Abstract
Anthropogenic climate change poses a substantial threat to societal living conditions. Here, we argue that neuroscience can substantially contribute to the fight against climate change and provide a framework and a roadmap to organize and prioritize neuroscience research in this domain. We outline how neuroscience can be used to: (1) investigate the negative impact of climate change on the human brain; (2) identify ways to adapt; (3) understand the neural substrates of decisions with pro-environmental and harmful outcomes; and (4) create neuroscience-based insights into communication and intervention strategies that aim to promote climate action. The paper is also a call to action for neuroscientists to join broader scientific efforts to tackle the existential environmental threats Earth is currently facing.
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References
IPCC Climate Change 2022: Impacts, Adaptation and Vulnerability (eds Pörtner, H.-O. et al.) (Cambridge Univ. Press, 2022).
Amel, E., Manning, C., Scott, B. & Koger, S. Beyond the roots of human inaction: fostering collective effort toward ecosystem conservation. Science 356, 275–279 (2017).
Addressing the Climate Crisis: An Action Plan for Psychologists (APA Task Force on Climate Change, 2022).
van der Linden, S. & Weber, E. U. Editorial overview: can behavioral science solve the climate crisis? Curr. Opin. Behav. Sci. 42, iii–viii (2021).
Aoki, R., Ito, A., Izuma, K. & Saijo, T. How can neuroscience contribute to the science of intergenerational sustainability? Preprint at https://econpapers.repec.org/RePEc:kch:wpaper:sdes-2020-11 (2020).
Sawe, N. & Chawla, K. Environmental neuroeconomics: how neuroscience can inform our understanding of human responses to climate change. Curr. Opin. Behav. Sci. 42, 147–154 (2021). A succinct outline of how neuroeconomics and neuroforecasting can be used to help understand human behaviour.
Wang, S. & van den Berg, B. Neuroscience and climate change: how brain recordings can help us understand human responses to climate change. Curr. Opin. Psychol. 42, 126–132 (2021).
Leeuwis, N., van Bommel, T. & Alimardani, M. A framework for application of consumer neuroscience in pro-environmental behavior change interventions. Front. Hum. Neurosci. 16, 886600 (2022).
Berman, M. G., Kardan, O., Kotabe, H. P., Nusbaum, H. C. & London, S. E. The promise of environmental neuroscience. Nat. Hum. Behav. 3, 414–417 (2019). This comment briefly motivates and highlights the utility of the field of environmental neuroscience.
Berman, M. G., Stier, A. J. & Akcelik, G. N. Environmental neuroscience. Am. Psychol. 74, 1039–1052 (2019).
Hebb, D. O. The Organization of Behavior: a Neuropsychological Theory (Wiley, 1949).
Blakemore, C. & Cooper, G. F. Development of the brain depends on the visual environment. Nature 228, 477–478 (1970).
Hackman, D. A., Farah, M. J. & Meaney, M. J. Socioeconomic status and the brain: mechanistic insights from human and animal research. Nat. Rev. Neurosci. 11, 651–659 (2010).
Peterson, B. S. et al. Effects of prenatal exposure to air pollutants (polycyclic aromatic hydrocarbons) on the development of brain white matter, cognition, and behavior in later childhood. JAMA Psychiatry 72, 531–540 (2015).
Pace, A., Luo, R., Hirsh-Pasek, K. & Golinkoff, R. M. Identifying pathways between socioeconomic status and language development. Annu. Rev. Linguist. 3, 285–308 (2017).
Neville, H. J. et al. Family-based training program improves brain function, cognition, and behavior in lower socioeconomic status preschoolers. Proc. Natl Acad. Sci. USA 110, 12138–12143 (2013).
Nielsen, K. S., Nicholas, K. A., Creutzig, F., Dietz, T. & Stern, P. C. The role of high-socioeconomic-status people in locking in or rapidly reducing energy-driven greenhouse gas emissions. Nat. Energy 6, 1011–1016 (2021).
