Eye blink rate increases as a function of cognitive load during an auditory oddball paradigm

Saccades and Blinks Index Cognitive Demand during Auditory Noncanonical Sentence Comprehension

Noncanonical sentence structures pose comprehension challenges because they require increased cognitive demand. Prosody may partially alleviate this cognitive load. These findings largely stem from behavioral studies, yet physiological measures may reveal additional insights into how cognition is deployed to parse sentences. Pupillometry has been at the forefront of investigations into physiological measures of cognitive demand during auditory sentence comprehension. This study offers an alternative approach by examining whether eye-tracking measures, including blinks and saccades, index cognitive demand during auditory noncanonical sentence comprehension and whether these metrics are sensitive to reductions in cognitive load associated with typical prosodic cues. We further investigated how eye-tracking patterns differ across correct and incorrect responses, as a function of time, and how each related to behavioral measures of cognition. Canonical and noncanonical sentence comprehension was measured in 30 younger adults using an auditory sentence-picture matching task. We also assessed participants' attention and working memory. Blinking and saccades both differentiate noncanonical sentences from canonical sentences. Saccades further distinguish noncanonical structures from each other. Participants made more saccades on incorrect than correct trials. The number of saccades also related to working memory, regardless of syntax. However, neither eye-tracking metric was sensitive to the changes in cognitive demand that was behaviorally observed in response to typical prosodic cues. Overall, these findings suggest that eye-tracking indices, particularly saccades, reflect cognitive demand during auditory noncanonical sentence comprehension when visual information is present, offering greater insights into the strategies and neural resources participants use to parse auditory sentences.

Differential Effects of Visual and Auditory Cognitive Tasks on Smooth Pursuit Eye Movements

Smooth pursuit eye movements (SPEM) are important to gather visual information that guides our interactions with moving objects (e.g., tracking a tennis ball, or following a car when driving). In many neurological conditions, from Parkinson's disease to stroke, the voluntary control of SPEM can be compromised. Therefore, SPEMs can serve as sensitive proxies for assessing cognitive and sensorimotor function. Prior research has shown that SPEMs are influenced by attention and working memory load, yet it remains unclear how the sensory modality of concurrent tasks interacts with these effects. Here, we conducted a 3 (working memory load: no load, easy [low load], and hard [high load]) × 2 (sensory modality: visual vs. auditory) experiment to examine how working memory load and secondary task modality interact to affect SPEM in healthy young adults. Participants tracked a moving circle while simultaneously performing an arithmetic task, where they added either constant (1) or variable (1-5) numbers which were presented visually or auditorily. Our results showed that a secondary auditory task increased tracking variability during high cognitive load. In contrast, we found that the visual task improved tracking, reducing variability irrespective of cognitive load. We interpret our results as evidence that auditory processing requires additional top-down control that is critical for the control of smooth pursuit, diverting resources required for smooth pursuit and, consequently, increasing SPEM variability. These findings emphasize the importance of sensory modality in understanding the interactions between working memory and oculomotor control. We suggest that auditory secondary cognitive tasks may provide a more sensitive test of sensorimotor control deficits in future research with clinical populations.

Revisiting eye blink in Parkinson's disease

Spontaneous blinking is a rapid and unconscious type of blinking that has been linked to several cognitive processes. Blink rate has been established as a reliable measure of cognitive processing and a predictor of dopamine-related cognitive function. Patients with Parkinson's disease (PD) have a reduced spontaneous blink rate. In this study, we propose an additional measure of blink characteristic, namely blink duration, and evaluate its alteration in a large cohort of 107 patients with PD. We also investigate the relationship between blink rate and blink duration and disease characteristics such as severity and dopaminergic neuronal loss. The results show that the blink rate is reduced, and blink duration is increased in patients compared to healthy controls. Blink rate is related to motor deficit severity and significantly correlated with dopamine depletion (dopamine transporter striatal binding ratio). Conversely, blink duration is related to non-motor aspects such as sleepiness. These findings highlight the potential of blink as a distinguishing feature of Parkinson's disease, underscoring the importance of incorporating blink assessments into standardized oculomotor testing protocols for PD.

