GitHub - JenniferLcook/social_learning: Scripts for analysing data from social learning tasks based on Behrens, et al. (2008, Nature 456, 245–249). Scripts are adapted from those used in Diaconescu et al. (2014, PLOS CB 10: e1003952) which are available here: http://www.translationalneuromodeling.org/tapas.

JenniferLcook / social_learning Public

Notifications You must be signed in to change notification settings
Fork 0
Star 1

Scripts for analysing data from social learning tasks based on Behrens, et al. (2008, Nature 456, 245–249). Scripts are adapted from those used in Diaconescu et al. (2014, PLOS CB 10: e1003952) which are available here: http://www.translationalneuromodeling.org/tapas.

1 star 0 forks Branches Tags Activity

Star

Notifications

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 11 Commits
Readme.txt		Readme.txt
rw_softmax_constant_weight_social_reward.m		rw_softmax_constant_weight_social_reward.m
rw_softmax_constant_weight_social_reward_config.m		rw_softmax_constant_weight_social_reward_config.m
rw_softmax_constant_weight_social_reward_namep.m		rw_softmax_constant_weight_social_reward_namep.m
rw_softmax_constant_weight_social_reward_transp.m		rw_softmax_constant_weight_social_reward_transp.m
tapas_rw_social_reward_vol.m		tapas_rw_social_reward_vol.m
tapas_rw_social_reward_vol_config.m		tapas_rw_social_reward_vol_config.m
tapas_rw_social_reward_vol_namep.m		tapas_rw_social_reward_vol_namep.m
tapas_rw_social_reward_vol_transp.m		tapas_rw_social_reward_vol_transp.m

Repository files navigation

This repository contains scripts for analysing data from social learning tasks based on Behrens, et al. (2008, Nature 456, 245–249). 
Scripts are adapted from those used in Diaconescu et al. (2014, PLOS CB 10: e1003952) which are part of the HGF toolbox, 
(released under the terms of the GNU General Public Licence (GPL), version 3; Copyright (C) 2012-2013 Christoph Mathys, TNU, UZH & ETHZ) 
and avilable here: http://www.translationalneuromodeling.org/tapas.

The scripts available in this repository have been adapted in order to provide separate alpha estimates for volatile and stable 
learning environments.