Eye blinks: new indices for the detection of deception

Pupillometry and autonomic nervous system responses to cognitive load and false feedback: an unsupervised machine learning approach

Objectives

Pupil dilation is controlled both by sympathetic and parasympathetic nervous system branches. We hypothesized that the dynamic of pupil size changes under cognitive load with additional false feedback can predict individual behavior along with heart rate variability (HRV) patterns and eye movements reflecting specific adaptability to cognitive stress. To test this, we employed an unsupervised machine learning approach to recognize groups of individuals distinguished by pupil dilation dynamics and then compared their autonomic nervous system (ANS) responses along with time, performance, and self-esteem indicators in cognitive tasks.

Methods

Cohort of 70 participants were exposed to tasks with increasing cognitive load and deception, with measurements of pupillary dynamics, HRV, eye movements, and cognitive performance and behavioral data. Utilizing machine learning k-means clustering algorithm, pupillometry data were segmented to distinct responses to increasing cognitive load and deceit. Further analysis compared clusters, focusing on how physiological (HRV, eye movements) and cognitive metrics (time, mistakes, self-esteem) varied across two clusters of different pupillary response patterns, investigating the relationship between pupil dynamics and autonomic reactions.

Results

Cluster analysis of pupillometry data identified two distinct groups with statistically significant varying physiological and behavioral responses. Cluster 0 showed elevated HRV, alongside larger initial pupil sizes. Cluster 1 participants presented lower HRV but demonstrated increased and pronounced oculomotor activity. Behavioral differences included reporting more errors and lower self-esteem in Cluster 0, and faster response times with more precise reactions to deception demonstrated by Cluster 1. Lifestyle variations such as smoking habits and differences in Epworth Sleepiness Scale scores were significant between the clusters.

Conclusion

The differentiation in pupillary dynamics and related metrics between the clusters underlines the complex interplay between autonomic regulation, cognitive load, and behavioral responses to cognitive load and deceptive feedback. These findings underscore the potential of pupillometry combined with machine learning in identifying individual differences in stress resilience and cognitive performance. Our research on pupillary dynamics and ANS patterns can lead to the development of remote diagnostic tools for real-time cognitive stress monitoring and performance optimization, applicable in clinical, educational, and occupational settings.

Attentional modulation of eye blinking is altered by sex, age, and task structure

Spontaneous eye blinking is gaining popularity as a proxy for higher cognitive functions, as it is readily modulated by both environmental demands and internal processes. Prior studies were impoverished in sample size, sex representation and age distribution, making it difficult to establish a complete picture of the behavior. Here we present eye-tracking data from a large cohort of normative participants (n=604, 393 F, aged 5-93 years) performing two tasks: one with structured, discrete trials (interleaved pro/anti-saccade task; IPAST) and one with a less structured, continuous organization in which participants watch movies (free-viewing; FV). Sex- and age-based analyses revealed that females had higher blink rates between the ages of 22 and 58 years in the IPAST, and 22 and 34 years in FV. We derived a continuous measure of blink probability to reveal behavioral changes driven by stimulus appearance in both paradigms. In the IPAST, blinks were suppressed near stimulus appearance, particularly on correct anti-saccade trials, which we attribute to the stronger inhibitory control required for anti-saccades compared to pro-saccades. In FV, blink suppression occurred immediately after scene changes, and the effect was sustained on scenes where gaze clustered among participants (indicating engagement of attention). Females were more likely than males to blink during appearance of novel stimuli in both tasks, but only within the age bin of 18-44 years. The consistency of blink patterns in each paradigm endorses blinking as a sensitive index for changes in visual processing and attention, while sex and age differences drive interindividual variability.Significance Statement Eye-tracking is becoming useful as a non-invasive tool for detecting preclinical markers of neurological and psychiatric disease. Blinks are understudied despite being an important supplement to saccade and pupil eye-tracking metrics. The present study is a crucial step in developing a healthy baseline for blink behavior to compare to clinical groups. While many prior blink studies suffered from small sample sizes with relatively low age- and sex-diversity (review by Jongkees & Colzato, 2016), our large cohort of healthy participants has permitted a more detailed analysis of sex and age effects in blink behavior. Furthermore, our analysis techniques are robust to temporal changes in blink probability, greatly clarifying the relationship between blinking, visual processing, and inhibitory control mechanisms on visual tasks.