Artifact filtering application to increase online parity in a communication BCI: progress toward use in daily-life

A significant challenge in developing reliable Brain-Computer Interfaces (BCIs) is the presence of artifacts in the acquired brain signals. These artifacts may lead to erroneous interpretations, poor fitting of models, and subsequent reduced online performance. Furthermore, BCIs in a home or hospital setting are more susceptible to environmental noise. Artifact handling procedures aim to reduce signal interference by filtering, reconstructing, and/or eliminating unwanted signal contaminants. While straightforward conceptually and largely undisputed as essential, suitable artifact handling application in BCI systems remains unsettled and may reduce performance in some cases. A potential confound that remains unexplored in the majority of BCI studies using these procedures is the lack of parity with online usage (e.g., online parity). This manuscript compares classification performance between frequently used offline digital filtering, using the whole dataset, and an online digital filtering approach where the segmented data epochs that would be used during closed-loop control are filtered instead. In a sample of healthy adults (n = 30) enrolled in a BCI pilot study to integrate new communication interfaces, there were significant benefits to model performance when filtering with online parity. While online simulations indicated similar performance across conditions in this study, there appears to be no drawback to the approach with greater online parity.

Assessment of PTSD in military personnel via machine learning based on physiological habituation in a virtual immersive environment

Posttraumatic stress disorder (PTSD) is a complex mental health condition triggered by exposure to traumatic events that leads to physical health problems and socioeconomic impairments. Although the complex symptomatology of PTSD makes diagnosis difficult, early identification and intervention are crucial to mitigate the long-term effects of PTSD and provide appropriate treatment. In this study, we explored the potential for physiological habituation to stressful events to predict PTSD status. We used passive physiological data collected from 21 active-duty United States military personnel and veterans in an immersive virtual environment with high-stress combat-related conditions involving trigger events such as explosions or flashbangs. In our work, we proposed a quantitative measure of habituation to stressful events that can be quantitatively estimated through physiological data such as heart rate, galvanic skin response and eye blinking. Using a Gaussian process classifier, we prove that habituation to stressful events is a predictor of PTSD status, measured via the PTSD Checklist Military version (PCL-M). Our algorithm achieved an accuracy of 80.95% across our cohort. These findings suggest that passively collected physiological data may provide a noninvasive and objective method to identify individuals with PTSD. These physiological markers could improve both the detection and treatment of PTSD.

Spontaneous eye blinking as a diagnostic and prognostic marker in disorders of consciousness: Protocol of an international multicentre longitudinal study

BACKGROUND

Diagnostic and prognostic decision-making in patients with Disorders of Consciousness (DoC) is challenging. It has been suggested that spontaneous eye blink rate is an index of patients' level of consciousness easy to detect in clinical practice. Further blinking features (i.e., amplitude, duration, variability in intervals between blinks) may change as a function of cognitive load, but have not been investigated in patients with DoC.

OBJECTIVE

This multicentre, longitudinal study aims at exploring the diagnostic and prognostic value of spontaneous eye blinking features in DoC.

METHODS

Eight European medical institutions will enrol consecutively admitted adult patients with DoC. Within two weeks from study entry demographic, anamnestic and clinical data will be collected. Moreover, patients will undergo two 20-minute EEG-EOG recordings at rest, to collect blinking features and EEG activity. A clinical follow-up will be performed after 6 months. A group of healthy individuals will be enrolled for reference.

RESULTS

Possible differences in blink features between patients and the reference group, differences across diagnostic sub-groups, and correlations between blinking features and clinical outcome will be investigated.

CONCLUSION

The results of this study might help clinicians to reduce misdiagnosis rate in DoC and provide useful information for prognostication and care pathway plan.

