TY - JOUR
T1 - How to study the neural mechanisms of multiple tasks
AU - Yang, Guangyu Robert
AU - Cole, Michael W.
AU - Rajan, Kanaka
N1 - Publisher Copyright:
© 2019
PY - 2019/10
Y1 - 2019/10
N2 - Most biological and artificial neural systems are capable of completing multiple tasks. However, the neural mechanism by which multiple tasks are accomplished within the same system is largely unclear. We start by discussing how different tasks can be related, and methods to generate large sets of inter-related tasks to study how neural networks and animals perform multiple tasks. We then argue that there are mechanisms that emphasize either specialization or flexibility. We will review two such neural mechanisms underlying multiple tasks at the neuronal level (modularity and mixed selectivity), and discuss how different mechanisms can emerge depending on training methods in neural networks.
AB - Most biological and artificial neural systems are capable of completing multiple tasks. However, the neural mechanism by which multiple tasks are accomplished within the same system is largely unclear. We start by discussing how different tasks can be related, and methods to generate large sets of inter-related tasks to study how neural networks and animals perform multiple tasks. We then argue that there are mechanisms that emphasize either specialization or flexibility. We will review two such neural mechanisms underlying multiple tasks at the neuronal level (modularity and mixed selectivity), and discuss how different mechanisms can emerge depending on training methods in neural networks.
UR - http://www.scopus.com/inward/record.url?scp=85071951786&partnerID=8YFLogxK
U2 - 10.1016/j.cobeha.2019.07.001
DO - 10.1016/j.cobeha.2019.07.001
M3 - Review article
AN - SCOPUS:85071951786
SN - 2352-1546
VL - 29
SP - 134
EP - 143
JO - Current Opinion in Behavioral Sciences
JF - Current Opinion in Behavioral Sciences
ER -