting the dynamic range of arousal in conflict-related conversations with a romantic partner moderates INS. Further, Zhang and colleagues [ 70 ] compared INS during a competitive button-pressing task performed by older romantic couples and older strangers and found that romantic couples were more competitive and showed greater INS than strangers. These studies suggest that dyads who are socially closer explore more of the ‘dynamic range’ of arousal.

Taking a cross-sectional approach to understand social closeness and relationship development, some studies compare romantic couples, friends and strangers at single moments in time. Such studies suggest that the nature of a dyad’s relationship influences INS during forms of interaction including joint motor action, conversation, and classroom learning [ 43 , 53 , 70 , 80 , 86 – 88 ]. Djalovski and colleagues [ 86 ] recruited romantic couples, friends and strangers to complete a finger tapping task as dyads, and a conversation-based empathy-giving task while brain activity was measured using EEG. During the finger tapping task, INS was greatest between romantic couples, followed by friends, and lowest between strangers. The authors suggest that cumulative joint experience with a specific partner enhances prediction of the partners movements, resulting in greater INS. The empathy-giving task revealed the opposite gradient with romantic couples showing the least INS, friends showing more, and strangers showing the most INS. Djalovski and colleagues propose that strangers monitor each other for potential negative responses more closely than couples to avoid the consequences of a potential misunderstanding. In another study examining verbal communication, Speer and colleagues [ 88 ] recruited friends and strangers to engage in prompted conversations with demarcated turns. The authors report that across the span of conversation, friends showed decreasing INS and strangers showed increasing INS, with the reductions in INS corresponding to more exploratory conversations and increases in INS seeking to converge on common ground. Though phrased differently, Speer and colleagues’s interpretation is closely aligned to Djalovski and colleagues’s interpretation: The less well a dyad knows each other, the greater the INS during verbal communication. To explore this further, we highlight that a central difference between the motor and verbal communication tasks is that the motor task (i.e., drawing specific objects with an ‘Etch A Sketch’) is highly specified, setting both dyad members’ expectations clearly and symmetrically, whereas the verbal communication tasks (i.e., describing a troubling or distressing event and conversing with demarcated turns) are temporally asymmetrical and inherently unpredictable. Within the framework of mutual prediction, we propose that social closeness and the degree of predictability of behavior induced by the task contribute to the opposite INS gradients.

To the best of our knowledge, five hyperscanning studies have recorded INS at multiple sessions and subsequently analyzed the aggregated time points, as opposed to reporting changes in INS across sessions [ 63 , 80 – 83 ]. These studies are reviewed in greater detail in a position piece by Moffat and colleagues [ 36 ]. Only one fNIRS hyperscanning study offers insights into the trajectory of INS during relationship formation [ 84 ]. Sened and colleagues’s [ 84 ] proof-of-concept study tracked the trajectory of INS over bilateral IFG in 8 clinician-patient dyads at the first, third and fifth sessions of a 6-session intervention, where dyads completed imagery and cognitive behavioral training procedures. Sened and colleagues report increasing INS across sessions, as well as an association between increasing INS and reduced anxiety symptoms, improved wellbeing and perceived quality of session, but not the therapeutic alliance (i.e., the patient’s rating of quality of the collaborative relationship between clinician and patient). One further study takes a unique approach to understanding INS in the context of relationship formation, though only encompassing two time points [ 85 ]. INS was recorded from 11 dyads at two sessions, the first within 5 days of the dyad becoming flatmates, and the second after 7 months of co-living. Wang and colleagues report that social closeness can be predicted from INS with approximately 69% accuracy, using a deep neural network model and EEG hyperscanning recordings from frontotemporal brain regions. These two studies [ 84 , 85 ] provide preliminary evidence that INS between dyads increases as dyads grow more familiar with each other, however, a larger sample size and number of time points would provide a richer picture of INS trajectories in developing relationships.

Most hyperscanning studies offer snapshots of INS in a single moment in time, and compare INS between contexts, tasks, or mental states. The trajectory in INS over days or weeks remains unknown, despite the value of granularity insights for understanding changes in behavior related to the investigated contexts, task, and mental states. Longitudinal hyperscanning studies typically include two time points, as opposed to a denser sampling of the trajectory of INS. Numerous reviews from different domains of social neuroscience (e.g., developmental, clinical, communication, etc.) recognize the lack of longitudinal insights into INS and call for longitudinal hyperscanning studies to be conducted [ 43 , 74 – 79 ]. The discrepancy between the number of calls for studies tracking INS trajectories and the paucity of studies reporting them substantiates the critical need for additional multi-session hyperscanning studies. Concretely, multi-session longitudinal designs can fill in the blanks in our understanding of the dynamics of forming and maintaining social connections–a field recently coined ‘relational neuroscience’ [ 43 ].

In the one study to date exploring intergenerational INS involving older adults, Dikker and colleagues [ 72 ] employed a neurocognitive model to simulate EEG-based INS during intergenerational social interactions between grandparents, parents, and grandchildren. In this seminal study, the authors found greater simulated INS between grandparent–grandchild dyads and grandparent–parent–child triads, relative to grandparent–parent and parent–child dyads. The authors report that the increase in simulated grandparent–child INS may be driven by age-related changes in the spectrum of brain activity. The authors also encourage the collection of real-world data to validate these simulations [ 72 ]. These findings underscore how including people of all ages, particularly underrepresented older adults, in intergenerational hyperscanning will enhance our understanding of INS and a wider array of types of social connections.