Spontaneous eye blinks in horses (Equus caballus) are modulated by attention

Spontaneous eye blinks are brief closures of both eyelids. The spontaneous eye blink rate (SEBR) exceeds physiological corneal needs and is modulated by emotions and cognitive states, including vigilance and attention, in humans. In several animal species, the SEBR is modulated by stress and antipredator vigilance, which may limit the loss of visual information due to spontaneous eye closing. Here, we investigated whether the SEBR is modulated by attention in the domestic horse (Equus caballus). Our data supported previous studies indicating a tonic SEBR specific to each individual. We also found that, superimposed on a tonic SEBR, phasic changes were induced by cognitive processing. Attention downmodulated the SEBR, with the magnitude of blink inhibition proportional to the degree of attentional selectivity. On the other hand, reward anticipation upregulated the SEBR. Our data also suggested that horses possess the cognitive property of object permanence: they understand that an object that is no longer in their visual field has not ceased to exist. In conclusion, our results suggested that spontaneous eye blinks in horses are modulated by attentional cognitive processing.

Now it's your turn!: Eye blink rate in a Jenga task modulated by interaction of task wait times, effortful control, and internalizing behaviors

Dopamine is a versatile neurotransmitter with implications in many domains, including anxiety and effortful control. Where high levels of effortful control are often regarded as adaptive, other work suggests that high levels of effortful control may be a risk factor for anxiety. Dopamine signaling may be key in understanding these relations. Eye blink rate is a non-invasive proxy metric of midbrain dopamine activity. However, much work with eye blink rate has been constrained to screen-based tasks which lack in ecological validity. We tested whether changes in eye blink rate during a naturalistic effortful control task differ as a function of parent-reported effortful control and internalizing behaviors. Children played a Jenga-like game with an experimenter, but for each trial the experimenter took an increasingly long time to take their turn. Blinks-per-second were computed during each wait period. Multilevel modeling examined the relation between duration of wait period, effortful control, and internalizing behaviors on eye blink rate. We found a significant 3-way interaction between effortful control, internalizing behaviors, and duration of the wait period. Probing this interaction revealed that for children with low reported internalizing behaviors (-1 SD) and high reported effortful control (+1 SD), eye blink rate significantly decreased as they waited longer to take their turn. These findings index task-related changes in midbrain dopamine activity in relation to naturalistic task demands, and that these changes may vary as a function of individual differences in effortful control and internalizing behaviors. We discuss possible top-down mechanisms that may underlie these differences.

The psychophysiology of Mastermind: Characterizing response times and blinking in a high-stakes television game show

Television game shows have proven to be a valuable resource for studying human behavior under conditions of high stress and high stakes. However, previous work has focused mostly on choices-ignoring much of the rich visual information that is available on screen. Here, we take a first step to extracting more of this information by investigating the response times and blinking of contestants in the BBC show Mastermind. In Mastermind, contestants answer rapid-fire quiz questions while a camera slowly zooms in on their faces. By labeling contestants' behavior and blinks from 25 episodes, we asked how accuracy, response times, and blinking varied over the course of the game. For accuracy and response times, we tested whether contestants responded more accurately and more slowly after an error-exhibiting the "post-error increase in accuracy" and "post-error slowing" which has been repeatedly observed in the lab. For blinking, we tested whether blink rates varied according to the cognitive demands of the game-decreasing during periods of cognitive load, such as when pondering a response, and increasing at event boundaries in the task, such as the start of a question. In contrast to the lab, evidence for post-error changes in accuracy and response time was weak, with only marginal effects observed. In line with the lab, blinking varied over the course of the game much as we predicted. Overall, our findings demonstrate the potential of extracting dynamic signals from game shows to study the psychophysiology of behavior in the real world.

Blink-Related Oscillations Provide Naturalistic Assessments of Brain Function and Cognitive Workload within Complex Real-World Multitasking Environments

BACKGROUND

There is a significant need to monitor human cognitive performance in complex environments, with one example being pilot performance. However, existing assessments largely focus on subjective experiences (e.g., questionnaires) and the evaluation of behavior (e.g., aircraft handling) as surrogates for cognition or utilize brainwave measures which require artificial setups (e.g., simultaneous auditory stimuli) that intrude on the primary tasks. Blink-related oscillations (BROs) are a recently discovered neural phenomenon associated with spontaneous blinking that can be captured without artificial setups and are also modulated by cognitive loading and the external sensory environment-making them ideal for brain function assessment within complex operational settings.

