scholarly journals MT-aIAT: Integrating mouse tracking into memory-detection aIAT

2021 ◽  
Author(s):  
Xinyi Xu ◽  
Xianqing Liu ◽  
Xiaoqing Hu ◽  
Haiyan Wu
Keyword(s):  
Computational Modeling ◽  
Implicit Association Test ◽  
Credit Card ◽  
Congruency Effect ◽  
Detection Method ◽  
Order Effect ◽  
Connectionist Model ◽  
Behavioral Performance ◽  
Mouse Tracking ◽  
Real Time Measurement

This study assesses the validity of a newly integrated memory detection method, MT-aIAT, which is a combination of the autobiographical Implicit Association Test (aIAT) and the mouse-tracking method. Participants were assigned to steal a credit card and then performed the aIAT while mouse tracker was recording their motor trajectories. Replicating previous work, we found a RT congruency effect. Critically, the mouse trajectories indicate a congruency effect and a block order effect, suggesting the validity of mouse-tracking technique in unraveling real-time measurement of the IAT congruency effect. Lastly, to test the computational modeling in MT-aIAT, we posited a connectionist model combined with the drift-discussion model to simulate participants’ behavioral performance. Our model captures the ubiquitous implicit bias towards the autobiographical event. Implications of the MT-aIAT in identifying autobiographical memories, the combination of MT-aIAT with computational modeling approach were discussed.

scholarly journals The easy-money effect: credit card spending and hard-work reminders

2017 ◽  
Vol 34 (7) ◽  
pp. 541-551 ◽  
Author(s):  
King-Yin Wong ◽  
Michael Lynn
Keyword(s):  
Implicit Association Test ◽  
Credit Card ◽  
Design Methodology ◽  
Credit Cards ◽  
Association Test ◽  
Hard Work ◽  
Implicit Association ◽  
Consumer Spending ◽  
Content Type ◽  
Practical Implications

Purpose This research paper aims to examine the proposed easy-money effect of credit cards, which stimulates consumers to overspend. This paper shows how such an easy-money effect can be weakened. Design/methodology/approach In Study 1, an implicit association test was conducted with a sample of 169 participants to test the proposed credit card easy-money effect. In Study 2, experimental data were collected online from 365 participants to test the effectiveness of a hard-work reminder in weakening credit cards’ easy-money effect on consumer spending. Findings The proposed credit card easy-money effect exists, with spendthrift (ST) participants associating money with hard work less in the implicit association test after being presented with a credit card cue versus neutral cue. The results from Study 2 show that ST participants spent more on their dinner than tightwad participants when shown a credit card cue. However, this effect could be weakened when STs were also reminded of their hard work by a picture accompanied with words. Practical implications This paper suggests that credit cards’ spending-stimulating effect is due to consumers’ associations between credit cards and easy money. Based on this notion, this paper suggests conditions in which credit cards will stimulate more and less spending. Originality/value This is the first research attempt to examine the credit cards’ easy-money effect and the effectiveness of reminding consumers of their hard work to mitigate credit cards’ long-established spending-stimulating effect.

scholarly journals Neuronal congruency effects in macaque frontal cortex

2021 ◽  
Author(s):  
Tao Yao ◽  
Wim Vanduffel
Keyword(s):  
Selective Attention ◽  
Frontal Cortex ◽  
Congruency Effect ◽  
Irrelevant Stimulus ◽  
Relative Activity ◽  
Behavioral Performance ◽  
Activity Levels ◽  
Neuronal Mechanisms ◽  
Stimulus Features ◽  
Task Irrelevant

Abstract The interplay between task-relevant and task-irrelevant stimulus features induces conflicts which impair human behavioral performance in many perceptual and cognitive tasks, a.k.a. a behavioral congruency effect. The neuronal mechanisms underlying behavioral congruency effects, however, are poorly understood. We recorded single unit activity in monkey frontal cortex using a novel task-switching paradigm and discovered a neuronal congruency effect that is carried by task-relevant and -irrelevant neurons. The former neurons provide more signal, the latter less noise in congruent compared to incongruent conditions. Their relative activity levels determine the neuronal congruency effect and behavioral performance. Although these neuronal congruency signals are sensitive to selective attention, they cannot be entirely explained by selective attention as gauged by response time. We propose that such neuronal congruency effects can explain behavioral congruency effects in general, as well as previous fMRI and EEG results in various conflict paradigms.

scholarly journals Fuzzy Particle Swarm Optimization Feature Selection and Aggrandized Classifier for Uncovering Frauds in Credit Card Deals

2020 ◽  
Vol 9 (3) ◽  
pp. 227-234
Keyword(s):  
Feature Selection ◽  
Particle Swarm Optimization ◽  
Credit Card ◽  
Drift Rate ◽  
Detection Method ◽  
Concept Drift ◽  
Research Work ◽  
Credit Cards ◽  
Fraud Detection ◽  
Swarm Optimization

In today's economy, credit card plays a very important role. The rise of credit card customers improved, credit card scam cases were also on the rise. Numerous procedures are anticipated to challenge the evolution of the frauds in credit cards. In this research work, proposed an innovative fraud detection method which utilizes the similar cardholder’s behavioral patterns to construct a current cardholder’s interactive profile in order to stay away from the credit card scams. However, the selection of optimal features from the samples and the decision cost for accuracy becomes main important problem. To illuminate these issues this proposed research work presents an innovative fraud detection technique that makes out of four phases: 1. To augment a cardholder’s behavioral styles, first we divide all cardholders into distinctive groups making use of the cardholder’s historical transaction data such that the members of each group have the similar transaction behavior by K-means. 2. Introduces a new Fuzzy Particle Swarm Optimization (FPSO) feature selection for the amplification of fraud detection in credit cards. 3. By means of a prolonged wrapper method, an ensemble classification are performed by Aggrandized Kernel based Support Vector Machine (AKSVM).4.Refreshing the cardholder’s social profile with an input system. This Proposed work adopts the external quality metrics as Accuracy, Recall, Concept drift rate and Fraud feature rate. The UCI dataset is used and is done in MATLAB framework. The analytical measures were used to estimate the routine of the mentioned fraud detection technique. The simulation results show that this proposed innovative fraud detection method provides better accuracy results than other fraud detection techniques. The low concept drift rate results the gain of the innovative method to classify the transactions accurately.

