A cognitive style dataset including functional near-infrared spectroscopy, eye-tracking, psychometric and behavioral measures

The dataset includes data from the triangulated investigation reported in our paper: ‘Psychophysiological indices of cognitive style: A triangulated study incorporating neuroimaging, eye-tracking, psychometric and behavioral measures’ [1,2]. The data was collected at the Directorate of Psychology & Public Health laboratories at the University of Salford, UK, in 2015 among an English-speaking sample. The dataset includes measures described in the paper including information-processing/cognitive style recorded as Cognitive Style Index [CSI; 3] scores, comparative visual search (CVS) task behavioral measures (reaction time and accuracy), eye-movement data (fixation duration, number of saccades, number of comparative saccades and distance moved) and prefrontal cortex (PFC) oxygenated hemoglobin (oxy-Hb) recorded using functional near-infrared spectroscopy (fNIRS)

Autism detection based on eye movement sequences on the web: a scanpath trend analysis approach

This is an accepted manuscript of an article published by ACM in W4A '20: Proceedings of the 17th International Web for All Conference on 20/04/2020, available online: https://doi.org/10.1145/3371300.3383340 The accepted version of the publication may differ from the final published version.Autism diagnostic procedure is a subjective, challenging and expensive procedure and relies on behavioral, historical and parental report information. In our previous, we proposed a machine learning classifier to be used as a potential screening tool or used in conjunction with other diagnostic methods, thus aiding established diagnostic methods. The classifier uses eye movements of people on web pages but it only considers non-sequential data. It achieves the best accuracy by combining data from several web pages and it has varying levels of accuracy on different web pages. In this present paper, we investigate whether it is possible to detect autism based on eye-movement sequences and achieve stable accuracy across different web pages to be not dependent on specific web pages. We used Scanpath Trend Analysis (STA) which is designed for identifying a trending path of a group of users on a web page based on their eye movements. We first identify trending paths of people with autism and neurotypical people. To detect whether or not a person has autism, we calculate the similarity of his/her path to the trending paths of people with autism and neurotypical people. If the path is more similar to the trending path of neurotypical people, we classify the person as a neurotypical person. Otherwise, we classify her/him as a person with autism. We systematically evaluate our approach with an eye-tracking dataset of 15 verbal and highly-independent people with autism and 15 neurotypical people on six web pages. Our evaluation shows that the STA approach performs better on individual web pages and provides more stable accuracy across different pages

Does alcohol catch the eye? Investigating young adults’ attention to alcohol consumption

Many studies on young adults' motivations for drinking overlook the symbolic aspects of alcohol use. However, research indicates that young adults' alcohol consumption is also driven by signaling motivations. Although the interest of a receiver is a necessary prerequisite of a signal, no previous studies have verified whether drinking behavior indeed attracts young adults' attention. Therefore, we conducted two studies. A two-part eye-tracking study ( N1 = 135, N2 = 140) showed that both young men and young women pay special visual attention to male and female drinking behavior. Additionally, a recall experiment ( N = 321) confirmed that observed male and female drinking is better remembered than observed nonsignaling, functional behavior. Moreover, alcoholic beverages also receive special attention, as they were recalled better than other functional products, and also nonalcoholic drinks similar in color and shape. In summary, the experiments clearly showed that male and female drinking behavior can be used as a signal, as both behaviors clearly function as an attention-attracting cue. Additionally, as alcoholic beverages draw more attention than nonalcoholic drinks, this attention is clearly linked to the alcohol element of the drinking behavior

Generalization Strategies in Finding the <i>n</i>th Term Rule for Simple Quadratic Sequences

In this study, we identify ways in which a sample of 18 graduates with mathematics-related first degrees found the nth term for quadratic sequences from the first values of a sequence of data, presented on a computer screen in various formats: tabular, scattered data pairs and sequential. Participants’ approaches to identifying the nth term were recorded with eye-tracking technology. Our aims are to identify their strategies and to explore whether and how format influences these strategies. Qualitative analysis of eye-tracking data offers several strategies: Sequence of Differences, Building a Relationship, Known Formula, Linear Recursive and Initial Conjecture. Sequence of Differences was the most common strategy, but Building a Relationship was more likely to lead to the right formula. Building from Square and Factor Search were the most successful methods of Building a Relationship. Findings about the influence of format on the range of strategies were inconclusive but analysis indicated sporadic evidence of possible influences

Using distributional statistics to acquire morphophonological alternations: evidence from production and perception

Morphophonological alternations, such as the voicing alternation that arises in a morphological paradigm due to final-devoicing in Dutch, are notoriously difficult for children to acquire. This has previously been attributed to their unpredictability. In fact, the presence or absence of a voicing alternation is partly predictable if the phonological context of the word is taken into account, and adults have been shown to use this information (Ernestus and Baayen, 2003). This study investigates whether voicing alternations are predictable from the child’s input, and whether children can make use of this information. A corpus study of child-directed speech establishes that the likelihood of a stem-final obstruent alternating is somewhat predictable on the basis of the phonological properties of the stem. In Experiment 1 Dutch 3-year-olds’ production accuracy in a plural-elicitation task is shown to be sensitive to the distributional statistics. However, distributional properties do not play a role in children’s sensitivity to mispronunciations of voicing in a Preferential Looking Task in Experiment 2