To date, older adults’ representation in the hyperscanning literature is limited to two hyperscanning studies [ 70 , 71 ], one study simulating INS [ 72 ], and one position piece arguing for the inclusion of older adults in such studies [ 36 ]. It is critical to address this knowledge gap as the real-world settings in which older adults interact with younger adults and children (with their children and grandchildren, in assisted living, when seeking medical care, in community programs or through volunteer work) are numerous. Moreover, the proportion of older adults in the world’s population is projected to continue growing until the end of this century [ 73 ], meaning that filling this knowledge gap will benefit a steadily increasing number of people.

Many hyperscanning studies on collaboration can be considered intergenerational, in that they examine collaboration between parent-child/infant or student-teacher dyads (for reviews, see [ 68 , 69 ]). Though these studies offer the field of social neuroscience a valuable starting point for understanding intergenerational collaboration, two gaps in the literature have yet to be filled: First, the hyperscanning literature on collaboration distinctly lacks any representation of older adults. Second, the hyperscanning literature more generally offers very few longitudinal perspectives into INS exceeding two time points. We now briefly explore the importance of addressing these gaps.

In studies comparing INS while dyads perform tasks collaboratively and alone, INS is consistently greater for collaborative performance than solo performance. This pattern has been observed for finger tapping [ 48 ], cognitive tasks such as n-back and object detection tasks [ 49 , 50 ], singing [ 51 ], tracing shapes on a screen using computer buttons or a stylus [ 52 , 53 ], drawing specific verbs as in Pictionary [ 54 ], among other activities. A meta-analysis of fNIRS hyperscanning studies by Czeszumski and colleagues [ 55 ] reports that during collaboration, INS is commonly observed between both interactants’ prefrontal cortex (PFC), inferior frontal cortex (IFG) or temporoparietal junction (TPJ). INS in the prefrontal and inferior frontal cortices is proposed to reflect initiation and reception of joint attention [ 56 – 58 ], a social competence that depends on cognitive control [ 59 , 60 ]. INS in the TPJ, a key node of the Theory of Mind (ToM) network [ 61 , 62 ], is believed to reflect perspective taking and integration of social information [ 55 ]. Complementary findings from EEG hyperscanning studies suggest that the strength and nature of collaboration shape the levels of INS recorded over frontal and prefrontal brain regions for alpha, beta, and theta frequency bands [ 63 – 67 ]. Specifically, the alpha band may index joint attention and visual processing, while beta and theta bands may reflect joint encoding of sensorimotor information [ 37 , 63 , 64 ]. In combination, the findings from fNIRS and EEG hyperscanning studies indicate that INS levels during collaboration are shaped by processes such as joint attention and perspective taking, which underpin the mutual prediction framework [ 40 ].

The role of INS in social behavior remains debated [ 40 – 43 ], with two main theoretical conceptualisations: common cognitive processing and mutual prediction. The common cognitive processing framework posits that interacting people perceive similar stimuli, which results in both people’s brains responding in comparable ways at comparable time delays [ 44 ]. This framework can explain why individuals viewing the same movie or simultaneously imitating an instructor may show heightened INS. Capturing the interactive and turn-based aspects of real social interactions, the mutual prediction framework posits that interacting people predict potential changes in the environment that they share, such as social information about each other, and that the interdependence of these continuous predictions leads to heightened INS [ 45 – 47 ]. We embed our interpretation of INS during collaborative drawing in the mutual prediction framework, in that we would argue that collaborative drawing inherently involves different (even if complementary) stimuli for each participant created by the other.

One source of physiological information is brain activity. Recording brain activity from two or more people while they interact is commonly referred to as ‘hyperscanning’ and offers a measure of interpersonal neural synchrony (INS; the extent to which patterns of brain activity are temporally aligned). Mobile functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) are particularly well suited to recording brain activity during social interactions in real-world settings [ 36 , 37 ]. Hyperscanning with non-mobile techniques, such as functional magnetic resonance imaging (fMRI) and magneto-encephalography (MEG), is possible, though it offers less realistic social interactions and is less logistically feasible [ 38 , 39 ].

Despite the mounting behavioral and qualitative evidence that repeated intergenerational interactions yield social benefits, including reduced loneliness, little is known about the physiological aspects that contribute to how and why these intergenerational programs offer such benefits. This is important because the neurophysiological signatures of budding intergenerational relationships have the potential to be harnessed as tools to promote the formation of new social connections, yet they remain unknown [ 36 ].

To combat loneliness, policy makers, researchers [ 1 , 21 , 22 ], and health practitioners [ 5 ] promote the creation of opportunities for meaningful social interactions for all members of society, and especially for those from populations most susceptible to loneliness. This typically involves initiating community programs that provide a platform for regular socializing opportunities [ 6 , 23 – 25 ]. Some community programs are intentionally designed to bring together members of different age groups, i.e., to be intergenerational. One reason for this is that people of all ages experience loneliness [ 26 – 28 ]. Another is that intergenerational social interactions can improve social and physical wellbeing for older adults, as well as increase empathy and feelings of social closeness toward older adults from younger participants [ 2 ]. The observed improvements seem to stem from repeated intergenerational contact [ 29 – 31 ]. In this context, repeated intergenerational contact requires regular engagement in intergenerational community programs, which is most likely to be achieved by ensuring that programs offer meaningful social interactions. One approach that has been shown to be particularly successful in this domain is arts-based and creative activities [ 32 ]. Indeed, a growing body of evidence documents the social and physical health benefits of intergenerational arts programs for participants of all ages [ 30 , 33 – 35 ].

