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Motor Cost Influences Perceptual Decisions.

ABSTRACT: Perceptual decision making has been widely studied using tasks in which subjects are asked to discriminate a visual stimulus and instructed to report their decision with a movement. In these studies, performance is measured by assessing the accuracy of the participants' choices as a function of the ambiguity of the visual stimulus. Typically, the reporting movement is considered as a mere means of reporting the decision with no influence on the decision-making process. However, recent studies have shown that even subtle differences of biomechanical costs between movements may influence how we select between them. Here we investigated whether this purely motor cost could also influence decisions in a perceptual discrimination task in detriment of accuracy. In other words, are perceptual decisions only dependent on the visual stimulus and entirely orthogonal to motor costs? Here we show the results of a psychophysical experiment in which human subjects were presented with a random dot motion discrimination task and asked to report the perceived motion direction using movements of different biomechanical cost. We found that the pattern of decisions exhibited a significant bias towards the movement of lower cost, even when this bias reduced performance accuracy. This strongly suggests that motor costs influence decision making in visual discrimination tasks for which its contribution is neither instructed nor beneficial.

SUBMITTER: Marcos E

PROVIDER: S-EPMC4684499 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Motor Cost Influences Perceptual Decisions.

Marcos Encarni E Cos Ignasi I Girard Benoît B Verschure Paul F M J PF

PloS one 20151216 12

Perceptual decision making has been widely studied using tasks in which subjects are asked to discriminate a visual stimulus and instructed to report their decision with a movement. In these studies, performance is measured by assessing the accuracy of the participants' choices as a function of the ambiguity of the visual stimulus. Typically, the reporting movement is considered as a mere means of reporting the decision with no influence on the decision-making process. However, recent studies ha ...[more]

PMID: 26673222

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Project description:IntroductionThe regulation of one's step length by placing one's foot at a specific position within gait, otherwise known as 'locomotor pointing', is well understood in walking and running gait. The current study was the first to broaden this understanding to a larger cohort and to describe the influence of age on the regulation of locomotor pointing when walking up to and stepping onto a curb-like platform.MethodsYounger (n = 17, mean age: 25.35 years, range: 19-33) and older adults (n = 105, mean age: 71.49 years, range: 61-86) participated in a walking experiment, requiring them to approach and step onto a curb-like platform. Linear mixed effects modeling was used to study the main outcome variables: onset of regulation, the regulation strategy and the strength of perceptual-motor coupling.ResultsResults showed that with older age, participants showed less variability in foot placement during their approach and seemed to prefer to shorten their steps. Furthermore, the strength of the perceptual-motor relationship was found to be related to age; regulation of step length of both younger and older participants was based on a participant's current foot position. The strength of this relationship increased as participants got closer to the curb and was stronger with increasing age. Furthermore, younger adults on average lengthened their steps as they got closer to the curb, whereas older adults showed significantly less lengthening compared to their younger counterparts. No age-related differences were found in terms of onset of regulation.DiscussionThe results suggest that the strength of the perceptual-motor relationship in gait is related to age. It is argued that this age-related increase in the strength of perceptual-motor coupling is required to cope with increasing demands linked to the age-related declines of action capabilities. The implications of the findings are discussed in the context of increased falls risks and deficits in perceptual-motor functioning.

Project description:Perceptual confidence is an important internal signal about the certainty of our decisions and there is a substantial debate on how it is computed. We highlight three confidence metric types from the literature: observers either use 1) the full probability distribution to compute probability correct (Probability metrics), 2) point estimates from the perceptual decision process to estimate uncertainty (Evidence-Strength metrics), or 3) heuristic confidence from stimulus-based cues to uncertainty (Heuristic metrics). These metrics are rarely tested against one another, so we examined models of all three types on a suprathreshold spatial discrimination task. Observers were shown a cloud of dots sampled from a dot generating distribution and judged if the mean of the distribution was left or right of centre. In addition to varying the horizontal position of the mean, there were two sensory uncertainty manipulations: the number of dots sampled and the spread of the generating distribution. After every two perceptual decisions, observers made a confidence forced-choice judgement whether they were more confident in the first or second decision. Model results showed that the majority of observers were best-fit by either: 1) the Heuristic model, which used dot cloud position, spread, and number of dots as cues; or 2) an Evidence-Strength model, which computed the distance between the sensory measurement and discrimination criterion, scaled according to sensory uncertainty. An accidental repetition of some sessions also allowed for the measurement of confidence agreement for identical pairs of stimuli. This N-pass analysis revealed that human observers were more consistent than their best-fitting model would predict, indicating there are still aspects of confidence that are not captured by our modelling. As such, we propose confidence agreement as a useful technique for computational studies of confidence. Taken together, these findings highlight the idiosyncratic nature of confidence computations for complex decision contexts and the need to consider different potential metrics and transformations in the confidence computation.

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Motor Cost Influences Perceptual Decisions.

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Motor Cost Influences Perceptual Decisions.

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