Modeling attentional modulation of population-wide neuronal variability in visual cortex


 Neuronal variability is a reflection of recurrent circuitry and cellular physiology, and its modulation is a reliable signature of cognitive and processing state. A pervasive yet puzzling feature of cortical circuits is that despite their complex wiring, population-wide shared spiking variability is low dimensional. Current circuit models cannot internally produce low dimensional shared variability, and rather assume that it is inherited from outside the circuit.  We show that differential attentional modulation of shared variability within and between cortical areas is difficult to explain with externally imposed variability. However, if the spatial and temporal scales of inhibitory coupling match physiology, network models internally generate the low dimensional shared variability of our multi-electrode recordings. Further, top-down modulation of inhibitory neurons in our model provides a parsimonious mechanism that controls population-wide variability in agreement with experimental results.  Our work extend simplified cortical models to identify how overlooked circuit and physiology details are needed to explain previously mysterious population-wide shared variability. 

Thursday, December 13, 2018 - 12:00

704 Thackeray 

Speaker Information
Chengcheng Huang
University of Pittsburgh