Loneliness can be defined as “a negative, subjective emotional state resulting from a discrepancy between one’s desired and actual experiences of connection” [ 6 ]. Put more succinctly, loneliness can be thought of as perceived social isolation. Policy makers and researchers have long emphasized the severe risk that loneliness poses to physical and mental health [ 1 , 7 , 8 ]. Public figures and media outlets go so far as to compare the adverse health impacts (e.g., mortality) of loneliness to those of smoking cigarettes [ 9 ]. Considering everyday functioning, longitudinal studies show that loneliness and social isolation can precipitate declines in cognitive functioning including verbal ability, numeracy, and short-term memory [ 10 , 11 ]. Loneliness is also associated with reduced perceptual speed [ 12 ] and biases toward negative evaluations of social information [ 13 – 15 ]. At the brain level, chronic loneliness and episodes of social isolation have been associated with altered structure (typically reduction in tissue volume) and altered function of prefrontal and posterior superior temporal cortices, as well as the insula, hippocampus, and amygdala [ 16 – 18 ]. Attentional, visual, and default mode networks are also reported to show stronger functional connectivity in lonely individuals, which is believed to be associated with the bias toward processing social information negatively and a tendency toward increased rumination [ 18 – 20 ].

Experiences of loneliness can have serious negative consequences for physical and mental health. As a result, widespread efforts are being made to combat loneliness [ 1 ]. According to meta-analyses of behavioral studies, community programs providing opportunities for repeated contact between generations can improve older adults’ (65 + years) physical, social, and cognitive health [ 2 ], while also reducing younger adults’ stereotypes about aging [ 3 , 4 ]. Moreover, physicians are increasingly prescribing attendance at such programs—a practice called social prescribing [ 5 ]–further highlighting the value the medical field attributes to such programs. To date, the existing evidence base for intergenerational community programs consists of behavioral and qualitative studies. While offering promising results in terms of self-reported benefits and social engagement, such studies offer little insight into how or why intergenerational relationships develop on a physiological level. In this study, we sought to provide a physiological perspective on the trajectory of intergenerational relationship development using a longitudinal hyperscanning approach, comparing intergenerational and same-generation dyads who completed a six-week creative drawing program. Specifically, we tracked the trajectories of dyads’ interpersonal neural synchrony (INS) and changes in social connectedness.

Attitudes towards generations (allophilia). Summed. We observed a negative relationship between summed allophilia scores and INS in LTPJ~LPTJ and LIFG~RIFG. We also found a group difference for RIFG~RTPJ, where the relationship between INS and the summed allophilia scores was more positive for the intergenerational dyads than same-generation dyads. An interaction was observed in LIFG~LTPJ, with a task difference for intergenerational dyads only ( Fig 3 ; Tables S and T in S5 Appendix in S1 File ). Difference. We did not observe an association between INS and allophilia difference scores, and group did not influence this relationship. We observed a task difference in RIFG~RIFG, where the relationship between INS and the difference in allophilia scores was more positive for drawing together than alone. We found an interaction for RIFG~RIFG, where we observed a task difference for same-generation dyads only ( Fig 3 ; Tables U and V in S5 Appendix in S1 File ).

Social closeness. Summed. We observed a positive relationship between summed social closeness scores and INS in RIFG~RTPJ. In LIFG~LIFG, we observed a task difference, whereby there was a more positive relationship between INS and summed social closeness for drawing together than alone. We observed a group difference for RIFG~RIFG, whereby intergenerational dyads showed a more positive relationship than same-generation dyads, and RIFG~RTPJ where intergenerational dyads showed a more negative relationship than same-generation dyads. We observed interactions for LIFG~LIFG and RIFG~RIFG, RIFG~RTPJ. In LIFG~LIFG, there was a task difference for same-generation dyads only. In RIFG~RIFG, there was a group difference for drawing alone only. In RIFG~RTPJ, we observed a task difference for the same-generation dyads only and a group difference only when dyads drew alone ( Fig 3 ; Tables O and P in S5 Appendix in S1 File ). Difference. We did not observe an association between INS and social closeness difference scores. Neither group nor task influenced this relationship. We found an interaction for RIFG~RIFG: There was a task difference for both groups and a group difference when drawing alone only ( Fig 3 ; Tables Q and R in S5 Appendix in S1 File ).

(A) Slope of change in INS across levels of self-report measures for ROI pairs with at least one real vs. pseudo difference revealed by contrasts (point estimates from models and contrasts with 95% HPD in Tables K–V in S5 Appendix). Lines indicate whether the 95% HPD for each INS~Self-report measure slope excludes 0 (solid), indicating an association, or includes 0 (dashed), indicating no association. Shading shows 95%, 89%, and 50% intervals for the posterior predictive distributions. Results of task, group, and task*group contrasts for the panels above are as follows. LIFG~LIFG Social closeness (Sum): Task difference, negative relationship for drawing alone and drawing alone < together. Interaction, together > alone for same generation. RIFG~RIFG Loneliness (Dif): Task difference, drawing together < alone. RIFG~RIFG Social Closeness (Sum): Group difference, intergenerational > same generation dyads. Interaction, intergenerational > same generation for drawing alone. RIFG~RIFG Social Closeness (Dif): Interactions, drawing together > alone for intergenerational dyads, drawing together < alone for same generation dyads, and intergenerational > same generation for drawing alone. RIFG~RIFG Allophilia (Dif): Task difference, positive relationship for drawing together and drawing together > alone. Interaction difference, drawing together > alone for same generation dyads. LTPJ~LTPJ Loneliness (Dif): Interaction difference, intergenerational < same generation dyads for drawing alone. LTPJ~LTPJ Allophilia (Sum): Negative relationship. Group difference, negative relationship for intergenerational dyads only. Task difference, negative relationship for drawing alone and together. LIFG~RIFG Allophilia (Sum): Negative relationship. Group difference, negative relationship for same-generation dyads only. LIFG~LTPJ Allophilia (Sum): Interaction, drawing together < alone for intergenerational dyads. RIFG~RTPJ Loneliness (Sum): No differences. RIFG~RTPJ Loneliness (Dif): Interaction, drawing together < alone for same-generation dyads only. RIFG~RTPJ Social Closeness (Sum): Positive relationship. Group difference, positive relationship for same-generation dyads and intergenerational < same-generation. Task difference, positive relationship for drawing alone. Interactions, drawing together < alone for same-generation dyads, and intergenerational < same-generation for drawing alone. RIFG~RTPJ Allophilia (Sum): Group difference, intergenerational > same-generation dyads. (B) Visualization of all possible ROI pairs (n = 10). Dashed lines indicate ROI pairs where i) neither INS for all sessions combined nor ii) the slope of change in INS differed between real and pseudo dyads. Solid lines indicate ROI pairs where INS (for sessions combined or slope of change across sessions) differed between real and pseudo dyads. Black solid lines indicate ROI pairs where task, group, and task*group contrasts showed differences. Analyses of HbR, visualized in Fig E in S3 Appendix in S1 File , showed similar pattern of results for Social Closeness (Sum) and Allophilia (Dif) in RIFG~RIFG, as well as Loneliness (Dif) in LTPJ~LTPJ. Brains created in BioRender. Moffat, R. (2026) https://BioRender.com/6p18lgg . Fig 3 was created using code shared in the OSF repository “Longitudinal perspectives on intergenerational inter-brain synchrony”: https://osf.io/xcgp6 . Code for individual panels in this figure: https://osf.io/xcgp6/files/6xty4 .

