scholarly journals fMRI Evidence for a Dual Process Account of the Speed-Accuracy Tradeoff in Decision-Making

PLoS ONE ◽  
2008 ◽  
Vol 3 (7) ◽  
pp. e2635 ◽  
Author(s):  
Jason Ivanoff ◽  
Philip Branning ◽  
René Marois
Keyword(s):  
Decision Making ◽  
Dual Process ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

scholarly journals Inhibition of Pre–Supplementary Motor Area by Continuous Theta Burst Stimulation Leads to More Cautious Decision-making and More Efficient Sensory Evidence Integration

2017 ◽  
Vol 29 (8) ◽  
pp. 1433-1444 ◽  
Author(s):  
Tuğçe Tosun ◽  
Dilara Berkay ◽  
Alexander T. Sack ◽  
Yusuf Ö. Çakmak ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Decision Threshold ◽  
Theta Burst Stimulation ◽  
Burst Stimulation ◽  
Sensory Evidence ◽  
Speed Accuracy ◽  
Theta Burst ◽  
Continuous Theta Burst Stimulation ◽  
Accuracy Tradeoff ◽  
Evidence Integration

Decisions are made based on the integration of available evidence. The noise in evidence accumulation leads to a particular speed–accuracy tradeoff in decision-making, which can be modulated and optimized by adaptive decision threshold setting. Given the effect of pre-SMA activity on striatal excitability, we hypothesized that the inhibition of pre-SMA would lead to higher decision thresholds and an increased accuracy bias. We used offline continuous theta burst stimulation to assess the effect of transient inhibition of the right pre-SMA on the decision processes in a free-response two-alternative forced-choice task within the drift diffusion model framework. Participants became more cautious and set higher decision thresholds following right pre-SMA inhibition compared with inhibition of the control site (vertex). Increased decision thresholds were accompanied by an accuracy bias with no effects on post-error choice behavior. Participants also exhibited higher drift rates as a result of pre-SMA inhibition compared with the vertex inhibition. These results, in line with the striatal theory of speed–accuracy tradeoff, provide evidence for the functional role of pre-SMA activity in decision threshold modulation. Our results also suggest that pre-SMA might be a part of the brain network associated with the sensory evidence integration.

scholarly journals Adaptive integration of habits into depth-limited planning defines a habitual-goal–directed spectrum

2016 ◽  
Vol 113 (45) ◽  
pp. 12868-12873 ◽  
Author(s):  
Mehdi Keramati ◽  
Peter Smittenaar ◽  
Raymond J. Dolan ◽  
Peter Dayan
Keyword(s):  
Decision Making ◽  
Decision Process ◽  
Time Pressure ◽  
Human Subjects ◽  
Mental Simulation ◽  
Adaptive Integration ◽  
Accurate Evaluation ◽  
The Cost ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

Behavioral and neural evidence reveal a prospective goal-directed decision process that relies on mental simulation of the environment, and a retrospective habitual process that caches returns previously garnered from available choices. Artificial systems combine the two by simulating the environment up to some depth and then exploiting habitual values as proxies for consequences that may arise in the further future. Using a three-step task, we provide evidence that human subjects use such a normative plan-until-habit strategy, implying a spectrum of approaches that interpolates between habitual and goal-directed responding. We found that increasing time pressure led to shallower goal-directed planning, suggesting that a speed-accuracy tradeoff controls the depth of planning with deeper search leading to more accurate evaluation, at the cost of slower decision-making. We conclude that subjects integrate habit-based cached values directly into goal-directed evaluations in a normative manner.

scholarly journals Decision Making by Ensembles of Accumulators

2020 ◽  
Author(s):  
Gregory Edward Cox ◽  
Gordon D. Logan ◽  
Jeffrey Schall ◽  
Thomas Palmeri
Keyword(s):  
Decision Making ◽  
Response Times ◽  
Computational Framework ◽  
Neural Ensembles ◽  
High Level ◽  
Speed Accuracy ◽  
The Relationship ◽  
Different Levels ◽  
Accuracy Tradeoff ◽  
Rt Distributions