Doell, K. C., Pärnamets, P., Harris, E. A., Hackel, L. M. & Van Bavel, J. J. Understanding the effects of partisan identity on climate change. Curr. Opin. Behav. Sci. 42, 54–59 (2021). This review summarizes social psychology and cognitive neuroscience research, outlining how partisan identities impact climate action.
Brosch, T. Affect and emotions as drivers of climate change perception and action: a review. Curr. Opin. Behav. Sci. 42, 15–21 (2021). This review article examines recent findings and emerging trends in the role of affect and emotion in climate change perceptions, and their potential to drive sustainable actions.
Hickman, C. et al. Climate anxiety in children and young people and their beliefs about government responses to climate change: a global survey. Lancet Planet. Health 5, e863–e873 (2021).
Hsiang, S. M., Burke, M. & Miguel, E. Quantifying the influence of climate on human conflict. Science 341, 1235367 (2013).
Ruszkiewicz, J. A. et al. Brain diseases in changing climate. Environ. Res. 177, 108637 (2019).
Mora, C., Counsell, C. W. W., Bielecki, C. R. & Louis, L. V. Twenty-seven ways a heat wave can kill you: deadly heat in the era of climate change. Circ. Cardiovasc. Qual. Outcomes 10, e004233 (2017).
Gifford, R. The dragons of inaction: psychological barriers that limit climate change mitigation and adaptation. Am. Psychol. 66, 290–302 (2011).
Sawe, N. Using neuroeconomics to understand environmental valuation. Ecol. Econ. 135, 1–9 (2017).
Berkman, E. & Falk, E. Beyond brain mapping: using neural measures to predict real-world outcomes. Curr. Dir. Psychol. Sci. 22, 45–50 (2013). A perspective article that discusses the integration of neuroscience with traditional psychological methods to predict long-term behaviour, highlighting the potential for bridging the gap between laboratory research and real-world applications.
Karmarkar, U. R. & Yoon, C. Consumer neuroscience: advances in understanding consumer psychology. Curr. Opin. Psychol. 10, 160–165 (2016).
Brevers, D. et al. Brain mechanisms underlying prospective thinking of sustainable behaviours. Nat. Sustain. 4, 433–439 (2021).
Doell, K. C., Conte, B. & Brosch, T. Interindividual differences in environmentally relevant positive trait affect impacts sustainable behavior in everyday life. Sci. Rep. 11, 20423 (2021).
Falk, E. B., Berkman, E. T. & Lieberman, M. D. From neural responses to population behavior: neural focus group predicts population-level media effects. Psychol. Sci. 23, 439–445 (2012).
Kühn, S. et al. Spend time outdoors for your brain – an in-depth longitudinal MRI study. World J. Biol. Psychiatry 23, 201–207 (2021).
Tost, H. et al. Neural correlates of individual differences in affective benefit of real-life urban green space exposure. Nat. Neurosci. 22, 1389–1393 (2019).
Martin, L. et al. Nature contact, nature connectedness and associations with health, wellbeing and pro-environmental behaviours. J. Environ. Psychol. 68, 101389 (2020).
Zuo, J. et al. Impacts of heat waves and corresponding measures: a review. J. Clean. Prod. 92, 1–12 (2015).
Hsiang, S. M., Meng, K. C. & Cane, M. A. Civil conflicts are associated with the global climate. Nature 476, 438–441 (2011).
Zammit, C., Torzhenskaya, N., Ozarkar, P. D. & Calleja Agius, J. Neurological disorders vis-à-vis climate change. Early Hum. Dev. 155, 105217 (2021).
Orru, H., Ebi, K. L. & Forsberg, B. The interplay of climate change and air pollution on health. Curr. Environ. Health Rep. 4, 504–513 (2017).
O'Dell, K. et al. Estimated mortality and morbidity attributable to smoke plumes in the United States: not just a western US problem. GeoHealth 5, e2021GH000457 (2021).
Tsai, T. L. et al. Fine particulate matter is a potential determinant of Alzheimer’s disease: a systemic review and meta-analysis. Environ. Res. 177, 108638 (2019).
Wu, J. et al. Association between ambient air pollution and MRI-defined brain infarcts in health examinations in China. Int. J. Environ. Res. Public Health 18, 4325 (2021).