Loneliness. Summed. We did not observe an association between INS and summed loneliness scores. Neither group nor task influenced this relationship. We observed an interaction in RIFG~RTPJ, for the intergenerational dyads, whereby the INS~summed loneliness relationship was more negative for drawing alone than together ( Fig 3 ; Tables K and L in S5 Appendix in S1 File ). Difference. We did not observe an association between INS and loneliness difference scores, and group did not influence this relationship. Task influenced the INS~loneliness difference relationship for RIFG~RIFG, whereby the relationship was more negative for drawing together than alone. We observed interactions for RIFG~RIFG, RIFG~RTPJ, and LTPJ~LTPJ. For RIFG~RIFG, we observed a task difference for intergenerational dyads only. For LTPJ~LPTJ, we observed a task difference for intergenerational, but not same-generation dyads and a difference between groups for drawing alone but not together. For RIFG~RTPJ, we observed a task difference for same-generation dyads only ( Fig 3 ; Tables M and N in S5 Appendix in S1 File ).

Change in INS levels across sessions. We observed no difference between drawing alone and together but did observe the following differences between groups: We observed a more positive INS slope for the same generation than the intergenerational dyads in LIFG~LTPJ. We also found interactions between group and task. Intergenerational dyads showed a more positive INS slope for drawing together than alone in LTPJ~LPTJ, and more positive INS slopes for drawing alone than together in RTPJ~RTPJ, LIFG~RTPJ, and RIFG~RTPJ. For drawing together, the INS slope was more positive for same-generation dyads than intergenerational dyads. Same-generation dyads further showed more positive INS slopes than intergenerational dyads for drawing together in RTPJ~RTPJ, LIFG~RTPJ and RIFG~RTPJ. Intergenerational dyads showed more positive INS slopes than same-generation dyads when drawing alone in LIFG~RTPJ and RIFG~RTPJ. These differences correspond to changes in the magnitude of ~0.006 to 0.011 change in coupling from one session to the next (equivalent to 32% of the range between the minimum and maximum 95% HPD values observed in real and pseudo dyads for all sessions combined; Table A in S5 Appendix in S1 File ). Point estimates and 95% HPD per ROI pair, task and group from models are visualized in Fig 2C . A full list of point estimates and 95% HPDs from contrasts is presented in Tables H–J in S5 Appendix in S1 File .

INS levels for all sessions combined. We observed no differences between groups but did observe differences between tasks. We observed greater INS for drawing together than alone in LTPJ~LTPJ, LIFG~RIFG, RIFG~LTPJ and RIFG~RTPJ. With respect to the interaction between group and task, we found that in LTPJ~LTPJ, INS was greater for drawing together than alone for intergenerational dyads. In RIFG~RTPJ, INS was greater for drawing together than alone for same-generation dyads. These differences correspond to ~0.01 difference in coupling (equivalent to 39% of the range between the minimum and maximum 95% HPD value observed in real and pseudo dyads for all sessions combined; Table A in S5 Appendix in S1 File ). Point estimates and 95% HPD per ROI pair, task and group from models are visualized in Fig 1C . A full list of point estimates and 95% HPDs from contrasts is presented in Table F in S5 Appendix in S1 File . We also contrasted the first and second instances of drawing together. We found no differences and ruled out order-related changes in INS level while drawing together (Table G in S5 Appendix in S1 File ).

INS levels for all sessions combined. When intergenerational dyads drew together, there was a trend of greater INS when the LIFG belonged to the older adult and the LTPJ belonged to the younger adult than vice versa (95% HPD include 0, 3% of HPD < 0). We observed no differences in INS for any composition of any ROI pair for drawing alone. Change in INS levels across sessions. We observed no differences in the INS slopes across sessions for any composition of any ROI pair, for drawing alone or together.

For the intergenerational dyads specifically, we examined whether INS differed as a function of the generational composition of the ROI pairs. In other words, whether an ROI belonging to an older or younger member of a dyad influenced INS levels for all sessions or slopes across sessions. Full table of estimates and contrasts with HPD available in Table E in S5 Appendix S1 File .

