Trust games of various kinds have been used in behavioural economics and psychology research (see [34 ]). In particular, the MRT we used was based on variants in several earlier studies (see examples in [17 (link), 35 , 36 ]).
The current MRT was first modeled using regression models (see [16 (link)]) of various depths: one step models for the increase/decrease of the amount sent to the partner and models which track the effects of more distant investments/repayments. These models generated signals of increases and decreases in investments and returns that were correlated with fMRI data. One seminal study on the effect of BPD in the trustgame by King-Casas et al. (see [6 ]) included the concept of “coaxing” (repaying substanially more than the fair split) the partner (back) into cooperating/trust whenever trust was running low, as signified by small investments.
Furthermore, an earlier study (see [37 (link)]) used clustering to associate trustgame investment and repayment levels to various clinical populations.
An I-POMDP generative model for the trust task which included inequality aversion, inference and theory of mind level was previously proposed [8 ]. This model was later refined rather substantially to include faster calculation and planning as a parameter [10 (link)].
The I-POMDP framework itself has been used in a considerable number of studies. Notable among these are investigations of the depth of tactical reasoning directly in competitive games (see [38 –40 ]). It has also been used for deriving optimal strategies in repeated games (see [41 ]).
The benefits of a variant of the framework for fitting human behavioural data were recently exhibited in [42 ].
The current MRT was first modeled using regression models (see [16 (link)]) of various depths: one step models for the increase/decrease of the amount sent to the partner and models which track the effects of more distant investments/repayments. These models generated signals of increases and decreases in investments and returns that were correlated with fMRI data. One seminal study on the effect of BPD in the trustgame by King-Casas et al. (see [6 ]) included the concept of “coaxing” (repaying substanially more than the fair split) the partner (back) into cooperating/trust whenever trust was running low, as signified by small investments.
Furthermore, an earlier study (see [37 (link)]) used clustering to associate trustgame investment and repayment levels to various clinical populations.
An I-POMDP generative model for the trust task which included inequality aversion, inference and theory of mind level was previously proposed [8 ]. This model was later refined rather substantially to include faster calculation and planning as a parameter [10 (link)].
The I-POMDP framework itself has been used in a considerable number of studies. Notable among these are investigations of the depth of tactical reasoning directly in competitive games (see [38 –40 ]). It has also been used for deriving optimal strategies in repeated games (see [41 ]).
The benefits of a variant of the framework for fitting human behavioural data were recently exhibited in [42 ].
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