Evidence map›Paper›PMID 41709875›Full record

ArticlePNAS nexus2026

Brain activity reveals how wildlife imagery evokes engagement on social media.

Tara Srirangarajan, Nik Sawe, Tierney Thys, Xinzhe Cynthia Wu, Brian Knutson

Abstract read
In one paragraph

Article in PNAS nexus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Tara SrirangarajanDepartment of Psychology, Stanford University, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0002-7435-6347
Nik SaweEmmett Interdisciplinary Program in Environment and Resources, Stanford University, Stanford, CA 94305, USA.
Tierney ThysCalifornia Academy of Sciences, National Geographic, San Francisco, CA 94118, USA.ORCID https://orcid.org/0000-0002-3019-0808
Xinzhe Cynthia WuDepartment of Psychology, Stanford University, Stanford, CA 94305, USA.
Brian KnutsonDepartment of Psychology, Stanford University, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0002-7669-426X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vivid images of wildlife can motivate environmental advocacy and charitable giving, yet the mechanisms that drive their broad appeal remain unclear. To investigate how wildlife images influence online behavior, we combined behavioral experiments, neuroimaging data, and large-scale social media engagement data from National Geographic's Instagram. Consistent with findings on charitable giving to humans, activity in brain circuits associated with anticipatory affect (i.e. the nucleus accumbens or NAcc) and value integration (i.e. the medial prefrontal cortex or MPFC) predicted individual liking and donations to depicted wildlife. Further, group MPFC activity forecast aggregate engagement (i.e. likes controlling for followers) with wildlife images on social media. Auxiliary analyses indicated that neural activity in circuits associated with socioemotional processing (i.e. facial salience and mentalizing) correlated with MPFC activity. In a neurally inspired model, these socioemotional features forecast social media engagement in other wildlife images online. Together, these findings imply that neural activity not only forecasts engagement with wildlife imagery on social media but can also inform theoretical models of which wildlife image features most powerfully promote sustainable behavior.

Indexed as

choiceconservationsocial media

Identifiers

PMID41709875
PMCPMC12910511

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.