scholarly journals A Novel Capacitive Detection Scheme With Inherent Self-Calibration

2007 ◽  
Author(s):  
Alexander A. Trusov ◽  
Andrei M. Shkel
Keyword(s):  
Parallel Plate ◽  
Detection Method ◽  
Critical Parameters ◽  
Detection Scheme ◽  
Resonant Structures ◽  
Self Calibration ◽  
Real Time Measurement ◽  
Sinusoidal Motion ◽  
Measurement Algorithm ◽  
Capacitive Detection

This paper reports a novel capacitive detection method which is robust to variations of such critical parameters as the nominal capacitance, frequency and amplitude of the probing voltage, and gain of the trans-impedance amplifier. The approach constructively utilizes inherent nonlinearity of parallel plate sense capacitors in order to measure amplitude of sinusoidal motion. In the case of parallel plate detection signal, multiple harmonics exist and carry redundant information about the amplitude of mechanical motion. The amplitude of motion can be extracted from the ratio of two simultaneously measured harmonics. The paper presents details of a real-time measurement algorithm. Functionality of the algorithm is confirmed by simulations and experiments. The technique is especially valuable for capacitive detection and self-calibration in resonant structures, such as gyroscopes, resonant microbalances, and chemical sensors.

The Detection and the Neural Correlates of Behavioral (Prior) Intentions

2011 ◽  
Vol 23 (12) ◽  
pp. 3888-3902 ◽  
Author(s):  
Sara Agosta ◽  
Umberto Castiello ◽  
Davide Rigoni ◽  
Stefano Lionetti ◽  
Giuseppe Sartori
Keyword(s):  
Implicit Association Test ◽  
Congruency Effect ◽  
Mental Representations ◽  
Reaction Times ◽  
Neural Correlates ◽  
Positive Component ◽  
Late Positive Component ◽  
Intentional Actions ◽  
Prior Intention ◽  
First Time

Prior intentions are abstract mental representations that are believed to be the prime cause of our intentional actions. To date, only a few studies have focused on the possibility that single prior intentions could be identified in people's minds. Here, for the first time, we used the autobiographical Implicit Association Test (aIAT) in order to identify a specific prior intention on the basis of a pattern of associations derived from reaction times (Experiment 1). The aIAT is based on two critical blocks: the block associating intentions with true sentences (congruent block) gave rise to faster reaction times (RTs) than the block associating intentions with false sentences (incongruent block). Furthermore, when comparing intentions with hopes, it was revealed that the reported effect was intention-specific: The pattern of associations reflected a congruency effect when intentions and the logical category “True” were paired, but not when hopes and the “True” category were paired (Experiment 2). Finally, we investigated the neural bases of the congruency effect that leads to the identification of an intention (Experiment 3). We found a reduced late positive component (LPC) for the incongruent with respect to the congruent block, suggesting that the incongruent block needs additional resources of cognitive control with respect to the congruent block.

The Real-time Measurement of the Process of Person Construal Based on Mouse-tracking Technology

2013 ◽  
Vol 20 (5) ◽  
pp. 770-781
Author(s):  
Xiao-Bin ZHANG ◽  
Bin ZUO ◽  
Meng-Jie XUE ◽  
Wen JIANG ◽  
Fei-Xiang HOU
Keyword(s):  
Real Time ◽  
Time Measurement ◽  
Mouse Tracking ◽  
The Real ◽  
Real Time Measurement ◽  
Tracking Technology ◽  
Person Construal

Cognitive Dynamics of Religiosity and Intertemporal Choice Behavior

2020 ◽  
Vol 51 (9) ◽  
pp. 719-739
Author(s):  
Cinzia Calluso ◽  
Mohammad Amin Zandi ◽  
Maria Giovanna Devetag
Keyword(s):  
Implicit Association Test ◽  
Choice Behavior ◽  
Intertemporal Choice ◽  
Temporal Discounting ◽  
Cognitive Conflict ◽  
Self Control ◽  
Implicit Association ◽  
Mouse Tracking ◽  
Control Groups ◽  
Cognitive Dynamics

The preference for smaller-sooner rewards over larger-delayed ones (temporal discounting, TD) has been suggested to be influenced by religiosity, through its role in enhancing self-control. Here we investigate this issue in Muslims, Catholics, and two control groups of Italian and Iranian atheists, by measuring implicit religiosity (implicit association test, IAT) and the cognitive dynamics underlying TD (using mouse tracking). Results showed that Muslims are the most farsighted, while Catholics are the most shortsighted and both atheists’ groups fall in between these two extremes; additionally, these results are also shaped by implicit religiosity (IAT). Mouse tracking analyses reveal that Muslims show higher cognitive conflict compared to the other groups, which arises only in later stages of processing. This indicates that farsighted behavior in Muslims requires the recruitment of self-control in order to regulate intertemporal decision-making. Our findings suggest that the highly demanding religious precepts enforced in (most) Islamic communities may help strengthen self-control abilities.

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