Types Of Mental Tasks Research Articles

EEG based Brain Alertness Monitoring by Statistical and Artificial Neural Network Approach

Since several work requires continuous alertness like efficient driving, learning, etc. efficient measurement of the alertness states through neural activity is a crucial challenge for the researchers. This work reports a practical method to investigate the alertness state from electroencephalography (EEG) of the human brain. Here, we have proposed a novel idea to monitor the brain alertness from EEG signal that can discriminate the alertness state comparing resting state with a simple statistical threshold. We have investigated two different types of mental tasks: alphabet counting & virtual driving to monitor their alertness level. The EEG signals are acquired from several participants regarding alphabet counting and virtual motor driving tasks. A 9-channel wireless EEG system has been used to acquire their EEG signals from frontal, central, and parietal lobe of the brain. With suitable preprocessing, signal dimensions are reduced by principal component analysis and the features of the signals are extracted by the discrete wavelet transformation method. Using the features, alertness states are classified using the artificial neural network. Additionally, the relative power of responsible frequency band to alertness is analyzed with statistical inference. We have found that the beta relative power increases at a significant level due to alertness which is good enough to differentiate the alertness state from the control state. It is also found that the increment of beta relative power for virtual driving is much greater than the alphabet counting mental alertness. We hope that this work will be very helpful to monitor constant alertness for efficient driving and learning.

Retrieving Binary Answers Using Whole-Brain Activity Pattern Classification.

Multivariate pattern analysis (MVPA) has been successfully employed to advance our understanding of where and how information regarding different mental states is represented in the human brain, bringing new insights into how these states come to fruition, and providing a promising complement to the mass-univariate approach. Here, we employed MVPA to classify whole-brain activity patterns occurring in single fMRI scans, in order to retrieve binary answers from experiment participants. Five healthy volunteers performed two types of mental task while in the MRI scanner: counting down numbers and recalling positive autobiographical events. Data from these runs were used to train individual machine learning based classifiers that predicted which mental task was being performed based on the voxel-based brain activity patterns. On a different day, the same volunteers reentered the scanner and listened to six statements (e.g., “the month you were born is an odd number”), and were told to countdown numbers if the statement was true (yes) or recall positive events otherwise (no). The previously trained classifiers were then used to assign labels (yes/no) to the scans collected during the 24-second response periods following each one of the statements. Mean classification accuracies at the single scan level were in the range of 73.6 to 80.8%, significantly above chance for all participants. When applying a majority vote on the scans within each response period, i.e., the most frequent label (yes/no) in the response period becomes the answer to the previous statement, 5.0 to 5.8 sentences, out of 6, were correctly classified in each one of the runs, on average. These results indicate that binary answers can be retrieved from whole-brain activity patterns, suggesting that MVPA provides an alternative way to establish basic communication with unresponsive patients when other techniques are not successful.

Detection of mental imagery and attempted movements in patients with disorders of consciousness using EEG.

Further development of an EEG based communication device for patients with disorders of consciousness (DoC) could benefit from addressing the following gaps in knowledge—first, an evaluation of different types of motor imagery; second, an evaluation of passive feet movement as a mean of an initial classifier setup; and third, rapid delivery of biased feedback. To that end we investigated whether complex and/or familiar mental imagery, passive, and attempted feet movement can be reliably detected in patients with DoC using EEG recordings, aiming to provide them with a means of communication. Six patients in a minimally conscious state (MCS) took part in this study. The patients were verbally instructed to perform different mental imagery tasks (sport, navigation), as well as attempted feet movements, to induce distinctive event-related (de)synchronization (ERD/S) patterns in the EEG. Offline classification accuracies above chance level were reached in all three tasks (i.e., attempted feet, sport, and navigation), with motor tasks yielding significant (p < 0.05) results more often than navigation (sport: 10 out of 18 sessions; attempted feet: 7 out of 14 sessions; navigation: 4 out of 12 sessions). The passive feet movements, evaluated in one patient, yielded mixed results: whereas time-frequency analysis revealed task-related EEG changes over neurophysiological plausible cortical areas, the classification results were not significant enough (p < 0.05) to setup an initial classifier for the detection of attempted movements. Concluding, the results presented in this study are consistent with the current state of the art in similar studies, to which we contributed by comparing different types of mental tasks, notably complex motor imagery and attempted feet movements, within patients. Furthermore, we explored new venues, such as an evaluation of passive feet movement as a mean of an initial classifier setup, and rapid delivery of biased feedback.

An analysis of safe driving using concurrent tasks: effects of making decisions from the traffic sign information and performing verbal versus spatial-imagery tasks

Driving requires performing different subtasks concurrently that can interfere. Specifically, two driving sub-tasks are analysed in this work: Participants judge manoeuvres regulated by traffic signs (turn left or turn right...

A step towards multi-level human interface devices: a system that responds to EEG/SEMG triggers

This project forms the basis of our wider project scope which is to develop a multi-level interface device, which can increase the levels of interaction at the human machine interface (HMI). This paper describes the work done so far to establish a viable, practical, low equipment and low computation cost system which is responsive to electroencephalogram-surface electromyogram (EEG-SEMG) triggers. The system consists of the user required to perform tasks for our system to achieve four states of switching. The system then uses this as a trigger in order to help the user operate everyday equipment. It is intended that the device can be worn or carried around easily, whether the person is able-bodied or disabled. The setup of the equipment, the process of the experiments, the types of mental tasks that the user was required to perform, signal processing and corresponding trigger output commands that were generated are described.

