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Computa-onal phenotyping using a social hierarchy probe

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Citation

Vilares, I., Hula, A., Nolte, T., Cui, Z., Lohrenz, T., Dayan, P., et al. (2017). Computa-onal phenotyping using a social hierarchy probe. Poster presented at 15th Annual Meeting of the Society for NeuroEconomics (SNE 2017), Toronto, Canada.


Cite as: https://hdl.handle.net/21.11116/0000-0005-1F44-D
Abstract
IntroducPon: Borderline Personality Disorder (BPD) and AnP-Social Personality Disorder (ASPD) are
psychopathologies characterized by profoundly aberrant interpersonal behaviour that strongly affect the
lives of both individual paPents and those around them. BPDs and ASPDs share many behavioural
characterisPcs, such as impulsivity and difficulty in sustaining long-lasPng social relaPonships, and
although they are considered different disorders, the disPncPon between them is somePmes blurred.
One notable disPncPon is the manner of interpersonal interacPons, with ASPD paPents tending to
exploit others, whereas BPD paPents tend to be exploited themselves. However, this disPncPon has yet
to be fashioned into a quanPfiable psychometric instrument. Methods: Here, we have parPcipants play a
mulP-round Social Hierarchy decision-making paradigm (119 controls, 219 BPDs and 23 ASPDs), and
applied computaPonal models to the obtained behaviour. Results: We found that ASPD parPcipants,
when playing the Social Hierarchy game, gave significantly less to the other player when compared to
Controls and BPDs. Furthermore, ASPDs challenged more, were in the dominant posiPon more o{en,
used more money to defend their alpha posiPon, and le{ their opponent with lower final earnings
compared to BPDs and Controls. BPDs, on the other hand, gave more to the other player compared to both ASPDs and controls, and le{ their opponent with more money. Indeed, BPDs were the only
populaPon of the three for whom both the parPcipant and their opponent finished with the same final
earnings. A logisPc regression model relaPng the decision to challenge to the transfer amount indicated
further differences between the populaPons: BPDs' decisions to challenge seemed more sensiPve to the
amount of money transferred by the opponent as compared to controls, while for ASPDs the opposite
paSern was observed. We are also developing a reinforcement-learning computaPonal model that takes
into account inequity aversion (both guilt and envy), as well as an intrinsic value for dominance and a
drive to remain in charge (alpha). Discussion: Our results suggest that ASPDs are less prosocial and value
social dominance more than healthy controls and BPDs, whilst the laSer are parPcularly sensiPve to
social signals, and offer specific computaPonal parameters that can be used to quanPtaPvely
characterize and phenotype each individual. These results open promising avenues by which different
psychiatric disease states could be characterized and disPnguished at the mechanisPc level, and offer a
tool by which to benchmark different treatment outcomes.