On the Number of Neurons and Time Scale of Integration Underlying the Formation of Percepts in the Brain

All of our perceptual experiences arise from the activity of neural populations. Here we study the formation of such percepts under the assumption that they emerge from a linear readout, i.e., a weighted sum of the neurons’ firing rates. We show that this assumption constrains the trial-to-trial covariance structure of neural activities and animal behavior. The predicted covariance structure depends on the readout parameters, and in particular on the temporal integration window w and typical number of neurons K used in the formation of the percept. Using these predictions, we show how to infer the readout parameters from joint measurements of a subject’s behavior and neural activities. We consider three such scenarios: (1) recordings from the complete neural population, (2) recordings of neuronal sub-ensembles whose size exceeds K, and (3) recordings of neuronal sub-ensembles that are smaller than K. Using theoretical arguments and artificially generated data, we show that the first two scenarios allow us to recover the typical spatial and temporal scales of the readout. In the third scenario, we show that the readout parameters can only be recovered by making additional assumptions about the structure of the full population activity. Our work provides the first thorough interpretation of (feed-forward) percept formation from a population of sensory neurons. We discuss applications to experimental recordings in classic sensory decision-making tasks, which will hopefully provide new insights into the nature of perceptual integration.Author Summary: This article deals with the interpretation of neural activities during perceptual decision-making tasks, where animals must assess the value of a sensory stimulus and take a decision on the basis of their percept. A “standard model” for these tasks has progressively emerged, whence the animal’s percept and subsequent choice on each trial are obtained from a linear integration of the activity of sensory neurons. However, up to date, there has been no principled method to estimate the parameters of this model: mainly, the typical number of neurons K from the population involved in conveying the percept, and the typical time scale w during which these neurons’ activities are integrated. In this article, we propose a novel method to estimate these quantities from experimental data, and thus assess the validity of the standard model of percept formation. In the process, we clarify the predictions of the standard model regarding two classic experimental measures in these tasks: sensitivity, which is the animal’s ability to distinguish nearby stimulus values, and choice signals, which assess the amount of correlation between the activity of single neurons and the animal’s ultimate choice on each trial.