Selection of Two Identical Pictures from a Group of Similar Ones II: Changes in Ongoing EEG Activity

Abstract The paper presents finding of an experiment the aim of which was to judge the impact of an instant cognitive activity (identical pictures searching) on behavior of ongoing EEG activity. Two types of mental task were used: The first — passive watching of a blank white oval and the second — active searching for identical pictures in a group of similar nine line-drawings of living individuals or inanimate objects filling out the white oval. Presented results showed that higher mental load pertinent to active searching for identical pictures in a group of similar pictures results in the prominent event-related desynchronization (ERD) — the mean Total Power value, a quantitative measure of ERD extent, in comparison with reference level (passive watching) was lower while solving the mental task. The results also showed that the actual mental task performance affects the ERD only at some scalp-recording sites. The mean EEG Total Power significantly decreases at parietal and frontal scalp-recording sites whereas the significant decrease of the Frequency at Maximum Power involves occipital scalp electrodes, too. Our results also demonstrated that some subject’s personality traits (moderation, openness and extraversion) affect the actual decrease/increase in size of Frequency at Maximum Power during active mental task solving. Presented findings point at the high suitability of the ERD method to uncover differences in people’s brain activation patterns when engaged in performing cognitively demanding tasks.

Multivariate workload evaluation combining physiological and subjective measures

This paper suggests a way to integrate different parameters into one index and results obtained by a newly developed index. The multivariate workload evaluation index, which integrates physiological parameters and one subjective parameter through Principle Components Analysis, was proposed to characterize task specific responses and individual differences in response patterns to mental tasks. Three different types of mental tasks were performed by 12 male participants. Heart rate variability, finger plethysmogram amplitude, and perspiration were used as physiological parameters. Three subscales, mental demand, temporal demand and effort out of six subscales in the NASA-Task Load Index were used as subjective scores. These parameters were standardized within each participant and then combined. It was possible to assess workload using this method from two different aspects, i.e. physiological and subjective, simultaneously.

The effect of mental loads on muscle tension, blood pressure and blink rate.

Surface electromyogram (EMG), blood pressure (BP), blink rate (BR) and heart rate (HR) were recorded before and during 4 types of mental task. The mental task involved 3 tasks that encompassed the memory (M), visual search (VS) and color-word (CW) tasks besides the control task (CT) of maintaining a similar posture while focusing on a single spot on the computer screen. Except for CW, any voluntary movement for response to visual stimuli given were not demanded. Slightly but significant increases in integrated EMG (iEMG) were shown in terapezius, biceps and gastrocnemius muscles during tasks except for CT. Especially in the trapezius muscle during M, the most remarkable enhancements of iEMG and BP were shown. In VS and CW tasks, significant decreases in BR were observed, although in M and CT tasks there were no significant changes in it. There were no significant changes in HR in any type of tasks. The present study demonstrated the increase in muscle tension due to mental needs of cognitive tasks per se accompanying changes in BP and BR. And, enhancement of these physiological responses by memory loads and eyeball movement was discussed as a possible mechanism.

Spectral analysis of heart rate variability under mental stress.

It has been claimed that an increase in the 0.1-Hz component in power spectra of heart rate variability indicates an increased sympathetic tone. We tested 135 middle-aged unmedicated men (mean age 44 +/- 7 years) with two types of mental tasks, a reaction-time test and a mental arithmetic test, to determine whether the results were comparable with those from tilt tests. Although both tasks significantly increased the heart rate and blood pressure, to the same extent as the tilt tests, energy in the 0.1-Hz band decreased during the reaction-time test (from 899 +/- 641 to 482 +/- 430; P less than 0.01) yet was unchanged during the mental arithmetic test. We conclude that the response of the 0.1-Hz component is a task-specific phenomenon.

Effects of daily noise on fetuses and cerebral hemisphere specialization in children

This paper first provides an overview of work by the author and colleagues on effects of noise on fetuses demonstrating growth inhibition. As a second issue, the effects of daily noise on the mental abilities of children are discussed in relation to task specification of cerebral hemispheres. Two different types of mental tasks were given to a total of 1286 children (7–10 years old) who live in a noisy area around an international airport or in a neighbouring quiet area, under conditions of no sound, jet-plane noise stimulus and music stimulus. In the quiet neighborhood, results may support a model that noise and calculation tasks are separately processed in the right and left cerebral hemisphere, respectively. Music perception and calculation are considered to be processed one after the other in the left hemisphere. In the pattern search task used as the right hemispheric task, no significant differences appeared under either stimulus sound, with the exception of a slight interference observed in the noise group. In the noisy living area, however, effects of temporary sound on mental tasks appeared to be quite different from the first-mentioned results. These facts suggest that daily noise affects the development of cerebral specialization of growing children. As little is known about effects of noise on growing children, it is recommended that international cooperation be initiated to establish the need for and conditions of healthy sound environments.

The impact of abnormal hours of work on various modes of information processing: a process model on human costs of performance

Abstract Most laboratory experiments on task performance show a performance deterioration due to a disturbed sleep/wake pattern. Field studies on performance, errors and accidents during night and shiftwork conditions, however, do not provide sufficient converging evidence in this respect. The conflicting results of field studies are probably caused by the measurement methods being based on the material aspects of performance, in which many confounding factors play an important role. Though workers seem to make more errors at night and react less efficiently, the time-of-day effect will often be overshadowed by the influence of situational, task-related and person-related factors. In particular the nature of the involved mental processes, the psychophysiological state of the person, and the invested effort are important for the outcome of performance. With respect to the nature of the involved mental processes, a taxonomy of mental tasks is presented, in which two types of mental tasks are distinguished w...