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The time-saving bias describes people's tendency to misestimate the time they can save by increasing the speed in which they perform an activity such as driving or completing a task. People typically underestimate time saved when increasing from a low speed and overestimate time saved when increasing from an already high speed. We suggest that this bias is the result of people's failure to recognize the curvilinear relationship between increasing speed and reducing activity time: As initial speed rises, the same speed increases will yield smaller reductions in time. We explore a new technique to de-bias these faulty estimations: converting measurements of speed to a pace measure (e.g., minutes per fixed distance). Utilizing common driving scenarios, we show that participants who received pace data made more accurate estimations of journey duration at various speeds, time-savings at various speed increases and the required speed to complete a journey.

The time-saving bias describes people’s tendency to misestimate the time they can save by increasing the speed in which they perform an activity such as driving or completing a task. People typically underestimate time saved when increasing from a low speed and overestimate time saved when increasing from an already high speed. We suggest that this bias is the result of people’s failure to recognize the curvilinear relationship between increasing speed and reducing activity time: As initial speed rises, the same speed increases will yield smaller reductions in time. We explore a new technique to de-bias these faulty estimations: converting measurements of speed to a pace measure (e.g., minutes per fixed distance). Utilizing common driving scenarios, we show that participants who received pace data made more accurate estimations of journey duration at various speeds, time-savings at various speed increases and the required speed to complete a journey.

Patients with mild cognitive impairment (MCI) may have difficulties in time perception, which in turn might contribute to some of their symptoms, especially memory deficits. The aim of this study was to evaluate perception of interval length and subjective passage of time in MCI patients as compared to healthy controls. Fifty-five MCI patients and 57 healthy controls underwent an experimental protocol for time perception on interval length, a questionnaire for the subjective passage of time and a neuropsychological evaluation. MCI patients presented no changes in the perception of interval length. However, for MCI patients, time seemed to pass more slowly than it did for controls. This experience was significantly correlated with memory deficits but not with performance in executive tests, nor with complaints of depression or anxiety. Memory deficits do not affect the perception of interval length, but are associated with alterations in the subjective passage of time. (JINS, 2016, 22, 755-764).

In published studies using the remember/know judgement paradigm, the remember-based old/new responses (supposed to be slow and effortful) are on average faster than the know-based responses (supposed to be fast and automatic), contrary to the dual-process theories' view. One widely believed cause of this finding is that it is an experimental artefact, meaning participants are unknowingly influenced by the instruction to first consider the remember before the know alternative. In Experiment 1, we hinted to participants to first consider the know experience. This did not reverse the order of the two response times (RT). In Experiment 2, we explicitly told them to first consider the familiarity experience. Additionally, we used a decision criterion favouring making quick familiarity responses. These measures significantly lowered the RT and increased the proportion of familiarity-based responses. However, they did not change the RT of the recollection-based responses and did not reverse the relative order of the two RTs. Based on this finding and participants' inability to inhibit the retrieval of contextual details, we concluded that the paradoxical RT results are probably not an experimental artefact and that retrieval of detailed information in recollective recognition might be automatic. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

We recorded activity from neurones in cortical motion-processing areas, middle temporal area (MT) and middle posterior superior temporal sulcus (MST), of anaesthetised and paralysed macaque monkeys in response to moving sinewave gratings modulated in luminance and chrominance. The activity of MT and MST neurones was highly dependent on luminance contrast. In three of four animals isoluminant chromatic modulations failed to activate MT/MST neurones significantly. At low luminance contrast a systematic dependence on chromaticity was revealed, attributable mostly to residual activity of the magnocellular pathway. Additionally, we found indications for a weak S-cone input, but rod intrusion could also have made a contribution. In contrast to the activity of MT and MST neurones, speed judgments and onset amplitude of evoked optokinetic eye movements in human subjects confronted with equivalent visual stimuli were largely independent of luminance modulation. Motion of every grating (including isoluminant) was readily visible for all but one observer. Similarity with the activity of MT/MST cells was found only for motion-nulling equivalent luminance contrast judgments at isoluminance. Our results suggest that areas MT and MST may not be involved in the processing of chromatic motion, but effects of central anaesthesia and/or the existence of intra- and inter-species differences must also be considered.

Many workers today engage in straightforward judgment tasks, increasing the need for interventions to improve accuracy. We propose a resource-rational and psychohygienic intervention, “wait short time”, which introduces a brief pause before displaying alternatives. This pause works as a harmonious triad: it clears the mind of prior judgment bias, restores present attention, and prepares the mind for future judgments; and all this without additional instructions. Based on a resource rationality framework, cognitive costs (e.g., irritation, cognitive conflict) are associated with prolonged thinking because of humans limited cognitive resources. Therefore, there should be an appropriately short thinking time to achieve higher accuracy with minimal workload. We investigated the effectiveness of the proposed intervention both theoretically and empirically. The computer simulations demonstrated that, under assumptions of limited cognitive resources, there was an optimal time at the early stages for maximizing total benefits. The results of behavioral experiment was consistent with the theoretical findings: Providing a waiting time (1 s or 2.5 s) improved judgment accuracy, but cognitive conflicts increased over time and an unnecessarily long time (2.5 s) induced more subjective irritation. Consequently, an appropriate time (1 s) could enhance judgment accuracy with less workload. We discuss the implications and limitations of the proposed intervention.

High-speed railway administrations are particularly concerned about safety and comfort issues, which are sometimes threatened by the differential deformation of substructures. Existing deformation-monitoring techniques are impractical for covering the whole range of a railway line at acceptable costs. Fortunately, the information about differential substructure deformation is contained in the dynamic inspection data of longitudinal level from comprehensive inspections trains. In order to detect potential differential deformations, an identification method, combining digital filtering, a convolutional neural network and infrastructure base information, is proposed. In this method, a low-pass filter is designed to remove short-waveband components of the longitudinal level. Then, a one-dimensional convolutional neural network is constructed to serve as a feature extractor from local longitudinal-level waveforms, and a binary classifier of potential differential deformations in place of the visual judgement of humans with profound expertise. Finally, the infrastructure base information is utilized to further classify the differential deformations into several types, according to the positional distribution of the substructures. The inspection data of four typical high-speed railways are selected to train and test the method. The results show that the convolutional neural network can identify differential substructure-deformations, with the precision, recall, accuracy and F1 score all exceeding 98% on the test data. In addition, four types of deformation can be further classified with the support of infrastructure base information. The proposed method can be used for directly locating adverse substructure deformations, and is also becoming a promising addition to existing deformation monitoring methods.