Evidence accumulation is a computational framework that accounts for behavior as well as the dynamics of individual neurons involved in decision making. Linking these two levels of description reveals a scaling paradox: How do choices and response times (RT) explained by models assuming single accumulators arise from a large ensemble of idiosyncratic accumulator neurons? We created a simulation model that makes decisions by aggregating across ensembles of accumulators, thereby instantiating the essential structure of neural ensembles that make decisions. Across different levels of simulated choice difficulty and speed-accuracy emphasis, choice proportions and RT distributions simulated by the ensembles are invariant to ensemble size and the accumulated evidence at RT is invariant across RT when the accumulators are at least moderately correlated in either baseline evidence or rates of accumulation and when RT is not governed by the most extreme accumulators. To explore the relationship between the low-level ensemble accumulators and high-level cognitive models, we fit simulated ensemble behavior with a standard LBA model. The standard LBA model generally recovered the core accumulator parameters (particularly drift rates and residual time) of individual ensemble accumulators with high accuracy, with variability parameters of the standard LBA modulating as a function of various ensemble parameters. Ensembles of accumulators also provide an alternative conception of speed-accuracy tradeoff without relying on varying thresholds of individual accumulators, instead by adjusting how ensembles of accumulators are aggregated or by how accumulators are correlated within ensembles. These results clarify relationships between neural and computational accounts of decision making.

scholarly journals Dynamic influences on static measures of metacognition

2020 ◽  
Author(s):  
Kobe Desender ◽  
Luc Vermeylen ◽  
Tom Verguts
Keyword(s):  
Decision Making ◽  
Neural Correlates ◽  
Independent Dataset ◽  
Evidence Accumulation ◽  
Domain Generality ◽  
Sources Of Variation ◽  
Human Participants ◽  
Speed Accuracy ◽  
Speed And Accuracy ◽  
Accuracy Tradeoff

AbstractHumans differ in their capability to judge the accuracy of their own choices via confidence judgments. Signal detection theory has been used to quantify the extent to which confidence tracks accuracy via M-ratio, often referred to as metacognitive efficiency. This measure, however, is static in that it does not consider the dynamics of decision making. This could be problematic because humans may shift their level of response caution to alter the tradeoff between speed and accuracy. Such shifts could induce unaccounted-for sources of variation in the assessment of metacognition. Instead, evidence accumulation frameworks consider decision making, including the computation of confidence, as a dynamic process unfolding over time. We draw on evidence accumulation frameworks to examine the influence of response caution on metacognition. Simulation results demonstrate that response caution has an influence on M-ratio. We then tested and confirmed that this was also the case in human participants who were explicitly instructed to either focus on speed or accuracy. We next demonstrated that this association between M-ratio and response caution was also present in an experiment without any reference towards speed. The latter finding was replicated in an independent dataset. In contrast, when data were analyzed with a novel dynamic measure of metacognition, which we refer to as v-ratio, in all of the three studies there was no effect of speed-accuracy tradeoff. These findings have important implications for research on metacognition, such as the question about domain-generality, individual differences in metacognition and its neural correlates.

scholarly journals Transcranial Direct Current Stimulation Does Not Influence the Speed–Accuracy Tradeoff in Perceptual Decision-making: Evidence from Three Independent Studies

2016 ◽  
Vol 28 (9) ◽  
pp. 1283-1294 ◽  
Author(s):  
Gilles de Hollander ◽  
Ludovica Labruna ◽  
Roberta Sellaro ◽  
Anne Trutti ◽  
Lorenza S. Colzato ◽  
...  
Keyword(s):  
Decision Making ◽  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Response Threshold ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Direct Current Stimulation ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