(A) Slope of change in INS across six sessions; black squares indicate that INS levels differ between real and pseudo dyads (i.e., 95% HPD of contrast distribution excludes 0). (B) Visualization of all possible ROI pairs (n = 10). Dashed lines indicate ROI pairs where the slope of change in INS did not differ between real and pseudo dyads. Solid lines indicate ROI pairs where the slope of change in INS differed between real and pseudo dyads. Black solid lines indicate ROI pairs where task, group, and task*group contrasts showed differences. (C) Slope of change in INS across sessions for all ROI pairs that differed between real and pseudo dyads, for which task, group, and task*group contrasts were computed. Solid lines indicate that the 95% HPD of an INS~Session slope excludes 0, indicating an association. Dashed lines indicate that the 95% HPD of an INS~Session slope includes 0, indicating no association. Gray shading shows 95%, 89%, and 50% intervals of the posterior predictive distributions. LTPJ~LTPJ: Interaction effect, drawing together > alone for intergenerational dyads. RTPJ~RTPJ: Interaction effects, drawing together < alone for intergenerational dyads and intergenerational < same generation dyads for drawing together. LIFG~LTPJ: Group effect, intergenerational < same generation dyads. LIFG~RTPJ: Interaction effects, drawing together < alone for intergenerational dyads, intergenerational > same generation dyads for drawing alone, and intergenerational < same generation dyads for drawing together. RIFG~RTPJ: Interaction effects, drawing together < alone for intergenerational dyads, intergenerational > same generation dyads for drawing alone, and intergenerational < same generation dyads for drawing together. Full list of point estimates from models and contrasts with 95% HPD available in Tables C and D in S5 Appendix in S1 File for HbO. HbR analyses, visualized in Fig D in S3 Appendix in S1 File , showed the same pattern of results for RTPJ~RTPJ and the same interaction effect of drawing together < alone for intergenerational dyads. Brains created in BioRender. Moffat, R. (2026) https://BioRender.com/6p18lgg . A and C were created using code shared in the OSF repository “Longitudinal perspectives on intergenerational inter-brain synchrony”: https://osf.io/xcgp6 . Code for A: https://osf.io/xcgp6/files/v5kyc . Code for C: https://osf.io/xcgp6/files/8rgu5 .

Change in INS levels across sessions. We observed a more positive slope of change for all ROI pairs that differed between real and pseudo dyads, with one exception (black squares Fig 2A ; solid lines in Fig 2B ; Table D in S5 Appendix in S1 File ). The ROI pairs showing differences were LIFG~RTPJ for intergenerational dyads drawing alone, LTPJ~LPTJ and RIFG~RTPJ for intergenerational dyads drawing together, no ROI pairs for same-generation dyads drawing alone, and RTPJ~RTPJ and LIFG~LTPJ for same-generation dyads drawing together. HbR analyses showed little similarity (reported in full in S1 Appendix in S1 File ).

(A) INS for all ROI pairs per task and group; black squares indicate that INS levels differ between real and pseudo dyads (i.e., 95% HPD of contrast distribution excludes 0). (B) Visualization of all possible ROI pairs (n = 10). Dashed lines indicate ROI pairs where INS did not differ between real and pseudo dyads. Solid lines indicate ROI pairs where INS differed between real and pseudo dyads. Black solid lines indicate ROI pairs where task, group, and task*group contrasts showed differences. Gray solid lines indicate ROI pairs where contrasts showed no differences for task, group, or task*group contrasts. (C) INS levels as point estimates with 95% HPD for all ROI pairs that differed between real and pseudo dyads, for which task, group, and task*group contrasts were computed. LIFG~LIFG: No differences. RIFG~RIFG: No differences. LTPJ~LTPJ: Task difference, drawing together > alone. Interaction, drawing together > alone for intergenerational dyads. LIFG~RIFG: Task difference, drawing together > alone. LIFG~LTPJ: No differences. RIFG~LTPJ: Task difference, drawing together > alone. RIFG~RTPJ: Task difference, drawing together > alone. Interaction, drawing together > alone for same-generation dyads. Full list of point estimates from models and contrasts with 95% HPDs available in Tables A and B in S5 Appendix in S1 File for HbO. HbR analyses visualized in Fig C in S3 Appendix in S1 File , showed the same pattern of results for LIFG~RIFG and RIFG~LTPJ. Brains created in BioRender. Moffat, R. (2026) https://BioRender.com/6p18lgg . A and C were created using code shared in the OSF repository “Longitudinal perspectives on intergenerational inter-brain synchrony”: https://osf.io/xcgp6 . Code for A: https://osf.io/xcgp6/files/v5kyc . Code to generate individual values, compute summary values, and generate each panel in C: https://osf.io/xcgp6/files/8rgu5 . Table of summary values shown in C: https://osf.io/xcgp6/files/ya5hn .

INS levels for all sessions combined. All differences between real and pseudo dyads corresponded to greater INS for real than pseudo dyads (black squares in Fig 1A ; solid lines in Fig 1B ; Table B in S5 Appendix in S1 File ). The ROI pairs showing differences were RIFG~RIFG for intergenerational dyads drawing alone, LIFG~LIFG, LTPJ~LTPJ, RIFG~RIFG, LIFG~RIFG, LIFG~LTPJ, RIFG~LTPJ for intergenerational dyads drawing together, no ROI pairs for same-generation dyads drawing alone, and LIFG~RIFG and RIFG~RTPJ for same-generation dyads drawing together. HbR analyses revealed similar results, in that LTPJ~LTPJ, LIFG~RIFG, and LIFG~LTPJ showed differences between real and pseudo dyads for intergenerational dyads drawing together (reported in full in S1 Appendix in S1 File ).