Insights from Eye Blinks into the Cognitive Processes Involved in Visual Word Recognition

Behavioral differences in speed and accuracy between reading familiar and unfamiliar words are well-established in the empirical literature. However, these standard measures of skill proficiency are limited in their ability to capture the moment-to-moment processing involved in visual word recognition. In the present study, the effect of word familiarity was initially investigated using an eye blink rate among adults and children. The probability of eye blinking was higher for familiar (real) words than for unfamiliar (pseudo)words. This counterintuitive pattern of results suggests that the processing of unfamiliar (pseudo)words is more demanding and perhaps less rewarding than the processing of familiar (real) words, as previously observed in both behavioral and pupillometry data. Our findings suggest that the measurement of eye blinks might shed new light on the cognitive processes involved in visual word recognition and other domains of human cognition.

Automatic and controlled information processing in the context of students’ ethnic background and social status: An eye-tracking study

Based on the continuum model of impression formation (Fiske & Neuberg, 1990), information processing can be more or less automated or controlled and thus relies more or less on stereotype-based or individual-based characteristics. Also, teachers’ impression formation can be influenced by social categories like students’ ethnic background or social status. However, when teachers form an impression of students’ abilities or performance social categories should not play a role. But a lot of empirical findings show that teachers make a difference depending on students’ backgrounds. Whether this can be explained by a more automated or controlled information processing depending on students’ backgrounds is still an open question. Accordingly, the purpose of this study was to investigate teacher students’ impression formation in dependence on students’ ethnic backgrounds and social status. In order to investigate whether information processing differs according to students’ ethnic backgrounds and social status, an experimental eye-tracking study with 45 teacher students was designed. As physiological processes are strongly connected to psychological processes, specific eye-movements can be interpreted as indicators for physiological arousal in first place, but might also allow conclusions about mental processes like information processing. Pupil diameter and blink rate were measured while participants read three case vignettes with manipulated student background. Analysis of variance with repeated measures showed differences in pupil diameter and blink rate according to students’ background. Results showed less arousal when forming an impression about students without immigrant background and with high social status compared to students with immigrant background and with low social status. This might indicate more automated information processing for non-immigrant students with high-status, and more controlled processing for students with immigrant background and low-status.

Detecting Deception from Gaze and Speech Using a Multimodal Attention LSTM-Based Framework

The automatic detection of deceptive behaviors has recently attracted the attention of the research community due to the variety of areas where it can play a crucial role, such as security or criminology. This work is focused on the development of an automatic deception detection system based on gaze and speech features. The first contribution of our research on this topic is the use of attention Long Short-Term Memory (LSTM) networks for single-modal systems with frame-level features as input. In the second contribution, we propose a multimodal system that combines the gaze and speech modalities into the LSTM architecture using two different combination strategies: Late Fusion and Attention-Pooling Fusion. The proposed models are evaluated over the Bag-of-Lies dataset, a multimodal database recorded in real conditions. On the one hand, results show that attentional LSTM networks are able to adequately model the gaze and speech feature sequences, outperforming a reference Support Vector Machine (SVM)-based system with compact features. On the other hand, both combination strategies produce better results than the single-modal systems and the multimodal reference system, suggesting that gaze and speech modalities carry complementary information for the task of deception detection that can be effectively exploited by using LSTMs.

To err is human but not deceptive

This study addresses a poorly understood but important question concerning the cognition of deception: How much more is there to lying than to responding incorrectly, the latter capturing how researchers have occasionally operationalized deception? A recent social-cognitive account of lying - Activation-Decision-Construction-Action Theory (ADCAT) - asserts a qualitative difference between the two - for instance, that deception involves Theory of Mind inferences and more proactive interference. To test these notions within-subjects, participants answered closed-ended and open-ended questions probing general truths honestly, deceptively, or with intentional errors. Response time and noncompliance with instructions were the dependent measures. Deceptive responding generally elicited the longest response times and the lowest instruction compliance, followed by intentional erring, supporting the theory. Although not the primary focus, response inhibition due to implausible deception was demonstrated for the first time.