Debette, S. et al. Association of MRI markers of vascular brain injury with incident stroke, mild cognitive impairment, dementia, and mortality. Stroke 41, 600–606 (2010).
Clayton, S. Climate anxiety: psychological responses to climate change. J. Anxiety Disord. 74, 102263 (2020).
Clayton, S. & Karazsia, B. T. Development and validation of a measure of climate change anxiety. J. Environ. Psychol. 69, 101434 (2020).
Beaglehole, B. et al. Psychological distress and psychiatric disorder after natural disasters: systematic review and meta-analysis. Br. J. Psychiatry 213, 716–722 (2018).
Boccia, M. et al. Different neural modifications underpin PTSD after different traumatic events: an fMRI meta-analytic study. Brain Imaging Behav. 10, 226–237 (2016).
Cohen, S., Janicki-Deverts, D. & Miller, G. E. Psychological stress and disease. J. Am. Med. Assoc. 298, 1685–1687 (2007).
Sudimac, S., Sale, V. & Kühn, S. How nature nurtures: amygdala activity decreases as the result of a one-hour walk in nature. Mol. Psychiatry 27, 4446–4452 (2022). An empirical paper that helps to highlight the utility of leveraging neuroscience methodologies to understand the acute impact of urban versus green spaces on the brain.
Dadvand, P. et al. The association between lifelong greenspace exposure and 3-dimensional brain magnetic resonance imaging in Barcelona schoolchildren. Environ. Health Perspect. 126, 027012 (2018).
Litleskare, S., Macintyre, T. E. & Calogiuri, G. Enable, reconnect and augment: a new era of virtual nature research and application. Int. J. Environ. Res. Public Health 17, 1738 (2020).
Yeo, N. L. et al. What is the best way of delivering virtual nature for improving mood? An experimental comparison of high definition TV, 360° video, and computer generated virtual reality. J. Environ. Psychol. 72, 101500 (2020).
Mostajeran, F., Krzikawski, J., Steinicke, F. & Kühn, S. Effects of exposure to immersive videos and photo slideshows of forest and urban environments. Sci. Rep. 11, 3994 (2021).
Markowitz, D. M. & Bailenson, J. N. Virtual reality and the psychology of climate change. Curr. Opin. Psychol. 42, 60–65 (2021).
Meijers, M. H. C., Torfadóttir, R. H., Wonneberger, A. & Maslowska, E. Experiencing climate change virtually: the effects of virtual reality on climate change related cognitions, emotions, and behavior. Environ. Commun. https://doi.org/10.1080/17524032.2023.2229043 (2023).
Wolfe, U. & Lindeborg, H. Neuroscience and sustainability: an online module on ‘environmental neuroscience’. J. Undergrad. Neurosci. Educ. 17, A20–A25 (2018).
Lange, F. & Dewitte, S. Measuring pro-environmental behavior: review and recommendations. J. Environ. Psychol. 63, 92–100 (2019). A review of diverse pro-environmental behaviour measurement methods, many of which can be adaptable for neuroscience.
Sawe, N., Srirangarajan, T., Sahoo, A., Tang, G. S. & Knutson, B. Neural responses clarify how ecolabels promote sustainable purchases. NeuroImage 263, 119668 (2022).
Brosch, T., Stussi, Y., Desrichard, O. & Sander, D. Not my future? Core values and the neural representation of future events. Cogn. Affect. Behav. Neurosci. 18, 476–484 (2018).
Baumgartner, T., Langenbach, B. P., Gianotti, L. R. R., Müri, R. M. & Knoch, D. Frequency of everyday pro-environmental behaviour is explained by baseline activation in lateral prefrontal cortex. Sci. Rep. 9, 9 (2019).
Vezich, I. S., Gunter, B. C. & Lieberman, M. D. The mere green effect: an fMRI study of pro-environmental advertisements. Soc. Neurosci. 12, 400–408 (2017).