The first step in our analysis of INS was to perform contrasts between the posterior predictive distributions computed for real and pseudo dyads’ INS levels. Pseudo dyads consist of pairs of participants who never interacted, but match a group type (e.g., both younger adults, or one older and one younger adult). We first did this for all sessions combined and then for changes in INS levels across sessions per combination of ROI pair, task, and group. These contrasts serve to assess whether the level of observed INS (or the slope of change in INS) differs meaningfully from a null distribution of INS levels (or slopes) made up of dyads who never interacted with one another. Further statistical analyses can then be performed on the ROI pairs where the posterior predictive distributions for real and pseudo dyads differ (i.e., the 95% HPD of the distribution of the difference excludes zero). To summarize these distributions for model parameters (e.g., INS levels for real dyads) and for contrasts (e.g., the difference between dyad types), we report point estimates from models and contrasts with 95% HPD in Tables A–D in S5 Appendix in S1 File .

Relationships between measures of social connection. As presented in Table 2 , greater social closeness was associated with reduced feelings of loneliness for same-generation dyads. A matching trend was observed for intergenerational dyads (95% HPD include 0, 4% of HPD > 0). Greater social closeness was associated with more positive attitudes toward other generations for intergeneration dyads but not same -generation dyads. Greater loneliness was associated with more positive attitudes toward other generations for same-generation dyads but not intergenerational dyads. None of these associations differed between groups.

Attitudes toward generations (allophilia). At the beginning of the first session, participants in both groups reported feeling similarly close to their own and other generations (intergenerational mean = 0.01, SD = 14.48; same-generation mean = −5.87, SD = 13.39 on a scale from −85 ′feel closer to own generation’ to 85 ′feel closer to other generation’). At the first session and for all sessions combined, same-generation dyads reported feeling closer to their own generation than the intergenerational dyads (session 1 = 4.65 and combined sessions = 4.48 points higher), who reported feeling equally close to their own and the other generation. Across sessions, allophilia scores stayed stable (i.e., no observed change across sessions for either group; Table 1 ).

Social closeness. At the end of the first session, both groups reported medium levels of loneliness (intergenerational mean = 3.32, SD = 1.63; same-generation mean = 2.87, SD = 1.17 on a scale from 1 ′no overlap’ to 7 ′complete overlap’, where more overlap indicates greater social closeness). At the first session, contrasts indicate a trend toward intergenerational dyads showing greater feelings of social closeness than same-generation dyads (0.56 higher; 95% HPD includes 0, 6% of HPD < 0). For all sessions combined, intergenerational dyads reported greater feelings of social closeness, compared to same-generation dyads (0.56 higher). Across sessions, feelings of social closeness increased for both groups (~4% per session), with no observed difference in rate between groups ( Table 1 ).

Unstandardized point estimates from models and group contrasts per self-reported measure with 95% HPD in square brackets. Point estimates for (1) the first session, (2) all six sessions combined, and (3) the slope of change across sessions. Self-report measures are loneliness, social closeness, and attitudes toward generations (allophilia). Visualizations of distributions for each measure and trajectory across sessions by age (i.e., older or younger adult) and group in Figs A and B in S3 Appendix in S1 File

Loneliness. At the beginning of the first session, both groups reported mid-low levels of loneliness (intergenerational mean = 1.50, SD = 1.30; same-generation mean = 2.33, SD = 1.65 on a scale from 0 ′least lonely’ to 6 ′most lonely’). Contrasts indicate that at the first session and for all sessions combined, intergenerational dyads reported feeling less lonely than same-generation dyads (session 1 = 0.68 and combined sessions = 0.61 points higher). Across sessions, feelings of loneliness showed small reductions for both groups (~1% per session), with no observed difference in rate of reduction between groups ( Table 1 ).

3 Discussion

We invited intergenerational and same-generation dyads to complete six sessions of creative drawing (resembling a community art program), and charted dyads’ levels of loneliness, social closeness, attitudes toward generations and INS as they formed social connections across six sessions. Our first aim was to characterize INS within intergenerational dyads comprising one young and one older adult. In a large sample (sessions combined), we show that INS among intergenerational dyads is largely comparable to same-generation dyads. Specifically, both dyad types show greater INS in LTPJ~LTPJ, LIFG~RIFG, RIFG~LTPJ, and RIFG~RTPJ for drawing together than alone, with the greatest differences in LIFG~RIFG for intergeneration dyads and RIFG~RTPJ for same-generation dyads. Our second aim was to chart the trajectory of INS in same-generation and intergenerational dyads, across repeated social interactions. While drawing together, ROI pairs that include the right TPJ (RTPJ~RTPJ, LIFG~RTPJ, and RIFG~RTPJ) showed decreasing INS for intergenerational dyads and increasing INS for same-generation dyads. Our third aim was to characterize the relationship between INS and social connectedness, via loneliness, social closeness, and attitudes toward generations. We found that the relationship between loneliness and INS in RIFG~RIFG differed when dyads drew alone and together: Greater similarity in dyadic levels of loneliness predicted greater INS when dyads drew together and lower INS when they drew alone. Greater social closeness predicted increasing INS in RIFG~RTPJ for all dyads and greater INS in RIFG~RIFG for intergenerational than same-generation dyads. With respect to dyadic attitudes towards generations, we observed that INS in LIFG~RIFG and LTPJ~LTPJ was elevated among dyads who felt further from other generations (i.e., closer to their own). Below, we explore the implications of these findings.

Individuals’ levels of loneliness and social closeness decreased and increased, respectively, across sessions, for both generational constellations. These findings match the target outcomes of the community programs proposed by policy makers, researchers, and health practitioners [1,5,21,22] and indicate that social connections were indeed formed. Practically, our results reveal a 1% reduction in loneliness scores per session and a 4% increase in social closeness per session. These incremental changes highlight the potential of repeated encounters. Further research with more than 6 sessions would be useful for ascertaining if and at which point these changes in loneliness and social closeness may plateau.