Joint Analysis of Eye Blinks and Brain Activity to Investigate Attentional Demand during a Visual Search Task

In several fields, the need for a joint analysis of brain activity and eye activity to investigate the association between brain mechanisms and manifest behavior has been felt. In this work, two levels of attentional demand, elicited through a conjunction search task, have been modelled in terms of eye blinks, brain activity, and brain network features. Moreover, the association between endogenous neural mechanisms underlying attentional demand and eye blinks, without imposing a time-locked structure to the analysis, has been investigated. The analysis revealed statistically significant spatial and spectral modulations of the recorded brain activity according to the different levels of attentional demand, and a significant reduction in the number of eye blinks when a higher amount of attentional investment was required. Besides, the integration of information coming from high-density electroencephalography (EEG), brain source localization, and connectivity estimation allowed us to merge spectral and causal information between brain areas, characterizing a comprehensive model of neurophysiological processes behind attentional demand. The analysis of the association between eye and brain-related parameters revealed a statistically significant high correlation (R > 0.7) of eye blink rate with anterofrontal brain activity at 8 Hz, centroparietal brain activity at 12 Hz, and a significant moderate correlation with the participation of right Intra Parietal Sulcus in alpha band (R = -0.62). Due to these findings, this work suggests the possibility of using eye blinks measured from one sensor placed on the forehead as an unobtrusive measure correlating with neural mechanisms underpinning attentional demand.

A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection

Neuroimaging technologies have improved our understanding of deception and also exhibit their potential in revealing the origins of its neural mechanism. In this study, a quantitative power analysis method that uses the Welch power spectrum estimation of functional near-infrared spectroscopy (fNIRS) signals was proposed to examine the brain activation difference between the spontaneous deceptive behavior and controlled behavior. The power value produced by the model was applied to quantify the activity energy of brain regions, which can serve as a neuromarker for deception detection. Interestingly, the power analysis results generated from the Welch spectrum estimation method demonstrated that the spontaneous deceptive behavior elicited significantly higher power than that from the controlled behavior in the prefrontal cortex. Meanwhile, the power findings also showed significant difference between the spontaneous deceptive behavior and controlled behavior, indicating that the reward system was only involved in the deception. The proposed power analysis method for processing fNIRS data provides us an additional insight to understand the cognitive mechanism of deception.

Disentangling top-down and bottom-up influences on blinks in the visual and auditory domain

Sensory input as well as cognitive factors can drive the modulation of blinking. Our aim was to dissociate sensory driven bottom-up from cognitive top-down influences on blinking behavior and compare these influences between the auditory and the visual domain. Using an oddball paradigm, we found a significant pre-stimulus decrease in blink probability for visual input compared to auditory input. Sensory input further led to an early post-stimulus blink increase in both modalities if a task demanded attention to the input. Only visual input caused a pronounced early increase without a task. In case of a target or the omission of a stimulus (as compared to standard input), an additional late increase in blink rate was found in the auditory and visual domain. This suggests that blink modulation must be based on the interpretation of the input, but does not need any sensory input at all to occur. Our results show a complex modulation of blinking based on top-down factors such as prediction and attention in addition to sensory-based influences. The magnitude of the modulation is mainly influenced by general attentional demands, while the latency of this modulation allows dissociating general from specific top-down influences that are independent of the sensory domain.

Selective attention, not cognitive load, elicited fewer eyeblinks in a concealed information test

The concealed information test (CIT), a memory detection test, compares physiological responses to crime-related and crime-unrelated items. This study elucidated processes involving spontaneous eyeblinks during the CIT by manipulating participants' intention to conceal. Thirty-four participants committed mock theft. In the CIT, wherein eyeblinks are measured simultaneously with autonomic responses, the secret group concealed the crime-related item, whereas the no-secret group did not. As a result, heart rate (HR) was modulated by the intention of concealment in autonomic measures, whereas the effect of concealment on the decrease of eyeblinks was not found to be significant. In addition, the latency of the first eyeblink was longer for the crime-related item in both groups. These results imply that CIT eyeblinks mainly involve the process of selective attention for the item, and the latency of the first eyeblink reflects a delay in attentional disengagement from the item. This study also suggested that there is still room for improvement in simultaneously measuring eyeblinks and autonomic responses in the CIT.