In perceptual decision-making tasks, people balance the speed and accuracy with which they make their decisions by modulating a response threshold. Neuroimaging studies suggest that this speed–accuracy tradeoff is implemented in a corticobasal ganglia network that includes an important contribution from the pre-SMA. To test this hypothesis, we used anodal transcranial direct current stimulation (tDCS) to modulate neural activity in pre-SMA while participants performed a simple perceptual decision-making task. Participants viewed a pattern of moving dots and judged the direction of the global motion. In separate trials, they were cued to either respond quickly or accurately. We used the diffusion decision model to estimate the response threshold parameter, comparing conditions in which participants received sham or anodal tDCS. In three independent experiments, we failed to observe an influence of tDCS on the response threshold. Additional, exploratory analyses showed no influence of tDCS on the duration of nondecision processes or on the efficiency of information processing. Taken together, these findings provide a cautionary note, either concerning the causal role of pre-SMA in decision-making or on the utility of tDCS for modifying response caution in decision-making tasks.

scholarly journals Neurally constrained modeling of speed-accuracy tradeoff during visual search: gated accumulation of modulated evidence

2019 ◽  
Vol 121 (4) ◽  
pp. 1300-1314 ◽  
Author(s):  
Mathieu Servant ◽  
Gabriel Tillman ◽  
Jeffrey D. Schall ◽  
Gordon D. Logan ◽  
Thomas J. Palmeri
Keyword(s):  
Decision Making ◽  
Visual Search ◽  
Response Times ◽  
Frontal Eye Field ◽  
Search Performance ◽  
Model Framework ◽  
Accumulator Model ◽  
Eye Field ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

Stochastic accumulator models account for response times and errors in perceptual decision making by assuming a noisy accumulation of perceptual evidence to a threshold. Previously, we explained saccade visual search decision making by macaque monkeys with a stochastic multiaccumulator model in which accumulation was driven by a gated feed-forward integration to threshold of spike trains from visually responsive neurons in frontal eye field that signal stimulus salience. This neurally constrained model quantitatively accounted for response times and errors in visual search for a target among varying numbers of distractors and replicated the dynamics of presaccadic movement neurons hypothesized to instantiate evidence accumulation. This modeling framework suggested strategic control over gate or over threshold as two potential mechanisms to accomplish speed-accuracy tradeoff (SAT). Here, we show that our gated accumulator model framework can account for visual search performance under SAT instructions observed in a milestone neurophysiological study of frontal eye field. This framework captured key elements of saccade search performance, through observed modulations of neural input, as well as flexible combinations of gate and threshold parameters necessary to explain differences in SAT strategy across monkeys. However, the trajectories of the model accumulators deviated from the dynamics of most presaccadic movement neurons. These findings demonstrate that traditional theoretical accounts of SAT are incomplete descriptions of the underlying neural adjustments that accomplish SAT, offer a novel mechanistic account of decision-making mechanisms during speed-accuracy tradeoff, and highlight questions regarding the identity of model and neural accumulators. NEW & NOTEWORTHY A gated accumulator model is used to elucidate neurocomputational mechanisms of speed-accuracy tradeoff. Whereas canonical stochastic accumulators adjust strategy only through variation of an accumulation threshold, we demonstrate that strategic adjustments are accomplished by flexible combinations of both modulation of the evidence representation and adaptation of accumulator gate and threshold. The results indicate how model-based cognitive neuroscience can translate between abstract cognitive models of performance and neural mechanisms of speed-accuracy tradeoff.

scholarly journals Integration of dynamic reward schedules and speed-accuracy tradeoff in perceptual decision making

2012 ◽  
Vol 12 (9) ◽  
pp. 166-166
Author(s):  
Y.-H. Liu ◽  
S.-W. Wu
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

scholarly journals Collective Decision-Making in Ideal Networks: The Speed-Accuracy Tradeoff

2014 ◽  
Vol 1 (1) ◽  
pp. 121-132 ◽  
Author(s):  
Vaibhav Srivastava ◽  
Naomi Ehrich Leonard
Keyword(s):  
Decision Making ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Speed Accuracy ◽  
Accuracy Tradeoff
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