Control of saccadic latency in a dynamic environment: allocation of saccades in time follows the matching law

Abstract

When exploring the visual environment, one uses saccades to shift gaze and fixation to gather spatially and temporally localized information. We propose that the temporal structure of our environment should constrain the temporal allocation of saccades. Here we probe the possibility of learning to control saccadic latencies in a choice paradigm. Six participants made saccades within 80–300 ms following a target horizontally stepping by 10° between two fixed locations. For each participant we constructed two classes of latencies, “short” and “long,” using the first and last quartiles of the individual baseline distribution (e.g., [80;152] ms and [185;300] ms, respectively). We then concurrently reinforced each class in three blocked conditions across ~60 experimental sessions per participant, using different reinforcement probabilities such that the relative ratio of reinforcement rates for short vs. long latencies was 9/1, 1/9, or 1/1. Latency distributions followed the reinforcement conditions: distributions shifted toward the shorter or longer values or became strongly bimodal. Moreover, the relative rates of short over long latencies matched the relative rates of reinforcers earned for the corresponding latencies (slope up to 0.95), which reveals the ability to choose when to saccade. Our results reveal that learned contingencies considerably affect the allocation of saccades in time and are in line with recent studies on the temporal adjustment of behavior to dynamic environments. This study provides strong evidence for fine operant control of saccadic latency, supporting the hypothesis of a cost-benefit control of saccade latencies.NEW & NOTEWORTHY Saccades may be regarded as an information-foraging behavior mostly concerned with the spatial localization of objects, yet our world is dynamic and environmental temporal regularities should also affect saccade decisions. We present behavioral data from a choice task establishing that humans can learn to choose their saccadic latencies depending on the reinforcement contingencies. This suggests a cost-benefit-based policy that takes into account the learned temporal properties of the environmental contingencies for controlling saccade triggering.