A novel blink detection method based on pupillometry noise

Pupillometry (or the measurement of pupil size) is commonly used as an index of cognitive load and arousal. Pupil size data are recorded using eyetracking devices that provide an output containing pupil size at various points in time. During blinks the eyetracking device loses track of the pupil, resulting in missing values in the output file. The missing-sample time window is preceded and followed by a sharp change in the recorded pupil size, due to the opening and closing of the eyelids. This eyelid signal can create artificial effects if it is not removed from the data. Thus, accurate detection of the onset and the offset of blinks is necessary for pupil size analysis. Although there are several approaches to detecting and removing blinks from the data, most of these approaches do not remove the eyelid signal or can result in a relatively large amount of data loss. The present work suggests a novel blink detection algorithm based on the fluctuations that characterize pupil data. These fluctuations ("noise") result from measurement error produced by the eyetracker device. Our algorithm finds the onset and offset of the blinks on the basis of this fluctuation pattern and its distinctiveness from the eyelid signal. By comparing our algorithm to three other common blink detection methods and to results from two independent human raters, we demonstrate the effectiveness of our algorithm in detecting blink onset and offset. The algorithm's code and example files for processing multiple eye blinks are freely available for download ( https://osf.io/jyz43 ).

Blink: Characteristics, Controls, and Relation to Dry Eyes

Blink is a complex phenomenon that is profoundly affected by diverse endogenous and exogenous stimuli. It has been studied in the context of cognition, emotional, and psychological states, as an indicator of fatigue and sleepiness, particularly in the automobile and transportation industry, in visual tasking, and finally, as it relates to tear film stability and ocular surface health. The fact that it is highly variable and has input from so many sources makes it very difficult to study. In the present review, the behavior of blink in many of these systems is discussed, ultimately returning in each instance to a discussion of how these factors affect blink in the context of dry eyes. Blink is important to ocular surface health and to an individual's optimal functioning and quality of life. Disturbances in blink, as cause or effect, result in a breakdown of tear film stability, optical clarity, and visual function.

Beyond eye gaze: What else can eyetracking reveal about cognition and cognitive development?

This review provides an introduction to two eyetracking measures that can be used to study cognitive development and plasticity: pupil dilation and spontaneous blink rate. We begin by outlining the rich history of gaze analysis, which can reveal the current focus of attention as well as cognitive strategies. We then turn to the two lesser-utilized ocular measures. Pupil dilation is modulated by the brain's locus coeruleus-norepinephrine system, which controls physiological arousal and attention, and has been used as a measure of subjective task difficulty, mental effort, and neural gain. Spontaneous eyeblink rate correlates with levels of dopamine in the central nervous system, and can reveal processes underlying learning and goal-directed behavior. Taken together, gaze, pupil dilation, and blink rate are three non-invasive and complementary measures of cognition with high temporal resolution and well-understood neural foundations. Here we review the neural foundations of pupil dilation and blink rate, provide examples of their usage, describe analytic methods and methodological considerations, and discuss their potential for research on learning, cognitive development, and plasticity.

Eyeblink Activity as an Index of Cognitive Processing: Temporal Distribution of Eyeblinks as an Indicator of Expectancy in Semantic Priming

Eyeblink activity was examined as a psychophysiological index of cognitive processing during a typical semantic priming task. To examine the expectancy-induced effects, the proportion of semantically related pairs was controlled. 8 undergraduates engaged in a lexical decision task for target words. Each condition differed in target type (Semantically Related with prime vs Unrelated vs Nonword) and proportion of Semantically Related pairs (High vs Low). As a result, the temporal distribution of blinks was clearly influenced by the semantic priming effect. The peak of blink bursts, which is correlated with the end of cognitive processing, occurred the fastest in the semantically Related and High proportion condition. While blink latency showed larger individual differences, the temporal distribution of blinks was suggested as a more efficient index of cognitive processing.

Mapping the small-world properties of brain networks in deception with functional near-infrared spectroscopy

Deception is not a rare occurrence among human behaviors; however, the present brain mapping techniques are insufficient to reveal the neural mechanism of deception under spontaneous or controlled conditions. Interestingly, functional near-infrared spectroscopy (fNIRS) has emerged as a highly promising neuroimaging technique that enables continuous and noninvasive monitoring of changes in blood oxygenation and blood volume in the human brain. In this study, fNIRS was used in combination with complex network theory to extract the attribute features of the functional brain networks underling deception in subjects exhibiting spontaneous or controlled behaviors. Our findings revealed that the small-world networks of the subjects engaged in spontaneous behaviors exhibited greater clustering coefficients, shorter average path lengths, greater average node degrees, and stronger randomness compared with those of subjects engaged in control behaviors. Consequently, we suggest that small-world network topology is capable of distinguishing well between spontaneous and controlled deceptions.