Guizar Rosales, E., Baumgartner, T. & Knoch, D. Interindividual differences in intergenerational sustainable behavior are associated with cortical thickness of the dorsomedial and dorsolateral prefrontal cortex. NeuroImage https://doi.org/10.1016/j.neuroimage.2022.119664 (2022).
Nash, K., Gianotti, L. R. R. & Knoch, D. A neural trait approach to exploring individual differences in social preferences. Front. Behav. Neurosci. 8, 458 (2014).
Sparkman, G. & Walton, G. M. Dynamic norms promote sustainable behavior, even if it is counternormative. Psychol. Sci. 28, 1663–1674 (2017).
de Bruin, D., van Baar, J. M., Rodríguez, P. L. & FeldmanHall, O. Shared neural representations and temporal segmentation of political content predict ideological similarity. Sci. Adv. 9, eabq5920 (2023).
Cacioppo, J. T., Cacioppo, S. & Petty, R. E. The neuroscience of persuasion: a review with an emphasis on issues and opportunities. Soc. Neurosci. 13, 129–172 (2018).
Kühn, S., Strelow, E. & Gallinat, J. Multiple ‘buy buttons’ in the brain: forecasting chocolate sales at point-of-sale based on functional brain activation using fMRI. NeuroImage 136, 122–128 (2016).
Knutson, B. & Genevsky, A. Neuroforecasting aggregate choice. Curr. Dir. Psychol. Sci. 27, 110–115 (2018). An excellent review about how neuroforecasting can be used to understand aggregate choice.
Genevsky, A., Yoon, C. & Knutson, B. When brain beats behavior: neuroforecasting crowdfunding outcomes. J. Neurosci. 37, 8625–8634 (2017).
Boksem, M. A. S. & Smidts, A. Brain responses to movie trailers predict individual preferences for movies and their population-wide commercial success. J. Mark. Res. 52, 482–492 (2015).
Langenbach, B. P., Savic, B., Baumgartner, T., Wyss, A. M. & Knoch, D. Mentalizing with the future: electrical stimulation of the right TPJ increases sustainable decision-making. Cortex 146, 227–237 (2022). An empirical paper demonstrating how neuroscience methodologies can be applied to answer questions related to sustainable behaviour.
Lamm, C., Bukowski, H. & Silani, G. From shared to distinct self-other representations in empathy: evidence from neurotypical function and socio-cognitive disorders. Phil. Trans. R. Soc. B 371, 20150083 (2016).
Langenbach, B. P., Baumgartner, T., Cazzoli, D., Müri, R. M. & Knoch, D. Inhibition of the right dlPFC by theta burst stimulation does not alter sustainable decision-making. Sci. Rep. 9, 13852 (2019).
MAGNETOM Prisma: Environmental Product Declaration (Siemens Healthcare GmbH, 2020).
Greenhouse Gas Equivalencies Calculator (US EPA, 2015); https://www.epa.gov/energy/greenhouse-gas-equivalencies-calculator
van Ewijk, S. & Hoekman, P. Emission reduction potentials for academic conference travel. J. Ind. Ecol. 25, 778–788 (2021).
Capstick, S. et al. Civil disobedience by scientists helps press for urgent climate action. Nat. Clim. Change 12, 773–774 (2022).
Rae, C. L., Farley, M., Jeffery, K. J. & Urai, A. E. Climate crisis and ecological emergency: why they concern (neuro)scientists, and what we can do. Brain Neurosci. Adv. 6, 239821282210754 (2022). This paper suggests different actions that scientists, especially neuroscientists, can take to make their professions more sustainable.
Lange, F. et al. Beyond self-reports: a call for more behavior in environmental psychology. J. Environ. Psychol. https://doi.org/10.1016/j.jenvp.2023.101965 (2023).
Doell, K. C. Megastudies to test the efficacy of behavioural interventions. Nat. Rev. Psychol. 2, 263–263 (2023).
ENIGMA-Environment (2023); https://enigma.ini.usc.edu/ongoing/enigma-environment/
Weisberg, D. S., Taylor, J. C. V. & Hopkins, E. J. Deconstructing the seductive allure of neuroscience explanations. Judgm. Decis. Mak. 10, 429–441 (2015).
