Although the brain is involved in powerful computations that construct our reality as well as control our motor and visual systems, many of these computations can take place in isolation from other animals. While this circuitry is interesting, it lacks the profound influence our social lives impact our biology. Because our world is largely socially constructed, we are fundamentally influenced by differing social interactions. Thus, it calls into question the neural basis of socially interacting brains and the specific computations that underlie a social interaction.

Classically, the way of understanding social behavior is through testing paradigms with which one animal is the subject. However, Dr. Weizhe Hong, an Assistant Professor in Neurobiology and Biological Chemistry at UCLA, joins us this week to uncover what is happening at the neuronal level between two socially interacting mice through simultaneous recordings of their brains.

In July of this year, the Hong lab published a paper in Cell displaying their findings: “when two animals interact, neural activity across their brains synchronize in a way that predicts how they will behave and how they form social dominance relationships” (Kingsbury et. al 2019, Cell). To get their findings, the lab utilizes a new microendoscopic calcium imaging technique.  They injected mice with an adeno-associated virus that selectively fluoresces neuronal cells after their release of calcium. Above the site of the viral injection, they implanted a gradient refractive index (GRIN) lens that gives higher resolution to the fluorescently-labeled cells during recordings. The GRIN lens and camera setup on a mouse is pictured below (NeuroNex):

Mosue.png

Specifically, Kingsbury et. al decided to record neuronal populations from the medial prefrontal cortex (mPFC), where it is known as the central hub that processes both social information as well as representations of social status (Utevsky and Platt, 2014; Wang et al., 2011; Zhou et al., 2017). From here, their experimental design was elegantly simple. They placed two mice in an open arena where they recorded both their behavior and neuronal firing in the mPFC. To understand the social interactions between the two mice, Kingsbury et. al annotated the videos for both non-social and social behaviors. They found that 66% of the behavior that the mice conducted was social behavior directed at their paired mouse. During these social interactions, the neural activity of the two animals were analyzed and showed a significant correlation compared to a randomized control, displayed below:  (Figure 1K,L)

Figure1

Utilizing this significant correlated neural activity between socially interacting mice, Kingsbury et. al placed mice of differing social rank to freely behave together. They found that in differing social rank interactions, there was a higher correlation of neural activity compared to similar ranked littermate controls. These and other findings from the paper have interestingly shown interbrain synchrony and “sets the groundwork for a more incisive investigation of the emergent neural properties of multi-individual systems, which may yet reveal a richer and deeper understanding of the social brain within this truly social world” (Kingsbury et. al, 2019, Cell).

To hear more about the work being done in Dr. Weizhe Hong’s lab, please join us at 4:00pm, Tuesday 10/1/2019 at the Marilyn G. Farquhar Seminar Room.

____________________________________________________________________________________________

Chiaki Santiago is a 1st year neurosciences PhD student currently rotating in Dr. Olivier George’s lab. You can find her on Twitter and LinkedIn.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s