Advancements in neuroscience research present opportunities and challenges,requiring substantial resources and funding.To address this,we describe here“Poke And Delayed Drink Intertemporal Choice Task(POKE-ADDICT)”,...Advancements in neuroscience research present opportunities and challenges,requiring substantial resources and funding.To address this,we describe here“Poke And Delayed Drink Intertemporal Choice Task(POKE-ADDICT)”,an open-source,versatile,and cost-effective apparatus for intertemporal choice testing in rodents.This allows quantification of delay discounting(DD),a cross-species phenomenon observed in decision making which provides valuable insights into higher-order cognitive functioning.In DD,the subjective value of a delayed reward is reduced as a function of the delay for its receipt.Using our apparatus,we implemented an effective intertemporal choice paradigm for the quantification of DD based on an adjusting delayed amount(ADA)algorithm using mango juice as a reward.Our paradigm requires limited training,a few 3D-printed parts and inexpensive electrical components,including a Raspberry Pi control unit.Furthermore,it is compatible with several in vivo procedures and the use of nose pokes instead of levers allows for faster task learning.Besides the main application described here,the apparatus can be further extended to implement other behavioral tests and protocols,including standard operant conditioning.In conclusion,we describe a versatile and cost-effective design based on Raspberry Pi that can support research in animal behavior,decision making and,more specifically,delay discounting.展开更多
文摘Advancements in neuroscience research present opportunities and challenges,requiring substantial resources and funding.To address this,we describe here“Poke And Delayed Drink Intertemporal Choice Task(POKE-ADDICT)”,an open-source,versatile,and cost-effective apparatus for intertemporal choice testing in rodents.This allows quantification of delay discounting(DD),a cross-species phenomenon observed in decision making which provides valuable insights into higher-order cognitive functioning.In DD,the subjective value of a delayed reward is reduced as a function of the delay for its receipt.Using our apparatus,we implemented an effective intertemporal choice paradigm for the quantification of DD based on an adjusting delayed amount(ADA)algorithm using mango juice as a reward.Our paradigm requires limited training,a few 3D-printed parts and inexpensive electrical components,including a Raspberry Pi control unit.Furthermore,it is compatible with several in vivo procedures and the use of nose pokes instead of levers allows for faster task learning.Besides the main application described here,the apparatus can be further extended to implement other behavioral tests and protocols,including standard operant conditioning.In conclusion,we describe a versatile and cost-effective design based on Raspberry Pi that can support research in animal behavior,decision making and,more specifically,delay discounting.