METHODS

Electroencephalography (EEG) data were recorded from eight adult participants (five F, M = 21.1 years) while they completed the Multi-Attribute Task Battery under three different cognitive loading conditions. BRO responses in time and frequency domains were derived from the EEG data, and comparisons of BRO responses across cognitive loading conditions were undertaken. Simultaneously, assessments of blink behavior were also undertaken.

RESULTS

Blink behavior assessments revealed decreasing blink rate with increasing cognitive load (p < 0.001). Prototypical BRO responses were successfully captured in all participants (p < 0.001). BRO responses reflected differences in task-induced cognitive loading in both time and frequency domains (p < 0.05). Additionally, reduced pre-blink theta band desynchronization with increasing cognitive load was also observed (p < 0.05).

CONCLUSION

This study confirms the ability of BRO responses to capture cognitive loading effects as well as preparatory pre-blink cognitive processes in anticipation of the upcoming blink during a complex multitasking situation. These successful results suggest that blink-related neural processing could be a potential avenue for cognitive state evaluation in operational settings-both specialized environments such as cockpits, space exploration, military units, etc. and everyday situations such as driving, athletics, human-machine interactions, etc.-where human cognition needs to be seamlessly monitored and optimized.

Spontaneous Eye Blinks Map the Probability of Perceptual Reinterpretation During Visual and Auditory Ambiguity

Spontaneous eye blinks are modulated around perceptual events. Our previous study, using a visual ambiguous stimulus, indicated that blink probability decreases before a reported perceptual switch. In the current study, we tested our hypothesis that an absence of blinks marks a time in which perceptual switches are facilitated in- and outside the visual domain. In three experiments, presenting either a visual motion quartet in light or darkness or a bistable auditory streaming stimulus, we found a co-occurrence of blink rate reduction with increased perceptual switch probability. In the visual domain, perceptual switches induced by a short interruption of visual input (blank) allowed an estimate of the timing of the perceptual event with respect to the motor response. This provided the first evidence that the blink reduction was not a consequence of the perceptual switch. Importantly, by showing that the time between switches and the previous blink was significantly longer than the inter-blink interval, our studies allowed to conclude that perceptual switches did not happen at random but followed a prolonged period of nonblinking. Correspondingly, blink rate and switch rate showed an inverse relationship. Our study supports the idea that the absence or presence of blinks maps perceptual processes independent of the sensory modality.

Decoding Eye Blink and Related EEG Activity in Realistic Working Environments

Accurately evaluating cognitive load during work-related tasks in complex real-world environments is challenging, leading researchers to investigate the use of eye blinking as a fundamental pacing mechanism for segmenting EEG data and understanding the neural mechanisms associated with cognitive workload. Yet, little is known about the temporal dynamics of eye blinks and related visual processing in relation to the representation of task-specific information. Therefore, we analyzed EEG responses from two experiments involving simulated driving (re-active and pro-active) with three levels of task load for each, as well as operating a steam engine (active vs. passive), to decode the temporal dynamics of eye blink activity and the subsequent neural activity that follows blinking. As a result, we successfully decoded the binary representation of difficulty levels for pro-active driving using multivariate pattern analysis. However, the decoding level varied for different re-active driving conditions, which could be attributed to the required level of alertness. Furthermore, our study revealed that it was possible to decode both driving types as well as steam engine operating conditions, with the most significant decoding activity observed approximately 200 ms after a blink. Additionally, our findings suggest that eye blinks have considerable potential for decoding various cognitive states that may not be discernible through neural activity, particularly near the peak of the blink. The findings demonstrate the potential of blink-related measures alongside EEG data to decode cognitive states during complex tasks, with implications for improving evaluations of cognitive and behavioral states during tasks, such as driving and operating machinery.