Eye-blinks in choice response tasks uncover hidden aspects of information processing

Spontaneous eye-blinks occur much more often than it would be necessary to maintain the tear film on the eyes. Various factors like cognitive demand, task engagement, or fatigue are influencing spontaneous blink rate. During cognitive information processing there is evidence that blinks occur preferably at moments that can be assigned to input stream segmentation. We investigated blinking behavior in three different visual choice response experiments (Experiment 1: spatial Stimulus-Response correspondence, Experiment 2: Change Detection, Experiment 3: Continuous performance Test - AX version). Blinks during the experimental tasks were suppressed when new information was expected, as well as during cognitive processing until the response was executed. Blinks in go trials occurred within a short and relatively constant interval after manual responses. However, blinks were not a side effect of manual behavior, as they occurred in a similar manner in no-go trials in which no manual response was executed. In these trials, blinks were delayed when a prepared response had to be inhibited, compared to trials in which no response was intended. Additionally, time on task effects for no-go blinks mirrored those obtained in go trials. Thus, blinks seem to provide a reliable measure for cognitive processing beyond (or rather additional to) manual responses.

Modulation of resource allocation by intelligent individuals in linguistic, mathematical and visuo-spatial tasks

This study investigates two questions: first, how individuals with high-intelligence allocate cognitive resources while solving linguistic, mathematical and visuo-spatial tasks with varying degree of difficulty as compared to individuals with low intelligence? Second, how to distinguish between high and low intelligent individuals by analyzing pupil dilation and eye blink together? We measured the response time, error rates along with pupil dilation and eye blink rate that indicate resource allocation. We divided the whole processing into three stages namely: pre-stimuli (5s prior to stimuli onset), during stimuli and post stimuli (until 5s after the response) for better assessment of preparation and resource allocation strategies. Individuals with high intelligence showed greater task evoked pupil dilation, decreased eye blink with less response time and error rates during-stimuli stage (processing) of tough linguistic and visuo-spatial tasks but not during mathematical tasks. The finding suggests that individuals with high intelligence allocate more resources if the task demands are high else they allocate less resources. Greater pre-stimuli pupil dilation and increased eye blink of high intelligent individuals in all tasks indicated their attentiveness and preparedness. The result of our study shows that individuals with high intelligence are more attentive and flexible in terms of altering the resource allocation strategy according to task demand. Eye-blinks along with pupil dilation and other behavioral parameters can be reliably used to assess the intelligence of an individual and the analysis of pupil dilation and blink rate at pre-stimuli stage can be crucial in distinguishing individuals with varying intelligence.

Quantitative Assessment of the Training Improvement in a Motor-Cognitive Task by Using EEG, ECG and EOG Signals

Generally, the training evaluation methods consist in experts supervision and qualitative check of the operator's skills improvement by asking them to perform specific tasks and by verifying the final performance. The aim of this work is to find out if it is possible to obtain quantitative information about the degree of the learning process throughout the training period by analyzing neuro-physiological signals, such as the electroencephalogram, the electrocardiogram and the electrooculogram. In fact, it is well known that such signals correlate with a variety of cognitive processes, e.g. attention, information processing, and working memory. A group of 10 subjects have been asked to train daily with the NASA multi-attribute-task-battery. During such training period the neuro-physiological, behavioral and subjective data have been collected. In particular, the neuro-physiological signals have been recorded on the first (T1), on the third (T3) and on the last training day (T5), while the behavioral and subjective data have been collected every day. Finally, all these data have been compared for a complete overview of the learning process and its relations with the neuro-physiological parameters. It has been shown how the integration of brain activity, in the theta and alpha frequency bands, with the autonomic parameters of heart rate and eyeblink rate could be used as metric for the evaluation of the learning progress, as well as the final training level reached by the subjects, in terms of request of cognitive resources.

