Rival Political Partisans May Have Different Brain Patterns When Processing Information
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US politics has become increasingly divided along partisan lines since the election of Donald Trump as President in 2016. What drives political partisanship in the brain? A new study has used neuroimaging to explore how political ideology and brain activity are linked.
The research is published in Science Advances.
Politically charged words
The study was conducted by researchers at Brown University, led by senior author Dr. Oriel FeldmanHall. They recruited 44 participants who self-reported their political ideologies as liberal or conservative. The researchers then had their participants perform two tasks from inside a functional magnetic resonance imaging (fMRI) machine while they monitored their brain activity.
In the first task, the participants were presented with a list of 30 words that had been pre-rated as particularly political by a separate participant group using Amazon’s Mechanical Turk crowdsourcing platform. These words included “abortion”, “addiction” and “foodstamps”. These were matched to 30 non-political words – including “harp”, “slug” and “wrench”.
Outside the fMRI machine, the participants were asked to arrange these words across a 2D space according to their similarity, with more closely related words placed next to each other. Once in the scanner, these words were flashed up in front of participants, who were then asked to rate them as political or non-political.
The participants were next shown clips of both neural news broadcasts and politically charged clips from a 2016 vice presidential debate inside the scanner.
The results of the study showed that volunteers with similar partisan beliefs had statistically significant similarities in how they represented words and processed information. Political bedfellows grouped the words in similar patterns and had similar activity patterns in their amygdalas, the emotional processing center of the brain.
FeldmanHall and colleagues suggest that these altered activity patterns may affect how individuals process incoming information from media sources, underlying an increasingly biased political landscape.
The researchers conclude, “Given that political polarization poses great challenges to communication and cooperation between parties and hinders political decision-making by complicating compromises between ideological extremes, gaining a better understanding of how political polarization arises is of paramount importance.”
Reference: de Bruin D, van Baar JM, Rodríguez PL and FeldmanHall O. Shared neural representations and temporal segmentation of political content predict ideological similarity. Sci. Adv. 2023;9. doi: 10.1126/sciadv.abq5920
This article is a rework of a press release issued by Brown University. Material has been edited for length and content.