Scale Invariant Contrasts of Response Latency Distributions

Individual differences in general speed lead to a positive correlation between the mean and standard deviation of mean latency. This “coarse” scaling effect causes the mean latency difference (MLD) to be spuriously correlated with general speed. Within individuals, the correlation between the mean and standard deviation of trial latencies leads contrasted distributions to increase their overlap as an MLD of fixed width is translated to the right. To address this “fine” scaling effect, contrasts based on within subject latency transformations including the logarithm, standardization, and ranking were evaluated and turned out to be distinctly superior to the MLD. Notably, the mean gaussian rank latency difference was internally consistent, eliminated fine scaling, meliorated coarse scaling, reduced correlations with general speed, increased statistical power to detect within subject and between group effects, and has the potential to increase the validity of inferences drawn from response latency data.

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

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.

Development and analysis of an operator steering model for teleoperated mobile robots under constant and variable latencies

SUMMARYLatency hinders a mobile robot teleoperator's ability to perform remote tasks. However, this effect is not well modeled. This paper develops a model for teleoperator steering behavior as a PD controller based on projected lateral displacement, which was tuned to reflect user performance determined by a 31-subject user study under constant and variable latency (having mean latencies between 0 and 750 ms). Additionally, we determined that operator performance under variable latency could be mapped to the expected performance of an equivalent constant latency. We then tested additional latency distributions in simulation and demonstrated equivalent steering performance among several different latency distributions.