LeDoux, J. The amygdala. Curr. Biol. 17, R868–R874 (2007).
Behbehani, M. M. Functional characteristics of the midbrain periaqueductal gray. Prog. Neurobiol. 46, 575–605 (1995).
Schacter, D. L. et al. The future of memory: remembering, imagining, and the brain. Neuron 76, 677–694 (2012).
Ballard, K. & Knutson, B. Dissociable neural representations of future reward magnitude and delay during temporal discounting. NeuroImage 45, 143–150 (2009).
Hare, T., Hakimi, S. & Rangel, A. Activity in dlPFC and its effective connectivity to vmPFC are associated with temporal discounting. Front. Neurosci. 8, 50 (2014).
Canessa, N. et al. The functional and structural neural basis of individual differences in loss aversion. J. Neurosci. 33, 14307–14317 (2013).
Levin, I. et al. A neuropsychological approach to understanding risk-taking for potential gains and losses. Front. Neurosci. 6, 15 (2012).
Schurz, M., Aichhorn, M., Martin, A. & Perner, J. Common brain areas engaged in false belief reasoning and visual perspective taking: a meta-analysis of functional brain imaging studies. Front. Hum. Neurosci. 7, 712 (2013).
Knutson, B. & Greer, S. M. Anticipatory affect: neural correlates and consequences for choice. Phil. Trans. R. Soc. B 363, 3771–3786 (2008).
Ruff, C. C. & Fehr, E. The neurobiology of rewards and values in social decision making. Nat. Rev. Neurosci. 15, 549–562 (2014).
Baxter, M. G. & Murray, E. A. The amygdala and reward. Nat. Rev. Neurosci. 3, 563–573 (2002).
Kahnt, T., Heinzle, J., Park, S. Q. & Haynes, J.-D. Decoding different roles for vmPFC and dlPFC in multi-attribute decision making. NeuroImage 56, 709–715 (2011).
Prévost, C., Pessiglione, M., Météreau, E., Cléry-Melin, M.-L. & Dreher, J.-C. Separate valuation subsystems for delay and effort decision costs. J. Neurosci. 30, 14080–14090 (2010).
Lopez-Gamundi, P. et al. The neural basis of effort valuation: a meta-analysis of functional magnetic resonance imaging studies. Neurosci. Biobehav. Rev. 131, 1275–1287 (2021).
Niendam, T. A. et al. Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions. Cogn. Affect. Behav. Neurosci. 12, 241–268 (2012).
Badre, D. & Nee, D. E. Frontal cortex and the hierarchical control of behavior. Trends Cogn. Sci. 22, 170–188 (2017).
Poldrack, R. Can cognitive processes be inferred from neuroimaging data? Trends Cogn. Sci. 10, 59–63 (2006).
Environmental Psychology: An Introduction (John Wiley & Sons, 2018).
Alcock, I., White, M. P., Pahl, S., Duarte-Davidson, R. & Fleming, L. E. Associations between pro-environmental behaviour and neighbourhood nature, nature visit frequency and nature appreciation: evidence from a nationally representative survey in England. Environ. Int. 136, 105441 (2020).
Mertens, S., Herberz, M., Hahnel, U. J. J. & Brosch, T. The effectiveness of nudging: a meta-analysis of choice architecture interventions across behavioral domains. Proc. Natl Acad. Sci. USA 119, e2107346118 (2022).
Acknowledgements
This work was supported in part by a grant from the Swiss National Science Foundation to K.C.D. (grant no. P400PS_190997), a National Science Foundation Smart and Connected Communities grant (grant no. CNS-1952050) to M.G.B., and grants from the John Templeton Foundation and Jigsaw to J.J.V.B. We would like to thank B. Todorova for her assistance with editing and formatting the manuscript.
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Doell, K.C., Berman, M.G., Bratman, G.N. et al. Leveraging neuroscience for climate change research. Nat. Clim. Chang. 13, 1288–1297 (2023). https://doi.org/10.1038/s41558-023-01857-4
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DOI: https://doi.org/10.1038/s41558-023-01857-4
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