Abstract
A key goal of social neuroscience is to understand the inter-brain neural relationship-the relationship between the neural activity of socially interacting individuals. Decades of research investigating this relationship have focused on the similarity in neural activity across brains. Here, we instead asked how neural activity differs between brains, and how that difference evolves alongside activity patterns shared between brains. Applying this framework to bats engaged in spontaneous social interactions revealed two complementary phenomena characterizing the inter-brain neural relationship: fast fluctuations of activity difference across brains unfolding in parallel with slow activity covariation across brains. A model reproduced these observations and generated multiple predictions that we confirmed using experimental data involving pairs of bats and a larger social group of bats. The model suggests that a simple computational mechanism involving positive and negative feedback could explain diverse experimental observations regarding the inter-brain neural relationship.
Highlights
IntroductionWhat is the relationship between the neural activity of socially interacting individuals?This central question in social neuroscience has motivated nearly two decades of research spanning a diversity of species and methodologies (e.g. Babiloni and Astolfi, 2014; Dumas et al., 2011; Freiwald, 2020; Hasson et al, 2012; Hasson and Frith, 2016; Hoffmann et al, 2019; Kingsbury and Hong, 2020; Koike et al, 2015; Konvalinka and Roepstorff, 2012; Liu et al., 2018; Montague et al, 2002; Redcay and Schilbach, 2020; Scholkmann et al, 2013; Schoot et al., 2016; Testard et al, 2021; Tseng et al, 2018; Wass et al, 2020)
The analyses in the main text focus on 30-150 Hz local field potential (LFP) power, as previous work has shown that this frequency range exhibits strong inter-brain correlation in bats (Zhang and Yartsev, 2019)
It is well known that neural activity is correlated between the brains of socially interacting individuals, in mice, bats, and humans (e.g., Dikker et al, 2014; Kingsbury et al, 2019; Kinreich et al, 2017; Levy et al, 2017; Montague et al, 2002; Piazza et al, 2020; Spiegelhalder et al, 2014; Stolk et al, 2014; Zadbood et al, 2017; Zhang and Yartsev, 2019)
Summary
What is the relationship between the neural activity of socially interacting individuals?This central question in social neuroscience has motivated nearly two decades of research spanning a diversity of species and methodologies (e.g. Babiloni and Astolfi, 2014; Dumas et al., 2011; Freiwald, 2020; Hasson et al, 2012; Hasson and Frith, 2016; Hoffmann et al, 2019; Kingsbury and Hong, 2020; Koike et al, 2015; Konvalinka and Roepstorff, 2012; Liu et al., 2018; Montague et al, 2002; Redcay and Schilbach, 2020; Scholkmann et al, 2013; Schoot et al., 2016; Testard et al, 2021; Tseng et al, 2018; Wass et al, 2020). Babiloni and Astolfi, 2014; Dumas et al., 2011; Freiwald, 2020; Hasson et al, 2012; Hasson and Frith, 2016; Hoffmann et al, 2019; Kingsbury and Hong, 2020; Koike et al, 2015; Konvalinka and Roepstorff, 2012; Liu et al., 2018; Montague et al, 2002; Redcay and Schilbach, 2020; Scholkmann et al, 2013; Schoot et al., 2016; Testard et al, 2021; Tseng et al, 2018; Wass et al, 2020) Despite this diversity, most research has tackled the study of inter-brain relationship from a single perspective: considering the neural activity of two interacting individuals as the two variables of interest and searching for similarities between them. We applied this approach to neural activity simultaneously recorded from socially interacting Egyptian fruit bats (Rousettus aegyptiacus), a mammalian species known for its high level of sociality
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