Usefulness of the Blink Reflex in Diagnosing Isolated Infraorbital Neuropathy Following Midface Augmentation with AlloPlastic Facial Implants: A Case Report

For the preoperative evaluation of infraorbital nerve injury, most clinicians depend on the patient’s subjective symptoms or judgements, lacking a generalized and objective evaluation method. Due to the limitations in subjective evaluations for accurate diagnosis of infraorbital nerve injury, we used the blink reflex to objectively evaluate injury to the infraorbital nerve. A 49-year-old female, who had previously undergone midface augmentation with alloplastic implants, presented with sensory loss in the left upper lip, nose tip, and lower palatal area. Physical examination revealed sensation loss in the area innervated by the infraorbital nerve. Facial three-dimensional computed tomography did not identify compression of the infraorbital nerve. The blink reflex study of the infraorbital nerve was evaluated preoperatively. After the patient was diagnosed with injury along the infraorbital nerve pathway from alloplastic facial implants, she underwent facial implant removal with decompression surgery. The patient experienced a significant decrease in hypoesthesia, and her sensory function improved. The blink reflex study was an effective method to objectively diagnose infraorbital neuropathy. Therefore, clinical use of the blink reflex study as an electrophysiological diagnostic tool is recommended to investigate infraorbital nerve injuries.

Relationship between Eye Blink Frequency and Incremental Exercise among Young Healthy Men

The aim of the study was to verify the correlation between the frequency of blinking and aerobic physical exercise. The research subjects were 13 healthy man aged 23.3 ± 1 year. Measurements of the blink rate and eye closure times were performed during a progressive aerobic test on a cycle ergometer. During the test, power was gradually increased every minute by 25 W, starting from 50 W. Data acquisition involved using a GoPro camera mounted to the helmet of the research subject. The test continued until the research subject refused to continue. The subjects did not know the goal of the test, in order to ensure objectivity and obtain natural results. The largest number of statistically significant differences was observed between the initial stages and 250 W, as well as between 250 W and 325 W. The analysis showed no significant differences in blink rate, eye closure time, and single blink time in terms of heart rate ranges. Regression models were also determined for eye closure time, blink frequency, and single blink time. The analysis showed that blink frequency and eye closure time were determined by a group of factors (the value of cycle ergometer load power, heart rate, body weight, adipose tissue mass, fat-free mass, and total body water and body surface ratio).

Let Complexity Bring Clarity: A Multidimensional Assessment of Cognitive Load Using Physiological Measures

The effects of cognitive load on driver behavior and traffic safety are unclear and in need of further investigation. Reliable measures of cognitive load for use in research and, subsequently, in the development and implementation of driver monitoring systems are therefore sought. Physiological measures are of interest since they can provide continuous recordings of driver state. Currently, however, a few issues related to their use in this context are not usually taken into consideration, despite being well-known. First, cognitive load is a multidimensional construct consisting of many mental responses (cognitive load components) to added task demand. Yet, researchers treat it as unidimensional. Second, cognitive load does not occur in isolation; rather, it is part of a complex response to task demands in a specific operational setting. Third, physiological measures typically correlate with more than one mental state, limiting the inferences that can be made from them individually. We suggest that acknowledging these issues and studying multiple mental responses using multiple physiological measures and independent variables will lead to greatly improved measurability of cognitive load. To demonstrate the potential of this approach, we used data from a driving simulator study in which a number of physiological measures (heart rate, heart rate variability, breathing rate, skin conductance, pupil diameter, eye blink rate, eye blink duration, EEG alpha power, and EEG theta power) were analyzed. Participants performed a cognitively loading n-back task at two levels of difficulty while driving through three different traffic scenarios, each repeated four times. Cognitive load components and other coinciding mental responses were assessed by considering response patterns of multiple physiological measures in relation to multiple independent variables. With this approach, the construct validity of cognitive load is improved, which is important for interpreting results accurately. Also, the use of multiple measures and independent variables makes the measurements (when analyzed jointly) more diagnostic-that is, better able to distinguish between different cognitive load components. This in turn improves the overall external validity. With more detailed, diagnostic, and valid measures of cognitive load, the effects of cognitive load on traffic safety can be better understood, and hence possibly mitigated.

