scholarly journals Neural Mechanisms for Executive Control of Speed-Accuracy Tradeoff

2020 ◽  
Author(s):  
Thomas R. Reppert ◽  
Richard P. Heitz ◽  
Jeffrey D. Schall
Keyword(s):  
Executive Control ◽  
Neural Mechanisms ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

scholarly journals Neural Mechanisms of Speed-Accuracy Tradeoff

Neuron ◽  
2012 ◽  
Vol 76 (3) ◽  
pp. 616-628 ◽  
Author(s):  
Richard P. Heitz ◽  
Jeffrey D. Schall
Keyword(s):  
Neural Mechanisms ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

scholarly journals Neural Mechanisms for Executive Control of Speed-Accuracy Tradeoff

2019 ◽  
Author(s):  
Thomas R. Reppert ◽  
Richard P. Heitz ◽  
Jeffrey D. Schall
Keyword(s):  
Visual Search ◽  
Frontal Cortex ◽  
Error Detection ◽  
Neural Mechanisms ◽  
Medial Frontal Cortex ◽  
List Type ◽  
Timing Errors ◽  
Supplementary Eye Field ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

SUMMARYThe balance of speed with accuracy requires error detection and performance adaptation. To date, neural concomitants of these processes have been investigated only with noninvasive measures. To provide the first neurophysiological description, macaque monkeys performed visual search under cued speed accuracy tradeoff (SAT). Monkeys changed SAT emphasis immediately after a cued switch while neuron discharges were sampled in medial frontal cortex area supplementary eye field (SEF). A multiplicity of SEF neurons signaled production of choice errors and timing errors. Modulation of SEF activity after choice errors predicted production of un-rewarded corrective saccades. Modulation of activity after timing errors signaled reward prediction error. Adaptation of performance during SAT of visual search was accomplished through pronounced changes in neural state from before search array presentation until after reward delivery. These results contextualize previous findings using noninvasive measures, complement neurophysiological findings in visuomotor structures, endorse the role of medial frontal cortex as a critic relative to the actor instantiated in visuomotor structures, and extend our understanding of the distributed neural mechanisms of SAT.HIGHLIGHTSMedial frontal cortex enables post-error adjustment during SATChoice and timing errors were signaled by partially overlapping neural poolsMedial frontal cortex can proactively modulate visuomotor processesMedial frontal cortex is to visuomotor circuits as critic to actor

Neuroticism and Speed-Accuracy Tradeoff in Self-Paced Speeded Mental Addition and Comparison

2010 ◽  
Vol 31 (3) ◽  
pp. 130-137 ◽  
Author(s):  
Hagen C. Flehmig ◽  
Michael B. Steinborn ◽  
Karl Westhoff ◽  
Robert Langner
Keyword(s):  
Reaction Time ◽  
Response Speed ◽  
Time Variability ◽  
Reaction Time Variability ◽  
Comparison Task ◽  
Processing Efficiency ◽  
Mental Addition ◽  
Speed Accuracy ◽  
The Relationship ◽  
Accuracy Tradeoff

Previous research suggests a relationship between neuroticism (N) and the speed-accuracy tradeoff in speeded performance: High-N individuals were observed performing less efficiently than low-N individuals and compensatorily overemphasizing response speed at the expense of accuracy. This study examined N-related performance differences in the serial mental addition and comparison task (SMACT) in 99 individuals, comparing several performance measures (i.e., response speed, accuracy, and variability), retest reliability, and practice effects. N was negatively correlated with mean reaction time but positively correlated with error percentage, indicating that high-N individuals tended to be faster but less accurate in their performance than low-N individuals. The strengthening of the relationship after practice demonstrated the reliability of the findings. There was, however, no relationship between N and distractibility (assessed via measures of reaction time variability). Our main findings are in line with the processing efficiency theory, extending the relationship between N and working style to sustained self-paced speeded mental addition.

Speed/accuracy tradeoff in directed forgetting

1997 ◽  
Author(s):  
Jeffry S. Kellogg ◽  
Xiangen Hu ◽  
William Marks
Keyword(s):  
Directed Forgetting ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

Trading accuracy for speed over the course of a decision

2021 ◽  
Author(s):  
Gerard Derosiere ◽  
David Thura ◽  
Paul Cisek ◽  
Julie Duqué
Keyword(s):  
Late Stage ◽  
Human Subjects ◽  
Sensory Information ◽  
Decision Task ◽  
Unique Extension ◽  
Dynamic Changes ◽  
Performance Accuracy ◽  
Accuracy Criterion ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

Humans and other animals often need to balance the desire to gather sensory information (to make the best choice) with the urgency to act, facing a speed-accuracy tradeoff (SAT). Given the ubiquity of SAT across species, extensive research has been devoted to understanding the computational mechanisms allowing its regulation at different timescales, including from one context to another, and from one decision to another. However, animals must frequently change their SAT on even shorter timescales - i.e., over the course of an ongoing decision - and little is known about the mechanisms that allow such rapid adaptations. The present study aimed at addressing this issue. Human subjects performed a decision task with changing evidence. In this task, subjects received rewards for correct answers but incurred penalties for mistakes. An increase or a decrease in penalty occurring halfway through the trial promoted rapid SAT shifts, favoring speeded decisions either in the early or in the late stage of the trial. Importantly, these shifts were associated with stage-specific adjustments in the accuracy criterion exploited for committing to a choice. Those subjects who decreased the most their accuracy criterion at a given decision stage exhibited the highest gain in speed, but also the highest cost in terms of performance accuracy at that time. Altogether, the current findings offer a unique extension of previous work, by suggesting that dynamic changes in accuracy criterion allow the regulation of the SAT within the timescale of a single decision.

Humanoid Robot Detection Using Deep Learning: A Speed-Accuracy Tradeoff

2018 ◽  
pp. 338-349 ◽  
Author(s):  
Mohammad Javadi ◽  
Sina Mokhtarzadeh Azar ◽  
Sajjad Azami ◽  
Saeed Shiry Ghidary ◽  
Soroush Sadeghnejad ◽  
...  
Keyword(s):  
Deep Learning ◽  
Humanoid Robot ◽  
Speed Accuracy ◽  
Accuracy Tradeoff
Sign in / Sign up

Export Citation Format

Share Document