Detecting false intent using eye blink measures

Eye blink measures have been shown to be diagnostic in detecting deception regarding past acts. Here we examined—across two experiments with increasing degrees of ecological validity—whether changes in eye blinking can be used to determine false intent regarding future actions. In both experiments, half of the participants engaged in a mock crime and then transported an explosive device with the intent of delivering it to a “contact” that would use it to cause a disturbance. Eye blinking was measured for all participants when presented with three types of questions: relevant to intent to transport an explosive device, relevant to intent to engage in an unrelated illegal act, and neutral questions. Experiment 1 involved standing participants watching a video interviewer with audio presented ambiently. Experiment 2 involved standing participants questioned by a live interviewer. Across both experiments, changes in blink count during and immediately following individual questions, total number of blinks, and maximum blink time length differentiated those with false intent from truthful intent participants. In response to questions relevant to intent to deliver an explosive device vs. questions relevant to intent to deliver illegal drugs, those with false intent showed a suppression of blinking during the questions when compared to the 10 s period after the end of the questions, a lower number of blinks, and shorter maximum blink duration. The results are discussed in relation to detecting deception about past activities as well as to the similarities and differences to detecting false intent as described by prospective memory and arousal.

Mental workload measurement for emergency operating procedures in digital nuclear power plants

Mental workload is a major consideration for the design of emergency operation procedures (EOPs) in nuclear power plants. Continuous and objective measures are desired. This paper compares seven mental workload measurement methods (pupil size, blink rate, blink duration, heart rate variability, parasympathetic/sympathetic ratio, total power and (Goals, Operations, Methods, and Section Rules)-(Keystroke Level Model) GOMS-KLM-based workload index) with regard to sensitivity, validity and intrusiveness. Eighteen participants performed two computerised EOPs of different complexity levels, and mental workload measures were collected during the experiment. The results show that the blink rate is sensitive to both the difference in the overall task complexity and changes in peak complexity within EOPs, that the error rate is sensitive to the level of arousal and correlate to the step error rate and that blink duration increases over the task period in both low and high complexity EOPs. Cardiac measures were able to distinguish tasks with different overall complexity. The intrusiveness of the physiological instruments is acceptable. Finally, the six physiological measures were integrated using group method of data handling to predict perceived overall mental workload.

PRACTITIONER SUMMARY

The study compared seven measures for evaluating the mental workload with emergency operation procedure in nuclear power plants. An experiment with simulated procedures was carried out, and the results show that eye response measures are useful for assessing temporal changes of workload whereas cardiac measures are useful for evaluating the overall workload.

Telling lies: the irrepressible truth?

Telling a lie takes longer than telling the truth but precisely why remains uncertain. We investigated two processes suggested to increase response times, namely the decision to lie and the construction of a lie response. In Experiments 1 and 2, participants were directed or chose whether to lie or tell the truth. A colored square was presented and participants had to name either the true color of the square or lie about it by claiming it was a different color. In both experiments we found that there was a greater difference between lying and telling the truth when participants were directed to lie compared to when they chose to lie. In Experiments 3 and 4, we compared response times when participants had only one possible lie option to a choice of two or three possible options. There was a greater lying latency effect when questions involved more than one possible lie response. Experiment 5 examined response choice mechanisms through the manipulation of lie plausibility. Overall, results demonstrate several distinct mechanisms that contribute to additional processing requirements when individuals tell a lie.

[Non-contact measurement of eye movements in the detection of deception]

The effectiveness of detecting deception by measuring eye movements without making contact was investigated. A deception-detection protocol was used with two conditions based on the stimulus similarity to the critical image. Volunteer participants (N = 63) were randomly assigned to either the high or the low-similarity condition. They were randomly presented with critical and non-critical images and their eye movements were measured without contact. High-similarity images were presented in the high-similarity condition and low-similarity images were presented in the low-similarity condition. The results showed no significant differences in eye movements between the critical and non-critical images in the high-similarity condition. In contrast, in the low-similarity condition, the frequency and total length of time for glancing at critical images were significantly lower than for glancing at non-critical images. These results are suggestive of the effectiveness of the non-contact measurement of eye movements for the detection of deception.

Combining blink, pupil, and response time measures in a concealed knowledge test

The response time (RT) based Concealed Knowledge Test (CKT) has been shown to accurately detect participants' knowledge of mock-crime-related information. Tests based on ocular measures such as pupil-size and blink-rate have sometimes resulted in poor classification, or lacked detailed classification analyses. The present study examines the fitness of multiple pupil and blink related responses in the CKT paradigm. To maximize classification efficiency, participants' concealed knowledge was assessed using both individual test measures and combinations of test measures. Results show that individual pupil-size, pupil-slope, and pre-response blink-rate measures produce efficient classifications. Combining pupil and blink measures yielded more accuracy classifications than individual ocular measures. Although RT-based tests proved efficient, combining RT with ocular measures had little incremental benefit. It is argued that covertly assessing ocular measures during RT-based tests may guard against effective countermeasure use in applied settings. A compound classification procedure was used to categorize individual participants and yielded high hit rates and low false-alarm rates without the need for adjustments between test paradigms and subject populations. We conclude that with appropriate test paradigms and classification analyses, ocular measures may prove as effective as other indices, though additional research is needed.