Spontaneous eye blinking as a diagnostic marker in prolonged disorders of consciousness

Clinical diagnosis of patients with prolonged disorders of consciousness is very challenging. As spontaneous eye blink rate (EBR) is reliably correlated with cognitive activity in healthy individuals, we investigated whether EBR could serve as a marker of patients' level of consciousness. We assessed ten patients in prolonged Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS; three females; mean age = 50.3 ± 17.8 years) and fourteen patients in Minimally Conscious State (MCS; three females; mean age = 52.9 ± 17.5 years) at their admission to a rehabilitation unit after the acute phase. During two separate 3-min rest conditions, we recorded patients' EBR by integrating on-line visual and off-line electro-oculographic count. We also assessed EBR during two auditory oddball tasks, i.e. passive listening and active counting of target tones in a sub-group of patients. EBR was significantly higher in MCS than in VS/UWS; moreover, EBR positively correlated with a validated index of responsiveness derived from the Coma Recovery Scale-Revised. Patients' mean EBR showed no significant differences within sessions and across experimental conditions of the oddball task, in both VS/UWS and MCS. Our findings suggest that, at least in the post-acute phase, observing patients' EBR for 3 min at rest could help to discriminate between VS/UWS and MCS, improving accuracy of clinical diagnosis.

Gaze Behavior During Navigation and Visual Search of an Open-World Virtual Environment

Eye tracking has been an essential tool within the vision science community for many years. However, the majority of studies involving eye-tracking technology employ a relatively passive approach through the use of static imagery, prescribed motion, or video stimuli. This is in contrast to our everyday interaction with the natural world where we navigate our environment while actively seeking and using task-relevant visual information. For this reason, an increasing number of vision researchers are employing virtual environment platforms, which offer interactive, realistic visual environments while maintaining a substantial level of experimental control. Here, we recorded eye movement behavior while subjects freely navigated through a rich, open-world virtual environment. Within this environment, subjects completed a visual search task where they were asked to find and count occurrence of specific targets among numerous distractor items. We assigned each participant into one of four target conditions: Humvees, motorcycles, aircraft, or furniture. Our results show a statistically significant relationship between gaze behavior and target objects across Target Conditions with increased visual attention toward assigned targets. Specifically, we see an increase in the number of fixations and an increase in dwell time on target relative to distractor objects. In addition, we included a divided attention task to investigate how search changed with the addition of a secondary task. With increased cognitive load, subjects slowed their speed, decreased gaze on objects, and increased the number of objects scanned in the environment. Overall, our results confirm previous findings and support that complex virtual environments can be used for active visual search experimentation, maintaining a high level of precision in the quantification of gaze information and visual attention. This study contributes to our understanding of how individuals search for information in a naturalistic (open-world) virtual environment. Likewise, our paradigm provides an intriguing look into the heterogeneity of individual behaviors when completing an un-timed visual search task while actively navigating.

Simultaneous Eye Blink Characterization and Elimination from Low-Channel Prefrontal EEG Signals Enhances Driver Drowsiness Detection

OBJECTIVE

Blink-related features derived from electroencephalography (EEG) have recently arisen as a meaningful measure of drivers cognitive state. Combined with band power features of low-channel prefrontal EEG data, blink-derived features enhance the detection of driver drowsiness. Yet, it remains unanswered whether synergy of combined blink and EEG band power features for the detection of driver drowsiness may be further boosted if a proper eye blink removal is also applied before EEG analysis. This paper proposes an algorithm for simultaneous eye blink feature extraction and elimination from low-channel prefrontal EEG data.

METHODS

Firstly, eye blink intervals (EBIs) are identified from the Fp1 EEG channel using variational mode extraction, and then blink-related features are derived. Secondly, the identified EBIs are projected to the rest of EEG channels and then filtered by a combination of principal component analysis and discrete wavelet transform. Thirdly, a support vector machine with 10-fold cross-validation is employed to classify alert and drowsy states from the derived blink and filtered EEG band power features.

MAIN RESULTS

When compared the synergy of eye blink and EEG features before and after filtering by the proposed algorithm, a significant improvement in the mean accuracy of driver drowsiness detection was achieved (71.2% vs. 78.1%, p<0.05).

SIGNIFICANCE

This paper validates a novel view of eye blinks as both a source of information and artifacts in EEG-based driver drowsiness detection.

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.