RT Journal Article
SR Electronic
T1 Identifying the most influential features of neural population responses for information encoding and behavior
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 577379
DO 10.1101/577379
A1 Ramon Nogueira
A1 Nicole E. Peltier
A1 Akiyuki Anzai
A1 Gregory C. DeAngelis
A1 Julio Martínez-Trujillo
A1 Rubén Moreno-Bote
YR 2019
UL http://biorxiv.org/content/early/2019/03/14/577379.abstract
AB Identifying the features of population responses that are relevant to the amount of information encoded by neuronal populations is a crucial step toward understanding the neural code. Statistical features such as tuning properties, individual and shared response variability, and global activity modulations could all affect the amount of information encoded and modulate behavioral performance. We show that two features in particular affect information: the modulation of population responses across conditions and the projection of the inverse population variability along the modulation axis. We demonstrate that fluctuations of these two quantities are correlated with fluctuations of behavioral performance in various tasks and brain regions. In contrast, fluctuations in mean correlations among neurons and global activity have negligible or inconsistent effects on the amount of information encoded and behavioral performance. Our results are consistent with predictions of a model that optimally decodes population responses, which suggests that in our behavioral tasks the readout of information is near-optimal.