The current and future status of the concealed information test for field use

The Concealed Information Test (CIT) is a psychophysiological technique for examining whether a person has knowledge of crime-relevant information. Many laboratory studies have shown that the CIT has good scientific validity. However, the CIT has seldom been used for actual criminal investigations. One successful exception is its use by the Japanese police. In Japan, the CIT has been widely used for criminal investigations, although its probative force in court is not strong. In this paper, we first review the current use of the field CIT in Japan. Then, we discuss two possible approaches to increase its probative force: sophisticated statistical judgment methods and combining new psychophysiological measures with classic autonomic measures. On the basis of these considerations, we propose several suggestions for future practice and research involving the field CIT.

The timing and temporal patterns of eye blinking are dynamically modulated by attention

A number of human behaviors and movements show self-similar temporal patterns in their occurrence over time. Human walking, finger tapping and heartbeat intervals have fluctuations that are statistically similar at multiple time scales. However, whether eye blinking, which is a unique human behavior that occurs spontaneously, embeds a similar temporal structure within other types of movements is largely unknown. In this study, we used attention-requiring tasks to assess how the temporal pattern of eye blinking is altered in both the second and sub-second time scales. Our results showed that eyeblink activity was more suppressed as the task difficulty level increased and was facilitated immediately after exposure to auditory stimuli, which were presented for 6 to 14s. Moreover, similar transient suppressive and facilitative patterns were observed in the response period, which lasted for less than one second. Furthermore, we found that spontaneous eye blinking intervals fluctuated according to an 1/f scaling property, which is widely observed in various human movements. These results suggest that the dynamics of eye blinking under specific cognitive tasks exhibit a similar temporal structure at multiple time scales.

Spontaneous eyeblinks are correlated with responses during the Stroop task

The timing and frequency of spontaneous eyeblinking is thought to be influenced by ongoing internal cognitive or neurophysiological processes, but how precisely these processes influence the dynamics of eyeblinking is still unclear. This study aimed to better understand the functional role of eyeblinking during cognitive processes by investigating the temporal pattern of eyeblinks during the performance of attentional tasks. The timing of spontaneous eyeblinks was recorded from 28 healthy subjects during the performance of both visual and auditory versions of the Stroop task, and the temporal distributions of eyeblinks were estimated in relation to the timing of stimulus presentation and vocal response during the tasks. We found that the spontaneous eyeblink rate increased during Stroop task performance compared with the resting rate. Importantly, the subjects (17/28 during the visual Stroop, 20/28 during the auditory Stroop) were more likely to blink before a vocal response in both tasks (150–250 msec) and the remaining subjects were more likely to blink soon after the vocal response (200–300 msec), regardless of the stimulus type (congruent or incongruent) or task difficulty. These findings show that spontaneous eyeblinks are closely associated with responses during the performance of the Stroop task on a short time scale and suggest that spontaneous eyeblinks likely signal a shift in the internal cognitive or attentional state of the subjects.

Blink detection robust to various facial poses

Applications based on eye-blink detection have increased, as a result of which it is essential for eye-blink detection to be robust and non-intrusive irrespective of the changes in the user's facial pose. However, most previous studies on camera-based blink detection have the disadvantage that their performances were affected by the facial pose. They also focused on blink detection using only frontal facial images. To overcome these disadvantages, we developed a new method for blink detection, which maintains its accuracy despite changes in the facial pose of the subject. This research is novel in the following four ways. First, the face and eye regions are detected by using both the AdaBoost face detector and a Lucas-Kanade-Tomasi (LKT)-based method, in order to achieve robustness to facial pose. Secondly, the determination of the state of the eye (being open or closed), needed for blink detection, is based on two features: the ratio of height to width of the eye region in a still image, and the cumulative difference of the number of black pixels of the eye region using an adaptive threshold in successive images. These two features are robustly extracted irrespective of the lighting variations by using illumination normalization. Thirdly, the accuracy of determining the eye state - open or closed - is increased by combining the above two features on the basis of the support vector machine (SVM). Finally, the SVM classifier for determining the eye state is adaptively selected according to the facial rotation. Experimental results using various databases showed that the blink detection by the proposed method is robust to various facial poses.

