A Common Cortical Circuit Mechanism for Perceptual Categorical Discrimination and Veridical Judgment

Feng Liu,Xiao-Jing Wang

doi:10.1371/journal.pcbi.1000253

Abstract

Perception involves two types of decisions about the sensory world: identification of stimulus features as analog quantities, or discrimination of the same stimulus features among a set of discrete alternatives. Veridical judgment and categorical discrimination have traditionally been conceptualized as two distinct computational problems. Here, we found that these two types of decision making can be subserved by a shared cortical circuit mechanism. We used a continuous recurrent network model to simulate two monkey experiments in which subjects were required to make either a two-alternative forced choice or a veridical judgment about the direction of random-dot motion. The model network is endowed with a continuum of bell-shaped population activity patterns, each representing a possible motion direction. Slow recurrent excitation underlies accumulation of sensory evidence, and its interplay with strong recurrent inhibition leads to decision behaviors. The model reproduced the monkey's performance as well as single-neuron activity in the categorical discrimination task. Furthermore, we examined how direction identification is determined by a combination of sensory stimulation and microstimulation. Using a population-vector measure, we found that direction judgments instantiate winner-take-all (with the population vector coinciding with either the coherent motion direction or the electrically elicited motion direction) when two stimuli are far apart, or vector averaging (with the population vector falling between the two directions) when two stimuli are close to each other. Interestingly, for a broad range of intermediate angular distances between the two stimuli, the network displays a mixed strategy in the sense that direction estimates are stochastically produced by winner-take-all on some trials and by vector averaging on the other trials, a model prediction that is experimentally testable. This work thus lends support to a common neurodynamic framework for both veridical judgment and categorical discrimination in perceptual decision making.

Highlights

Perceptual judgments involve detection, identification and discrimination of objects in a sensory scene [1,2]
Do they engage entirely separate brain mechanisms? In this work, we showed that these two types of decision making can be instantiated by a single cortical circuit
The results demonstrate that a common cortical circuit can perform both categorical discrimination and veridical judgment

Summary

Introduction

Perceptual judgments involve detection, identification and discrimination of objects in a sensory scene [1,2]. Those neural circuit models as well as abstract ramp-to-threshold models [26,27,28,29,30] are typically endowed with a simple architecture consisting of discrete neural pools, selective for categorical alternatives They are inadequate for exploring perceptual identification that requires neural representation of analog quantities, such as motion direction that can be an arbitrary angle between 0u and 360u. These studies centered on optimal algorithms for reading out a stimulus feature from sensory neural populations, such as inferring the orientation of a visual stimulus from neural activity in the primary visual cortex [33] and the direction of a motion stimulus from activity profiles across the middle temporal visual area (MT) [2] Such probabilistic inference is believed to occur in higher-order cortical areas downstream from primary sensory areas, and the underlying circuit mechanism remains unclear. It is unknown whether probabilistic estimation and categorical discrimination engage distinct decision processes or can be realized by a shared neural circuit mechanism

Methods

Results

Discussion

Conclusion