Considering all sessions together, we observed that the generational constellation (i.e., intergenerational versus same generation) predicted differences in individual’s levels of loneliness, social closeness and attitudes toward other generations. For example, simply being in the presence of a similar or quite differently aged person may alter one’s perceptions of one’s loneliness. If the other person is of a similar age, one might feel more lonely than if the person is older, in which case one would self-report feeling less lonely – perhaps by virtue of social comparison [93]. This finding should be validated in future work by comparing intergenerational dyads with same-generation dyads composed of two older adults, as well as two younger adults. Greater feelings of social closeness among intergenerational, as compared to same-generation, dyads may relate to overcoming perceived generational differences or generational stereotypes [94]. Notably, the distributions of difference in social closeness did not differ between groups, suggesting that the increased social closeness observed for intergenerational dyads was not driven by older or younger adults’ responses alone, but rather by both age groups. Intergenerational dyads held more charitable attitudes toward other generations than same-generation dyads, aligning with findings that contact with older adults reduces younger adults’ negative stereotypes of and anxiety regarding older adults [95]. Among intergenerational dyads, individuals’ attitudes toward generations were linked to their social closeness ratings, highlighting possible bidirectional interplay between attitudes and social closeness. Moreover, among same-generation dyads, greater loneliness was associated with a weaker preference towards one’s ‘own’ (younger) generation, highlighting the window of opportunity for intergenerational social activities in combatting loneliness.

This study offers novel insights into INS during collaboration in dyads composed of older and younger adults, adding rich empirical data to the two existing studies that involve older adults [70,72]. The fNIRS hyperscanning literature on collaboration focuses on the prefrontal and inferior frontal cortices and the TPJ [55]. The bilateral IFG play a role in the initiation and reception of joint attention [56–58] and the bilateral TPJ are central to the integration of social information [61,62]. Moreover, with some exceptions (e.g., 70), hyperscanning studies typically only report homologous pairs of brain areas (e.g., LIFG~LIFG), for which the interpretation of heightened INS may be simpler. We preregistered and now report exploratory analyses of INS that include non-homologous ROI pairs (e.g., LIFG~RIFG) and offer possible reasoning for observations of heightened INS.

In our large sample (all sessions combined), we show that INS in intergenerational dyads is largely comparable to same-generation dyads. That is, we observed greater INS in LTPJ~LTPJ, LIFG~RIFG, RIFG~LTPJ, and RIFG~RTPJ for drawing together than alone. This aligns with the existing findings that collaboration co-occurs with greater INS in brain regions that process social information. Considered in the context of the mutual prediction framework [45–47], these findings suggest that collaborative drawing results in heightened integration of social information (LTPJ~LTPJ) via joint attention (LIFG~RIFG), and perhaps, integration of the other person’s maintenance of joint attention as social information (RIFG~LTPJ and RIFG~RTPJ). We also observed robust differences in INS while drawing together and alone in separate ROI pairs for each group: LIFG~RIFG for the intergenerational dyads and RIFG~RTPJ for the same-generation dyads. We cautiously speculate that intergenerational dyads’ level of cognitive control while drawing together is particularly high and aligned within dyads, and that same-generation dyads may evaluate and integrate information regarding the strength or continuity of their partner’s joint attention. This interpretation requires further investigation using paradigms that can quantify joint attention and cognitive control, both of which would deepen our understanding of mutual prediction as a mechanism of INS.

INS in IFG is proposed by some researchers to be unique to verbal communication, though a few studies show that INS in IFG may also play a role in non-verbal communication [55]. With our very large sample, we can provide strong evidence that INS involving the IFG occurs during non-verbal communication, such as silent collaborative drawing.

Cross-sectional studies suggest that INS levels during collaboration decrease with higher levels of familiarity (such as friendship or stable romantic relationships) that require repeated social interactions to establish [53,70,80,86–88]. We document INS trajectories during collaboration and independent drawing by two (initial) strangers with the highest temporal granularity to date – 6 consecutive time points. Our findings demonstrate that INS changes from a dyad’s first encounter to the final recorded session, entailing ~6 hours of time spent together and ~90 min of collaborative activity spread across 6 weeks.

In our preregistration, we hypothesized that INS would increase across sessions for both groups, with a steeper rate of change for intergenerational dyads (see Section 5.1 for preregistration details). We included this (weak) hypothesis to document our initial thoughts collected from the limited intergenerational and/or longitudinal hypercanning research. Specifically, the prediction of increasing INS with a steeper slope for intergenerational dyads was based on Dikker and colleagues’ theoretical and simulated predictions about age-related differences in INS during verbal communication [72,96]. In contrast, our real-world data were collected while participants were specifically instructed to refrain from verbal communication during collaborative drawing, potentially leading to the difference between predicted and observed results. We observed that while dyads drew together, ROI pairs that include right TPJ (RTPJ~RTPJ, LIFG~RTPJ, and RIFG~RTPJ) showed decreasing INS across sessions among intergenerational dyads but increasing INS among same-generation dyads. This has potential implications for the mutual prediction framework, as well as the field of relational neuroscience, that merit further empirical investigation. For example, this may suggest that, in the context of collaborative drawing, intergenerational dyads’ monitoring and integration of their partner’s levels of joint attention may decrease with increasing familiarity, whereas same-generation dyads may monitor each other’s levels of joint attention more closely as familiarity increases. Across sessions, INS increased in RTPJ~RTPJ for same-generation dyads and LTPJ~LTPJ for intergenerational dyads. This difference in lateralization may be related to the integration of “matched” or “mismatched” predictions. Whereas the right TPJ is associated with identifying “mismatched” predictions, the left TPJ encodes both “matched” and “mismatched” predictions [97]. Accordingly, it is possible that same-generation dyads become increasingly sensitive to “mismatched” predictions with increasing familiarity while intergenerational dyads may encode more “matched” predictions with increasing familiarity. Alternatively for intergenerational dyads, the frequency or absolute amount of mismatched predictions may decrease with increasing familiarity.