Spontaneous eye blinks are entrained by finger tapping

We studied the mutual cross-talk between spontaneous eye blinks and continuous, self-paced unimanual and bimanual tapping. Both types of motor activities were analyzed with regard to their time-structure in synchronization-continuation tapping tasks which involved different task instructions, namely "standard" finger tapping (Experiment 1), "strong" tapping (Experiment 2) requiring more forceful finger movements, and "impulse-like" tapping (Experiment 3) where upward-downward finger movements had to be very fast. In a further control condition (Experiment 4), tapping was omitted altogether. The results revealed a prominent entrainment of spontaneous blink behavior by the manual tapping, with bimanual tapping being more effective than unimanual tapping, and with the "strong" and "impulse-like" tapping showing the largest effects on blink timing. Conversely, we found no significant effects of the tapping on the timing of the eye blinks across all experiments. The findings suggest a functional overlap of the motor control structures responsible for voluntary, rhythmic finger movements and eye blinking behavior.

Blink before and after you think: blinks occur prior to and following cognitive load indexed by pupillary responses

Pupil dilation and blinks provide complementary, mutually exclusive indices of information processing. Though each index is associated with cognitive load, the occurrence of a blink precludes the measurement of pupil diameter. These indices have generally been assessed in independent literatures. We examine the extent to which these measures are related on two cognitive tasks using a novel method that quantifies the proportion of trials on which blinks occur at each sample acquired during the trial. This measure allows cross-correlation of continuous pupil-dilation and blink waveforms. Results indicate that blinks occur during early sensory processing and following sustained information processing. Pupil dilation better reflects sustained information processing. Together these indices provide a rich picture of the time course of information processing, from early reactivity through sustained cognition, and after stimulus-related cognition ends.

Psychopathy and nonverbal indicators of deception in offenders

The current study examined psychopathy and nonverbal indicators of deception in an incarcerated sample. Nonverbal behaviors were coded from videotapes of 45 male offenders telling true and fabricated stories about crimes. Interpersonal features of psychopathy were associated with inflated views of lying ability, verbosity, and increases in blinking, illustrator use, and speech hesitations. While lying, the more psychopathic offenders spoke faster and demonstrated increases in blinking and head movements. Indicators of deception in offenders were somewhat different from those typically observed in non-offender populations. These findings indicate that personality factors may have an impact on nonverbal indicators of deception in criminal justice settings where the detection of deception is of utmost concern.

Spontaneous Eye Blink Rates vary according to individual differences in generalized control perception

This study tested the hypothesis that individual differences in generalized control perception for 43 undergraduate adults may be reflected in Spontaneous Eye Blink Rates during conversation in an interview. Control perception was assessed by means of Rotter's internal-external Locus of Control questionnaires, while Spontaneous Eye Blink Rates were computed from filmed videos of interviews consisting of a series of questions which could presumably have triggered different mental states. Pearson correlations and linear regression analyses indicated that the individual differences in Spontaneous Eye Blink Rates did not differ significantly across different questions, but that Spontaneous Eye Blink Rates measured over the entire interview correlated positively and significantly with an internal Locus of Control (r = .26). This could be interpreted as modest but corroborative evidence that a personality trait reflecting control perception may have a biological component. The possible roles of dopamine neurotransmission and frontal cortex involvement in higher cognition and Locus of Control are discussed.

Meticulously detailed eye region model and its application to analysis of facial images

We propose a system that is capable of detailed analysis of eye region images in terms of the position of the iris, degree of eyelid opening, and the shape, complexity, and texture of the eyelids. The system uses a generative eye region model that parameterizes the fine structure and motion of an eye. The structure parameters represent structural individuality of the eye, including the size and color of the iris, the width, boldness, and complexity of the eyelids, the width of the bulge below the eye, and the width of the illumination reflection on the bulge. The motion parameters represent movement of the eye, including the up-down position of the upper and lower eyelids and the 2D position of the iris. The system first registers the eye model to the input in a particular frame and individualizes it by adjusting the structure parameters. The system then tracks motion of the eye by estimating the motion parameters across the entire image sequence. Combined with image stabilization to compensate for appearance changes due to head motion, the system achieves accurate registration and motion recovery of eyes.