IRCS Conference Room
Since Fall 2009, IRCS has collaborated with Penn's Computational Neuroscience program to present a series of lectures during the academic year.
Princeton Neuroscience Institute
Ramping vs stepping: unlocking single-trial dynamics in parietal cortex during decision-making
The firing rates of neurons in the macaque lateral intraparietal (LIP) area exhibit gradual ramping that is commonly believed to reflect the accumulation of sensory evidence during decision making. However, ramping that appears in trial-averaged spike responses does not necessarily indicate that the spike rate ramps on single trials; a ramping average rate could also arise from instantaneous steps that occur at different times on each trial. In this talk, I will describe an approach to this problem based on explicit statistical latent-dynamical models of spike trains. We examined responses recorded during sensory decision-making using a model with either ramping "accumulation-to-bound" dynamics or discrete "stepping" dynamics. In contrast to previous findings, we found that two thirds of choice-selective neurons in LIP are better explained by a model with stepping dynamics. We show that the stepping model provides an accurate description of LIP spike trains, allows for accurate decoding of decisions, and reveals decision-related structure that is hidden by conventional stimulus-aligned spike rasters.