TY - JOUR
T1 - Dynamic divisive normalization predicts time-varying value coding in decision-related circuits
AU - Louie, Kenway
AU - Lofaro, Thomas
AU - Webb, Ryan
AU - Glimcher, Paul W.
N1 - Publisher Copyright:
© 2014 the authors.
PY - 2014/11/26
Y1 - 2014/11/26
N2 - Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding.
AB - Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding.
KW - Computational modeling
KW - Decision-making
KW - Divisive normalization
KW - Dynamical system
KW - Reward
UR - http://www.scopus.com/inward/record.url?scp=84911944263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84911944263&partnerID=8YFLogxK
U2 - 10.1523/JNEUROSCI.2851-14.2014
DO - 10.1523/JNEUROSCI.2851-14.2014
M3 - Article
C2 - 25429145
AN - SCOPUS:84911944263
SN - 0270-6474
VL - 34
SP - 16046
EP - 16057
JO - Journal of Neuroscience
JF - Journal of Neuroscience
IS - 48
ER -