We found that the relationship between loneliness and INS in RIFG~RIFG differed when dyads drew alone and together: Greater similarity in dyadic levels of loneliness predicted greater INS when dyads drew together and lower INS when they drew alone. This may point to how differences in loneliness can shape processes involved in mutual prediction, such as joint attention and perspective taking [40]. Experiences of loneliness predict changes in cognition, such as perceptual speed, memory, and negatively biased perceptions of social information [10,11,13–15]. It follows that these changes in cognition may co-occur with changes in joint attention or may alter the facility with which individuals engage in joint attention [98]. It is possible that lonelier individuals may require more numerous neural resources to maintain joint attention or alternatively present hypervigilant tendencies, both of which could result in elevated INS in RIFG~RIFG [19,99,100].

To understand INS beyond the changes in social connectedness incurred by repeated social interactions, we examined the extent to which dyads’ self-reported feelings of social closeness were reflected in INS. We observed that greater reported social closeness predicted greater INS in RIFG~RTPJ for all dyads and in RIFG~RIFG for the intergenerational dyads. We interpret the increasing INS in RIFG~RTPJ as meaning that dyads who feel close to one another monitor and integrate each other’s joint attention more than dyads who feel less socially close. Drawing on hyperscanning studies that find links between arousal and INS [70,87,101,102], we tentatively propose that the increasing INS for intergenerational dyads in RIFG~RIFG may reflect joint attention as well as heightened arousal or the facilitation of joint attention via heightened arousal.

With respect to dyadic attitudes towards generations, we observed that INS in LIFG~RIFG and LTPJ~LTPJ decreased as feelings of closeness to other generations increased. As this analysis is particularly exploratory in nature, with no empirical precedent, we offer a tentative suggestion that similarity in attitudes towards generations may give dyads a more internally consistent basis upon which they form predictions about each other’s behavior (i.e., elsewhere termed “common ground”; [88]). These findings can serve as a useful point of departure for research examining the impact of different sources of ‘common ground’ on INS. For example, studies could explore whether cumulative life experience (e.g., number of years lived) gives older adults an advantage for finding common ground and/or whether similarities in socialization (e.g., culture, age, socio-economic status, hobbies) play bigger role in establishing common ground that could shape the mutual prediction underpinning INS levels.

As recommended by Simons and colleagues [103], we make explicit the constraints on generality of this work. Our findings only generalize to the targeted brain regions (i.e., bilateral IFG and TPJ). Though our study offers typical coverage for fNIRS hyperscanning studies, we encourage the use of high-density fNIRS optode arrays in future research on this topic [104]. We observed overlap between HbO and HbR results for analyses of all sessions together and INS trajectories across sessions, with some overlap in HbO and HbR results for relationships between INS and self-reported measures. Our adequate pairing of sample size and conservative Bayesian approach notwithstanding, we encourage other researchers to replicate these findings. Moreover, the INS self-report measures are not necessarily generalizable across cultures, due to differences in formation of relationships [105,106]. Though our findings pertaining to changes in loneliness and social closeness across sessions are in line with findings from behavioral and qualitative studies performed as part of more elaborate and enriching community art programs, our sessions were attended by one dyad at a time, with partners assigned based on availability. Future studies could expand our paradigm to small group sessions with multiple dyads and free partner choice to reflect community programs more closely. We have no reason to believe that the results depend on other characteristics of the participants, materials, or context.

One design limitation of this study is that we did not have the resources to include a group of same-generation dyads composed of two older adults, though this would have been the optimal design. Without such a group, we cannot be sure that differences between groups are purely related to the generational constellation and not age-related differences in neural processing. Future research should compare same-generation dyads across different age ranges. Another design limitation pertains to gender pairings. We could not control for differences resulting from same gender and different gender pairings, because the combination of different ages and different genders resulted in eight unique gender pairings, each with a small number of dyads (Fig A in S2 Appendix in S1 File). Future research could focus on specific intergenerational gender pairings to gain a deeper understanding of the role of gender in INS trajectories.

A technical limitation of this study is that three optodes of one Photon Cap device unexpectedly became defective partway through data collection (and were replaced as rapidly as possible). This resulted in the exclusion of several participants’ right TPJ channels for the affected sessions. Thus, the number of data points for ROI pairs involving right TPJ, particularly RTPJ~RPTJ, is lower than for other ROI pairs (Fig B in S2 Appendix in S1 File). Our Bayesian approach accounted for this difference in sample size per ROI pair by partial pooling (for an excellent tutorial, see [107]), and our selection of the ‘best channel’ per ROI helped ensure the quality of signals included in the analysis. Another approach would be to aggregate signals from all channels of adequate signal quality per ROI. In Fig C in S2 Appendix in S1 File, we show that this approach yields a comparable pattern of numerically similar point estimates. Interested readers can find the strengths and weaknesses of each approach in the Methods. Finally, we used WTC (a linear measure) to quantify INS. We have also identified two-brain states in another analysis of these data, shedding light on intra- and inter-brain dynamics [108]. WTC is the dominant method for computing INS in fNIRS signals [109], even though the interpersonal synchrony is widely believed to be non-linear. Approaches from information theory show promise for delivering insights into non-linear aspects of INS [110] and should be considered in future research.

[END]
---
[1] Url: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003899

Published and (C) by PLOS One
Content appears here under this condition or license: Creative Commons - Attribution BY 4.0.

via Magical.Fish Gopher News Feeds:
gopher://magical.fish/1/feeds/news/plosone/